-------------------------------------------------------------------------------------------- log: c:\Gazelle\codeit3.log log type: text opened on: 11 May 2010, 09:02:20 . do descriptives . . /* Descriptives for explanatory variables for final period */ . . tab country if period==6, sum(product_herf) | Summary of (mean) product_herf country | Mean Std. Dev. Freq. ----------------------------------+------------------------------------ Algeria | .4435001 0 1 Argentina | .03533082 0 1 Australia | .03542862 0 1 Bangladesh | .08815639 0 1 Belgium | .02449928 0 1 Bolivia | .10492457 0 1 Botswana | .63200933 0 1 Brazil | .01614958 0 1 Burkina Faso | .39575255 0 1 Canada | .03253261 0 1 Chile | .10848781 0 1 China | .01192618 0 1 Colombia | .06817091 0 1 Costa Rica | .12736852 0 1 Denmark | .01341407 0 1 Dominican Republic | .05110317 0 1 Ecuador | .24617033 0 1 El Salvador | .06930081 0 1 France | .01600001 0 1 Gambia, The | .12666406 0 1 Ghana | .20190349 0 1 Guatemala | .04246958 0 1 Honduras | .0813739 0 1 India | .02802534 0 1 Indonesia | .02687458 0 1 Iran, Islamic Rep. | .69109535 0 1 Ireland | .0567633 0 1 Israel | .141507 0 1 Italy | .00804457 0 1 Japan | .03222787 0 1 Jordan | .0512266 0 1 Kenya | .07993247 0 1 Madagascar | .112067 0 1 Malawi | .31155407 0 1 Malaysia | .04292266 0 1 Mexico | .02889514 0 1 Morocco | .0304456 0 1 Netherlands | .01035465 0 1 New Zealand | .03099204 0 1 Nicaragua | .05490937 0 1 Nigeria | .81876087 0 1 Norway | .25594398 0 1 Pakistan | .04982532 0 1 Panama | .05172615 0 1 Paraguay | .17000608 0 1 Peru | .0771144 0 1 Philippines | .13212521 0 1 Portugal | .01933289 0 1 Senegal | .09454809 0 1 South Africa | .03139994 0 1 Spain | .02881926 0 1 Sri Lanka | .04126795 0 1 Sweden | .01658347 0 1 Syrian Arab Republic | .4305999 0 1 Thailand | .01617587 0 1 Togo | .1094309 0 1 Trinidad and Tobago | .17265847 0 1 Tunisia | .03726389 0 1 Turkey | .01472646 0 1 United Kingdom | .01722832 0 1 United States | .01081057 0 1 Uruguay | .03983587 0 1 Zambia | .25498044 0 1 Zimbabwe | .09294973 0 1 ----------------------------------+------------------------------------ Total | .12022794 .16706056 64 . tab country if period==6, sum(product_5) | Summary of (mean) product_5 country | Mean Std. Dev. Freq. ----------------------------------+------------------------------------ Algeria | .95843697 0 1 Argentina | .35482943 0 1 Australia | .32570979 0 1 Bangladesh | .61600274 0 1 Belgium | .27860355 0 1 Bolivia | .58270347 0 1 Botswana | .93490165 0 1 Brazil | .19732884 0 1 Burkina Faso | .7533623 0 1 Canada | .33833733 0 1 Chile | .5381543 0 1 China | .17984949 0 1 Colombia | .47365692 0 1 Costa Rica | .59797263 0 1 Denmark | .20449157 0 1 Dominican Republic | .39792138 0 1 Ecuador | .76855695 0 1 El Salvador | .48483917 0 1 France | .23004778 0 1 Gambia, The | .60851389 0 1 Ghana | .68095994 0 1 Guatemala | .3918151 0 1 Honduras | .50290632 0 1 India | .25646186 0 1 Indonesia | .29191491 0 1 Iran, Islamic Rep. | .88247025 0 1 Ireland | .4465566 0 1 Israel | .50817358 0 1 Italy | .13215493 0 1 Japan | .29401675 0 1 Jordan | .43158472 0 1 Kenya | .51807612 0 1 Madagascar | .63660431 0 1 Malawi | .81120062 0 1 Malaysia | .36466846 0 1 Mexico | .30255842 0 1 Morocco | .29829848 0 1 Netherlands | .16712143 0 1 New Zealand | .31992248 0 1 Nicaragua | .44269481 0 1 Nigeria | .97400254 0 1 Norway | .69865173 0 1 Pakistan | .39632711 0 1 Panama | .38196632 0 1 Paraguay | .68238693 0 1 Peru | .52812749 0 1 Philippines | .58959574 0 1 Portugal | .23125952 0 1 Senegal | .55646533 0 1 South Africa | .35070464 0 1 Spain | .26514956 0 1 Sri Lanka | .35120955 0 1 Sweden | .22955506 0 1 Syrian Arab Republic | .77171677 0 1 Thailand | .21220532 0 1 Togo | .63664496 0 1 Trinidad and Tobago | .72281557 0 1 Tunisia | .35695386 0 1 Turkey | .19813052 0 1 United Kingdom | .23782797 0 1 United States | .17719445 0 1 Uruguay | .34860519 0 1 Zambia | .76560265 0 1 Zimbabwe | .54073036 0 1 ----------------------------------+------------------------------------ Total | .46419077 .21864013 64 . tab country if period==6, sum(product_10) | Summary of (mean) product_10 country | Mean Std. Dev. Freq. ----------------------------------+------------------------------------ Algeria | .98313218 0 1 Argentina | .49173996 0 1 Australia | .48761618 0 1 Bangladesh | .78789783 0 1 Belgium | .34548518 0 1 Bolivia | .75306678 0 1 Botswana | .9685927 0 1 Brazil | .31739005 0 1 Burkina Faso | .8207038 0 1 Canada | .42542294 0 1 Chile | .65856844 0 1 China | .2769886 0 1 Colombia | .57781428 0 1 Costa Rica | .68634707 0 1 Denmark | .27921659 0 1 Dominican Republic | .57927471 0 1 Ecuador | .82544416 0 1 El Salvador | .61265206 0 1 France | .30370694 0 1 Gambia, The | .75755715 0 1 Ghana | .82774484 0 1 Guatemala | .55928552 0 1 Honduras | .6901257 0 1 India | .3435249 0 1 Indonesia | .39337578 0 1 Iran, Islamic Rep. | .90093887 0 1 Ireland | .61590785 0 1 Israel | .5961377 0 1 Italy | .2124614 0 1 Japan | .39715081 0 1 Jordan | .64405847 0 1 Kenya | .62309766 0 1 Madagascar | .78947496 0 1 Malawi | .88393408 0 1 Malaysia | .49855381 0 1 Mexico | .43295127 0 1 Morocco | .47978401 0 1 Netherlands | .23796801 0 1 New Zealand | .46383971 0 1 Nicaragua | .6469326 0 1 Nigeria | .98335868 0 1 Norway | .75906348 0 1 Pakistan | .58268988 0 1 Panama | .48194861 0 1 Paraguay | .81463838 0 1 Peru | .66443735 0 1 Philippines | .69132185 0 1 Portugal | .34651631 0 1 Senegal | .71207207 0 1 South Africa | .46618226 0 1 Spain | .33227676 0 1 Sri Lanka | .50331146 0 1 Sweden | .32697681 0 1 Syrian Arab Republic | .82517606 0 1 Thailand | .30899596 0 1 Togo | .75158721 0 1 Trinidad and Tobago | .78459895 0 1 Tunisia | .50345731 0 1 Turkey | .30880797 0 1 United Kingdom | .33700585 0 1 United States | .25490093 0 1 Uruguay | .46915177 0 1 Zambia | .881257 0 1 Zimbabwe | .65689743 0 1 ----------------------------------+------------------------------------ Total | .576914 .21019544 64 . tab country if period==6, sum(market_herf) | Summary of (mean) market_herf country | Mean Std. Dev. Freq. ----------------------------------+------------------------------------ Algeria | .11910941 0 1 Argentina | .07162002 0 1 Australia | .0783046 0 1 Bangladesh | .15400164 0 1 Belgium | .09876762 0 1 Bolivia | .15096202 0 1 Botswana | .64297187 0 1 Brazil | .07285219 0 1 Burkina Faso | .24529819 0 1 Canada | .73844826 0 1 Chile | .07086501 0 1 China | .10210362 0 1 Colombia | .20592587 0 1 Costa Rica | .23594889 0 1 Denmark | .0714139 0 1 Dominican Republic | .20522058 0 1 Ecuador | .20912887 0 1 El Salvador | .15347953 0 1 France | .06546953 0 1 Gambia, The | .21357989 0 1 Ghana | .09598408 0 1 Guatemala | .17481932 0 1 Honduras | .20115064 0 1 India | .05702737 0 1 Indonesia | .08998715 0 1 Iran, Islamic Rep. | .1987171 0 1 Ireland | .11249025 0 1 Israel | .16180985 0 1 Italy | .05805243 0 1 Japan | .10295627 0 1 Jordan | .11732529 0 1 Kenya | .06855199 0 1 Madagascar | .22531968 0 1 Malawi | .07454016 0 1 Malaysia | .09343925 0 1 Mexico | .75491226 0 1 Morocco | .15312234 0 1 Netherlands | .09519088 0 1 New Zealand | .08351212 0 1 Nicaragua | .16016145 0 1 Nigeria | .16836284 0 1 Norway | .09675448 0 1 Pakistan | .08353725 0 1 Panama | .25506067 0 1 Paraguay | .15502813 0 1 Peru | .10472355 0 1 Philippines | .11138903 0 1 Portugal | .11520316 0 1 Senegal | .11404547 0 1 South Africa | .05234626 0 1 Spain | .08290089 0 1 Sri Lanka | .16308764 0 1 Sweden | .05549361 0 1 Syrian Arab Republic | .14708836 0 1 Thailand | .07505314 0 1 Togo | .09187708 0 1 Trinidad and Tobago | .32669154 0 1 Tunisia | .17475516 0 1 Turkey | .05546881 0 1 United Kingdom | .06675658 0 1 United States | .08581433 0 1 Uruguay | .08795144 0 1 Zambia | .19375728 0 1 Zimbabwe | .09640973 0 1 ----------------------------------+------------------------------------ Total | .15537653 .13837791 64 . tab country if period==6, sum(market_5) | Summary of (mean) market_5 country | Mean Std. Dev. Freq. ----------------------------------+------------------------------------ Algeria | .69459492 0 1 Argentina | .50941372 0 1 Australia | .53555661 0 1 Bangladesh | .68266994 0 1 Belgium | .63668162 0 1 Bolivia | .735376 0 1 Botswana | .96599346 0 1 Brazil | .44151935 0 1 Burkina Faso | .81882095 0 1 Canada | .91423845 0 1 Chile | .48691133 0 1 China | .60654557 0 1 Colombia | .65266311 0 1 Costa Rica | .6503424 0 1 Denmark | .50411654 0 1 Dominican Republic | .76360995 0 1 Ecuador | .69422233 0 1 El Salvador | .78291965 0 1 France | .51249689 0 1 Gambia, The | .81960654 0 1 Ghana | .58802408 0 1 Guatemala | .72000861 0 1 Honduras | .72792739 0 1 India | .40918609 0 1 Indonesia | .56809384 0 1 Iran, Islamic Rep. | .84362489 0 1 Ireland | .65766394 0 1 Israel | .58359963 0 1 Italy | .48396537 0 1 Japan | .57256109 0 1 Jordan | .62287372 0 1 Kenya | .50684893 0 1 Madagascar | .77704358 0 1 Malawi | .54027933 0 1 Malaysia | .58460283 0 1 Mexico | .91904855 0 1 Morocco | .6685372 0 1 Netherlands | .59769082 0 1 New Zealand | .5549593 0 1 Nicaragua | .71618354 0 1 Nigeria | .66555017 0 1 Norway | .60274833 0 1 Pakistan | .49172321 0 1 Panama | .69009656 0 1 Paraguay | .70706284 0 1 Peru | .5370875 0 1 Philippines | .62853348 0 1 Portugal | .66948915 0 1 Senegal | .60306555 0 1 South Africa | .44352171 0 1 Spain | .59000719 0 1 Sri Lanka | .63522995 0 1 Sweden | .44284931 0 1 Syrian Arab Republic | .66710407 0 1 Thailand | .51569307 0 1 Togo | .59439117 0 1 Trinidad and Tobago | .73651499 0 1 Tunisia | .74747008 0 1 Turkey | .44533771 0 1 United Kingdom | .5082351 0 1 United States | .52067673 0 1 Uruguay | .52683818 0 1 Zambia | .76247627 0 1 Zimbabwe | .53890121 0 1 ----------------------------------+------------------------------------ Total | .6300254 .12484228 64 . tab country if period==6, sum(market_10) | Summary of (mean) market_10 country | Mean Std. Dev. Freq. ----------------------------------+------------------------------------ Algeria | .89444971 0 1 Argentina | .65086371 0 1 Australia | .70731759 0 1 Bangladesh | .83695674 0 1 Belgium | .77883911 0 1 Bolivia | .88983291 0 1 Botswana | .98850334 0 1 Brazil | .59488547 0 1 Burkina Faso | .93773592 0 1 Canada | .9413805 0 1 Chile | .68293381 0 1 China | .72020239 0 1 Colombia | .7586993 0 1 Costa Rica | .79409194 0 1 Denmark | .71050125 0 1 Dominican Republic | .87786198 0 1 Ecuador | .83586878 0 1 El Salvador | .91692805 0 1 France | .68681592 0 1 Gambia, The | .93101114 0 1 Ghana | .78033781 0 1 Guatemala | .84564877 0 1 Honduras | .84933436 0 1 India | .56606299 0 1 Indonesia | .7244758 0 1 Iran, Islamic Rep. | .91426367 0 1 Ireland | .83407223 0 1 Israel | .7212339 0 1 Italy | .61805069 0 1 Japan | .72605813 0 1 Jordan | .76097977 0 1 Kenya | .67177343 0 1 Madagascar | .88729441 0 1 Malawi | .73161781 0 1 Malaysia | .76104856 0 1 Mexico | .94378883 0 1 Morocco | .80716628 0 1 Netherlands | .73817188 0 1 New Zealand | .68639052 0 1 Nicaragua | .87870067 0 1 Nigeria | .82292372 0 1 Norway | .81176573 0 1 Pakistan | .64358175 0 1 Panama | .81195819 0 1 Paraguay | .84808749 0 1 Peru | .69392133 0 1 Philippines | .86264336 0 1 Portugal | .83895749 0 1 Senegal | .7888149 0 1 South Africa | .58873332 0 1 Spain | .72459054 0 1 Sri Lanka | .75475681 0 1 Sweden | .67953444 0 1 Syrian Arab Republic | .82109243 0 1 Thailand | .68154472 0 1 Togo | .74153346 0 1 Trinidad and Tobago | .82799911 0 1 Tunisia | .88405615 0 1 Turkey | .62006927 0 1 United Kingdom | .69449508 0 1 United States | .67142606 0 1 Uruguay | .70268029 0 1 Zambia | .89193386 0 1 Zimbabwe | .72425592 0 1 ----------------------------------+------------------------------------ Total | .77677352 .10023605 64 . . pwcorr product_herf product_5 product_10 pc_p market_herf market_5 market_10 pc_m | produc~f produc~5 produ~10 pc_p market~f market_5 marke~10 -------------+--------------------------------------------------------------- product_herf | 1.0000 product_5 | 0.8223 1.0000 product_10 | 0.7483 0.9837 1.0000 pc_p | 0.8832 0.9913 0.9703 1.0000 market_herf | 0.2400 0.2256 0.2326 0.2430 1.0000 market_5 | 0.4499 0.4596 0.4571 0.4779 0.8139 1.0000 market_10 | 0.4991 0.5420 0.5398 0.5552 0.6964 0.9581 1.0000 pc_m | 0.4285 0.4425 0.4430 0.4599 0.8832 0.9859 0.9451 | pc_m -------------+--------- pc_m | 1.0000 . . sum std product_herf product_5 product_10 pc_p market_herf market_5 market_10 pc_m trade k > aopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisis Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- std | 380 2.79084 2.165868 .3403846 11.73995 product_herf | 378 .1388201 .1726845 .0066051 .9194474 product_5 | 378 .5044964 .2467541 .0995808 .9867772 product_10 | 378 .615132 .2373926 .1722828 .9921577 pc_p | 378 -.6628909 1.419126 -2.87327 3.068816 -------------+-------------------------------------------------------- market_herf | 364 .1673507 .1465322 .0462265 .9439309 market_5 | 364 .6395142 .1347501 .3852565 .9907221 market_10 | 364 .7868594 .1033548 .566063 .9959067 pc_m | 364 -.4846218 1.384047 -2.816218 4.353554 trade | 380 .8032813 .1147423 .449657 1.157489 -------------+-------------------------------------------------------- kaopen | 380 .197638 1.528129 -1.797522 2.539847 sd_krg | 380 .1992478 .5894655 -1.97296 1.491564 sd_fgr | 380 -.1555548 .4308377 -1.543337 .8910471 sdtot | 380 7.597327 7.879338 0 56.32327 sdreer2 | 380 5455.332 103633.7 .0494973 2019770 -------------+-------------------------------------------------------- sdinfl | 380 8.819032 20.80822 .1907341 168.1267 ncrisis | 380 .0297472 .0564749 0 .1823216 . sum lningp growth2 sec2i sdgovspen pyearnatdisas~r govicrg growth2 qinst pcrisis war assas > sin Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- lningp | 380 7.740761 1.587223 4.75315 10.53136 growth2 | 316 1.14074 2.846261 -10.92424 10.12756 sec2i | 380 3.960843 .6718674 1.493604 5.024161 sdgovspen | 380 7.458527 11.02611 .1982006 93.24217 pyearnatdi~r | 380 .0626184 .114099 0 .5877867 -------------+-------------------------------------------------------- govicrg | 316 .3797951 1.842857 -3.256158 3.468414 growth2 | 316 1.14074 2.846261 -10.92424 10.12756 qinst | 358 6.121061 1.21556 3 8.8 pcrisis | 380 .0026316 .0512989 0 1 war | 380 .0342105 .1820092 0 1 -------------+-------------------------------------------------------- assassin | 380 .3473684 .9160938 0 9.8 . . sum product_herf product_5 product_10 pc_p market_herf market_5 market_10 pc_m, detail (mean) product_herf ------------------------------------------------------------- Percentiles Smallest 1% .0079014 .0066051 5% .0105418 .0069822 10% .014535 .0078032 Obs 378 25% .0288951 .0079014 Sum of Wgt. 378 50% .0705788 Mean .1388201 Largest Std. Dev. .1726845 75% .1896438 .8589318 90% .3458575 .8663617 Variance .0298199 95% .4854223 .8841929 Skewness 2.261213 99% .8589318 .9194474 Kurtosis 8.492995 (mean) product_5 ------------------------------------------------------------- Percentiles Smallest 1% .1272343 .0995808 5% .1627322 .1109203 10% .1973288 .1212482 Obs 378 25% .2919149 .1272343 Sum of Wgt. 378 50% .4764977 Mean .5044964 Largest Std. Dev. .2467541 75% .706779 .968758 90% .8791878 .9725561 Variance .0608876 95% .9251812 .9740025 Skewness .2782001 99% .968758 .9867772 Kurtosis 1.87495 (mean) product_10 ------------------------------------------------------------- Percentiles Smallest 1% .1973465 .1722828 5% .2411407 .179864 10% .2950889 .1915121 Obs 378 25% .4100395 .1973465 Sum of Wgt. 378 50% .6135913 Mean .615132 Largest Std. Dev. .2373926 75% .8254442 .9854717 90% .9476209 .9891158 Variance .0563553 95% .9706844 .9911423 Skewness -.0468811 99% .9854717 .9921577 Kurtosis 1.783057 (mean) pc_p ------------------------------------------------------------- Percentiles Smallest 1% -2.748914 -2.87327 5% -2.564436 -2.82992 10% -2.328104 -2.778635 Obs 378 25% -1.859004 -2.748914 Sum of Wgt. 378 50% -.8729338 Mean -.6628909 Largest Std. Dev. 1.419126 75% .3666652 2.815732 90% 1.280821 2.8947 Variance 2.013919 95% 1.886449 2.918354 Skewness .4982863 99% 2.815732 3.068816 Kurtosis 2.353025 (mean) market_herf ------------------------------------------------------------- Percentiles Smallest 1% .0518816 .0462265 5% .0606653 .048355 10% .0668207 .0498461 Obs 364 25% .0817993 .0518816 Sum of Wgt. 364 50% .1166606 Mean .1673507 Largest Std. Dev. .1465322 75% .1842959 .7384483 90% .3328561 .7456218 Variance .0214717 95% .5511 .7549123 Skewness 2.519307 99% .7384483 .9439309 Kurtosis 9.46238 (mean) market_5 ------------------------------------------------------------- Percentiles Smallest 1% .4185004 .3852565 5% .4508498 .4018989 10% .4795822 .4091861 Obs 364 25% .5298699 .4185004 Sum of Wgt. 364 50% .6296975 Mean .6395142 Largest Std. Dev. .1347501 75% .7227825 .9659935 90% .8308128 .9660822 Variance .0181576 95% .9091234 .9849434 Skewness .5474866 99% .9659935 .9907221 Kurtosis 2.637257 (mean) market_10 ------------------------------------------------------------- Percentiles Smallest 1% .5887333 .566063 5% .6241892 .5811026 10% .6524883 .5880287 Obs 364 25% .7046816 .5887333 Sum of Wgt. 364 50% .7870293 Mean .7868594 Largest Std. Dev. .1033548 75% .868828 .993471 90% .9295683 .9939797 Variance .0106822 95% .9614954 .9958552 Skewness .1052335 99% .993471 .9959067 Kurtosis 2.11246 (mean) pc_m ------------------------------------------------------------- Percentiles Smallest 1% -2.582899 -2.816218 5% -2.237661 -2.764768 10% -2.000683 -2.65433 Obs 364 25% -1.538012 -2.582899 Sum of Wgt. 364 50% -.6677355 Mean -.4846218 Largest Std. Dev. 1.384047 75% .2256655 3.26564 90% 1.352175 3.378016 Variance 1.915586 95% 2.564095 3.450386 Skewness .8922632 99% 3.26564 4.353554 Kurtosis 3.532053 . sum product_herf product_5 product_10 pc_p market_herf market_5 market_10 pc_m trade if pe > riod==6, detail (mean) product_herf ------------------------------------------------------------- Percentiles Smallest 1% .0080446 .0080446 5% .0119262 .0103547 10% .016 .0108106 Obs 64 25% .0288572 .0119262 Sum of Wgt. 64 50% .0514764 Mean .1202279 Largest Std. Dev. .1670606 75% .1270163 .4435001 90% .3115541 .6320093 Variance .0279092 95% .4435001 .6910954 Skewness 2.512824 99% .8187609 .8187609 Kurtosis 9.188225 (mean) product_5 ------------------------------------------------------------- Percentiles Smallest 1% .1321549 .1321549 5% .1798495 .1671214 10% .2044916 .1771944 Obs 64 25% .2929658 .1798495 Sum of Wgt. 64 50% .414753 Mean .4641908 Largest Std. Dev. .2186401 75% .6122583 .8824703 90% .768557 .9349017 Variance .0478035 95% .8824703 .958437 Skewness .5618003 99% .9740025 .9740025 Kurtosis 2.421687 (mean) product_10 ------------------------------------------------------------- Percentiles Smallest 1% .2124614 .2124614 5% .2769886 .237968 10% .308808 .2549009 Obs 64 25% .3952633 .2769886 Sum of Wgt. 64 50% .5809823 Mean .576914 Largest Std. Dev. .2101954 75% .755312 .9009389 90% .8277448 .9685927 Variance .0441821 95% .9009389 .9831322 Skewness .1050858 99% .9833587 .9833587 Kurtosis 1.959197 (mean) pc_p ------------------------------------------------------------- Percentiles Smallest 1% -2.70641 -2.70641 5% -2.445148 -2.565284 10% -2.305142 -2.50349 Obs 64 25% -1.884501 -2.445148 Sum of Wgt. 64 50% -1.081898 Mean -.8822234 Largest Std. Dev. 1.288809 75% -.1387105 1.886449 90% .9508642 2.102518 Variance 1.66103 95% 1.886449 2.236094 Skewness .8553965 99% 2.787972 2.787972 Kurtosis 3.214827 (mean) market_herf ------------------------------------------------------------- Percentiles Smallest 1% .0523463 .0523463 5% .0570274 .0554688 10% .0667566 .0554936 Obs 64 25% .0832065 .0570274 Sum of Wgt. 64 50% .1119396 Mean .1553765 Largest Std. Dev. .1383779 75% .1747872 .3266915 90% .2359489 .6429719 Variance .0191484 95% .3266915 .7384483 Skewness 3.15687 99% .7549123 .7549123 Kurtosis 13.35633 (mean) market_5 ------------------------------------------------------------- Percentiles Smallest 1% .4091861 .4091861 5% .4435217 .4415193 10% .4869113 .4428493 Obs 64 25% .5311974 .4435217 Sum of Wgt. 64 50% .6147096 Mean .6300254 Largest Std. Dev. .1248423 75% .7116232 .8436249 90% .7829196 .9142385 Variance .0155856 95% .8436249 .9190485 Skewness .5327098 99% .9659935 .9659935 Kurtosis 2.898188 (mean) market_10 ------------------------------------------------------------- Percentiles Smallest 1% .566063 .566063 5% .6180507 .5887333 10% .6508637 .5948855 Obs 64 25% .6985877 .6180507 Sum of Wgt. 64 50% .7699438 Mean .7767735 Largest Std. Dev. .1002361 75% .8487109 .9377359 90% .9142637 .9413805 Variance .0100473 95% .9377359 .9437888 Skewness .0025533 99% .9885033 .9885033 Kurtosis 2.187901 (mean) pc_m ------------------------------------------------------------- Percentiles Smallest 1% -2.764768 -2.764768 5% -2.374233 -2.542658 10% -1.996658 -2.453635 Obs 64 25% -1.56022 -2.374233 Sum of Wgt. 64 50% -.767427 Mean -.6044164 Largest Std. Dev. 1.302143 75% .1200749 1.168775 90% .7044655 3.14607 Variance 1.695577 95% 1.168775 3.229182 Skewness .9846496 99% 3.255761 3.255761 Kurtosis 4.31312 Trade Openness ------------------------------------------------------------- Percentiles Smallest 1% .6175278 .6175278 5% .6501986 .6259432 10% .6842942 .628546 Obs 64 25% .7912124 .6501986 Sum of Wgt. 64 50% .8569674 Mean .8409095 Largest Std. Dev. .1076427 75% .897793 1.026581 90% .9499624 1.039068 Variance .011587 95% 1.026581 1.074076 Skewness -.0015851 99% 1.132543 1.132543 Kurtosis 3.154376 . . la var trade "Trade Openness" . la var std "Growth Volatility" . . ***** plots . . gen ind = . (380 missing values generated) . replace ind = 1 if product_herf < .0288951 (94 real changes made) . replace ind = 2 if product_herf > .0288951 & product_herf <= .1896438 (189 real changes made) . replace ind = 3 if product_herf > .1896438 (97 real changes made) . . preserve . hadimvo std trade, gen(outlier) p(0.15) Beginning number of observations: 380 Initially accepted: 3 Expand to (n+k+1)/2: 191 Expand, p = .15: 376 Outliers remaining: 4 . drop if outlier == 1 (4 observations deleted) . graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output\h > erfprodlow", replace) legend(off) ytitle(Growth Volatility) graphregion(fcolor(white) lcol > or(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\herfprodlow.gph saved) . graph export "C:\Gazelle\Output\herfproflow.eps", replace (file C:\Gazelle\Output\herfproflow.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output\h > erfprodmid", replace) legend(off) ytitle(Growth Volatility) graphregion(fcolor(white) lcol > or(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\herfprodmid.gph saved) . graph export "C:\Gazelle\Output\herfprodmid.eps", replace (file C:\Gazelle\Output\herfprodmid.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output\h > erfprodhigh", replace) legend(off) ytitle(Growth Volatility) graphregion(fcolor(white) lco > lor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\herfprodhigh.gph saved) . graph export "C:\Gazelle\Output\herfprodhigh.eps", replace (file C:\Gazelle\Output\herfprodhigh.eps written in EPS format) . restore . . drop ind . gen ind = . (380 missing values generated) . replace ind = 1 if product_5 < .2919149 (94 real changes made) . replace ind = 2 if product_5 > .2919149 & product_5 <= .706779 (189 real changes made) . replace ind = 3 if product_5 > .706779 (97 real changes made) . . preserve . hadimvo std trade, gen(outlier) p(0.15) Beginning number of observations: 380 Initially accepted: 3 Expand to (n+k+1)/2: 191 Expand, p = .15: 376 Outliers remaining: 4 . drop if outlier == 1 (4 observations deleted) . * graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output > \5prodlow", replace) legend(off) title("Share of 5 Products is Low") ytitle(Growth Volatil > ity) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifcolor > (white) ilcolor(white)) . graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output\5 > prodlow", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculatio > ns") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\5prodlow.gph saved) . graph export "C:\Gazelle\Output\5prodlow.eps", replace (file C:\Gazelle\Output\5prodlow.eps written in EPS format) . * graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output > \5prodmid", replace) legend(off) title("Share of 5 Products is Average") ytitle(Growth Vol > atility) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifc > olor(white) ilcolor(white)) . graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output\5 > prodmid", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculatio > ns") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\5prodmid.gph saved) . graph export "C:\Gazelle\Output\5prodmid.eps", replace (file C:\Gazelle\Output\5prodmid.eps written in EPS format) . * graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output > \5prodhigh", replace) legend(off) title("Share of 5 Products is High") ytitle(Growth Volat > ility) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifcol > or(white) ilcolor(white)) . graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output\5 > prodhigh", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculati > ons") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\5prodhigh.gph saved) . graph export "C:\Gazelle\Output\5prodhigh.eps", replace (file C:\Gazelle\Output\5prodhigh.eps written in EPS format) . restore . . drop ind . gen ind = . (380 missing values generated) . replace ind = 1 if product_10 < .4100395 (94 real changes made) . replace ind = 2 if product_10 > .4100395 & product_5 <= .8254442 (230 real changes made) . replace ind = 3 if product_10 > .8254442 (96 real changes made) . . preserve . hadimvo std trade, gen(outlier) p(0.15) Beginning number of observations: 380 Initially accepted: 3 Expand to (n+k+1)/2: 191 Expand, p = .15: 376 Outliers remaining: 4 . drop if outlier == 1 (4 observations deleted) . graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output\1 > 0prodlow", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculati > ons") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\10prodlow.gph saved) . graph export "C:\Gazelle\Output\10prodlow.eps", replace (file C:\Gazelle\Output\10prodlow.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output\1 > 0prodmid", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculati > ons") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\10prodmid.gph saved) . graph export "C:\Gazelle\Output\10prodmid.eps", replace (file C:\Gazelle\Output\10prodmid.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output\1 > 0prodhigh", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculat > ions") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\10prodhigh.gph saved) . graph export "C:\Gazelle\Output\10prodhigh.eps", replace (file C:\Gazelle\Output\10prodhigh.eps written in EPS format) . restore . . drop ind . gen ind = . (380 missing values generated) . replace ind = 1 if market_herf < .0817993 (91 real changes made) . replace ind = 2 if market_herf > .0817993 & market_herf <= .1842959 (182 real changes made) . replace ind = 3 if market_herf > .1842959 (107 real changes made) . . graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output\h > erfmktlow", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calcula > tions") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\herfmktlow.gph saved) . graph export "C:\Gazelle\Output\herfmktlow.eps", replace (file C:\Gazelle\Output\herfmktlow.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output\h > erfmktmid", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calcula > tions") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\herfmktmid.gph saved) . graph export "C:\Gazelle\Output\herfmktmid.eps", replace (file C:\Gazelle\Output\herfmktmid.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output\h > erfmkthigh", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calcul > ations") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\herfmkthigh.gph saved) . graph export "C:\Gazelle\Output\herfmkthigh.eps", replace (file C:\Gazelle\Output\herfmkthigh.eps written in EPS format) . . drop ind . gen ind = . (380 missing values generated) . replace ind = 1 if market_5 < .5298699 (91 real changes made) . replace ind = 2 if market_5 > .5298699 & market_5 <= .7227825 (182 real changes made) . replace ind = 3 if market_5 > .7227825 (107 real changes made) . . * graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output > \5mktlow", replace) legend(off) title("Share of 5 Markets is Low") ytitle(Growth Volatilit > y) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifcolor( > white) ilcolor(white)) . graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output\5 > mktlow", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculatio > ns") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\5mktlow.gph saved) . graph export "C:\Gazelle\Output\5mktlow.eps", replace (file C:\Gazelle\Output\5mktlow.eps written in EPS format) . * graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output > \5mktmid", replace) legend(off) title("Share of 5 Markets is Average") ytitle(Growth Volat > ility) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifcol > or(white) ilcolor(white)) . graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output\5 > mktmid", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculation > s") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\5mktmid.gph saved) . graph export "C:\Gazelle\Output\5mktmid.eps", replace (file C:\Gazelle\Output\5mktmid.eps written in EPS format) . * graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output > \5mkthigh", replace) legend(off) title("Share of 5 Markets is High") ytitle(Growth Volatil > ity) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifcolor > (white) ilcolor(white)) . graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output\5 > mkthigh", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculatio > ns") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\5mkthigh.gph saved) . graph export "C:\Gazelle\Output\5mkthigh.eps", replace (file C:\Gazelle\Output\5mkthigh.eps written in EPS format) . . drop ind . gen ind = . (380 missing values generated) . replace ind = 1 if market_10 < .7046816 (91 real changes made) . replace ind = 2 if market_10 > .7046816 & market_5 <= .868828 (247 real changes made) . replace ind = 3 if market_10 > .868828 (107 real changes made) . . graph twoway (lfit std trade) (scatter std trade) if ind == 1, saving("C:\Gazelle\Output\1 > 0mktlow", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculatio > ns") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\10mktlow.gph saved) . graph export "C:\Gazelle\Output\10mktlow.eps", replace (file C:\Gazelle\Output\10mktlow.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 2, saving("C:\Gazelle\Output\1 > 0mktmid", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculatio > ns") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\10mktmid.gph saved) . graph export "C:\Gazelle\Output\10mktmid.eps", replace (file C:\Gazelle\Output\10mktmid.eps written in EPS format) . graph twoway (lfit std trade) (scatter std trade) if ind == 3, saving("C:\Gazelle\Output\1 > 0mkthigh", replace) legend(off) ytitle(Growth Volatility) note("Source: Authors' calculati > ons") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) (file C:\Gazelle\Output\10mkthigh.gph saved) . graph export "C:\Gazelle\Output\10mkthigh.eps", replace (file C:\Gazelle\Output\10mkthigh.eps written in EPS format) . . *graph combine graph1.gph graph4.gph graph2.gph graph5.gph graph3.gph graph6.gph, cols(2) . . egen id = group(country) id already defined r(110); end of do-file r(110); . graph twoway (scatter product_5 trade, mlabel(country)) if period == 6, ytitle("5 product > concentration") xtitle("Trade openness") yline(0.481, lcolor(maroon)) note("Source: Autho > rs' calculations") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) . . graph export "C:\Gazelle\Output\5prodopen.eps", replace (file C:\Gazelle\Output\5prodopen.eps written in EPS format) . . graph twoway (scatter product_10 trade, mlabel(country)) if period == 6, ytitle("Export co > ncentration") xtitle("Trade openness") yline(0.575, lcolor(maroon)) note("Source: Authors > ' calculations") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) . . graph export "C:\Gazelle\Output\10prodopen.eps", replace (file C:\Gazelle\Output\10prodopen.eps written in EPS format) . . * epstopdf 10prodopen.eps . . graph twoway (scatter product_herf trade, mlabel(country)) if period == 6, ytitle("Product > Herfindahl concentration") xtitle("Trade openness") yline(0.154, lcolor(maroon)) note("S > ource: Authors' calculations") graphregion(fcolor(white) lcolor(white) ifcolor(white) ilco > lor(white)) . . graph export "C:\Gazelle\Output\herfprodopen.eps", replace (file C:\Gazelle\Output\herfprodopen.eps written in EPS format) . . /* unrecognized command: / invalid command name r(199); . . graph twoway (scatter product_5 ingp, mlabel(wbcode)) if period == 6, ytitle("Concentratio > n of top 5 exports") xtitle("GDP per capita in initial period (2000 prices)") yline(0.710, > lcolor(maroon)) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(w > hite) ifcolor(white) ilcolor(white)) . . preserve . . keep if highincome == 1 (261 observations deleted) . . graph twoway (scatter product_5 ingp, mlabel(wbcode)) if period == 6, ytitle("Concentratio > n of top 5 exports") xtitle("GDP per capita in initial period (2000 prices)") yline(0.710, > lcolor(maroon)) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(w > hite) ifcolor(white) ilcolor(white)) . . restore . . preserve . . drop if highincome == 1 (119 observations deleted) . . graph twoway (scatter product_5 ingp, mlabel(wbcode)) if period == 6, ytitle("Concentratio > n of top 5 exports") xtitle("GDP per capita in initial period (2000 prices)") yline(0.710, > lcolor(maroon)) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(w > hite) ifcolor(white) ilcolor(white)) . . restore . . */ . . graph twoway (scatter product_5 ingp, mlabel(country)) if period == 6, ytitle("5 product c > oncentration") xtitle("GDP per capita in initial period (2000 prices)") yline(0.481, lcolo > r(maroon)) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white) > ifcolor(white) ilcolor(white)) . . graph export "C:\Gazelle\Output\5prodgdp.eps", replace (file C:\Gazelle\Output\5prodgdp.eps written in EPS format) . . graph twoway (scatter product_10 ingp, mlabel(country)) if period == 6, ytitle("10 product > concentration") xtitle("GDP per capita in initial period (2000 prices)") yline(0.575, lco > lor(maroon)) note("Source: Authors' calculations") graphregion(fcolor(white) lcolor(white > ) ifcolor(white) ilcolor(white)) . . graph export "C:\Gazelle\Output\10prodgdp.eps", replace (file C:\Gazelle\Output\10prodgdp.eps written in EPS format) . . * epstopdf 10prodgdp.eps . . graph twoway (scatter product_herf ingp, mlabel(country)) if period == 6, ytitle("Product > Herfindahl concentration") xtitle("GDP per capita in initial period (2000 prices)") yline( > 0.154, lcolor(maroon)) note("Source: Authors' calculations") graphregion(fcolor(white) lc > olor(white) ifcolor(white) ilcolor(white)) . . graph export "C:\Gazelle\Output\herfprodgdp.eps", replace (file C:\Gazelle\Output\herfprodgdp.eps written in EPS format) . . . . preserve . . keep if wbcode == "COL" | wbcode == "JOR" | wbcode == "KEN" | wbcode == "MEX" | wbcode == > "NIC" | wbcode == "ZAF" (349 observations deleted) . . graph twoway connected product_5 period, by(wbcode) ytitle("Share of 5 products indicator" > ) xtitle("Time") yline(0.481, lcolor(maroon)) note("Source: Authors' calculations") graphr > egion(fcolor(white) lcolor(white) ifcolor(white) ilcolor(white)) . end of do-file . do results . /* Benchmark error components regressions */ . . xtreg std trade kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, fe robust Fixed-effects (within) regression Number of obs = 380 Group variable (i): id Number of groups = 77 R-sq: within = 0.2043 Obs per group: min = 1 between = 0.1984 avg = 4.9 overall = 0.2014 max = 6 F(13,290) = 8.67 corr(u_i, Xb) = -0.0470 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- trade | 5.18821 3.174987 1.63 0.103 -1.06073 11.43715 kaopen | -.0387333 .117822 -0.33 0.743 -.270628 .1931613 sdtot | .0400519 .0274879 1.46 0.146 -.0140493 .094153 sdreer2 | 8.30e-07 4.98e-07 1.67 0.097 -1.51e-07 1.81e-06 sd_krg | .7213278 .20643 3.49 0.001 .3150368 1.127619 sd_fgr | .8550257 .3872435 2.21 0.028 .0928616 1.61719 sdinfl | .0059388 .0076816 0.77 0.440 -.00918 .0210577 ncrisis | 5.227059 2.274542 2.30 0.022 .7503544 9.703763 tyear1 | .7882735 .7043199 1.12 0.264 -.5979532 2.1745 tyear2 | .543584 .5440241 1.00 0.319 -.5271521 1.61432 tyear3 | .7348467 .4410526 1.67 0.097 -.1332233 1.602917 tyear4 | .450629 .3639912 1.24 0.217 -.2657704 1.167028 tyear5 | -.0267083 .3650767 -0.07 0.942 -.7452443 .6918277 _cons | -2.264734 2.768461 -0.82 0.414 -7.713557 3.184089 -------------+---------------------------------------------------------------- sigma_u | 1.3266641 sigma_e | 1.6596376 rho | .38986887 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F1 . xtreg std product_herf trade inter1 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyea > r*, fe robust Fixed-effects (within) regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.2038 Obs per group: min = 1 between = 0.3075 avg = 4.9 overall = 0.2502 max = 6 F(15,286) = 8.02 corr(u_i, Xb) = 0.0894 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- product_herf | -18.2741 12.88196 -1.42 0.157 -43.62957 7.08137 trade | -1.111666 3.695113 -0.30 0.764 -8.384732 6.161401 inter1 | 21.88816 16.0064 1.37 0.173 -9.617128 53.39344 kaopen | -.110314 .1113118 -0.99 0.323 -.3294083 .1087803 sdtot | .0436334 .0284923 1.53 0.127 -.0124479 .0997146 sdreer2 | 7.57e-07 4.89e-07 1.55 0.123 -2.07e-07 1.72e-06 sd_krg | .6829311 .2046908 3.34 0.001 .2800395 1.085823 sd_fgr | .9319271 .3800202 2.45 0.015 .1839359 1.679918 sdinfl | .004888 .0071056 0.69 0.492 -.0090978 .0188739 ncrisis | 5.25822 2.253485 2.33 0.020 .8226999 9.693739 tyear1 | -.2175028 .6951761 -0.31 0.755 -1.585813 1.150808 tyear2 | -.0597192 .512113 -0.12 0.907 -1.067708 .9482695 tyear3 | .243575 .424307 0.57 0.566 -.5915856 1.078736 tyear4 | .1226763 .3626345 0.34 0.735 -.5910947 .8364473 tyear5 | -.1202491 .3537469 -0.34 0.734 -.8165267 .5760285 _cons | 3.169462 3.110667 1.02 0.309 -2.953244 9.292167 -------------+---------------------------------------------------------------- sigma_u | 1.2221914 sigma_e | 1.6153787 rho | .36404556 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F2 . dis -_b[trade]/(_b[inter]) .05078845 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 F( 2, 286) = 1.24 Prob > F = 0.2906 . xtreg std product_5 trade inter2 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, > fe robust Fixed-effects (within) regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1972 Obs per group: min = 1 between = 0.3532 avg = 4.9 overall = 0.2545 max = 6 F(15,286) = 8.23 corr(u_i, Xb) = 0.1406 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- product_5 | -8.190564 6.890851 -1.19 0.236 -21.75378 5.372651 trade | -2.831377 5.185176 -0.55 0.585 -13.03732 7.374571 inter2 | 9.824446 8.526659 1.15 0.250 -6.958519 26.60741 kaopen | -.1064148 .1129796 -0.94 0.347 -.3287918 .1159621 sdtot | .0429293 .0285167 1.51 0.133 -.0131999 .0990585 sdreer2 | 8.24e-07 4.86e-07 1.69 0.091 -1.33e-07 1.78e-06 sd_krg | .6983668 .2067613 3.38 0.001 .2914001 1.105334 sd_fgr | .9007198 .3878671 2.32 0.021 .1372836 1.664156 sdinfl | .0049257 .0074113 0.66 0.507 -.0096618 .0195132 ncrisis | 4.84611 2.264888 2.14 0.033 .3881475 9.304073 tyear1 | -.1546678 .6928561 -0.22 0.824 -1.518412 1.209076 tyear2 | .0517526 .5309147 0.10 0.922 -.9932432 1.096749 tyear3 | .3036123 .4248134 0.71 0.475 -.5325449 1.13977 tyear4 | .1587908 .355875 0.45 0.656 -.5416755 .8592571 tyear5 | -.1232758 .3563143 -0.35 0.730 -.8246068 .5780553 _cons | 4.57676 4.237454 1.08 0.281 -3.763793 12.91731 -------------+---------------------------------------------------------------- sigma_u | 1.2058475 sigma_e | 1.6221114 rho | .35592569 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F3 . dis -_b[trade]/(_b[inter]) .28819708 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 F( 2, 286) = 0.94 Prob > F = 0.3917 . xtreg std product_10 trade inter3 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear* > , fe robust Fixed-effects (within) regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1958 Obs per group: min = 1 between = 0.3471 avg = 4.9 overall = 0.2497 max = 6 F(15,286) = 8.33 corr(u_i, Xb) = 0.1379 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- product_10 | -7.314134 6.651621 -1.10 0.272 -20.40647 5.778207 trade | -3.219911 5.77289 -0.56 0.577 -14.58265 8.14283 inter3 | 8.74285 8.118681 1.08 0.282 -7.237096 24.7228 kaopen | -.1063386 .1150892 -0.92 0.356 -.3328679 .1201906 sdtot | .0420913 .0285782 1.47 0.142 -.014159 .0983416 sdreer2 | 8.39e-07 4.89e-07 1.72 0.087 -1.23e-07 1.80e-06 sd_krg | .6939001 .2051917 3.38 0.001 .2900227 1.097777 sd_fgr | .903724 .3897243 2.32 0.021 .1366323 1.670816 sdinfl | .0049817 .0074963 0.66 0.507 -.0097733 .0197367 ncrisis | 4.880162 2.267999 2.15 0.032 .4160748 9.344249 tyear1 | -.124064 .6849512 -0.18 0.856 -1.472249 1.224121 tyear2 | .0701494 .5402699 0.13 0.897 -.9932603 1.133559 tyear3 | .321783 .4287249 0.75 0.454 -.5220733 1.165639 tyear4 | .1691541 .3585613 0.47 0.637 -.5365998 .8749079 tyear5 | -.1128804 .3570114 -0.32 0.752 -.8155836 .5898228 _cons | 4.921044 4.762618 1.03 0.302 -4.453185 14.29527 -------------+---------------------------------------------------------------- sigma_u | 1.2120243 sigma_e | 1.6234654 rho | .35788814 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F4 . dis -_b[trade]/(_b[inter]) .36829074 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 F( 2, 286) = 0.86 Prob > F = 0.4233 . xtreg std pc_p trade inter7 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, fe r > obust Fixed-effects (within) regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1989 Obs per group: min = 1 between = 0.3412 avg = 4.9 overall = 0.2539 max = 6 F(15,286) = 8.20 corr(u_i, Xb) = 0.1219 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- pc_p | -1.678899 1.31078 -1.28 0.201 -4.258898 .9010994 trade | 3.370711 3.051793 1.10 0.270 -2.636113 9.377534 inter7 | 2.031247 1.643929 1.24 0.218 -1.204487 5.266982 kaopen | -.1096042 .1134407 -0.97 0.335 -.3328888 .1136803 sdtot | .0432125 .0285707 1.51 0.132 -.013023 .099448 sdreer2 | 8.15e-07 4.86e-07 1.68 0.095 -1.41e-07 1.77e-06 sd_krg | .7018289 .2074808 3.38 0.001 .2934459 1.110212 sd_fgr | .9120042 .3861273 2.36 0.019 .1519925 1.672016 sdinfl | .0049087 .0073578 0.67 0.505 -.0095735 .019391 ncrisis | 4.91882 2.2579 2.18 0.030 .4746109 9.363028 tyear1 | -.2058947 .7053204 -0.29 0.771 -1.594172 1.182383 tyear2 | -.00139 .5236751 -0.00 0.998 -1.032136 1.029356 tyear3 | .2736858 .4259578 0.64 0.521 -.5647241 1.112096 tyear4 | .1341937 .358751 0.37 0.709 -.5719335 .8403209 tyear5 | -.1304601 .3558471 -0.37 0.714 -.8308715 .5699514 _cons | -.5719513 2.602602 -0.22 0.826 -5.694636 4.550733 -------------+---------------------------------------------------------------- sigma_u | 1.2065552 sigma_e | 1.6203764 rho | .35668573 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F5 . dis -_b[trade]/(_b[inter]) -1.6594291 . test trade inter ( 1) trade = 0 ( 2) inter7 = 0 F( 2, 286) = 1.02 Prob > F = 0.3637 . . xtreg std market_herf trade inter4 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear > *, fe robust Fixed-effects (within) regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2188 Obs per group: min = 1 between = 0.2349 avg = 4.8 overall = 0.2216 max = 6 F(15,273) = 8.41 corr(u_i, Xb) = 0.0294 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- market_herf | -12.5403 9.50131 -1.32 0.188 -31.24545 6.16485 trade | .606736 3.911735 0.16 0.877 -7.094264 8.307736 inter4 | 16.7152 12.02584 1.39 0.166 -6.959967 40.39037 kaopen | -.0276263 .1198962 -0.23 0.818 -.263665 .2084125 sdtot | .0447521 .0327955 1.36 0.174 -.0198121 .1093164 sdreer2 | 9.25e-07 5.04e-07 1.83 0.068 -6.78e-08 1.92e-06 sd_krg | .6800897 .2059442 3.30 0.001 .2746491 1.08553 sd_fgr | 1.025568 .3885101 2.64 0.009 .2607113 1.790425 sdinfl | .003093 .0073444 0.42 0.674 -.0113659 .0175519 ncrisis | 5.986289 2.448846 2.44 0.015 1.165266 10.80731 tyear1 | .4573728 .648619 0.71 0.481 -.8195581 1.734304 tyear2 | .277392 .551186 0.50 0.615 -.8077233 1.362507 tyear3 | .6440808 .4553991 1.41 0.158 -.2524596 1.540621 tyear4 | .2508214 .3638954 0.69 0.491 -.4655764 .9672192 tyear5 | -.0030282 .3699571 -0.01 0.993 -.7313597 .7253033 _cons | 1.349508 3.203547 0.42 0.674 -4.957289 7.656305 -------------+---------------------------------------------------------------- sigma_u | 1.2603668 sigma_e | 1.6518483 rho | .3679587 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F6 . dis -_b[trade]/(_b[inter]) -.03629846 . test trade inter ( 1) trade = 0 ( 2) inter4 = 0 F( 2, 273) = 1.68 Prob > F = 0.1891 . xtreg std market_5 trade inter5 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, > fe robust Fixed-effects (within) regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2106 Obs per group: min = 1 between = 0.1861 avg = 4.8 overall = 0.2058 max = 6 F(15,273) = 8.45 corr(u_i, Xb) = 0.0342 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- market_5 | -8.054818 10.14121 -0.79 0.428 -28.01973 11.9101 trade | -1.395644 8.891661 -0.16 0.875 -18.90058 16.10929 inter5 | 8.814172 13.2386 0.67 0.506 -17.24855 34.8769 kaopen | -.0374934 .1193538 -0.31 0.754 -.2724642 .1974774 sdtot | .0437518 .0330146 1.33 0.186 -.0212439 .1087474 sdreer2 | 8.92e-07 4.96e-07 1.80 0.073 -8.43e-08 1.87e-06 sd_krg | .7051438 .212821 3.31 0.001 .2861648 1.124123 sd_fgr | .9765939 .3839179 2.54 0.012 .220778 1.73241 sdinfl | .0031142 .0073522 0.42 0.672 -.01136 .0175885 ncrisis | 5.706981 2.399442 2.38 0.018 .9832194 10.43074 tyear1 | .6134836 .6964961 0.88 0.379 -.7577024 1.98467 tyear2 | .3973118 .5683464 0.70 0.485 -.7215869 1.516211 tyear3 | .7417277 .487242 1.52 0.129 -.2175015 1.700957 tyear4 | .2994686 .3754444 0.80 0.426 -.4396657 1.038603 tyear5 | -.0008391 .3703173 -0.00 0.998 -.7298797 .7282015 _cons | 3.66921 6.744368 0.54 0.587 -9.60837 16.94679 -------------+---------------------------------------------------------------- sigma_u | 1.2989968 sigma_e | 1.6605011 rho | .37964524 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F7 . dis -_b[trade]/(_b[inter]) .15834091 . test trade inter ( 1) trade = 0 ( 2) inter5 = 0 F( 2, 273) = 0.98 Prob > F = 0.3777 . xtreg std market_10 trade inter6 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, > fe robust Fixed-effects (within) regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2114 Obs per group: min = 1 between = 0.2043 avg = 4.8 overall = 0.2129 max = 6 F(15,273) = 8.19 corr(u_i, Xb) = 0.0488 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- market_10 | -12.53265 11.73487 -1.07 0.286 -35.63499 10.56968 trade | -6.997092 12.08211 -0.58 0.563 -30.78303 16.78885 inter6 | 14.26611 15.27897 0.93 0.351 -15.81346 44.34569 kaopen | -.0441328 .1199252 -0.37 0.713 -.2802285 .1919629 sdtot | .0447855 .032836 1.36 0.174 -.0198584 .1094294 sdreer2 | 9.22e-07 4.99e-07 1.85 0.066 -6.01e-08 1.91e-06 sd_krg | .7142415 .2138398 3.34 0.001 .2932568 1.135226 sd_fgr | .9771507 .3842058 2.54 0.012 .220768 1.733533 sdinfl | .0028901 .0073173 0.39 0.693 -.0115155 .0172957 ncrisis | 5.776968 2.397965 2.41 0.017 1.056114 10.49782 tyear1 | .5950901 .6909071 0.86 0.390 -.7650929 1.955273 tyear2 | .3681905 .5539029 0.66 0.507 -.7222735 1.458655 tyear3 | .723535 .4825118 1.50 0.135 -.2263819 1.673452 tyear4 | .2893934 .3727938 0.78 0.438 -.4445227 1.02331 tyear5 | -.0098074 .3712276 -0.03 0.979 -.7406401 .7210253 _cons | 8.377918 9.201754 0.91 0.363 -9.737499 26.49333 -------------+---------------------------------------------------------------- sigma_u | 1.2865384 sigma_e | 1.6596377 rho | .37536038 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F8 . dis -_b[trade]/(_b[inter]) .4904694 . test trade inter ( 1) trade = 0 ( 2) inter6 = 0 F( 2, 273) = 1.11 Prob > F = 0.3299 . xtreg std pc_m trade inter8 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, fe r > obust Fixed-effects (within) regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2132 Obs per group: min = 1 between = 0.2235 avg = 4.8 overall = 0.2200 max = 6 F(15,273) = 8.16 corr(u_i, Xb) = 0.0474 Prob > F = 0.0000 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- pc_m | -1.228195 1.005577 -1.22 0.223 -3.207866 .7514758 trade | 4.600253 3.359677 1.37 0.172 -2.013915 11.21442 inter8 | 1.513893 1.304696 1.16 0.247 -1.054651 4.082436 kaopen | -.0470812 .1183229 -0.40 0.691 -.2800224 .18586 sdtot | .0453579 .0329653 1.38 0.170 -.0195406 .1102563 sdreer2 | 9.24e-07 4.97e-07 1.86 0.064 -5.50e-08 1.90e-06 sd_krg | .7031853 .2103486 3.34 0.001 .2890738 1.117297 sd_fgr | 1.000463 .3856729 2.59 0.010 .2411924 1.759735 sdinfl | .002974 .0072656 0.41 0.683 -.0113297 .0172778 ncrisis | 5.808717 2.415431 2.40 0.017 1.053479 10.56396 tyear1 | .5070157 .6674646 0.76 0.448 -.8070162 1.821048 tyear2 | .2859692 .5560153 0.51 0.607 -.8086535 1.380592 tyear3 | .6605196 .472443 1.40 0.163 -.2695751 1.590614 tyear4 | .2550569 .3710781 0.69 0.492 -.4754815 .9855954 tyear5 | -.0079225 .3721104 -0.02 0.983 -.7404932 .7246481 _cons | -1.754013 2.903559 -0.60 0.546 -7.470225 3.9622 -------------+---------------------------------------------------------------- sigma_u | 1.2709874 sigma_e | 1.6578289 rho | .37018352 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store F9 . dis -_b[trade]/(_b[inter]) -3.0386916 . test trade inter ( 1) trade = 0 ( 2) inter8 = 0 F( 2, 273) = 1.31 Prob > F = 0.2707 . . estout * using "C:\Gazelle\Output\fe.tex", replace style(tex) varlabels(_cons Constant) ce > lls (b(star fmt(%9.3f)) se(par fmt(%9.2f))) stats (r2 r2_a F N, labels("R$^2$" "Adjusted R > $^2$" "F" "N")) starlevels(* 0.10 ** 0.05 *** 0.01) & F1 & F2 & F3 & F4 & F5 > & F6 & F7 & F8 & F9 \\ & b/se & b/se & b/se & b/se & b/se > & b/se & b/se & b/se & b/se \\ trade & 5.188 & -1.112 & -2.831 & -3.220 & 3.371 > & 0.607 & -1.396 & -6.997 & 4.600 \\ & (3.17) & (3.70) & (5.19) & (5.77) & (3.05) > & (3.91) & (8.89) & (12.08) & (3.36) \\ kaopen & -0.039 & -0.110 & -0.106 & -0.106 & -0.110 > & -0.028 & -0.037 & -0.044 & -0.047 \\ & (0.12) & (0.11) & (0.11) & (0.12) & (0.11) > & (0.12) & (0.12) & (0.12) & (0.12) \\ sdtot & 0.040 & 0.044 & 0.043 & 0.042 & 0.043 > & 0.045 & 0.044 & 0.045 & 0.045 \\ & (0.03) & (0.03) & (0.03) & (0.03) & (0.03) > & (0.03) & (0.03) & (0.03) & (0.03) \\ sdreer2 & 0.000* & 0.000 & 0.000* & 0.000* & 0.000* > & 0.000* & 0.000* & 0.000* & 0.000* \\ & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) > & (0.00) & (0.00) & (0.00) & (0.00) \\ sd_krg & 0.721***& 0.683***& 0.698***& 0.694***& 0.702*** > & 0.680***& 0.705***& 0.714***& 0.703***\\ & (0.21) & (0.20) & (0.21) & (0.21) & (0.21) > & (0.21) & (0.21) & (0.21) & (0.21) \\ sd_fgr & 0.855** & 0.932** & 0.901** & 0.904** & 0.912** > & 1.026***& 0.977** & 0.977** & 1.000***\\ & (0.39) & (0.38) & (0.39) & (0.39) & (0.39) > & (0.39) & (0.38) & (0.38) & (0.39) \\ sdinfl & 0.006 & 0.005 & 0.005 & 0.005 & 0.005 > & 0.003 & 0.003 & 0.003 & 0.003 \\ & (0.01) & (0.01) & (0.01) & (0.01) & (0.01) > & (0.01) & (0.01) & (0.01) & (0.01) \\ ncrisis & 5.227** & 5.258** & 4.846** & 4.880** & 4.919** > & 5.986** & 5.707** & 5.777** & 5.809** \\ & (2.27) & (2.25) & (2.26) & (2.27) & (2.26) > & (2.45) & (2.40) & (2.40) & (2.42) \\ tyear1 & 0.788 & -0.218 & -0.155 & -0.124 & -0.206 > & 0.457 & 0.613 & 0.595 & 0.507 \\ & (0.70) & (0.70) & (0.69) & (0.68) & (0.71) > & (0.65) & (0.70) & (0.69) & (0.67) \\ tyear2 & 0.544 & -0.060 & 0.052 & 0.070 & -0.001 > & 0.277 & 0.397 & 0.368 & 0.286 \\ & (0.54) & (0.51) & (0.53) & (0.54) & (0.52) > & (0.55) & (0.57) & (0.55) & (0.56) \\ tyear3 & 0.735* & 0.244 & 0.304 & 0.322 & 0.274 > & 0.644 & 0.742 & 0.724 & 0.661 \\ & (0.44) & (0.42) & (0.42) & (0.43) & (0.43) > & (0.46) & (0.49) & (0.48) & (0.47) \\ tyear4 & 0.451 & 0.123 & 0.159 & 0.169 & 0.134 > & 0.251 & 0.299 & 0.289 & 0.255 \\ & (0.36) & (0.36) & (0.36) & (0.36) & (0.36) > & (0.36) & (0.38) & (0.37) & (0.37) \\ tyear5 & -0.027 & -0.120 & -0.123 & -0.113 & -0.130 > & -0.003 & -0.001 & -0.010 & -0.008 \\ & (0.37) & (0.35) & (0.36) & (0.36) & (0.36) > & (0.37) & (0.37) & (0.37) & (0.37) \\ product_herf& & -18.274 & & & > & & & & \\ & & (12.88) & & & > & & & & \\ inter1 & & 21.888 & & & > & & & & \\ & & (16.01) & & & > & & & & \\ product_5 & & & -8.191 & & > & & & & \\ & & & (6.89) & & > & & & & \\ inter2 & & & 9.824 & & > & & & & \\ & & & (8.53) & & > & & & & \\ product_10 & & & & -7.314 & > & & & & \\ & & & & (6.65) & > & & & & \\ inter3 & & & & 8.743 & > & & & & \\ & & & & (8.12) & > & & & & \\ pc_p & & & & & -1.679 > & & & & \\ & & & & & (1.31) > & & & & \\ inter7 & & & & & 2.031 > & & & & \\ & & & & & (1.64) > & & & & \\ market_herf & & & & & > & -12.540 & & & \\ & & & & & > & (9.50) & & & \\ inter4 & & & & & > & 16.715 & & & \\ & & & & & > & (12.03) & & & \\ market_5 & & & & & > & & -8.055 & & \\ & & & & & > & & (10.14) & & \\ inter5 & & & & & > & & 8.814 & & \\ & & & & & > & & (13.24) & & \\ market_10 & & & & & > & & & -12.533 & \\ & & & & & > & & & (11.73) & \\ inter6 & & & & & > & & & 14.266 & \\ & & & & & > & & & (15.28) & \\ pc_m & & & & & > & & & & -1.228 \\ & & & & & > & & & & (1.01) \\ inter8 & & & & & > & & & & 1.514 \\ & & & & & > & & & & (1.30) \\ Constant & -2.265 & 3.169 & 4.577 & 4.921 & -0.572 > & 1.350 & 3.669 & 8.378 & -1.754 \\ & (2.77) & (3.11) & (4.24) & (4.76) & (2.60) > & (3.20) & (6.74) & (9.20) & (2.90) \\ R$^2$ & 0.204 & 0.204 & 0.197 & 0.196 & 0.199 > & 0.219 & 0.211 & 0.211 & 0.213 \\ Adjusted R$^2$& 0.176 & 0.171 & 0.164 & 0.163 & 0.166 > & 0.185 & 0.177 & 0.177 & 0.179 \\ F & 8.668 & 8.025 & 8.225 & 8.328 & 8.199 > & 8.410 & 8.449 & 8.190 & 8.161 \\ N & 380.000 & 378.000 & 378.000 & 378.000 & 378.000 > & 364.000 & 364.000 & 364.000 & 364.000 \\ . estimates clear . . xtreg std trade kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, re robust cluste > r(country) Random-effects GLS regression Number of obs = 380 Group variable (i): id Number of groups = 77 R-sq: within = 0.1932 Obs per group: min = 1 between = 0.3583 avg = 4.9 overall = 0.2555 max = 6 Random effects u_i ~ Gaussian Wald chi2(13) = 3758.77 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 77 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- trade | 2.563886 1.313501 1.95 0.051 -.0105289 5.138301 kaopen | -.1574516 .0754843 -2.09 0.037 -.305398 -.0095052 sdtot | .0517575 .0179245 2.89 0.004 .0166262 .0868888 sdreer2 | 2.81e-08 5.01e-07 0.06 0.955 -9.53e-07 1.01e-06 sd_krg | .8065235 .185947 4.34 0.000 .4420742 1.170973 sd_fgr | .7290313 .3665961 1.99 0.047 .0105162 1.447546 sdinfl | .0076979 .0079987 0.96 0.336 -.0079793 .0233751 ncrisis | 5.16892 2.326 2.22 0.026 .610045 9.727795 tyear1 | .3870742 .6841708 0.57 0.572 -.9538759 1.728024 tyear2 | .204178 .4362157 0.47 0.640 -.6507891 1.059145 tyear3 | .3637799 .3461998 1.05 0.293 -.3147593 1.042319 tyear4 | .2474762 .2939864 0.84 0.400 -.3287266 .823679 tyear5 | -.2007533 .3616901 -0.56 0.579 -.9096529 .5081464 _cons | -.0246072 1.223573 -0.02 0.984 -2.422766 2.373552 -------------+---------------------------------------------------------------- sigma_u | .91562214 sigma_e | 1.6596376 rho | .23334808 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R1 . xtreg std product_herf trade inter1 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyea > r*, re robust cluster(country) Random-effects GLS regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1986 Obs per group: min = 1 between = 0.3773 avg = 4.9 overall = 0.2735 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 4781.00 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 77 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- product_herf | -12.17887 4.848122 -2.51 0.012 -21.68102 -2.676728 trade | .0157829 1.251369 0.01 0.990 -2.436855 2.468421 inter1 | 15.77885 5.97788 2.64 0.008 4.062426 27.49528 kaopen | -.1663049 .0749898 -2.22 0.027 -.3132822 -.0193275 sdtot | .0425814 .0205121 2.08 0.038 .0023784 .0827845 sdreer2 | 1.66e-07 4.94e-07 0.34 0.737 -8.03e-07 1.14e-06 sd_krg | .7392341 .1647673 4.49 0.000 .4162961 1.062172 sd_fgr | .7904614 .3669542 2.15 0.031 .0712443 1.509679 sdinfl | .0079444 .0077113 1.03 0.303 -.0071695 .0230584 ncrisis | 5.056288 2.336178 2.16 0.030 .477463 9.635113 tyear1 | -.2134791 .5126862 -0.42 0.677 -1.218325 .7913673 tyear2 | -.0090275 .4139237 -0.02 0.983 -.8203032 .8022481 tyear3 | .2478809 .341623 0.73 0.468 -.4216878 .9174496 tyear4 | .1613334 .2926646 0.55 0.581 -.4122787 .7349454 tyear5 | -.164951 .3552544 -0.46 0.642 -.8612368 .5313348 _cons | 2.076882 1.169788 1.78 0.076 -.2158598 4.369624 -------------+---------------------------------------------------------------- sigma_u | .89147854 sigma_e | 1.6153787 rho | .23345811 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R2 . dis -_b[trade]/(_b[inter]) -.00100026 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 8.63 Prob > chi2 = 0.0134 . xtreg std product_5 trade inter2 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, > re robust cluster(country) Random-effects GLS regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1934 Obs per group: min = 1 between = 0.3884 avg = 4.9 overall = 0.2749 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 4817.66 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 77 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- product_5 | -6.732107 3.692957 -1.82 0.068 -13.97017 .5059557 trade | -2.664485 2.100024 -1.27 0.205 -6.780456 1.451486 inter2 | 9.222608 4.552687 2.03 0.043 .2995055 18.14571 kaopen | -.1527368 .0728248 -2.10 0.036 -.2954709 -.0100028 sdtot | .041401 .0212081 1.95 0.051 -.0001661 .0829681 sdreer2 | 1.74e-07 5.05e-07 0.34 0.730 -8.16e-07 1.16e-06 sd_krg | .7496032 .1619348 4.63 0.000 .4322169 1.06699 sd_fgr | .7775244 .3753089 2.07 0.038 .0419326 1.513116 sdinfl | .0077895 .0079099 0.98 0.325 -.0077136 .0232927 ncrisis | 4.946097 2.339775 2.11 0.035 .3602226 9.531971 tyear1 | -.265427 .5087406 -0.52 0.602 -1.26254 .7316864 tyear2 | -.0030426 .4266488 -0.01 0.994 -.8392589 .8331736 tyear3 | .2457824 .3374802 0.73 0.466 -.4156666 .9072314 tyear4 | .1563699 .2936798 0.53 0.594 -.419232 .7319718 tyear5 | -.1806417 .357785 -0.50 0.614 -.8818873 .5206039 _cons | 3.959847 1.767552 2.24 0.025 .4955086 7.424185 -------------+---------------------------------------------------------------- sigma_u | .8922986 sigma_e | 1.6221114 rho | .23230057 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R3 . dis -_b[trade]/(_b[inter]) .28890795 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 4.66 Prob > chi2 = 0.0971 . xtreg std product_10 trade inter3 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear* > , re robust cluster(country) Random-effects GLS regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1920 Obs per group: min = 1 between = 0.3860 avg = 4.9 overall = 0.2728 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 4974.39 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 77 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- product_10 | -5.659876 3.774984 -1.50 0.134 -13.05871 1.738957 trade | -3.086198 2.504759 -1.23 0.218 -7.995435 1.823038 inter3 | 8.08414 4.624226 1.75 0.080 -.9791757 17.14746 kaopen | -.1493394 .0729798 -2.05 0.041 -.2923771 -.0063017 sdtot | .0400065 .0211781 1.89 0.059 -.0015018 .0815148 sdreer2 | 1.96e-07 5.09e-07 0.39 0.700 -8.01e-07 1.19e-06 sd_krg | .7455606 .1642539 4.54 0.000 .4236288 1.067492 sd_fgr | .7809262 .3775213 2.07 0.039 .040998 1.520854 sdinfl | .0080098 .0079926 1.00 0.316 -.0076553 .023675 ncrisis | 4.975726 2.338631 2.13 0.033 .3920931 9.559359 tyear1 | -.2645208 .5039536 -0.52 0.600 -1.252252 .7232101 tyear2 | .0028503 .4283884 0.01 0.995 -.8367755 .8424761 tyear3 | .2559193 .336192 0.76 0.447 -.403005 .9148436 tyear4 | .1637161 .2929883 0.56 0.576 -.4105304 .7379625 tyear5 | -.1699155 .3580473 -0.47 0.635 -.8716754 .5318443 _cons | 4.138828 2.081149 1.99 0.047 .0598514 8.217804 -------------+---------------------------------------------------------------- sigma_u | .89474813 sigma_e | 1.6234654 rho | .23298147 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R4 . dis -_b[trade]/(_b[inter]) .38175961 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 3.52 Prob > chi2 = 0.1723 . xtreg std pc_p trade inter7 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, re r > obust cluster(country) Random-effects GLS regression Number of obs = 378 Group variable (i): id Number of groups = 77 R-sq: within = 0.1949 Obs per group: min = 1 between = 0.3853 avg = 4.9 overall = 0.2751 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 4934.51 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 77 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- pc_p | -1.209376 .6365674 -1.90 0.057 -2.457025 .0382732 trade | 3.09759 1.555425 1.99 0.046 .049014 6.146167 inter7 | 1.658277 .7909154 2.10 0.036 .1081112 3.208443 kaopen | -.1515982 .0738723 -2.05 0.040 -.2963852 -.0068112 sdtot | .0402138 .0215447 1.87 0.062 -.0020131 .0824408 sdreer2 | 1.92e-07 5.07e-07 0.38 0.706 -8.02e-07 1.19e-06 sd_krg | .7450367 .1617315 4.61 0.000 .4280488 1.062025 sd_fgr | .7836984 .3745541 2.09 0.036 .0495859 1.517811 sdinfl | .0079895 .007907 1.01 0.312 -.0075079 .023487 ncrisis | 4.960638 2.340581 2.12 0.034 .3731826 9.548093 tyear1 | -.2618949 .5048965 -0.52 0.604 -1.251474 .7276839 tyear2 | -.0119209 .4226624 -0.03 0.977 -.840324 .8164822 tyear3 | .2492774 .3387694 0.74 0.462 -.4146984 .9132531 tyear4 | .1570957 .2940936 0.53 0.593 -.4193172 .7335085 tyear5 | -.1721308 .3563031 -0.48 0.629 -.870472 .5262105 _cons | -.2377058 1.369663 -0.17 0.862 -2.922196 2.446785 -------------+---------------------------------------------------------------- sigma_u | .89130823 sigma_e | 1.6203764 rho | .23228618 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R5 . dis -_b[trade]/(_b[inter]) -1.8679573 . test trade inter ( 1) trade = 0 ( 2) inter7 = 0 chi2( 2) = 5.02 Prob > chi2 = 0.0813 . . xtreg std market_herf trade inter4 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear > *, re robust cluster(country) Random-effects GLS regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2106 Obs per group: min = 1 between = 0.3318 avg = 4.8 overall = 0.2531 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 3959.04 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 76 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- market_herf | -14.59064 7.929009 -1.84 0.066 -30.13122 .9499272 trade | -.3041083 1.845477 -0.16 0.869 -3.921177 3.312961 inter4 | 18.97351 10.55995 1.80 0.072 -1.723609 39.67064 kaopen | -.1726314 .0740956 -2.33 0.020 -.3178561 -.0274066 sdtot | .0484765 .0217963 2.22 0.026 .0057566 .0911965 sdreer2 | 1.49e-07 5.39e-07 0.28 0.782 -9.07e-07 1.20e-06 sd_krg | .7835805 .1760321 4.45 0.000 .4385639 1.128597 sd_fgr | .7990916 .3751821 2.13 0.033 .0637481 1.534435 sdinfl | .0065999 .0079063 0.83 0.404 -.0088961 .0220959 ncrisis | 5.256462 2.442381 2.15 0.031 .4694833 10.04344 tyear1 | .2687277 .557476 0.48 0.630 -.8239052 1.361361 tyear2 | .1846432 .4280912 0.43 0.666 -.6544001 1.023687 tyear3 | .4095244 .3481417 1.18 0.239 -.2728208 1.09187 tyear4 | .1718194 .2933415 0.59 0.558 -.4031193 .7467582 tyear5 | -.1525173 .3694989 -0.41 0.680 -.8767218 .5716872 _cons | 2.195809 1.476991 1.49 0.137 -.6990409 5.090658 -------------+---------------------------------------------------------------- sigma_u | .87481736 sigma_e | 1.6518483 rho | .21903994 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R6 . dis -_b[trade]/(_b[inter]) .01602805 . test trade inter ( 1) trade = 0 ( 2) inter4 = 0 chi2( 2) = 6.45 Prob > chi2 = 0.0398 . xtreg std market_5 trade inter5 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, > re robust cluster(country) Random-effects GLS regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2018 Obs per group: min = 1 between = 0.3220 avg = 4.8 overall = 0.2464 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 3810.06 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 76 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- market_5 | -10.73137 7.298483 -1.47 0.141 -25.03613 3.573399 trade | -5.528896 5.664193 -0.98 0.329 -16.63051 5.572719 inter5 | 13.25006 9.534237 1.39 0.165 -5.436703 31.93682 kaopen | -.1831055 .0764596 -2.39 0.017 -.3329635 -.0332475 sdtot | .0509962 .0229492 2.22 0.026 .0060167 .0959757 sdreer2 | 1.51e-07 5.40e-07 0.28 0.780 -9.07e-07 1.21e-06 sd_krg | .8240477 .1831266 4.50 0.000 .4651262 1.182969 sd_fgr | .8027191 .3692357 2.17 0.030 .0790304 1.526408 sdinfl | .0059816 .0079065 0.76 0.449 -.0095148 .021478 ncrisis | 5.041553 2.403294 2.10 0.036 .3311837 9.751922 tyear1 | .3079915 .6048157 0.51 0.611 -.8774255 1.493409 tyear2 | .1575326 .4178064 0.38 0.706 -.6613528 .9764181 tyear3 | .4033714 .3495142 1.15 0.248 -.2816638 1.088407 tyear4 | .1385244 .29084 0.48 0.634 -.4315115 .7085603 tyear5 | -.1681658 .3636607 -0.46 0.644 -.8809276 .544596 _cons | 6.542403 4.247346 1.54 0.123 -1.782242 14.86705 -------------+---------------------------------------------------------------- sigma_u | .89612022 sigma_e | 1.6605011 rho | .22555192 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R7 . dis -_b[trade]/(_b[inter]) .41727336 . test trade inter ( 1) trade = 0 ( 2) inter5 = 0 chi2( 2) = 4.85 Prob > chi2 = 0.0885 . xtreg std market_10 trade inter6 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, > re robust cluster(country) Random-effects GLS regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2036 Obs per group: min = 1 between = 0.3204 avg = 4.8 overall = 0.2468 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 3939.31 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 76 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- market_10 | -14.29692 8.904427 -1.61 0.108 -31.74928 3.155431 trade | -10.49541 8.596614 -1.22 0.222 -27.34446 6.353644 inter6 | 17.36787 11.61902 1.49 0.135 -5.40499 40.14072 kaopen | -.185659 .0781173 -2.38 0.017 -.3387661 -.032552 sdtot | .0520472 .0234148 2.22 0.026 .0061549 .0979394 sdreer2 | 1.68e-07 5.46e-07 0.31 0.758 -9.02e-07 1.24e-06 sd_krg | .8352033 .1866622 4.47 0.000 .4693521 1.201055 sd_fgr | .8007592 .3661287 2.19 0.029 .0831601 1.518358 sdinfl | .0056505 .0079857 0.71 0.479 -.0100011 .0213021 ncrisis | 5.069404 2.39431 2.12 0.034 .3766427 9.762165 tyear1 | .3373953 .6191549 0.54 0.586 -.8761261 1.550917 tyear2 | .1702968 .4148392 0.41 0.681 -.642773 .9833666 tyear3 | .4173022 .3513927 1.19 0.235 -.2714148 1.106019 tyear4 | .1446399 .2932111 0.49 0.622 -.4300433 .7193232 tyear5 | -.1748273 .3647416 -0.48 0.632 -.8897078 .5400532 _cons | 10.72222 6.483287 1.65 0.098 -1.984786 23.42923 -------------+---------------------------------------------------------------- sigma_u | .89798161 sigma_e | 1.6596377 rho | .22645982 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R8 . dis -_b[trade]/(_b[inter]) .60430043 . test trade inter ( 1) trade = 0 ( 2) inter6 = 0 chi2( 2) = 5.18 Prob > chi2 = 0.0748 . xtreg std pc_m trade inter8 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, re r > obust cluster(country) Random-effects GLS regression Number of obs = 364 Group variable (i): id Number of groups = 76 R-sq: within = 0.2058 Obs per group: min = 1 between = 0.3211 avg = 4.8 overall = 0.2489 max = 6 Random effects u_i ~ Gaussian Wald chi2(15) = 3931.65 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 76 clusters in country) ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- pc_m | -1.290037 .7551312 -1.71 0.088 -2.770067 .1899932 trade | 3.782609 1.619689 2.34 0.020 .608077 6.95714 inter8 | 1.63263 .9965585 1.64 0.101 -.3205892 3.585848 kaopen | -.1815203 .0763385 -2.38 0.017 -.3311411 -.0318996 sdtot | .0503248 .0226948 2.22 0.027 .0058439 .0948057 sdreer2 | 1.76e-07 5.38e-07 0.33 0.744 -8.78e-07 1.23e-06 sd_krg | .8140672 .1797544 4.53 0.000 .461755 1.166379 sd_fgr | .8047056 .3714797 2.17 0.030 .0766187 1.532793 sdinfl | .0059882 .007871 0.76 0.447 -.0094386 .021415 ncrisis | 5.128452 2.415332 2.12 0.034 .3944875 9.862417 tyear1 | .2972812 .5829156 0.51 0.610 -.8452125 1.439775 tyear2 | .1490775 .4188649 0.36 0.722 -.6718825 .9700376 tyear3 | .399043 .349099 1.14 0.253 -.2851785 1.083264 tyear4 | .1428306 .2927649 0.49 0.626 -.430978 .7166393 tyear5 | -.1636169 .3659059 -0.45 0.655 -.8807793 .5535455 _cons | -.9893275 1.442425 -0.69 0.493 -3.816428 1.837773 -------------+---------------------------------------------------------------- sigma_u | .89520956 sigma_e | 1.6578289 rho | .22575945 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . estimates store R9 . dis -_b[trade]/(_b[inter]) -2.3168811 . test trade inter ( 1) trade = 0 ( 2) inter8 = 0 chi2( 2) = 5.49 Prob > chi2 = 0.0643 . . estout * using "C:\Gazelle\Output\re.tex", replace style(tex) varlabels(_cons Constant) ce > lls (b(star fmt(%9.3f)) se(par fmt(%9.2f))) stats (r2_o chi2 N, labels("R$^2$" "$\chi^2$" > "N")) starlevels(* 0.10 ** 0.05 *** 0.01) & R1 & R2 & R3 & R4 & R5 > & R6 & R7 & R8 & R9 \\ & b/se & b/se & b/se & b/se & b/se > & b/se & b/se & b/se & b/se \\ trade & 2.564* & 0.016 & -2.664 & -3.086 & 3.098** > & -0.304 & -5.529 & -10.495 & 3.783** \\ & (1.31) & (1.25) & (2.10) & (2.50) & (1.56) > & (1.85) & (5.66) & (8.60) & (1.62) \\ kaopen & -0.157** & -0.166** & -0.153** & -0.149** & -0.152** > & -0.173** & -0.183** & -0.186** & -0.182** \\ & (0.08) & (0.07) & (0.07) & (0.07) & (0.07) > & (0.07) & (0.08) & (0.08) & (0.08) \\ sdtot & 0.052***& 0.043** & 0.041* & 0.040* & 0.040* > & 0.048** & 0.051** & 0.052** & 0.050** \\ & (0.02) & (0.02) & (0.02) & (0.02) & (0.02) > & (0.02) & (0.02) & (0.02) & (0.02) \\ sdreer2 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 > & 0.000 & 0.000 & 0.000 & 0.000 \\ & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) > & (0.00) & (0.00) & (0.00) & (0.00) \\ sd_krg & 0.807***& 0.739***& 0.750***& 0.746***& 0.745*** > & 0.784***& 0.824***& 0.835***& 0.814***\\ & (0.19) & (0.16) & (0.16) & (0.16) & (0.16) > & (0.18) & (0.18) & (0.19) & (0.18) \\ sd_fgr & 0.729** & 0.790** & 0.778** & 0.781** & 0.784** > & 0.799** & 0.803** & 0.801** & 0.805** \\ & (0.37) & (0.37) & (0.38) & (0.38) & (0.37) > & (0.38) & (0.37) & (0.37) & (0.37) \\ sdinfl & 0.008 & 0.008 & 0.008 & 0.008 & 0.008 > & 0.007 & 0.006 & 0.006 & 0.006 \\ & (0.01) & (0.01) & (0.01) & (0.01) & (0.01) > & (0.01) & (0.01) & (0.01) & (0.01) \\ ncrisis & 5.169** & 5.056** & 4.946** & 4.976** & 4.961** > & 5.256** & 5.042** & 5.069** & 5.128** \\ & (2.33) & (2.34) & (2.34) & (2.34) & (2.34) > & (2.44) & (2.40) & (2.39) & (2.42) \\ tyear1 & 0.387 & -0.213 & -0.265 & -0.265 & -0.262 > & 0.269 & 0.308 & 0.337 & 0.297 \\ & (0.68) & (0.51) & (0.51) & (0.50) & (0.50) > & (0.56) & (0.60) & (0.62) & (0.58) \\ tyear2 & 0.204 & -0.009 & -0.003 & 0.003 & -0.012 > & 0.185 & 0.158 & 0.170 & 0.149 \\ & (0.44) & (0.41) & (0.43) & (0.43) & (0.42) > & (0.43) & (0.42) & (0.41) & (0.42) \\ tyear3 & 0.364 & 0.248 & 0.246 & 0.256 & 0.249 > & 0.410 & 0.403 & 0.417 & 0.399 \\ & (0.35) & (0.34) & (0.34) & (0.34) & (0.34) > & (0.35) & (0.35) & (0.35) & (0.35) \\ tyear4 & 0.247 & 0.161 & 0.156 & 0.164 & 0.157 > & 0.172 & 0.139 & 0.145 & 0.143 \\ & (0.29) & (0.29) & (0.29) & (0.29) & (0.29) > & (0.29) & (0.29) & (0.29) & (0.29) \\ tyear5 & -0.201 & -0.165 & -0.181 & -0.170 & -0.172 > & -0.153 & -0.168 & -0.175 & -0.164 \\ & (0.36) & (0.36) & (0.36) & (0.36) & (0.36) > & (0.37) & (0.36) & (0.36) & (0.37) \\ product_herf& & -12.179** & & & > & & & & \\ & & (4.85) & & & > & & & & \\ inter1 & & 15.779***& & & > & & & & \\ & & (5.98) & & & > & & & & \\ product_5 & & & -6.732* & & > & & & & \\ & & & (3.69) & & > & & & & \\ inter2 & & & 9.223** & & > & & & & \\ & & & (4.55) & & > & & & & \\ product_10 & & & & -5.660 & > & & & & \\ & & & & (3.77) & > & & & & \\ inter3 & & & & 8.084* & > & & & & \\ & & & & (4.62) & > & & & & \\ pc_p & & & & & -1.209* > & & & & \\ & & & & & (0.64) > & & & & \\ inter7 & & & & & 1.658** > & & & & \\ & & & & & (0.79) > & & & & \\ market_herf & & & & & > & -14.591* & & & \\ & & & & & > & (7.93) & & & \\ inter4 & & & & & > & 18.974* & & & \\ & & & & & > & (10.56) & & & \\ market_5 & & & & & > & & -10.731 & & \\ & & & & & > & & (7.30) & & \\ inter5 & & & & & > & & 13.250 & & \\ & & & & & > & & (9.53) & & \\ market_10 & & & & & > & & & -14.297 & \\ & & & & & > & & & (8.90) & \\ inter6 & & & & & > & & & 17.368 & \\ & & & & & > & & & (11.62) & \\ pc_m & & & & & > & & & & -1.290* \\ & & & & & > & & & & (0.76) \\ inter8 & & & & & > & & & & 1.633 \\ & & & & & > & & & & (1.00) \\ Constant & -0.025 & 2.077* & 3.960** & 4.139** & -0.238 > & 2.196 & 6.542 & 10.722* & -0.989 \\ & (1.22) & (1.17) & (1.77) & (2.08) & (1.37) > & (1.48) & (4.25) & (6.48) & (1.44) \\ R$^2$ & 0.255 & 0.274 & 0.275 & 0.273 & 0.275 > & 0.253 & 0.246 & 0.247 & 0.249 \\ $\chi^2$ & 3758.774 & 4781.005 & 4817.664 & 4974.388 & 4934.506 > & 3959.035 & 3810.065 & 3939.309 & 3931.649 \\ N & 380.000 & 378.000 & 378.000 & 378.000 & 378.000 > & 364.000 & 364.000 & 364.000 & 364.000 \\ . estimates clear . . /* Benchmark system GMM regressions */ . . xtabond2 std l.std trade kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncrisis tyear*, robust > gmm(l.std, lag(2 3) collapse) gmm(trade, lag(2 3) collapse) iv(tyear*) gmm(ncrisis, lag(2 > 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 3) collapse) nodiffsarg > an Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 32 Obs per group: min = 1 Wald chi2(13) = 513.04 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | -.121583 .1780436 -0.68 0.495 -.4705419 .227376 trade | -.5864018 4.133295 -0.14 0.887 -8.687511 7.514708 kaopen | -.4674834 .2138978 -2.19 0.029 -.8867154 -.0482513 sdtot | -.0560138 .0610108 -0.92 0.359 -.1755928 .0635652 sdreer2 | 4.50e-07 1.23e-06 0.37 0.714 -1.95e-06 2.85e-06 sd_krg | .5393269 .5830565 0.92 0.355 -.6034428 1.682097 sd_fgr | .2614974 1.317663 0.20 0.843 -2.321074 2.844069 sdinfl | .0190206 .0177653 1.07 0.284 -.0157988 .0538399 ncrisis | 4.498659 11.65526 0.39 0.700 -18.34523 27.34255 tyear2 | .449404 1.129362 0.40 0.691 -1.764104 2.662912 tyear3 | .2993572 .5123514 0.58 0.559 -.7048331 1.303547 tyear4 | .217954 .3916039 0.56 0.578 -.5495756 .9854836 tyear5 | -.0107081 .8169292 -0.01 0.990 -1.61186 1.590444 _cons | 3.602444 3.383807 1.06 0.287 -3.029697 10.23458 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.41 Pr > z = 0.016 Arellano-Bond test for AR(2) in first differences: z = -0.39 Pr > z = 0.694 Hansen test of overid. restrictions: chi2(18) = 16.50 Prob > chi2 = 0.558 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G1 . xtabond2 std l.std product_herf trade inter1 kaopen sdtot sdreer2 sd_krg sd_fgr sdinfl ncr > isis tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) iv(tyear > *) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2 > ) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 926.22 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1670408 .1218892 1.37 0.171 -.0718577 .4059392 product_herf | -27.89423 9.769793 -2.86 0.004 -47.04267 -8.745787 trade | -5.160318 2.991811 -1.72 0.085 -11.02416 .703524 inter1 | 33.59909 11.30023 2.97 0.003 11.45104 55.74713 kaopen | -.3326315 .1702632 -1.95 0.051 -.6663413 .0010784 sdtot | -.0080207 .037074 -0.22 0.829 -.0806845 .064643 sdreer2 | 2.23e-07 1.04e-06 0.21 0.831 -1.82e-06 2.27e-06 sd_krg | .2894088 .3599622 0.80 0.421 -.4161043 .9949218 sd_fgr | 2.074776 .956046 2.17 0.030 .2009599 3.948591 sdinfl | .0262845 .0125117 2.10 0.036 .0017619 .050807 ncrisis | -2.289905 5.93627 -0.39 0.700 -13.92478 9.34497 tyear2 | -.9761604 .8282115 -1.18 0.239 -2.599425 .6471044 tyear3 | -.1449802 .3882927 -0.37 0.709 -.9060199 .6160595 tyear4 | -.1954696 .3635514 -0.54 0.591 -.9080172 .517078 tyear5 | .5311787 .5549466 0.96 0.338 -.5564967 1.618854 _cons | 6.940305 2.576965 2.69 0.007 1.889547 11.99106 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.45 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.40 Pr > z = 0.689 Hansen test of overid. restrictions: chi2(37) = 37.46 Prob > chi2 = 0.448 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G2 . gen divstar1 = -_b[trade]/(_b[inter]) . dis divstar1 .15358506 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 9.03 Prob > chi2 = 0.0110 . matrix list e(V) symmetric e(V)[16,16] L. std product_herf trade inter1 kaopen L.std .01485698 product_herf -.27902422 95.448856 trade -.14003127 19.730696 8.9509335 inter1 .32437236 -109.45306 -23.194977 127.69521 kaopen .00723503 .05558209 -.09197787 -.01767021 .02898957 sdtot -.00130819 .04625532 .01423373 -.08635438 .00042506 sdreer2 4.642e-08 -1.201e-06 -5.898e-07 1.602e-06 -2.833e-08 sd_krg -.00616414 -.29907266 -.12351188 .22176063 .00077826 sd_fgr .01251242 -2.0909699 -.70813702 2.3805521 -.0192307 sdinfl -.00025837 -.00529277 .00214788 .01053782 .00017937 ncrisis -.02350113 -1.1285701 -1.6182877 1.3584486 .47119373 tyear2 -.02112142 3.4519746 .93481851 -3.9535584 .02830527 tyear3 -.00556817 .78297968 .31248212 -.69387511 .00808817 tyear4 -.00175622 1.1673657 .28974472 -1.2563311 .00154016 tyear5 -.00670858 .10800307 -.04872039 .02130679 -.0120367 _cons .09301758 -17.597816 -7.5418772 20.504179 .0153447 sdtot sdreer2 sd_krg sd_fgr sdinfl sdtot .00137448 sdreer2 -1.961e-08 1.089e-12 sd_krg .00320738 1.007e-08 .12957281 sd_fgr .0031905 2.130e-07 .01396538 .91402387 sdinfl -.00001084 -9.742e-09 -.00124887 .00129964 .00015654 ncrisis -.0134914 -1.594e-06 -.12580922 -1.8658732 .0024971 tyear2 .00031146 -1.726e-07 .01937726 -.6231616 -.00102264 tyear3 -.00348018 8.062e-08 .01300261 .0108597 -.00052341 tyear4 .00005442 5.096e-09 -.04937159 -.09909397 -.00022322 tyear5 -.00036168 9.014e-08 -.05690928 .37844872 .00115291 _cons -.01296269 6.407e-07 .13344555 .85448061 -.00216114 ncrisis tyear2 tyear3 tyear4 tyear5 ncrisis 35.239297 tyear2 1.0277488 .68593433 tyear3 -.20695872 .09975772 .15077122 tyear4 -.37432405 .15268904 .06192961 .1321696 tyear5 -1.0029936 -.16422423 .09488379 .05836581 .30796574 _cons .07556321 -1.0300931 -.3163213 -.33140157 .099847 _cons _cons 6.6407471 . gen cidivstar1 = _se[trade]^2 + divstar1^2*_se[inter]^2 + 2*divstar1*(-23.194977) . dis cidivstar1 4.8382516 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tyear*) gmm > (ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) coll > apse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 787.58 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0930649 .1525841 0.61 0.542 -.2059945 .3921243 product_5 | -20.0449 8.50415 -2.36 0.018 -36.71272 -3.377071 trade | -11.80383 5.362795 -2.20 0.028 -22.31471 -1.292945 inter2 | 24.56514 9.844498 2.50 0.013 5.270278 43.86 kaopen | -.3803622 .1843439 -2.06 0.039 -.7416696 -.0190548 sd_krg | .1757297 .4345982 0.40 0.686 -.6760672 1.027527 sd_fgr | 1.502153 .9973452 1.51 0.132 -.4526079 3.456913 sdtot | -.0069617 .0506619 -0.14 0.891 -.1062572 .0923338 sdreer2 | -1.07e-08 1.31e-06 -0.01 0.993 -2.58e-06 2.56e-06 sdinfl | .0260831 .0143508 1.82 0.069 -.0020439 .0542101 ncrisis | .2271647 5.867532 0.04 0.969 -11.27299 11.72732 tyear2 | -.6314051 .8798267 -0.72 0.473 -2.355834 1.093024 tyear3 | -.1497427 .3877059 -0.39 0.699 -.9096324 .610147 tyear4 | -.0507945 .4070561 -0.12 0.901 -.8486097 .7470207 tyear5 | .4035388 .7031843 0.57 0.566 -.9746772 1.781755 _cons | 12.23954 4.589115 2.67 0.008 3.245039 21.23404 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.23 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.10 Pr > z = 0.919 Hansen test of overid. restrictions: chi2(37) = 32.84 Prob > chi2 = 0.664 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G3 . gen divstar2 = -_b[trade]/(_b[inter]) . dis divstar2 .48051143 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 6.23 Prob > chi2 = 0.0444 . matrix list e(V) symmetric e(V)[16,16] L. std product_5 trade inter2 kaopen sd_krg L.std .02328192 product_5 -.28176497 72.320561 trade -.24184543 39.652994 28.759569 inter2 .31417592 -82.975833 -46.01984 96.914133 kaopen .01322154 -.07954949 -.11565592 .06900527 .03398268 sd_krg .00578536 -1.3367468 -.75251717 1.3500203 .0131588 .18887564 sd_fgr -.02409417 -.41733888 -.47070735 .72526966 -.07152372 -.13484267 sdtot -.00103269 -.05562602 -.01911724 .02846578 .00381498 .00900538 sdreer2 7.165e-08 -9.335e-07 -1.312e-06 1.464e-06 -6.598e-08 -8.342e-08 sdinfl -.00097928 .03462973 .02559497 -.03687752 -.0003528 -.00228836 ncrisis .16738376 -23.48688 -11.654457 25.411724 .51591907 .71108778 tyear2 .00752956 1.9663863 1.4618238 -2.5394144 .0570519 .09651671 tyear3 -.00507992 .53272225 .71369744 -.53140633 -.00789834 -.01712271 tyear4 -.00910208 1.4843568 1.0131488 -1.6917837 .00387788 -.05100868 tyear5 -.04052954 1.7665265 1.0504502 -1.8585997 -.05806038 -.18470227 _cons .15046542 -33.864807 -24.296082 38.960234 .00541658 .63203564 sd_fgr sdtot sdreer2 sdinfl ncrisis tyear2 sd_fgr .99469747 sdtot -.01678682 .00256663 sdreer2 4.584e-07 -4.471e-08 1.714e-12 sdinfl .00302746 -.00005978 -1.137e-08 .00020594 ncrisis -2.0086511 .12377521 -2.486e-06 -.01673086 34.427936 tyear2 -.71357307 .01450053 -3.506e-07 -.00206875 .5967294 .7740951 tyear3 .09206349 -.00523462 1.111e-07 -.00002717 -.66846078 .03488405 tyear4 -.13393651 .00298898 -1.147e-07 .00058236 -.55397984 .19215532 tyear5 .54421337 -.01209909 1.952e-07 .00372486 -2.047612 -.28561053 _cons .77529591 .00856892 1.324e-06 -.02024471 8.4976007 -1.5345224 tyear3 tyear4 tyear5 _cons tyear3 .1503159 tyear4 .05904345 .16569463 tyear5 .13377666 .05947636 .49446822 _cons -.61415786 -.96384616 -.68474563 21.059977 . gen cidivstar2 = _se[trade]^2 + divstar2^2*_se[inter]^2 + 2*divstar2*(-46.01984) . dis cidivstar2 6.9100747 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(tyear*) g > mm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) co > llapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 730.70 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0805123 .1490453 0.54 0.589 -.2116111 .3726357 product_10 | -16.95374 8.077003 -2.10 0.036 -32.78437 -1.123103 trade | -11.9998 5.864835 -2.05 0.041 -23.49467 -.5049352 inter3 | 20.86214 9.417753 2.22 0.027 2.403685 39.3206 kaopen | -.3624476 .1823901 -1.99 0.047 -.7199255 -.0049696 sd_krg | .2587305 .4176507 0.62 0.536 -.5598499 1.077311 sd_fgr | 1.485466 .9736789 1.53 0.127 -.4229098 3.393841 sdtot | .0166203 .0497256 0.33 0.738 -.0808401 .1140808 sdreer2 | -2.77e-07 1.21e-06 -0.23 0.818 -2.64e-06 2.09e-06 sdinfl | .0221839 .0144067 1.54 0.124 -.0060528 .0504206 ncrisis | 1.995087 5.497383 0.36 0.717 -8.779585 12.76976 tyear2 | -.5722799 .8633936 -0.66 0.507 -2.2645 1.11994 tyear3 | -.165093 .3840579 -0.43 0.667 -.9178327 .5876467 tyear4 | -.0639295 .3923212 -0.16 0.871 -.8328649 .7050059 tyear5 | .3136312 .686261 0.46 0.648 -1.031416 1.658678 _cons | 12.22817 4.992472 2.45 0.014 2.443102 22.01323 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.22 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.18 Pr > z = 0.858 Hansen test of overid. restrictions: chi2(37) = 34.70 Prob > chi2 = 0.577 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G4 . gen divstar3 = -_b[trade]/(_b[inter]) . dis divstar3 .57519507 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 4.93 Prob > chi2 = 0.0851 . matrix list e(V) symmetric e(V)[16,16] L. std product_10 trade inter3 kaopen sd_krg L.std .0222145 product_10 -.21844213 65.237976 trade -.23896386 42.046212 34.396292 inter3 .23690566 -75.367816 -49.413193 88.69407 kaopen .01298615 .07506617 -.07073098 -.09324507 .03326614 sd_krg .00907785 -1.0246735 -.660318 1.0296426 .01187366 .17443214 sd_fgr -.0338721 -.7894326 -.51043172 1.1058736 -.07541377 -.11850897 sdtot -.00040951 -.0652147 -.01717563 .03995418 .00231816 .00903628 sdreer2 6.172e-08 -3.261e-07 -1.278e-06 7.857e-07 -3.726e-08 -8.325e-08 sdinfl -.00099196 .02536488 .02480169 -.02655462 -.00041349 -.00229445 ncrisis .06658774 -17.300824 -10.573852 18.760646 .42255874 .55474023 tyear2 .01727626 1.9587449 1.4720126 -2.4840099 .06446078 .08762877 tyear3 -.00707658 .50972119 .70692602 -.51673461 -.00428544 -.01192838 tyear4 -.00749338 1.2812992 1.0238206 -1.4899901 .00432809 -.04493531 tyear5 -.04467033 1.2419588 .98571264 -1.2969723 -.05752568 -.17201921 _cons .15006177 -36.021929 -28.937019 41.867081 -.0306017 .54984648 sd_fgr sdtot sdreer2 sdinfl ncrisis tyear2 sd_fgr .94805067 sdtot -.01748273 .00247264 sdreer2 4.355e-07 -3.778e-08 1.452e-12 sdinfl .00341982 -.00016854 -9.181e-09 .00020755 ncrisis -1.8142813 .11995157 -2.229e-06 -.0184684 30.221217 tyear2 -.68136687 .01394939 -3.019e-07 -.00261913 .69377102 .74544853 tyear3 .10074631 -.00503488 9.880e-08 .0001456 -.53163243 .02469982 tyear4 -.14165717 .00362327 -1.147e-07 .00032563 -.36719574 .18391341 tyear5 .52078971 -.01325071 1.920e-07 .00398833 -1.696345 -.28666474 _cons .8247319 .01073589 1.177e-06 -.01871462 7.8715494 -1.5566009 tyear3 tyear4 tyear5 _cons tyear3 .1475005 tyear4 .04808994 .15391592 tyear5 .12817952 .0426789 .47095422 _cons -.60954996 -.96446519 -.61596717 24.924774 . gen cidivstar3 = _se[trade]^2 + divstar3^2*_se[inter]^2 + 2*divstar3*(-49.413193) . dis cidivstar3 6.8962188 . xtabond2 std l.std pc_p trade inter7 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisis tye > ar*, robust gmm(l.std, lag(2 4)) gmm(trade pc_p inter7, lag(2 2)) iv(tyear*) gmm(ncrisis, > lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) collapse) nodi > ffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 662.33 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0955189 .1432996 0.67 0.505 -.1853432 .3763811 pc_p | -2.320229 1.344465 -1.73 0.084 -4.955333 .3148744 trade | 1.420444 3.298591 0.43 0.667 -5.044677 7.885564 inter7 | 2.750996 1.580356 1.74 0.082 -.3464456 5.848437 kaopen | -.3525714 .170375 -2.07 0.039 -.6865002 -.0186425 sd_krg | .3605096 .445243 0.81 0.418 -.5121507 1.23317 sd_fgr | 1.394346 .927152 1.50 0.133 -.4228385 3.211531 sdtot | .042666 .0410828 1.04 0.299 -.0378548 .1231868 sdreer2 | -5.74e-07 1.12e-06 -0.51 0.610 -2.78e-06 1.63e-06 sdinfl | .0192926 .0141406 1.36 0.172 -.0084225 .0470077 ncrisis | 2.945502 4.933744 0.60 0.550 -6.724459 12.61546 tyear2 | -.5700101 .842132 -0.68 0.498 -2.220559 1.080538 tyear3 | -.3177854 .3855605 -0.82 0.410 -1.07347 .4378994 tyear4 | -.1295463 .3743639 -0.35 0.729 -.8632861 .6041934 tyear5 | .1566525 .6395004 0.24 0.806 -1.096745 1.41005 _cons | 1.08504 2.759034 0.39 0.694 -4.322567 6.492646 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.08 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.34 Pr > z = 0.732 Hansen test of overid. restrictions: chi2(37) = 37.29 Prob > chi2 = 0.456 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G5 . gen divstar4 = -_b[trade]/(_b[inter]) . dis divstar4 -.51633799 . test trade inter ( 1) trade = 0 ( 2) inter7 = 0 chi2( 2) = 3.42 Prob > chi2 = 0.1810 . matrix list e(V) symmetric e(V)[16,16] L. std pc_p trade inter7 kaopen sd_krg sd_fgr L.std .02053479 pc_p -.01497627 1.8075871 trade -.09647014 -2.3929968 10.880705 inter7 .01413186 -2.106879 2.8509305 2.4975259 kaopen .00959105 .06785243 -.2043537 -.08418715 .02902764 sd_krg .00022667 -.11221782 -.00444583 .10023722 .00483477 .19824135 sd_fgr -.03055251 -.03848341 -.02610613 .05332339 -.05484957 -.10638563 .85961092 sdtot -.00146076 .00437438 -.01416836 -.0101504 .00133963 .00621939 -.00396536 sdreer2 6.560e-08 -2.405e-07 -3.009e-07 3.114e-07 -3.777e-08 -2.123e-08 2.074e-07 sdinfl -.0007103 .00275073 .0057772 -.00249181 .00001807 -.00257802 .00310585 ncrisis -.02383658 -1.2048442 1.6002979 1.2348956 .27332764 .47161554 -1.5366619 tyear2 .01844582 .21254551 .07329907 -.26846686 .05385385 .08934896 -.61953157 tyear3 -.00627447 .08774615 .3750746 -.09787569 .00012408 .00567859 .0387201 tyear4 -.00264559 .1589447 .02531736 -.17926469 .00692747 -.05664113 -.10619304 tyear5 -.03193253 .1320385 .11506942 -.13433517 -.03718261 -.16577958 .44990846 _cons .02803703 1.9654994 -8.8287165 -2.2677687 .09846758 -.0668629 .38568827 sdtot sdreer2 sdinfl ncrisis tyear2 tyear3 tyear4 sdtot .0016878 sdreer2 -2.563e-08 1.263e-12 sdinfl -.00004064 -1.103e-08 .00019996 ncrisis .02413453 -1.154e-06 -.00882825 24.341831 tyear2 .00558496 -1.642e-07 -.0023868 .57824448 .70918631 tyear3 -.00265206 5.813e-08 -.00036868 -.16427384 .07386495 .14865693 tyear4 .00201048 -7.522e-08 .00032851 -.29578643 .15922994 .05541109 .14014833 tyear5 -.00378678 5.219e-08 .00330272 -1.2496081 -.24640654 .09380824 .05952989 _cons -.00095843 4.259e-07 -.00249929 -2.401222 -.4008296 -.32173815 -.09810592 tyear5 _cons tyear5 .40896073 _cons .09989136 7.6122674 . gen cidivstar4 = _se[trade]^2 + divstar4^2*_se[inter]^2 + 2*divstar4*(2.8509305) . dis cidivstar4 8.6024704 . xtabond2 std l.std market_herf trade inter4 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncri > sis tyear*, robust gmm(l.std, lag(2 4)) gmm(trade market_herf inter4, lag(2 2)) iv(tyear*) > gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) > collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 289 Time variable : period Number of groups = 74 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 783.17 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .121218 .1618552 0.75 0.454 -.1960124 .4384483 market_herf | -31.82891 16.4199 -1.94 0.053 -64.01133 .3535101 trade | -4.163597 4.05382 -1.03 0.304 -12.10894 3.781745 inter4 | 36.13987 19.26149 1.88 0.061 -1.611953 73.89168 kaopen | -.2183034 .1822698 -1.20 0.231 -.5755457 .1389389 sd_krg | 1.256627 .4001997 3.14 0.002 .4722497 2.041004 sd_fgr | .7060296 .8827309 0.80 0.424 -1.024091 2.43615 sdtot | .0467605 .0478583 0.98 0.329 -.0470401 .1405611 sdreer2 | 1.05e-07 1.31e-06 0.08 0.936 -2.45e-06 2.67e-06 sdinfl | -.0017159 .013171 -0.13 0.896 -.0275305 .0240987 ncrisis | 3.244849 4.357174 0.74 0.456 -5.295056 11.78475 tyear2 | .5500373 .7810994 0.70 0.481 -.9808895 2.080964 tyear3 | .3519502 .379807 0.93 0.354 -.3924579 1.096358 tyear4 | .0164717 .3752609 0.04 0.965 -.7190261 .7519695 tyear5 | -.4251932 .5245948 -0.81 0.418 -1.45338 .6029937 _cons | 5.66046 3.382672 1.67 0.094 -.9694556 12.29037 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.02 Pr > z = 0.003 Arellano-Bond test for AR(2) in first differences: z = 0.98 Pr > z = 0.328 Hansen test of overid. restrictions: chi2(37) = 40.41 Prob > chi2 = 0.322 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G6 . dis -_b[trade]/(_b[inter]) .11520787 . test trade inter ( 1) trade = 0 ( 2) inter4 = 0 chi2( 2) = 3.64 Prob > chi2 = 0.1619 . xtabond2 std l.std market_5 trade inter5 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisis > tyear*, robust gmm(l.std, lag(2 4)) gmm(trade market_5 inter5, lag(2 2)) iv(tyear*) gmm(n > crisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) collap > se) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 289 Time variable : period Number of groups = 74 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 749.97 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .2101895 .174573 1.20 0.229 -.1319674 .5523463 market_5 | -32.60127 22.64474 -1.44 0.150 -76.98414 11.7816 trade | -19.90336 16.13307 -1.23 0.217 -51.52359 11.71687 inter5 | 35.56895 26.80157 1.33 0.184 -16.96116 88.09906 kaopen | -.2252979 .2011896 -1.12 0.263 -.6196222 .1690264 sd_krg | 1.505978 .5919692 2.54 0.011 .3457392 2.666216 sd_fgr | -.3440045 1.015432 -0.34 0.735 -2.334216 1.646207 sdtot | .0941222 .0867845 1.08 0.278 -.0759723 .2642167 sdreer2 | -5.17e-07 1.63e-06 -0.32 0.751 -3.71e-06 2.68e-06 sdinfl | -.0112207 .0154393 -0.73 0.467 -.0414812 .0190399 ncrisis | 5.670913 5.775827 0.98 0.326 -5.6495 16.99133 tyear2 | 1.161253 .8366504 1.39 0.165 -.4785515 2.801058 tyear3 | .0979743 .4147552 0.24 0.813 -.714931 .9108797 tyear4 | .0103865 .3885089 0.03 0.979 -.7510768 .7718499 tyear5 | -1.090785 .6756562 -1.61 0.106 -2.415046 .2334772 _cons | 19.61217 13.63013 1.44 0.150 -7.1024 46.32673 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.16 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 1.37 Pr > z = 0.169 Hansen test of overid. restrictions: chi2(37) = 45.09 Prob > chi2 = 0.170 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G7 . dis -_b[trade]/(_b[inter]) .55957109 . test trade inter ( 1) trade = 0 ( 2) inter5 = 0 chi2( 2) = 1.98 Prob > chi2 = 0.3725 . xtabond2 std l.std market_10 trade inter6 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s tyear*, robust gmm(l.std, lag(2 4)) gmm(trade market_10 inter6, lag(2 2)) iv(tyear*) gmm > (ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) coll > apse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 289 Time variable : period Number of groups = 74 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 860.07 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .2464081 .1835487 1.34 0.179 -.1133407 .606157 market_10 | -40.55187 29.03091 -1.40 0.162 -97.45141 16.34768 trade | -31.76798 26.22164 -1.21 0.226 -83.16145 19.62548 inter6 | 45.52551 34.91476 1.30 0.192 -22.90616 113.9572 kaopen | -.28058 .1942101 -1.44 0.149 -.6612248 .1000648 sd_krg | 1.31548 .558538 2.36 0.019 .2207655 2.410194 sd_fgr | -.236738 1.04144 -0.23 0.820 -2.277923 1.804447 sdtot | .0783403 .0809542 0.97 0.333 -.080327 .2370076 sdreer2 | -2.27e-07 1.45e-06 -0.16 0.876 -3.08e-06 2.62e-06 sdinfl | -.0090503 .0155361 -0.58 0.560 -.0395005 .0213999 ncrisis | 5.24238 5.880563 0.89 0.373 -6.283312 16.76807 tyear2 | 1.110482 .8399798 1.32 0.186 -.5358479 2.756813 tyear3 | .1236047 .3890169 0.32 0.751 -.6388545 .8860639 tyear4 | .0833575 .3777903 0.22 0.825 -.6570979 .8238128 tyear5 | -.9466036 .6712513 -1.41 0.158 -2.262232 .3690249 _cons | 29.69534 21.71231 1.37 0.171 -12.86 72.25067 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.13 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 1.28 Pr > z = 0.201 Hansen test of overid. restrictions: chi2(37) = 41.06 Prob > chi2 = 0.297 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G8 . dis -_b[trade]/(_b[inter]) .69780624 . test trade inter ( 1) trade = 0 ( 2) inter6 = 0 chi2( 2) = 2.48 Prob > chi2 = 0.2900 . xtabond2 std l.std pc_m trade inter8 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisis tye > ar*, robust gmm(l.std, lag(2 4)) gmm(trade pc_m inter8, lag(2 2)) iv(tyear*) gmm(ncrisis, > lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 2) collapse) nodi > ffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 289 Time variable : period Number of groups = 74 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 507.85 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0941699 .1672258 0.56 0.573 -.2335867 .4219265 pc_m | -3.583612 1.967276 -1.82 0.069 -7.439402 .2721768 trade | 6.502473 3.934376 1.65 0.098 -1.208762 14.21371 inter8 | 3.868505 2.313615 1.67 0.095 -.6660975 8.403107 kaopen | -.3354664 .1709236 -1.96 0.050 -.6704705 -.0004622 sd_krg | 1.453068 .560567 2.59 0.010 .3543767 2.551759 sd_fgr | -.1172248 .9894798 -0.12 0.906 -2.05657 1.82212 sdtot | .1047463 .0739131 1.42 0.156 -.0401207 .2496133 sdreer2 | -8.05e-07 1.51e-06 -0.53 0.594 -3.77e-06 2.16e-06 sdinfl | -.0082677 .0139783 -0.59 0.554 -.0356646 .0191293 ncrisis | 4.538922 5.088225 0.89 0.372 -5.433815 14.51166 tyear2 | .9941381 .9197569 1.08 0.280 -.8085523 2.796829 tyear3 | .1530232 .4610678 0.33 0.740 -.7506532 1.0567 tyear4 | .0828842 .3913867 0.21 0.832 -.6842197 .849988 tyear5 | -.8776592 .6754282 -1.30 0.194 -2.201474 .4461557 _cons | -4.121722 3.510107 -1.17 0.240 -11.00141 2.757961 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.97 Pr > z = 0.003 Arellano-Bond test for AR(2) in first differences: z = 1.19 Pr > z = 0.234 Hansen test of overid. restrictions: chi2(37) = 43.79 Prob > chi2 = 0.206 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store G9 . dis -_b[trade]/(_b[inter]) -1.6808752 . test trade inter ( 1) trade = 0 ( 2) inter8 = 0 chi2( 2) = 3.33 Prob > chi2 = 0.1891 . . estout * using "C:\Gazelle\Output\gmm.tex", replace style(tex) varlabels(_cons Constant) c > ells (b(star fmt(%9.3f)) se(par fmt(%9.2f))) stats (chi2 sargan sarganp ar2 ar2p N, labels > ("$\chi^2$" "Sargan" "Sargan p" "AR(2)" "AR(2) p" "N")) starlevels(* 0.10 ** 0.05 *** 0.01 > ) & G1 & G2 & G3 & G4 & G5 > & G6 & G7 & G8 & G9 \\ & b/se & b/se & b/se & b/se & b/se > & b/se & b/se & b/se & b/se \\ L.std & -0.122 & 0.167 & 0.093 & 0.081 & 0.096 > & 0.121 & 0.210 & 0.246 & 0.094 \\ & (0.18) & (0.12) & (0.15) & (0.15) & (0.14) > & (0.16) & (0.17) & (0.18) & (0.17) \\ trade & -0.586 & -5.160* & -11.804** & -12.000** & 1.420 > & -4.164 & -19.903 & -31.768 & 6.502* \\ & (4.13) & (2.99) & (5.36) & (5.86) & (3.30) > & (4.05) & (16.13) & (26.22) & (3.93) \\ kaopen & -0.467** & -0.333* & -0.380** & -0.362** & -0.353** > & -0.218 & -0.225 & -0.281 & -0.335** \\ & (0.21) & (0.17) & (0.18) & (0.18) & (0.17) > & (0.18) & (0.20) & (0.19) & (0.17) \\ sdtot & -0.056 & -0.008 & -0.007 & 0.017 & 0.043 > & 0.047 & 0.094 & 0.078 & 0.105 \\ & (0.06) & (0.04) & (0.05) & (0.05) & (0.04) > & (0.05) & (0.09) & (0.08) & (0.07) \\ sdreer2 & 0.000 & 0.000 & -0.000 & -0.000 & -0.000 > & 0.000 & -0.000 & -0.000 & -0.000 \\ & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) > & (0.00) & (0.00) & (0.00) & (0.00) \\ sd_krg & 0.539 & 0.289 & 0.176 & 0.259 & 0.361 > & 1.257***& 1.506** & 1.315** & 1.453***\\ & (0.58) & (0.36) & (0.43) & (0.42) & (0.45) > & (0.40) & (0.59) & (0.56) & (0.56) \\ sd_fgr & 0.261 & 2.075** & 1.502 & 1.485 & 1.394 > & 0.706 & -0.344 & -0.237 & -0.117 \\ & (1.32) & (0.96) & (1.00) & (0.97) & (0.93) > & (0.88) & (1.02) & (1.04) & (0.99) \\ sdinfl & 0.019 & 0.026** & 0.026* & 0.022 & 0.019 > & -0.002 & -0.011 & -0.009 & -0.008 \\ & (0.02) & (0.01) & (0.01) & (0.01) & (0.01) > & (0.01) & (0.02) & (0.02) & (0.01) \\ ncrisis & 4.499 & -2.290 & 0.227 & 1.995 & 2.946 > & 3.245 & 5.671 & 5.242 & 4.539 \\ & (11.66) & (5.94) & (5.87) & (5.50) & (4.93) > & (4.36) & (5.78) & (5.88) & (5.09) \\ tyear2 & 0.449 & -0.976 & -0.631 & -0.572 & -0.570 > & 0.550 & 1.161 & 1.110 & 0.994 \\ & (1.13) & (0.83) & (0.88) & (0.86) & (0.84) > & (0.78) & (0.84) & (0.84) & (0.92) \\ tyear3 & 0.299 & -0.145 & -0.150 & -0.165 & -0.318 > & 0.352 & 0.098 & 0.124 & 0.153 \\ & (0.51) & (0.39) & (0.39) & (0.38) & (0.39) > & (0.38) & (0.41) & (0.39) & (0.46) \\ tyear4 & 0.218 & -0.195 & -0.051 & -0.064 & -0.130 > & 0.016 & 0.010 & 0.083 & 0.083 \\ & (0.39) & (0.36) & (0.41) & (0.39) & (0.37) > & (0.38) & (0.39) & (0.38) & (0.39) \\ tyear5 & -0.011 & 0.531 & 0.404 & 0.314 & 0.157 > & -0.425 & -1.091 & -0.947 & -0.878 \\ & (0.82) & (0.55) & (0.70) & (0.69) & (0.64) > & (0.52) & (0.68) & (0.67) & (0.68) \\ product_herf& & -27.894***& & & > & & & & \\ & & (9.77) & & & > & & & & \\ inter1 & & 33.599***& & & > & & & & \\ & & (11.30) & & & > & & & & \\ product_5 & & & -20.045** & & > & & & & \\ & & & (8.50) & & > & & & & \\ inter2 & & & 24.565** & & > & & & & \\ & & & (9.84) & & > & & & & \\ product_10 & & & & -16.954** & > & & & & \\ & & & & (8.08) & > & & & & \\ inter3 & & & & 20.862** & > & & & & \\ & & & & (9.42) & > & & & & \\ pc_p & & & & & -2.320* > & & & & \\ & & & & & (1.34) > & & & & \\ inter7 & & & & & 2.751* > & & & & \\ & & & & & (1.58) > & & & & \\ market_herf & & & & & > & -31.829* & & & \\ & & & & & > & (16.42) & & & \\ inter4 & & & & & > & 36.140* & & & \\ & & & & & > & (19.26) & & & \\ market_5 & & & & & > & & -32.601 & & \\ & & & & & > & & (22.64) & & \\ inter5 & & & & & > & & 35.569 & & \\ & & & & & > & & (26.80) & & \\ market_10 & & & & & > & & & -40.552 & \\ & & & & & > & & & (29.03) & \\ inter6 & & & & & > & & & 45.526 & \\ & & & & & > & & & (34.91) & \\ pc_m & & & & & > & & & & -3.584* \\ & & & & & > & & & & (1.97) \\ inter8 & & & & & > & & & & 3.869* \\ & & & & & > & & & & (2.31) \\ Constant & 3.602 & 6.940***& 12.240***& 12.228** & 1.085 > & 5.660* & 19.612 & 29.695 & -4.122 \\ & (3.38) & (2.58) & (4.59) & (4.99) & (2.76) > & (3.38) & (13.63) & (21.71) & (3.51) \\ $\chi^2$ & 513.040 & 926.220 & 787.581 & 730.702 & 662.332 > & 783.173 & 749.972 & 860.066 & 507.845 \\ Sargan & 16.502 & 37.458 & 32.840 & 34.704 & 37.293 > & 40.410 & 45.090 & 41.059 & 43.789 \\ Sargan p & 0.558 & 0.448 & 0.664 & 0.577 & 0.456 > & 0.322 & 0.170 & 0.297 & 0.206 \\ AR(2) & -0.394 & 0.400 & 0.101 & 0.179 & 0.343 > & 0.978 & 1.375 & 1.279 & 1.191 \\ AR(2) p & 0.694 & 0.689 & 0.919 & 0.858 & 0.732 > & 0.328 & 0.169 & 0.201 & 0.234 \\ N & 302.000 & 302.000 & 302.000 & 302.000 & 302.000 > & 289.000 & 289.000 & 289.000 & 289.000 \\ . estimates clear . . preserve . keep if period == 6 (316 observations deleted) . count if product_herf ~= . 64 . count if product_herf <= divstar1 51 . count if product_5 ~= . 64 . count if product_5 <= divstar2 36 . count if product_10 ~= . 64 . count if product_10 <= divstar3 30 . count if pc_p ~= . 64 . count if pc_p <= divstar4 43 . restore . . /* Robustness checks */ . . . /* Inclusion of additional economic controls */ . . * (a) Initial GDP per capita . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis lningp tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) i > v(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(lningp sdinfl sdreer2 sd_krg kaopen sdtot s > d_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 941.72 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1568487 .1306513 1.20 0.230 -.0992232 .4129206 product_herf | -23.60752 8.873651 -2.66 0.008 -40.99956 -6.215482 trade | -4.249785 2.881992 -1.47 0.140 -9.898386 1.398816 inter1 | 28.5089 10.4553 2.73 0.006 8.016893 49.00091 kaopen | -.314113 .1757117 -1.79 0.074 -.6585017 .0302756 sd_krg | .2976451 .3828185 0.78 0.437 -.4526654 1.047956 sd_fgr | 1.637552 .9258209 1.77 0.077 -.1770231 3.452128 sdtot | .0132066 .0419204 0.32 0.753 -.0689559 .0953692 sdreer2 | -1.95e-07 1.07e-06 -0.18 0.856 -2.30e-06 1.91e-06 sdinfl | .0250842 .0125176 2.00 0.045 .00055 .0496183 ncrisis | -1.867782 5.345409 -0.35 0.727 -12.34459 8.609028 lningp | .0585826 .2054963 0.29 0.776 -.3441828 .461348 tyear2 | -.6883111 .7714287 -0.89 0.372 -2.200284 .8236613 tyear3 | -.1818406 .4448952 -0.41 0.683 -1.053819 .6901379 tyear4 | -.0647665 .343482 -0.19 0.850 -.7379788 .6084459 tyear5 | .3780786 .5653765 0.67 0.504 -.730039 1.486196 _cons | 5.477311 2.656362 2.06 0.039 .2709361 10.68369 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.26 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.44 Pr > z = 0.662 Hansen test of overid. restrictions: chi2(38) = 42.36 Prob > chi2 = 0.289 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C1 . dis -_b[trade]/(_b[inter]) .14906869 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 7.47 Prob > chi2 = 0.0239 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s lningp tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tyea > r*) gmm(ncrisis, lag(2 2) eq(level)) gmm(lningp sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 886.99 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0887288 .1587293 0.56 0.576 -.2223749 .3998325 product_5 | -18.12815 9.035913 -2.01 0.045 -35.83821 -.4180826 trade | -10.85266 5.087507 -2.13 0.033 -20.82399 -.8813305 inter2 | 22.46621 10.28209 2.18 0.029 2.313682 42.61875 kaopen | -.3612281 .1967413 -1.84 0.066 -.7468339 .0243778 sd_krg | .1534545 .4425981 0.35 0.729 -.7140218 1.020931 sd_fgr | 1.353424 .9738592 1.39 0.165 -.5553051 3.262153 sdtot | -.0001576 .0496554 -0.00 0.997 -.0974804 .0971653 sdreer2 | -2.46e-07 1.35e-06 -0.18 0.855 -2.89e-06 2.40e-06 sdinfl | .0269206 .0152163 1.77 0.077 -.0029028 .0567441 ncrisis | .479187 5.784574 0.08 0.934 -10.85837 11.81674 lningp | .0263506 .2047841 0.13 0.898 -.3750188 .42772 tyear2 | -.5363642 .8680021 -0.62 0.537 -2.237617 1.164889 tyear3 | -.1736844 .427465 -0.41 0.685 -1.0115 .6641316 tyear4 | -.0007323 .3942507 -0.00 0.999 -.7734495 .7719849 tyear5 | .364662 .7068995 0.52 0.606 -1.020835 1.750159 _cons | 11.07134 4.908422 2.26 0.024 1.451005 20.69167 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.04 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.13 Pr > z = 0.900 Hansen test of overid. restrictions: chi2(38) = 33.28 Prob > chi2 = 0.687 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C2 . dis -_b[trade]/(_b[inter]) .48306585 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 5.04 Prob > chi2 = 0.0803 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is lningp tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(ty > ear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(lningp sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 804.64 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0841837 .1495749 0.56 0.574 -.2089778 .3773452 product_10 | -17.52289 8.979211 -1.95 0.051 -35.12182 .0760437 trade | -11.9835 5.861115 -2.04 0.041 -23.47107 -.4959226 inter3 | 21.20438 10.13705 2.09 0.036 1.336117 41.07263 kaopen | -.3448425 .1790227 -1.93 0.054 -.6957206 .0060356 sd_krg | .2848453 .4383399 0.65 0.516 -.5742851 1.143976 sd_fgr | 1.438235 .892616 1.61 0.107 -.3112599 3.18773 sdtot | .0213069 .0490071 0.43 0.664 -.0747453 .1173591 sdreer2 | -3.95e-07 1.26e-06 -0.31 0.753 -2.86e-06 2.07e-06 sdinfl | .0227923 .0156347 1.46 0.145 -.0078511 .0534357 ncrisis | 1.876622 5.461172 0.34 0.731 -8.827079 12.58032 lningp | -.0565744 .1927983 -0.29 0.769 -.4344521 .3213034 tyear2 | -.4984886 .8435073 -0.59 0.555 -2.151732 1.154755 tyear3 | -.1597712 .4187275 -0.38 0.703 -.9804621 .6609197 tyear4 | -.0600369 .3841042 -0.16 0.876 -.8128672 .6927934 tyear5 | .2751097 .6642504 0.41 0.679 -1.026797 1.577017 _cons | 12.75994 5.669647 2.25 0.024 1.647634 23.87224 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.20 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.21 Pr > z = 0.834 Hansen test of overid. restrictions: chi2(38) = 36.09 Prob > chi2 = 0.558 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .56514267 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 4.53 Prob > chi2 = 0.1036 . . * (b) Growth rate . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis growth2 tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) > iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(growth2 sdinfl sdreer2 sd_krg kaopen sdtot > sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 43 Obs per group: min = 3 Wald chi2(15) = 640.90 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .3149054 .1265588 2.49 0.013 .0668547 .5629561 product_herf | -30.61339 10.90325 -2.81 0.005 -51.98336 -9.243418 trade | -6.50266 3.930629 -1.65 0.098 -14.20655 1.201231 inter1 | 35.61641 12.99057 2.74 0.006 10.15535 61.07746 kaopen | -.3169124 .2526874 -1.25 0.210 -.8121706 .1783458 sd_krg | -.1227327 .3860775 -0.32 0.751 -.8794307 .6339653 sd_fgr | 2.855539 .8565161 3.33 0.001 1.176798 4.534279 sdtot | -.0105823 .0395712 -0.27 0.789 -.0881404 .0669758 sdreer2 | 1.02e-06 1.12e-06 0.91 0.363 -1.18e-06 3.22e-06 sdinfl | .0130674 .0142673 0.92 0.360 -.0148959 .0410308 ncrisis | -1.709621 5.791764 -0.30 0.768 -13.06127 9.642028 growth2 | -.148967 .1860935 -0.80 0.423 -.5137036 .2157695 tyear2 | -2.366761 1.066193 -2.22 0.026 -4.456461 -.2770605 tyear3 | -1.203586 .579066 -2.08 0.038 -2.338535 -.0686379 tyear4 | -1.188364 .5349121 -2.22 0.026 -2.236773 -.1399558 _cons | 9.233909 3.025117 3.05 0.002 3.304788 15.16303 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.99 Pr > z = 0.003 Arellano-Bond test for AR(2) in first differences: z = 0.40 Pr > z = 0.688 Hansen test of overid. restrictions: chi2(27) = 25.56 Prob > chi2 = 0.543 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C3 . dis -_b[trade]/(_b[inter]) .18257484 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 7.55 Prob > chi2 = 0.0229 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s growth2 tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tye > ar*) gmm(ncrisis, lag(2 2) eq(level)) gmm(growth2 sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 43 Obs per group: min = 3 Wald chi2(15) = 466.28 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0448291 .1740179 0.26 0.797 -.2962397 .3858979 product_5 | -19.63843 10.41444 -1.89 0.059 -40.05035 .7734928 trade | -11.37206 7.282364 -1.56 0.118 -25.64523 2.901116 inter2 | 21.64081 12.94399 1.67 0.095 -3.728938 47.01056 kaopen | -.444819 .2547918 -1.75 0.081 -.9442018 .0545638 sd_krg | .2213955 .4058039 0.55 0.585 -.5739656 1.016757 sd_fgr | 1.740658 1.007135 1.73 0.084 -.2332895 3.714606 sdtot | .0073011 .0393165 0.19 0.853 -.0697579 .0843601 sdreer2 | 4.23e-07 1.39e-06 0.31 0.760 -2.29e-06 3.14e-06 sdinfl | .0084237 .0153115 0.55 0.582 -.0215863 .0384337 ncrisis | -1.990424 5.648042 -0.35 0.725 -13.06038 9.079535 growth2 | -.2600088 .1761098 -1.48 0.140 -.6051776 .08516 tyear2 | -1.243841 1.321411 -0.94 0.347 -3.833759 1.346077 tyear3 | -.6237614 .6997216 -0.89 0.373 -1.995191 .7476676 tyear4 | -.6208713 .6679399 -0.93 0.353 -1.930009 .6882669 _cons | 14.05761 5.338959 2.63 0.008 3.593441 24.52178 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.36 Pr > z = 0.018 Arellano-Bond test for AR(2) in first differences: z = -0.05 Pr > z = 0.961 Hansen test of overid. restrictions: chi2(27) = 22.46 Prob > chi2 = 0.714 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C4 . dis -_b[trade]/(_b[inter]) .52549121 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 2.83 Prob > chi2 = 0.2428 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is growth2 tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(t > year*) gmm(ncrisis, lag(2 2) eq(level)) gmm(growth2 sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 43 Obs per group: min = 3 Wald chi2(15) = 462.21 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0623666 .1750957 0.36 0.722 -.2808146 .4055478 product_10 | -12.87738 10.22069 -1.26 0.208 -32.90957 7.154804 trade | -9.737733 8.41425 -1.16 0.247 -26.22936 6.753894 inter3 | 13.61192 13.02465 1.05 0.296 -11.91593 39.13977 kaopen | -.3982612 .2400479 -1.66 0.097 -.8687465 .0722241 sd_krg | .1326149 .3677073 0.36 0.718 -.5880781 .853308 sd_fgr | 1.715177 .9670038 1.77 0.076 -.1801156 3.610469 sdtot | .0186223 .0390863 0.48 0.634 -.0579855 .0952301 sdreer2 | 3.31e-07 1.43e-06 0.23 0.816 -2.47e-06 3.13e-06 sdinfl | .0079718 .0157042 0.51 0.612 -.0228078 .0387514 ncrisis | .0378778 5.497517 0.01 0.995 -10.73706 10.81281 growth2 | -.2023967 .1707554 -1.19 0.236 -.5370711 .1322777 tyear2 | -1.169718 1.225039 -0.95 0.340 -3.57075 1.231314 tyear3 | -.670054 .6470117 -1.04 0.300 -1.938174 .5980657 tyear4 | -.5708395 .6417398 -0.89 0.374 -1.828626 .6869475 _cons | 12.57444 6.189291 2.03 0.042 .4436486 24.70523 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.35 Pr > z = 0.019 Arellano-Bond test for AR(2) in first differences: z = 0.09 Pr > z = 0.929 Hansen test of overid. restrictions: chi2(27) = 21.14 Prob > chi2 = 0.780 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .71538277 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 1.34 Prob > chi2 = 0.5119 . . * (c) Human capital . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis sec2i tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) iv > (tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sec2i sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 1005.93 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1602555 .1226306 1.31 0.191 -.080096 .400607 product_herf | -26.75898 8.95592 -2.99 0.003 -44.31226 -9.205694 trade | -4.256632 2.79463 -1.52 0.128 -9.734007 1.220743 inter1 | 32.19512 10.5046 3.06 0.002 11.60647 52.78376 kaopen | -.3175249 .164624 -1.93 0.054 -.640182 .0051322 sd_krg | .2574671 .3492648 0.74 0.461 -.4270794 .9420135 sd_fgr | 1.865765 .9012438 2.07 0.038 .0993594 3.63217 sdtot | -.0055093 .039053 -0.14 0.888 -.0820516 .0710331 sdreer2 | -6.86e-10 1.07e-06 -0.00 0.999 -2.10e-06 2.10e-06 sdinfl | .0278254 .0124347 2.24 0.025 .0034538 .0521969 ncrisis | -1.823343 5.655327 -0.32 0.747 -12.90758 9.260895 sec2i | -.0203217 .4275111 -0.05 0.962 -.8582281 .8175847 tyear2 | -.8222094 .786523 -1.05 0.296 -2.363766 .7193473 tyear3 | -.1163332 .3902088 -0.30 0.766 -.8811285 .648462 tyear4 | -.1153413 .3441024 -0.34 0.737 -.7897697 .5590871 tyear5 | .4838173 .5446279 0.89 0.374 -.5836337 1.551268 _cons | 6.184 2.738911 2.26 0.024 .8158337 11.55217 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.39 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.36 Pr > z = 0.716 Hansen test of overid. restrictions: chi2(38) = 39.37 Prob > chi2 = 0.408 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C5 . dis -_b[trade]/(_b[inter]) .1322136 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 9.53 Prob > chi2 = 0.0085 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s sec2i tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tyear > *) gmm(ncrisis, lag(2 2) eq(level)) gmm(sec2i sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, l > ag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 826.09 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0972587 .1580738 0.62 0.538 -.2125603 .4070778 product_5 | -19.77984 8.768293 -2.26 0.024 -36.96538 -2.594305 trade | -12.01813 5.436165 -2.21 0.027 -22.67282 -1.363444 inter2 | 24.47854 10.12697 2.42 0.016 4.63005 44.32703 kaopen | -.4235829 .1814747 -2.33 0.020 -.7792667 -.0678991 sd_krg | .1843966 .4247089 0.43 0.664 -.6480176 1.016811 sd_fgr | 1.577668 1.004459 1.57 0.116 -.3910357 3.546371 sdtot | -.0043297 .0507079 -0.09 0.932 -.1037154 .095056 sdreer2 | -7.98e-08 1.31e-06 -0.06 0.952 -2.66e-06 2.50e-06 sdinfl | .0269443 .0144584 1.86 0.062 -.0013935 .0552822 ncrisis | -1.039588 6.159182 -0.17 0.866 -13.11136 11.03219 sec2i | .2263269 .4415696 0.51 0.608 -.6391336 1.091787 tyear2 | -.7173309 .8802641 -0.81 0.415 -2.442617 1.007955 tyear3 | -.1456106 .3883727 -0.37 0.708 -.906807 .6155858 tyear4 | -.0283955 .4186624 -0.07 0.946 -.8489587 .7921677 tyear5 | .4671612 .7141237 0.65 0.513 -.9324955 1.866818 _cons | 11.43147 5.069529 2.25 0.024 1.495379 21.36757 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.17 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.12 Pr > z = 0.903 Hansen test of overid. restrictions: chi2(38) = 32.07 Prob > chi2 = 0.739 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C6 . dis -_b[trade]/(_b[inter]) .49096606 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 5.90 Prob > chi2 = 0.0522 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is sec2i tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(tye > ar*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sec2i sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 737.42 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .099575 .1551156 0.64 0.521 -.2044461 .4035961 product_10 | -16.31971 8.257871 -1.98 0.048 -32.50484 -.1345821 trade | -11.82593 6.073698 -1.95 0.052 -23.73016 .0783018 inter3 | 20.20558 9.619081 2.10 0.036 1.352525 39.05863 kaopen | -.4252893 .1713967 -2.48 0.013 -.7612206 -.089358 sd_krg | .2909161 .4102436 0.71 0.478 -.5131467 1.094979 sd_fgr | 1.654636 .9720138 1.70 0.089 -.2504764 3.559748 sdtot | .0199207 .0499305 0.40 0.690 -.0779414 .1177827 sdreer2 | -3.51e-07 1.16e-06 -0.30 0.763 -2.63e-06 1.93e-06 sdinfl | .0237587 .0147197 1.61 0.107 -.0050914 .0526087 ncrisis | -.1972313 5.54869 -0.04 0.972 -11.07246 10.678 sec2i | .2604587 .4898527 0.53 0.595 -.6996349 1.220552 tyear2 | -.7190153 .8546783 -0.84 0.400 -2.394154 .9561234 tyear3 | -.1635485 .3840509 -0.43 0.670 -.9162745 .5891775 tyear4 | -.0601072 .4038189 -0.15 0.882 -.8515776 .7313633 tyear5 | .4080521 .6940126 0.59 0.557 -.9521876 1.768292 _cons | 11.01025 5.452799 2.02 0.043 .3229565 21.69754 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.25 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.25 Pr > z = 0.803 Hansen test of overid. restrictions: chi2(38) = 34.39 Prob > chi2 = 0.637 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .5852804 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 4.43 Prob > chi2 = 0.1089 . . * (d) Government expenditure volatility . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis sdgovspen tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2) > ) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdgovspen sdinfl sdreer2 sd_krg kaopen s > dtot sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 991.72 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1676481 .1374351 1.22 0.223 -.1017197 .437016 product_herf | -28.43583 9.954648 -2.86 0.004 -47.94658 -8.925074 trade | -5.111098 2.975702 -1.72 0.086 -10.94337 .7211695 inter1 | 33.8241 11.24027 3.01 0.003 11.79358 55.85461 kaopen | -.3292333 .1642621 -2.00 0.045 -.651181 -.0072855 sd_krg | .284804 .3673755 0.78 0.438 -.4352388 1.004847 sd_fgr | 2.0201 .9572214 2.11 0.035 .1439803 3.896219 sdtot | .0013461 .0369665 0.04 0.971 -.0711069 .0737991 sdreer2 | 8.72e-08 1.10e-06 0.08 0.937 -2.07e-06 2.24e-06 sdinfl | .024426 .0145078 1.68 0.092 -.0040087 .0528608 ncrisis | -2.448558 5.689451 -0.43 0.667 -13.59968 8.702561 sdgovspen | .0106645 .0235203 0.45 0.650 -.0354343 .0567634 tyear2 | -.9523591 .8284121 -1.15 0.250 -2.576017 .6712989 tyear3 | -.1880855 .4011004 -0.47 0.639 -.9742279 .5980569 tyear4 | -.2008813 .3598437 -0.56 0.577 -.9061619 .5043993 tyear5 | .4795661 .5563534 0.86 0.389 -.6108665 1.569999 _cons | 6.822946 2.558816 2.67 0.008 1.807759 11.83813 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.39 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.46 Pr > z = 0.644 Hansen test of overid. restrictions: chi2(38) = 38.37 Prob > chi2 = 0.453 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C7 . dis -_b[trade]/(_b[inter]) .1511082 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 9.29 Prob > chi2 = 0.0096 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s sdgovspen tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(t > year*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdgovspen sdinfl sdreer2 sd_krg kaopen sdtot s > d_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 805.75 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0816876 .1513583 0.54 0.589 -.2149693 .3783444 product_5 | -18.46597 8.408092 -2.20 0.028 -34.94552 -1.986408 trade | -10.75199 5.395796 -1.99 0.046 -21.32756 -.176425 inter2 | 22.53721 9.942491 2.27 0.023 3.050285 42.02413 kaopen | -.3705169 .1719832 -2.15 0.031 -.7075978 -.033436 sd_krg | .1671292 .4335309 0.39 0.700 -.6825758 1.016834 sd_fgr | 1.421192 .991529 1.43 0.152 -.5221692 3.364553 sdtot | -.0036373 .0418591 -0.09 0.931 -.0856796 .078405 sdreer2 | -9.63e-08 1.20e-06 -0.08 0.936 -2.45e-06 2.26e-06 sdinfl | .0244907 .0151042 1.62 0.105 -.005113 .0540944 ncrisis | .2283176 5.258784 0.04 0.965 -10.07871 10.53534 sdgovspen | .0120491 .0230712 0.52 0.601 -.0331696 .0572679 tyear2 | -.5542972 .8823088 -0.63 0.530 -2.283591 1.174996 tyear3 | -.1395413 .3763563 -0.37 0.711 -.8771861 .5981036 tyear4 | -.0271005 .3998823 -0.07 0.946 -.8108554 .7566544 tyear5 | .3706504 .6780613 0.55 0.585 -.9583254 1.699626 _cons | 11.33028 4.638822 2.44 0.015 2.238351 20.4222 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.28 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.18 Pr > z = 0.859 Hansen test of overid. restrictions: chi2(38) = 31.19 Prob > chi2 = 0.775 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C8 . dis -_b[trade]/(_b[inter]) .47707734 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 5.14 Prob > chi2 = 0.0766 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is sdgovspen tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv > (tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdgovspen sdinfl sdreer2 sd_krg kaopen sdtot > sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 766.17 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0759759 .1462416 0.52 0.603 -.2106523 .362604 product_10 | -14.96393 8.107644 -1.85 0.065 -30.85462 .9267639 trade | -10.66089 5.970042 -1.79 0.074 -22.36196 1.040175 inter3 | 18.38172 9.657012 1.90 0.057 -.54568 37.30911 kaopen | -.3667295 .1728479 -2.12 0.034 -.7055051 -.027954 sd_krg | .2132606 .4205812 0.51 0.612 -.6110635 1.037585 sd_fgr | 1.476845 .9653919 1.53 0.126 -.4152883 3.368979 sdtot | .0075341 .0427378 0.18 0.860 -.0762304 .0912986 sdreer2 | -1.18e-07 1.13e-06 -0.10 0.917 -2.34e-06 2.11e-06 sdinfl | .0205616 .0146965 1.40 0.162 -.008243 .0493661 ncrisis | 1.079768 4.918786 0.22 0.826 -8.560876 10.72041 sdgovspen | .0140439 .0218855 0.64 0.521 -.0288509 .0569387 tyear2 | -.5349527 .8625426 -0.62 0.535 -2.225505 1.1556 tyear3 | -.1188847 .3745532 -0.32 0.751 -.8529956 .6152261 tyear4 | -.0299956 .3865907 -0.08 0.938 -.7876995 .7277083 tyear5 | .3552971 .6677789 0.53 0.595 -.9535254 1.66412 _cons | 11.15738 5.07246 2.20 0.028 1.215538 21.09922 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.34 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.26 Pr > z = 0.793 Hansen test of overid. restrictions: chi2(38) = 32.54 Prob > chi2 = 0.720 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .57997264 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 3.65 Prob > chi2 = 0.1613 . . * (e) Natural disaster . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis pyearnatdisas~r tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, la > g(2 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(pyearnatdisas~r sdinfl sdreer2 sd_ > krg kaopen sdtot sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 870.56 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1717902 .1333725 1.29 0.198 -.0896152 .4331956 product_herf | -25.17898 10.32531 -2.44 0.015 -45.41621 -4.941752 trade | -5.203812 3.132994 -1.66 0.097 -11.34437 .9367446 inter1 | 30.02505 11.82281 2.54 0.011 6.852759 53.19734 kaopen | -.3793647 .1674567 -2.27 0.023 -.7075738 -.0511556 sd_krg | .3125561 .3757888 0.83 0.406 -.4239764 1.049089 sd_fgr | 1.843063 .9686579 1.90 0.057 -.0554715 3.741598 sdtot | -.0046497 .0397794 -0.12 0.907 -.0826159 .0733165 sdreer2 | 2.79e-07 1.14e-06 0.24 0.807 -1.96e-06 2.51e-06 sdinfl | .0265633 .0131978 2.01 0.044 .000696 .0524306 ncrisis | -2.723893 5.427783 -0.50 0.616 -13.36215 7.914367 pyearnatdi~r | -3.4499 2.547684 -1.35 0.176 -8.44327 1.543469 tyear2 | -1.105255 .9250036 -1.19 0.232 -2.918229 .7077182 tyear3 | -.3736641 .4625367 -0.81 0.419 -1.280219 .5328912 tyear4 | -.3001328 .4126829 -0.73 0.467 -1.108976 .5087109 tyear5 | .4136436 .5607857 0.74 0.461 -.6854762 1.512763 _cons | 7.261458 2.771395 2.62 0.009 1.829624 12.69329 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.34 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.11 Pr > z = 0.909 Hansen test of overid. restrictions: chi2(38) = 38.05 Prob > chi2 = 0.467 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C9 . dis -_b[trade]/(_b[inter]) .17331568 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 6.50 Prob > chi2 = 0.0387 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s pyearnatdisas~r tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2) > ) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(pyearnatdisas~r sdinfl sdreer2 sd_krg ka > open sdtot sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 843.18 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0711234 .1647273 0.43 0.666 -.2517362 .393983 product_5 | -18.02026 8.246228 -2.19 0.029 -34.18257 -1.857947 trade | -10.66736 5.389951 -1.98 0.048 -21.23147 -.1032524 inter2 | 21.64569 9.531317 2.27 0.023 2.96465 40.32673 kaopen | -.4095282 .1580485 -2.59 0.010 -.7192975 -.0997589 sd_krg | .2217953 .4435543 0.50 0.617 -.6475552 1.091146 sd_fgr | 1.242613 1.061932 1.17 0.242 -.8387369 3.323962 sdtot | .0092993 .0470439 0.20 0.843 -.082905 .1015035 sdreer2 | -4.09e-07 1.33e-06 -0.31 0.758 -3.01e-06 2.19e-06 sdinfl | .0291836 .0160959 1.81 0.070 -.0023638 .060731 ncrisis | -1.078528 4.912304 -0.22 0.826 -10.70647 8.54941 pyearnatdi~r | -1.623554 2.719766 -0.60 0.551 -6.954197 3.707089 tyear2 | -.6065988 .9063722 -0.67 0.503 -2.383056 1.169858 tyear3 | -.3026886 .4771969 -0.63 0.526 -1.237977 .6326002 tyear4 | -.0700051 .4384548 -0.16 0.873 -.9293607 .7893505 tyear5 | .3007045 .7332093 0.41 0.682 -1.136359 1.737768 _cons | 11.55699 4.694771 2.46 0.014 2.355407 20.75857 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.10 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = -0.01 Pr > z = 0.991 Hansen test of overid. restrictions: chi2(38) = 33.30 Prob > chi2 = 0.686 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store C10 . dis -_b[trade]/(_b[inter]) .49281692 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 5.16 Prob > chi2 = 0.0757 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is pyearnatdisas~r tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 > 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(pyearnatdisas~r sdinfl sdreer2 sd_krg > kaopen sdtot sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 738.92 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0492276 .1612318 0.31 0.760 -.2667809 .365236 product_10 | -15.72185 7.972182 -1.97 0.049 -31.34704 -.0966626 trade | -10.67315 5.727565 -1.86 0.062 -21.89897 .5526761 inter3 | 18.97992 9.30984 2.04 0.041 .7329673 37.22687 kaopen | -.3845779 .1593883 -2.41 0.016 -.6969733 -.0721825 sd_krg | .3012287 .4224435 0.71 0.476 -.5267454 1.129203 sd_fgr | 1.316393 1.008174 1.31 0.192 -.6595928 3.292379 sdtot | .0332805 .0473525 0.70 0.482 -.0595286 .1260897 sdreer2 | -8.52e-07 1.28e-06 -0.67 0.506 -3.36e-06 1.66e-06 sdinfl | .027153 .01603 1.69 0.090 -.0042652 .0585712 ncrisis | .2413327 4.596973 0.05 0.958 -8.768569 9.251235 pyearnatdi~r | -.2348328 2.650632 -0.09 0.929 -5.429976 4.96031 tyear2 | -.4998916 .8967163 -0.56 0.577 -2.257423 1.25764 tyear3 | -.2305608 .4684596 -0.49 0.623 -1.148725 .6876032 tyear4 | -.0384467 .4220268 -0.09 0.927 -.8656041 .7887107 tyear5 | .2685449 .6970192 0.39 0.700 -1.097588 1.634677 _cons | 11.30472 4.933557 2.29 0.022 1.635125 20.97431 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.24 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.17 Pr > z = 0.866 Hansen test of overid. restrictions: chi2(38) = 34.28 Prob > chi2 = 0.642 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .56233885 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 4.18 Prob > chi2 = 0.1234 . . /* > * (e) Foreign growth > > xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis mtp_gr tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) i > v(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(mtp_gr sdinfl sdreer2 sd_krg kaopen sdtot s > d_fgr, lag(2 2) collapse) nodiffsargan > estimates store C11 > dis -_b[trade]/(_b[inter]) > test trade inter > xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s mtp_gr tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tyea > r*) gmm(ncrisis, lag(2 2) eq(level)) gmm(mtp_gr sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan > estimates store C12 > dis -_b[trade]/(_b[inter]) > test trade inter > xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is mtp_gr tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(ty > ear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(mtp_gr sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan > dis -_b[trade]/(_b[inter]) > test trade inter > */ . . estout * using "C:\Gazelle\Output\econtrols.tex", replace style(tex) varlabels(_cons Const > ant) cells (b(star fmt(%9.3f)) se(par fmt(%9.2f))) stats (chi2 sargan sarganp ar2 ar2p N, > labels("$\chi^2$" "Sargan" "Sargan p" "AR(2)" "AR(2) p" "N")) starlevels(* 0.10 ** 0.05 ** > * 0.01) & C1 & C2 & C3 & C4 & C5 > & C6 & C7 & C8 & C9 & C10 \\ & b/se & b/se & b/se & b/se & b/se > & b/se & b/se & b/se & b/se & b/se \\ L.std & 0.157 & 0.089 & 0.315** & 0.045 & 0.160 > & 0.097 & 0.168 & 0.082 & 0.172 & 0.071 \\ & (0.13) & (0.16) & (0.13) & (0.17) & (0.12) > & (0.16) & (0.14) & (0.15) & (0.13) & (0.16) \\ product_herf& -23.608***& & -30.613***& & -26.759*** > & & -28.436***& & -25.179** & \\ & (8.87) & & (10.90) & & (8.96) > & & (9.95) & & (10.33) & \\ trade & -4.250 & -10.853** & -6.503* & -11.372 & -4.257 > & -12.018** & -5.111* & -10.752** & -5.204* & -10.667** \\ & (2.88) & (5.09) & (3.93) & (7.28) & (2.79) > & (5.44) & (2.98) & (5.40) & (3.13) & (5.39) \\ inter1 & 28.509***& & 35.616***& & 32.195*** > & & 33.824***& & 30.025** & \\ & (10.46) & & (12.99) & & (10.50) > & & (11.24) & & (11.82) & \\ kaopen & -0.314* & -0.361* & -0.317 & -0.445* & -0.318* > & -0.424** & -0.329** & -0.371** & -0.379** & -0.410***\\ & (0.18) & (0.20) & (0.25) & (0.25) & (0.16) > & (0.18) & (0.16) & (0.17) & (0.17) & (0.16) \\ sd_krg & 0.298 & 0.153 & -0.123 & 0.221 & 0.257 > & 0.184 & 0.285 & 0.167 & 0.313 & 0.222 \\ & (0.38) & (0.44) & (0.39) & (0.41) & (0.35) > & (0.42) & (0.37) & (0.43) & (0.38) & (0.44) \\ sd_fgr & 1.638* & 1.353 & 2.856***& 1.741* & 1.866** > & 1.578 & 2.020** & 1.421 & 1.843* & 1.243 \\ & (0.93) & (0.97) & (0.86) & (1.01) & (0.90) > & (1.00) & (0.96) & (0.99) & (0.97) & (1.06) \\ sdtot & 0.013 & -0.000 & -0.011 & 0.007 & -0.006 > & -0.004 & 0.001 & -0.004 & -0.005 & 0.009 \\ & (0.04) & (0.05) & (0.04) & (0.04) & (0.04) > & (0.05) & (0.04) & (0.04) & (0.04) & (0.05) \\ sdreer2 & -0.000 & -0.000 & 0.000 & 0.000 & -0.000 > & -0.000 & 0.000 & -0.000 & 0.000 & -0.000 \\ & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) > & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) \\ sdinfl & 0.025** & 0.027* & 0.013 & 0.008 & 0.028** > & 0.027* & 0.024* & 0.024 & 0.027** & 0.029* \\ & (0.01) & (0.02) & (0.01) & (0.02) & (0.01) > & (0.01) & (0.01) & (0.02) & (0.01) & (0.02) \\ ncrisis & -1.868 & 0.479 & -1.710 & -1.990 & -1.823 > & -1.040 & -2.449 & 0.228 & -2.724 & -1.079 \\ & (5.35) & (5.78) & (5.79) & (5.65) & (5.66) > & (6.16) & (5.69) & (5.26) & (5.43) & (4.91) \\ lningp & 0.059 & 0.026 & & & > & & & & & \\ & (0.21) & (0.20) & & & > & & & & & \\ tyear2 & -0.688 & -0.536 & -2.367** & -1.244 & -0.822 > & -0.717 & -0.952 & -0.554 & -1.105 & -0.607 \\ & (0.77) & (0.87) & (1.07) & (1.32) & (0.79) > & (0.88) & (0.83) & (0.88) & (0.93) & (0.91) \\ tyear3 & -0.182 & -0.174 & -1.204** & -0.624 & -0.116 > & -0.146 & -0.188 & -0.140 & -0.374 & -0.303 \\ & (0.44) & (0.43) & (0.58) & (0.70) & (0.39) > & (0.39) & (0.40) & (0.38) & (0.46) & (0.48) \\ tyear4 & -0.065 & -0.001 & -1.188** & -0.621 & -0.115 > & -0.028 & -0.201 & -0.027 & -0.300 & -0.070 \\ & (0.34) & (0.39) & (0.53) & (0.67) & (0.34) > & (0.42) & (0.36) & (0.40) & (0.41) & (0.44) \\ tyear5 & 0.378 & 0.365 & & & 0.484 > & 0.467 & 0.480 & 0.371 & 0.414 & 0.301 \\ & (0.57) & (0.71) & & & (0.54) > & (0.71) & (0.56) & (0.68) & (0.56) & (0.73) \\ product_5 & & -18.128** & & -19.638* & > & -19.780** & & -18.466** & & -18.020** \\ & & (9.04) & & (10.41) & > & (8.77) & & (8.41) & & (8.25) \\ inter2 & & 22.466** & & 21.641* & > & 24.479** & & 22.537** & & 21.646** \\ & & (10.28) & & (12.94) & > & (10.13) & & (9.94) & & (9.53) \\ growth2 & & & -0.149 & -0.260 & > & & & & & \\ & & & (0.19) & (0.18) & > & & & & & \\ sec2i & & & & & -0.020 > & 0.226 & & & & \\ & & & & & (0.43) > & (0.44) & & & & \\ sdgovspen & & & & & > & & 0.011 & 0.012 & & \\ & & & & & > & & (0.02) & (0.02) & & \\ pyearnatdisaster& & & & & > & & & & -3.450 & -1.624 \\ & & & & & > & & & & (2.55) & (2.72) \\ Constant & 5.477** & 11.071** & 9.234***& 14.058***& 6.184** > & 11.431** & 6.823***& 11.330** & 7.261***& 11.557** \\ & (2.66) & (4.91) & (3.03) & (5.34) & (2.74) > & (5.07) & (2.56) & (4.64) & (2.77) & (4.69) \\ $\chi^2$ & 941.723 & 886.991 & 640.903 & 466.282 & 1005.925 > & 826.088 & 991.720 & 805.750 & 870.560 & 843.176 \\ Sargan & 42.357 & 33.280 & 25.565 & 22.456 & 39.375 > & 32.070 & 38.368 & 31.190 & 38.051 & 33.298 \\ Sargan p & 0.289 & 0.687 & 0.543 & 0.714 & 0.408 > & 0.739 & 0.453 & 0.775 & 0.467 & 0.686 \\ AR(2) & 0.438 & 0.126 & 0.402 & -0.049 & 0.364 > & 0.121 & 0.462 & 0.178 & 0.114 & -0.012 \\ AR(2) p & 0.662 & 0.900 & 0.688 & 0.961 & 0.716 > & 0.903 & 0.644 & 0.859 & 0.909 & 0.991 \\ N & 302.000 & 302.000 & 238.000 & 238.000 & 302.000 > & 302.000 & 302.000 & 302.000 & 302.000 & 302.000 \\ . estimates clear . . /* Inclusion of additional political economic controls */ . . * (a) Government quality . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis govicrg tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) > iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(govicrg sdinfl sdreer2 sd_krg kaopen sdtot > sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 43 Obs per group: min = 3 Wald chi2(15) = 581.82 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .3429348 .1365444 2.51 0.012 .0753127 .610557 product_herf | -29.12342 10.42432 -2.79 0.005 -49.55471 -8.692136 trade | -5.208049 3.865911 -1.35 0.178 -12.7851 2.368998 inter1 | 33.40954 12.01158 2.78 0.005 9.867278 56.95181 kaopen | -.2816377 .2854135 -0.99 0.324 -.8410379 .2777625 sd_krg | -.1464281 .4003843 -0.37 0.715 -.9311669 .6383106 sd_fgr | 2.785372 .9092066 3.06 0.002 1.003359 4.567384 sdtot | -.00539 .048061 -0.11 0.911 -.0995878 .0888078 sdreer2 | 1.10e-06 1.06e-06 1.04 0.297 -9.70e-07 3.18e-06 sdinfl | .0168441 .0128511 1.31 0.190 -.0083435 .0420317 ncrisis | -1.244852 5.503874 -0.23 0.821 -12.03225 9.542542 govicrg | -.170428 .2350651 -0.73 0.468 -.6311471 .2902911 tyear2 | -2.179245 1.162104 -1.88 0.061 -4.456927 .0984383 tyear3 | -1.170354 .6108403 -1.92 0.055 -2.367579 .0268706 tyear4 | -1.064289 .6046212 -1.76 0.078 -2.249325 .1207472 _cons | 7.851359 2.985371 2.63 0.009 2.00014 13.70258 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.11 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.26 Pr > z = 0.792 Hansen test of overid. restrictions: chi2(27) = 29.78 Prob > chi2 = 0.324 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P1 . dis -_b[trade]/(_b[inter]) .15588506 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 7.86 Prob > chi2 = 0.0196 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s govicrg tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tye > ar*) gmm(ncrisis, lag(2 2) eq(level)) gmm(govicrg sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 43 Obs per group: min = 3 Wald chi2(15) = 472.88 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .2348613 .1994691 1.18 0.239 -.1560909 .6258136 product_5 | -24.27084 9.415567 -2.58 0.010 -42.72501 -5.816665 trade | -15.15103 6.255674 -2.42 0.015 -27.41193 -2.890136 inter2 | 28.06636 11.0136 2.55 0.011 6.480106 49.65262 kaopen | -.2505905 .3544989 -0.71 0.480 -.9453955 .4442146 sd_krg | .0429156 .45582 0.09 0.925 -.8504751 .9363063 sd_fgr | 2.007063 .9609153 2.09 0.037 .1237032 3.890422 sdtot | -.0198041 .0504733 -0.39 0.695 -.1187299 .0791217 sdreer2 | 1.47e-06 1.36e-06 1.08 0.281 -1.20e-06 4.15e-06 sdinfl | .0128073 .0151702 0.84 0.399 -.0169257 .0425403 ncrisis | .2222432 7.121426 0.03 0.975 -13.7355 14.17998 govicrg | -.2829206 .236808 -1.19 0.232 -.7470558 .1812146 tyear2 | -1.248573 1.335298 -0.94 0.350 -3.865708 1.368562 tyear3 | -.7280882 .7215513 -1.01 0.313 -2.142303 .6861264 tyear4 | -.6464469 .6908642 -0.94 0.349 -2.000516 .707622 _cons | 16.19942 4.888987 3.31 0.001 6.617186 25.78166 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.99 Pr > z = 0.003 Arellano-Bond test for AR(2) in first differences: z = 0.13 Pr > z = 0.897 Hansen test of overid. restrictions: chi2(27) = 25.75 Prob > chi2 = 0.532 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P2 . dis -_b[trade]/(_b[inter]) .53982887 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 6.84 Prob > chi2 = 0.0327 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is govicrg tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(t > year*) gmm(ncrisis, lag(2 2) eq(level)) gmm(govicrg sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 43 Obs per group: min = 3 Wald chi2(15) = 470.49 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .2167698 .1923439 1.13 0.260 -.1602174 .593757 product_10 | -22.06545 10.67849 -2.07 0.039 -42.99491 -1.135989 trade | -17.1153 7.788905 -2.20 0.028 -32.38128 -1.849329 inter3 | 24.7939 12.60477 1.97 0.049 .0890057 49.4988 kaopen | -.2080472 .3645791 -0.57 0.568 -.9226091 .5065147 sd_krg | .0852543 .4537846 0.19 0.851 -.8041471 .9746558 sd_fgr | 2.022138 .9134206 2.21 0.027 .2318669 3.81241 sdtot | .0056139 .0472181 0.12 0.905 -.0869318 .0981596 sdreer2 | 1.35e-06 1.33e-06 1.02 0.310 -1.25e-06 3.94e-06 sdinfl | .0080678 .0159276 0.51 0.612 -.0231497 .0392854 ncrisis | 1.290175 6.758117 0.19 0.849 -11.95549 14.53584 govicrg | -.337307 .2199528 -1.53 0.125 -.7684066 .0937927 tyear2 | -1.123861 1.297328 -0.87 0.386 -3.666577 1.418855 tyear3 | -.7338627 .7075692 -1.04 0.300 -2.120673 .6529474 tyear4 | -.608311 .6694832 -0.91 0.364 -1.920474 .7038519 _cons | 18.11083 6.205087 2.92 0.004 5.949087 30.27258 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.79 Pr > z = 0.005 Arellano-Bond test for AR(2) in first differences: z = 0.16 Pr > z = 0.870 Hansen test of overid. restrictions: chi2(27) = 24.57 Prob > chi2 = 0.599 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .69030286 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 4.83 Prob > chi2 = 0.0894 . . * (b) Institutional quality . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis qinst tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) iv > (tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(qinst sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 286 Time variable : period Number of groups = 71 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 97.32 avg = 4.03 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1461624 .116922 1.25 0.211 -.0830005 .3753254 product_herf | -32.04223 12.89005 -2.49 0.013 -57.30626 -6.778201 trade | -3.763504 2.887534 -1.30 0.192 -9.422967 1.895958 inter1 | 36.39268 14.59527 2.49 0.013 7.786471 64.99889 kaopen | -.1310741 .2446129 -0.54 0.592 -.6105067 .3483584 sd_krg | .3839903 .3614652 1.06 0.288 -.3244686 1.092449 sd_fgr | 1.354178 .9845183 1.38 0.169 -.5754423 3.283798 sdtot | .0330223 .0494659 0.67 0.504 -.0639292 .1299737 sdreer2 | .010655 .0209891 0.51 0.612 -.0304829 .0517929 sdinfl | .026382 .0141329 1.87 0.062 -.0013179 .0540819 ncrisis | -5.641052 5.067226 -1.11 0.266 -15.57263 4.290528 qinst | -.4190892 .4756105 -0.88 0.378 -1.351269 .5130903 tyear2 | -.5012298 .8220437 -0.61 0.542 -2.112406 1.109946 tyear3 | -.1906979 .4142194 -0.46 0.645 -1.002553 .6211573 tyear4 | .1405242 .3633352 0.39 0.699 -.5715997 .852648 tyear5 | .3433147 .5816356 0.59 0.555 -.79667 1.483299 _cons | 8.026793 3.735309 2.15 0.032 .7057224 15.34786 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.21 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.25 Pr > z = 0.805 Hansen test of overid. restrictions: chi2(38) = 37.07 Prob > chi2 = 0.512 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P3 . dis -_b[trade]/(_b[inter]) .10341377 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 6.25 Prob > chi2 = 0.0440 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s qinst tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tyear > *) gmm(ncrisis, lag(2 2) eq(level)) gmm(qinst sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, l > ag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 286 Time variable : period Number of groups = 71 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 46.05 avg = 4.03 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0305411 .1380668 0.22 0.825 -.2400648 .3011471 product_5 | -11.90338 9.008115 -1.32 0.186 -29.55896 5.752197 trade | -5.177671 5.122709 -1.01 0.312 -15.218 4.862655 inter2 | 13.20816 10.65365 1.24 0.215 -7.672614 34.08893 kaopen | -.0852573 .2536955 -0.34 0.737 -.5824913 .4119767 sd_krg | .3463343 .4285311 0.81 0.419 -.4935712 1.18624 sd_fgr | .9796269 1.10602 0.89 0.376 -1.188133 3.147387 sdtot | .0385983 .0549866 0.70 0.483 -.0691735 .14637 sdreer2 | .0104044 .0215643 0.48 0.629 -.0318609 .0526697 sdinfl | .0273686 .0152059 1.80 0.072 -.0024345 .0571717 ncrisis | -2.006151 4.052919 -0.49 0.621 -9.949726 5.937424 qinst | -.5804568 .5294956 -1.10 0.273 -1.618249 .4573354 tyear2 | -.2332289 .9104434 -0.26 0.798 -2.017665 1.551207 tyear3 | -.1869967 .3863257 -0.48 0.628 -.9441812 .5701877 tyear4 | .2482822 .384294 0.65 0.518 -.5049203 1.001485 tyear5 | .2727283 .6725554 0.41 0.685 -1.045456 1.590913 _cons | 10.51019 5.662673 1.86 0.063 -.5884456 21.60883 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.91 Pr > z = 0.004 Arellano-Bond test for AR(2) in first differences: z = 0.16 Pr > z = 0.875 Hansen test of overid. restrictions: chi2(38) = 38.33 Prob > chi2 = 0.455 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P4 . dis -_b[trade]/(_b[inter]) .39200558 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 1.55 Prob > chi2 = 0.4604 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is qinst tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(tye > ar*) gmm(ncrisis, lag(2 2) eq(level)) gmm(qinst sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 286 Time variable : period Number of groups = 71 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 51.22 avg = 4.03 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0152289 .138595 0.11 0.913 -.2564124 .2868702 product_10 | -10.14728 8.877244 -1.14 0.253 -27.54636 7.251796 trade | -4.854534 5.88211 -0.83 0.409 -16.38326 6.67419 inter3 | 11.08586 10.71945 1.03 0.301 -9.923874 32.09559 kaopen | -.0635795 .2520464 -0.25 0.801 -.5575814 .4304224 sd_krg | .4162469 .3945962 1.05 0.291 -.3571473 1.189641 sd_fgr | .9071355 1.064419 0.85 0.394 -1.179087 2.993358 sdtot | .0554332 .0581592 0.95 0.341 -.0585567 .1694231 sdreer2 | .008482 .0230097 0.37 0.712 -.0366162 .0535802 sdinfl | .0240059 .0145315 1.65 0.099 -.0044753 .0524872 ncrisis | -.297366 3.993069 -0.07 0.941 -8.123638 7.528906 qinst | -.582567 .531296 -1.10 0.273 -1.623888 .458754 tyear2 | -.1599477 .8903949 -0.18 0.857 -1.90509 1.585194 tyear3 | -.1637235 .3851974 -0.43 0.671 -.9186965 .5912495 tyear4 | .2540348 .3986938 0.64 0.524 -.5273907 1.03546 tyear5 | .1783498 .6190533 0.29 0.773 -1.034972 1.391672 _cons | 10.28812 5.955204 1.73 0.084 -1.383866 21.9601 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.89 Pr > z = 0.004 Arellano-Bond test for AR(2) in first differences: z = 0.29 Pr > z = 0.774 Hansen test of overid. restrictions: chi2(38) = 41.11 Prob > chi2 = 0.336 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .43790322 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 1.14 Prob > chi2 = 0.5669 . . * (c) Political volatility . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis pcrisis tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) > iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(pcrisis sdinfl sdreer2 sd_krg kaopen sdtot > sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(16) = 1018.76 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1908067 .12988 1.47 0.142 -.0637535 .4453669 product_herf | -26.49397 9.756285 -2.72 0.007 -45.61594 -7.372005 trade | -4.854842 2.906565 -1.67 0.095 -10.55161 .8419212 inter1 | 31.8255 11.33447 2.81 0.005 9.610354 54.04065 kaopen | -.3371901 .1675298 -2.01 0.044 -.6655424 -.0088378 sd_krg | .2747947 .3637393 0.76 0.450 -.4381211 .9877106 sd_fgr | 1.984562 .9697922 2.05 0.041 .0838044 3.88532 sdtot | -.006627 .0369723 -0.18 0.858 -.0790914 .0658374 sdreer2 | 1.92e-07 1.03e-06 0.19 0.853 -1.84e-06 2.22e-06 sdinfl | .0262267 .0124532 2.11 0.035 .0018188 .0506345 ncrisis | -2.960873 5.506864 -0.54 0.591 -13.75413 7.832382 pcrisis | -1.850971 2.333719 -0.79 0.428 -6.424975 2.723033 tyear2 | -.9108198 .8352123 -1.09 0.275 -2.547806 .7261663 tyear3 | -.1673432 .3865167 -0.43 0.665 -.9249019 .5902155 tyear4 | -.1653671 .3651064 -0.45 0.651 -.8809625 .5502284 tyear5 | .5278979 .5605955 0.94 0.346 -.570849 1.626645 _cons | 6.624032 2.531379 2.62 0.009 1.66262 11.58544 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.38 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.45 Pr > z = 0.652 Hansen test of overid. restrictions: chi2(36) = 36.42 Prob > chi2 = 0.449 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P5 . dis -_b[trade]/(_b[inter]) .15254565 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 7.97 Prob > chi2 = 0.0186 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s pcrisis tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tye > ar*) gmm(ncrisis, lag(2 2) eq(level)) gmm(pcrisis sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(16) = 820.53 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1076856 .1756939 0.61 0.540 -.2366681 .4520393 product_5 | -20.32431 8.746661 -2.32 0.020 -37.46745 -3.181175 trade | -11.85277 5.381923 -2.20 0.028 -22.40114 -1.304394 inter2 | 24.82392 10.05317 2.47 0.014 5.120061 44.52778 kaopen | -.384803 .1761575 -2.18 0.029 -.7300653 -.0395407 sd_krg | .1756758 .4362409 0.40 0.687 -.6793408 1.030692 sd_fgr | 1.490136 1.012083 1.47 0.141 -.4935102 3.473782 sdtot | -.0058213 .0519859 -0.11 0.911 -.1077118 .0960693 sdreer2 | -9.94e-09 1.31e-06 -0.01 0.994 -2.57e-06 2.55e-06 sdinfl | .0259505 .0144388 1.80 0.072 -.0023491 .0542501 ncrisis | -.0662686 5.291081 -0.01 0.990 -10.4366 10.30406 pcrisis | -.9395194 3.099547 -0.30 0.762 -7.014521 5.135482 tyear2 | -.628889 .8822042 -0.71 0.476 -2.357977 1.1002 tyear3 | -.1664841 .4018656 -0.41 0.679 -.9541262 .621158 tyear4 | -.0520103 .4080137 -0.13 0.899 -.8517025 .747682 tyear5 | .4026655 .7073747 0.57 0.569 -.9837635 1.789094 _cons | 12.27698 4.597787 2.67 0.008 3.265484 21.28848 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.10 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.14 Pr > z = 0.892 Hansen test of overid. restrictions: chi2(36) = 32.52 Prob > chi2 = 0.635 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P6 . dis -_b[trade]/(_b[inter]) .47747363 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 6.10 Prob > chi2 = 0.0473 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is pcrisis tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(t > year*) gmm(ncrisis, lag(2 2) eq(level)) gmm(pcrisis sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(16) = 758.26 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0878737 .1670456 0.53 0.599 -.2395297 .415277 product_10 | -17.18981 8.494021 -2.02 0.043 -33.83778 -.5418305 trade | -12.1003 6.041716 -2.00 0.045 -23.94184 -.2587526 inter3 | 21.10381 9.831642 2.15 0.032 1.834145 40.37347 kaopen | -.3641249 .1772405 -2.05 0.040 -.7115098 -.01674 sd_krg | .259561 .4191067 0.62 0.536 -.5618731 1.080995 sd_fgr | 1.481492 .9848998 1.50 0.133 -.448876 3.41186 sdtot | .0175973 .0518603 0.34 0.734 -.084047 .1192416 sdreer2 | -2.83e-07 1.21e-06 -0.23 0.815 -2.66e-06 2.09e-06 sdinfl | .0221164 .0145267 1.52 0.128 -.0063554 .0505883 ncrisis | 1.870399 5.010709 0.37 0.709 -7.95041 11.69121 pcrisis | -.4653822 3.394717 -0.14 0.891 -7.118905 6.18814 tyear2 | -.5730956 .8620109 -0.66 0.506 -2.262606 1.116415 tyear3 | -.1753373 .4022725 -0.44 0.663 -.9637768 .6131023 tyear4 | -.0664921 .3921878 -0.17 0.865 -.8351661 .702182 tyear5 | .3117654 .6925474 0.45 0.653 -1.045603 1.669133 _cons | 12.31296 5.108097 2.41 0.016 2.301279 22.32465 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.13 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.19 Pr > z = 0.847 Hansen test of overid. restrictions: chi2(36) = 34.43 Prob > chi2 = 0.543 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .57337037 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 4.63 Prob > chi2 = 0.0988 . . * (d) Conflict . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis war tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) iv(t > year*) gmm(ncrisis, lag(2 2) eq(level)) gmm(war sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 850.07 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1392634 .1287005 1.08 0.279 -.112985 .3915118 product_herf | -25.01781 10.16848 -2.46 0.014 -44.94767 -5.087955 trade | -4.855949 2.859838 -1.70 0.090 -10.46113 .7492299 inter1 | 29.46313 11.74197 2.51 0.012 6.449286 52.47697 kaopen | -.317706 .1732353 -1.83 0.067 -.657241 .0218289 sd_krg | .2611364 .4203304 0.62 0.534 -.5626961 1.084969 sd_fgr | 2.107496 .9211578 2.29 0.022 .3020599 3.912932 sdtot | .0342401 .0448887 0.76 0.446 -.0537401 .1222203 sdreer2 | -1.12e-06 1.32e-06 -0.85 0.397 -3.70e-06 1.47e-06 sdinfl | .0202131 .0122134 1.65 0.098 -.0037248 .044151 ncrisis | -3.850656 5.203866 -0.74 0.459 -14.05005 6.348734 war | 2.471935 2.17663 1.14 0.256 -1.794181 6.73805 tyear2 | -1.14904 .7926414 -1.45 0.147 -2.702588 .4045087 tyear3 | -.3831453 .4194654 -0.91 0.361 -1.205282 .4389917 tyear4 | -.2152898 .3517545 -0.61 0.541 -.9047159 .4741363 tyear5 | .5317335 .5854014 0.91 0.364 -.6156321 1.679099 _cons | 6.657603 2.454512 2.71 0.007 1.846849 11.46836 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.50 Pr > z = 0.000 Arellano-Bond test for AR(2) in first differences: z = 0.12 Pr > z = 0.902 Hansen test of overid. restrictions: chi2(38) = 41.20 Prob > chi2 = 0.332 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P7 . dis -_b[trade]/(_b[inter]) .16481447 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 6.42 Prob > chi2 = 0.0403 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s war tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(tyear*) > gmm(ncrisis, lag(2 2) eq(level)) gmm(war sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag(2 > 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 725.48 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .068331 .1511564 0.45 0.651 -.2279301 .3645921 product_5 | -16.00248 7.924658 -2.02 0.043 -31.53452 -.4704342 trade | -9.428943 4.836306 -1.95 0.051 -18.90793 .0500431 inter2 | 19.09127 9.124828 2.09 0.036 1.206934 36.9756 kaopen | -.3296441 .1856751 -1.78 0.076 -.6935606 .0342724 sd_krg | .3095292 .4626741 0.67 0.503 -.5972953 1.216354 sd_fgr | 1.442039 1.027162 1.40 0.160 -.5711619 3.455239 sdtot | .0365923 .0514753 0.71 0.477 -.0642974 .137482 sdreer2 | -1.11e-06 1.28e-06 -0.86 0.388 -3.62e-06 1.40e-06 sdinfl | .0207743 .0144891 1.43 0.152 -.0076239 .0491725 ncrisis | -.2640639 4.897277 -0.05 0.957 -9.86255 9.334422 war | 1.618722 1.845446 0.88 0.380 -1.998285 5.23573 tyear2 | -.6210293 .8820868 -0.70 0.481 -2.349888 1.107829 tyear3 | -.2764901 .3686918 -0.75 0.453 -.9991127 .4461325 tyear4 | -.067824 .3915949 -0.17 0.862 -.8353358 .6996879 tyear5 | .2931537 .7155933 0.41 0.682 -1.109383 1.695691 _cons | 10.3129 4.173529 2.47 0.013 2.132936 18.49287 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.23 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.05 Pr > z = 0.963 Hansen test of overid. restrictions: chi2(38) = 34.93 Prob > chi2 = 0.612 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P8 . dis -_b[trade]/(_b[inter]) .49388777 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 4.51 Prob > chi2 = 0.1049 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is war tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv(tyear > *) gmm(ncrisis, lag(2 2) eq(level)) gmm(war sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, lag > (2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 659.96 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0712779 .1512527 0.47 0.637 -.2251719 .3677277 product_10 | -14.33125 8.012463 -1.79 0.074 -30.03539 1.372888 trade | -10.18494 5.571751 -1.83 0.068 -21.10537 .7354885 inter3 | 17.10809 9.2615 1.85 0.065 -1.044114 35.2603 kaopen | -.3100985 .1856396 -1.67 0.095 -.6739454 .0537483 sd_krg | .4106517 .4452101 0.92 0.356 -.461944 1.283247 sd_fgr | 1.404825 .9877211 1.42 0.155 -.5310731 3.340722 sdtot | .0545514 .0493173 1.11 0.269 -.0421087 .1512114 sdreer2 | -1.15e-06 1.16e-06 -1.00 0.319 -3.42e-06 1.11e-06 sdinfl | .015899 .0148413 1.07 0.284 -.0131895 .0449874 ncrisis | 1.852172 4.634271 0.40 0.689 -7.230834 10.93518 war | 1.447921 1.877912 0.77 0.441 -2.232718 5.12856 tyear2 | -.5453039 .855352 -0.64 0.524 -2.221763 1.131155 tyear3 | -.2870265 .367575 -0.78 0.435 -1.00746 .4334072 tyear4 | -.0990207 .3850808 -0.26 0.797 -.8537652 .6557237 tyear5 | .1682186 .6881656 0.24 0.807 -1.180561 1.516998 _cons | 10.80406 4.777833 2.26 0.024 1.439678 20.16844 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.19 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.18 Pr > z = 0.856 Hansen test of overid. restrictions: chi2(38) = 37.00 Prob > chi2 = 0.516 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .59532895 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 3.59 Prob > chi2 = 0.1658 . . * (e) Assassinations . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis assassin tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag(2 2)) > iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(assassin sdinfl sdreer2 sd_krg kaopen sdt > ot sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 1018.06 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1644238 .124254 1.32 0.186 -.0791096 .4079572 product_herf | -26.09684 9.611296 -2.72 0.007 -44.93464 -7.259047 trade | -5.278096 3.180341 -1.66 0.097 -11.51145 .9552583 inter1 | 31.45612 11.15061 2.82 0.005 9.60132 53.31093 kaopen | -.3301985 .1648783 -2.00 0.045 -.6533541 -.007043 sd_krg | .3222589 .3571118 0.90 0.367 -.3776674 1.022185 sd_fgr | 1.513565 .848961 1.78 0.075 -.1503682 3.177498 sdtot | -.0104035 .0361764 -0.29 0.774 -.0813079 .0605009 sdreer2 | -4.38e-08 1.05e-06 -0.04 0.967 -2.11e-06 2.02e-06 sdinfl | .0273889 .0128585 2.13 0.033 .0021868 .0525911 ncrisis | -1.898641 5.932783 -0.32 0.749 -13.52668 9.7294 assassin | -.1218497 .2160174 -0.56 0.573 -.5452361 .3015367 tyear2 | -.6302542 .7558738 -0.83 0.404 -2.11174 .8512312 tyear3 | -.1688707 .3839987 -0.44 0.660 -.9214942 .5837529 tyear4 | -.0702457 .3513112 -0.20 0.842 -.758803 .6183116 tyear5 | .3304119 .5504744 0.60 0.548 -.748498 1.409322 _cons | 6.92407 2.692393 2.57 0.010 1.647077 12.20106 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.32 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.39 Pr > z = 0.698 Hansen test of overid. restrictions: chi2(38) = 40.49 Prob > chi2 = 0.361 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P9 . dis -_b[trade]/(_b[inter]) .16779234 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 8.12 Prob > chi2 = 0.0173 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s assassin tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) iv(ty > ear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(assassin sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 729.44 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0683273 .1567943 0.44 0.663 -.2389838 .3756385 product_5 | -20.92699 8.755876 -2.39 0.017 -38.08819 -3.765784 trade | -11.97177 5.464312 -2.19 0.028 -22.68163 -1.261919 inter2 | 25.36454 10.08943 2.51 0.012 5.589621 45.13946 kaopen | -.38378 .1904028 -2.02 0.044 -.7569626 -.0105975 sd_krg | .2891023 .439941 0.66 0.511 -.5731662 1.151371 sd_fgr | 1.175159 .9259135 1.27 0.204 -.6395983 2.989916 sdtot | -.0013061 .0487985 -0.03 0.979 -.0969493 .0943371 sdreer2 | 2.56e-08 1.29e-06 0.02 0.984 -2.51e-06 2.56e-06 sdinfl | .0231309 .0138726 1.67 0.095 -.0040588 .0503207 ncrisis | .2514468 5.977796 0.04 0.966 -11.46482 11.96771 assassin | .2055191 .3247625 0.63 0.527 -.4310038 .8420419 tyear2 | -.3895643 .8119495 -0.48 0.631 -1.980956 1.201828 tyear3 | -.128196 .3932258 -0.33 0.744 -.8989043 .6425124 tyear4 | -.0516048 .4243046 -0.12 0.903 -.8832265 .7800168 tyear5 | .2336165 .686002 0.34 0.733 -1.110923 1.578156 _cons | 12.37785 4.632735 2.67 0.008 3.297855 21.45784 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.25 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.06 Pr > z = 0.952 Hansen test of overid. restrictions: chi2(38) = 32.79 Prob > chi2 = 0.709 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store P10 . dis -_b[trade]/(_b[inter]) .47198856 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 6.32 Prob > chi2 = 0.0424 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is assassin tyear*, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2)) iv( > tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(assassin sdinfl sdreer2 sd_krg kaopen sdtot s > d_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 302 Time variable : period Number of groups = 76 Number of instruments = 55 Obs per group: min = 1 Wald chi2(16) = 730.99 avg = 3.97 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0465431 .1526621 0.30 0.760 -.2526691 .3457553 product_10 | -19.09521 8.469009 -2.25 0.024 -35.69416 -2.496258 trade | -12.70604 6.130145 -2.07 0.038 -24.7209 -.6911756 inter3 | 22.89028 9.864232 2.32 0.020 3.556738 42.22382 kaopen | -.3737275 .1901482 -1.97 0.049 -.7464111 -.0010439 sd_krg | .3932161 .4274607 0.92 0.358 -.4445914 1.231024 sd_fgr | 1.277069 .9255895 1.38 0.168 -.5370526 3.091192 sdtot | .0333335 .0463409 0.72 0.472 -.057493 .1241601 sdreer2 | -2.65e-07 1.16e-06 -0.23 0.819 -2.54e-06 2.01e-06 sdinfl | .0181213 .0137929 1.31 0.189 -.0089122 .0451548 ncrisis | 1.830851 5.537722 0.33 0.741 -9.022886 12.68459 assassin | .2943868 .357705 0.82 0.411 -.406702 .9954756 tyear2 | -.4139989 .8100478 -0.51 0.609 -2.001663 1.173666 tyear3 | -.1698923 .3896914 -0.44 0.663 -.9336734 .5938889 tyear4 | -.1236554 .4226476 -0.29 0.770 -.9520295 .7047187 tyear5 | .151869 .6683765 0.23 0.820 -1.158125 1.461863 _cons | 12.96494 5.170342 2.51 0.012 2.831257 23.09863 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.19 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.11 Pr > z = 0.916 Hansen test of overid. restrictions: chi2(38) = 34.14 Prob > chi2 = 0.648 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .55508447 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 5.38 Prob > chi2 = 0.0677 . . estout * using "C:\Gazelle\Output\pcontrols.tex", replace style(tex) varlabels(_cons Const > ant) cells (b(star fmt(%9.3f)) se(par fmt(%9.2f))) stats (r2 r2_a chi2 sargan sarganp ar2 > ar2p N, labels("R$^2$" "Adjusted R$^2$" "$\chi^2$" "Sargan" "Sargan p" "AR(2)" "AR(2) p" " > N")) starlevels(* 0.10 ** 0.05 *** 0.01) & P1 & P2 & P3 & P4 & P5 > & P6 & P7 & P8 & P9 & P10 \\ & b/se & b/se & b/se & b/se & b/se > & b/se & b/se & b/se & b/se & b/se \\ L.std & 0.343** & 0.235 & 0.146 & 0.031 & 0.191 > & 0.108 & 0.139 & 0.068 & 0.164 & 0.068 \\ & (0.14) & (0.20) & (0.12) & (0.14) & (0.13) > & (0.18) & (0.13) & (0.15) & (0.12) & (0.16) \\ product_herf& -29.123***& & -32.042** & & -26.494*** > & & -25.018** & & -26.097***& \\ & (10.42) & & (12.89) & & (9.76) > & & (10.17) & & (9.61) & \\ trade & -5.208 & -15.151** & -3.764 & -5.178 & -4.855* > & -11.853** & -4.856* & -9.429* & -5.278* & -11.972** \\ & (3.87) & (6.26) & (2.89) & (5.12) & (2.91) > & (5.38) & (2.86) & (4.84) & (3.18) & (5.46) \\ inter1 & 33.410***& & 36.393** & & 31.826*** > & & 29.463** & & 31.456***& \\ & (12.01) & & (14.60) & & (11.33) > & & (11.74) & & (11.15) & \\ kaopen & -0.282 & -0.251 & -0.131 & -0.085 & -0.337** > & -0.385** & -0.318* & -0.330* & -0.330** & -0.384** \\ & (0.29) & (0.35) & (0.24) & (0.25) & (0.17) > & (0.18) & (0.17) & (0.19) & (0.16) & (0.19) \\ sd_krg & -0.146 & 0.043 & 0.384 & 0.346 & 0.275 > & 0.176 & 0.261 & 0.310 & 0.322 & 0.289 \\ & (0.40) & (0.46) & (0.36) & (0.43) & (0.36) > & (0.44) & (0.42) & (0.46) & (0.36) & (0.44) \\ sd_fgr & 2.785***& 2.007** & 1.354 & 0.980 & 1.985** > & 1.490 & 2.107** & 1.442 & 1.514* & 1.175 \\ & (0.91) & (0.96) & (0.98) & (1.11) & (0.97) > & (1.01) & (0.92) & (1.03) & (0.85) & (0.93) \\ sdtot & -0.005 & -0.020 & 0.033 & 0.039 & -0.007 > & -0.006 & 0.034 & 0.037 & -0.010 & -0.001 \\ & (0.05) & (0.05) & (0.05) & (0.05) & (0.04) > & (0.05) & (0.04) & (0.05) & (0.04) & (0.05) \\ sdreer2 & 0.000 & 0.000 & 0.011 & 0.010 & 0.000 > & -0.000 & -0.000 & -0.000 & -0.000 & 0.000 \\ & (0.00) & (0.00) & (0.02) & (0.02) & (0.00) > & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) \\ sdinfl & 0.017 & 0.013 & 0.026* & 0.027* & 0.026** > & 0.026* & 0.020* & 0.021 & 0.027** & 0.023* \\ & (0.01) & (0.02) & (0.01) & (0.02) & (0.01) > & (0.01) & (0.01) & (0.01) & (0.01) & (0.01) \\ ncrisis & -1.245 & 0.222 & -5.641 & -2.006 & -2.961 > & -0.066 & -3.851 & -0.264 & -1.899 & 0.251 \\ & (5.50) & (7.12) & (5.07) & (4.05) & (5.51) > & (5.29) & (5.20) & (4.90) & (5.93) & (5.98) \\ govicrg & -0.170 & -0.283 & & & > & & & & & \\ & (0.24) & (0.24) & & & > & & & & & \\ tyear2 & -2.179* & -1.249 & -0.501 & -0.233 & -0.911 > & -0.629 & -1.149 & -0.621 & -0.630 & -0.390 \\ & (1.16) & (1.34) & (0.82) & (0.91) & (0.84) > & (0.88) & (0.79) & (0.88) & (0.76) & (0.81) \\ tyear3 & -1.170* & -0.728 & -0.191 & -0.187 & -0.167 > & -0.166 & -0.383 & -0.276 & -0.169 & -0.128 \\ & (0.61) & (0.72) & (0.41) & (0.39) & (0.39) > & (0.40) & (0.42) & (0.37) & (0.38) & (0.39) \\ tyear4 & -1.064* & -0.646 & 0.141 & 0.248 & -0.165 > & -0.052 & -0.215 & -0.068 & -0.070 & -0.052 \\ & (0.60) & (0.69) & (0.36) & (0.38) & (0.37) > & (0.41) & (0.35) & (0.39) & (0.35) & (0.42) \\ product_5 & & -24.271***& & -11.903 & > & -20.324** & & -16.002** & & -20.927** \\ & & (9.42) & & (9.01) & > & (8.75) & & (7.92) & & (8.76) \\ inter2 & & 28.066** & & 13.208 & > & 24.824** & & 19.091** & & 25.365** \\ & & (11.01) & & (10.65) & > & (10.05) & & (9.12) & & (10.09) \\ qinst & & & -0.419 & -0.580 & > & & & & & \\ & & & (0.48) & (0.53) & > & & & & & \\ tyear5 & & & 0.343 & 0.273 & 0.528 > & 0.403 & 0.532 & 0.293 & 0.330 & 0.234 \\ & & & (0.58) & (0.67) & (0.56) > & (0.71) & (0.59) & (0.72) & (0.55) & (0.69) \\ pcrisis & & & & & -1.851 > & -0.940 & & & & \\ & & & & & (2.33) > & (3.10) & & & & \\ war & & & & & > & & 2.472 & 1.619 & & \\ & & & & & > & & (2.18) & (1.85) & & \\ assassin & & & & & > & & & & -0.122 & 0.206 \\ & & & & & > & & & & (0.22) & (0.32) \\ Constant & 7.851***& 16.199***& 8.027** & 10.510* & 6.624*** > & 12.277***& 6.658***& 10.313** & 6.924** & 12.378***\\ & (2.99) & (4.89) & (3.74) & (5.66) & (2.53) > & (4.60) & (2.45) & (4.17) & (2.69) & (4.63) \\ R$^2$ & & & & & > & & & & & \\ Adjusted R$^2$& & & & & > & & & & & \\ $\chi^2$ & 581.818 & 472.883 & 97.317 & 46.052 & 1018.760 > & 820.530 & 850.067 & 725.483 & 1018.058 & 729.437 \\ Sargan & 29.776 & 25.755 & 37.067 & 38.329 & 36.424 > & 32.517 & 41.199 & 34.925 & 40.490 & 32.788 \\ Sargan p & 0.324 & 0.532 & 0.512 & 0.455 & 0.449 > & 0.635 & 0.332 & 0.612 & 0.361 & 0.709 \\ AR(2) & 0.264 & 0.130 & 0.246 & 0.158 & 0.451 > & 0.135 & 0.123 & 0.046 & 0.388 & 0.060 \\ AR(2) p & 0.792 & 0.897 & 0.805 & 0.875 & 0.652 > & 0.892 & 0.902 & 0.963 & 0.698 & 0.952 \\ N & 238.000 & 238.000 & 286.000 & 286.000 & 302.000 > & 302.000 & 302.000 & 302.000 & 302.000 & 302.000 \\ . estimates clear . . /* Subsample analysis */ . . * (a) Without final period . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis tyear* if period < 6, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag( > 2 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot s > d_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 41 Obs per group: min = 3 Wald chi2(14) = 587.50 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .3287327 .1284387 2.56 0.010 .0769975 .580468 product_herf | -29.44677 11.22576 -2.62 0.009 -51.44886 -7.444679 trade | -7.407467 3.776585 -1.96 0.050 -14.80944 -.0054954 inter1 | 34.60444 13.264 2.61 0.009 8.607482 60.6014 kaopen | -.4072548 .2681642 -1.52 0.129 -.9328471 .1183375 sd_krg | -.2811277 .4135301 -0.68 0.497 -1.091632 .5293764 sd_fgr | 2.938135 .9227107 3.18 0.001 1.129656 4.746615 sdtot | -.0132398 .0506486 -0.26 0.794 -.1125091 .0860296 sdreer2 | 1.33e-06 1.23e-06 1.09 0.277 -1.07e-06 3.73e-06 sdinfl | .0165221 .0147564 1.12 0.263 -.0123998 .0454441 ncrisis | -1.11911 5.641748 -0.20 0.843 -12.17673 9.938513 tyear2 | -2.63675 1.139854 -2.31 0.021 -4.870822 -.4026782 tyear3 | -1.461048 .5771719 -2.53 0.011 -2.592284 -.3298117 tyear4 | -1.28766 .5832139 -2.21 0.027 -2.430738 -.144582 _cons | 9.847616 3.092965 3.18 0.001 3.785516 15.90972 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.03 Pr > z = 0.002 Arellano-Bond test for AR(2) in first differences: z = 0.47 Pr > z = 0.639 Hansen test of overid. restrictions: chi2(26) = 24.86 Prob > chi2 = 0.527 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S1 . dis -_b[trade]/(_b[inter]) .21406115 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 7.04 Prob > chi2 = 0.0296 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s tyear* if period < 6, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) > iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 41 Obs per group: min = 3 Wald chi2(14) = 463.12 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1260052 .1686921 0.75 0.455 -.2046253 .4566357 product_5 | -18.4955 11.93311 -1.55 0.121 -41.88397 4.892958 trade | -13.54746 7.540808 -1.80 0.072 -28.32717 1.232254 inter2 | 21.80528 14.33765 1.52 0.128 -6.296002 49.90656 kaopen | -.5362475 .3010881 -1.78 0.075 -1.126369 .0538742 sd_krg | -.1639948 .4622723 -0.35 0.723 -1.070032 .7420422 sd_fgr | 2.145681 1.086898 1.97 0.048 .0154005 4.275961 sdtot | -.0158953 .053703 -0.30 0.767 -.1211513 .0893608 sdreer2 | 1.21e-06 1.52e-06 0.80 0.425 -1.76e-06 4.18e-06 sdinfl | .0157304 .0160871 0.98 0.328 -.0157998 .0472606 ncrisis | -1.269901 6.601452 -0.19 0.847 -14.20851 11.66871 tyear2 | -1.969596 1.440739 -1.37 0.172 -4.793393 .8542 tyear3 | -1.184129 .7368752 -1.61 0.108 -2.628378 .2601196 tyear4 | -.9464423 .7788541 -1.22 0.224 -2.472968 .5800838 _cons | 15.20967 5.735566 2.65 0.008 3.96817 26.45117 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.82 Pr > z = 0.005 Arellano-Bond test for AR(2) in first differences: z = 0.27 Pr > z = 0.789 Hansen test of overid. restrictions: chi2(26) = 21.80 Prob > chi2 = 0.700 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S2 . dis -_b[trade]/(_b[inter]) .62129257 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 3.23 Prob > chi2 = 0.1986 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is tyear* if period < 6, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2) > ) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity tyear5 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 238 Time variable : period Number of groups = 73 Number of instruments = 41 Obs per group: min = 3 Wald chi2(14) = 417.66 avg = 3.26 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1065502 .1729583 0.62 0.538 -.2324418 .4455422 product_10 | -12.69634 11.29553 -1.12 0.261 -34.83516 9.44249 trade | -12.24816 8.367347 -1.46 0.143 -28.64785 4.151543 inter3 | 14.4791 13.88365 1.04 0.297 -12.73236 41.69056 kaopen | -.5142668 .298017 -1.73 0.084 -1.098369 .0698357 sd_krg | -.1341765 .4297459 -0.31 0.755 -.9764629 .70811 sd_fgr | 2.075146 1.014692 2.05 0.041 .0863869 4.063905 sdtot | .0018589 .0515336 0.04 0.971 -.099145 .1028628 sdreer2 | 1.07e-06 1.49e-06 0.71 0.476 -1.86e-06 3.99e-06 sdinfl | .0124262 .0165932 0.75 0.454 -.0200958 .0449482 ncrisis | -.5637616 6.450884 -0.09 0.930 -13.20726 12.07974 tyear2 | -1.818197 1.367509 -1.33 0.184 -4.498465 .8620717 tyear3 | -1.152983 .709664 -1.62 0.104 -2.543899 .2379325 tyear4 | -.8710341 .7436594 -1.17 0.241 -2.32858 .5865116 _cons | 14.23118 6.389534 2.23 0.026 1.707923 26.75444 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.67 Pr > z = 0.008 Arellano-Bond test for AR(2) in first differences: z = 0.25 Pr > z = 0.802 Hansen test of overid. restrictions: chi2(26) = 20.15 Prob > chi2 = 0.784 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .84591962 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 2.43 Prob > chi2 = 0.2964 . . * (b) Without first period . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis tyear* if period > 2, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, lag( > 2 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot s > d_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 283 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(14) = 778.21 avg = 3.72 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1749028 .1225855 1.43 0.154 -.0653604 .415166 product_herf | -27.49741 10.01052 -2.75 0.006 -47.11767 -7.877141 trade | -6.544965 3.521069 -1.86 0.063 -13.44613 .3562044 inter1 | 33.35802 11.76466 2.84 0.005 10.29972 56.41633 kaopen | -.303464 .1681112 -1.81 0.071 -.6329558 .0260278 sd_krg | .2279141 .3697788 0.62 0.538 -.4968392 .9526673 sd_fgr | 2.037303 .9381901 2.17 0.030 .1984838 3.876122 sdtot | -.0049433 .037578 -0.13 0.895 -.0785948 .0687082 sdreer2 | 2.23e-07 1.05e-06 0.21 0.832 -1.84e-06 2.28e-06 sdinfl | .0261071 .0126395 2.07 0.039 .0013342 .05088 ncrisis | -2.395491 5.852694 -0.41 0.682 -13.86656 9.075578 tyear2 | -1.162967 .8931225 -1.30 0.193 -2.913455 .5875212 tyear3 | -.2483878 .4389784 -0.57 0.572 -1.10877 .611994 tyear4 | -.2087901 .3648064 -0.57 0.567 -.9237975 .5062173 tyear5 | .5255822 .561881 0.94 0.350 -.5756844 1.626849 _cons | 8.01738 3.012446 2.66 0.008 2.113093 13.92167 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.39 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.42 Pr > z = 0.674 Hansen test of overid. restrictions: chi2(37) = 37.79 Prob > chi2 = 0.433 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S3 . dis -_b[trade]/(_b[inter]) .19620362 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 8.09 Prob > chi2 = 0.0175 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s tyear* if period > 2, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2)) > iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fgr, > lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 283 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(14) = 806.91 avg = 3.72 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1127131 .1552727 0.73 0.468 -.1916159 .4170421 product_5 | -21.48 8.36369 -2.57 0.010 -37.87253 -5.087472 trade | -12.37662 5.203791 -2.38 0.017 -22.57587 -2.17738 inter2 | 26.1283 9.693763 2.70 0.007 7.128871 45.12772 kaopen | -.389698 .1841551 -2.12 0.034 -.7506353 -.0287607 sd_krg | .2079701 .4406013 0.47 0.637 -.6555925 1.071533 sd_fgr | 1.555648 .9844508 1.58 0.114 -.3738398 3.485136 sdtot | -.0038421 .0504231 -0.08 0.939 -.1026695 .0949853 sdreer2 | 1.83e-08 1.31e-06 0.01 0.989 -2.54e-06 2.58e-06 sdinfl | .0254792 .0143342 1.78 0.075 -.0026152 .0535737 ncrisis | -.2196594 6.135785 -0.04 0.971 -12.24558 11.80626 tyear2 | -.6722302 .9533018 -0.71 0.481 -2.540667 1.196207 tyear3 | -.1684872 .4021614 -0.42 0.675 -.9567089 .6197346 tyear4 | -.0821922 .4012592 -0.20 0.838 -.8686458 .7042614 tyear5 | .3869155 .7103675 0.54 0.586 -1.005379 1.77921 _cons | 12.74882 4.47339 2.85 0.004 3.981133 21.5165 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.22 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.15 Pr > z = 0.878 Hansen test of overid. restrictions: chi2(37) = 30.59 Prob > chi2 = 0.762 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S4 . dis -_b[trade]/(_b[inter]) .47368654 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 7.36 Prob > chi2 = 0.0252 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is tyear* if period > 2, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 2) > ) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 283 Time variable : period Number of groups = 76 Number of instruments = 53 Obs per group: min = 1 Wald chi2(14) = 777.69 avg = 3.72 Prob > chi2 = 0.000 max = 4 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .1086258 .1519012 0.72 0.475 -.1890952 .4063468 product_10 | -18.5754 7.943215 -2.34 0.019 -34.14382 -3.006985 trade | -12.63943 5.734148 -2.20 0.028 -23.87815 -1.400701 inter3 | 22.63588 9.315379 2.43 0.015 4.378075 40.89369 kaopen | -.3725859 .1831315 -2.03 0.042 -.731517 -.0136548 sd_krg | .308781 .4197649 0.74 0.462 -.513943 1.131505 sd_fgr | 1.562221 .9512602 1.64 0.101 -.3022147 3.426657 sdtot | .017833 .049947 0.36 0.721 -.0800614 .1157273 sdreer2 | -2.16e-07 1.20e-06 -0.18 0.857 -2.57e-06 2.14e-06 sdinfl | .0215074 .0143965 1.49 0.135 -.0067093 .049724 ncrisis | 1.553863 5.68363 0.27 0.785 -9.585846 12.69357 tyear2 | -.5493632 .9107581 -0.60 0.546 -2.334416 1.23569 tyear3 | -.1620288 .3964872 -0.41 0.683 -.9391294 .6150718 tyear4 | -.1005104 .3863661 -0.26 0.795 -.857774 .6567532 tyear5 | .2959648 .6878909 0.43 0.667 -1.052277 1.644206 _cons | 12.80951 4.884486 2.62 0.009 3.236096 22.38293 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.24 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.26 Pr > z = 0.794 Hansen test of overid. restrictions: chi2(37) = 33.97 Prob > chi2 = 0.612 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .55838005 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 5.95 Prob > chi2 = 0.0510 . . * (c) Without high income economies . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis tyear* if highincome==0, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, l > ag(2 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdto > t sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 207 Time variable : period Number of groups = 53 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 522.71 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .251457 .1255655 2.00 0.045 .0053531 .4975608 product_herf | -21.97303 8.905244 -2.47 0.014 -39.42699 -4.519075 trade | -5.078506 3.753236 -1.35 0.176 -12.43471 2.277701 inter1 | 25.27356 10.48219 2.41 0.016 4.728843 45.81828 kaopen | -.3776171 .1864112 -2.03 0.043 -.7429763 -.0122578 sd_krg | .8054046 .4700129 1.71 0.087 -.1158037 1.726613 sd_fgr | 2.732065 1.023044 2.67 0.008 .7269355 4.737194 sdtot | .0204821 .0382964 0.53 0.593 -.0545775 .0955417 sdreer2 | 6.61e-07 1.01e-06 0.65 0.515 -1.33e-06 2.65e-06 sdinfl | .0121254 .0114687 1.06 0.290 -.0103528 .0346037 ncrisis | -.9701086 5.54758 -0.17 0.861 -11.84317 9.902949 tyear2 | -.5742697 .9629922 -0.60 0.551 -2.4617 1.31316 tyear3 | -.0774734 .5693833 -0.14 0.892 -1.193444 1.038497 tyear4 | -.3188457 .3762348 -0.85 0.397 -1.056252 .418561 tyear5 | .7676313 .7210768 1.06 0.287 -.6456533 2.180916 _cons | 6.752117 3.122633 2.16 0.031 .6318682 12.87237 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.37 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.88 Pr > z = 0.378 Hansen test of overid. restrictions: chi2(37) = 37.68 Prob > chi2 = 0.438 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S5 . dis -_b[trade]/(_b[inter]) .20094142 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 6.39 Prob > chi2 = 0.0409 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s tyear* if highincome==0, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2 > )) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_f > gr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 207 Time variable : period Number of groups = 53 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 779.31 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .3003982 .1533391 1.96 0.050 -.0001409 .6009373 product_5 | -25.07388 9.850286 -2.55 0.011 -44.38009 -5.767675 trade | -16.99404 7.098738 -2.39 0.017 -30.90731 -3.080769 inter2 | 29.7557 11.55374 2.58 0.010 7.110777 52.40061 kaopen | -.1551284 .2105465 -0.74 0.461 -.567792 .2575352 sd_krg | .9071376 .4584905 1.98 0.048 .0085129 1.805762 sd_fgr | 2.863151 1.075097 2.66 0.008 .7559999 4.970302 sdtot | .0181091 .0453222 0.40 0.689 -.0707209 .106939 sdreer2 | 1.22e-06 1.28e-06 0.96 0.339 -1.29e-06 3.74e-06 sdinfl | .0060802 .0128605 0.47 0.636 -.0191259 .0312863 ncrisis | 2.857011 5.948254 0.48 0.631 -8.801353 14.51537 tyear2 | -.5649018 .9636852 -0.59 0.558 -2.45369 1.323886 tyear3 | .1252807 .564125 0.22 0.824 -.980384 1.230945 tyear4 | -.3409668 .4352531 -0.78 0.433 -1.194047 .5121135 tyear5 | .688987 .7843913 0.88 0.380 -.8483918 2.226366 _cons | 16.41964 6.146368 2.67 0.008 4.372977 28.4663 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.31 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.81 Pr > z = 0.415 Hansen test of overid. restrictions: chi2(37) = 28.96 Prob > chi2 = 0.825 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S6 . dis -_b[trade]/(_b[inter]) .57111888 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 6.67 Prob > chi2 = 0.0356 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is tyear* if highincome==0, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 > 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd > _fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 207 Time variable : period Number of groups = 53 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 706.34 avg = 3.91 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .3011708 .155628 1.94 0.053 -.0038545 .6061961 product_10 | -26.66714 10.99446 -2.43 0.015 -48.21589 -5.118395 trade | -21.28498 9.279563 -2.29 0.022 -39.47259 -3.097375 inter3 | 31.19422 12.80283 2.44 0.015 6.101131 56.28731 kaopen | -.1470246 .2107986 -0.70 0.486 -.5601822 .266133 sd_krg | 1.184103 .4823297 2.45 0.014 .2387544 2.129452 sd_fgr | 3.058428 1.052433 2.91 0.004 .9956967 5.12116 sdtot | .047853 .046477 1.03 0.303 -.0432403 .1389463 sdreer2 | 1.12e-06 1.25e-06 0.89 0.372 -1.34e-06 3.57e-06 sdinfl | -.0004667 .0135248 -0.03 0.972 -.0269747 .0260413 ncrisis | 4.59548 5.654016 0.81 0.416 -6.486187 15.67715 tyear2 | -.7004211 .9769898 -0.72 0.473 -2.615286 1.214444 tyear3 | .0826978 .5556086 0.15 0.882 -1.006275 1.171671 tyear4 | -.4947215 .4471723 -1.11 0.269 -1.371163 .3817202 tyear5 | .5689827 .7545857 0.75 0.451 -.9099781 2.047943 _cons | 20.13655 8.008484 2.51 0.012 4.440208 35.83289 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.33 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.87 Pr > z = 0.387 Hansen test of overid. restrictions: chi2(37) = 28.09 Prob > chi2 = 0.854 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) .68233744 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 5.94 Prob > chi2 = 0.0513 . . * (d) Without low income economies . . xtabond2 std l.std product_herf trade inter1 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncr > isis tyear* if lowincome==0, robust gmm(l.std, lag(2 4)) gmm(trade product_herf inter1, la > g(2 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot > sd_fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 231 Time variable : period Number of groups = 57 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 774.98 avg = 4.05 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0743361 .139227 0.53 0.593 -.1985438 .3472159 product_herf | -37.76804 11.99635 -3.15 0.002 -61.28045 -14.25563 trade | -3.775852 3.101994 -1.22 0.224 -9.855649 2.303945 inter1 | 40.95862 12.84111 3.19 0.001 15.79051 66.12673 kaopen | -.5503651 .1685377 -3.27 0.001 -.8806928 -.2200374 sd_krg | .3687839 .3178592 1.16 0.246 -.2542086 .9917764 sd_fgr | 1.075648 .8660578 1.24 0.214 -.6217943 2.77309 sdtot | .0455214 .0582168 0.78 0.434 -.0685814 .1596242 sdreer2 | -4.28e-07 1.20e-06 -0.36 0.722 -2.79e-06 1.93e-06 sdinfl | .0175009 .012431 1.41 0.159 -.0068634 .0418652 ncrisis | -2.573192 3.853946 -0.67 0.504 -10.12679 4.980404 tyear2 | -.5352781 .8046186 -0.67 0.506 -2.112301 1.041745 tyear3 | -.2559013 .5643746 -0.45 0.650 -1.362055 .8502527 tyear4 | -.4581843 .4198838 -1.09 0.275 -1.281141 .3647728 tyear5 | .1367256 .5791452 0.24 0.813 -.9983781 1.271829 _cons | 6.051641 2.830975 2.14 0.033 .5030325 11.60025 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.22 Pr > z = 0.001 Arellano-Bond test for AR(2) in first differences: z = 0.93 Pr > z = 0.350 Hansen test of overid. restrictions: chi2(37) = 35.55 Prob > chi2 = 0.537 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S7 . dis -_b[trade]/(_b[inter]) .092187 . test trade inter ( 1) trade = 0 ( 2) inter1 = 0 chi2( 2) = 11.27 Prob > chi2 = 0.0036 . xtabond2 std l.std product_5 trade inter2 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncrisi > s tyear* if lowincome==0, robust gmm(l.std, lag(2 4)) gmm(trade product_5 inter2, lag(2 2) > ) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_fg > r, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 231 Time variable : period Number of groups = 57 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 830.32 avg = 4.05 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | -.0057095 .1519037 -0.04 0.970 -.3034353 .2920164 product_5 | -5.390051 8.649767 -0.62 0.533 -22.34328 11.56318 trade | -2.959202 4.800612 -0.62 0.538 -12.36823 6.449826 inter2 | 6.141254 10.81159 0.57 0.570 -15.04907 27.33157 kaopen | -.580742 .1732125 -3.35 0.001 -.9202323 -.2412517 sd_krg | .3043572 .3808983 0.80 0.424 -.4421897 1.050904 sd_fgr | 1.265928 1.096305 1.15 0.248 -.88279 3.414645 sdtot | .011429 .0512573 0.22 0.824 -.0890335 .1118915 sdreer2 | 1.94e-07 9.75e-07 0.20 0.842 -1.72e-06 2.10e-06 sdinfl | .0169531 .0123298 1.37 0.169 -.0072129 .0411192 ncrisis | -5.687232 3.702367 -1.54 0.125 -12.94374 1.569274 tyear2 | -.3897792 .880309 -0.44 0.658 -2.115153 1.335595 tyear3 | .0911606 .4832348 0.19 0.850 -.8559622 1.038283 tyear4 | -.1744854 .3700774 -0.47 0.637 -.8998237 .5508529 tyear5 | .5337449 .7136011 0.75 0.454 -.8648875 1.932377 _cons | 5.556003 3.993797 1.39 0.164 -2.271695 13.3837 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -2.95 Pr > z = 0.003 Arellano-Bond test for AR(2) in first differences: z = 1.03 Pr > z = 0.304 Hansen test of overid. restrictions: chi2(37) = 35.77 Prob > chi2 = 0.527 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . estimates store S8 . dis -_b[trade]/(_b[inter]) .48185626 . test trade inter ( 1) trade = 0 ( 2) inter2 = 0 chi2( 2) = 0.39 Prob > chi2 = 0.8225 . xtabond2 std l.std product_10 trade inter3 kaopen sd_krg sd_fgr sdtot sdreer2 sdinfl ncris > is tyear* if lowincome==0, robust gmm(l.std, lag(2 4)) gmm(trade product_10 inter3, lag(2 > 2)) iv(tyear*) gmm(ncrisis, lag(2 2) eq(level)) gmm(sdinfl sdreer2 sd_krg kaopen sdtot sd_ > fgr, lag(2 2) collapse) nodiffsargan Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm. tyear1 dropped due to collinearity Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Dynamic panel-data estimation, one-step system GMM ------------------------------------------------------------------------------ Group variable: id Number of obs = 231 Time variable : period Number of groups = 57 Number of instruments = 53 Obs per group: min = 1 Wald chi2(15) = 745.78 avg = 4.05 Prob > chi2 = 0.000 max = 5 ------------------------------------------------------------------------------ | Robust std | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- std | L1. | .0126269 .1605524 0.08 0.937 -.3020501 .3273039 product_10 | -.2953033 8.303481 -0.04 0.972 -16.56983 15.97922 trade | -.8926175 5.14041 -0.17 0.862 -10.96764 9.182402 inter3 | .4407229 10.42508 0.04 0.966 -19.99206 20.87351 kaopen | -.5256939 .1792543 -2.93 0.003 -.8770258 -.1743619 sd_krg | .3420644 .3948074 0.87 0.386 -.4317439 1.115873 sd_fgr | 1.46178 .9918404 1.47 0.141 -.4821914 3.405752 sdtot | .017481 .0512509 0.34 0.733 -.0829689 .1179309 sdreer2 | 5.02e-07 9.18e-07 0.55 0.584 -1.30e-06 2.30e-06 sdinfl | .0100489 .0129122 0.78 0.436 -.0152585 .0353563 ncrisis | -4.904055 3.083585 -1.59 0.112 -10.94777 1.139661 tyear2 | -.3908667 .8657688 -0.45 0.652 -2.087742 1.306009 tyear3 | .2185068 .4524265 0.48 0.629 -.6682328 1.105246 tyear4 | -.1303897 .3471603 -0.38 0.707 -.8108115 .5500321 tyear5 | .608627 .6618148 0.92 0.358 -.6885062 1.90576 _cons | 3.597397 4.154425 0.87 0.387 -4.545125 11.73992 ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -3.01 Pr > z = 0.003 Arellano-Bond test for AR(2) in first differences: z = 0.95 Pr > z = 0.342 Hansen test of overid. restrictions: chi2(37) = 36.63 Prob > chi2 = 0.486 Warning: Sargan/Hansen tests are weak when instruments are many. ------------------------------------------------------------------------------ . dis -_b[trade]/(_b[inter]) 2.0253488 . test trade inter ( 1) trade = 0 ( 2) inter3 = 0 chi2( 2) = 0.08 Prob > chi2 = 0.9601 . . estout * using "C:\Gazelle\Output\subsample.tex", replace style(tex) varlabels(_cons Const > ant) cells (b(star fmt(%9.3f)) se(par fmt(%9.2f))) stats (chi2 sargan sarganp ar2 ar2p N, > labels("$\chi^2$" "Sargan" "Sargan p" "AR(2)" "AR(2) p" "N")) starlevels(* 0.10 ** 0.05 ** > * 0.01) & S1 & S2 & S3 & S4 & S5 > & S6 & S7 & S8 \\ & b/se & b/se & b/se & b/se & b/se > & b/se & b/se & b/se \\ L.std & 0.329** & 0.126 & 0.175 & 0.113 & 0.251** > & 0.300* & 0.074 & -0.006 \\ & (0.13) & (0.17) & (0.12) & (0.16) & (0.13) > & (0.15) & (0.14) & (0.15) \\ product_herf& -29.447***& & -27.497***& & -21.973** > & & -37.768***& \\ & (11.23) & & (10.01) & & (8.91) > & & (12.00) & \\ trade & -7.407** & -13.547* & -6.545* & -12.377** & -5.079 > & -16.994** & -3.776 & -2.959 \\ & (3.78) & (7.54) & (3.52) & (5.20) & (3.75) > & (7.10) & (3.10) & (4.80) \\ inter1 & 34.604***& & 33.358***& & 25.274** > & & 40.959***& \\ & (13.26) & & (11.76) & & (10.48) > & & (12.84) & \\ kaopen & -0.407 & -0.536* & -0.303* & -0.390** & -0.378** > & -0.155 & -0.550***& -0.581***\\ & (0.27) & (0.30) & (0.17) & (0.18) & (0.19) > & (0.21) & (0.17) & (0.17) \\ sd_krg & -0.281 & -0.164 & 0.228 & 0.208 & 0.805* > & 0.907** & 0.369 & 0.304 \\ & (0.41) & (0.46) & (0.37) & (0.44) & (0.47) > & (0.46) & (0.32) & (0.38) \\ sd_fgr & 2.938***& 2.146** & 2.037** & 1.556 & 2.732*** > & 2.863***& 1.076 & 1.266 \\ & (0.92) & (1.09) & (0.94) & (0.98) & (1.02) > & (1.08) & (0.87) & (1.10) \\ sdtot & -0.013 & -0.016 & -0.005 & -0.004 & 0.020 > & 0.018 & 0.046 & 0.011 \\ & (0.05) & (0.05) & (0.04) & (0.05) & (0.04) > & (0.05) & (0.06) & (0.05) \\ sdreer2 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 > & 0.000 & -0.000 & 0.000 \\ & (0.00) & (0.00) & (0.00) & (0.00) & (0.00) > & (0.00) & (0.00) & (0.00) \\ sdinfl & 0.017 & 0.016 & 0.026** & 0.025* & 0.012 > & 0.006 & 0.018 & 0.017 \\ & (0.01) & (0.02) & (0.01) & (0.01) & (0.01) > & (0.01) & (0.01) & (0.01) \\ ncrisis & -1.119 & -1.270 & -2.395 & -0.220 & -0.970 > & 2.857 & -2.573 & -5.687 \\ & (5.64) & (6.60) & (5.85) & (6.14) & (5.55) > & (5.95) & (3.85) & (3.70) \\ tyear2 & -2.637** & -1.970 & -1.163 & -0.672 & -0.574 > & -0.565 & -0.535 & -0.390 \\ & (1.14) & (1.44) & (0.89) & (0.95) & (0.96) > & (0.96) & (0.80) & (0.88) \\ tyear3 & -1.461** & -1.184 & -0.248 & -0.168 & -0.077 > & 0.125 & -0.256 & 0.091 \\ & (0.58) & (0.74) & (0.44) & (0.40) & (0.57) > & (0.56) & (0.56) & (0.48) \\ tyear4 & -1.288** & -0.946 & -0.209 & -0.082 & -0.319 > & -0.341 & -0.458 & -0.174 \\ & (0.58) & (0.78) & (0.36) & (0.40) & (0.38) > & (0.44) & (0.42) & (0.37) \\ product_5 & & -18.496 & & -21.480** & > & -25.074** & & -5.390 \\ & & (11.93) & & (8.36) & > & (9.85) & & (8.65) \\ inter2 & & 21.805 & & 26.128***& > & 29.756** & & 6.141 \\ & & (14.34) & & (9.69) & > & (11.55) & & (10.81) \\ tyear5 & & & 0.526 & 0.387 & 0.768 > & 0.689 & 0.137 & 0.534 \\ & & & (0.56) & (0.71) & (0.72) > & (0.78) & (0.58) & (0.71) \\ Constant & 9.848***& 15.210***& 8.017***& 12.749***& 6.752** > & 16.420***& 6.052** & 5.556 \\ & (3.09) & (5.74) & (3.01) & (4.47) & (3.12) > & (6.15) & (2.83) & (3.99) \\ $\chi^2$ & 587.504 & 463.118 & 778.215 & 806.906 & 522.709 > & 779.314 & 774.980 & 830.324 \\ Sargan & 24.855 & 21.798 & 37.788 & 30.593 & 37.677 > & 28.957 & 35.547 & 35.771 \\ Sargan p & 0.527 & 0.700 & 0.433 & 0.762 & 0.438 > & 0.825 & 0.537 & 0.527 \\ AR(2) & 0.470 & 0.267 & 0.421 & 0.154 & 0.881 > & 0.814 & 0.935 & 1.028 \\ AR(2) p & 0.639 & 0.789 & 0.674 & 0.878 & 0.378 > & 0.415 & 0.350 & 0.304 \\ N & 238.000 & 238.000 & 283.000 & 283.000 & 207.000 > & 207.000 & 231.000 & 231.000 \\ . estimates clear . end of do-file . log close log: C:\Gazelle\codeit3b.log log type: text closed on: 11 May 2010, 09:05:40 --------------------------------------------------------------------------------------------