<p>Hungary to Malaysia ------log: K:\Hungary_to_Malaysia.log opened on: 26 Jul 2006, 07:42:21</p><p>. *Dropping Hungary . drop if ccode==453440 (10 observations deleted)</p><p>. . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist op > en english gdpdfrationew white whitemg, stat(n mean sd median min max) col(sta > t)</p><p> variable | N mean sd p50 min max ------+------rimp | 1000 490919 1561268 7348 0 1.39e+07 immig | 1000 33202.42 117083.7 2790 0 1137050 gdp | 1000 2.78e+11 9.69e+11 1.63e+10 1.92e+08 8.99e+12 gdpau | 1000 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 1000 105.6361 16.92474 102.6773 60.87417 207.3465 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.95e+07 1.54e+08 1.04e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1042.171 10901.79 13.89535 .0068 270182.6 remote | 1000 6782.308 4121.956 6797 1293 39620 dist | 1000 13346.82 3525.066 14215 2409 17972 open | 1000 .7064996 .3887772 .63295 .0671 3.2192 english | 1000 .38 .4856293 0 0 1 gdpdfratio~w | 1000 1.051848 .181104 1.015772 .5844526 2.009028 white | 1000 .13 .3364717 0 0 1 whitemg | 1000 20501.65 116468.1 0 0 1137050 ------. sort white</p><p>. *IIIB. Descriptives Original Unites(sub sample for "white" and "non-white" cou > ntries)--RHS Variables: . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remo > te dist phone open english gdpdfrationew white whitemg, stat(n mean sd median > min max) col(stat) </p><p>------> white = 0</p><p> variable | N mean sd p50 min max ------+------rimp | 870 404626.7 1597655 2944.5 0 1.39e+07 immig | 870 14598.58 27144.22 1403.5 0 158613 gdp | 870 2.37e+11 1.00e+12 1.00e+10 1.92e+08 8.99e+12 gdpau | 870 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 870 104.7542 17.28051 101.6138 60.87417 207.3465 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.34e+07 1.65e+08 1.07e+07 41000 1.26e+09 popau | 870 1.82e+07 612839.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 870 1181.904 11681.84 19.96485 .0068 270182.6 remote | 870 7215.099 4083.187 6955 1293 39620 dist | 870 13173.82 3411.925 14040 2410 17972 phone | 870 155.748 241.022 47.025 .54 1449.75 open | 870 .7136564 .4102182 .62645 .0671 3.2192 english | 870 .3908046 .4882114 0 0 1 gdpdfratio~w | 870 1.043312 .185957 1 .5844526 2.009028 white | 870 0 0 0 0 0 whitemg | 870 0 0 0 0 0 ------</p><p>------> white = 1</p><p> variable | N mean sd p50 min max ------+------rimp | 130 1068414 1138347 522863.5 40432 3843839 immig | 130 157705 288518.8 21174 2612 1137050 gdp | 130 5.56e+11 6.58e+11 2.54e+11 5.15e+10 2.69e+12 gdpau | 130 3.83e+11 4.46e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 130 111.5379 12.89742 112.2247 85.45601 143.9587 gdpdfau | 130 100.7173 4.649088 100.8223 94.42464 109.9797 pop | 130 2.34e+07 2.55e+07 8837000 3477200 8.22e+07 popau | 130 1.82e+07 614856.7 1.82e+07 1.73e+07 1.92e+07 xrate1 | 130 107.0323 293.6987 4.4722 .3774 1261.556 remote | 130 3885.938 3089.96 2888 1530 12501 dist | 130 14504.62 4031.974 15931 2409 17493 phone | 130 734.716 269.9717 652.085 343.99 1487.08 open | 130 .6586038 .1850905 .64065 .3517 1.2967 english | 130 .3076923 .4633239 0 0 1 gdpdfratio~w | 130 1.108974 .1314272 1.116445 .8254872 1.441221 white | 130 1 0 1 1 1 whitemg | 130 157705 288518.8 21174 2612 1137050 ------</p><p>. . . **Regression of Imports . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Imports . xtgls lrimp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8729.61 Log likelihood = -547.1466 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3054968 .0308466 9.90 0.000 .2450385 .365955 lgdp | 1.196976 .033775 35.44 0.000 1.130778 1.263174 lgdpau | .1713219 .5978752 0.29 0.774 -1.000492 1.343136 lgdpdfrati~w | -.9036172 .2432338 -3.72 0.000 -1.380347 -.4268876 lpopau | -2.535706 2.060685 -1.23 0.219 -6.574575 1.503162 lpop | .0286916 .0411682 0.70 0.486 -.0519966 .1093799 lxrate1 | -.1368478 .0166431 -8.22 0.000 -.1694678 -.1042279 lremote | -.4224619 .0786595 -5.37 0.000 -.5766317 -.268292 ldist | -2.184429 .166197 -13.14 0.000 -2.510169 -1.858689 lopen | .2651824 .0551138 4.81 0.000 .1571614 .3732034 english | .932337 .1310391 7.11 0.000 .6755052 1.189169 white | 4.557529 .5701526 7.99 0.000 3.44005 5.675007 lwhitemg | -.4138027 .0504544 -8.20 0.000 -.5126915 -.314914 _cons | 40.46189 18.98059 2.13 0.033 3.260616 77.66317 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000952 lgdp | -.000319 .001141 lgdpau | -.000957 .001417 .357455 lgdpdfrati~w | -.000804 .000151 -.009351 .059163 lpopau | .001838 -.008094 -1.20728 .048237 4.24642 lpop | -.000127 -.000766 .000101 .000221 -.000161 .001695 lxrate1 | .000098 .000155 .000339 .00022 -.002484 -.000093 .000277 lremote | .000453 .000047 -.00066 -.001864 -.002152 -.000274 .000059 ldist | .001782 .001061 .000613 -.001054 -.015393 -.000034 .001795 lopen | -.000127 .000576 .00234 .000837 -.015796 .000338 .000158 english | -.001257 .002987 .003136 .00206 -.011559 -.001455 .000555 white | .004241 -.002083 .002708 -.01053 -.024394 .005164 .000183 lwhitemg | -.000548 .000192 -.000253 .000959 .002761 -.000418 -.00005 _cons | -.02309 .072138 10.6303 -.592841 -38.4852 -.004622 .01083</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .006187 ldist | .004595 .027621 lopen | .001341 .001077 .003038 english | -.003367 .002956 -.000829 .017171 white | .000724 -.002782 -.000103 -.000453 .325074 lwhitemg | .000109 -.000425 -.000084 .000211 -.028214 .002546 _cons | -.039757 -.102628 .161729 .05915 .285617 -.029786 360.263</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 69907.08 Log likelihood = -980.1007 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0505492 .014211 3.56 0.000 .0226962 .0784022 lgdp | 1.608723 .0540198 29.78 0.000 1.502846 1.7146 lgdpau | .8876892 .3538703 2.51 0.012 .1941163 1.581262 lgdpdfrati~w | -.4474079 .1486019 -3.01 0.003 -.7386624 -.1561535 lpopau | -6.388743 1.196395 -5.34 0.000 -8.733635 -4.043852 lpop | -.3533118 .0894458 -3.95 0.000 -.5286222 -.1780013 lxrate1 | -.1206392 .020536 -5.87 0.000 -.1608891 -.0803894 lremote | -.9488164 .126176 -7.52 0.000 -1.196117 -.7015159 ldist | -3.203713 .1659226 -19.31 0.000 -3.528916 -2.878511 lopen | -.0567575 .026667 -2.13 0.033 -.1090238 -.0044912 english | .9988392 .0851043 11.74 0.000 .8320379 1.165641 white | 4.66538 .7779235 6.00 0.000 3.140677 6.190082 lwhitemg | -.4592575 .0722652 -6.36 0.000 -.6008948 -.3176203 _cons | 95.30965 11.43085 8.34 0.000 72.90561 117.7137 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000202 lgdp | -.000194 .002918 lgdpau | -.001134 .002244 .125224 lgdpdfrati~w | -.000515 .000931 -.011127 .022083 lpopau | .004491 -.009102 -.414477 .021341 1.43136 lpop | .000053 -.0046 -.00226 -.000226 .007271 .008001 lxrate1 | -.000017 .000343 .00003 .000471 -.003443 -.00041 .000422 lremote | .00013 -.001303 -.008395 -.005071 .030688 .001522 -.000191 ldist | .000431 -.002397 -.007498 -.002537 .020694 .00386 .000382 lopen | .00003 -.000175 -.001042 .000791 .003898 .00038 -.000085 english | -.000397 .000376 .003183 .002731 -.020633 .000086 .001131 white | .000509 -.015508 -.01451 -.00777 .058525 .023965 -.001608 lwhitemg | -.00009 .000621 .000416 .000208 -.002714 -.000849 .000143 _cons | -.046778 .131801 3.73653 -.030161 -13.2801 -.131903 .051216</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .01592 ldist | .008324 .02753 lopen | .000959 .000437 .000711 english | -.00311 .001846 -.000419 .007243 white | .021497 -.016201 .002415 -.003536 .605165 lwhitemg | .000033 .003473 -.000123 .000447 -.05325 .005222 _cons | -.499131 -.494659 -.052411 .253077 -.635745 -.001052 130.664</p><p>. . . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 6800.08 Log likelihood = -935.4606 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0607264 .0173633 3.50 0.000 .0266949 .0947578 lgdp | 1.680097 .0666956 25.19 0.000 1.549376 1.810818 lgdpau | .2981585 .4385496 0.68 0.497 -.561383 1.1577 lgdpdfrati~w | -.5027812 .1755326 -2.86 0.004 -.8468188 -.1587437 lpopau | -4.032084 1.515262 -2.66 0.008 -7.001943 -1.062225 lpop | -.497343 .0806023 -6.17 0.000 -.6553205 -.3393655 lxrate1 | -.1391181 .0243476 -5.71 0.000 -.1868385 -.0913978 lremote | -.3387469 .1251036 -2.71 0.007 -.5839454 -.0935483 ldist | -4.520097 .3295104 -13.72 0.000 -5.165925 -3.874268 lopen | .0225949 .0354189 0.64 0.524 -.0468249 .0920148 english | 1.480639 .1454415 10.18 0.000 1.195579 1.765699 white | 11.5541 1.901119 6.08 0.000 7.827975 15.28023 lwhitemg | -.9406264 .1890368 -4.98 0.000 -1.311132 -.5701211 _cons | 79.28285 14.43008 5.49 0.000 51.00041 107.5653 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000301 lgdp | -.000459 .004448 lgdpau | -.001284 .002703 .192326 lgdpdfrati~w | -.000557 .001342 -.012888 .030812 lpopau | .003987 -.016528 -.642245 .036593 2.29602 lpop | .00032 -.003772 -.001279 -.001112 .004386 .006497 lxrate1 | -6.6e-06 .000349 -.000211 .000851 -.003742 -.000516 .000593 lremote | -.000078 -.000628 -.007106 -.001911 .022475 -.000369 .000024 ldist | .001335 .008839 -.008559 -.002218 -.016608 -.001136 .000893 lopen | .000073 -.000507 -.000431 .001465 .002246 .000797 -.000176 english | -.000673 .001273 .004222 .001825 -.037031 .004496 .001663 white | .000209 -.030792 -.001102 .000853 .011054 .028894 .003979 lwhitemg | -.000036 .00152 -.000927 -.000391 .004612 -.001771 -.000381 _cons | -.039828 .086105 5.73193 -.274049 -21.0294 -.04409 .055787</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .015651 ldist | .005871 .108577 lopen | .0006 -.000551 .001255 english | -.003474 .007369 -.001106 .021153 white | .01444 -.137649 .002179 .030313 3.61426 lwhitemg | .00048 .010346 -.000086 -.003106 -.351817 .035735 _cons | -.359154 -.77462 -.02756 .354168 1.22516 -.158429 208.227</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2256.29 Log likelihood = -1111.455 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0864071 .0414661 2.08 0.037 .005135 .1676792 lgdp | .9389794 .0801356 11.72 0.000 .7819165 1.096042 lgdpau | -.4631616 .8445905 -0.55 0.583 -2.118529 1.192205 lgdpdfrati~w | -.4149194 .3486752 -1.19 0.234 -1.09831 .2684715 lpopau | .210095 2.893649 0.07 0.942 -5.461353 5.881543 lpop | .0395503 .0987049 0.40 0.689 -.1539078 .2330083 lxrate1 | -.1397375 .0334248 -4.18 0.000 -.2052489 -.074226 lremote | .5804134 .2331761 2.49 0.013 .1233966 1.03743 ldist | -1.581484 .3323814 -4.76 0.000 -2.23294 -.9300285 lopen | .3500095 .0793272 4.41 0.000 .1945311 .5054879 english | 1.702871 .2431128 7.00 0.000 1.226379 2.179364 white | 1.699555 2.221539 0.77 0.444 -2.654581 6.053691 lwhitemg | .1700155 .1949556 0.87 0.383 -.2120903 .5521214 _cons | -.2145379 27.44812 -0.01 0.994 -54.01187 53.58279 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001719 lgdp | -.001604 .006422 lgdpau | -.001808 .001549 .713333 lgdpdfrati~w | -.000357 .001594 -.012704 .121574 lpopau | .0034 -.009876 -2.38912 .040072 8.3732 lpop | .00033 -.00573 4.2e-06 -.000968 -.000756 .009743 lxrate1 | .000122 .000911 .000542 .002003 -.007727 -.001195 .001117 lremote | .001231 .00045 -.027832 -.015149 .086998 .000714 -.000804 ldist | .00432 -.007449 -.019974 -.006782 .061547 .011208 -.000182 lopen | .000268 -.001137 .00485 .002455 -.026341 .002979 -.000176 english | -.003638 .00095 .009815 .005851 -.019068 -.000552 .001474 white | .003253 -.023452 .100043 .002938 -.400414 .020219 .000393 lwhitemg | -.000491 .00087 -.010575 -.00169 .043525 -.000192 -.000191 _cons | -.037099 .141057 21.3397 -.281714 -77.4297 -.122252 .114575</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054371 ldist | .020289 .110477 lopen | .001921 -.000991 .006293 english | -.014914 .012431 -.001942 .059104 white | .041369 -.02821 .007121 .040006 4.93523 lwhitemg | -.0007 .006479 -.000422 -.002852 -.422198 .038008 _cons | -1.38918 -1.76045 .282364 .049701 4.10816 -.513474 753.399</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 54771.55 Log likelihood = -913.8515 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0242456 .0136529 1.78 0.076 -.0025136 .0510047 lgdp | 1.545476 .0533422 28.97 0.000 1.440927 1.650025 lgdpau | .6522811 .3630878 1.80 0.072 -.059358 1.36392 lgdpdfrati~w | -.2486545 .1376421 -1.81 0.071 -.518428 .0211191 lpopau | -6.573338 1.228628 -5.35 0.000 -8.981404 -4.165272 lpop | -.1468597 .0912827 -1.61 0.108 -.3257705 .032051 lxrate1 | -.0455096 .0185874 -2.45 0.014 -.0819402 -.009079 lremote | -.6187321 .1494471 -4.14 0.000 -.911643 -.3258212 ldist | -2.458252 .1654915 -14.85 0.000 -2.782609 -2.133894 lopen | -.0440779 .0275896 -1.60 0.110 -.0981526 .0099968 english | 1.154401 .1125644 10.26 0.000 .9337784 1.375023 white | 3.674228 .8714425 4.22 0.000 1.966232 5.382224 lwhitemg | -.2720855 .0801684 -3.39 0.001 -.4292127 -.1149583 _cons | 92.31228 11.61608 7.95 0.000 69.54518 115.0794 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000186 lgdp | -.000195 .002845 lgdpau | -.000884 .002024 .131833 lgdpdfrati~w | -.000344 .000797 -.007569 .018945 lpopau | .003156 -.007095 -.437129 .012119 1.50953 lpop | .000112 -.004578 -.001755 -.000152 .003655 .008333 lxrate1 | 2.3e-06 .000221 -.000061 .000462 -.00253 -.000249 .000345 lremote | -4.1e-06 -.000959 -.013536 -.004617 .049251 .000257 -.000203 ldist | .000828 -.005357 -.004294 .001055 .003919 .009538 .000625 lopen | .000017 -.000096 -.000958 .000881 .003458 .000275 -.000067 english | -.000316 -.000294 .003512 .002699 -.018487 .000217 .000946 white | .000489 -.015811 -.016467 -.002086 .030565 .02759 .001906 lwhitemg | -.000086 .000707 .000088 -.000291 .002136 -.001419 -.000212 _cons | -.03492 .131914 3.94605 -.005405 -13.9617 -.13562 .036608</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .022334 ldist | -.002546 .027387 lopen | .001147 .000267 .000761 english | -.004435 .006535 -.000475 .012671 white | .017592 .030745 .001119 .006414 .759412 lwhitemg | .00083 -.001854 6.0e-06 -.000428 -.066687 .006427 _cons | -.610899 -.230514 -.047509 .186899 -.609238 -.019662 134.933</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7683.48 Log likelihood = -968.7751 Prob > chi2 = 0.0000</p><p>------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2041574 .0303222 6.73 0.000 .144727 .2635878 lgdp | 1.605751 .0703344 22.83 0.000 1.467898 1.743604 lgdpau | -.1653545 .5812381 -0.28 0.776 -1.30456 .9738513 lgdpdfrati~w | -.1483988 .2500638 -0.59 0.553 -.6385149 .3417173 lpopau | -1.302685 2.03788 -0.64 0.523 -5.296856 2.691487 lpop | -.5042116 .0802252 -6.28 0.000 -.6614501 -.3469732 lxrate1 | -.1293165 .027133 -4.77 0.000 -.1824962 -.0761368 lremote | -.2322287 .1267629 -1.83 0.067 -.4806795 .016222 ldist | -3.198401 .3322458 -9.63 0.000 -3.849591 -2.547211 lopen | .1099389 .0484285 2.27 0.023 .0150209 .204857 english | .9337362 .1380184 6.77 0.000 .6632251 1.204247 white | 10.96063 1.86079 5.89 0.000 7.313551 14.60771 lwhitemg | -.9532426 .1852621 -5.15 0.000 -1.31635 -.5901357 _cons | 33.48625 19.41185 1.73 0.085 -4.560271 71.53277 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000919 lgdp | -.001335 .004947 lgdpau | -.001577 .002803 .337838 lgdpdfrati~w | -.001151 .002571 -.02107 .062532 lpopau | .004089 -.015523 -1.14893 .083856 4.15295 lpop | .000779 -.004094 -.001114 -.001717 .005613 .006436 lxrate1 | .000071 .000281 -.00019 .001138 -.004232 -.00058 .000736 lremote | -.000036 -.000262 -.004072 -.000525 .006213 -.000637 .000086 ldist | .004189 .002158 -.010688 -.00249 -.014772 .001103 .00124 lopen | .000136 -.000742 .001745 .001554 -.00822 .001418 -.000277 english | -.00155 .003323 .001884 .004219 -.017451 .000703 .001803 white | -.000131 -.026033 .012406 .001885 .000892 .020267 .004284 lwhitemg | .000044 .001491 -.001905 -.000539 .003303 -.001284 -.000389 _cons | -.051599 .12276 10.322 -.90424 -38.5311 -.078215 .060792</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .016069 ldist | .009276 .110387 lopen | .00042 -.000906 .002345 english | -.003645 -.000911 -.001593 .019049 white | .012787 -.160215 .003388 .018093 3.46254 lwhitemg | .000522 .014524 -.000228 -.002161 -.338773 .034322 _cons | -.210247 -.696467 .090509 .186308 1.30751 -.158876 376.82</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8117.36 Log likelihood = -1109.064 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0152121 .0145657 1.04 0.296 -.0133361 .0437602 lgdp | 1.308612 .0480455 27.24 0.000 1.214445 1.40278 lgdpau | .4371002 .4628878 0.94 0.345 -.4701432 1.344344 lgdpdfrati~w | -.0774501 .1463403 -0.53 0.597 -.3642718 .2093716 lpopau | -5.321543 1.573403 -3.38 0.001 -8.405356 -2.23773 lpop | .1366584 .0699739 1.95 0.051 -.0004879 .2738047 lxrate1 | -.0582689 .0182259 -3.20 0.001 -.0939911 -.0225467 lremote | -.6150068 .1580684 -3.89 0.000 -.9248152 -.3051983 ldist | -3.216958 .2164123 -14.86 0.000 -3.641119 -2.792798 lopen | .0614056 .0382359 1.61 0.108 -.0135354 .1363467 english | 2.461527 .1309535 18.80 0.000 2.204863 2.718191 white | 4.508582 1.161559 3.88 0.000 2.231968 6.785196 lwhitemg | -.1969908 .0979515 -2.01 0.044 -.3889722 -.0050095 _cons | 83.98665 15.16142 5.54 0.000 54.27082 113.7025 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000212 lgdp | -.000335 .002308 lgdpau | .000058 -.000157 .214265 lgdpdfrati~w | -.000351 .000538 .001497 .021415 lpopau | -.001665 .001981 -.710777 -.004378 2.4756 lpop | .000156 -.002619 -.000249 -.00003 -.002345 .004896 lxrate1 | -.000011 .00019 .000242 .000557 -.002051 -.00034 .000332 lremote | .000106 .000705 -.018714 -.00004 .05796 -.000838 -.000031 ldist | .000526 .000322 -.011528 -.000421 .024026 .00076 .000365 lopen | .00005 -.000239 .000012 .001662 .000491 .00056 -.000117 english | -.000647 .000091 .001663 .001205 -.007973 .002239 .000855 white | .000198 -.013167 -.006577 -.00093 .01113 .023809 -.000116 lwhitemg | -5.3e-06 .000681 -.00083 .000227 .003162 -.001537 .000071 _cons | .025012 -.047335 6.44979 .004179 -23.1609 .02608 .023436</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .024986 ldist | .015699 .046834 lopen | .000791 .000023 .001462 english | -.003089 .00304 -.00114 .017149 white | .005971 -.007537 .000512 .032882 1.34922 lwhitemg | .001199 .002747 7.2e-06 -.002798 -.109985 .009594 _cons | -.843061 -.707148 -.0195 .042415 -.088586 -.058318 229.869</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 439.42 Log likelihood = -634.8579 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5008631 .0540553 9.27 0.000 .3949166 .6068095 lgdp | .0636429 .091356 0.70 0.486 -.1154116 .2426973 lgdpau | -.4187589 .6774945 -0.62 0.537 -1.746624 .9091059 lgdpdfrati~w | -.3128567 .2331528 -1.34 0.180 -.7698277 .1441144 lpopau | -.120817 2.308607 -0.05 0.958 -4.645604 4.40397 lpop | .2310282 .0975359 2.37 0.018 .0398614 .422195 lxrate1 | -.095695 .026188 -3.65 0.000 -.1470226 -.0443674 lremote | .2537969 .2398893 1.06 0.290 -.2163776 .7239713 ldist | -2.02081 .5466167 -3.70 0.000 -3.092159 -.9494614 lopen | .0640197 .0577829 1.11 0.268 -.0492326 .177272 english | .584665 .2518518 2.32 0.020 .0910445 1.078285 white | 12.01794 .9736579 12.34 0.000 10.10961 13.92628 lwhitemg | -1.124013 .0963059 -11.67 0.000 -1.312769 -.935257 _cons | 28.4286 22.23647 1.28 0.201 -15.15409 72.01129 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002922 lgdp | -.001702 .008346 lgdpau | -.000476 -.000741 .458999 lgdpdfrati~w | -.001093 .002244 -.007062 .05436 lpopau | -.001704 -.009768 -1.51611 .019384 5.32967 lpop | -.000065 -.005533 -.000679 -.001405 .004529 .009513 lxrate1 | .000118 .000051 .000495 .001483 -.00481 -.000521 .000686 lremote | .002828 .004466 -.02433 -.007451 .055075 -.00373 .000567 ldist | .010105 -.009229 -.022342 -.002664 -.000864 .015731 .001821 lopen | -.000516 .001692 -.002162 .000069 -.001736 -.000019 -.000069 english | -.000244 .00087 .004246 .006235 -.031847 .005643 .001187 white | .016146 -.020348 .005824 -.000311 -.052947 .024756 .004228 lwhitemg | -.001592 .000496 -.001931 -.000549 .011087 -.001305 -.000283 _cons | -.060252 .135258 13.5655 -.130783 -48.9556 -.19587 .046385</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .057547 ldist | .046548 .29879 lopen | .001107 -.001014 .003339 english | -.006576 .015047 .000057 .063429 white | .019872 -.015551 -.003619 .085456 .94801 lwhitemg | .000422 .005675 .000054 -.006417 -.088308 .009275 _cons | -1.27534 -2.76858 .052718 .177425 .588794 -.16554 494.461</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2755.64 Log likelihood = -585.215 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1544131 .0346854 4.45 0.000 .086431 .2223952 lgdp | .2596788 .0563554 4.61 0.000 .1492243 .3701334 lgdpau | -.120629 .0737217 -1.64 0.102 -.2651209 .0238629 lgdpdfrati~w | -.1217909 .0473333 -2.57 0.010 -.2145624 -.0290194 lpopau | 2.590759 .2965377 8.74 0.000 2.009555 3.171962 lpop | .7779753 .1033667 7.53 0.000 .5753803 .9805704 lxrate1 | -.0149342 .0091433 -1.63 0.102 -.0328547 .0029863 lremote | .1332333 .0355647 3.75 0.000 .0635277 .2029389 ldist | -3.261986 .3532469 -9.23 0.000 -3.954337 -2.569635 lopen | -.0153153 .0325942 -0.47 0.638 -.0791988 .0485681 english | .6134506 .2802808 2.19 0.029 .0641102 1.162791 white | 23.47744 2.987837 7.86 0.000 17.62138 29.33349 lwhitemg | -2.214038 .2773754 -7.98 0.000 -2.757684 -1.670393 _cons | -22.90938 5.415801 -4.23 0.000 -33.52415 -12.2946 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001203 lgdp | -.000706 .003176 lgdpau | -.000854 -.000331 .005435 lgdpdfrati~w | .000374 -.001237 .001034 .00224 lpopau | .005742 -.001118 -.018655 .000236 .087935 lpop | -.000235 -.002525 .001279 .000627 -.005024 .010685 lxrate1 | 1.4e-07 .000077 -.000054 .000024 .000737 -.000236 .000084 lremote | -.000379 .001292 -.000781 -.001204 -.000124 -.000827 .000048 ldist | .004465 -.000729 -.003792 .00019 .025711 -.001742 -.000157 lopen | -.000381 -.000215 .00026 -.000504 -.004856 .001192 -.000187 english | -.001001 -.000129 .000954 .000234 -.00727 .000574 .000036 white | .003671 -.006806 .000749 .002478 -.000861 .029109 -.000655 lwhitemg | -.000692 .000243 .000253 -.000142 -.00234 -.002983 .000065 _cons | -.099672 -.005684 .20144 -.008638 -1.14172 -.036306 -.008139</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .001265 ldist | -.000262 .124783 lopen | .000259 -.000943 .001062 english | -.000202 .054731 .000054 .078557 white | -.002876 .02238 .001734 .037697 8.92717 lwhitemg | .000178 -.005327 -.00001 -.002719 -.816163 .076937 _cons | .00089 -1.50143 .070629 -.445943 -.54561 .128404 29.3309</p><p>. . . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 506.02 Log likelihood = -551.6919 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5297602 .0493116 10.74 0.000 .4331113 .6264091 lgdp | .0199915 .0782318 0.26 0.798 -.13334 .173323 lgdpau | 1.938342 .7829564 2.48 0.013 .4037756 3.472908 lgdpdfrati~w | -.6300529 .2774145 -2.27 0.023 -1.173775 -.0863305 lpopau | -9.415261 2.688109 -3.50 0.000 -14.68386 -4.146664 lpop | .3232593 .0970473 3.33 0.001 .1330501 .5134684 lxrate1 | -.1074051 .0252815 -4.25 0.000 -.1569559 -.0578543 lremote | -.0082021 .2553862 -0.03 0.974 -.5087499 .4923456 ldist | -1.52557 .3199279 -4.77 0.000 -2.152617 -.8985223 lopen | .0520696 .0536335 0.97 0.332 -.0530501 .1571892 english | -.0828532 .2213737 -0.37 0.708 -.5167377 .3510314 white | 9.211419 1.088818 8.46 0.000 7.077375 11.34546 lwhitemg | -.8428342 .0964417 -8.74 0.000 -1.031856 -.6538119 _cons | 117.3809 25.50777 4.60 0.000 67.38664 167.3753 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002432 lgdp | -.001481 .00612 lgdpau | .000435 -.00033 .613021 lgdpdfrati~w | -.001247 .001561 -.017532 .076959 lpopau | -.005809 -.005432 -2.04572 .067445 7.22593 lpop | -.00017 -.004377 -.000767 -.000818 .000395 .009418 lxrate1 | .000143 -.000168 .000377 .00086 -.00396 -.000392 .000639 lremote | .001511 .004166 -.022753 -.012123 .063218 -.002576 .00041 ldist | .004744 .001143 -.009801 -.003385 -.00864 .004176 .000751 lopen | -.000261 .000726 .00027 -.0004 -.009488 .000565 -9.4e-06 english | -.001906 .001727 .004248 .004611 -.020655 -.000373 .001 white | .013488 -.026139 .01378 -.006537 -.069438 .030278 .005489 lwhitemg | -.00133 .001322 -.002723 -.000208 .013656 -.001736 -.000445 _cons | .046532 -.00788 18.1756 -.618043 -66.5959 -.052895 .051274</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .065222 ldist | .030686 .102354 lopen | .001188 .002027 .002877 english | -.010107 .020628 -.000024 .049006 white | .020342 .002733 -.001921 .01838 1.18552 lwhitemg | .000677 .000202 .000096 -.001019 -.100561 .009301 _cons | -1.36089 -.963446 .099551 .076543 .548139 -.151591 650.646</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1397.30 Log likelihood = -316.9672 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0372462 .016728 2.23 0.026 .00446 .0700324 lgdp | .2159262 .0533874 4.04 0.000 .1112888 .3205635 lgdpau | -.2431661 .2905729 -0.84 0.403 -.8126786 .3263464 lgdpdfrati~w | -.4054864 .1893745 -2.14 0.032 -.7766536 -.0343191 lpopau | 2.82328 1.039363 2.72 0.007 .7861659 4.860394 lpop | .1176112 .0677301 1.74 0.082 -.0151374 .2503597 lxrate1 | -.0766152 .0176693 -4.34 0.000 -.1112464 -.041984 lremote | -.1288012 .1064026 -1.21 0.226 -.3373465 .0797441 ldist | -1.279698 .2282448 -5.61 0.000 -1.727049 -.832346 lopen | .0064489 .0243693 0.26 0.791 -.041314 .0542118 english | 1.965973 .2077213 9.46 0.000 1.558847 2.373099 white | 9.233493 1.77666 5.20 0.000 5.751303 12.71568 lwhitemg | -.683164 .1834239 -3.72 0.000 -1.042668 -.3236598 _cons | -32.35039 10.62605 -3.04 0.002 -53.17707 -11.52372 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00028 lgdp | -.000308 .00285 lgdpau | .000231 -.001391 .084433 lgdpdfrati~w | -.000512 -.000204 -.001583 .035863 lpopau | -.001111 .006588 -.289939 .021633 1.08028 lpop | .000129 -.002767 .000926 .000776 -.007395 .004587 lxrate1 | -.000016 .000154 .001097 .000684 -.005301 -.000143 .000312 lremote | .000142 .000901 -.00618 -.002788 .021685 -.000523 -.000268 ldist | .000826 .000609 -.001864 -.001115 -.002526 .002931 -.000265 lopen | .000023 -.000238 -.000192 .000951 -.000645 .000304 -9.6e-06 english | -.000169 -.002353 .003053 .00321 -.009975 .004373 .000272 white | .001681 -.021421 .013403 .003043 -.072525 .024085 .000981 lwhitemg | -.00017 .001241 -.001104 -.000026 .005204 -.001657 -.000067 _cons | .007283 -.104355 2.67863 -.329197 -10.511 .064237 .061129</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .011322 ldist | .001519 .052096 lopen | -.000106 -.000099 .000594 english | -.002633 .017499 -.000079 .043148 white | .009469 -.020485 .001226 .067719 3.15652 lwhitemg | -.000348 .000805 -.000064 -.006473 -.321468 .033644 _cons | -.319128 -.480871 .017534 -.082477 1.03669 -.062151 112.913</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1047.13 Log likelihood = -859.0035 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2112718 .0665422 3.18 0.001 .0808514 .3416922 lgdp | .4886882 .1104013 4.43 0.000 .2723057 .7050708 lgdpau | -2.184976 1.147944 -1.90 0.057 -4.434905 .0649526 lgdpdfrati~w | -1.008651 .4524731 -2.23 0.026 -1.895482 -.1218201 lpopau | 4.022566 3.937443 1.02 0.307 -3.694681 11.73981 lpop | .2038669 .1240258 1.64 0.100 -.0392192 .446953 lxrate1 | -.1410991 .0402711 -3.50 0.000 -.220029 -.0621692 lremote | 1.558941 .2869961 5.43 0.000 .9964387 2.121443 ldist | -1.474721 .5117786 -2.88 0.004 -2.477789 -.4716538 lopen | -.0126535 .0778508 -0.16 0.871 -.1652383 .1399314 english | .218224 .2629177 0.83 0.407 -.2970852 .7335331 white | 10.77462 1.440941 7.48 0.000 7.950423 13.59881 lwhitemg | -.8547509 .1387903 -6.16 0.000 -1.126775 -.5827269 _cons | -19.67024 36.98177 -0.53 0.595 -92.15318 52.8127 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004428 lgdp | -.004569 .012188 lgdpau | -.0017 .005532 1.31778 lgdpdfrati~w | -.001531 .004435 -.006428 .204732 lpopau | .00127 -.026861 -4.40836 .072266 15.5035 lpop | .001655 -.010178 -.002545 -.002716 .011202 .015382 lxrate1 | .000124 .001624 .001 .001684 -.010654 -.001518 .001622 lremote | .000437 -.002007 -.032726 -.020904 .083222 .002806 .000656 ldist | .013359 -.010892 -.009458 -.010016 -.015708 .01622 -.002134 lopen | .000324 -.000747 .007058 .001187 -.035606 .002133 -.000357 english | -.006287 .011631 .006811 .001137 -.027254 -.008816 -.000628 white | .026445 -.049808 -.041512 -.039174 .049654 .048954 .005278 lwhitemg | -.003145 .00304 -.000193 .000941 .013135 -.002473 -.000867 _cons | -.051861 .320446 38.8694 -1.01474 -141.845 -.309768 .145074</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .082367 ldist | .022212 .261917 lopen | .003067 .004318 .006061 english | -.001932 .027393 -.000838 .069126 white | .129337 .142522 .00172 .032152 2.07631 lwhitemg | -.004617 -.018769 -.00004 -.005059 -.189291 .019263 _cons | -1.44353 -2.24469 .324629 -.0755 -2.02793 -.002906 1367.65</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 557.42 Log likelihood = -138.1569 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0457924 .0304901 1.50 0.133 -.0139671 .105552 lgdp | .1564997 .0603637 2.59 0.010 .0381891 .2748104 lgdpau | .4239838 .4266398 0.99 0.320 -.4122148 1.260182 lgdpdfrati~w | .3797864 .1895263 2.00 0.045 .0083217 .7512512 lpopau | 2.306613 1.505324 1.53 0.125 -.6437679 5.256994 lpop | .2864698 .0805492 3.56 0.000 .1285964 .4443433 lxrate1 | -.0292299 .0165791 -1.76 0.078 -.0617243 .0032645 lremote | -.0682604 .1398186 -0.49 0.625 -.3422997 .2057789 ldist | -2.166637 .4262938 -5.08 0.000 -3.002158 -1.331117 lopen | .0559712 .0387703 1.44 0.149 -.0200173 .1319597 english | .8067258 .1886868 4.28 0.000 .4369065 1.176545 white | 15.69671 1.218607 12.88 0.000 13.30828 18.08513 lwhitemg | -1.336775 .1143335 -11.69 0.000 -1.560864 -1.112685 _cons | -36.16262 15.44842 -2.34 0.019 -66.44097 -5.884273 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00093 lgdp | -.000694 .003644 lgdpau | -.000442 -.000165 .182022 lgdpdfrati~w | -.000733 .000999 -.001047 .03592 lpopau | .000428 .001665 -.611659 .017337 2.266 lpop | -.00012 -.002676 .000346 .000577 -.004553 .006488 lxrate1 | .000058 .000099 .000193 .000593 -.002799 -.000111 .000275 lremote | .000683 .00231 -.008893 -.00379 .028522 -.001725 .000044 ldist | .002694 -.004013 -.010697 -.007875 -4.2e-07 .009176 .00011 lopen | -.000078 6.5e-06 .000145 .000417 -.003876 .000528 -.000054 english | -.001539 -.000742 .002733 .002725 -.010774 .004736 .000143 white | .00469 -.017735 .031948 -.004289 -.283144 .025883 .003717 lwhitemg | -.000596 .001022 -.003458 .000152 .029228 -.001966 -.000406 _cons | -.013838 -.04185 5.5513 -.218654 -21.7693 -.04865 .037762 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .019549 ldist | .017508 .181726 lopen | .000247 .000117 .001503 english | -.004278 .006334 .000253 .035603 white | -.006528 -.014827 -.000869 .044082 1.485 lwhitemg | .001053 .002173 .000141 -.003515 -.135812 .013072 _cons | -.600368 -1.67332 .049852 .02148 4.00028 -.411133 238.654</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 266.22 Log likelihood = 146.5087 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0017144 .019965 0.09 0.932 -.0374162 .040845 lgdp | .2843683 .0519278 5.48 0.000 .1825917 .3861448 lgdpau | -.3210589 .3644592 -0.88 0.378 -1.035386 .393268 lgdpdfrati~w | -.0960939 .1487989 -0.65 0.518 -.3877344 .1955465 lpopau | 4.617901 1.329837 3.47 0.001 2.011468 7.224335 lpop | -.0724865 .0615299 -1.18 0.239 -.1930829 .0481098 lxrate1 | -.1039135 .0155828 -6.67 0.000 -.1344553 -.0733717 lremote | .3678271 .1336508 2.75 0.006 .1058762 .6297779 ldist | -1.314931 .2812289 -4.68 0.000 -1.86613 -.7637326 lopen | .0325948 .030057 1.08 0.278 -.0263158 .0915054 english | .2341264 .1658588 1.41 0.158 -.0909508 .5592036 white | 9.254427 2.006536 4.61 0.000 5.321689 13.18717 lwhitemg | -.7826359 .1908129 -4.10 0.000 -1.156622 -.4086495 _cons | -63.15974 14.10171 -4.48 0.000 -90.79859 -35.52088 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000399 lgdp | -.000387 .002696 lgdpau | .000263 -.000596 .132831 lgdpdfrati~w | -.000477 .000487 -.006578 .022141 lpopau | -.002558 .003575 -.456473 .0297 1.76847 lpop | .000029 -.002265 -.00019 -.000048 .00101 .003786 lxrate1 | 2.0e-06 .00001 .000509 .000496 -.004721 -.000125 .000243 lremote | .000336 .001766 -.008157 -.001354 .028849 -.001505 -.000078 ldist | .001807 -.001838 -.002349 -.001604 .002488 .004507 .000049 lopen | -.000017 .000034 .000072 .000174 -.001668 .000191 -.000031 english | -.000463 -.001846 -.000104 .000885 .021957 .004587 .000199 white | .002644 -.01559 .016966 -.005085 -.13929 .015533 .001889 lwhitemg | -.000308 .000975 -.002097 .000483 .01437 -.001199 -.000142 _cons | .022298 -.064058 4.20094 -.326005 -17.7392 -.050926 .065337</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .017863 ldist | .007466 .07909 lopen | .000108 -.000541 .000903 english | -.001316 .015224 -.000319 .027509 white | .000113 .014032 -.000902 .034367 4.02619 lwhitemg | .000706 -.002309 .000108 -.003155 -.376402 .03641 _cons | -.507052 -.840523 .026837 -.531716 1.80959 -.168409 198.858</p><p>. xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 501.48 Log likelihood = -651.3583 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .218622 .0542858 4.03 0.000 .1122239 .3250202 lgdp | .7468104 .1026651 7.27 0.000 .5455905 .9480302 lgdpau | -.499068 .6404911 -0.78 0.436 -1.754408 .7562714 lgdpdfrati~w | -.2915824 .2711341 -1.08 0.282 -.8229954 .2398307 lpopau | 2.704849 2.206215 1.23 0.220 -1.619253 7.028951 lpop | -.3324576 .1434559 -2.32 0.020 -.6136259 -.0512892 lxrate1 | -.1340064 .0308294 -4.35 0.000 -.1944309 -.0735819 lremote | .0624607 .2276826 0.27 0.784 -.383789 .5087105 ldist | -3.035253 .6797898 -4.46 0.000 -4.367617 -1.70289 lopen | .0337928 .0644372 0.52 0.600 -.0925019 .1600875 english | -.5481728 .4252831 -1.29 0.197 -1.381712 .2853666 white | 19.69186 4.037298 4.88 0.000 11.7789 27.60482 lwhitemg | -1.798818 .3718793 -4.84 0.000 -2.527688 -1.069948 _cons | -12.36373 21.7854 -0.57 0.570 -55.06233 30.33487 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002947 lgdp | -.002367 .01054 lgdpau | .000933 -.000759 .410229 lgdpdfrati~w | -.001666 .003213 -.008472 .073514 lpopau | -.007469 -.0021 -1.36465 .052863 4.86738 lpop | -.000198 -.007472 -.001621 -.00153 -.004886 .02058 lxrate1 | .00013 .000511 .001917 .001123 -.009978 -.000767 .00095 lremote | .000795 .00411 -.01918 -.011836 .038393 -.002763 .000545 ldist | .012471 .010308 -.004581 -.003125 -.053111 .003329 .000681 lopen | .000454 -.001021 -.000925 -.000122 -.010164 .001843 -.000192 english | -.006307 .002061 .002428 .005331 -.014704 .017322 .000767 white | .007082 -.033894 .11446 .020831 -.309528 .069705 .005128 lwhitemg | -.001353 .001455 -.012142 -.003133 .036812 -.005263 -.000589 _cons | .018176 -.192193 12.1255 -.641456 -44.6514 -.039124 .098978</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .051839 ldist | .028181 .462114 lopen | .000615 .003323 .004152 english | -.003253 .120821 -.001608 .180866 white | .026651 .238152 .004768 .281131 16.2998 lwhitemg | -.000072 -.037826 -.000327 -.030091 -1.47467 .138294 _cons | -.900393 -4.0157 .151681 -1.28011 -.877722 .138947 474.604</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1106.44 Log likelihood = -566.7942 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2259065 .0483323 4.67 0.000 .131177 .3206361 lgdp | .5741992 .1040149 5.52 0.000 .3703338 .7780646 lgdpau | 1.171778 .7189799 1.63 0.103 -.2373963 2.580953 lgdpdfrati~w | -.0273712 .3063749 -0.09 0.929 -.627855 .5731125 lpopau | -5.134419 2.490345 -2.06 0.039 -10.01541 -.2534315 lpop | .5003614 .1299591 3.85 0.000 .2456462 .7550766 lxrate1 | -.0991497 .0330371 -3.00 0.003 -.1639013 -.0343981 lremote | -.4244055 .2612232 -1.62 0.104 -.9363935 .0875825 ldist | -2.232071 .4386393 -5.09 0.000 -3.091788 -1.372353 lopen | -.0821202 .0743588 -1.10 0.269 -.2278607 .0636203 english | 1.049964 .3256832 3.22 0.001 .4116362 1.688291 white | 22.92503 3.073865 7.46 0.000 16.90036 28.94969 lwhitemg | -2.223663 .2733613 -8.13 0.000 -2.759441 -1.687884 _cons | 61.52538 23.86091 2.58 0.010 14.75884 108.2919 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002336 lgdp | -.002057 .010819 lgdpau | -.002421 .006546 .516932 lgdpdfrati~w | -.002247 .005037 -.018324 .093866 lpopau | .007144 -.042123 -1.73277 .055519 6.20182 lpop | .000312 -.009001 -.00435 -.004341 .02151 .016889 lxrate1 | .000079 .00082 .000118 .001889 -.005556 -.000999 .001091 lremote | .000735 .003243 -.010643 -.022783 .024116 -.001351 -.000153 ldist | .008372 -.004205 -.010338 -.004975 .000564 .015464 .000669 lopen | .000232 .00007 .001249 .003106 -.016457 .001206 -.00008 english | -.003392 .002774 .004285 .007685 -.021554 -.001194 .001023 white | .007633 -.036693 .033872 -.0235 -.070512 .061194 .004965 lwhitemg | -.001009 .001183 -.004731 -.000216 .017522 -.003934 -.000588 _cons | -.109418 .441479 15.326 -.324268 -57.1344 -.437639 .075631</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .068238 ldist | .012068 .192404 lopen | .001488 .001787 .005529 english | -.011434 .05795 -.00191 .10607 white | .043457 .05559 .004235 .002888 9.44865 lwhitemg | -.000139 -.008214 -.000502 .000955 -.824504 .074726 _cons | -.863266 -1.87538 .189232 -.270054 -.830518 -.043557 569.343</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1566.51 Log likelihood = -751.1944 Prob > chi2 = 0.0000</p><p>------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0655857 .0345308 1.90 0.058 -.0020933 .1332648 lgdp | 1.009729 .0961518 10.50 0.000 .821275 1.198183 lgdpau | 1.01497 .7074211 1.43 0.151 -.3715495 2.40149 lgdpdfrati~w | -.1143451 .2738876 -0.42 0.676 -.6511548 .4224647 lpopau | 2.93815 2.458215 1.20 0.232 -1.879862 7.756163 lpop | -.449501 .1405272 -3.20 0.001 -.7249293 -.1740726 lxrate1 | -.1518669 .0222595 -6.82 0.000 -.1954948 -.108239 lremote | -.4225046 .2251998 -1.88 0.061 -.8638881 .0188789 ldist | -1.812887 .746265 -2.43 0.015 -3.27554 -.350235 lopen | -.0582184 .0728458 -0.80 0.424 -.2009936 .0845568 english | .1320527 .3346648 0.39 0.693 -.5238783 .7879838 white | 28.59197 2.676341 10.68 0.000 23.34644 33.8375 lwhitemg | -2.664377 .2581362 -10.32 0.000 -3.170315 -2.158439 _cons | -67.37182 24.56685 -2.74 0.006 -115.522 -19.22167 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001192 lgdp | -.001755 .009245 lgdpau | .000307 .002284 .500445 lgdpdfrati~w | -.001752 .004359 -.014031 .075014 lpopau | -.0075 -.013063 -1.66495 .050645 6.04282 lpop | .001635 -.011101 -.004468 -.003933 .028592 .019748 lxrate1 | .000039 .000301 .000266 .000768 -.008548 -.000676 .000495 lremote | .000426 .002675 -.028557 -.006203 .048213 -.002843 .000507 ldist | .007659 .013887 -.013601 .000127 -.087125 .009896 .001096 lopen | .000365 -.000785 .000386 .004812 -.009666 .001229 -.000337 english | -.001259 .002511 .000308 .002456 -.003454 .000517 .000869 white | .014026 -.059843 -.016697 -.037911 -.246907 .069554 .00913 lwhitemg | -.001416 .003943 -.001847 .002465 .036455 -.005034 -.000858 _cons | .049491 -.029216 14.9041 -.521888 -56.3315 -.488182 .120637</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .050715 ldist | .048986 .556911 lopen | .000125 .002536 .005307 english | .003652 .063153 -.00165 .112001 white | .083101 .046093 -.009492 .216343 7.1628 lwhitemg | -.004381 -.014703 .000955 -.02352 -.678062 .066634 _cons | -.980422 -4.46325 .122277 -.661535 3.51982 -.377505 603.53</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 547.88 Log likelihood = -568.4741 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4420544 .0601044 7.35 0.000 .3242519 .559857 lgdp | .2620293 .0992822 2.64 0.008 .0674398 .4566187 lgdpau | 1.100231 .7446167 1.48 0.140 -.3591911 2.559653 lgdpdfrati~w | -.4754869 .3194391 -1.49 0.137 -1.101576 .1506022 lpopau | -4.614111 2.571369 -1.79 0.073 -9.653901 .425679 lpop | .2991743 .1056793 2.83 0.005 .0920468 .5063019 lxrate1 | -.0714386 .0345587 -2.07 0.039 -.1391724 -.0037049 lremote | -.2280546 .2351349 -0.97 0.332 -.6889105 .2328013 ldist | -1.245248 .572647 -2.17 0.030 -2.367615 -.1228804 lopen | .0920538 .0723611 1.27 0.203 -.0497714 .233879 english | -.1503734 .2798894 -0.54 0.591 -.6989465 .3981998 white | 18.97312 2.048802 9.26 0.000 14.95755 22.9887 lwhitemg | -1.825047 .1958155 -9.32 0.000 -2.208838 -1.441255 _cons | 53.47414 24.36916 2.19 0.028 5.711472 101.2368 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003613 lgdp | -.003227 .009857 lgdpau | -.002254 .006551 .554454 lgdpdfrati~w | -.002286 .005949 -.008758 .102041 lpopau | .005054 -.035412 -1.8541 .048371 6.61194 lpop | .000956 -.006407 -.004541 -.00447 .012634 .011168 lxrate1 | .000368 .000468 -.000115 .000958 -.004308 -.000685 .001194 lremote | -.000502 .002979 -.010798 -.018683 .002494 .001587 .001215 ldist | .01173 .000156 -.006286 -.011167 -.064256 .006518 .000643 lopen | -.000359 .000884 .002139 -.000111 -.023207 .001613 -.000145 english | -.004017 .006824 .005429 .001564 -.023151 -.000134 -.001656 white | .021655 -.040079 -.009532 -.074958 .105207 .017259 -.001482 lwhitemg | -.002631 .002311 -.001144 .004395 .001695 -.000427 -.000227 _cons | -.094772 .278566 16.3133 -.457511 -59.9689 -.198877 .052817</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .055288 ldist | .035099 .327925 lopen | .002503 .003091 .005236 english | .008536 .086848 -.000114 .078338 white | .118554 .207387 -.008343 .143196 4.19759 lwhitemg | -.007817 -.02993 .000775 -.016479 -.3918 .038344 _cons | -.65596 -2.37266 .238982 -.800089 -3.9935 .327253 593.856</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1531.31 Log likelihood = -242.2113 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0042793 .0228777 0.19 0.852 -.0405602 .0491188 lgdp | .4391276 .0819722 5.36 0.000 .2784651 .5997901 lgdpau | -.3241993 .4922563 -0.66 0.510 -1.289004 .6406052 lgdpdfrati~w | .1773169 .2237387 0.79 0.428 -.2612028 .6158366 lpopau | 1.198482 1.698868 0.71 0.481 -2.131238 4.528202 lpop | -.2323772 .1158194 -2.01 0.045 -.459379 -.0053754 lxrate1 | -.0402512 .0226815 -1.77 0.076 -.0847062 .0042037 lremote | -.0647559 .169257 -0.38 0.702 -.3964935 .2669818 ldist | -3.861632 .5195635 -7.43 0.000 -4.879958 -2.843306 lopen | .0128867 .0499615 0.26 0.796 -.085036 .1108094 english | -.0163697 .3022435 -0.05 0.957 -.6087561 .5760166 white | 16.03595 2.614341 6.13 0.000 10.91193 21.15996 lwhitemg | -1.167722 .2810891 -4.15 0.000 -1.718647 -.6167976 _cons | 21.06517 17.01823 1.24 0.216 -12.28994 54.42027 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000523 lgdp | -.000669 .006719 lgdpau | .000196 -.002087 .242316 lgdpdfrati~w | -.000837 .002465 -.009476 .050059 lpopau | -.001589 .000203 -.808919 .049496 2.88615 lpop | .000258 -.006157 .000125 -.000983 -.002758 .013414 lxrate1 | -.000023 .000181 .001354 .001037 -.006523 -.000541 .000514 lremote | .000103 .002222 -.016867 -.003796 .049393 -.002935 -.000114 ldist | .002296 .003591 -.010035 -.000878 -.015658 .018315 -.000371 lopen | .000045 -.000114 -.002124 .001118 .002554 .000823 -.000042 english | -.001084 .000447 .00177 .001763 -.002587 .004433 .000614 white | .004354 -.036555 .048084 -.011314 -.295683 .061451 .002305 lwhitemg | -.000472 .001507 -.00577 .000305 .03612 -.004947 -.000062 _cons | .007937 -.053588 7.35165 -.62244 -26.9309 -.178593 .078349</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .028648 ldist | .012594 .269946 lopen | .000152 .000902 .002496 english | .000218 .061453 3.9e-06 .091351 white | -.00377 .155508 -.001828 .109629 6.83478 lwhitemg | .002989 -.020241 .000234 -.011095 -.724791 .079011 _cons | -.748948 -2.56056 -.006819 -.685027 2.0055 -.234466 289.62 . . clear</p><p>. insheet using k:\book1.txt (104 vars, 1010 obs)</p><p>. *Dropping Indonesia . drop if ccode==453560 (10 observations deleted)</p><p>. . . . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist op > en english gdpdfrationew white whitemg, stat(n mean sd median min max) col(sta > t) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 480733.9 1560783 7348 0 1.39e+07 immig | 1000 33046.77 117081.5 2790 0 1137050 gdp | 1000 2.77e+11 9.70e+11 1.63e+10 1.92e+08 8.99e+12 gdpau | 1000 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 1000 105.497 16.5633 102.6773 60.87417 184.0119 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.77e+07 1.53e+08 1.02e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1018.645 10900.02 13.89535 .0068 270182.6 remote | 1000 6713.199 4138.674 6764 1293 39620 dist | 1000 13450.01 3438.651 14305 2409 17972 open | 1000 .7101332 .3894539 .63885 .0671 3.2192 english | 1000 .37 .4830459 0 0 1 gdpdfratio~w | 1000 1.050534 .1784156 1.013736 .5844526 1.94877 white | 1000 .13 .3364717 0 0 1 whitemg | 1000 20501.65 116468.1 0 0 1137050 ------</p><p>. . sort white</p><p>. *IIIB. Descriptives Original Unites(sub sample for "white" and "non-white" cou > ntries)--RHS Variables: . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remo > te dist phone open english gdpdfrationew white whitemg, stat(n mean sd median > min max) col(stat) </p><p>------> white = 0</p><p> variable | N mean sd p50 min max ------+------rimp | 870 392919.6 1596471 2944.5 0 1.39e+07 immig | 870 14419.67 27010.31 1403.5 0 158613 gdp | 870 2.35e+11 1.00e+12 1.00e+10 1.92e+08 8.99e+12 gdpau | 870 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 870 104.5943 16.86464 101.6138 60.87417 184.0119 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.13e+07 1.64e+08 1.03e+07 41000 1.26e+09 popau | 870 1.82e+07 612839.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 870 1154.863 11680.26 19.96485 .0068 270182.6 remote | 870 7135.663 4110.863 6927 1293 39620 dist | 870 13292.43 3314.92 14051 2410 17972 phone | 870 159.1009 241.9731 49.795 .54 1449.75 open | 870 .717833 .4108799 .63875 .0671 3.2192 english | 870 .3793103 .4854945 0 0 1 gdpdfratio~w | 870 1.041802 .1828736 1 .5844526 1.94877 white | 870 0 0 0 0 0 whitemg | 870 0 0 0 0 0 ------</p><p>------> white = 1</p><p> variable | N mean sd p50 min max ------+------rimp | 130 1068414 1138347 522863.5 40432 3843839 immig | 130 157705 288518.8 21174 2612 1137050 gdp | 130 5.56e+11 6.58e+11 2.54e+11 5.15e+10 2.69e+12 gdpau | 130 3.83e+11 4.46e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 130 111.5379 12.89742 112.2247 85.45601 143.9587 gdpdfau | 130 100.7173 4.649088 100.8223 94.42464 109.9797 pop | 130 2.34e+07 2.55e+07 8837000 3477200 8.22e+07 popau | 130 1.82e+07 614856.7 1.82e+07 1.73e+07 1.92e+07 xrate1 | 130 107.0323 293.6987 4.4722 .3774 1261.556 remote | 130 3885.938 3089.96 2888 1530 12501 dist | 130 14504.62 4031.974 15931 2409 17493 phone | 130 734.716 269.9717 652.085 343.99 1487.08 open | 130 .6586038 .1850905 .64065 .3517 1.2967 english | 130 .3076923 .4633239 0 0 1 gdpdfratio~w | 130 1.108974 .1314272 1.116445 .8254872 1.441221 white | 130 1 0 1 1 1 whitemg | 130 157705 288518.8 21174 2612 1137050 ------</p><p>. . . . **Regression of Imports . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . . **I. Aggregate Imports . xtgls lrimp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 9132.66 Log likelihood = -546.7767 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3344265 .0308187 10.85 0.000 .2740229 .3948301 lgdp | 1.197077 .0331448 36.12 0.000 1.132115 1.26204 lgdpau | .1296837 .5972609 0.22 0.828 -1.040926 1.300294 lgdpdfrati~w | -1.036727 .2496679 -4.15 0.000 -1.526067 -.5473871 lpopau | -2.484968 2.060065 -1.21 0.228 -6.522621 1.552685 lpop | -.0071285 .0426965 -0.17 0.867 -.0908122 .0765551 lxrate1 | -.1339624 .016662 -8.04 0.000 -.1666193 -.1013055 lremote | -.3915755 .0778987 -5.03 0.000 -.5442541 -.2388969 ldist | -2.026915 .1586052 -12.78 0.000 -2.337776 -1.716055 lopen | .2555495 .0560243 4.56 0.000 .1457439 .3653552 english | .8301979 .1333792 6.22 0.000 .5687795 1.091616 white | 4.336572 .5694161 7.62 0.000 3.220537 5.452607 lwhitemg | -.4055836 .0504282 -8.04 0.000 -.504421 -.3067461 _cons | 39.51179 18.97477 2.08 0.037 2.321929 76.70165 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00095 lgdp | -.0003 .001099 lgdpau | -.000976 .001334 .356721 lgdpdfrati~w | -.000901 .000084 -.007945 .062334 lpopau | .002191 -.007932 -1.20592 .045159 4.24387 lpop | -.000163 -.00077 .000306 .000594 -.000842 .001823 lxrate1 | .000077 .00015 .000438 .000283 -.002725 -.000055 .000278 lremote | .000536 .000116 -.000808 -.002276 -.00223 -.000513 -8.5e-06 ldist | .001712 .001125 .000415 -.002133 -.01413 -.000608 .001455 lopen | -.000199 .000576 .002457 .00112 -.01661 .000494 .000187 english | -.001293 .00273 .003612 .00307 -.012434 -.000966 .000737 white | .004337 -.002048 .00401 -.007811 -.026982 .006185 .00073 lwhitemg | -.000543 .000187 -.000339 .000764 .002815 -.000494 -.000083 _cons | -.028381 .071604 10.6273 -.572541 -38.4818 .006457 .015509</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .006068 ldist | .005554 .025156 lopen | .001211 .000831 .003139 english | -.004024 .001531 -.000479 .01779 white | -.002488 -.003224 .000468 .005025 .324235 lwhitemg | .000301 -.000252 -.000112 -.000235 -.028261 .002543 _cons | -.039976 -.093174 .173155 .077371 .30173 -.029857 360.042</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 78808.06 Log likelihood = -978.7231 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0506532 .0135226 3.75 0.000 .0241495 .077157 lgdp | 1.67324 .0488425 34.26 0.000 1.577511 1.76897 lgdpau | .8850739 .3493839 2.53 0.011 .200294 1.569854 lgdpdfrati~w | -.5103122 .1457128 -3.50 0.000 -.7959039 -.2247204 lpopau | -6.245437 1.180396 -5.29 0.000 -8.558971 -3.931904 lpop | -.4741722 .0815932 -5.81 0.000 -.6340919 -.3142526 lxrate1 | -.1270311 .0205339 -6.19 0.000 -.1672768 -.0867854 lremote | -.9049371 .093857 -9.64 0.000 -1.088893 -.7209807 ldist | -2.940946 .1521253 -19.33 0.000 -3.239107 -2.642786 lopen | -.06234 .0262106 -2.38 0.017 -.1137117 -.0109683 english | .9521092 .0860557 11.06 0.000 .7834432 1.120775 white | 3.861625 .7662694 5.04 0.000 2.359765 5.363485 lwhitemg | -.3925014 .0732356 -5.36 0.000 -.5360406 -.2489622 _cons | 90.55332 11.08644 8.17 0.000 68.8243 112.2823 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000183 lgdp | -.000241 .002386 lgdpau | -.001168 .001719 .122069 lgdpdfrati~w | -.000568 .000496 -.011359 .021232 lpopau | .004621 -.006829 -.403455 .02229 1.39333 lpop | .000144 -.003762 -.001462 .000517 .003719 .006657 lxrate1 | -.000027 .000257 -.000063 .000436 -.003202 -.00026 .000422 lremote | .000392 .000171 -.006346 -.003227 .022972 -.000971 .000031 ldist | .00068 -.002948 -.006078 -.000472 .014268 .004974 .000488 lopen | .000041 -.000087 -.00096 .000904 .003562 .000236 -.000076 english | -.000402 .00019 .002917 .002727 -.020095 .000392 .001157 white | .001002 -.010739 -.010778 -.00367 .038892 .016514 -.000577 lwhitemg | -.000082 .000491 .00046 .000193 -.002459 -.000674 .000101 _cons | -.052984 .100017 3.60457 -.07684 -12.8056 -.082296 .046344</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .008809 ldist | .001743 .023142 lopen | .000612 .000304 .000687 english | -.002731 .002846 -.000405 .007406</p><p> white | .008295 -.004794 .001539 -.001266 .587169 lwhitemg | -.000108 .00155 -.00011 .000343 -.054603 .005363 _cons | -.295913 -.332673 -.044527 .237385 -.403067 .01383 122.909</p><p>. . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7929.75 Log likelihood = -944.4683 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .158728 .0264878 5.99 0.000 .1068129 .210643 lgdp | 1.725849 .0708 24.38 0.000 1.587084 1.864615 lgdpau | -.0439947 .5975751 -0.07 0.941 -1.21522 1.127231 lgdpdfrati~w | -.4677339 .2435489 -1.92 0.055 -.945081 .0096133 lpopau | -2.053878 2.08829 -0.98 0.325 -6.146852 2.039096 lpop | -.6625021 .0822729 -8.05 0.000 -.8237541 -.5012501 lxrate1 | -.1705445 .028007 -6.09 0.000 -.2254373 -.1156517 lremote | -.3407898 .1327903 -2.57 0.010 -.601054 -.0805257 ldist | -3.320111 .356115 -9.32 0.000 -4.018083 -2.622138 lopen | .0762079 .0459937 1.66 0.098 -.013938 .1663538 english | .7940889 .14606 5.44 0.000 .5078166 1.080361 white | 8.855036 1.890639 4.68 0.000 5.149451 12.56062 lwhitemg | -.7678 .1894829 -4.05 0.000 -1.13918 -.3964204 _cons | 45.46043 19.98748 2.27 0.023 6.285685 84.63518 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000702 lgdp | -.001111 .005013 lgdpau | -.002251 .00456 .357096 lgdpdfrati~w | -.000992 .002563 -.023036 .059316 lpopau | .006478 -.021236 -1.21282 .084796 4.36096 lpop | .000762 -.0043 -.001977 -.002256 .006286 .006769 lxrate1 | .000042 .000525 .000265 .000947 -.005907 -.000829 .000784 lremote | -.000015 -.000151 -.00712 -.001398 .021873 -.001873 .000107 ldist | .003253 .006173 -.01491 -.002679 .008623 -.003013 .001196 lopen | .000117 -.00063 .00023 .002109 -.000617 .00114 -.000242 english | -.001186 .003156 .008148 .001003 -.048347 .001516 .001873 white | .001333 -.028778 .0172 -.006146 -.057634 .026168 .003985 lwhitemg | -.000088 .001671 -.002841 -.000016 .011025 -.0019 -.000428 _cons | -.068615 .131896 10.9193 -.844179 -40.5434 -.015722 .075661</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .017633 ldist | .011788 .126818 lopen | .000461 -.000969 .002115 english | -.006354 -.003229 -.001667 .021334 white | .003847 -.169926 .002679 .025942 3.57452 lwhitemg | .00158 .014698 -.000181 -.003303 -.351726 .035904 _cons | -.410516 -1.17374 .005355 .573714 2.29899 -.267814 399.5</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2602.98 Log likelihood = -1095.429 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0896262 .0391713 2.29 0.022 .0128519 .1664006 lgdp | .9677747 .0793903 12.19 0.000 .8121727 1.123377 lgdpau | -.2922241 .7900492 -0.37 0.711 -1.840692 1.256244 lgdpdfrati~w | -.4283251 .3319124 -1.29 0.197 -1.078861 .2222112 lpopau | -.196991 2.715117 -0.07 0.942 -5.518522 5.12454 lpop | -.0322458 .0952835 -0.34 0.735 -.218998 .1545063 lxrate1 | -.1429047 .0331453 -4.31 0.000 -.2078682 -.0779412 lremote | .556396 .223354 2.49 0.013 .1186302 .9941617 ldist | -1.535294 .3295158 -4.66 0.000 -2.181133 -.8894551 lopen | .3098901 .0787245 3.94 0.000 .1555928 .4641873 english | 1.54066 .2260538 6.82 0.000 1.097603 1.983718 white | 1.476603 2.139793 0.69 0.490 -2.717314 5.67052 lwhitemg | .1904576 .1857766 1.03 0.305 -.1736579 .5545731 _cons | 2.251508 25.8809 0.09 0.931 -48.47412 52.97714 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001534 lgdp | -.001477 .006303 lgdpau | -.001672 .001949 .624178 lgdpdfrati~w | -.000158 .000878 -.007935 .110166 lpopau | .0031 -.009993 -2.0947 .035404 7.37186 lpop | .000377 -.005515 -.000439 -.000667 -.001426 .009079 lxrate1 | .000092 .000891 .000583 .001523 -.006763 -.001131 .001099 lremote | .001204 .000249 -.022605 -.015471 .070052 .001284 -.000877 ldist | .003885 -.007654 -.018636 -.006149 .061048 .011465 -.000442 lopen | .000283 -.001182 .005716 .001796 -.030589 .002919 -.000181 english | -.003045 .001111 .006003 .004106 -.004616 -.002593 .001695 white | .003759 -.022535 .089826 .001394 -.360968 .017196 .001028 lwhitemg | -.000506 .000684 -.009358 -.0014 .038768 .000172 -.00024 _cons | -.034139 .135837 18.7298 -.310545 -68.3751 -.102199 .100544</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .049887 ldist | .019183 .108581 lopen | .001702 -.001065 .006198 english | -.010784 .015912 -.002085 .0511 white | .041775 -.020643 .007132 .028085 4.57871 lwhitemg | -.001177 .005914 -.000436 -.001405 -.387189 .034513 _cons | -1.199 -1.75642 .335537 -.133124 3.66601 -.458232 669.821</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 60844.79 Log likelihood = -911.8971 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .025224 .0133443 1.89 0.059 -.0009304 .0513784 lgdp | 1.584092 .0528376 29.98 0.000 1.480532 1.687652 lgdpau | .7287046 .3538521 2.06 0.039 .0351672 1.422242 lgdpdfrati~w | -.2901081 .1366145 -2.12 0.034 -.5578676 -.0223486 lpopau | -6.770709 1.197971 -5.65 0.000 -9.118689 -4.422728 lpop | -.2196962 .0918331 -2.39 0.017 -.3996858 -.0397066 lxrate1 | -.048557 .0188781 -2.57 0.010 -.0855574 -.0115566 lremote | -.6560747 .1488453 -4.41 0.000 -.9478062 -.3643433 ldist | -2.524686 .1655648 -15.25 0.000 -2.849187 -2.200185 lopen | -.0544341 .0270119 -2.02 0.044 -.1073765 -.0014917 english | 1.135334 .1127081 10.07 0.000 .9144297 1.356237 white | 3.470622 .8910957 3.89 0.000 1.724107 5.217137 lwhitemg | -.2678626 .0827471 -3.24 0.001 -.4300439 -.1056813 _cons | 94.86697 11.33207 8.37 0.000 72.65653 117.0774 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000178 lgdp | -.000187 .002792 lgdpau | -.00083 .001898 .125211 lgdpdfrati~w | -.00034 .000685 -.00754 .018664 lpopau | .002996 -.006365 -.415034 .011661 1.43514 lpop | .000113 -.004573 -.001651 .000066 .002655 .008433 lxrate1 | 8.3e-07 .0002 -.00006 .000478 -.002676 -.000202 .000356 lremote | -.000027 -.000806 -.013186 -.00482 .048543 -.000027 -.000231 ldist | .000809 -.00534 -.003801 .001416 .001763 .009612 .000661 lopen | .000017 -.000093 -.00099 .00087 .003595 .000263 -.000072 english | -.000309 -.000228 .003499 .00287 -.018912 .000098 .000996 white | .000574 -.016583 -.014727 -.000629 .020723 .029678 .002063 lwhitemg | -.000097 .000816 -.00006 -.000432 .00294 -.001662 -.000219 _cons | -.033484 .122787 3.74631 -.000957 -13.279 -.121935 .038609</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .022155 ldist | -.003447 .027412 lopen | .001111 .000224 .00073 english | -.004613 .006273 -.000493 .012703 white | .013182 .034558 .001027 .0071 .794051 lwhitemg | .001259 -.00234 .000011 -.000537 -.070569 .006847 _cons | -.596673 -.201919 -.04808 .198425 -.506728 -.02667 128.416</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8377.14 Log likelihood = -970.8747 Prob > chi2 = 0.0000</p><p>------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2486739 .0314081 7.92 0.000 .1871153 .3102326 lgdp | 1.593757 .0706408 22.56 0.000 1.455303 1.73221 lgdpau | -.2331274 .5942879 -0.39 0.695 -1.39791 .9316554 lgdpdfrati~w | -.2609343 .2602609 -1.00 0.316 -.7710363 .2491677 lpopau | -.9763655 2.082484 -0.47 0.639 -5.057959 3.105228 lpop | -.539227 .0816396 -6.60 0.000 -.6992377 -.3792164 lxrate1 | -.1498434 .0276466 -5.42 0.000 -.2040296 -.0956571 lremote | -.2903862 .1222007 -2.38 0.017 -.5298951 -.0508773 ldist | -2.692291 .3502522 -7.69 0.000 -3.378773 -2.00581 lopen | .0982425 .0491732 2.00 0.046 .0018648 .1946202 english | .7500494 .1487737 5.04 0.000 .4584583 1.04164 white | 9.636434 1.878371 5.13 0.000 5.954895 13.31797 lwhitemg | -.843716 .1875269 -4.50 0.000 -1.211262 -.4761701 _cons | 26.3425 19.88216 1.32 0.185 -12.62581 65.31081 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000986 lgdp | -.001452 .00499 lgdpau | -.00189 .003273 .353178 lgdpdfrati~w | -.001269 .002727 -.023001 .067736 lpopau | .005278 -.017564 -1.20085 .091858 4.33674 lpop | .000827 -.004247 -.001153 -.001713 .00708 .006665 lxrate1 | .000071 .000352 -.000156 .001099 -.004472 -.000635 .000764 lremote | .000127 -.000341 -.003975 -.001295 .006798 -.001456 .00005 ldist | .004798 .001691 -.012948 -.005136 -.004846 -.001045 .000937 lopen | .000154 -.000753 .001518 .001808 -.007279 .001369 -.000306 english | -.001765 .003418 .003407 .004302 -.021377 .000935 .001979 white | -.000504 -.025707 .017578 .003907 -.011303 .02375 .004742 lwhitemg | .00012 .001532 -.002439 -.000885 .004546 -.001704 -.000456 _cons | -.068725 .150818 10.7947 -.961981 -40.308 -.073937 .066337</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .014933 ldist | .011721 .122677 lopen | .000354 -.00107 .002418 english | -.005894 -.009423 -.001928 .022134 white | .002503 -.19223 .002919 .033644 3.52828 lwhitemg | .001442 .018066 -.000209 -.003812 -.346495 .035166 _cons | -.220877 -.894396 .083976 .306397 1.70418 -.20111 395.3</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8012.18 Log likelihood = -1117.663 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0272098 .0166509 1.63 0.102 -.0054253 .0598449 lgdp | 1.366324 .0514126 26.58 0.000 1.265557 1.467091 lgdpau | .3847505 .5356319 0.72 0.473 -.6650687 1.43457 lgdpdfrati~w | -.0921347 .1801449 -0.51 0.609 -.4452122 .2609429 lpopau | -4.735326 1.81976 -2.60 0.009 -8.30199 -1.168662 lpop | .0374978 .0746464 0.50 0.615 -.1088064 .183802 lxrate1 | -.0724908 .0213807 -3.39 0.001 -.1143962 -.0305855 lremote | -.8943535 .1680117 -5.32 0.000 -1.22365 -.5650566 ldist | -3.249526 .2270418 -14.31 0.000 -3.69452 -2.804533 lopen | .0919103 .0451203 2.04 0.042 .0034762 .1803444 english | 2.316465 .1502622 15.42 0.000 2.021957 2.610974 white | 3.678235 1.149271 3.20 0.001 1.425705 5.930765 lwhitemg | -.1713654 .096334 -1.78 0.075 -.3601765 .0174458 _cons | 78.81245 17.38295 4.53 0.000 44.7425 112.8824 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000277 lgdp | -.000447 .002643 lgdpau | -.000287 .000214 .286902 lgdpdfrati~w | -.000574 .000708 .00228 .032452 lpopau | -.000809 .001349 -.952393 -.005819 3.31153 lpop | .000204 -.002936 -.000145 .000224 -.003349 .005572 lxrate1 | -.000029 .000258 .000518 .000768 -.003188 -.000417 .000457 lremote | .000292 .000786 -.0191 -.002314 .059483 -.001444 -.000311 ldist | .000754 .000451 -.013867 -.002639 .033726 -.000939 .000104 lopen | .000083 -.000368 -.000201 .002081 .000912 .000813 -.00015 english | -.000907 .000481 .004109 .00254 -.014934 .002088 .001276 white | .000264 -.014246 .000668 .000398 -.013156 .027043 .000159 lwhitemg | 5.2e-06 .000759 -.001401 5.6e-06 .005009 -.001867 .000046 _cons | .017887 -.05115 8.56659 .029775 -30.7633 .058103 .038963</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .028228 ldist | .020219 .051548 lopen | .000996 .000044 .002036 english | -.005392 .000205 -.001501 .022579 white | -.001157 -.013233 .000953 .041483 1.32082 lwhitemg | .001953 .003562 -.000012 -.003771 -.10697 .00928 _cons | -.918819 -.864607 -.024022 .131767 .21056 -.084527 302.167</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 447.98 Log likelihood = -644.853 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4970358 .0544329 9.13 0.000 .3903494 .6037222 lgdp | .0543863 .0917998 0.59 0.554 -.125538 .2343105 lgdpau | -.4173677 .7321337 -0.57 0.569 -1.852323 1.017588 lgdpdfrati~w | -.2608501 .2524954 -1.03 0.302 -.755732 .2340318 lpopau | -.0758425 2.495406 -0.03 0.976 -4.966748 4.815063 lpop | .2551975 .0960636 2.66 0.008 .0669164 .4434786 lxrate1 | -.0925395 .027138 -3.41 0.001 -.1457289 -.03935 lremote | .2881258 .2539145 1.13 0.256 -.2095376 .7857891 ldist | -2.246813 .5717058 -3.93 0.000 -3.367336 -1.12629 lopen | .0660891 .0593631 1.11 0.266 -.0502605 .1824387 english | .6883317 .2515381 2.74 0.006 .1953261 1.181337 white | 12.44984 .9609598 12.96 0.000 10.56639 14.33328 lwhitemg | -1.153311 .0951843 -12.12 0.000 -1.339869 -.9667532 _cons | 29.20106 24.00556 1.22 0.224 -17.84897 76.25109 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002963 lgdp | -.001573 .008427 lgdpau | -.000631 -.00008 .53602 lgdpdfrati~w | -.001319 .002427 -.007078 .063754 lpopau | -.002031 -.012783 -1.77232 .018569 6.22705 lpop | -.000186 -.005511 -.000905 -.0013 .007312 .009228 lxrate1 | .000117 .000022 .000367 .001555 -.004861 -.000525 .000736 lremote | .003105 .004479 -.027445 -.008744 .062539 -.003839 .0007 ldist | .01084 -.009761 -.026515 -.002686 .008364 .014168 .002159 lopen | -.00057 .002082 -.002062 -.000256 -.00246 -.000208 -.000081 english | -.000154 .000873 .005618 .007084 -.036361 .005432 .001155 white | .015909 -.019473 .005126 -.001508 -.050845 .023293 .004323 lwhitemg | -.001571 .000321 -.002266 -.000544 .012299 -.001155 -.000275 _cons | -.061449 .170089 15.8514 -.119364 -57.2482 -.215434 .046826</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .064473 ldist | .053415 .326847 lopen | .001188 -.001894 .003524 english | -.008973 .008293 .000232 .063271 white | .021279 -.036972 -.004035 .085549 .923444 lwhitemg | .000752 .008369 -8.5e-06 -.00689 -.085819 .00906 _cons | -1.44233 -3.10673 .064644 .30622 .772595 -.204021 576.267</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3977.01 Log likelihood = -593.6717 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1266923 .0274164 4.62 0.000 .0729572 .1804275 lgdp | .2104699 .0473927 4.44 0.000 .117582 .3033578 lgdpau | -.0940067 .0511231 -1.84 0.066 -.1942061 .0061928 lgdpdfrati~w | -.1092723 .0344096 -3.18 0.001 -.1767138 -.0418308 lpopau | 2.673855 .218964 12.21 0.000 2.244694 3.103017 lpop | .8277703 .0974713 8.49 0.000 .6367302 1.018811 lxrate1 | -.0118021 .0066305 -1.78 0.075 -.0247976 .0011935 lremote | .1332294 .027212 4.90 0.000 .0798947 .186564 ldist | -3.301477 .3365547 -9.81 0.000 -3.961112 -2.641842 lopen | .003174 .0250385 0.13 0.899 -.0459005 .0522485 english | .8165757 .2794046 2.92 0.003 .2689528 1.364199 white | 24.33197 2.970209 8.19 0.000 18.51047 30.15348 lwhitemg | -2.243427 .2755067 -8.14 0.000 -2.78341 -1.703443 _cons | -24.19503 4.788843 -5.05 0.000 -33.58099 -14.80907 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000752 lgdp | -.000374 .002246 lgdpau | -.000533 -.000441 .002614 lgdpdfrati~w | .000251 -.000903 .000542 .001184 lpopau | .003744 .000323 -.009247 .000264 .047945 lpop | -.000259 -.001951 .00118 .000482 -.003782 .009501 lxrate1 | .000012 .000058 -.000037 .000022 .000467 -.000181 .000044 lremote | -.00024 .000946 -.000446 -.000716 .000019 -.000629 .000021 ldist | .002682 -.000249 -.002291 .000158 .018245 -.001764 -.000044 lopen | -.000293 -.000186 .000233 -.000278 -.003119 .000914 -.000114 english | -.00051 -.000191 .000462 .000201 -.005514 -.000839 .000035 white | .002199 -.00505 .001103 .001852 -.001782 .027364 -.000431 lwhitemg | -.000426 .000137 .000138 -.000072 -.001856 -.002842 .000039 _cons | -.06383 -.017829 .104948 -.003704 -.695417 -.049924 -.005319</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .00074 ldist | -.000116 .113269 lopen | .000127 -.000749 .000627 english | -.00021 .055281 -.000025 .078067 white | -.002204 .023951 .001157 .042961 8.82214 lwhitemg | .000094 -.004632 -2.4e-06 -.00332 -.806092 .075904 _cons | -.00344 -1.30994 .044408 -.445568 -.564877 .116159 22.933</p><p>. . </p><p>. **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 499.50 Log likelihood = -555.8705 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5038655 .0500237 10.07 0.000 .4058209 .6019102 lgdp | .0184012 .0779851 0.24 0.813 -.1344469 .1712492 lgdpau | 1.930098 .7869371 2.45 0.014 .3877293 3.472466 lgdpdfrati~w | -.4550641 .2848002 -1.60 0.110 -1.013262 .1031341 lpopau | -9.447321 2.701942 -3.50 0.000 -14.74303 -4.151613 lpop | .3860639 .0982526 3.93 0.000 .1934923 .5786356 lxrate1 | -.0900904 .026503 -3.40 0.001 -.1420353 -.0381455 lremote | .0160296 .2537579 0.06 0.950 -.4813267 .513386 ldist | -1.786536 .3322698 -5.38 0.000 -2.437773 -1.135299 lopen | .0582823 .0540488 1.08 0.281 -.0476513 .1642159 english | .0040724 .225805 0.02 0.986 -.4384973 .446642 white | 9.814357 1.108077 8.86 0.000 7.642565 11.98615 lwhitemg | -.8904651 .0984001 -9.05 0.000 -1.083326 -.6976045 _cons | 119.3352 25.65639 4.65 0.000 69.04956 169.6208 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002502 lgdp | -.001492 .006082 lgdpau | .000425 -.000524 .61927 lgdpdfrati~w | -.001455 .001547 -.016404 .081111 lpopau | -.00565 -.00497 -2.06629 .062888 7.30049 lpop | -.000336 -.004215 -.000585 -.00009 -.00088 .009654 lxrate1 | .000113 -.000147 .000548 .001037 -.004832 -.000289 .000702 lremote | .001623 .004265 -.02344 -.012395 .065333 -.002915 .000401 ldist | .005459 .001031 -.01011 -.005023 -.005197 .002191 .000251 lopen | -.000305 .000776 .000019 -.000124 -.008768 .000649 -.000014 english | -.002224 .001723 .004762 .005417 -.023281 .00036 .00118 white | .012007 -.02514 .016392 -.0012 -.086422 .033426 .006929 lwhitemg | -.001207 .001247 -.002935 -.000667 .01517 -.002062 -.000585 _cons | .03928 -.011971 18.3611 -.56909 -67.3269 -.022313 .063723</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .064393 ldist | .029993 .110403 lopen | .001195 .001876 .002921 english | -.01057 .017842 .000041 .050988 white | .018605 -.016857 -.0017 .026067 1.22784 lwhitemg | .000664 .001818 .000072 -.001635 -.104627 .009683 _cons | -1.3606 -1.04875 .093106 .125087 .887351 -.179235 658.25</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1444.05 Log likelihood = -334.3749 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0327662 .0183935 1.78 0.075 -.0032843 .0688168 lgdp | .2154575 .0586913 3.67 0.000 .1004246 .3304904 lgdpau | -.0755369 .3456832 -0.22 0.827 -.7530635 .6019897 lgdpdfrati~w | -.3662568 .2125988 -1.72 0.085 -.7829428 .0504292 lpopau | 1.581449 1.215136 1.30 0.193 -.8001739 3.963071 lpop | .1451284 .0729333 1.99 0.047 .0021818 .288075 lxrate1 | -.0642892 .0187068 -3.44 0.001 -.1009538 -.0276245 lremote | -.1859979 .1211413 -1.54 0.125 -.4234306 .0514347 ldist | -1.486812 .290581 -5.12 0.000 -2.056341 -.917284 lopen | -.0002715 .0321918 -0.01 0.993 -.0633662 .0628233 english | 2.210591 .2323917 9.51 0.000 1.755112 2.666071 white | 10.21923 1.835455 5.57 0.000 6.621801 13.81665 lwhitemg | -.795032 .1892403 -4.20 0.000 -1.165936 -.4241279 _cons | -14.02854 12.18802 -1.15 0.250 -37.91663 9.859546 ------</p><p>. vce | limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000338 lgdp | -.000351 .003445 lgdpau | .000269 -.000577 .119497 lgdpdfrati~w | -.000278 -.000651 -.004676 .045198 lpopau | -.001596 .002118 -.404903 .034604 1.47656 lpop | .000112 -.003387 -.000177 .001055 -.002369 .005319 lxrate1 | -4.3e-06 .000188 .001264 .000613 -.005975 -.000208 .00035 lremote | .00031 .001151 -.006857 -.00331 .021961 -.000654 -.000447 ldist | .001176 .00046 -.002986 .00003 -.00466 .003365 -.000269 lopen | .000039 -.000318 -.000767 .001412 -.00005 .000463 -.000013 english | -.000281 -.002272 .002521 .003352 -.005265 .003005 .000363 white | .001695 -.0242 .008421 .001878 -.03627 .022824 .000811 lwhitemg | -.000156 .001325 -.00099 .000073 .003697 -.00125 -.00008 _cons | .010176 -.054901 3.68398 -.47463 -14.0438 .008752 .069677</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .014675 ldist | .006366 .084437 lopen | .000095 .000063 .001036 english | -.003323 .031589 -.000201 .054006 white | .009686 -.046312 .001808 .056337 3.3689 lwhitemg | -.000309 .004107 -.000082 -.005009 -.342616 .035812 _cons | -.384335 -.77797 .018557 -.260394 .889882 -.080114 148.548</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1159.30 Log likelihood = -830.4568 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1337476 .0618909 2.16 0.031 .0124436 .2550516 lgdp | .5115141 .1058674 4.83 0.000 .3040178 .7190103 lgdpau | -2.276633 1.078251 -2.11 0.035 -4.389967 -.1632996 lgdpdfrati~w | -.8836542 .4256513 -2.08 0.038 -1.717915 -.049393 lpopau | 4.90403 3.694091 1.33 0.184 -2.336256 12.14432 lpop | .2641816 .1212946 2.18 0.029 .0264486 .5019146 lxrate1 | -.1237885 .0386497 -3.20 0.001 -.1995405 -.0480364 lremote | 1.691458 .2737762 6.18 0.000 1.154866 2.228049 ldist | -2.211378 .3581163 -6.18 0.000 -2.913273 -1.509482 lopen | .0040913 .0752033 0.05 0.957 -.1433045 .1514871 english | .2596365 .2512475 1.03 0.301 -.2327995 .7520725 white | 11.2408 1.451409 7.74 0.000 8.396092 14.08551 lwhitemg | -.8627616 .139651 -6.18 0.000 -1.136472 -.5890507 _cons | -27.32983 34.63921 -0.79 0.430 -95.22143 40.56177 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00383 lgdp | -.003928 .011208 lgdpau | -.001774 .005023 1.16263 lgdpdfrati~w | -.001592 .004084 -.000057 .181179 lpopau | .00206 -.024125 -3.88484 .04133 13.6463 lpop | .001167 -.009777 -.002122 -.002404 .011486 .014712 lxrate1 | .000082 .001471 .000762 .00155 -.008824 -.001437 .001494 lremote | .00146 -.002418 -.033503 -.019386 .088535 .001899 .000705 ldist | .010349 -.009875 -.009076 -.010613 .011572 .006225 -.003018 lopen | .000319 -.000751 .005945 .001069 -.031325 .001946 -.000359 english | -.005263 .009185 .006367 .000893 -.022818 -.006648 -.000599 white | .023765 -.049537 -.041517 -.035718 .072427 .04955 .004076 lwhitemg | -.002653 .002995 .000036 .000989 .009194 -.002507 -.000664 _cons | -.047204 .296078 34.2566 -.647914 -125.109 -.218748 .13183</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .074953 ldist | .019892 .128247 lopen | .002871 .004305 .005656 english | -.003485 .018769 -.000733 .063125 white | .113797 .100779 .001893 .036243 2.10659 lwhitemg | -.004265 -.011945 -.000063 -.005233 -.193092 .019502 _cons | -1.40648 -1.25955 .287435 -.024561 -1.87014 -.013365 1199.87</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 535.33 Log likelihood = -125.3823 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0239222 .0285003 0.84 0.401 -.0319373 .0797817 lgdp | .1804419 .0629937 2.86 0.004 .0569766 .3039072 lgdpau | .439333 .4422154 0.99 0.320 -.4273934 1.306059 lgdpdfrati~w | .3749705 .1939741 1.93 0.053 -.0052118 .7551529 lpopau | 2.020986 1.551661 1.30 0.193 -1.020214 5.062186 lpop | .3014539 .0831854 3.62 0.000 .1384136 .4644942 lxrate1 | -.0150618 .0175187 -0.86 0.390 -.0493979 .0192743 lremote | -.0542184 .1382199 -0.39 0.695 -.3251244 .2166877 ldist | -2.360659 .4382408 -5.39 0.000 -3.219595 -1.501723 lopen | .0589061 .0421482 1.40 0.162 -.0237028 .1415151 english | .9778641 .194696 5.02 0.000 .5962669 1.359461 white | 16.36535 1.258135 13.01 0.000 13.89945 18.83125 lwhitemg | -1.388223 .1176427 -11.80 0.000 -1.618799 -1.157648 _cons | -30.91928 15.82695 -1.95 0.051 -61.93953 .1009639 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000812 lgdp | -.000684 .003968 lgdpau | -.000452 -.000325 .195555 lgdpdfrati~w | -.000705 .000779 -.001441 .037626 lpopau | .000687 .001712 -.654351 .020335 2.40765 lpop | -.000067 -.003004 .000586 .000679 -.004252 .00692 lxrate1 | .000054 .000113 .000168 .000628 -.002496 -.000089 .000307 lremote | .000834 .002358 -.008437 -.003873 .022759 -.001848 .000111 ldist | .00254 -.004337 -.010439 -.008466 .001843 .008873 .000269 lopen | -4.5e-06 -.000067 .000016 .000122 -.005195 .000595 -.000062 english | -.001254 -.00126 .00323 .003146 -.00932 .005664 .000189 white | .004352 -.019319 .034641 -.003042 -.282828 .028886 .00349 lwhitemg | -.000489 .001057 -.003581 .000077 .028791 -.002202 -.00039 _cons | -.018235 -.037534 5.89783 -.250527 -22.9815 -.05593 .03062</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .019105 ldist | .019115 .192055 lopen | .000077 .000369 .001776 english | -.005367 .009506 -.000141 .037907 white | -.005192 -.012512 -.000629 .049265 1.5829 lwhitemg | .000664 .002064 .000066 -.004176 -.144554 .01384 _cons | -.527145 -1.80977 .075251 -.041668 3.88244 -.39398 250.492</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 276.48 Log likelihood = 169.6645 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0016673 .0186021 0.09 0.929 -.0347922 .0381267 lgdp | .283708 .0506728 5.60 0.000 .1843911 .3830248 lgdpau | -.2788714 .3621001 -0.77 0.441 -.9885745 .4308317 lgdpdfrati~w | -.0968363 .1348863 -0.72 0.473 -.3612086 .167536 lpopau | 4.138465 1.310516 3.16 0.002 1.569901 6.707028 lpop | -.0319697 .0619387 -0.52 0.606 -.1533673 .0894279 lxrate1 | -.0908917 .0149801 -6.07 0.000 -.1202521 -.0615312 lremote | .3317861 .1340891 2.47 0.013 .0689762 .594596 ldist | -1.282065 .282197 -4.54 0.000 -1.835161 -.7289694 lopen | .0215934 .0279237 0.77 0.439 -.033136 .0763228 english | .4444363 .1854107 2.40 0.017 .0810381 .8078346 white | 9.875978 2.039902 4.84 0.000 5.877845 13.87411 lwhitemg | -.8530065 .1937874 -4.40 0.000 -1.232823 -.4731902 _cons | -56.94471 13.81839 -4.12 0.000 -84.02826 -29.86117 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000346 lgdp | -.000342 .002568 lgdpau | .000281 -.00071 .131116 lgdpdfrati~w | -.00037 .000359 -.006612 .018194 lpopau | -.002392 .003601 -.44879 .02705 1.71745 lpop | .000026 -.002135 -.000071 4.9e-06 .000153 .003836 lxrate1 | 9.0e-06 2.9e-06 .000407 .000446 -.004053 -.000097 .000224 lremote | .000274 .001706 -.008735 -.0014 .030314 -.001367 -.000051 ldist | .001459 -.001165 -.002838 -.00117 .005237 .00424 .000055 lopen | -9.3e-07 -.000031 .000157 .000152 -.001837 .000201 -.000026 english | -.000494 -.001898 -.000216 .000774 .022396 .005186 .000224 white | .002193 -.015274 .016529 -.003789 -.12926 .01706 .001833 lwhitemg | -.000259 .000931 -.002079 .000318 .013577 -.001387 -.000141 _cons | .022155 -.066503 4.12919 -.278755 -17.1205 -.042377 .056463</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .01798 ldist | .007588 .079635 lopen | 7.2e-06 -.000481 .00078 english | -.001033 .018267 -.000263 .034377 white | .000631 .017496 -.000474 .045062 4.1612 lwhitemg | .000707 -.002736 .00007 -.00432 -.388497 .037554 _cons | -.518981 -.889599 .028855 -.575874 1.58625 -.147768 190.948</p><p>. xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 556.70 Log likelihood = -634.1971 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1480213 .0488938 3.03 0.002 .0521912 .2438514 lgdp | .7478536 .0989655 7.56 0.000 .5538849 .9418224 lgdpau | -.4605897 .6029521 -0.76 0.445 -1.642354 .7211748 lgdpdfrati~w | -.1825226 .2531214 -0.72 0.471 -.6786314 .3135861 lpopau | 2.466109 2.074566 1.19 0.235 -1.599965 6.532183 lpop | -.2373959 .1422587 -1.67 0.095 -.5162178 .041426 lxrate1 | -.1160253 .0293583 -3.95 0.000 -.1735666 -.058484 lremote | .0900613 .2139894 0.42 0.674 -.3293502 .5094727 ldist | -3.935681 .673576 -5.84 0.000 -5.255866 -2.615497 lopen | .0247898 .0623476 0.40 0.691 -.0974093 .146989 english | -.398522 .4217016 -0.95 0.345 -1.225042 .4279978 white | 20.48551 3.978311 5.15 0.000 12.68816 28.28285 lwhitemg | -1.834066 .3637467 -5.04 0.000 -2.546996 -1.121135 _cons | -2.478254 20.6257 -0.12 0.904 -42.90388 37.94737 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002391 lgdp | -.001935 .009794 lgdpau | .000776 -.000962 .363551 lgdpdfrati~w | -.001464 .002641 -.006057 .06407 lpopau | -.006137 -.001438 -1.20766 .041056 4.30382 lpop | -.00025 -.007201 -.001246 -.00094 -.005856 .020238 lxrate1 | .000095 .000391 .001742 .001041 -.008929 -.000566 .000862 lremote | .000795 .004098 -.017935 -.010218 .035496 -.002825 .000481 ldist | .009959 .014069 -.005522 -.001851 -.03868 -.003116 .000133 lopen | .000376 -.000872 -.000924 .000253 -.0089 .001695 -.000165 english | -.005366 .00116 .002208 .004749 -.015121 .016669 .000828 white | .004796 -.03144 .095578 .019029 -.263113 .070307 .004255 lwhitemg | -.000982 .001252 -.010067 -.002731 .03098 -.005386 -.000467 _cons | .017804 -.22227 10.7415 -.522337 -39.5258 .027912 .092105</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .045791 ldist | .026496 .453705 lopen | .000603 .003097 .003887 english | -.002984 .127021 -.001547 .177832 white | .018982 .224154 .004893 .284881 15.827 lwhitemg | .000079 -.036473 -.000322 -.030639 -1.42134 .132312 _cons | -.815056 -4.10545 .131412 -1.30283 -.995725 .170701 425.419 . xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1361.71 Log likelihood = -570.9229 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2046837 .0469951 4.36 0.000 .112575 .2967923 lgdp | .5980394 .1009074 5.93 0.000 .4002645 .7958143 lgdpau | .6829374 .6306875 1.08 0.279 -.5531874 1.919062 lgdpdfrati~w | .1492742 .2820444 0.53 0.597 -.4035228 .7020712 lpopau | -2.940041 2.182307 -1.35 0.178 -7.217285 1.337203 lpop | .519454 .1288955 4.03 0.000 .2668236 .7720845 lxrate1 | -.0895471 .0292799 -3.06 0.002 -.1469346 -.0321596 lremote | -.291754 .2249746 -1.30 0.195 -.7326962 .1491882 ldist | -2.136291 .4457718 -4.79 0.000 -3.009987 -1.262594 lopen | -.0614048 .0707436 -0.87 0.385 -.2000598 .0772502 english | 1.098097 .3193852 3.44 0.001 .4721136 1.724081 white | 24.22008 3.076989 7.87 0.000 18.18929 30.25087 lwhitemg | -2.318903 .2739561 -8.46 0.000 -2.855847 -1.781959 _cons | 34.84271 21.04814 1.66 0.098 -6.410876 76.0963 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002209 lgdp | -.001921 .010182 lgdpau | -.002338 .005398 .397767 lgdpdfrati~w | -.001896 .003132 -.008995 .079549 lpopau | .006878 -.035062 -1.33073 .03356 4.76247 lpop | .000344 -.008523 -.003814 -.002411 .0177 .016614 lxrate1 | .000052 .000671 .000686 .001208 -.00644 -.00085 .000857 lremote | .000519 .003831 -.016785 -.017363 .035804 -.002875 .000516 ldist | .008326 -.003639 -.009957 -.003119 .000818 .01788 .000364 lopen | .000216 -.000015 .000474 .002067 -.013168 .001306 -.000069 english | -.003218 .002403 .005901 .00609 -.024458 -.000926 .000692 white | .00601 -.035234 .013496 -.016725 -.011678 .058919 .003418 lwhitemg | -.0009 .001219 -.002964 -.00008 .010761 -.004074 -.000355 _cons | -.107886 .352283 11.8382 -.243821 -43.9729 -.406831 .074971</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .050614 ldist | .006954 .198712 lopen | .001416 .002284 .005005 english | -.008042 .061104 -.001698 .102007 white | .027052 .057603 .003842 .011596 9.46786 lwhitemg | .000148 -.009725 -.000433 .000418 -.82763 .075052 _cons | -.688452 -1.9552 .151796 -.318368 -1.13814 .034106 443.024</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1413.10 Log likelihood = -742.5797 Prob > chi2 = 0.0000</p><p>------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0303225 .0357052 0.85 0.396 -.0396584 .1003033 lgdp | 1.050755 .0995901 10.55 0.000 .8555623 1.245948 lgdpau | 1.018883 .7210503 1.41 0.158 -.3943492 2.432116 lgdpdfrati~w | -.0067721 .277348 -0.02 0.981 -.5503643 .5368201 lpopau | 2.507397 2.51685 1.00 0.319 -2.425539 7.440332 lpop | -.3435818 .1494024 -2.30 0.021 -.636405 -.0507585 lxrate1 | -.1281796 .0232327 -5.52 0.000 -.1737149 -.0826443 lremote | -.6012739 .1957407 -3.07 0.002 -.9849186 -.2176292 ldist | -2.988782 .6606883 -4.52 0.000 -4.283707 -1.693857 lopen | -.0477416 .0752314 -0.63 0.526 -.1951925 .0997092 english | .379874 .3377004 1.12 0.261 -.2820066 1.041755 white | 29.08998 2.621298 11.10 0.000 23.95233 34.22763 lwhitemg | -2.717921 .2544333 -10.68 0.000 -3.216601 -2.219241 _cons | -50.11264 24.85224 -2.02 0.044 -98.82213 -1.403149 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001275 lgdp | -.001998 .009918 lgdpau | -.000361 .001536 .519914 lgdpdfrati~w | -.001964 .004371 -.017235 .076922 lpopau | -.00418 -.017838 -1.73848 .05796 6.33453 lpop | .001104 -.010666 -.00316 -.00246 .024086 .022321 lxrate1 | .000038 .000399 .00056 .00089 -.009014 -.000704 .00054 lremote | .001394 .004195 -.018013 -.00367 .022459 -.005233 .000169 ldist | .005413 .016245 -.018135 .001168 -.064681 -.003036 .000928 lopen | .000317 -.000791 -.000322 .004945 -.010206 .001808 -.000333 english | -.001188 .002128 .000695 .002449 -.011968 .007258 .001109 white | .014219 -.055263 .015207 -.027274 -.22154 .087292 .005758 lwhitemg | -.001236 .003638 -.002936 .001867 .02926 -.007038 -.000565 _cons | .038405 .011703 15.5611 -.617401 -59.0603 -.352621 .123166</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .038314 ldist | .058348 .436509 lopen | .00153 .004113 .00566 english | .001977 .08304 -.002 .114042 white | .022914 .069973 -.003372 .213353 6.8712 lwhitemg | -.001084 -.014507 .000515 -.023335 -.655916 .064736 _cons | -.807376 -3.48538 .113312 -.806234 2.18867 -.22319 617.634</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 580.44 Log likelihood = -567.7476 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .394185 .0561231 7.02 0.000 .2841857 .5041843 lgdp | .232193 .0941744 2.47 0.014 .0476146 .4167714 lgdpau | .9511065 .6746746 1.41 0.159 -.3712315 2.273444 lgdpdfrati~w | -.2651242 .2921077 -0.91 0.364 -.8376448 .3073963 lpopau | -3.648066 2.329123 -1.57 0.117 -8.213064 .9169321 lpop | .3484017 .1047008 3.33 0.001 .1431918 .5536116 lxrate1 | -.0739101 .0331603 -2.23 0.026 -.138903 -.0089172 lremote | -.0346674 .2177502 -0.16 0.874 -.46145 .3921151 ldist | -1.611732 .6024258 -2.68 0.007 -2.792465 -.4309989 lopen | .1154453 .0651072 1.77 0.076 -.0121623 .243053 english | -.0776613 .2908886 -0.27 0.789 -.6477926 .4924699 white | 20.12861 1.975163 10.19 0.000 16.25736 23.99986 lwhitemg | -1.87849 .1915793 -9.81 0.000 -2.253979 -1.503002 _cons | 43.01625 22.22836 1.94 0.053 -.5505372 86.58304 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00315 lgdp | -.00263 .008869 lgdpau | -.002067 .006506 .455186 lgdpdfrati~w | -.002409 .00554 -.00251 .085327 lpopau | .003564 -.033903 -1.5214 .021618 5.42482 lpop | .000811 -.006004 -.004562 -.003727 .014434 .010962 lxrate1 | .000267 .000402 -.000287 .000733 -.002771 -.000613 .0011 lremote | .000536 .002787 -.009618 -.015976 .003373 .000514 .001308 ldist | .011344 .000875 -.004766 -.011125 -.061912 .006433 -.000062 lopen | -.000294 .001023 .00191 .000026 -.019799 .001139 -.000101 english | -.003298 .005692 .005857 .002179 -.023089 -.000034 -.0015 white | .020097 -.034985 -.013546 -.066701 .088782 .01056 -.001439 lwhitemg | -.002387 .001876 -.000739 .004035 .002917 -.000035 -.000125 _cons | -.088441 .262938 13.3675 -.185925 -49.0542 -.224053 .038892</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .047415 ldist | .035373 .362917 lopen | .001981 .003029 .004239 english | .005438 .098896 .000227 .084616 white | .09455 .216818 -.008202 .160594 3.90127 lwhitemg | -.006568 -.031974 .000641 -.018752 -.369833 .036703 _cons | -.621434 -2.79716 .19642 -.880546 -3.4983 .306706 494.1</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1566.03 Log likelihood = -262.3729 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0190589 .0296595 -0.64 0.520 -.0771905 .0390727 lgdp | .3333485 .0866602 3.85 0.000 .1634975 .5031994 lgdpau | -.2939749 .5356325 -0.55 0.583 -1.343795 .7558456 lgdpdfrati~w | .2346833 .2351261 1.00 0.318 -.2261555 .695522 lpopau | 1.209064 1.847929 0.65 0.513 -2.412811 4.830939 lpop | -.1110335 .117527 -0.94 0.345 -.3413821 .1193152 lxrate1 | -.0160842 .0228439 -0.70 0.481 -.0608574 .028689 lremote | -.0139239 .1843735 -0.08 0.940 -.3752894 .3474415 ldist | -4.660349 .5177753 -9.00 0.000 -5.67517 -3.645528 lopen | .0250262 .0526593 0.48 0.635 -.0781842 .1282366 english | .0230285 .3185912 0.07 0.942 -.6013989 .6474558 white | 17.20086 2.602789 6.61 0.000 12.09949 22.30223 lwhitemg | -1.209082 .2796942 -4.32 0.000 -1.757272 -.6608914 _cons | 27.7123 18.42598 1.50 0.133 -8.401965 63.82656 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00088 lgdp | -.001058 .00751 lgdpau | .000554 -.002118 .286902 lgdpdfrati~w | -.001007 .002872 -.013443 .055284 lpopau | -.002736 -.001244 -.9598 .060465 3.41484 lpop | .000109 -.00651 -.000349 -.000971 .001618 .013813 lxrate1 | 2.9e-06 .000143 .00123 .001012 -.006387 -.00041 .000522 lremote | .000275 .002259 -.020296 -.004421 .060204 -.002142 -.000221 ldist | .00326 .004464 -.010581 -.001044 -.009132 .014908 -.000595 lopen | .000054 4.1e-06 -.001712 .000947 .001329 .000762 -.000048 english | -.001592 .001872 .001066 .002056 -.000872 .004361 .000547 white | .006276 -.038808 .046343 -.009905 -.288519 .060829 .002758 lwhitemg | -.000644 .001626 -.006219 -.000094 .037925 -.00451 -.000136 _cons | .016078 -.048259 8.73171 -.706306 -31.9474 -.211067 .081334</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .033994 ldist | .016393 .268091 lopen | .000386 .001265 .002773 english | -.000083 .075897 -.000147 .1015 white | -.000127 .160248 -.003358 .118194 6.77451 lwhitemg | .002982 -.02107 .000371 -.012561 -.717795 .078229 _cons | -.93375 -2.64096 -.004295 -.860297 1.90483 -.25233 339.517</p><p>. . . clear</p><p>. insheet using k:\book1.txt (104 vars, 1010 obs)</p><p>. *Dropping Portugal . drop if ccode==454100 (10 observations deleted)</p><p>. . . . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist op > en english gdpdfrationew white whitemg, stat(n mean sd median min max) col(sta > t) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 490523.8 1561379 7348 0 1.39e+07 immig | 1000 33286.64 117075.4 2790 0 1137050 gdp | 1000 2.78e+11 9.70e+11 1.63e+10 1.92e+08 8.99e+12 gdpau | 1000 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 1000 105.6237 16.92502 102.6773 60.87417 207.3465 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.95e+07 1.54e+08 1.04e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1041.963 10901.81 13.89535 .0068 270182.6 remote | 1000 6769.02 4134.254 6797 1293 39620 dist | 1000 13323.55 3502.039 14215 2409 17735 open | 1000 .7085053 .3898744 .63425 .0671 3.2192 english | 1000 .38 .4856293 0 0 1 gdpdfratio~w | 1000 1.051735 .1811786 1.013736 .5844526 2.009028 white | 1000 .13 .3364717 0 0 1 whitemg | 1000 20501.65 116468.1 0 0 1137050 ------. . sort white</p><p>. *IIIB. Descriptives Original Unites(sub sample for "white" and "non-white" cou > ntries)--RHS Variables: . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remo > te dist phone open english gdpdfrationew white whitemg, stat(n mean sd median > min max) col(stat) </p><p>------> white = 0</p><p> variable | N mean sd p50 min max ------+------rimp | 870 404172.4 1597756 2944.5 0 1.39e+07 immig | 870 14695.39 27169.74 1403.5 0 158613 gdp | 870 2.36e+11 1.00e+12 1.00e+10 1.92e+08 8.99e+12 gdpau | 870 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 870 104.74 17.2801 101.6138 60.87417 207.3465 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.34e+07 1.65e+08 1.07e+07 41000 1.26e+09 popau | 870 1.82e+07 612839.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 870 1181.665 11681.86 19.96485 .0068 270182.6 remote | 870 7199.825 4099.067 6955 1293 39620 dist | 870 13147.07 3383.172 14040 2410 17735 phone | 870 153.1578 237.2128 47.025 .54 1449.75 open | 870 .7159618 .4113726 .63155 .0671 3.2192 english | 870 .3908046 .4882114 0 0 1 gdpdfratio~w | 870 1.043182 .1860345 1 .5844526 2.009028 white | 870 0 0 0 0 0 whitemg | 870 0 0 0 0 0 ------</p><p>------> white = 1</p><p> variable | N mean sd p50 min max ------+------rimp | 130 1068414 1138347 522863.5 40432 3843839 immig | 130 157705 288518.8 21174 2612 1137050 gdp | 130 5.56e+11 6.58e+11 2.54e+11 5.15e+10 2.69e+12 gdpau | 130 3.83e+11 4.46e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 130 111.5379 12.89742 112.2247 85.45601 143.9587 gdpdfau | 130 100.7173 4.649088 100.8223 94.42464 109.9797 pop | 130 2.34e+07 2.55e+07 8837000 3477200 8.22e+07 popau | 130 1.82e+07 614856.7 1.82e+07 1.73e+07 1.92e+07 xrate1 | 130 107.0323 293.6987 4.4722 .3774 1261.556 remote | 130 3885.938 3089.96 2888 1530 12501 dist | 130 14504.62 4031.974 15931 2409 17493 phone | 130 734.716 269.9717 652.085 343.99 1487.08 open | 130 .6586038 .1850905 .64065 .3517 1.2967 english | 130 .3076923 .4633239 0 0 1 gdpdfratio~w | 130 1.108974 .1314272 1.116445 .8254872 1.441221 white | 130 1 0 1 1 1 whitemg | 130 157705 288518.8 21174 2612 1137050 ------</p><p>. . . **Regression of Imports . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Imports . xtgls lrimp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 9156.89 Log likelihood = -550.5136 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3194417 .0306634 10.42 0.000 .2593425 .3795408 lgdp | 1.189474 .0332744 35.75 0.000 1.124257 1.25469 lgdpau | .1675787 .6031747 0.28 0.781 -1.014622 1.349779 lgdpdfrati~w | -.9267291 .2447235 -3.79 0.000 -1.406378 -.4470798 lpopau | -2.670235 2.080182 -1.28 0.199 -6.747317 1.406846 lpop | .03316 .0409384 0.81 0.418 -.0470777 .1133978 lxrate1 | -.1316052 .0166028 -7.93 0.000 -.164146 -.0990643 lremote | -.4242781 .077334 -5.49 0.000 -.57585 -.2727063 ldist | -2.131756 .1645227 -12.96 0.000 -2.454214 -1.809297 lopen | .2790665 .055435 5.03 0.000 .1704159 .3877172 english | .895735 .1296813 6.91 0.000 .6415643 1.149906 white | 4.567365 .5760605 7.93 0.000 3.438307 5.696422 lwhitemg | -.420029 .051105 -8.22 0.000 -.5201929 -.319865 _cons | 42.37089 19.14633 2.21 0.027 4.844767 79.89702 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00094 lgdp | -.000297 .001107 lgdpau | -.00087 .001365 .36382 lgdpdfrati~w | -.0008 .000165 -.009569 .05989 lpopau | .001597 -.007942 -1.23001 .049358 4.32716 lpop | -.000134 -.000748 .000135 .000192 -.000301 .001676 lxrate1 | .000092 .000158 .000368 .000202 -.002631 -.000095 .000276 lremote | .000457 .000015 -.000491 -.001757 -.002758 -.000248 .000065 ldist | .001688 .001116 .001029 -.00108 -.017237 -.000011 .001754 lopen | -.000149 .000585 .002462 .000808 -.016489 .000341 .000148 english | -.001155 .002903 .002827 .002101 -.010374 -.001454 .000563 white | .004492 -.002255 .002986 -.010348 -.024488 .005212 .000165 lwhitemg | -.000561 .000198 -.000299 .000949 .002872 -.000423 -.000043 _cons | -.020976 .07114 10.8355 -.607104 -39.2077 -.003656 .01283</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .005981 ldist | .004498 .027068 lopen | .001349 .00095 .003073 english | -.003466 .003166 -.000859 .016817 white | .000556 -.002304 -.00008 -.00143 .331846 lwhitemg | .000111 -.000421 -.000083 .000258 -.028917 .002612 _cons | -.03117 -.078078 .171207 .047848 .278518 -.030465 366.582</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 76621.88 Log likelihood = -979.2281 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0521938 .0142614 3.66 0.000 .024242 .0801456 lgdp | 1.607838 .0523827 30.69 0.000 1.50517 1.710506 lgdpau | .8629981 .3603255 2.40 0.017 .1567731 1.569223 lgdpdfrati~w | -.4418522 .149149 -2.96 0.003 -.7341788 -.1495256 lpopau | -6.296107 1.217353 -5.17 0.000 -8.682076 -3.910138 lpop | -.3534453 .0864132 -4.09 0.000 -.5228122 -.1840785 lxrate1 | -.1200416 .0204612 -5.87 0.000 -.1601449 -.0799383 lremote | -.9560621 .112675 -8.49 0.000 -1.176901 -.7352232 ldist | -3.217482 .1532159 -21.00 0.000 -3.517779 -2.917184 lopen | -.0527994 .0269156 -1.96 0.050 -.105553 -.0000457 english | .998922 .0838515 11.91 0.000 .834576 1.163268 white | 4.695807 .7596517 6.18 0.000 3.206917 6.184697 lwhitemg | -.4637035 .0711229 -6.52 0.000 -.6031019 -.3243051 _cons | 94.6257 11.53773 8.20 0.000 72.01218 117.2392 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000203 lgdp | -.000224 .002744 lgdpau | -.001204 .002122 .129834 lgdpdfrati~w | -.000559 .000832 -.011569 .022245 lpopau | .004735 -.00868 -.429742 .023138 1.48195 lpop | .000094 -.004301 -.002004 -.000058 .006525 .007467 lxrate1 | -.000021 .000325 2.7e-06 .000422 -.003297 -.000385 .000419 lremote | .000274 -.000779 -.007809 -.004005 .027733 .00065 -.000054 ldist | .00048 -.001604 -.007258 -.002465 .020455 .002319 .000433 lopen | .000036 -.000145 -.001009 .00087 .003725 .000336 -.000079 english | -.000419 .000401 .003222 .00256 -.020493 .000042 .001118 white | .000671 -.013274 -.013236 -.007373 .055678 .019918 -.001489 lwhitemg | -.000081 .000535 .000435 .000339 -.003037 -.00067 .000154 _cons | -.050667 .115143 3.86081 -.058683 -13.6915 -.102377 .047902</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .012696 ldist | .007649 .023475 lopen | .000823 .000344 .000724 english | -.002756 .001424 -.000409 .007031 white | .018271 -.028791 .002154 -.004321 .577071 lwhitemg | -.000254 .004371 -.000126 .000565 -.051677 .005058 _cons | -.430714 -.445866 -.048396 .251134 -.459349 -.003482 133.119</p><p>. . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7363.19 Log likelihood = -945.8043 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .068838 .0178126 3.86 0.000 .0339259 .10375 lgdp | 1.724177 .0666276 25.88 0.000 1.593589 1.854765 lgdpau | .38536 .4539338 0.85 0.396 -.5043338 1.275054 lgdpdfrati~w | -.5289291 .1809548 -2.92 0.003 -.8835939 -.1742643 lpopau | -4.314805 1.56783 -2.75 0.006 -7.387696 -1.241914 lpop | -.5273632 .0807929 -6.53 0.000 -.6857143 -.3690121 lxrate1 | -.143422 .0253086 -5.67 0.000 -.1930259 -.0938181 lremote | -.4650092 .125289 -3.71 0.000 -.710571 -.2194473 ldist | -4.386982 .3280921 -13.37 0.000 -5.030031 -3.743934 lopen | .0160716 .0355646 0.45 0.651 -.0536337 .085777 english | 1.466935 .1468604 9.99 0.000 1.179094 1.754776 white | 10.99874 1.904587 5.77 0.000 7.265814 14.73166 lwhitemg | -.925749 .1895416 -4.88 0.000 -1.297244 -.5542543 _cons | 81.0747 14.9139 5.44 0.000 51.84399 110.3054 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000317 lgdp | -.000507 .004439 lgdpau | -.001536 .003522 .206056 lgdpdfrati~w | -.000585 .001345 -.015158 .032745 lpopau | .004981 -.019079 -.688916 .042063 2.45809 lpop | .000358 -.003859 -.001784 -.000869 .006378 .006527 lxrate1 | -.000013 .000406 -.000113 .000867 -.004366 -.000565 .000641 lremote | -.000082 -.000769 -.007176 -.002335 .024581 -.000815 .000051 ldist | .001324 .008547 -.008611 -.002716 -.013443 -.001554 .000997 lopen | .000075 -.0005 -.000705 .001471 .003367 .000752 -.000169 english | -.000711 .001407 .005549 .002443 -.04202 .004184 .001821 white | .00033 -.030652 -.002149 .002021 .01378 .028237 .004109 lwhitemg | -.000039 .001559 -.000986 -.000547 .004792 -.001761 -.0004 _cons | -.049119 .112299 6.13958 -.302342 -22.5236 -.05456 .061657</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .015697 ldist | .005823 .107644 lopen | .000629 -.000504 .001265 english | -.004646 .00641 -.001186 .021568 white | .013238 -.141034 .002029 .02955 3.62745 lwhitemg | .000712 .010895 -.00007 -.003132 -.353536 .035926 _cons | -.381872 -.803677 -.039128 .422374 1.25637 -.167932 222.425</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2205.13 Log likelihood = -1109.52 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0887634 .0413874 2.14 0.032 .0076456 .1698812 lgdp | .9333425 .0808521 11.54 0.000 .7748752 1.09181 lgdpau | -.3862975 .8441512 -0.46 0.647 -2.040803 1.268208 lgdpdfrati~w | -.4152865 .3491173 -1.19 0.234 -1.099544 .2689709 lpopau | -.0507418 2.893115 -0.02 0.986 -5.721143 5.619659 lpop | .0461238 .0994586 0.46 0.643 -.1488116 .2410591 lxrate1 | -.1396465 .0334941 -4.17 0.000 -.2052937 -.0739994 lremote | .5424014 .2340979 2.32 0.021 .083578 1.001225 ldist | -1.610055 .334205 -4.82 0.000 -2.265085 -.9550252 lopen | .3543255 .0797075 4.45 0.000 .1981017 .5105494 english | 1.72343 .2461027 7.00 0.000 1.241078 2.205783 white | 1.761224 2.214135 0.80 0.426 -2.5784 6.100849 lwhitemg | .1605521 .1944335 0.83 0.409 -.2205306 .5416348 _cons | 2.719749 27.46058 0.10 0.921 -51.102 56.5415 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001713 lgdp | -.001613 .006537 lgdpau | -.001818 .001411 .712591 lgdpdfrati~w | -.000357 .001405 -.011773 .121883 lpopau | .003512 -.009567 -2.38725 .038538 8.37011 lpop | .000339 -.005824 .000257 -.00084 -.001477 .009892 lxrate1 | .000117 .000921 .000525 .001942 -.007596 -.00121 .001122 lremote | .001311 .000702 -.027666 -.015537 .086184 .000444 -.000789 ldist | .004333 -.007146 -.020265 -.00707 .062822 .010914 -.000197 lopen | .00027 -.001152 .005119 .002412 -.027493 .003013 -.000184 english | -.003678 .000944 .009903 .006017 -.019533 -.000356 .001478 white | .003356 -.023984 .102225 .003799 -.408853 .021013 .000423 lwhitemg | -.000488 .000911 -.010741 -.001751 .044203 -.00028 -.000191 _cons | -.039424 .133543 21.328 -.272697 -77.4283 -.112049 .112928</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054802 ldist | .021212 .111693 lopen | .001892 -.000908 .006353 english | -.015358 .012506 -.001919 .060567 white | .039253 -.02978 .007131 .041424 4.90239 lwhitemg | -.000574 .006603 -.000421 -.003025 -.419669 .037804 _cons | -1.39387 -1.79555 .293778 .055313 4.22277 -.522178 754.084</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 63045.95 Log likelihood = -913.6051 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0225708 .0135106 1.67 0.095 -.0039096 .0490511 lgdp | 1.552777 .0522012 29.75 0.000 1.450464 1.655089 lgdpau | .646807 .3624128 1.78 0.074 -.0635091 1.357123 lgdpdfrati~w | -.2594909 .1360017 -1.91 0.056 -.5260494 .0070677 lpopau | -6.53316 1.224569 -5.34 0.000 -8.933272 -4.133048 lpop | -.1594695 .0889229 -1.79 0.073 -.3337552 .0148162 lxrate1 | -.047225 .0183844 -2.57 0.010 -.0832577 -.0111923 lremote | -.5926918 .1447977 -4.09 0.000 -.8764902 -.3088935 ldist | -2.508801 .1555393 -16.13 0.000 -2.813653 -2.20395 lopen | -.0441191 .027556 -1.60 0.109 -.0981278 .0098896 english | 1.132223 .1111613 10.19 0.000 .9143505 1.350095 white | 3.585768 .8722217 4.11 0.000 1.876245 5.295291 lwhitemg | -.2629315 .0800711 -3.28 0.001 -.419868 -.105995 _cons | 92.10852 11.57381 7.96 0.000 69.42427 114.7928 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000183 lgdp | -.00018 .002725 lgdpau | -.000892 .00209 .131343 lgdpdfrati~w | -.000343 .000873 -.007565 .018496 lpopau | .003206 -.007511 -.43504 .012624 1.49957 lpop | .000085 -.004371 -.001934 -.000346 .004838 .007907 lxrate1 | 3.8e-07 .000233 -.000099 .000441 -.00232 -.000279 .000338 lremote | .000027 -.001254 -.013122 -.004074 .046559 .00093 -.000123 ldist | .00076 -.004876 -.004769 .00065 .007286 .008389 .000536 lopen | .000017 -.000095 -.00092 .000893 .003293 .000279 -.000065 english | -.000321 -.00016 .003389 .002538 -.01746 -.000116 .000909 white | .000295 -.014365 -.017899 -.003269 .040778 .024473 .001518 lwhitemg | -.000066 .000564 .000259 -.000139 .000915 -.001085 -.000167 _cons | -.03506 .1343 3.92666 -.01296 -13.8706 -.142945 .034528</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .020966 ldist | -.000993 .024192 lopen | .00111 .000278 .000759 english | -.004064 .005637 -.000475 .012357 white | .022315 .02323 .001214 .004853 .760771 lwhitemg | .000285 -.001037 -8.3e-06 -.000274 -.06671 .006411 _cons | -.584847 -.248684 -.045664 .180955 -.690648 -.009361 133.953</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8564.53 Log likelihood = -977.9686 Prob > chi2 = 0.0000 ------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2377562 .0316952 7.50 0.000 .1756349 .2998776 lgdp | 1.583651 .0723131 21.90 0.000 1.44192 1.725382 lgdpau | -.1290556 .619803 -0.21 0.835 -1.343847 1.085736 lgdpdfrati~w | -.1343049 .2618532 -0.51 0.608 -.6475276 .3789179 lpopau | -1.518139 2.171214 -0.70 0.484 -5.773641 2.737363 lpop | -.4930394 .0817598 -6.03 0.000 -.6532856 -.3327932 lxrate1 | -.1235553 .0278842 -4.43 0.000 -.1782073 -.0689033 lremote | -.3501319 .1231391 -2.84 0.004 -.5914801 -.1087837 ldist | -3.040361 .3321147 -9.15 0.000 -3.691294 -2.389428 lopen | .1167653 .049968 2.34 0.019 .0188299 .2147007 english | .8869861 .1399608 6.34 0.000 .6126679 1.161304 white | 10.60666 1.858105 5.71 0.000 6.96484 14.24848 lwhitemg | -.941202 .1848641 -5.09 0.000 -1.303529 -.5788749 _cons | 35.81365 20.61596 1.74 0.082 -4.592891 76.2202 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001005 lgdp | -.001519 .005229 lgdpau | -.001781 .003471 .384156 lgdpdfrati~w | -.001257 .002742 -.024606 .068567 lpopau | .00475 -.017126 -1.30786 .097098 4.71417 lpop | .000899 -.004384 -.001486 -.001779 .006583 .006685 lxrate1 | .000071 .000297 -.00007 .001157 -.00483 -.000587 .000778 lremote | .000028 -.000538 -.003881 -.000634 .006588 -.001001 .000191 ldist | .004441 .001362 -.010719 -.002878 -.01319 .00108 .001382 lopen | .000142 -.000756 .00177 .001608 -.008523 .001443 -.000263 english | -.001678 .00362 .002744 .004523 -.020391 .000332 .001945 white | .000314 -.02682 .013746 .001938 -.004631 .020476 .004565 lwhitemg | .000037 .00156 -.002145 -.000577 .003946 -.001318 -.000403 _cons | -.058283 .140535 11.7373 -1.03515 -43.6863 -.078728 .064806</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .015163 ldist | .00924 .1103 lopen | .000385 -.000912 .002497 english | -.004446 -.001776 -.001626 .019589 white | .011723 -.162026 .003501 .017218 3.45256 lwhitemg | .0007 .01502 -.000237 -.002158 -.337593 .034175 _cons | -.202202 -.704594 .095103 .226657 1.40248 -.170427 425.018</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8148.68 Log likelihood = -1106.858 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0178994 .0152059 1.18 0.239 -.0119036 .0477024 lgdp | 1.331638 .0497775 26.75 0.000 1.234076 1.4292 lgdpau | .5006555 .4897345 1.02 0.307 -.4592064 1.460517 lgdpdfrati~w | -.0680136 .1587801 -0.43 0.668 -.3792168 .2431896 lpopau | -5.383924 1.664394 -3.23 0.001 -8.646076 -2.121772 lpop | .1095928 .0717597 1.53 0.127 -.0310535 .2502392 lxrate1 | -.0647704 .0193235 -3.35 0.001 -.1026438 -.0268971 lremote | -.7914682 .1603591 -4.94 0.000 -1.105766 -.4771701 ldist | -3.327498 .2148823 -15.49 0.000 -3.748659 -2.906336 lopen | .0734909 .0406687 1.81 0.071 -.0062183 .1532002 english | 2.42674 .1351598 17.95 0.000 2.161832 2.691649 white | 4.215889 1.163981 3.62 0.000 1.934529 6.497249 lwhitemg | -.1994663 .0978518 -2.04 0.042 -.3912524 -.0076803 _cons | 85.93497 15.95197 5.39 0.000 54.66968 117.2002 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000231 lgdp | -.00037 .002478 lgdpau | -.000058 .000049 .23984 lgdpdfrati~w | -.000429 .000604 .001918 .025211 lpopau | -.00135 .001398 -.795903 -.005105 2.77021 lpop | .000173 -.002788 -.000371 .000015 -.001931 .005149 lxrate1 | -.000016 .00022 .000328 .00061 -.002356 -.00039 .000373 lremote | .000169 .000667 -.018251 -.000884 .056777 -.000878 -.000125 ldist | .000571 .000389 -.011434 -.00102 .024465 .000501 .000315 lopen | .00006 -.000291 -.000068 .001831 .000652 .000655 -.000126 english | -.000717 .000261 .002258 .00151 -.00939 .002001 .000962 white | .000265 -.013815 -.005581 -.001131 .010068 .024429 -.000212 lwhitemg | -5.2e-06 .000708 -.000846 .000206 .003021 -.00156 .000078 _cons | .022386 -.044551 7.18269 .012429 -25.8019 .025104 .02741</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .025715 ldist | .016269 .046174 lopen | .000875 .000076 .001654 english | -.003651 .002884 -.001261 .018268 white | .005498 -.008819 .000713 .032976 1.35485 lwhitemg | .001231 .002875 3.4e-06 -.002831 -.110112 .009575 _cons | -.844771 -.71207 -.021727 .05589 -.076177 -.057272 254.465</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 434.85 Log likelihood = -630.9148 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4697487 .053933 8.71 0.000 .364042 .5754553 lgdp | .022172 .0905768 0.24 0.807 -.1553552 .1996993 lgdpau | -.4422498 .687456 -0.64 0.520 -1.789639 .9051392 lgdpdfrati~w | -.3326395 .2347495 -1.42 0.156 -.79274 .1274611 lpopau | .1078994 2.343582 0.05 0.963 -4.485437 4.701236 lpop | .2571117 .0968704 2.65 0.008 .0672492 .4469741 lxrate1 | -.0973829 .0257662 -3.78 0.000 -.1478838 -.046882 lremote | .2793262 .243377 1.15 0.251 -.197684 .7563365 ldist | -2.286463 .5338845 -4.28 0.000 -3.332857 -1.240068 lopen | .0460418 .0576549 0.80 0.425 -.0669597 .1590433 english | .5768711 .2528838 2.28 0.023 .081228 1.072514 white | 12.15188 .9488234 12.81 0.000 10.29222 14.01154 lwhitemg | -1.108393 .0926167 -11.97 0.000 -1.289919 -.9268676 _cons | 28.27745 22.51177 1.26 0.209 -15.8448 72.3997 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002909 lgdp | -.001464 .008204 lgdpau | -.000509 -.000046 .472596 lgdpdfrati~w | -.001177 .002612 -.006145 .055107 lpopau | -.001918 -.012732 -1.56197 .015403 5.49238 lpop | -.000235 -.0056 -.001113 -.001455 .007695 .009384 lxrate1 | .000072 .000047 .000368 .001419 -.00444 -.000496 .000664 lremote | .002723 .004166 -.025009 -.007154 .056865 -.003632 .00071 ldist | .01001 -.007682 -.022358 -.001865 -.001753 .013311 .001687 lopen | -.000589 .002102 -.00204 -.000019 -.002215 -.000291 -.000049 english | -.000073 .000577 .005414 .006881 -.034375 .005483 .001162 white | .015037 -.021013 .003025 -.001074 -.034915 .024564 .004189 lwhitemg | -.001537 .000475 -.001884 -.000535 .010255 -.001164 -.000259 _cons | -.056683 .157025 13.9658 -.106858 -50.4369 -.210449 .043795</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .059232 ldist | .045593 .285033 lopen | .001104 -.001104 .003324 english | -.008695 .013588 .00027 .06395 white | .021199 -.029937 -.004737 .081187 .900266 lwhitemg | .000527 .006705 .000066 -.006267 -.082257 .008578 _cons | -1.28693 -2.6087 .053667 .230592 .515416 -.165851 506.78</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 4428.64 Log likelihood = -609.5744 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1242194 .0269618 4.61 0.000 .0713752 .1770635 lgdp | .2244857 .0475986 4.72 0.000 .1311942 .3177772 lgdpau | -.1033974 .0512206 -2.02 0.044 -.2037879 -.0030069 lgdpdfrati~w | -.1184796 .0346341 -3.42 0.001 -.1863612 -.0505979 lpopau | 2.748969 .2191367 12.54 0.000 2.319469 3.178469 lpop | .7920654 .0982543 8.06 0.000 .5994906 .9846403 lxrate1 | -.0115917 .0068792 -1.69 0.092 -.0250747 .0018914 lremote | .1452456 .0276377 5.26 0.000 .0910768 .1994145 ldist | -3.350071 .3328372 -10.07 0.000 -4.00242 -2.697722 lopen | .0050815 .0257721 0.20 0.844 -.0454309 .0555939 english | .757898 .2739758 2.77 0.006 .2209153 1.294881 white | 24.22543 2.957618 8.19 0.000 18.42861 30.02225 lwhitemg | -2.236796 .2745222 -8.15 0.000 -2.774849 -1.698742 _cons | -24.56247 4.806475 -5.11 0.000 -33.98299 -15.14195 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000727 lgdp | -.000378 .002266 lgdpau | -.000505 -.000468 .002624 lgdpdfrati~w | .000257 -.00089 .000555 .0012 lpopau | .003614 .000564 -.009204 .000289 .048021 lpop | -.000237 -.001854 .001165 .000416 -.003454 .009654 lxrate1 | .000014 .000069 -.000039 .000027 .000516 -.000189 .000047 lremote | -.000246 .000964 -.00047 -.000729 .000085 -.000587 .000022 ldist | .002594 -.000078 -.002309 .000082 .017791 -.002071 -.000039 lopen | -.00029 -.000216 .000226 -.000301 -.003228 .000904 -.000126 english | -.000496 -.000528 .000631 .000363 -.005327 .000058 .000029 white | .002185 -.004683 .001152 .001764 .000135 .02804 -.000395 lwhitemg | -.000408 .000109 .00012 -.00007 -.001994 -.002989 .000033 _cons | -.061695 -.02512 .105123 -.002969 -.705348 -.056984 -.006322</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .000764 ldist | -.000039 .110781 lopen | .000131 -.000731 .000664 english | -.000364 .056621 -7.5e-06 .075063 white | -.002094 .021655 .000942 .040822 8.7475 lwhitemg | .000083 -.004314 .000019 -.003183 -.799957 .075362 _cons | -.00594 -1.27783 .047244 -.470388 -.594722 .118918 23.1022</p><p>. . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 521.02 Log likelihood = -557.0863 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5071861 .0501343 10.12 0.000 .4089247 .6054475 lgdp | -.0254319 .0782283 -0.33 0.745 -.1787565 .1278927 lgdpau | 1.930076 .7896047 2.44 0.015 .3824794 3.477673 lgdpdfrati~w | -.6742177 .2816909 -2.39 0.017 -1.226322 -.1221138 lpopau | -9.325848 2.714417 -3.44 0.001 -14.64601 -4.005689 lpop | .376943 .0966015 3.90 0.000 .1876075 .5662785 lxrate1 | -.1161943 .0261251 -4.45 0.000 -.1673987 -.06499 lremote | .0315782 .2519475 0.13 0.900 -.4622298 .5253863 ldist | -1.684051 .3165797 -5.32 0.000 -2.304536 -1.063567 lopen | .0427608 .0538152 0.79 0.427 -.0627152 .1482367 english | -.0196011 .224803 -0.09 0.931 -.4602069 .4210046</p><p> white | 9.567148 1.093808 8.75 0.000 7.423323 11.71097 lwhitemg | -.8432237 .0966972 -8.72 0.000 -1.032747 -.6537007 _cons | 117.5571 25.72403 4.57 0.000 67.13887 167.9752 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002513 lgdp | -.001405 .00612 lgdpau | .000522 -.000293 .623476 lgdpdfrati~w | -.001264 .001746 -.017981 .07935 lpopau | -.006571 -.006076 -2.08273 .068991 7.36806 lpop | -.000293 -.004327 -.00057 -.000777 .000219 .009332 lxrate1 | .000175 -.000128 .000541 .000951 -.004995 -.000412 .000683 lremote | .001698 .004172 -.021751 -.012091 .06124 -.003121 .000284 ldist | .005138 .002104 -.008143 -.002462 -.016976 .002747 .000976 lopen | -.000261 .000715 .000327 -.000408 -.009914 .000609 8.1e-06 english | -.002343 .001381 .004198 .004773 -.01934 .000385 .000932 white | .012826 -.026545 .015882 -.006696 -.074949 .031006 .005482 lwhitemg | -.001339 .001303 -.002902 -.000261 .014694 -.001764 -.000487 _cons | .051584 -.008544 18.4862 -.64839 -67.8661 -.036359 .062214</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .063478 ldist | .029349 .100223 lopen | .001168 .002152 .002896 english | -.011371 .018286 -.000031 .050536 white | .016502 -.001625 -.001729 .022887 1.19642 lwhitemg | .000793 -.000118 .000079 -.001136 -.101071 .00935 _cons | -1.31773 -.837153 .103655 .0859 .657484 -.160985 661.726</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1479.97 Log likelihood = -343.5619 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval]</p><p>------+------limmig | .0263825 .0171724 1.54 0.124 -.0072749 .0600398 lgdp | .1791172 .0535608 3.34 0.001 .0741399 .2840945 lgdpau | -.2630462 .3062056 -0.86 0.390 -.8631982 .3371058 lgdpdfrati~w | -.4279195 .2008109 -2.13 0.033 -.8215016 -.0343375 lpopau | 2.82563 1.093471 2.58 0.010 .6824649 4.968794 lpop | .1686898 .0682549 2.47 0.013 .0349127 .3024669 lxrate1 | -.0833828 .0184504 -4.52 0.000 -.1195449 -.0472206 lremote | -.1198235 .1104546 -1.08 0.278 -.3363104 .0966635 ldist | -1.397671 .2475275 -5.65 0.000 -1.882816 -.9125261 lopen | .0124218 .02562 0.48 0.628 -.0377926 .0626361 english | 2.056049 .218207 9.42 0.000 1.628371 2.483727 white | 9.812052 1.781019 5.51 0.000 6.321319 13.30279 lwhitemg | -.7186988 .1831724 -3.92 0.000 -1.07771 -.3596874 _cons | -30.73952 11.20156 -2.74 0.006 -52.69417 -8.784869 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000295 lgdp | -.000321 .002869 lgdpau | .000282 -.001468 .093762 lgdpdfrati~w | -.00042 -.000402 -.001312 .040325 lpopau | -.001297 .006732 -.321549 .022487 1.19568 lpop | .000132 -.002779 .000916 .000971 -.007747 .004659 lxrate1 | -.000011 .000161 .001219 .000774 -.005816 -.000146 .00034 lremote | .000186 .000893 -.006866 -.003307 .024219 -.000405 -.000368 ldist | .000955 .000876 -.002789 -.000931 -.000114 .002739 -.000299 lopen | .000028 -.000274 -.00016 .001068 -.000894 .000339 -9.3e-06 english | -.000172 -.002789 .003229 .003654 -.014305 .005173 .000257 white | .001603 -.022867 .014301 .003622 -.080163 .024837 .001008 lwhitemg | -.000156 .001417 -.001231 -.000073 .006192 -.001727 -.000079 _cons | .007442 -.107403 2.9741 -.351966 -11.6385 .070206 .067337</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .0122 ldist | .003227 .06127 lopen | -.000116 -.000076 .000656 english | -.002909 .025204 -.000068 .047614 white | .010934 -.035523 .001416 .062783 3.17203 lwhitemg | -.000487 .002425 -.000072 -.00578 -.32208 .033552 _cons | -.36814 -.603791 .020865 -.090336 1.29156 -.092208 125.475</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1094.96 Log likelihood = -837.9038 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0968771 .0638685 1.52 0.129 -.0283028 .222057 lgdp | .5212526 .1078169 4.83 0.000 .3099355 .7325698 lgdpau | -2.380939 1.090517 -2.18 0.029 -4.518313 -.2435646 lgdpdfrati~w | -1.09083 .441698 -2.47 0.014 -1.956543 -.2251182 lpopau | 5.598692 3.737466 1.50 0.134 -1.726606 12.92399 lpop | .2452029 .1231848 1.99 0.047 .0037652 .4866406 lxrate1 | -.1715976 .0389703 -4.40 0.000 -.247978 -.0952172 lremote | 1.766789 .2797282 6.32 0.000 1.218531 2.315046 ldist | -2.035304 .4352921 -4.68 0.000 -2.888461 -1.182147 lopen | -.0078974 .0752148 -0.10 0.916 -.1553156 .1395209 english | .288331 .2557889 1.13 0.260 -.213006 .789668 white | 11.19059 1.525278 7.34 0.000 8.2011 14.18008 lwhitemg | -.8347942 .1471931 -5.67 0.000 -1.123287 -.5463011 _cons | -37.92606 35.10888 -1.08 0.280 -106.7382 30.88608 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004079 lgdp | -.004175 .011624 lgdpau | -.002079 .005785 1.18923 lgdpdfrati~w | -.00177 .004558 -.000669 .195097 lpopau | .003513 -.027716 -3.97471 .05161 13.9686 lpop | .001309 -.010012 -.00268 -.002838 .013224 .015174 lxrate1 | .000075 .001547 .000777 .001427 -.009133 -.001531 .001519 lremote | .001704 -.003358 -.03462 -.022181 .090247 .002926 .000927 ldist | .011478 -.009775 -.009396 -.010328 .003332 .010802 -.002528 lopen | .00033 -.000781 .006408 .000841 -.032952 .002034 -.000361 english | -.005361 .010697 .007168 .001257 -.027449 -.008691 -.000441 white | .025743 -.050143 -.043163 -.04219 .074852 .04837 .004574 lwhitemg | -.002864 .002934 -.000087 .001242 .010061 -.002313 -.000707 _cons | -.074106 .337795 35.057 -.797983 -128.002 -.287642 .129693</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .078248 ldist | .02042 .189479 lopen | .002766 .004235 .005657 english | -.003627 .022804 -.000676 .065428 white | .126338 .113996 .002121 .027893 2.32647 lwhitemg | -.004881 -.01455 -.000107 -.004796 -.214028 .021666 _cons | -1.4342 -1.7852 .303441 -.008392 -2.07835 .005157 1232.63</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 564.79 Log likelihood = -93.35484 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0284354 .0282932 1.01 0.315 -.0270182 .0838891 lgdp | .1361638 .0588475 2.31 0.021 .0208247 .2515028 lgdpau | .3390156 .3995034 0.85 0.396 -.4439967 1.122028 lgdpdfrati~w | .3561704 .1837151 1.94 0.053 -.0039046 .7162453 lpopau | 2.304246 1.409654 1.63 0.102 -.4586252 5.067117 lpop | .3099671 .0784223 3.95 0.000 .1562623 .4636719 lxrate1 | -.0301747 .0164441 -1.83 0.067 -.0624045 .0020551</p><p> lremote | -.0278513 .125686 -0.22 0.825 -.2741914 .2184887 ldist | -2.262419 .4228087 -5.35 0.000 -3.091109 -1.43373 lopen | .0566143 .0373959 1.51 0.130 -.0166803 .1299088 english | .884231 .1847197 4.79 0.000 .522187 1.246275 white | 16.18959 1.215571 13.32 0.000 13.80711 18.57206 lwhitemg | -1.360877 .1131472 -12.03 0.000 -1.582641 -1.139112 _cons | -33.17937 14.5341 -2.28 0.022 -61.66568 -4.693056 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000801 lgdp | -.000584 .003463 lgdpau | -.000509 -.00014 .159603 lgdpdfrati~w | -.000683 .000811 -.000584 .033751 lpopau | .00134 .001671 -.535051 .016764 1.98712</p><p> lpop | -.000129 -.002549 .000376 .000582 -.004907 .00615 lxrate1 | .000053 .000103 .000217 .000545 -.002612 -.000121 .00027 lremote | .000838 .002019 -.007107 -.003313 .020559 -.001557 .000106 ldist | .002396 -.003353 -.009739 -.007708 .000129 .008101 .000133 lopen | -.000022 -.000043 .000061 .000324 -.003928 .000517 -.000047 english | -.001229 -.000841 .003005 .002615 -.014742 .004665 .00011 white | .003656 -.017101 .028662 -.004176 -.262907 .025476 .003358 lwhitemg | -.000443 .000926 -.002945 .000236 .025758 -.001919 -.000363 _cons | -.027536 -.044611 4.84229 -.221022 -19.0805 -.032232 .03343</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .015797 ldist | .016579 .178767 lopen | .000045 .000294 .001398 english | -.004791 .00583 .000152 .034121 white | -.00604 -.025689 -.000354 .046786 1.47761 lwhitemg | .000642 .003249 .000053 -.003951 -.134379 .012802 _cons | -.470422 -1.66111 .054096 .091974 3.84745 -.373046 211.24</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 257.33 Log likelihood = 163.268 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0100409 .0181377 -0.55 0.580 -.04559 .0255083 lgdp | .2575036 .0505501 5.09 0.000 .1584273 .35658 lgdpau | -.3040616 .3471429 -0.88 0.381 -.9844491 .376326 lgdpdfrati~w | -.1133802 .1412982 -0.80 0.422 -.3903196 .1635592 lpopau | 4.272561 1.264313 3.38 0.001 1.794552 6.750569 lpop | -.0506741 .0601367 -0.84 0.399 -.1685399 .0671917 lxrate1 | -.1012378 .0150807 -6.71 0.000 -.1307954 -.0716802 lremote | .3539631 .1270154 2.79 0.005 .1050175 .6029087 ldist | -1.385574 .2746741 -5.04 0.000 -1.923925 -.8472223 lopen | .0245476 .0283501 0.87 0.387 -.0310176 .0801129 english | .2764998 .1698855 1.63 0.104 -.0564696 .6094692</p><p> white | 9.606983 1.989022 4.83 0.000 5.708571 13.5054 lwhitemg | -.7997218 .1888978 -4.23 0.000 -1.169955 -.4294889 _cons | -56.78443 13.43348 -4.23 0.000 -83.11357 -30.45529 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000329 lgdp | -.000372 .002555 lgdpau | .000199 -.000691 .120508 lgdpdfrati~w | -.000448 .000434 -.005468 .019965 lpopau | -.002052 .003775 -.413391 .024934 1.59849 lpop | .000063 -.00213 -.000091 -.00007 .000149 .003616 lxrate1 | -1.9e-06 -2.1e-06 .000455 .000461 -.00424 -.000112 .000227 lremote | .000293 .001771 -.007426 -.001235 .0264 -.001348 -.000064 ldist | .001641 -.001904 -.002497 -.001537 .00463 .004592 .000046 lopen | -6.5e-06 .000012 .000135 .000192 -.001876 .000177 -.000028 english | -.000411 -.001791 .000123 .000725 .019736 .004736 .000212 white | .002335 -.014676 .016905 -.00463 -.133648 .015725 .001864 lwhitemg | -.00025 .000929 -.001946 .000464 .01331 -.001257 -.000132 _cons | .016989 -.063293 3.80422 -.27395 -16.0365 -.04201 .058846 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .016133 ldist | .007276 .075446 lopen | .000068 -.000464 .000804 english | -.001331 .015677 -.000323 .028861 white | -.001545 .015707 -.000686 .036922 3.95621 lwhitemg | .000691 -.002352 .000087 -.003497 -.369585 .035682 _cons | -.470924 -.834926 .028795 -.50867 1.69357 -.152482 180.458</p><p>. xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 461.02 Log likelihood = -678.8746 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval]</p><p>------+------limmig | .1722142 .0530418 3.25 0.001 .0682541 .2761743 lgdp | .7386342 .103786 7.12 0.000 .5352174 .942051 lgdpau | -.6500304 .6705563 -0.97 0.332 -1.964297 .6642358 lgdpdfrati~w | -.3490698 .2808695 -1.24 0.214 -.8995639 .2014244 lpopau | 3.758096 2.310149 1.63 0.104 -.7697132 8.285906 lpop | -.2965176 .1474685 -2.01 0.044 -.5855505 -.0074847 lxrate1 | -.1499564 .0317175 -4.73 0.000 -.2121216 -.0877912 lremote | .1421966 .2342146 0.61 0.544 -.3168556 .6012488 ldist | -3.310665 .6939471 -4.77 0.000 -4.670776 -1.950553 lopen | .0387889 .0644589 0.60 0.547 -.0875482 .1651261 english | -.4358269 .4318843 -1.01 0.313 -1.282305 .4106507 white | 20.4735 4.176446 4.90 0.000 12.28782 28.65918 lwhitemg | -1.829563 .3833548 -4.77 0.000 -2.580924 -1.078201 _cons | -24.06906 22.79283 -1.06 0.291 -68.74218 20.60406 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002813 lgdp | -.002332 .010772 lgdpau | .001386 -.001577 .449646 lgdpdfrati~w | -.001904 .00354 -.011003 .078888 lpopau | -.009337 .000928 -1.49634 .063014 5.33679 lpop | -.000097 -.007978 -.001416 -.001849 -.006763 .021747 lxrate1 | .000151 .000511 .002031 .001268 -.010649 -.000804 .001006 lremote | .001045 .00429 -.020427 -.012144 .039904 -.002887 .000484 ldist | .011413 .010509 -.006085 -.004485 -.052645 .005274 .000409 lopen | .000459 -.00103 -.000918 -.000164 -.010407 .001839 -.000196 english | -.006155 .002928 .001199 .006031 -.014833 .017149 .000532 white | .00746 -.033866 .125105 .018196 -.375749 .073487 .005208 lwhitemg | -.001285 .001374 -.013101 -.002928 .04241 -.005569 -.000599 _cons | .043517 -.222525 13.3166 -.735198 -49.0387 -.037842 .110456</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054856 ldist | .032676 .481563 lopen | .000639 .003122 .004155 english | -.00401 .128725 -.00144 .186524 white | .028702 .259039 .004525 .293684 17.4427 lwhitemg | -.000231 -.03906 -.000306 -.031967 -1.57439 .146961 _cons | -.964621 -4.24204 .157471 -1.33219 -.336198 .090882 519.513</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1175.49 Log likelihood = -575.5818 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1739229 .045648 3.81 0.000 .0844544 .2633913 lgdp | .5545926 .096714 5.73 0.000 .3650367 .7441485 lgdpau | .6649297 .6216074 1.07 0.285 -.5533984 1.883258 lgdpdfrati~w | -.0103192 .2736234 -0.04 0.970 -.5466112 .5259728 lpopau | -2.846907 2.148375 -1.33 0.185 -7.057646 1.363831 lpop | .5841719 .1226859 4.76 0.000 .343712 .8246318 lxrate1 | -.0964526 .0301166 -3.20 0.001 -.15548 -.0374252 lremote | -.2571137 .2227487 -1.15 0.248 -.6936932 .1794657 ldist | -2.299946 .4563953 -5.04 0.000 -3.194464 -1.405427 lopen | -.0729371 .068514 -1.06 0.287 -.2072221 .0613479 english | 1.221383 .3233516 3.78 0.000 .587626 1.855141 white | 24.24393 3.098551 7.82 0.000 18.17088 30.31698 lwhitemg | -2.294231 .2740661 -8.37 0.000 -2.831391 -1.757072 _cons | 35.25527 20.69399 1.70 0.088 -5.304211 75.81475 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002084 lgdp | -.001777 .009354 lgdpau | -.002345 .004663 .386396 lgdpdfrati~w | -.0018 .002755 -.005257 .07487 lpopau | .006977 -.032265 -1.29073 .019274 4.61552 lpop | .000335 -.007426 -.002752 -.001899 .012853 .015052 lxrate1 | .000068 .000611 .000395 .00123 -.005038 -.000779 .000907 lremote | .000485 .003668 -.016635 -.017164 .036458 -.002766 .000483 ldist | .007607 -.001185 -.008749 -.001687 -.007484 .015988 .000445 lopen | .000215 -.000228 .000635 .001973 -.012938 .001567 -.000095 english | -.003278 .001532 .005507 .005663 -.023866 .0009 .00061 white | .005753 -.03148 .017814 -.012108 -.019671 .052156 .004678 lwhitemg | -.000877 .001027 -.003154 -.000391 .011008 -.003744 -.000471 _cons | -.104674 .304018 11.457 -.115616 -42.486 -.337344 .058817</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .049617 ldist | .006307 .208297 lopen | .001324 .002212 .004694 english | -.008032 .062886 -.001566 .104556 white | .025282 .034792 .004894 .015469 9.60102 lwhitemg | .000247 -.007841 -.000472 .000457 -.834297 .075112 _cons | -.686506 -1.9586 .145877 -.344229 -.867983 .015512 428.241 . xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1695.69 Log likelihood = -761.6325 Prob > chi2 = 0.0000</p><p>------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0604128 .0349294 1.73 0.084 -.0080476 .1288733 lgdp | 1.036239 .0993471 10.43 0.000 .841522 1.230955 lgdpau | .7430203 .732011 1.02 0.310 -.691695 2.177736 lgdpdfrati~w | -.1012687 .2931925 -0.35 0.730 -.6759154 .473378 lpopau | 3.775588 2.548039 1.48 0.138 -1.218478 8.769653 lpop | -.4573398 .1456388 -3.14 0.002 -.7427867 -.1718929 lxrate1 | -.1516339 .0251384 -6.03 0.000 -.2009042 -.1023636</p><p> lremote | -.3001995 .2006969 -1.50 0.135 -.6935582 .0931592 ldist | -1.413843 .7642149 -1.85 0.064 -2.911677 .0839903 lopen | -.0318307 .0741464 -0.43 0.668 -.1771549 .1134936 english | .0421561 .3364824 0.13 0.900 -.6173373 .7016496 white | 28.46025 2.589472 10.99 0.000 23.38498 33.53552 lwhitemg | -2.652407 .2491352 -10.65 0.000 -3.140703 -2.164111 _cons | -79.46205 25.3572 -3.13 0.002 -129.1613 -29.76284 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00122 lgdp | -.00198 .00987 lgdpau | .000017 .000604 .53584 lgdpdfrati~w | -.00228 .00411 -.017367 .085962 lpopau | -.007402 -.008212 -1.79153 .073875 6.4925</p><p> lpop | .001809 -.012119 -.003844 -.003499 .026591 .021211 lxrate1 | .000015 .000496 .001123 .001002 -.010996 -.000909 .000632 lremote | .00141 .00435 -.018801 -.005417 .016068 -.003504 .000352 ldist | .007667 .011952 -.026473 -.008344 -.06997 .01237 .00148 lopen | .000249 -.000497 -.002218 .005105 -.00161 .000823 -.000271 english | -.00145 .003656 .00439 .004595 -.010017 -.001231 .001094 white | .017964 -.057835 .047152 -.031899 -.44538 .070234 .009189 lwhitemg | -.00163 .003932 -.005902 .00247 .049933 -.005014 -.000906 _cons | .049207 -.059584 16.137 -.757766 -60.429 -.489633 .134988</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .040279 ldist | .073446 .584024 lopen | .001583 .001917 .005498 english | -.000067 .054343 -.00105 .11322 white | .039448 .112013 -.008457 .215034 6.70536 lwhitemg | -.002713 -.017804 .001007 -.024188 -.635142 .062068 _cons | -.873087 -4.87866 .0499 -.54216 4.82046 -.478835 642.988</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 489.61 Log likelihood = -588.7158 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3625979 .0568412 6.38 0.000 .2511912 .4740047 lgdp | .2298792 .0964948 2.38 0.017 .040753 .4190055 lgdpau | 1.117573 .7365248 1.52 0.129 -.3259894 2.561135 lgdpdfrati~w | -.5360761 .3131689 -1.71 0.087 -1.149876 .0777236 lpopau | -4.391215 2.54419 -1.73 0.084 -9.377735 .5953052 lpop | .3817684 .1030221 3.71 0.000 .1798488 .583688 lxrate1 | -.1042807 .0327675 -3.18 0.001 -.1685038 -.0400576 lremote | .0482848 .2206614 0.22 0.827 -.3842036 .4807732 ldist | -1.563309 .5932678 -2.64 0.008 -2.726093 -.4005258 lopen | .0919748 .0707299 1.30 0.193 -.0466532 .2306029 english | -.0408124 .2816846 -0.14 0.885 -.5929041 .5112792</p><p> white | 19.54097 2.076355 9.41 0.000 15.47139 23.61055 lwhitemg | -1.802088 .196605 -9.17 0.000 -2.187427 -1.416749 _cons | 49.80833 24.04697 2.07 0.038 2.677136 96.93953 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003231 lgdp | -.003067 .009311 lgdpau | -.002256 .006403 .542469 lgdpdfrati~w | -.002709 .005805 -.009812 .098075 lpopau | .005143 -.034298 -1.81523 .049071 6.4729 lpop | .001157 -.005965 -.004044 -.003719 .010687 .010614 lxrate1 | .00019 .000364 -.000242 .00077 -.003184 -.000463 .001074 lremote | .000378 .002977 -.007575 -.015711 -.005752 .000606 .001249 ldist | .011028 .003332 -.002399 -.009429 -.085664 .004738 .000526 lopen | -.000315 .000778 .00222 .000046 -.022574 .001645 -.000149 english | -.003132 .007548 .006459 .00323 -.032127 -.001295 -.000995 white | .023335 -.036658 -.000775 -.067676 .06839 .012073 -.000091 lwhitemg | -.002575 .002009 -.001607 .004158 .004119 -.000199 -.000242 _cons | -.101397 .238401 15.9139 -.486114 -58.4002 -.157124 .038342</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .048691 ldist | .038537 .351967 lopen | .002327 .003853 .005003 english | .00782 .098095 .00005 .079346 white | .105288 .216157 -.00788 .141376 4.31125 lwhitemg | -.007617 -.032043 .000723 -.017449 -.399497 .038654 _cons | -.570283 -2.41796 .221895 -.783673 -3.59239 .320645 578.257</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1527.34 Log likelihood = -240.4558 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval]</p><p>------+------limmig | -.0000556 .0252608 -0.00 0.998 -.0495659 .0494547 lgdp | .4086143 .0817787 5.00 0.000 .248331 .5688975 lgdpau | -.361918 .472482 -0.77 0.444 -1.287966 .5641297 lgdpdfrati~w | .1579953 .223798 0.71 0.480 -.2806408 .5966314 lpopau | 1.492688 1.630188 0.92 0.360 -1.702422 4.687798 lpop | -.2053141 .1154418 -1.78 0.075 -.4315759 .0209477 lxrate1 | -.0421345 .0222725 -1.89 0.059 -.0857879 .0015189 lremote | .0054632 .1650747 0.03 0.974 -.3180772 .3290037 ldist | -3.957252 .5079682 -7.79 0.000 -4.952852 -2.961653 lopen | -.0024782 .0483103 -0.05 0.959 -.0971646 .0922082 english | -.0679611 .2803388 -0.24 0.808 -.617415 .4814927 white | 17.10944 2.547544 6.72 0.000 12.11634 22.10253 lwhitemg | -1.261077 .2724716 -4.63 0.000 -1.795112 -.7270426 _cons | 17.76772 16.4016 1.08 0.279 -14.37882 49.91426 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000638 lgdp | -.000765 .006688 lgdpau | .00014 -.002198 .223239 lgdpdfrati~w | -.001067 .002667 -.009161 .050086 lpopau | -.001145 .002051 -.74451 .051463 2.65751 lpop | .000151 -.006132 -.000019 -.001042 -.003966 .013327 lxrate1 | -.000034 .00016 .00132 .000967 -.00625 -.000461 .000496 lremote | .000152 .00222 -.016332 -.003253 .046982 -.002228 -.000086 ldist | .002545 .002882 -.011041 -.001777 -.012228 .017699 -.000321 lopen | .000059 -.000216 -.001941 .001359 .001935 .000811 -.000015 english | -.001306 .000616 .001414 .002318 -.002967 .004649 .000527 white | .004016 -.037367 .033911 -.016505 -.230634 .062945 .001961 lwhitemg | -.000443 .00167 -.004034 .000971 .027541 -.004965 -.000016 _cons | .002702 -.074223 6.79312 -.662233 -24.8644 -.153545 .073426</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .02725 ldist | .01372 .258032 lopen | .000053 .000833 .002334 english | -.000178 .053566 .000134 .07859 white | .002735 .154832 .000057 .107396 6.48998 lwhitemg | .001988 -.019639 .000072 -.010905 -.684509 .074241 _cons | -.732687 -2.46165 .002094 -.595266 1.25072 -.138681 269.012</p><p>. . . clear</p><p>. insheet using k:\book1.txt (104 vars, 1010 obs)</p><p>. *Dropping Malaysia . drop if ccode==454580 (10 observations deleted)</p><p>. . . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist op > en english gdpdfrationew white whitemg, stat(n mean sd median min max) col(sta > t) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 478531.1 1559266 7348 0 1.39e+07 immig | 1000 32694.03 117003.3 2790 0 1137050 gdp | 1000 2.78e+11 9.70e+11 1.63e+10 1.92e+08 8.99e+12 gdpau | 1000 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 1000 105.5849 16.88431 102.6773 60.87417 207.3465 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.94e+07 1.54e+08 1.02e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1043.094 10901.71 16.2185 .0068 270182.6 remote | 1000 6730.858 4145.482 6764 1293 39620 dist | 1000 13438.77 3463.287 14305 2409 17972 open | 1000 .6976544 .3745764 .63155 .0671 3.2192 english | 1000 .37 .4830459 0 0 1 gdpdfratio~w | 1000 1.051367 .1809408 1.013736 .5844526 2.009028 white | 1000 .13 .3364717 0 0 1 whitemg | 1000 20501.65 116468.1 0 0 1137050 ------</p><p>. . sort white</p><p>. *IIIB. Descriptives Original Unites(sub sample for "white" and "non-white" cou > ntries)--RHS Variables: . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remo > te dist phone open english gdpdfrationew white whitemg, stat(n mean sd median > min max) col(stat) </p><p>------> white = 0</p><p> variable | N mean sd p50 min max ------+------rimp | 870 390387.7 1594626 2944.5 0 1.39e+07 immig | 870 14014.22 26332.15 1403.5 0 158613 gdp | 870 2.36e+11 1.00e+12 1.00e+10 1.92e+08 8.99e+12 gdpau | 870 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 870 104.6954 17.23196 101.6138 60.87417 207.3465 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.33e+07 1.65e+08 1.03e+07 41000 1.26e+09 popau | 870 1.82e+07 612839.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 870 1182.965 11681.74 22.9426 .0068 270182.6 remote | 870 7155.961 4116.651 6927 1293 39620 dist | 870 13279.51 3343.661 14051 2410 17972 phone | 870 156.6631 242.0474 47.025 .54 1449.75 open | 870 .7034895 .3949042 .6248 .0671 3.2192 english | 870 .3793103 .4854945 0 0 1 gdpdfratio~w | 870 1.04276 .1857486 1 .5844526 2.009028 white | 870 0 0 0 0 0 whitemg | 870 0 0 0 0 0 ------</p><p>------> white = 1</p><p> variable | N mean sd p50 min max ------+------rimp | 130 1068414 1138347 522863.5 40432 3843839 immig | 130 157705 288518.8 21174 2612 1137050 gdp | 130 5.56e+11 6.58e+11 2.54e+11 5.15e+10 2.69e+12 gdpau | 130 3.83e+11 4.46e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 130 111.5379 12.89742 112.2247 85.45601 143.9587 gdpdfau | 130 100.7173 4.649088 100.8223 94.42464 109.9797 pop | 130 2.34e+07 2.55e+07 8837000 3477200 8.22e+07 popau | 130 1.82e+07 614856.7 1.82e+07 1.73e+07 1.92e+07 xrate1 | 130 107.0323 293.6987 4.4722 .3774 1261.556 remote | 130 3885.938 3089.96 2888 1530 12501 dist | 130 14504.62 4031.974 15931 2409 17493 phone | 130 734.716 269.9717 652.085 343.99 1487.08 open | 130 .6586038 .1850905 .64065 .3517 1.2967 english | 130 .3076923 .4633239 0 0 1 gdpdfratio~w | 130 1.108974 .1314272 1.116445 .8254872 1.441221 white | 130 1 0 1 1 1 whitemg | 130 157705 288518.8 21174 2612 1137050 ------</p><p>. . . **Regression of Imports . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Imports . xtgls lrimp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8769.08 Log likelihood = -552.3821 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3319121 .0308639 10.75 0.000 .27142 .3924042 lgdp | 1.188423 .0331268 35.87 0.000 1.123495 1.25335 lgdpau | .0546165 .6094788 0.09 0.929 -1.13994 1.249173 lgdpdfrati~w | -.9819625 .2481502 -3.96 0.000 -1.468328 -.4955971 lpopau | -2.436458 2.100719 -1.16 0.246 -6.553792 1.680877 lpop | .0271248 .040996 0.66 0.508 -.0532259 .1074755 lxrate1 | -.1376873 .0173529 -7.93 0.000 -.1716984 -.1036763 lremote | -.4295646 .0757036 -5.67 0.000 -.5779409 -.2811883 ldist | -2.166136 .1720829 -12.59 0.000 -2.503412 -1.828859 lopen | .2977019 .0574748 5.18 0.000 .1850534 .4103505 english | .8885425 .1279535 6.94 0.000 .6377582 1.139327 white | 4.56261 .5723084 7.97 0.000 3.440907 5.684314 lwhitemg | -.4254808 .0509182 -8.36 0.000 -.5252786 -.325683 _cons | 41.97249 19.38767 2.16 0.030 3.973362 79.97162 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000953 lgdp | -.000297 .001097 lgdpau | -.000887 .001301 .371464 lgdpdfrati~w | -.000775 .000085 -.007577 .061579 lpopau | .001623 -.007857 -1.25471 .043208 4.41302 lpop | -.000147 -.000745 .000154 .000205 -.000204 .001681 lxrate1 | .000074 .000154 .000325 .000203 -.002217 -.000072 .000301 lremote | .000468 .000077 -.000575 -.00176 -.00286 -.000237 .000107 ldist | .001476 .000993 .000167 -.001279 -.010838 .000217 .002018 lopen | -.000135 .000614 .002512 .000688 -.017782 .00029 .000085 english | -.001141 .002787 .002824 .002072 -.010536 -.001397 .000523 white | .004742 -.002074 .003194 -.010107 -.027212 .004974 .000172 lwhitemg | -.00058 .000187 -.000304 .000945 .003053 -.000391 -.000032 _cons | -.01897 .072401 11.0529 -.555764 -40.0435 -.008238 .003945</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .005731 ldist | .005243 .029613 lopen | .00135 .000137 .003303 english | -.003302 .00248 -.000749 .016372 white | -.000312 -.002231 .000083 -.000256 .327537 lwhitemg | .00014 -.00023 -.000103 .00018 -.028679 .002593 _cons | -.03397 -.19292 .199521 .057899 .322282 -.035486 375.882</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 72690.02 Log likelihood = -993.4403 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0507731 .0135944 3.73 0.000 .0241285 .0774177 lgdp | 1.651868 .0501365 32.95 0.000 1.553602 1.750134 lgdpau | .8288366 .3495792 2.37 0.018 .1436741 1.513999 lgdpdfrati~w | -.5101017 .1461042 -3.49 0.000 -.7964608 -.2237427 lpopau | -6.184542 1.181515 -5.23 0.000 -8.50027 -3.868815 lpop | -.4310168 .0838222 -5.14 0.000 -.5953053 -.2667282 lxrate1 | -.1151397 .0205117 -5.61 0.000 -.1553419 -.0749375 lremote | -.8981665 .0994518 -9.03 0.000 -1.093088 -.7032446 ldist | -2.823473 .1584179 -17.82 0.000 -3.133966 -2.512979 lopen | -.0699412 .0265698 -2.63 0.008 -.122017 -.0178654 english | .9939125 .0858138 11.58 0.000 .8257204 1.162105 white | 3.81619 .7964741 4.79 0.000 2.255129 5.37725 lwhitemg | -.3764344 .0762765 -4.94 0.000 -.5259336 -.2269353 _cons | 89.58546 11.10597 8.07 0.000 67.81817 111.3528 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000185 lgdp | -.000241 .002514 lgdpau | -.001179 .00181 .122206 lgdpdfrati~w | -.000553 .000454 -.011169 .021346 lpopau | .00465 -.007056 -.404097 .021364 1.39598 lpop | .000146 -.003972 -.001583 .000581 .003938 .007026 lxrate1 | -.000025 .000265 -.000067 .000439 -.003209 -.000278 .000421 lremote | .000358 .000067 -.006822 -.003517 .024742 -.000799 .000015 ldist | .000708 -.003719 -.006321 -.000097 .013421 .006487 .000558 lopen | .000041 -.000097 -.000983 .000889 .003698 .000252 -.00008 english | -.000396 .000177 .002975 .002755 -.020505 .000439 .001154 white | .000964 -.011506 -.011248 -.003057 .039195 .017902 -.000586 lwhitemg | -.000083 .000509 .000432 .000109 -.002234 -.00072 .000095 _cons | -.053198 .110254 3.6179 -.067777 -12.8375 -.100048 .046121</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .009891 ldist | .001361 .025096 lopen | .000673 .000319 .000706 english | -.002797 .003441 -.000422 .007364 white | .008723 .003026 .001626 -.000676 .634371 lwhitemg | .000016 .000962 -.00011 .000273 -.059029 .005818 _cons | -.318431 -.334712 -.04687 .237006 -.480609 .015913 123.342 . . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7870.40 Log likelihood = -950.2895 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0950162 .0222862 4.26 0.000 .0513359 .1386964 lgdp | 1.798205 .0713393 25.21 0.000 1.658382 1.938027 lgdpau | .1967765 .5643969 0.35 0.727 -.9094212 1.302974 lgdpdfrati~w | -.4589376 .210714 -2.18 0.029 -.8719294 -.0459457 lpopau | -3.124809 1.944532 -1.61 0.108 -6.936022 .6864033 lpop | -.7369972 .078161 -9.43 0.000 -.89019 -.5838044 lxrate1 | -.1450545 .0271775 -5.34 0.000 -.1983215 -.0917875 lremote | -.3929521 .1303276 -3.02 0.003 -.6483895 -.1375146 ldist | -4.19125 .3645294 -11.50 0.000 -4.905715 -3.476786 lopen | .0591057 .0424221 1.39 0.164 -.02404 .1422515 english | .9865931 .1379477 7.15 0.000 .7162206 1.256966 white | 9.353472 1.96826 4.75 0.000 5.495753 13.21119 lwhitemg | -.8118031 .1970068 -4.12 0.000 -1.197929 -.4256768 _cons | 65.44854 18.39358 3.56 0.000 29.39777 101.4993 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000497 lgdp | -.000849 .005089 lgdpau | -.001944 .004921 .318544 lgdpdfrati~w | -.000751 .001859 -.016436 .0444 lpopau | .005715 -.025174 -1.06462 .044616 3.7812 lpop | .000626 -.00404 -.002433 -.000979 .010973 .006109 lxrate1 | .00001 .000583 -.000034 .001028 -.005079 -.000826 .000739 lremote | -.00008 -.001118 -.009126 -.001416 .030966 -.001531 .000227 ldist | .002043 .009224 -.010014 -.003499 -.015848 -.001855 .001323 lopen | .000084 -.000534 -.000136 .001973 .000557 .000958 -.000179 english | -.000857 .003415 .006743 .002756 -.037381 .00083 .001742 white | .001562 -.030623 .000719 .004304 .026199 .020678 .003445 lwhitemg | -.000129 .00155 -.001848 -.000836 .00655 -.001341 -.0004 _cons | -.054812 .161014 9.43408 -.332633 -34.6026 -.092193 .066407</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .016985 ldist | .006066 .132882 lopen | .000522 -.000769 .0018 english | -.006424 .007318 -.001355 .01903 white | .014194 -.166337 .002611 .005543 3.87405 lwhitemg | .00104 .012756 -.000147 -.001747 -.38002 .038812 _cons | -.433338 -.985531 -.00658 .331057 1.3331 -.201689 338.324</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2093.85 Log likelihood = -1102.658 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0877301 .0421807 2.08 0.038 .0050575 .1704026 lgdp | .9250313 .0816721 11.33 0.000 .7649569 1.085106 lgdpau | -.4391755 .8188661 -0.54 0.592 -2.044123 1.165772 lgdpdfrati~w | -.4545578 .3446277 -1.32 0.187 -1.130016 .2209001 lpopau | .0931077 2.81162 0.03 0.974 -5.417567 5.603782 lpop | .0614884 .1004838 0.61 0.541 -.1354563 .258433 lxrate1 | -.1297017 .0333195 -3.89 0.000 -.1950067 -.0643966 lremote | .5386806 .2295831 2.35 0.019 .0887059 .9886553 ldist | -1.525142 .3471277 -4.39 0.000 -2.205499 -.8447837 lopen | .3196298 .0797412 4.01 0.000 .16334 .4759196 english | 1.683746 .2440313 6.90 0.000 1.205453 2.162038 white | 1.539698 2.185708 0.70 0.481 -2.744211 5.823606 lwhitemg | .1887808 .1927763 0.98 0.327 -.1890539 .5666155 _cons | .8545275 26.80095 0.03 0.975 -51.67437 53.38343 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001779 lgdp | -.00168 .00667 lgdpau | -.001379 .00107 .670542 lgdpdfrati~w | -.0003 .001657 -.008789 .118768 lpopau | .001981 -.008148 -2.24722 .03443 7.90521 lpop | .000337 -.00591 .000237 -.001275 -.00241 .010097 lxrate1 | .00012 .000882 .000592 .002066 -.007577 -.001144 .00111 lremote | .001303 .000746 -.027457 -.0143 .083169 .000213 -.000657 ldist | .004426 -.007319 -.019224 -.006203 .058758 .011444 -.000087 lopen | .000294 -.001106 .005045 .001656 -.028502 .00287 -.00019 english | -.003729 .001275 .008992 .005777 -.014943 -.000647 .001432 white | .004243 -.024938 .113501 .007475 -.460947 .022036 .000899 lwhitemg | -.000588 .000996 -.011917 -.002064 .049368 -.000356 -.000213 _cons | -.025141 .118746 20.0994 -.299457 -73.3321 -.100269 .108317</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .052708 ldist | .020312 .120498 lopen | .001795 -.000997 .006359 english | -.014123 .013848 -.00188 .059551 white | .036657 -.026081 .006414 .038155 4.77732 lwhitemg | -.00042 .006189 -.000392 -.002688 -.410332 .037163 _cons | -1.32129 -1.83836 .316267 -.023153 4.77489 -.574333 718.291</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 55884.36 Log likelihood = -922.2653 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0252197 .0135892 1.86 0.063 -.0014146 .051854 lgdp | 1.558779 .0539686 28.88 0.000 1.453003 1.664556 lgdpau | .6597161 .3583793 1.84 0.066 -.0426945 1.362127 lgdpdfrati~w | -.2909801 .140794 -2.07 0.039 -.5669313 -.015029 lpopau | -6.552746 1.213705 -5.40 0.000 -8.931565 -4.173927 lpop | -.1769547 .0934082 -1.89 0.058 -.3600313 .0061219 lxrate1 | -.0484403 .0192136 -2.52 0.012 -.0860982 -.0107824 lremote | -.650715 .1509658 -4.31 0.000 -.9466025 -.3548274 ldist | -2.502114 .170603 -14.67 0.000 -2.83649 -2.167738 lopen | -.0536621 .0269762 -1.99 0.047 -.1065345 -.0007897 english | 1.159382 .1099805 10.54 0.000 .9438242 1.37494 white | 3.558418 .8872718 4.01 0.000 1.819397 5.297439 lwhitemg | -.2679494 .0818223 -3.27 0.001 -.428318 -.1075807 _cons | 92.69599 11.48846 8.07 0.000 70.17903 115.213 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000185 lgdp | -.000192 .002913 lgdpau | -.000944 .002046 .128436 lgdpdfrati~w | -.000361 .000654 -.007825 .019823 lpopau | .00344 -.006806 -.425746 .011517 1.47308 lpop | .000113 -.004761 -.001749 .000193 .00277 .008725 lxrate1 | -1.1e-06 .000213 -.000033 .000511 -.002888 -.000215 .000369 lremote | -.000027 -.000936 -.013228 -.005491 .04899 .000158 -.000257 ldist | .000809 -.005423 -.004419 .00167 .002678 .009892 .000737 lopen | .000019 -.000101 -.000984 .0008 .003628 .00027 -.000072 english | -.000322 -.00018 .003761 .003131 -.020692 .000224 .001044 white | .000464 -.016638 -.016068 -.000874 .022359 .029586 .002388 lwhitemg | -.000087 .000784 .000118 -.000444 .002624 -.001588 -.000259 _cons | -.03771 .128402 3.84461 .009935 -13.633 -.126031 .040768</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .022791 ldist | -.003076 .029105 lopen | .001129 .000227 .000728 english | -.004725 .006214 -.000488 .012096 white | .016971 .032762 .001034 .007594 .787251 lwhitemg | .000937 -.002084 .000014 -.000625 -.069401 .006695 _cons | -.611418 -.223488 -.048857 .219476 -.512371 -.026043 131.985</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 8739.02 Log likelihood = -980.905 Prob > chi2 = 0.0000</p><p>------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1248714 .02467 5.06 0.000 .0765192 .1732236 lgdp | 1.825572 .070182 26.01 0.000 1.688018 1.963126 lgdpau | .0249068 .5948312 0.04 0.967 -1.140941 1.190755 lgdpdfrati~w | -.4335251 .2280058 -1.90 0.057 -.8804083 .0133581 lpopau | -2.675511 2.041263 -1.31 0.190 -6.676312 1.32529 lpop | -.7800982 .075145 -10.38 0.000 -.9273796 -.6328167 lxrate1 | -.1366665 .0278533 -4.91 0.000 -.1912579 -.0820751 lremote | -.3368959 .1233527 -2.73 0.006 -.5786626 -.0951291 ldist | -3.600693 .3466666 -10.39 0.000 -4.280147 -2.921239 lopen | .0809146 .0452894 1.79 0.074 -.007851 .1696803 english | .8328061 .1240826 6.71 0.000 .5896086 1.076004 white | 9.228247 1.950654 4.73 0.000 5.405035 13.05146 lwhitemg | -.8322535 .1951462 -4.26 0.000 -1.214733 -.4497739 _cons | 56.33691 19.21466 2.93 0.003 18.67687 93.99694 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000609 lgdp | -.001061 .004926 lgdpau | -.002082 .004581 .353824 lgdpdfrati~w | -.000926 .002232 -.018861 .051987 lpopau | .00676 -.02494 -1.17993 .048527 4.16675 lpop | .000791 -.003996 -.002604 -.001128 .014092 .005647 lxrate1 | .000011 .00057 -.000244 .001144 -.00497 -.000852 .000776 lremote | -.0001 -.000934 -.007114 -.00121 .021 -.000958 .000266 ldist | .002499 .005377 -.012058 -.004552 -.002019 .00077 .001165 lopen | .000087 -.000614 .000298 .00234 -.001723 .001244 -.000199 english | -.000861 .00362 .004373 .002802 -.024357 -.001308 .001721 white | .001499 -.027417 .003958 .005282 .029549 .013457 .003482 lwhitemg | -.000098 .00149 -.001812 -.000961 .004451 -.000748 -.000384 _cons | -.071053 .204425 10.4381 -.33835 -38.0851 -.162747 .071778</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .015216 ldist | .006332 .120178 lopen | .000322 -.001206 .002051 english | -.00461 .008998 -.001184 .015396 white | .017667 -.16782 .003977 -.009854 3.80505 lwhitemg | .000471 .0145 -.000287 -.000091 -.374011 .038082 _cons | -.321557 -1.00149 .02293 .175618 1.22587 -.188196 369.203</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7943.73 Log likelihood = -1105.774 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0193193 .0152058 1.27 0.204 -.0104835 .0491222 lgdp | 1.334891 .0490521 27.21 0.000 1.23875 1.431031 lgdpau | .4745109 .4805468 0.99 0.323 -.4673435 1.416365 lgdpdfrati~w | -.0828652 .1551472 -0.53 0.593 -.3869481 .2212177 lpopau | -5.348937 1.63314 -3.28 0.001 -8.549832 -2.148042 lpop | .0910258 .0714394 1.27 0.203 -.0489928 .2310443 lxrate1 | -.0579902 .0191233 -3.03 0.002 -.0954711 -.0205093 lremote | -.7260258 .1579493 -4.60 0.000 -1.035601 -.4164508 ldist | -3.154192 .2203222 -14.32 0.000 -3.586016 -2.722369 lopen | .0627187 .0401126 1.56 0.118 -.0159005 .141338 english | 2.395015 .1351291 17.72 0.000 2.130166 2.659863 white | 4.044611 1.151494 3.51 0.000 1.787724 6.301498 lwhitemg | -.1709226 .0968186 -1.77 0.077 -.3606835 .0188384 _cons | 83.99528 15.67968 5.36 0.000 53.26367 114.7269 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000231 lgdp | -.000375 .002406 lgdpau | -.00005 4.4e-06 .230925 lgdpdfrati~w | -.000405 .000563 .001937 .024071 lpopau | -.001334 .001686 -.766026 -.005187 2.66714 lpop | .000176 -.002722 -.00021 .000029 -.002675 .005104 lxrate1 | -.000015 .000202 .000299 .000589 -.002218 -.000374 .000366 lremote | .000164 .00066 -.017809 -.000682 .055382 -.001009 -.00009 ldist | .000581 .000154 -.011749 -.000962 .025256 .000539 .000383 lopen | .000056 -.000271 .000046 .001772 .000277 .000634 -.00013 english | -.000709 .000278 .002344 .001436 -.009876 .002073 .000932 white | .000305 -.01327 -.003665 -.000767 .001729 .024428 -.000157 lwhitemg | -7.3e-06 .000677 -.00102 .000183 .00373 -.001601 .000082 _cons | .021873 -.04522 6.91866 .012779 -24.8662 .033262 .025121</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .024948 ldist | .016487 .048542 lopen | .000806 -.00008 .001609 english | -.00378 .00238 -.001216 .01826 white | .003208 -.007239 .000712 .034101 1.32594 lwhitemg | .001443 .002904 -.000014 -.002992 -.107699 .009374 _cons | -.826757 -.737778 -.016401 .066434 .004485 -.065294 245.852</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremo > te ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 450.63 Log likelihood = -654.5953 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5338211 .0550389 9.70 0.000 .4259469 .6416954 lgdp | .0269234 .0938892 0.29 0.774 -.157096 .2109428 lgdpau | -.7293405 .7927076 -0.92 0.358 -2.283019 .8243379 lgdpdfrati~w | -.523833 .3114311 -1.68 0.093 -1.134227 .0865608 lpopau | .5244073 2.71081 0.19 0.847 -4.788682 5.837497 lpop | .2375072 .0982911 2.42 0.016 .0448601 .4301542 lxrate1 | -.1278113 .0297886 -4.29 0.000 -.1861959 -.0694267 lremote | .3946583 .2519649 1.57 0.117 -.0991838 .8885004 ldist | -1.859803 .5313172 -3.50 0.000 -2.901166 -.8184408 lopen | .0316061 .0625833 0.51 0.614 -.091055 .1542671 english | .5200914 .2558086 2.03 0.042 .0187158 1.021467 white | 12.06072 .9818357 12.28 0.000 10.13635 13.98508 lwhitemg | -1.107911 .0954537 -11.61 0.000 -1.294997 -.9208251 _cons | 23.90025 25.78718 0.93 0.354 -26.6417 74.4422 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003029 lgdp | -.00186 .008815 lgdpau | -.000956 .00064 .628385 lgdpdfrati~w | -.002363 .004066 .000776 .096989 lpopau | -.00013 -.017092 -2.08287 .021827 7.34849 lpop | -.000033 -.005876 -.001774 -.001096 .012278 .009661 lxrate1 | .000043 .000144 .001522 .001497 -.009152 -.000655 .000887 lremote | .002868 .003978 -.021884 -.011639 .041186 -.003638 .000717 ldist | .010071 -.00893 -.019073 -.006611 -.018884 .014256 .001874 lopen | -.000795 .00265 -.002708 -.001281 -.004494 -.000549 .000014 english | -.000397 .000756 .007752 .010843 -.039831 .005349 .00157 white | .01605 -.023152 .012926 -.003035 -.06049 .02504 .005263 lwhitemg | -.001578 .000623 -.002502 -.000722 .011681 -.001214 -.000347 _cons | -.069772 .216471 18.4463 -.389946 -67.2459 -.277636 .089346</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .063486 ldist | .047996 .282298 lopen | .001393 -.001353 .003917 english | -.010062 .015497 .000328 .065438 white | .022537 -.017646 -.006216 .079715 .964001 lwhitemg | .000696 .006067 .000146 -.006166 -.087861 .009111 _cons | -1.15956 -2.38829 .103446 .248002 .585167 -.170706 664.979</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000</p><p>Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2907.56 Log likelihood = -616.3773 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1402468 .0343343 4.08 0.000 .0729528 .2075407 lgdp | .2533077 .0581338 4.36 0.000 .1393676 .3672478 lgdpau | -.1330392 .0772249 -1.72 0.085 -.2843972 .0183189 lgdpdfrati~w | -.1195086 .0501241 -2.38 0.017 -.2177501 -.0212671 lpopau | 2.193367 .3048959 7.19 0.000 1.595782 2.790952 lpop | .7796286 .1015577 7.68 0.000 .5805791 .9786781 lxrate1 | -.0119991 .0102345 -1.17 0.241 -.0320582 .0080601 lremote | .1295857 .0380937 3.40 0.001 .0549235 .2042479 ldist | -3.317351 .3551619 -9.34 0.000 -4.013455 -2.621246 lopen | -.0210881 .0360066 -0.59 0.558 -.0916597 .0494835 english | .6390322 .2696306 2.37 0.018 .1105659 1.167498 white | 23.13174 2.908814 7.95 0.000 17.43057 28.83291 lwhitemg | -2.17589 .272055 -8.00 0.000 -2.709108 -1.642672 _cons | -15.20298 5.429719 -2.80 0.005 -25.84503 -4.560924 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001179 lgdp | -.000808 .00338 lgdpau | -.000789 -.000415 .005964 lgdpdfrati~w | .000433 -.001249 .001187 .002512 lpopau | .005409 -.000749 -.01992 .000486 .092961 lpop | -.000193 -.002344 .001234 .000422 -.005645 .010314 lxrate1 | 4.6e-06 .000126 -.000059 .000054 .00099 -.000283 .000105 lremote | -.000445 .00141 -.000945 -.001348 -.000025 -.000752 .000052 ldist | .00416 .000715 -.004217 -.000455 .023646 -.00357 -.000127 lopen | -.000384 -.000335 .000217 -.000659 -.005578 .001255 -.000252 english | -.001037 -.001203 .001525 .000742 -.006904 .003322 .000026 white | .003563 -.007181 .001089 .002464 -.002349 .028591 -.0007 lwhitemg | -.000622 .000263 .000191 -.000154 -.001836 -.003005 .000058 _cons | -.090778 -.031939 .216296 -.006708 -1.17395 -.006303 -.013126</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .001451 ldist | .000351 .12614 lopen | .000311 -.000976 .001296 english | -.00067 .058062 .000098 .072701 white | -.003056 .014225 .001681 .037631 8.4612 lwhitemg | .000196 -.004623 .000017 -.002671 -.779607 .074014 _cons | -.007366 -1.47747 .086145 -.513545 -.433674 .114647 29.4819</p><p>. . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 518.50 Log likelihood = -571.5843 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5506437 .0496053 11.10 0.000 .4534192 .6478683 lgdp | -.0624212 .0690227 -0.90 0.366 -.1977033 .0728608 lgdpau | 1.951153 .8025235 2.43 0.015 .3782363 3.524071 lgdpdfrati~w | -.7602772 .2899309 -2.62 0.009 -1.328531 -.1920231 lpopau | -9.79757 2.757821 -3.55 0.000 -15.2028 -4.39234 lpop | .420478 .0808545 5.20 0.000 .2620062 .5789499 lxrate1 | -.1182201 .0257038 -4.60 0.000 -.1685988 -.0678415 lremote | .0830013 .2510091 0.33 0.741 -.4089674 .57497 ldist | -1.355502 .3079915 -4.40 0.000 -1.959154 -.7518497 lopen | .0239292 .0543644 0.44 0.660 -.0826231 .1304815 english | -.2347975 .2208761 -1.06 0.288 -.6677067 .1981118 white | 9.558887 1.056939 9.04 0.000 7.487324 11.63045 lwhitemg | -.8449663 .0950509 -8.89 0.000 -1.031263 -.65867 _cons | 121.3033 26.0882 4.65 0.000 70.17139 172.4353 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002461 lgdp | -.001482 .004764 lgdpau | .00047 -.001464 .644044 lgdpdfrati~w | -.001334 .001226 -.017699 .08406 lpopau | -.006211 -.00061 -2.15155 .074661 7.60558 lpop | -.000143 -.002376 .000749 -.000574 -.005831 .006537 lxrate1 | .000166 -.000166 .000564 .000766 -.004684 -.000522 .000661 lremote | .001643 .004714 -.021028 -.01238 .056484 -.003481 .000376 ldist | .004307 .003293 -.00744 -.00236 -.018847 .001843 .001049 lopen | -.000224 .000347 .000319 -.000626 -.010327 .001109 -9.6e-06 english | -.002129 .000489 .00376 .004932 -.016566 .001041 .001121 white | .014086 -.019527 .021452 -.007443 -.095432 .019254 .004951 lwhitemg | -.001388 .001146 -.002996 -7.3e-06 .014395 -.001362 -.000407 _cons | .054691 -.084569 19.0808 -.74409 -69.9774 .041845 .057829</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .063006 ldist | .02854 .094859 lopen | .001459 .002585 .002955 english | -.011148 .023558 -.000534 .048786 white | .015843 -.002916 .000075 .018756 1.11712 lwhitemg | .000725 .000084 .000031 -.000642 -.096838 .009035 _cons | -1.25256 -.776429 .104513 .008801 .899502 -.158107 680.594</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1294.98 Log likelihood = -341.1891 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0341623 .0175423 1.95 0.051 -.0002201 .0685446 lgdp | .226508 .0574338 3.94 0.000 .1139398 .3390761 lgdpau | -.2357906 .3299163 -0.71 0.475 -.8824147 .4108335 lgdpdfrati~w | -.417591 .20598 -2.03 0.043 -.8213045 -.0138776 lpopau | 2.682141 1.173807 2.28 0.022 .3815208 4.982761 lpop | .098146 .0725962 1.35 0.176 -.0441401 .240432 lxrate1 | -.0788137 .0189773 -4.15 0.000 -.1160085 -.0416188 lremote | -.1465019 .1173703 -1.25 0.212 -.3765435 .0835397 ldist | -1.320355 .2267935 -5.82 0.000 -1.764862 -.8758479 lopen | .0063611 .0269268 0.24 0.813 -.0464144 .0591366 english | 2.037492 .2286799 8.91 0.000 1.589288 2.485696 white | 9.337921 1.792701 5.21 0.000 5.824292 12.85155 lwhitemg | -.6995349 .1846708 -3.79 0.000 -1.061483 -.3375867 _cons | -29.54573 11.86655 -2.49 0.013 -52.80374 -6.28771 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000308 lgdp | -.000333 .003299 lgdpau | .000244 -.001511 .108845 lgdpdfrati~w | -.000494 -.000416 -.001518 .042428 lpopau | -.001201 .007105 -.372732 .024231 1.37782 lpop | .000134 -.003244 .000902 .000932 -.007455 .00527 lxrate1 | -.000016 .00019 .001294 .000788 -.006202 -.000204 .00036 lremote | .000205 .001186 -.007633 -.003702 .027056 -.000669 -.000407 ldist | .00084 .000587 -.001885 -.001193 -.002579 .002789 -.000307 lopen | .000029 -.000286 -.000129 .001145 -.001111 .000378 -9.7e-06 english | -.000242 -.002485 .003594 .003812 -.010273 .004509 .000297 white | .001834 -.024 .013568 .00335 -.072713 .026854 .000831 lwhitemg | -.000183 .001363 -.001141 -.000036 .005208 -.001783 -.000062 _cons | .008083 -.114221 3.42648 -.370633 -13.3321 .068399 .072364</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .013776 ldist | .001503 .051435 lopen | -.000091 -.000094 .000725 english | -.003944 .015918 .00003 .052295 white | .011003 -.02896 .001739 .080985 3.21378 lwhitemg | -.000485 .001747 -.000103 -.007942 -.326366 .034103 _cons | -.393838 -.470183 .023235 -.065109 1.11584 -.069723 140.815</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 862.57 Log likelihood = -853.4692 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1479942 .066684 2.22 0.026 .017296 .2786924 lgdp | .4785117 .1135271 4.21 0.000 .2560027 .7010206 lgdpau | -2.557765 1.145473 -2.23 0.026 -4.80285 -.3126794 lgdpdfrati~w | -1.172274 .4552319 -2.58 0.010 -2.064512 -.2800355 lpopau | 5.504458 3.932279 1.40 0.162 -2.202667 13.21158 lpop | .3207497 .1307636 2.45 0.014 .0644578 .5770416 lxrate1 | -.1519091 .0403824 -3.76 0.000 -.2310571 -.072761 lremote | 1.85293 .2752625 6.73 0.000 1.313425 2.392434 ldist | -1.021746 .5609298 -1.82 0.069 -2.121148 .0776565 lopen | -.0568908 .0769925 -0.74 0.460 -.2077933 .0940116 english | .3373416 .2724529 1.24 0.216 -.1966563 .8713395 white | 11.3185 1.494644 7.57 0.000 8.389048 14.24794 lwhitemg | -.8540065 .1442011 -5.92 0.000 -1.136635 -.5713775 _cons | -42.62506 37.00964 -1.15 0.249 -115.1626 29.91249 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004447 lgdp | -.004662 .012888 lgdpau | -.001809 .005271 1.31211 lgdpdfrati~w | -.001717 .004214 -.005786 .207236 lpopau | .002367 -.028279 -4.39169 .074297 15.4628 lpop | .001526 -.010748 -.001532 -.002196 .009333 .017099 lxrate1 | .000074 .001706 .001 .001632 -.010933 -.001584 .001631 lremote | .001665 -.002191 -.028547 -.018328 .069615 .001592 .000929 ldist | .013795 -.012344 -.010598 -.009545 -.011805 .020561 -.002037 lopen | .000284 -.000688 .008754 .001401 -.040184 .002024 -.000364 english | -.005555 .01106 .007086 .002247 -.029903 -.008003 -.000494 white | .028913 -.05246 -.030454 -.031689 .028334 .051404 .005479 lwhitemg | -.00327 .003225 -.000614 .000687 .013391 -.002718 -.000874 _cons | -.078103 .359411 38.7056 -1.09825 -141.468 -.349695 .145786</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .075769 ldist | .023571 .314642 lopen | .002954 .002849 .005928 english | -.006091 .030653 -.001047 .074231 white | .116598 .159039 .001 .048807 2.23396 lwhitemg | -.004706 -.02077 .000068 -.007393 -.205611 .020794 _cons | -1.2664 -2.83435 .371164 -.039485 -2.01141 .024999 1369.71</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 614.86 Log likelihood = -42.69433 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0365132 .0269416 1.36 0.175 -.0162913 .0893177 lgdp | .1152563 .052178 2.21 0.027 .0129892 .2175233 lgdpau | .3509277 .3410792 1.03 0.304 -.3175753 1.019431 lgdpdfrati~w | .2941357 .1558234 1.89 0.059 -.0112725 .599544 lpopau | 2.473032 1.217139 2.03 0.042 .0874835 4.858581 lpop | .3628207 .0665913 5.45 0.000 .2323041 .4933373 lxrate1 | -.0160641 .0140239 -1.15 0.252 -.0435504 .0114222 lremote | -.0211016 .1098 -0.19 0.848 -.2363058 .1941025 ldist | -1.843604 .3970552 -4.64 0.000 -2.621818 -1.065391 lopen | -.001002 .028692 -0.03 0.972 -.0572373 .0552333 english | .9302966 .1641363 5.67 0.000 .6085953 1.251998 white | 14.95784 1.112051 13.45 0.000 12.77826 17.13742 lwhitemg | -1.233811 .1029094 -11.99 0.000 -1.43551 -1.032112 _cons | -40.79778 12.87815 -3.17 0.002 -66.03849 -15.55708 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000726 lgdp | -.000511 .002723 lgdpau | -.00052 .000029 .116335 lgdpdfrati~w | -.0006 .00052 .000478 .024281 lpopau | .001881 -.000351 -.393292 .011795 1.48143 lpop | -.000064 -.001738 .000317 .000184 -.00082 .004434 lxrate1 | .000062 .000026 .000277 .000414 -.002173 -.000091 .000197 lremote | .000647 .001515 -.006377 -.002898 .019173 -.000995 3.4e-06 ldist | .003133 -.002548 -.010087 -.008561 .010393 .004453 -.000015 lopen | -.000086 .000056 .00062 .000103 -.004098 .000212 -.000037 english | -.000676 -.00044 .002726 .001982 -.006124 .003309 .000147 white | .003315 -.013241 .028271 -.004627 -.227041 .017931 .002667 lwhitemg | -.000424 .000739 -.002872 .000432 .022438 -.001418 -.000288 _cons | -.044151 -.015022 3.61934 -.139542 -14.516 -.059167 .028417</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .012056 ldist | .013828 .157653 lopen | .000074 -.000417 .000823 english | -.003403 .000725 -.000122 .026941 white | -.005239 -.0207 -.000861 .037836 1.23666 lwhitemg | .000595 .001895 .000138 -.003486 -.11184 .01059 _cons | -.405346 -1.55933 .051275 .005966 3.24975 -.311007 165.847</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 194.79 Log likelihood = 140.9592 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .002055 .0175499 0.12 0.907 -.0323422 .0364522 lgdp | .207372 .045768 4.53 0.000 .1176682 .2970757 lgdpau | -.3316978 .3521151 -0.94 0.346 -1.021831 .358435 lgdpdfrati~w | -.1804499 .144403 -1.25 0.211 -.4634746 .1025748 lpopau | 3.908241 1.28204 3.05 0.002 1.395488 6.420994 lpop | -.0603147 .0556283 -1.08 0.278 -.1693442 .0487147 lxrate1 | -.0828674 .0148211 -5.59 0.000 -.1119163 -.0538184 lremote | .3497872 .1296483 2.70 0.007 .0956813 .6038932 ldist | -1.112946 .2822746 -3.94 0.000 -1.666194 -.5596976 lopen | -.0044375 .0290108 -0.15 0.878 -.0612976 .0524226 english | .0850584 .1478965 0.58 0.565 -.2048134 .3749301 white | 9.364784 2.552984 3.67 0.000 4.361027 14.36854 lwhitemg | -.7343207 .253771 -2.89 0.004 -1.231703 -.2369386 _cons | -51.46792 13.68056 -3.76 0.000 -78.28132 -24.65452 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000308 lgdp | -.000312 .002095 lgdpau | .000139 -.000795 .123985 lgdpdfrati~w | -.000418 .000361 -.004791 .020852 lpopau | -.001762 .006971 -.426314 .020177 1.64363 lpop | .000046 -.001815 -.000066 -.000196 -.002359 .003095 lxrate1 | -.00001 -.000023 .000474 .000497 -.00449 -.000057 .00022 lremote | .000234 .001474 -.009144 -.001379 .035123 -.000716 -.000078 ldist | .00152 -.001672 -.003265 -.002271 .005875 .004544 .00009 lopen | .000014 -.000046 .000381 .000314 -.002633 .000116 -.000022 english | -.000587 -.001384 -.00007 .000243 .01226 .003977 .000306 white | .002069 -.014834 .024225 -.002267 -.206158 .016043 .002539 lwhitemg | -.000241 .001033 -.002825 .000319 .020518 -.001295 -.000193 _cons | .014443 -.108241 3.95158 -.202363 -16.5639 -.00464 .061866 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .016809 ldist | .007842 .079679 lopen | -.000052 -.000299 .000842 english | -.000546 .009841 -.000582 .021873 white | -.003216 .014665 -.00113 .028819 6.51773 lwhitemg | .001037 -.002324 .000136 -.002423 -.639876 .0644 _cons | -.585041 -.883021 .036432 -.326069 2.72675 -.253973 187.158</p><p>. xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 431.98 Log likelihood = -691.0528 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1913406 .0549612 3.48 0.000 .0836187 .2990626 lgdp | .8233892 .1086583 7.58 0.000 .610423 1.036355 lgdpau | -.7092657 .6996954 -1.01 0.311 -2.080643 .662112 lgdpdfrati~w | -.3237112 .2959639 -1.09 0.274 -.9037898 .2563674 lpopau | 3.339293 2.41337 1.38 0.166 -1.390825 8.069411 lpop | -.2964811 .1520925 -1.95 0.051 -.5945769 .0016147 lxrate1 | -.145279 .0315891 -4.60 0.000 -.2071926 -.0833654 lremote | .2586802 .2379501 1.09 0.277 -.2076933 .7250538 ldist | -2.430754 .6583423 -3.69 0.000 -3.721081 -1.140427 lopen | .0353004 .077052 0.46 0.647 -.1157187 .1863195 english | -.2029521 .4282801 -0.47 0.636 -1.042366 .6364614 white | 19.7012 4.251035 4.63 0.000 11.36932 28.03307 lwhitemg | -1.820594 .3893784 -4.68 0.000 -2.583761 -1.057426 _cons | -27.0673 23.65843 -1.14 0.253 -73.43697 19.30237 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003021 lgdp | -.002817 .011807 lgdpau | .000987 -.000647 .489574 lgdpdfrati~w | -.001978 .00407 -.008872 .087595 lpopau | -.006313 -.005089 -1.63103 .057579 5.82435 lpop | 3.2e-06 -.008896 -.001387 -.001811 -.004936 .023132 lxrate1 | .000172 .000515 .002159 .001374 -.011225 -.000782 .000998 lremote | .000817 .003577 -.021325 -.01289 .04228 -.002843 .000498 ldist | .011301 .003542 -.004812 -.003321 -.039299 .010351 .000559 lopen | .000317 -.000833 -.000253 .001044 -.016811 .002313 -.000127 english | -.006608 .001702 .003307 .006709 -.017077 .01816 .000424 white | .008922 -.043989 .136738 .032156 -.33393 .082674 .005153 lwhitemg | -.001382 .002247 -.014379 -.004269 .039871 -.006246 -.000616 _cons | .014959 -.079687 14.4774 -.726388 -53.6525 -.120114 .114609</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .05662 ldist | .02385 .433415 lopen | .000852 .002439 .005937 english | -.007532 .102558 -.001475 .183424 white | .018314 .229133 .007698 .274134 18.0713 lwhitemg | .001257 -.034206 -.000539 -.030258 -1.62639 .151616 _cons | -.893584 -3.8758 .239628 -1.05111 -.893813 .099357 559.721</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1522.60 Log likelihood = -595.3658 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2118056 .0472209 4.49 0.000 .1192545 .3043568 lgdp | .4334084 .0833099 5.20 0.000 .2701239 .5966928 lgdpau | .581719 .6679271 0.87 0.384 -.7273941 1.890832 lgdpdfrati~w | -.0829084 .2844702 -0.29 0.771 -.6404597 .4746429 lpopau | -2.767788 2.304217 -1.20 0.230 -7.28397 1.748394 lpop | .724758 .1009963 7.18 0.000 .5268088 .9227071 lxrate1 | -.0872913 .028634 -3.05 0.002 -.1434128 -.0311698 lremote | -.1910399 .2342325 -0.82 0.415 -.6501272 .2680474 ldist | -2.100939 .4166308 -5.04 0.000 -2.91752 -1.284357 lopen | -.1484158 .0735086 -2.02 0.043 -.29249 -.0043415 english | .8986697 .3142428 2.86 0.004 .2827652 1.514574 white | 22.39045 3.398967 6.59 0.000 15.72859 29.0523 lwhitemg | -2.13102 .2984844 -7.14 0.000 -2.716039 -1.546002 _cons | 34.07892 21.91525 1.56 0.120 -8.87418 77.03201 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00223 lgdp | -.001942 .006941 lgdpau | -.001989 .002886 .446127 lgdpdfrati~w | -.001798 .00146 -.015867 .080923 lpopau | .005742 -.021603 -1.49173 .058512 5.30941 lpop | .000277 -.003954 -.000754 -.000329 .000448 .0102 lxrate1 | .000043 .000481 .000676 .001289 -.006405 -.000586 .00082 lremote | .000571 .004002 -.015062 -.017707 .032292 -.002971 .000397 ldist | .007694 .003139 -.005166 -.000345 -.018779 .003645 .000556 lopen | .000277 -.001113 -.000621 .002141 -.007846 .0029 -.000091 english | -.003115 -.003431 .00215 .003188 -.003124 .007885 .000388 white | .006995 -.021166 .052409 -.000357 -.136769 .037629 .004516 lwhitemg | -.000967 .000897 -.005612 -.001047 .018194 -.003441 -.000416 _cons | -.091278 .13016 13.1918 -.498617 -48.6503 -.066006 .074064</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054865 ldist | .007632 .173581 lopen | .001329 .003191 .005404 english | -.009051 .05846 -.00327 .098749 white | .021846 .000243 .010673 .037611 11.553 lwhitemg | .000732 -.005287 -.000796 -.000658 -.999949 .089093 _cons | -.721179 -1.44738 .083748 -.54502 .512748 -.068823 480.278</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1740.90 Log likelihood = -765.6579 Prob > chi2 = 0.0000</p><p>------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0686035 .035967 1.91 0.056 -.0018904 .1390975 lgdp | 1.075977 .1033084 10.42 0.000 .8734966 1.278458 lgdpau | .3858196 .7561438 0.51 0.610 -1.096195 1.867834 lgdpdfrati~w | -.1428155 .3064407 -0.47 0.641 -.7434283 .4577974 lpopau | 4.695421 2.620582 1.79 0.073 -.440825 9.831667 lpop | -.5319849 .1470803 -3.62 0.000 -.820257 -.2437128 lxrate1 | -.1390734 .0271226 -5.13 0.000 -.1922326 -.0859141 lremote | -.2127817 .1997174 -1.07 0.287 -.6042207 .1786573 ldist | -1.059271 .7687087 -1.38 0.168 -2.565912 .4473703 lopen | -.023556 .076032 -0.31 0.757 -.172576 .125464 english | .0246626 .3364269 0.07 0.942 -.634722 .6840471 white | 26.8348 2.79959 9.59 0.000 21.3477 32.32189 lwhitemg | -2.495829 .2709482 -9.21 0.000 -3.026878 -1.96478 _cons | -89.273 26.19387 -3.41 0.001 -140.612 -37.93396 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001294 lgdp | -.002175 .010673 lgdpau | -.000014 -.000731 .571754 lgdpdfrati~w | -.002312 .003318 -.010589 .093906 lpopau | -.007508 -.002132 -1.90896 .056744 6.86745 lpop | .001921 -.012793 -.002505 -.002138 .022568 .021633 lxrate1 | -.000018 .000635 .001428 .0012 -.011699 -.001076 .000736 lremote | .001446 .005202 -.02013 -.006316 .0204 -.004138 .000417 ldist | .006221 .017382 -.033278 -.007092 -.018509 .007465 .00163 lopen | .000279 -.000498 -.00248 .004905 -.002506 .000817 -.000224 english | -.001285 .003731 .004255 .004147 -.014242 -.001284 .001407 white | .018566 -.062297 .068087 -.023228 -.486092 .069712 .007736 lwhitemg | -.001661 .004374 -.007515 .001872 .051923 -.005082 -.000754 _cons | .067695 -.19136 17.2193 -.668586 -64.1494 -.397727 .135553</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .039887 ldist | .077179 .590913 lopen | .002051 .00326 .005781 english | .001285 .063739 -.001207 .113183 white | .025167 .020206 -.005923 .191803 7.8377 lwhitemg | -.001663 -.009645 .000809 -.021496 -.747487 .073413 _cons | -.95015 -5.69359 .054926 -.572873 6.05837 -.565941 686.119</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 581.48 Log likelihood = -603.3401 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4222855 .0581391 7.26 0.000 .308335 .536236 lgdp | .1433391 .0905419 1.58 0.113 -.0341198 .3207981 lgdpau | 1.054676 .8043717 1.31 0.190 -.5218637 2.631215 lgdpdfrati~w | -.5605185 .3355624 -1.67 0.095 -1.218209 .0971717 lpopau | -4.594573 2.767635 -1.66 0.097 -10.01904 .8298913 lpop | .4320484 .096287 4.49 0.000 .2433294 .6207674 lxrate1 | -.0826161 .0341734 -2.42 0.016 -.1495948 -.0156375 lremote | .0951663 .2294555 0.41 0.678 -.3545582 .5448907 ldist | -1.249281 .5597692 -2.23 0.026 -2.346408 -.1521532 lopen | .0390512 .0745575 0.52 0.600 -.1070788 .1851812 english | -.2478168 .2756301 -0.90 0.369 -.7880418 .2924082 white | 20.39 2.025967 10.06 0.000 16.41918 24.36082 lwhitemg | -1.880687 .1976264 -9.52 0.000 -2.268028 -1.493347 _cons | 52.27307 26.01926 2.01 0.045 1.276257 103.2699 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00338 lgdp | -.002922 .008198 lgdpau | -.001541 .003577 .647014 lgdpdfrati~w | -.001795 .003024 -.001299 .112602 lpopau | .001571 -.023328 -2.15787 .029583 7.6598 lpop | .00077 -.004688 -.001743 -.001982 .00055 .009271 lxrate1 | .000321 .000363 -.000143 .00097 -.004268 -.000511 .001168 lremote | -.000466 .005165 -.010401 -.016195 -.001265 -.000902 .001447 ldist | .007762 .011966 .004491 -.004954 -.094573 -.003911 .000874 lopen | -.000188 .000225 .001518 -.000944 -.022543 .002414 -.00019 english | -.004324 .007948 .004718 .001347 -.019994 -.000602 -.001359 white | .019695 -.029082 .00888 -.052481 .03155 .008785 -.000629 lwhitemg | -.002319 .001561 -.002688 .002945 .007641 -.000119 -.00025 _cons | -.021222 .035101 18.8282 -.410601 -69.1054 .040087 .048432</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .05265 ldist | .031718 .313342 lopen | .003195 .00604 .005559 english | .009368 .094673 -.00063 .075972 white | .106849 .156134 -.005861 .123434 4.10454 lwhitemg | -.007455 -.026919 .000651 -.014804 -.391984 .039056 _cons | -.561119 -2.06766 .212621 -.932219 -2.78763 .248935 677.002</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1438.56 Log likelihood = -267.813 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0011183 .0231062 -0.05 0.961 -.0464057 .044169 lgdp | .4457468 .0828292 5.38 0.000 .2834046 .608089 lgdpau | -.342732 .5198446 -0.66 0.510 -1.361609 .6761446 lgdpdfrati~w | .0911286 .2333234 0.39 0.696 -.3661768 .5484341 lpopau | 1.359956 1.793152 0.76 0.448 -2.154557 4.874469 lpop | -.2210392 .1168356 -1.89 0.059 -.4500328 .0079543 lxrate1 | -.0425862 .0237795 -1.79 0.073 -.0891932 .0040208 lremote | -.0052482 .1751979 -0.03 0.976 -.3486297 .3381333 ldist | -3.44841 .520911 -6.62 0.000 -4.469377 -2.427443 lopen | .0013466 .0529162 0.03 0.980 -.1023672 .1050604 english | -.1840383 .3165908 -0.58 0.561 -.804545 .4364683 white | 14.94325 2.76683 5.40 0.000 9.520358 20.36613 lwhitemg | -1.043887 .2975052 -3.51 0.000 -1.626986 -.4607871 _cons | 14.13057 17.84937 0.79 0.429 -20.85355 49.1147 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000534 lgdp | -.000686 .006861 lgdpau | -9.0e-07 -.001507 .270238 lgdpdfrati~w | -.00091 .002001 -.007918 .05444 lpopau | -.000954 -.000707 -.902314 .044433 3.21539 lpop | .000221 -.006389 -.000074 -.00087 -.00251 .013651 lxrate1 | -.000026 .000146 .001355 .001216 -.006751 -.000502 .000565 lremote | .000139 .002285 -.017775 -.00483 .051035 -.002457 -.000149 ldist | .002432 .001838 -.008903 -.002735 -.017109 .019906 -.000033 lopen | .000062 -.0002 -.001619 .001115 .000071 .000856 -.000048 english | -.000967 -.001994 .0043 .00187 -.006137 .008057 .000881 white | .004562 -.0408 .060989 -.005178 -.361924 .065506 .003376 lwhitemg | -.000483 .001918 -.00745 -.000111 .043561 -.005245 -.000143 _cons | .001873 -.036237 8.15494 -.549254 -29.9256 -.195276 .078936</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .030694 ldist | .013872 .271348 lopen | .000159 .000209 .0028 english | -.001535 .066747 -.000658 .10023 white | -.006 .16421 -.00248 .124596 7.65535 lwhitemg | .003363 -.020219 .000344 -.011882 -.812775 .088509 _cons | -.789677 -2.57725 .029263 -.73314 2.72464 -.321238 318.6</p><p>. closed on: 26 Jul 2006, 07:50:30 ------</p>