<p>Greece to Madagascar ------log: K:\Greeceto Madagascar.log opened on: 25 Jul 2006, 19:25:36</p><p>. . *Dropping Greece . drop if ccode==162880 (10 observations deleted)</p><p>. . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist open english gdpdfration > ew white whitemg, stat(n mean sd median min max) col(stat) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 490692.9 1561333 7348 0 1.39e+07 immig | 1000 32163.15 116680 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 105.6172 16.91667 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 1.02e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1041.43 10901.85 13.89535 .0068 270182.6 remote | 1000 6767.609 4135.31 6797 1293 39620 dist | 1000 13352.02 3528.07 14215 2409 17972 open | 1000 .7107736 .3890883 .63975 .0671 3.2192 english | 1000 .37 .4830459 0 0 1 gdpdfratio~w | 1000 1.051665 .181073 1.015772 .5844526 2.009028 white | 1000 .12 .3251241 0 0 1 whitemg | 1000 19202.69 115962.6 0 0 1137050 ------</p><p>. . sort white</p><p>. *IIIB. Descriptives Original Unites(sub sample for "white" and "non-white" countries)--RHS Variables > : . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist phone open eng > lish 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 | 880 400345.4 1589043 3126 0 1.39e+07 immig | 880 14727.79 27016.52 1505 0 158613 gdp | 880 2.35e+11 9.96e+11 1.05e+10 1.92e+08 8.99e+12 gdpau | 880 3.83e+11 4.44e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 880 104.8121 17.21914 101.7094 60.87417 207.3465 gdpdfau | 880 100.7173 4.633806 100.8223 94.42464 109.9797 pop | 880 5.29e+07 1.64e+08 1.05e+07 41000 1.26e+09 popau | 880 1.82e+07 612835.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 880 1169.546 11615.77 21.6609 .0068 270182.6 remote | 880 7159.151 4093.339 6938.5 1293 39620 dist | 880 13201.9 3402.569 14045.5 2410 17972 phone | 880 157.5574 241.028 49.13 .54 1449.75 open | 880 .7155966 .4091255 .63385 .0671 3.2192 english | 880 .3863636 .4871925 0 0 1 gdpdfratio~w | 880 1.043893 .185446 1 .5844526 2.009028 white | 880 0 0 0 0 0 whitemg | 880 0 0 0 0 0 ------</p><p>------> white = 1</p><p> variable | N mean sd p50 min max ------+------rimp | 120 1153241 1144725 557964.5 77099 3843839 immig | 120 160022.4 300276.5 17525 2612 1137050 gdp | 120 5.92e+11 6.72e+11 2.91e+11 5.15e+10 2.69e+12 gdpau | 120 3.83e+11 4.46e+10 3.80e+11 3.19e+11 4.52e+11 gdpdefnew | 120 111.521 13.129 112.2247 85.45601 143.9587 gdpdfau | 120 100.7173 4.65059 100.8223 94.42464 109.9797 pop | 120 2.45e+07 2.62e+07 8363820 3477200 8.22e+07 popau | 120 1.82e+07 615055.4 1.82e+07 1.73e+07 1.92e+07 xrate1 | 120 101.9149 305.1406 4.01625 .3774 1261.556 remote | 120 3896.3 3216.858 2809.5 1530 12501 dist | 120 14452.92 4193.792 15956 2409 17493 phone | 120 744.3583 272.0964 656.67 343.99 1487.08 open | 120 .675405 .181901 .65115 .3517 1.2967 english | 120 .25 .4348283 0 0 1 gdpdfratio~w | 120 1.108656 .1322944 1.117028 .8254872 1.441221 white | 120 1 0 1 1 1 whitemg | 120 160022.4 300276.5 17525 2612 1137050 ------</p><p>. . . **Regression of Imports . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000 . . **I. Aggregate Imports . xtgls lrimp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 9387.11 Log likelihood = -550.5287 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3311778 .0303683 10.91 0.000 .271657 .3906985 lgdp | 1.192529 .0310885 38.36 0.000 1.131597 1.253461 lgdpau | .2933321 .6030863 0.49 0.627 -.8886954 1.47536 lgdpdfrati~w | -.8289077 .2442678 -3.39 0.001 -1.307664 -.3501515 lpopau | -3.100607 2.079688 -1.49 0.136 -7.176721 .9755068 lpop | .0243778 .0412202 0.59 0.554 -.0564123 .1051679 lxrate1 | -.1253936 .0163015 -7.69 0.000 -.1573439 -.0934433 lremote | -.4322973 .0765841 -5.64 0.000 -.5823993 -.2821952 ldist | -2.066736 .1486536 -13.90 0.000 -2.358091 -1.77538 lopen | .272361 .0534975 5.09 0.000 .1675079 .377214 english | .9299396 .1036742 8.97 0.000 .7267419 1.133137 white | 4.584061 .4753754 9.64 0.000 3.652342 5.515779 lwhitemg | -.4252197 .0419208 -10.14 0.000 -.507383 -.3430565 _cons | 45.51357 19.11859 2.38 0.017 8.041814 82.98532 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000922 lgdp | -.000279 .000966 lgdpau | -.000836 .001298 .363713 lgdpdfrati~w | -.000824 .000244 -.009367 .059667 lpopau | .001864 -.007884 -1.23067 .050239 4.3251 lpop | -.00016 -.000655 .000078 .000119 -.000025 .001699 lxrate1 | .000097 .000142 .000374 .00019 -.002497 -.000129 .000266 lremote | .000404 .000205 -.000462 -.001745 -.003222 -.000238 .000052 .005865 ldist | .00164 .000705 .000981 -.000914 -.015353 .00024 .001339 .00522 .022098 lopen | -.000215 .000713 .002143 .000802 -.015132 .000291 .000181 .001307 .001633 english | -.000984 .001968 .002789 .00242 -.011173 -.000767 .000494 -.002372 .000968 white | .003598 .002181 .002889 -.011448 -.019352 .002108 .000689 -.003576 .011848 lwhitemg | -.000473 -.000191 -.000258 .001039 .002094 -.00013 -.000084 .000479 -.001547 _cons | -.025403 .076413 10.8515 -.629275 -39.1771 -.011867 .015474 -.034828 -.059247</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002862 english | -.000047 .010748 white | -.004448 .027699 .225982 lwhitemg | .000329 -.002324 -.019433 .001757 _cons | .148555 .086655 .031976 -.005756 365.521</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 76427.30 Log likelihood = -973.6812 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0531504 .0142643 3.73 0.000 .0251928 .081108 lgdp | 1.608108 .0522596 30.77 0.000 1.505682 1.710535 lgdpau | .8847219 .3639811 2.43 0.015 .1713321 1.598112 lgdpdfrati~w | -.4388931 .1507952 -2.91 0.004 -.7344464 -.1433399 lpopau | -6.242305 1.229219 -5.08 0.000 -8.651531 -3.833079 lpop | -.3555423 .0872896 -4.07 0.000 -.5266266 -.1844579 lxrate1 | -.1348412 .020804 -6.48 0.000 -.1756163 -.0940661 lremote | -.9874904 .1002633 -9.85 0.000 -1.184003 -.790978 ldist | -3.342909 .1779107 -18.79 0.000 -3.691608 -2.994211 lopen | -.0484027 .0271674 -1.78 0.075 -.1016499 .0048445 english | .9391452 .0888362 10.57 0.000 .7650295 1.113261 white | 5.052451 .8081619 6.25 0.000 3.468483 6.636419 lwhitemg | -.5102482 .0777342 -6.56 0.000 -.6626045 -.3578919 _cons | 94.7344 11.56409 8.19 0.000 72.06921 117.3996 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000203 lgdp | -.000272 .002731 lgdpau | -.001267 .001856 .132482 lgdpdfrati~w | -.000594 .000514 -.012169 .022739 lpopau | .004958 -.007392 -.437992 .024609 1.51098 lpop | .000172 -.004322 -.001552 .000563 .004115 .007619 lxrate1 | -.000025 .000286 -.000058 .000418 -.003247 -.000306 .000433 lremote | .000381 .000369 -.006802 -.003509 .024322 -.001358 .000069 .010053 ldist | .000691 -.002225 -.006726 -.000879 .015766 .003714 .000621 .003122 .031652 lopen | .000044 -.000112 -.000994 .00095 .003638 .000287 -.000076 .000643 .000282 english | -.000417 .000116 .003159 .002745 -.020799 .000515 .001169 -.002937 .003027 white | .001169 -.014593 -.00941 -.002126 .03824 .023257 -.001457 .002521 -.013491 lwhitemg | -.000103 .000824 .000288 1.3e-06 -.002265 -.00126 .000186 .000576 .002456 _cons | -.055782 .097952 3.91409 -.089985 -13.8749 -.073155 .045379 -.328962 -.432436</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000738 english | -.000409 .007892 white | .001974 -.001719 .653126 lwhitemg | -.000146 .00041 -.061147 .006043 _cons | -.045256 .242405 -.309808 .001871 133.728</p><p>. . . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 7655.82 Log likelihood = -924.395 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1079281 .0249019 4.33 0.000 .0591213 .1567348 lgdp | 1.749329 .0740335 23.63 0.000 1.604226 1.894431 lgdpau | .3028557 .6278881 0.48 0.630 -.9277823 1.533494 lgdpdfrati~w | -.3821795 .2382988 -1.60 0.109 -.8492366 .0848775 lpopau | -2.937579 2.177879 -1.35 0.177 -7.206144 1.330986 lpop | -.6662399 .0824327 -8.08 0.000 -.8278049 -.5046748 lxrate1 | -.139217 .0289979 -4.80 0.000 -.1960519 -.0823822 lremote | -.3373833 .1390419 -2.43 0.015 -.6099005 -.0648661 ldist | -3.86761 .3462551 -11.17 0.000 -4.546258 -3.188963 lopen | .0906147 .0452372 2.00 0.045 .0019515 .179278 english | 1.068944 .1455461 7.34 0.000 .7836784 1.354209 white | 8.585664 1.864799 4.60 0.000 4.930726 12.2406 lwhitemg | -.7025082 .1873985 -3.75 0.000 -1.069803 -.3352138 _cons | 55.6305 20.46604 2.72 0.007 15.51781 95.7432 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .00062 lgdp | -.001001 .005481 lgdpau | -.0023 .006833 .394243 lgdpdfrati~w | -.000913 .002057 -.025578 .056786 lpopau | .005881 -.028187 -1.33281 .086834 4.74316 lpop | .000713 -.004531 -.004608 -.001065 .015832 .006795 lxrate1 | .000017 .000592 .000907 .000875 -.007887 -.000832 .000841 lremote | -.0001 -.000862 -.008588 -.002214 .026187 -.001539 .000237 .019333 ldist | .002668 .007735 -.008302 -.002906 -.025162 -.002135 .001692 .008441 .119893 lopen | .000097 -.000535 -.00033 .001516 .001317 .001017 -.000148 .000557 -.000574 english | -.001143 .003413 .008864 .003463 -.042889 .001322 .002159 -.006081 .003704 white | .001578 -.030939 .001617 .000141 .008618 .025435 .004068 .01274 -.13915 lwhitemg | -.000142 .001521 -.0022 -.000526 .008102 -.001659 -.000433 .001326 .010551 _cons | -.052197 .172252 11.8757 -.807718 -43.44 -.113232 .084114 -.416064 -.737323</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002046 english | -.00135 .021184 white | .00309 .017261 3.47747 lwhitemg | -.000207 -.002596 -.34173 .035118 _cons | -.016765 .388236 1.28286 -.193797 418.859</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 2679.06 Log likelihood = -1124.78 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1249766 .0392264 3.19 0.001 .0480942 .2018589 lgdp | .8916273 .079025 11.28 0.000 .7367411 1.046513 lgdpau | -.9566093 .9623979 -0.99 0.320 -2.842875 .9296559 lgdpdfrati~w | .0019852 .3634762 0.01 0.996 -.710415 .7143854 lpopau | .8380423 3.288755 0.25 0.799 -5.607798 7.283883 lpop | .0295868 .0967726 0.31 0.760 -.160084 .2192576</p><p> lxrate1 | -.0874001 .0321259 -2.72 0.007 -.1503658 -.0244344 lremote | .4864375 .2487786 1.96 0.051 -.0011595 .9740345 ldist | -1.236612 .3082765 -4.01 0.000 -1.840822 -.6324008 lopen | .3206537 .0801332 4.00 0.000 .1635954 .477712 english | 1.9163 .2529399 7.58 0.000 1.420547 2.412053 white | .5319754 1.942959 0.27 0.784 -3.276153 4.340104 lwhitemg | .3158837 .1650818 1.91 0.056 -.0076706 .639438 _cons | .368453 30.88617 0.01 0.990 -60.16733 60.90423 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001539 lgdp | -.001394 .006245 lgdpau | -.000107 -.00053 .92621 lgdpdfrati~w | .000654 .002148 -.034538 .132115 lpopau | -.00445 -.00136 -3.10302 .093912 10.8159 lpop | .000197 -.005447 -.00051 -.002541 .001867 .009365 lxrate1 | .000171 .000755 .000818 .002707 -.009664 -.001131 .001032 lremote | .001923 .000064 -.033534 -.007819 .105267 .001205 -.000739 .061891 ldist | .003934 -.005546 -.019634 -.001438 .044808 .007719 .000253 .031857 .095034 lopen | .000162 -.000789 .000539 .001596 -.007041 .002876 -.000195 .002804 -.0013 english | -.003774 .000871 .008277 .002457 -.008892 -.000903 .000982 -.018809 .005135 white | .000709 -.028333 .000449 -.027213 .05229 .029169 -.00374 .037418 .003785 lwhitemg | -.000121 .001234 -.002031 .001373 .002334 -.001087 .000284 .000195 .004336 _cons | .043231 .038062 27.7107 -.720536 -99.4642 -.120945 .13675 -1.72957 -1.43718</p><p>| lopen english white lwhitemg _cons ------+------lopen | .006421 english | -.002158 .063979 white | .009467 .076863 3.77509 lwhitemg | -.000684 -.007157 -.311615 .027252 _cons | .065255 .038428 -1.05089 -.040607 953.956</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 57297.43 Log likelihood = -906.4859 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0252725 .0135577 1.86 0.062 -.0013001 .051845 lgdp | 1.546273 .054659 28.29 0.000 1.439143 1.653402 lgdpau | .7143331 .3550913 2.01 0.044 .018367 1.410299 lgdpdfrati~w | -.2603092 .137138 -1.90 0.058 -.5290948 .0084764 lpopau | -6.72283 1.201528 -5.60 0.000 -9.077781 -4.367879 lpop | -.1467022 .0941378 -1.56 0.119 -.3312089 .0378044 lxrate1 | -.0549155 .0190623 -2.88 0.004 -.092277 -.017554 lremote | -.6637535 .1521184 -4.36 0.000 -.9619001 -.3656069 ldist | -2.483571 .1721855 -14.42 0.000 -2.821049 -2.146094 lopen | -.0444073 .0270439 -1.64 0.101 -.0974123 .0085977 english | 1.111233 .1185173 9.38 0.000 .8789431 1.343522 white | 3.925557 .982064 4.00 0.000 2.000747 5.850367 lwhitemg | -.3118668 .095842 -3.25 0.001 -.4997137 -.1240199 _cons | 93.83116 11.37884 8.25 0.000 71.52903 116.1333 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000184 lgdp | -.0002 .002988 lgdpau | -.000871 .002024 .12609 lgdpdfrati~w | -.000337 .000747 -.007569 .018807 lpopau | .003156 -.006874 -.417745 .011862 1.44367 lpop | .000128 -.004853 -.001765 -.000041 .003182 .008862 lxrate1 | -6.1e-07 .000211 -.00011 .000458 -.002534 -.00023 .000363 lremote | -.00005 -.000837 -.013295 -.005175 .048505 -.000025 -.000141 .02314 ldist | .000852 -.005935 -.004399 .001391 .003476 .010474 .000693 -.003351 .029648 lopen | .000018 -.000103 -.000945 .000827 .003463 .00028 -.000071 .00111 .00025 english | -.000306 -.000497 .003129 .00286 -.017738 .000351 .001034 -.00427 .00753 white | .000882 -.017819 -.007797 .001362 .003918 .032511 .000836 -.000365 .040888 lwhitemg | -.00013 .000877 -.00081 -.000682 .004685 -.001865 -.000074 .002772 -.002723 _cons | -.035237 .133982 3.7744 .000039 -13.3641 -.136397 .036636 -.602068 -.237772</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000731 english | -.000493 .014046 white | .001197 .004875 .96445 lwhitemg | -8.7e-06 -.000084 -.090387 .009186 _cons | -.047312 .175096 -.367013 -.043906 129.478</p><p>. </p><p>. *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 8303.91 Log likelihood = -944.5557 Prob > chi2 = 0.0000 ------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2350753 .0324994 7.23 0.000 .1713777 .298773 lgdp | 1.57182 .0758937 20.71 0.000 1.423071 1.720569 lgdpau | .0156751 .6626794 0.02 0.981 -1.283153 1.314503 lgdpdfrati~w | -.1151279 .267149 -0.43 0.667 -.6387304 .4084745 lpopau | -1.820266 2.314284 -0.79 0.432 -6.35618 2.715648 lpop | -.5327342 .0823502 -6.47 0.000 -.6941377 -.3713308 lxrate1 | -.1292222 .0289191 -4.47 0.000 -.1859026 -.0725418 lremote | -.3107685 .1289432 -2.41 0.016 -.5634926 -.0580444 ldist | -3.074014 .3422591 -8.98 0.000 -3.74483 -2.403199 lopen | .1194063 .0504406 2.37 0.018 .0205446 .218268 english | .8171685 .1368782 5.97 0.000 .5488922 1.085445 white | 9.240564 1.855988 4.98 0.000 5.602895 12.87823 lwhitemg | -.785234 .1862169 -4.22 0.000 -1.150212 -.4202556 _cons | 37.85046 21.82574 1.73 0.083 -4.927213 80.62812 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001056 lgdp | -.00161 .00576 lgdpau | -.002015 .005109 .439144 lgdpdfrati~w | -.001167 .002726 -.029423 .071369 lpopau | .00475 -.021814 -1.49401 .112019 5.35591 lpop | .000988 -.004679 -.003006 -.001699 .010878 .006782 lxrate1 | .000095 .000382 .00046 .001045 -.006612 -.000677 .000836 lremote | -8.4e-06 -.000722 -.005066 -.001332 .011264 -.001294 .00025 .016626 ldist | .004619 .002525 -.008763 -.002679 -.023971 .000295 .001838 .009353 .117141 lopen | .000128 -.000676 .001043 .001404 -.005815 .001367 -.000208 .000352 -.000918 english | -.001697 .004123 .005095 .004329 -.026057 -.000306 .002047 -.004812 -.00061 white | .001559 -.029537 .009781 -.000756 .000997 .022184 .004012 .012265 -.149402 lwhitemg | -.000097 .001658 -.002265 -.000463 .00564 -.001505 -.000385 .001014 .012988 _cons | -.053198 .158736 13.3654 -1.15545 -49.3589 -.094805 .074872 -.254136 -.659061</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002544 english | -.001436 .018736 white | .00408 .010229 3.44469 lwhitemg | -.000309 -.00178 -.339028 .034677 _cons | .06896 .25062 1.32248 -.177853 476.363</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 8642.47 Log likelihood = -1108.553 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0157963 .0111371 1.42 0.156 -.006032 .0376246 lgdp | 1.304063 .0399145 32.67 0.000 1.225832 1.382294 lgdpau | .6704192 .3295221 2.03 0.042 .0245677 1.316271 lgdpdfrati~w | -.0844937 .0905818 -0.93 0.351 -.2620308 .0930433 lpopau | -7.255706 1.119171 -6.48 0.000 -9.449241 -5.062171 lpop | .1059401 .0561862 1.89 0.059 -.0041827 .216063 lxrate1 | -.02032 .0122817 -1.65 0.098 -.0443916 .0037516 lremote | -.4067515 .12964 -3.14 0.002 -.6608411 -.1526618 ldist | -3.156201 .24817 -12.72 0.000 -3.642605 -2.669797 lopen | .0114202 .0279674 0.41 0.683 -.0433948 .0662353 english | 2.566891 .1124506 22.83 0.000 2.346492 2.787291 white | 6.566077 1.396572 4.70 0.000 3.828847 9.303308 lwhitemg | -.3601438 .1277199 -2.82 0.005 -.6104703 -.1098173 _cons | 107.9772 11.10308 9.72 0.000 86.21555 129.7388 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000124 lgdp | -.000205 .001593 lgdpau | .000353 -.000962 .108585 lgdpdfrati~w | -.000065 .000224 .000072 .008205 lpopau | -.002326 .003348 -.358621 -.002139 1.25254 lpop | .000106 -.001671 .000546 7.5e-06 -.00335 .003157 lxrate1 | .000011 .000058 -.000285 .000273 -.000162 -.000122 .000151 lremote | .000075 .00073 -.014781 .003081 .042734 -.000731 .000344 .016807 ldist | .000425 .001144 -.009756 .001887 .015905 .000227 .000512 .011813 .061588 lopen | 9.3e-06 -.000066 .000547 .001178 -.001272 .00025 -.000062 .000757 .000123 english | -.000312 .000016 -.001157 .000037 .001229 .001694 .000386 -.001124 .004518 white | -.000079 -.010077 -.009467 .003503 .041657 .011781 .000797 .008319 -.119321 lwhitemg | .000026 .000568 -.000318 -.00008 -.000366 -.000642 -.000026 .000429 .013834</p><p>_cons | .027203 -.055797 3.33793 -.02528 -11.9198 .0321 .001825 -.591515 -.739093</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000782 english | -.000602 .012645 white | .000734 .008453 1.95041 lwhitemg | -.00003 -.000525 -.174681 .016312 _cons | -.004043 -.053291 .65731 -.124661 123.278</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 582.00 Log likelihood = -572.134 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3700374 .0405026 9.14 0.000 .2906537 .4494211 lgdp | .1082356 .0534517 2.02 0.043 .0034722 .212999 lgdpau | .456046 .3456805 1.32 0.187 -.2214754 1.133567 lgdpdfrati~w | -.6249579 .1313177 -4.76 0.000 -.8823358 -.3675799 lpopau | -3.493499 1.296364 -2.69 0.007 -6.034325 -.9526734 lpop | .4992088 .0809156 6.17 0.000 .3406172 .6578003 lxrate1 | -.1356636 .0233115 -5.82 0.000 -.1813533 -.0899739 lremote | .2456686 .151094 1.63 0.104 -.0504703 .5418074 ldist | -1.12548 .3956639 -2.84 0.004 -1.900967 -.349993 lopen | .1252932 .0194156 6.45 0.000 .0872392 .1633471 english | .7044846 .2136325 3.30 0.001 .2857725 1.123197 white | 10.54013 .7287972 14.46 0.000 9.111713 11.96855 lwhitemg | -1.001386 .0742797 -13.48 0.000 -1.146971 -.8558005 _cons | 49.54151 13.59756 3.64 0.000 22.89077 76.19224 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .00164 lgdp | -.000511 .002857 lgdpau | .003399 -.003592 .119495 lgdpdfrati~w | -.001301 -.00067 -.003808 .017244 lpopau | -.020993 .02282 -.425295 .010661 1.68056 lpop | -.000643 -.002159 -.000484 .001 -.007849 .006547 lxrate1 | .000078 .000108 .001517 .000797 -.008322 -.000366 .000543 lremote | .002257 .001996 -.011732 -.005736 .033288 -.002642 -.00029 .022829 ldist | .004038 -.004765 -.000685 -.000884 -.069148 .01329 .000983 .017877 .15655 lopen | .0004 -.000424 .000119 -.000752 -.003762 .000213 -.00017 .000464 .001147 english | -.002003 .000546 -.002388 .003703 .002533 .00583 .001094 -.002433 .014518 white | .006626 -.003032 .025239 -.000248 -.164447 .009164 .003808 .005755 -.029121 lwhitemg | -.000725 -.000207 -.003084 .000198 .016401 -.000276 -.000385 .000073 .00576 _cons | .213722 -.286534 4.0972 -.030547 -16.6141 -.011069 .091323 -.626451 -.615549</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000377 english | -.000939 .045639 white | .000539 .047177 .531145 lwhitemg | -.000018 -.00202 -.051272 .005517 _cons | .050082 -.224012 2.12712 -.230191 184.894</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 3219.02 Log likelihood = -593.5572 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1374692 .0324804 4.23 0.000 .0738088 .2011296 lgdp | .2700827 .0555976 4.86 0.000 .1611134 .3790519 lgdpau | -.1236487 .067354 -1.84 0.066 -.2556601 .0083626 lgdpdfrati~w | -.1319195 .0443626 -2.97 0.003 -.2188685 -.0449705 lpopau | 2.649922 .2746441 9.65 0.000 2.111629 3.188214 lpop | .7702596 .1017661 7.57 0.000 .5708017 .9697176 lxrate1 | -.0125568 .0087629 -1.43 0.152 -.0297317 .0046181 lremote | .1503049 .0342075 4.39 0.000 .0832595 .2173503 ldist | -3.226607 .3520282 -9.17 0.000 -3.91657 -2.536645 lopen | -.0096735 .031642 -0.31 0.760 -.0716908 .0523438 english | .776768 .2801212 2.77 0.006 .2277406 1.325796 white | 23.81469 3.035656 7.84 0.000 17.86491 29.76446 lwhitemg | -2.215677 .2868336 -7.72 0.000 -2.77786 -1.653493 _cons | -24.40038 5.284477 -4.62 0.000 -34.75776 -14.04299 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001055 lgdp | -.000628 .003091 lgdpau | -.00073 -.000469 .004537 lgdpdfrati~w | .000364 -.001207 .000915 .001968 lpopau | .005041 -.000175 -.015534 .00034 .075429 lpop | -.000243 -.002377 .001301 .000542 -.004904 .010356 lxrate1 | 8.7e-06 .000088 -.000051 .000037 .000743 -.000241 .000077 lremote | -.000362 .001297 -.000731 -.001111 8.5e-06 -.000775 .000037 .00117 ldist | .003735 -.000262 -.003345 .000032 .022878 -.002182 -.000112 -.000066 .123924 lopen | -.00037 -.00025 .000251 -.000484 -.004604 .001145 -.000187 .000231 -.000858 english | -.00072 -.000509 .000845 .000412 -.006333 .000518 .000045 -.000383 .057669 white | .00325 -.005796 .000875 .002067 -.000552 .029745 -.000601 -.00253 .011555 lwhitemg | -.000582 .00011 .000215 -.000078 -.002247 -.003074 .000055 .00011 -.003881 _cons | -.085555 -.023051 .170953 -.005701 -1.01136 -.033161 -.008941 -.004698 -1.46058</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001001 english | -.000023 .078468 white | .001462 .027379 9.21521 lwhitemg | 4.2e-06 -.001541 -.85743 .082274 _cons | .067723 -.477696 -.483477 .118424 27.9257</p><p>. . . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 523.48 Log likelihood = -548.1348 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5334269 .049988 10.67 0.000 .4354523 .6314015 lgdp | -.0008857 .0767782 -0.01 0.991 -.1513683 .1495969 lgdpau | 2.071311 .7930406 2.61 0.009 .5169803 3.625642 lgdpdfrati~w | -.7038911 .2852919 -2.47 0.014 -1.263053 -.1447293 lpopau | -10.27812 2.725575 -3.77 0.000 -15.62014 -4.936088 lpop | .362242 .093998 3.85 0.000 .1780093 .5464746 lxrate1 | -.1127222 .0261451 -4.31 0.000 -.1639656 -.0614789 lremote | .0066571 .2542585 0.03 0.979 -.4916805 .5049947 ldist | -1.52016 .3243997 -4.69 0.000 -2.155972 -.8843486 lopen | .0439066 .0543593 0.81 0.419 -.0626357 .1504488 english | -.0785377 .2368967 -0.33 0.740 -.5428467 .3857712 white | 9.383766 1.123252 8.35 0.000 7.182232 11.5853 lwhitemg | -.8483653 .1007906 -8.42 0.000 -1.045911 -.6508193 _cons | 127.9287 25.85871 4.95 0.000 77.24658 178.6109 ------. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002499 lgdp | -.001522 .005895 lgdpau | .000362 -.000448 .628913 lgdpdfrati~w | -.001421 .001555 -.019056 .081391 lpopau | -.005542 -.004844 -2.10063 .076133 7.42876 lpop | -.000235 -.003899 -.000346 -.000756 -.001263 .008836 lxrate1 | .000152 -.000192 .000402 .000839 -.004172 -.000434 .000684 lremote | .001744 .004224 -.021086 -.01259 .05793 -.002935 .000457 .064647 ldist | .005063 .001263 -.009237 -.003667 -.009937 .002745 .000911 .030708 .105235 lopen | -.000262 .000642 .000454 -.000503 -.010603 .000729 -.000017 .001259 .001944 english | -.001923 .001108 .003766 .005328 -.018923 -.000154 .001316 -.010648 .026967 white | .012965 -.024409 .018587 -.006151 -.084569 .028149 .00574 .017983 -.007223 lwhitemg | -.001265 .00123 -.003018 -.000159 .014596 -.001691 -.000443 .000728 .001436 _cons | .040667 -.018423 18.6477 -.720325 -68.4603 -.020681 .053135 -1.30833 -.968072</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002955 english | -.000319 .05612 white | -.001112 .015624 1.2617 lwhitemg | .000046 -.000135 -.108639 .010159 _cons | .112879 .011179 .786462 -.171003 668.673</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1654.38 Log likelihood = -326.9527 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0523704 .0190146 2.75 0.006 .0151024 .0896384 lgdp | .214912 .0556748 3.86 0.000 .1057914 .3240325 lgdpau | -.1076629 .3537492 -0.30 0.761 -.8009985 .5856728 lgdpdfrati~w | -.4481144 .1976721 -2.27 0.023 -.8355445 -.0606842 lpopau | 1.859957 1.248641 1.49 0.136 -.587335 4.307249 lpop | .1098579 .0717602 1.53 0.126 -.0307895 .2505054 lxrate1 | -.05795 .0182059 -3.18 0.001 -.0936328 -.0222671 lremote | -.1942601 .1163976 -1.67 0.095 -.4223953 .033875 ldist | -1.376286 .1431765 -9.61 0.000 -1.656907 -1.095665 lopen | -.0269968 .0243867 -1.11 0.268 -.0747938 .0208001 english | 2.083308 .1975593 10.55 0.000 1.696099 2.470517 white | 8.274286 1.189132 6.96 0.000 5.943631 10.60494 lwhitemg | -.5812291 .1126841 -5.16 0.000 -.8020859 -.3603722 _cons | -18.36732 12.33939 -1.49 0.137 -42.55209 5.81745 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000362 lgdp | -.000347 .0031 lgdpau | .000213 -.001513 .125138 lgdpdfrati~w | -.000645 -.000035 -.001498 .039074 lpopau | -.001065 .005295 -.426978 .022452 1.55911 lpop | .00004 -.002899 .000883 .000673 -.006499 .00515 lxrate1 | -.000017 .000169 .001276 .000698 -.006016 -.000166 .000331 lremote | .000193 .001241 -.008672 -.003724 .031053 -.000782 -.000468 .013548 ldist | .000712 .001117 -.000514 -.002258 -.000764 .001232 -.000311 -.00131 .0205 lopen | .000015 -.000232 .000356 .00095 -.002156 .00029 -9.5e-06 -.000073 -.000162 english | -.000499 -.004084 .006084 .002796 -.019643 .005035 .000423 -.007025 .001631 white | .001681 -.024896 .011967 -.000912 -.057503 .03015 -.000059 -.000625 -.007779 lwhitemg | -.000183 .001604 -.001106 .000305 .005089 -.002291 .000019 .000642 -.000892 _cons | .009656 -.091007 3.89563 -.330797 -14.9451 .063943 .070455 -.402501 -.198933</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000595 english | -.000361 .03903 white | .000612 .088815 1.41403 lwhitemg | .000014 -.007912 -.130102 .012698 _cons | .028607 .216106 .779189 -.051021 152.261</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1049.99 Log likelihood = -843.4196 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1297805 .0642737 2.02 0.043 .0038063 .2557547 lgdp | .5256299 .1083781 4.85 0.000 .3132129 .738047 lgdpau | -2.246376 1.083564 -2.07 0.038 -4.370123 -.1226289 lgdpdfrati~w | -1.019317 .4380333 -2.33 0.020 -1.877847 -.1607879 lpopau | 4.858502 3.714765 1.31 0.191 -2.422304 12.13931 lpop | .2593488 .1236444 2.10 0.036 .0170102 .5016873 lxrate1 | -.1640029 .0402326 -4.08 0.000 -.2428574 -.0851484 lremote | 1.539147 .2850687 5.40 0.000 .9804229 2.097872 ldist | -1.847338 .4765575 -3.88 0.000 -2.781373 -.9133024 lopen | .0040419 .0741026 0.05 0.957 -.1411965 .1492803 english | .1117897 .2640528 0.42 0.672 -.4057442 .6293237 white | 11.80425 1.618256 7.29 0.000 8.63253 14.97598 lwhitemg | -.9749635 .1694457 -5.75 0.000 -1.307071 -.642856 _cons | -29.45605 34.98472 -0.84 0.400 -98.02485 39.11275 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .004131 lgdp | -.004242 .011746 lgdpau | -.002134 .005373 1.17411 lgdpdfrati~w | -.001863 .004464 .000769 .191873 lpopau | .003635 -.026402 -3.92486 .044828 13.7995 lpop | .001323 -.009918 -.001665 -.002379 .008771 .015288 lxrate1 | .000098 .001671 .000541 .001355 -.00837 -.001681 .001619 lremote | .001781 -.002514 -.036441 -.02266 .098655 .001262 .001434 .081264 ldist | .011955 -.01028 -.011293 -.011629 .003558 .014016 -.002202 .024026 .227107 lopen | .00032 -.00082 .00664 .000815 -.033348 .002085 -.000388 .002399 .004077 english | -.005268 .011172 .003655 -.000333 -.01427 -.009577 .000036 .002263 .025498 white | .021976 -.052556 -.01213 -.026878 -.046441 .062951 -.001683 .069732 .098581 lwhitemg | -.002406 .003361 -.003956 -.00054 .025495 -.004367 .000059 .001931 -.012598 _cons | -.078869 .319608 34.6547 -.707191 -126.539 -.259844 .114673 -1.5834 -2.17217</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005491 english | -.000906 .069724 white | .006856 -.028754 2.61875 lwhitemg | -.000686 .0026 -.261719 .028712 _cons | .308816 -.212283 -.358773 -.211729 1223.93</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 580.25 Log likelihood = -123.9382 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0435222 .0291951 1.49 0.136 -.0136991 .1007435 lgdp | .1263176 .0601068 2.10 0.036 .0085105 .2441248 lgdpau | .2989716 .4229197 0.71 0.480 -.5299359 1.127879 lgdpdfrati~w | .3553838 .1883922 1.89 0.059 -.0138582 .7246257 lpopau | 2.665812 1.486464 1.79 0.073 -.2476031 5.579227 lpop | .322971 .0812208 3.98 0.000 .1637812 .4821608 lxrate1 | -.0212639 .0161442 -1.32 0.188 -.0529059 .0103781 lremote | -.0515016 .1328894 -0.39 0.698 -.3119601 .2089569 ldist | -2.08309 .4470924 -4.66 0.000 -2.959375 -1.206805 lopen | .0342619 .0355247 0.96 0.335 -.0353653 .103889 english | 1.049133 .2037814 5.15 0.000 .6497285 1.448537 white | 14.67589 1.387561 10.58 0.000 11.95632 17.39546 lwhitemg | -1.186951 .1381241 -8.59 0.000 -1.457669 -.9162324 _cons | -39.74838 15.32545 -2.59 0.009 -69.78571 -9.711044 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000852 lgdp | -.000645 .003613 lgdpau | -.000511 -.000068 .178861 lgdpdfrati~w | -.000663 .000759 -.00086 .035492 lpopau | .001317 .000774 -.600047 .018169 2.20957 lpop | -.000105 -.002744 .000311 .000721 -.003569 .006597 lxrate1 | .000055 .000076 .000196 .000549 -.002626 -.000092 .000261 lremote | .000868 .002063 -.007987 -.002935 .023692 -.001585 .000052 .01766 ldist | .002866 -.005548 -.01133 -.006309 .011539 .010344 .000029 .018181 .199892 lopen | -.000051 6.6e-06 .000401 .00036 -.004406 .000459 -.000049 .000048 -.00002 english | -.001174 -.001837 .002035 .003124 -.006296 .00552 .000198 -.004647 .016749 white | .003817 -.015763 .036018 -.006378 -.290833 .024281 .003348 -.007328 -.026128 lwhitemg | -.000453 .000762 -.003984 .000497 .030295 -.0018 -.000357 .000951 .003969 _cons | -.031138 -.010855 5.43849 -.256634 -21.2077 -.076841 .035823 -.532323 -2.01565</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001262 english | -.000094 .041527 white | -.000102 .032339 1.92533 lwhitemg | .00002 -.002153 -.187397 .019078 _cons | .055861 -.121005 4.13019 -.429785 234.869</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 249.73 Log likelihood = 135.6087 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0057813 .0195717 0.30 0.768 -.0325785 .0441412 lgdp | .2590776 .0507209 5.11 0.000 .1596664 .3584887 lgdpau | -.3077517 .3535816 -0.87 0.384 -1.000759 .3852555 lgdpdfrati~w | -.0982163 .1429167 -0.69 0.492 -.3783279 .1818953 lpopau | 4.254485 1.288274 3.30 0.001 1.729514 6.779455 lpop | -.0684615 .0614505 -1.11 0.265 -.1889022 .0519792 lxrate1 | -.0947932 .0152559 -6.21 0.000 -.1246941 -.0648922 lremote | .3251191 .1306186 2.49 0.013 .0691114 .5811269 ldist | -1.33333 .2846948 -4.68 0.000 -1.891321 -.7753384 lopen | .0193849 .0291623 0.66 0.506 -.0377721 .076542 english | .2642521 .166186 1.59 0.112 -.0614664 .5899707 white | 9.382888 2.506151 3.74 0.000 4.470923 14.29485 lwhitemg | -.7755829 .2489963 -3.11 0.002 -1.263607 -.2875591 _cons | -56.49043 13.673 -4.13 0.000 -83.28901 -29.69185 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000383 lgdp | -.000345 .002573 lgdpau | .000248 -.000693 .12502 lgdpdfrati~w | -.000426 .000464 -.006159 .020425 lpopau | -.002464 .004521 -.429415 .027476 1.65965 lpop | -5.0e-06 -.002182 -.000117 -.000104 -.000139 .003776 lxrate1 | 2.4e-06 -4.0e-06 .000503 .000474 -.004575 -.000102 .000233 lremote | .00033 .001736 -.008107 -.001173 .028005 -.001416 -.000067 .017061 ldist | .001716 -.001324 -.002484 -.00149 .002211 .004082 .000067 .007651 .081051 lopen | -9.8e-06 .00003 .000095 .000167 -.001715 .000163 -.000026 .0001 -.000432 english | -.000514 -.001632 -.000077 .000756 .020466 .004361 .000196 -.001217 .014694 white | .002233 -.014309 .022761 -.004448 -.176612 .014884 .002086 -.003437 .004138 lwhitemg | -.000268 .000837 -.002691 .000435 .017905 -.001119 -.000153 .001037 -.00132 _cons | .021696 -.080568 3.95854 -.299786 -16.6346 -.031945 .062829 -.4901 -.857575</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00085 english | -.000396 .027618 white | -.000606 .023094 6.28079 lwhitemg | .000071 -.001949 -.615886 .061999 _cons | .026479 -.504103 2.38767 -.222457 186.951 . xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 497.72 Log likelihood = -664.2044 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1768853 .05314 3.33 0.001 .0727329 .2810376 lgdp | .7429416 .1040117 7.14 0.000 .5390824 .9468009 lgdpau | -.6971969 .6807035 -1.02 0.306 -2.031351 .6369574 lgdpdfrati~w | -.3192683 .279874 -1.14 0.254 -.8678113 .2292748 lpopau | 4.137204 2.345857 1.76 0.078 -.460591 8.734998 lpop | -.2691949 .1482055 -1.82 0.069 -.5596723 .0212825 lxrate1 | -.1392666 .0314126 -4.43 0.000 -.2008342 -.077699 lremote | .1696736 .2370148 0.72 0.474 -.2948668 .634214 ldist | -3.077528 .691404 -4.45 0.000 -4.432655 -1.722401 lopen | .0300183 .0653535 0.46 0.646 -.0980721 .1581088 english | -.1950759 .4434575 -0.44 0.660 -1.064237 .6740847 white | 16.87624 4.613077 3.66 0.000 7.834775 25.9177 lwhitemg | -1.357054 .4554818 -2.98 0.003 -2.249782 -.4643257 _cons | -32.27859 23.12584 -1.40 0.163 -77.60441 13.04723 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002824 lgdp | -.002336 .010818 lgdpau | .001443 -.00149 .463357 lgdpdfrati~w | -.001801 .003326 -.012115 .078329 lpopau | -.009455 .000322 -1.54288 .065578 5.50304 lpop | -.000167 -.007884 -.001638 -.001808 -.006242 .021965 lxrate1 | .000152 .000475 .001974 .001222 -.010489 -.000773 .000987 lremote | .001002 .004421 -.021011 -.012245 .041321 -.002804 .000523 .056176 ldist | .011335 .011115 -.006203 -.004269 -.052509 .006562 .000551 .032795 .478039 lopen | .000451 -.000992 -.000714 -.000087 -.011317 .001862 -.000189 .00064 .002989 english | -.006322 .002697 -.000172 .005594 -.010363 .018963 .0008 -.002953 .133994 white | .00958 -.029664 .161382 .024608 -.500893 .063792 .002375 .004916 .167033 lwhitemg | -.001557 .000775 -.017801 -.003994 .057557 -.004311 -.000198 .003074 -.027891 _cons | .046209 -.223812 13.7382 -.744887 -50.5888 -.059317 .107983 -.989968 -4.24335</p><p>| lopen english white lwhitemg _cons ------+------lopen | .004271 english | -.00175 .196655 white | .008519 .152302 21.2805 lwhitemg | -.000851 -.013594 -2.05761 .207464 _cons | .167325 -1.45489 1.96324 -.182753 534.805</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1175.44 Log likelihood = -576.6353 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2149346 .0474422 4.53 0.000 .1219497 .3079196 lgdp | .541306 .0956998 5.66 0.000 .3537378 .7288742 lgdpau | .7909604 .6860747 1.15 0.249 -.5537212 2.135642 lgdpdfrati~w | -.074485 .2939281 -0.25 0.800 -.6505735 .5016035 lpopau | -3.363428 2.374389 -1.42 0.157 -8.017145 1.290288 lpop | .5807087 .1179361 4.92 0.000 .3495581 .8118593 lxrate1 | -.0797496 .0297749 -2.68 0.007 -.1381073 -.0213919 lremote | -.2554966 .2435263 -1.05 0.294 -.7327993 .2218061 ldist | -2.196152 .432636 -5.08 0.000 -3.044103 -1.348201 lopen | -.1154077 .0746391 -1.55 0.122 -.2616977 .0308824 english | 1.076851 .317179 3.40 0.001 .455192 1.698511 white | 24.44467 3.235139 7.56 0.000 18.10392 30.78543 lwhitemg | -2.308337 .2958286 -7.80 0.000 -2.888151 -1.728524 _cons | 39.70182 22.7592 1.74 0.081 -4.905383 84.30903 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002251 lgdp | -.001958 .009158 lgdpau | -.002107 .004904 .470698 lgdpdfrati~w | -.00194 .00311 -.021038 .086394 lpopau | .006172 -.033288 -1.57636 .070584 5.63772 lpop | .000284 -.006799 -.002905 -.002041 .013435 .013909 lxrate1 | .000042 .000671 .000659 .001504 -.007193 -.000834 .000887 lremote | .000563 .004064 -.014421 -.018336 .030378 -.003085 .000354 .059305 ldist | .008346 -.002041 -.008544 -.002107 -.002268 .012475 .00021 .006738 .187174 lopen | .000242 -.000324 .00006 .002582 -.011501 .001874 -.000055 .001436 .002323 english | -.002999 .00062 .004313 .005416 -.01758 .001032 .000634 -.010219 .056489 white | .006413 -.027088 .034139 -.014691 -.085874 .050718 .00364 .041974 .035477 lwhitemg | -.000939 .000785 -.004732 -.000405 .016987 -.003783 -.000364 -.000495 -.008091 _cons | -.10126 .31421 13.9729 -.555681 -51.9768 -.30193 .090522 -.735159 -1.77914</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005571 english | -.002197 .100602 white | .00791 .001677 10.4661 lwhitemg | -.000753 .001487 -.94005 .087515 _cons | .132072 -.318275 -.419341 -.027615 517.981</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1875.50 Log likelihood = -765.7125 Prob > chi2 = 0.0000 ------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0955005 .0360009 2.65 0.008 .02494 .1660611 lgdp | .9681142 .0972557 9.95 0.000 .7774966 1.158732 lgdpau | .833151 .7071831 1.18 0.239 -.5529024 2.219204 lgdpdfrati~w | -.1182447 .2822381 -0.42 0.675 -.6714213 .4349319 lpopau | 3.384109 2.45725 1.38 0.168 -1.432012 8.200231 lpop | -.4025201 .142939 -2.82 0.005 -.6826755 -.1223648 lxrate1 | -.1457258 .0222992 -6.54 0.000 -.1894315 -.1020202 lremote | -.3416663 .1926449 -1.77 0.076 -.7192433 .0359108 ldist | -1.249834 .7663014 -1.63 0.103 -2.751758 .2520886 lopen | -.083254 .0745316 -1.12 0.264 -.2293332 .0628253 english | .2149472 .3557216 0.60 0.546 -.4822544 .9121488 white | 26.12057 4.174913 6.26 0.000 17.93789 34.30325 lwhitemg | -2.375914 .4377964 -5.43 0.000 -3.23398 -1.517849 _cons | -76.09738 24.58823 -3.09 0.002 -124.2894 -27.90534 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist</p><p>------+------limmig | .001296 lgdp | -.002046 .009459 lgdpau | -.000967 .002783 .500108 lgdpdfrati~w | -.002218 .004658 -.01635 .079658 lpopau | -.00452 -.012926 -1.66412 .062152 6.03808 lpop | .001874 -.011603 -.0061 -.004511 .031177 .020432 lxrate1 | .000067 .000294 .000332 .000734 -.008811 -.000637 .000497 lremote | .001713 .003293 -.017276 -.004863 .011764 -.002063 .000396 .037112 ldist | .008279 .010208 -.031087 -.005719 -.058695 .014487 .001753 .072942 .587218 lopen | .000309 -.000915 -.000311 .004596 -.008079 .001264 -.000358 .000982 .000694 english | -.000984 .003182 .000837 .002465 -.007769 -.000404 .00094 .002337 .074961 white | .009446 -.062277 .044722 -.022995 -.113751 .070131 .002231 -.025217 -.323101 lwhitemg | -.00064 .004409 -.006554 .001163 .015255 -.005066 -.000126 .004338 .030064 _cons | .018455 -.01104 14.9866 -.6085 -56.2854 -.53877 .117409 -.810271 -4.97306</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005555</p><p> english | -.001849 .126538 white | .001021 -.003853 17.4299 lwhitemg | -6.2e-06 .000083 -1.81505 .191666 _cons | .127341 -.707083 4.28961 -.424306 604.581</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 538.66 Log likelihood = -579.4465 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3969151 .0582854 6.81 0.000 .2826779 .5111523 lgdp | .2898127 .0985515 2.94 0.003 .0966554 .48297 lgdpau | 1.185084 .7544304 1.57 0.116 -.2935729 2.66374 lgdpdfrati~w | -.5316353 .3192582 -1.67 0.096 -1.15737 .0940992 lpopau | -4.729325 2.605298 -1.82 0.069 -9.835615 .3769642 lpop | .3300364 .1055108 3.13 0.002 .123239 .5368337 lxrate1 | -.0873857 .0344519 -2.54 0.011 -.1549101 -.0198613 lremote | -.0143732 .2312264 -0.06 0.950 -.4675686 .4388221 ldist | -1.343693 .580563 -2.31 0.021 -2.481576 -.2058107 lopen | .101332 .0720214 1.41 0.159 -.0398273 .2424913 english | -.1008651 .2840222 -0.36 0.722 -.6575384 .4558081 white | 20.69667 2.790943 7.42 0.000 15.22653 26.16682 lwhitemg | -1.974219 .2861634 -6.90 0.000 -2.535089 -1.413349 _cons | 51.38667 24.69361 2.08 0.037 2.988086 99.78525 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .003397 lgdp | -.00319 .009712 lgdpau | -.002247 .006346 .569165 lgdpdfrati~w | -.002532 .005902 -.010675 .101926 lpopau | .00481 -.03428 -1.90414 .053666 6.78758 lpop | .001038 -.006294 -.003756 -.003921 .009432 .011133 lxrate1 | .000341 .000463 -.00035 .000875 -.003465 -.00065 .001187 lremote | .000222 .002843 -.010904 -.017179 .003452 .000489 .001616 .053466 ldist | .011103 .000826 -.007059 -.011342 -.062946 .005896 .000736 .038635 .337053 lopen | -.000307 .000782 .00235 .000174 -.023476 .00174 -.000181 .002139 .003036 english | -.003554 .006996 .003724 .001513 -.01703 -.001017 -.001496 .00931 .093958 white | .017531 -.031019 .071771 -.04794 -.220968 .033944 -.006608 .053077 .118539 lwhitemg | -.002009 .001347 -.009869 .001731 .036747 -.002475 .000382 -.001217 -.020107 _cons | -.091992 .26111 16.7604 -.512406 -61.5719 -.15347 .040274 -.672941 -2.4942</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005187 english | -.000494 .080669 white | .005635 .054632 7.78936 lwhitemg | -.000773 -.00719 -.787562 .081889 _cons | .241398 -.924089 .273184 -.127846 609.774</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1533.15 Log likelihood = -277.0036 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0014769 .0241081 0.06 0.951 -.0457741 .0487279 lgdp | .4250867 .0830131 5.12 0.000 .2623841 .5877893 lgdpau | -.3950659 .5112325 -0.77 0.440 -1.397063 .6069313 lgdpdfrati~w | .1531802 .2312302 0.66 0.508 -.3000227 .6063831 lpopau | 1.478085 1.762663 0.84 0.402 -1.976671 4.932841 lpop | -.2050643 .1167217 -1.76 0.079 -.4338346 .023706 lxrate1 | -.0391653 .0231349 -1.69 0.090 -.0845089 .0061782 lremote | -.0035268 .1730421 -0.02 0.984 -.3426832 .3356296 ldist | -3.761239 .5255437 -7.16 0.000 -4.791286 -2.731192 lopen | .0145071 .0517268 0.28 0.779 -.0868756 .1158897 english | -.0808905 .3269418 -0.25 0.805 -.7216847 .5599037 white | 14.35931 3.162921 4.54 0.000 8.160098 20.55852 lwhitemg | -.9663833 .3434985 -2.81 0.005 -1.639628 -.2931386 _cons | 16.69222 17.615 0.95 0.343 -17.83254 51.21699 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000581 lgdp | -.000748 .006891 lgdpau | .000204 -.001994 .261359 lgdpdfrati~w | -.000907 .002448 -.010205 .053467 lpopau | -.001603 .000243 -.872667 .052331 3.10698 lpop | .000252 -.006327 -.000225 -.000938 -.001024 .013624 lxrate1 | -.000019 .000142 .001418 .001072 -.00691 -.00049 .000535 lremote | .000134 .002093 -.017329 -.003856 .050018 -.002294 -.000123 .029944 ldist | .002569 .001964 -.009444 -.001418 -.014557 .020338 -.000213 .013237 .276196 lopen | .00004 -.000068 -.002127 .001077 .002224 .000776 -.000053 .000215 .00038 english | -.001053 -.001324 .003312 .001764 -.004288 .007389 .000812 -.00076 .073464 white | .004569 -.0367 .054942 -.003734 -.29801 .060339 .002254 -.017067 .146969 lwhitemg | -.000482 .001459 -.006579 -.000477 .036201 -.00468 -.000035 .004583 -.018529 _cons | .006679 -.04047 7.9114 -.648408 -28.9673 -.222852 .081605 -.771225 -2.65824</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002676 english | -.000622 .106891 white | -.001719 .100621 10.0041 lwhitemg | .000208 -.009411 -1.0761 .117991 _cons | .003168 -.813413 2.07827 -.24763 310.288</p><p>. . clear</p><p>. insheet using k:\book1.txt (104 vars, 1010 obs)</p><p>. . *Dropping Guinea-Bisau . drop if ccode==163240 (10 observations deleted)</p><p>. . . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist open english gdpdfration > ew white whitemg, stat(n mean sd median min max) col(stat) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 491197.4 1561183 8397.5 0 1.39e+07 immig | 1000 33462.02 117038.5 2986.5 0 1137050 gdp | 1000 2.79e+11 9.69e+11 1.74e+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 105.6973 16.9395 102.7439 60.87417 207.3465 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.96e+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 1040.992 10901.88 13.89535 .0068 270182.6 remote | 1000 6733.485 4145.89 6764 1293 39620 dist | 1000 13333.85 3514.172 14215 2409 17972 open | 1000 .7095294 .389513 .6384 .0671 3.2192 english | 1000 .38 .4856293 0 0 1 gdpdfratio~w | 1000 1.052499 .1815139 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" countries)--RHS Variables > : . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist phone open eng > lish gdpdfrationew white whitemg, stat(n mean sd median min max) col(stat) ------> white = 0</p><p> variable | N mean sd p50 min max ------+------rimp | 870 404946.6 1597577 3443.5 0 1.39e+07 immig | 870 14896.97 27125.08 1606 0 158613 gdp | 870 2.37e+11 1.00e+12 1.09e+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 | 870 104.8245 17.3007 101.6682 60.87417 207.3465 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.35e+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 1180.549 11681.95 19.96485 .0068 270182.6 remote | 870 7158.98 4116.81 6927 1293 39620 dist | 870 13158.91 3398.218 14040 2410 17972 phone | 870 159.2907 241.8643 49.865 .54 1449.75 open | 870 .717139 .4109572 .6373 .0671 3.2192 english | 870 .3908046 .4882114 0 0 1 gdpdfratio~w | 870 1.04406 .1864499 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 lremote 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) = 8114.92 Log likelihood = -526.5259 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3509804 .0309416 11.34 0.000 .290336 .4116248 lgdp | 1.198916 .0329359 36.40 0.000 1.134363 1.263469 lgdpau | .0992335 .6092098 0.16 0.871 -1.094796 1.293263 lgdpdfrati~w | -.9307348 .2474573 -3.76 0.000 -1.415742 -.4457273 lpopau | -2.623754 2.100772 -1.25 0.212 -6.741191 1.493684 lpop | .0262654 .0400439 0.66 0.512 -.0522193 .1047501 lxrate1 | -.132808 .0171852 -7.73 0.000 -.1664903 -.0991257 lremote | -.4476398 .0734735 -6.09 0.000 -.5916453 -.3036344 ldist | -2.119031 .168057 -12.61 0.000 -2.448416 -1.789645 lopen | .3145064 .0574882 5.47 0.000 .2018317 .4271812 english | .9356267 .1222657 7.65 0.000 .6959903 1.175263 white | 4.76602 .5591177 8.52 0.000 3.670169 5.861871 lwhitemg | -.4500186 .0497992 -9.04 0.000 -.5476232 -.352414 _cons | 43.13112 19.40328 2.22 0.026 5.101397 81.16084 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000957 lgdp | -.000307 .001085 lgdpau | -.000857 .00134 .371137 lgdpdfrati~w | -.000739 .000066 -.009083 .061235 lpopau | .001473 -.008041 -1.25369 .047821 4.41324 lpop | -.000136 -.000727 -3.9e-06 .000149 .000396 .001604 lxrate1 | .000075 .000139 .000264 .00018 -.002035 -.000067 .000295 lremote | .000489 .000186 -.000127 -.001568 -.005094 -.000181 .000178 .005398 ldist | .001471 .000704 -.00016 -.001169 -.009735 .000462 .001994 .006063 .028243 lopen | -.000134 .000646 .002488 .000668 -.017955 .000228 .000085 .001461 .000321 english | -.001112 .002596 .002445 .001681 -.009137 -.001288 .000462 -.002641 .002455 white | .004801 -.001301 .00315 -.010869 -.027735 .004205 .000404 -.000641 .002867 lwhitemg | -.00058 .000131 -.00027 .001016 .002933 -.000316 -.000044 .000101 -.000501 _cons | -.017414 .076459 11.047 -.593821 -40.0745 -.016184 .002445 -.017572 -.194017</p><p>| lopen english white lwhitemg _cons ------+------lopen | .003305 english | -.000733 .014949 white | -.000689 .003086 .312613 lwhitemg | -.000028 -.000069 -.027466 .00248 _cons | .200596 .042753 .278623 -.031197 376.487</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 55206.65 Log likelihood = -956.5316 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0517949 .0142908 3.62 0.000 .0237855 .0798043 lgdp | 1.601099 .0529635 30.23 0.000 1.497292 1.704905 lgdpau | .8658322 .364675 2.37 0.018 .1510824 1.580582 lgdpdfrati~w | -.4264911 .1527737 -2.79 0.005 -.725922 -.1270602 lpopau | -6.340832 1.231939 -5.15 0.000 -8.755388 -3.926276 lpop | -.3231129 .085682 -3.77 0.000 -.4910465 -.1551794 lxrate1 | -.1207528 .0205137 -5.89 0.000 -.1609588 -.0805468 lremote | -.9745984 .1006307 -9.68 0.000 -1.171831 -.7773659 ldist | -3.300297 .1698179 -19.43 0.000 -3.633134 -2.96746 lopen | -.0501898 .0271821 -1.85 0.065 -.1034657 .0030862 english | 1.005994 .0889267 11.31 0.000 .8317006 1.180287 white | 4.900032 .7641597 6.41 0.000 3.402307 6.397758 lwhitemg | -.4871559 .0726125 -6.71 0.000 -.6294737 -.344838 _cons | 95.95317 11.58514 8.28 0.000 73.24671 118.6596 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000204 lgdp | -.000282 .002805 lgdpau | -.001258 .001775 .132988 lgdpdfrati~w | -.000615 .000444 -.012448 .02334 lpopau | .005006 -.007764 -.439749 .025477 1.51767 lpop | .000169 -.004224 -.001458 .000516 .004386 .007341 lxrate1 | -.000029 .000307 -.00003 .000422 -.003271 -.000341 .000421 lremote | .000394 .000661 -.006673 -.00372 .023034 -.001379 .000071 .010127 ldist | .000608 -.000959 -.006536 -.001915 .015638 .002007 .000556 .005149 .028838 lopen | .000045 -.000107 -.001008 .000945 .003691 .000282 -.000075 .000642 .00026 english | -.000441 .000334 .00325 .002629 -.020976 .000279 .001118 -.002634 .002706 white | .001249 -.014506 -.010049 -.002663 .042419 .021555 -.001194 .003214 -.024724 lwhitemg | -.000105 .000822 .000399 .000081 -.002699 -.001137 .000152 .000373 .003353 _cons | -.055881 .088415 3.92743 -.083495 -13.9245 -.061093 .045793 -.336903 -.425373</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000739 english | -.000403 .007908 white | .001838 -.002239 .58394 lwhitemg | -.000135 .000406 -.053944 .005273 _cons | -.045584 .242762 -.236581 -.002506 134.215</p><p>. . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 7456.89 Log likelihood = -926.9251 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .201454 .030622 6.58 0.000 .141436 .2614719 lgdp | 1.638886 .073559 22.28 0.000 1.494713 1.783059 lgdpau | -.0330655 .6246571 -0.05 0.958 -1.257371 1.19124 lgdpdfrati~w | -.2293643 .2611691 -0.88 0.380 -.7412464 .2825178 lpopau | -1.857945 2.175642 -0.85 0.393 -6.122125 2.406235 lpop | -.5436258 .0805823 -6.75 0.000 -.7015643 -.3856873 lxrate1 | -.156112 .0287098 -5.44 0.000 -.2123822 -.0998418 lremote | -.3890459 .1302059 -2.99 0.003 -.6442448 -.1338471 ldist | -3.240319 .3403597 -9.52 0.000 -3.907412 -2.573227 lopen | .1146388 .0490299 2.34 0.019 .0185419 .2107357 english | .870778 .1393673 6.25 0.000 .597623 1.143933 white | 9.504274 1.835693 5.18 0.000 5.90638 13.10217 lwhitemg | -.8318209 .1835752 -4.53 0.000 -1.191622 -.4720201 _cons | 41.14934 20.63608 1.99 0.046 .7033782 81.59531 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000938 lgdp | -.001409 .005411 lgdpau | -.001883 .003929 .390197 lgdpdfrati~w | -.001239 .002979 -.025415 .068209 lpopau | .005034 -.021105 -1.31784 .091365 4.73342 lpop | .00089 -.004407 -.002081 -.001922 .010153 .006494 lxrate1 | .000079 .000455 .000048 .001194 -.005989 -.000731 .000824 lremote | -.000044 -.00029 -.005135 -.00124 .010103 -.001078 .000152 .016954 ldist | .004228 .00309 -.011188 -.002954 -.013684 .000467 .001715 .00949 .115845 lopen | .000123 -.000662 .000999 .001761 -.006097 .001336 -.000225 .000429 -.000957 english | -.001472 .00368 .003661 .004164 -.020852 .000036 .001919 -.004549 .001709 white | .001427 -.026969 .011708 -.000139 -.008544 .020629 .004188 .011532 -.138422 lwhitemg | -.00011 .001465 -.002148 -.000529 .006141 -.001327 -.000433 .000832 .011846 _cons | -.05963 .171167 11.7581 -.914415 -43.727 -.111805 .076755 -.248956 -.767927</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002404 english | -.001579 .019423 white | .003486 .01173 3.36977 lwhitemg | -.000249 -.001801 -.330643 .0337 _cons | .074487 .181096 1.29807 -.174938 425.848</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 2503.48 Log likelihood = -1092.916 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1025432 .0352133 2.91 0.004 .0335265 .17156 lgdp | .9505767 .0701557 13.55 0.000 .813074 1.088079 lgdpau | -.3934879 .8168367 -0.48 0.630 -1.994458 1.207483 lgdpdfrati~w | -.379297 .3278162 -1.16 0.247 -1.021805 .2632109 lpopau | .2876713 2.794657 0.10 0.918 -5.189755 5.765098 lpop | -.031222 .086837 -0.36 0.719 -.2014194 .1389754 lxrate1 | -.1585725 .0309876 -5.12 0.000 -.219307 -.097838 lremote | .4737102 .2178407 2.17 0.030 .0467502 .9006702 ldist | -1.42807 .2893373 -4.94 0.000 -1.995161 -.8609796 lopen | .3878395 .0718552 5.40 0.000 .247006 .528673 english | 1.719349 .2302923 7.47 0.000 1.267985 2.170714 white | 1.184611 2.210313 0.54 0.592 -3.147524 5.516745 lwhitemg | .2011762 .1936309 1.04 0.299 -.1783333 .5806858 _cons | -3.059053 26.24436 -0.12 0.907 -54.49706 48.37895 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .00124 lgdp | -.001089 .004922 lgdpau | -.001347 .00082 .667222 lgdpdfrati~w | -.000171 .001372 -.013772 .107463 lpopau | .001092 -.005494 -2.24084 .030135 7.81011 lpop | .000274 -.004473 .000781 -.000711 -.002911 .007541 lxrate1 | .000113 .000788 .000359 .001939 -.006594 -.00113 .00096 lremote | .001204 -.00033 -.025139 -.013739 .081588 .000926 -.000932 .047455 ldist | .003526 -.007339 -.017541 -.004761 .048014 .010474 -.00007 .015451 .083716 lopen | .00021 -.001139 .00453 .0023 -.022158 .002896 -.000167 .001144 -.001297 english | -.002717 -.00044 .008031 .004943 -.016305 .00013 .001513 -.014097 .008583 white | .002515 -.018686 .100843 .005013 -.388603 .014087 .000212 .040111 -.007325 lwhitemg | -.000366 .000577 -.010472 -.001781 .041695 .000023 -.000166 -.000877 .004086 _cons | -.011746 .105324 20.0473 -.104245 -71.8388 -.0954 .102972 -1.25092 -1.2897</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005163 english | -.0018 .053035 white | .006616 .04631 4.88548 lwhitemg | -.000398 -.003521 -.4176 .037493 _cons | .231977 .099343 3.69303 -.458564 688.767</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 38320.73 Log likelihood = -889.0487 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0250382 .0137297 1.82 0.068 -.0018715 .0519479 lgdp | 1.555008 .0563534 27.59 0.000 1.444557 1.665459 lgdpau | .7244896 .3688793 1.96 0.050 .0014995 1.44748 lgdpdfrati~w | -.2217896 .1382151 -1.60 0.109 -.4926862 .0491069 lpopau | -6.759 1.248681 -5.41 0.000 -9.20637 -4.311629 lpop | -.1655622 .094981 -1.74 0.081 -.3517216 .0205972 lxrate1 | -.0423303 .0184461 -2.29 0.022 -.0784839 -.0061766 lremote | -.6384091 .1489928 -4.28 0.000 -.9304296 -.3463886 ldist | -2.426248 .1833671 -13.23 0.000 -2.785641 -2.066856 lopen | -.036263 .0279564 -1.30 0.195 -.0910564 .0185305 english | 1.207036 .1183224 10.20 0.000 .9751285 1.438944 white | 3.686059 .8686556 4.24 0.000 1.983525 5.388593 lwhitemg | -.2769415 .0800426 -3.46 0.001 -.433822 -.1200609 _cons | 93.37866 11.8465 7.88 0.000 70.15994 116.5974 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000189 lgdp | -.000226 .003176 lgdpau | -.000757 .002106 .136072 lgdpdfrati~w | -.000357 .000836 -.007208 .019103 lpopau | .002545 -.007618 -.45079 .012178 1.5592 lpop | .000162 -.004992 -.002002 -.000232 .004748 .009021 lxrate1 | 7.1e-06 .00024 -1.4e-06 .000445 -.002572 -.000281 .00034 lremote | .000025 -.000883 -.014314 -.004041 .051425 .000155 -.000194 .022199 ldist | .000907 -.006014 -.004116 .00067 .00194 .011154 .000593 -.002107 .033623 lopen | .00002 -.000136 -.001053 .000976 .003689 .000351 -.000069 .001089 .000387 english | -.000295 -.000552 .003381 .002409 -.017052 .000594 .000873 -.004322 .008239 white | .000807 -.017703 -.016058 -.001353 .030662 .030543 .001815 .014032 .036832 lwhitemg | -.000105 .000803 -.000123 -.000314 .002902 -.001621 -.000212 .001127 -.002282 _cons | -.029239 .143387 4.06751 -.016978 -14.4313 -.163601 .03606 -.630351 -.276656</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000782 english | -.000442 .014 white | .001277 .0075 .754563 lwhitemg | -5.2e-06 -.000443 -.066252 .006407 _cons | -.049882 .149123 -.655286 -.024185 140.34</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 7881.39 Log likelihood = -955.3519 Prob > chi2 = 0.0000</p><p>------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2775043 .0337788 8.22 0.000 .2112991 .3437095 lgdp | 1.558189 .0730283 21.34 0.000 1.415056 1.701321 lgdpau | -.110713 .6085473 -0.18 0.856 -1.303444 1.082018 lgdpdfrati~w | -.129351 .2699425 -0.48 0.632 -.6584286 .3997265 lpopau | -1.256763 2.125208 -0.59 0.554 -5.422095 2.908569 lpop | -.4915072 .0806836 -6.09 0.000 -.6496442 -.3333701 lxrate1 | -.1384769 .0280689 -4.93 0.000 -.1934909 -.083463 lremote | -.3226908 .1212141 -2.66 0.008 -.560266 -.0851155 ldist | -2.569246 .3299241 -7.79 0.000 -3.215885 -1.922606 lopen | .1293024 .0512607 2.52 0.012 .0288334 .2297715 english | .8011592 .1383436 5.79 0.000 .5300107 1.072308 white | 9.687701 1.812693 5.34 0.000 6.134889 13.24051 lwhitemg | -.8584144 .1808298 -4.75 0.000 -1.212834 -.5039946 _cons | 26.63031 20.27208 1.31 0.189 -13.10224 66.36285 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001141 lgdp | -.001687 .005333 lgdpau | -.001481 .00231 .37033 lgdpdfrati~w | -.001446 .003319 -.025412 .072869 lpopau | .004604 -.016433 -1.25095 .094419 4.51651 lpop | .000949 -.004364 -.00043 -.002168 .005557 .00651 lxrate1 | .000087 .000362 -.000443 .001316 -.004396 -.000647 .000788 lremote | .000038 -.000342 -.003414 -.000819 .003072 -.000818 .000109 .014693 ldist | .005148 -.00075 -.011277 -.004041 -.005302 .002124 .001429 .009131 .10885 lopen | .000129 -.000729 .001846 .001799 -.010491 .001499 -.000274 .000338 -.00137 english | -.001713 .003354 .000985 .004597 -.009218 -.000131 .001831 -.004174 -.001201 white | -.000098 -.023233 .016643 .001903 -.007926 .01715 .003784 .011174 -.155572 lwhitemg | .000079 .001257 -.002218 -.000703 .004086 -.00103 -.000366 .000615 .014727 _cons | -.068258 .175753 11.1666 -.966906 -41.9449 -.098272 .067046 -.157596 -.777943</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002628 english | -.001755 .019139 white | .004114 .012488 3.28585 lwhitemg | -.000313 -.001662 -.322264 .032699 _cons | .129268 .094112 1.30308 -.165443 410.957</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 9249.22 Log likelihood = -1096.895 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0323878 .0168248 1.93 0.054 -.0005882 .0653638 lgdp | 1.354445 .0496918 27.26 0.000 1.25705 1.451839 lgdpau | .418864 .5481131 0.76 0.445 -.6554179 1.493146 lgdpdfrati~w | -.0324833 .1836591 -0.18 0.860 -.3924485 .327482 lpopau | -4.984954 1.861545 -2.68 0.007 -8.633515 -1.336392 lpop | .0786083 .0696171 1.13 0.259 -.0578386 .2150552 lxrate1 | -.0763191 .0212155 -3.60 0.000 -.1179007 -.0347375 lremote | -1.047331 .1646135 -6.36 0.000 -1.369968 -.724695 ldist | -3.494652 .212748 -16.43 0.000 -3.91163 -3.077674 lopen | .1066097 .0459811 2.32 0.020 .0164885 .196731 english | 2.348385 .1405013 16.71 0.000 2.073008 2.623763 white | 3.780045 1.151834 3.28 0.001 1.522493 6.037597 lwhitemg | -.2040738 .096415 -2.12 0.034 -.3930437 -.015104 _cons | 85.3411 17.65804 4.83 0.000 50.73197 119.9502 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000283 lgdp | -.000459 .002469 lgdpau | -.000357 .000465 .300428 lgdpdfrati~w | -.000603 .000805 .001794 .033731 lpopau | -.000802 .000729 -.998623 -.004082 3.46535 lpop | .000226 -.002654 -.000642 6.9e-07 -.00103 .004847 lxrate1 | -.000034 .000267 .000452 .000758 -.002965 -.000437 .00045 lremote | .00031 .000529 -.017769 -.002657 .055176 -.000698 -.000335 .027098 ldist | .000716 .000433 -.01216 -.002103 .027498 .000141 .000202 .017948 .045262 lopen | .000101 -.00039 -.000241 .001911 .000925 .000827 -.000135 .001185 .000418 english | -.000927 .000752 .003382 .002476 -.011353 .001258 .001244 -.004416 .002418 white | .000358 -.012783 -.003599 -.001568 .005807 .022295 -.000141 .005478 -.007694 lwhitemg | -4.8e-06 .000677 -.000916 .000171 .002981 -.001446 .000074 .001245 .002744 _cons | .019815 -.045871 8.95403 .011657 -32.0309 .021351 .036431 -.856355 -.743086</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002114 english | -.001586 .019741 white | .000915 .031157 1.32672 lwhitemg | .000021 -.002705 -.1075 .009296 _cons | -.028132 .069305 -.056104 -.054735 311.806</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 584.45 Log likelihood = -564.5788 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2594088 .0382128 6.79 0.000 .184513 .3343046 lgdp | .0372301 .0459322 0.81 0.418 -.0527954 .1272556 lgdpau | .364399 .254099 1.43 0.152 -.1336259 .8624239 lgdpdfrati~w | -.4088186 .0975014 -4.19 0.000 -.5999179 -.2177194 lpopau | -2.259273 1.030442 -2.19 0.028 -4.278901 -.2396444 lpop | .5479701 .0758038 7.23 0.000 .3993974 .6965427 lxrate1 | -.089153 .020082 -4.44 0.000 -.1285129 -.049793 lremote | .2142392 .1155808 1.85 0.064 -.012295 .4407734 ldist | -1.497148 .3735535 -4.01 0.000 -2.229299 -.7649964 lopen | .0918944 .0154302 5.96 0.000 .0616518 .122137 english | .6671696 .2113149 3.16 0.002 .253 1.081339 white | 10.64489 .6660312 15.98 0.000 9.339495 11.95029 lwhitemg | -.9718278 .0660425 -14.72 0.000 -1.101269 -.8423868 _cons | 36.52904 11.21611 3.26 0.001 14.54587 58.51221 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .00146 lgdp | -.000245 .00211 lgdpau | .003649 -.002681 .064566 lgdpdfrati~w | -.001238 -.001051 -.001917 .009507 lpopau | -.020923 .017548 -.246322 .004358 1.06181 lpop | -.000657 -.00152 -.000891 .001234 -.005943 .005746 lxrate1 | -6.7e-07 -.000033 .001176 .000713 -.006492 -.000152 .000403 lremote | .001249 .001587 -.007906 -.003889 .025994 -.001998 -.000374 .013359 ldist | .0038 -.002255 .006023 -.001354 -.081008 .01136 .000568 .007163 .139542 lopen | .000372 -.000267 .000525 -.00053 -.004386 .000066 -.00013 .000263 .000974 english | -.001688 .000559 -.002131 .002777 -.000743 .005579 .000811 -.002818 .014961 white | .003711 -.003122 .017368 .002262 -.131695 .010887 .002946 .001541 -.034715 lwhitemg | -.000578 -.000087 -.0024 .000171 .014333 -.000577 -.000264 .000058 .004336 _cons | .212752 -.236769 2.45634 .025787 -10.7763 -.022409 .075672 -.416579 -.361579</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000238 english | -.000761 .044654 white | .000192 .045273 .443598 lwhitemg | -.000038 -.002192 -.0415 .004362 _cons | .051579 -.171615 1.87607 -.199561 125.801</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 3869.61 Log likelihood = -596.4866 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1472326 .0309438 4.76 0.000 .0865839 .2078813 lgdp | .2760931 .0532696 5.18 0.000 .1716866 .3804995 lgdpau | -.1217849 .0617161 -1.97 0.048 -.2427463 -.0008234 lgdpdfrati~w | -.1400897 .0410215 -3.42 0.001 -.2204905 -.059689 lpopau | 3.12812 .2584875 12.10 0.000 2.621494 3.634746 lpop | .8013258 .1004105 7.98 0.000 .6045249 .9981268 lxrate1 | -.0155528 .0079935 -1.95 0.052 -.0312197 .0001141 lremote | .1665506 .0318558 5.23 0.000 .1041143 .228987 ldist | -3.181197 .3471863 -9.16 0.000 -3.861669 -2.500724 lopen | .0053023 .0292928 0.18 0.856 -.0521105 .0627151 english | .7776234 .2754945 2.82 0.005 .237664 1.317583 white | 25.9308 2.89995 8.94 0.000 20.247 31.6146 lwhitemg | -2.357931 .2739284 -8.61 0.000 -2.894821 -1.821042 _cons | -33.66277 5.223593 -6.44 0.000 -43.90083 -23.42472 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000958 lgdp | -.000533 .002838 lgdpau | -.000669 -.000472 .003809 lgdpdfrati~w | .000322 -.00113 .000778 .001683 lpopau | .00472 .000132 -.013254 .000261 .066816 lpop | -.000248 -.002422 .001317 .000594 -.004584 .010082 lxrate1 | 9.2e-06 .000073 -.000045 .000031 .000624 -.000227 .000064 lremote | -.000314 .001193 -.000625 -.000974 .00006 -.00079 .00003 .001015 ldist | .003437 -.000296 -.002959 .000088 .023102 -.001466 -.000094 -.000061 .120538 lopen | -.000344 -.000215 .00025 -.000404 -.004065 .001122 -.000158 .000193 -.000805 english | -.000626 .00002 .000573 .000159 -.005819 .000234 .000041 -.000152 .054353 white | .002894 -.006786 .001466 .002413 -.001573 .034058 -.000586 -.002878 .03182 lwhitemg | -.000547 .000255 .000156 -.000125 -.002265 -.003208 .000053 .000154 -.00583 _cons | -.080863 -.020921 .147252 -.004414 -.93995 -.040322 -.007005 -.004861 -1.45078</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000858 english | -.000047 .075897 white | .001701 .050574 8.40971 lwhitemg | -.000025 -.004204 -.781988 .075037 _cons | .057747 -.455581 -.721295 .137751 27.2859</p><p>. . . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 471.74 Log likelihood = -543.064 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5245192 .0490491 10.69 0.000 .4283847 .6206536 lgdp | -.015166 .0740304 -0.20 0.838 -.1602628 .1299309 lgdpau | 1.879069 .7756984 2.42 0.015 .3587282 3.39941 lgdpdfrati~w | -.5929936 .2740295 -2.16 0.030 -1.130082 -.0559056 lpopau | -9.023944 2.664402 -3.39 0.001 -14.24608 -3.801811 lpop | .3389742 .0904157 3.75 0.000 .1617626 .5161857 lxrate1 | -.1083398 .0252211 -4.30 0.000 -.1577722 -.0589074 lremote | .0148316 .2517158 0.06 0.953 -.4785222 .5081855 ldist | -1.503137 .3121672 -4.82 0.000 -2.114974 -.8913007 lopen | .0382345 .0527748 0.72 0.469 -.0652022 .1416712 english | -.14811 .2214853 -0.67 0.504 -.5822132 .2859933 white | 9.169329 1.058657 8.66 0.000 7.0944 11.24426 lwhitemg | -.8252045 .0942368 -8.76 0.000 -1.009905 -.6405039 _cons | 112.5887 25.27099 4.46 0.000 63.05851 162.119 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002406 lgdp | -.001384 .00548 lgdpau | .000521 -.00062 .601708 lgdpdfrati~w | -.001207 .001408 -.017403 .075092 lpopau | -.006609 -.004174 -2.00871 .066265 7.09904 lpop | -.000143 -.003529 -.000232 -.000661 -.001814 .008175 lxrate1 | .000148 -.000177 .0004 .00088 -.003942 -.000425 .000636 lremote | .001573 .004238 -.022377 -.011693 .063053 -.003055 .000344 .063361 ldist | .004558 .001862 -.008816 -.002425 -.011628 .003318 .000941 .029496 .097448 lopen | -.000243 .000636 .000169 -.000411 -.0089 .000722 -.000019 .001197 .002144 english | -.001815 .000847 .00391 .004263 -.018133 .000334 .000962 -.010189 .022136 white | .013876 -.023212 .014956 -.006671 -.078335 .025904 .004995 .017279 .002207 lwhitemg | -.001378 .00121 -.002736 -.00015 .014193 -.001604 -.000412 .000771 -.000044 _cons | .05616 -.02819 17.8428 -.61191 -65.4164 -.017574 .049947 -1.3347 -.885063</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002785 english | -.000244 .049056 white | -.001388 .018341 1.12075 lwhitemg | .00007 -.000789 -.095653 .008881 _cons | .090604 .03881 .700378 -.158134 638.623</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1144.32 Log likelihood = -352.0027 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0333544 .0183043 1.82 0.068 -.0025213 .0692301 lgdp | .301373 .0612132 4.92 0.000 .1813973 .4213488 lgdpau | -.3106115 .3082082 -1.01 0.314 -.9146886 .2934655 lgdpdfrati~w | -.3221096 .2018557 -1.60 0.111 -.7177395 .0735202 lpopau | 2.26888 1.099137 2.06 0.039 .1146124 4.423149 lpop | .159722 .0717846 2.23 0.026 .0190268 .3004171 lxrate1 | -.0736504 .0188209 -3.91 0.000 -.1105386 -.0367622 lremote | -.1760274 .1104051 -1.59 0.111 -.3924173 .0403626 ldist | -1.319847 .2144257 -6.16 0.000 -1.740113 -.89958 lopen | .0011121 .0253056 0.04 0.965 -.0484859 .0507101 english | 2.147451 .2192417 9.79 0.000 1.717745 2.577157 white | 9.839693 1.77481 5.54 0.000 6.361129 13.31826 lwhitemg | -.7689475 .1828046 -4.21 0.000 -1.127238 -.4106571 _cons | -23.34394 11.17648 -2.09 0.037 -45.24943 -1.438446 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000335 lgdp | -.000383 .003747 lgdpau | .000306 -.002102 .094992 lgdpdfrati~w | -.000607 .000376 -.001188 .040746 lpopau | -.001109 .005553 -.323002 .020327 1.2081 lpop | .0001 -.002803 .000974 .001027 -.009321 .005153 lxrate1 | -.000017 .000203 .001257 .000858 -.005914 -.000165 .000354 lremote | .000191 .000804 -.006906 -.003588 .025339 -.000669 -.000359 .012189 ldist | .000881 .000869 -.002 -.0015 -.001221 .002567 -.000326 .001014 .045978 lopen | .000027 -.000301 -.000096 .001034 -.000835 .00033 -.000011 -.000122 -.0001 english | -.000353 -.001765 .003577 .004552 -.018085 .00512 .000374 -.004324 .015855 white | .001667 -.02261 .01545 .003713 -.088848 .026873 .001111 .009198 -.025813 lwhitemg | -.000162 .001117 -.001132 -.000251 .007303 -.00191 -.000095 -.000289 .001226 _cons | .006301 -.090668 2.97169 -.330158 -11.75 .091308 .067363 -.357565 -.435524</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00064 english | -.000104 .048067 white | .001331 .074594 3.14995 lwhitemg | -.000056 -.007314 -.319701 .033418 _cons | .019263 .041598 1.28631 -.093304 124.914</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 749.53 Log likelihood = -841.5946 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .115374 .0652122 1.77 0.077 -.0124396 .2431876 lgdp | .7146226 .1210263 5.90 0.000 .4774154 .9518298 lgdpau | -2.19674 1.101507 -1.99 0.046 -4.355654 -.0378261 lgdpdfrati~w | -.9438566 .4413709 -2.14 0.032 -1.808928 -.0787856 lpopau | 4.166351 3.782004 1.10 0.271 -3.246241 11.57894 lpop | .160938 .124611 1.29 0.197 -.083295 .4051711 lxrate1 | -.1284781 .0403663 -3.18 0.001 -.2075946 -.0493617 lremote | 1.567336 .27858 5.63 0.000 1.021329 2.113343 ldist | -1.857342 .4918836 -3.78 0.000 -2.821416 -.8932676 lopen | .0038908 .0763369 0.05 0.959 -.1457267 .1535083 english | .5791471 .2715436 2.13 0.033 .0469314 1.111363 white | 10.96138 1.478673 7.41 0.000 8.063238 13.85953 lwhitemg | -.8808913 .1434488 -6.14 0.000 -1.162046 -.5997367 _cons | -22.55872 35.6056 -0.63 0.526 -92.34441 47.22697 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .004253 lgdp | -.004842 .014647 lgdpau | -.002355 .007755 1.21332 lgdpdfrati~w | -.001965 .005691 .000148 .194808 lpopau | .005564 -.040844 -4.05991 .045781 14.3036 lpop | .001663 -.010787 -.002993 -.002971 .014924 .015528 lxrate1 | .000037 .001882 .001143 .0017 -.010893 -.001599 .001629 lremote | .001843 -.004724 -.033853 -.021251 .092204 .003177 .00077 .077607 ldist | .012974 -.014213 -.012737 -.012005 .012523 .016027 -.002746 .023878 .241949 lopen | .000277 -.000507 .00684 .001125 -.035324 .002037 -.00035 .002661 .003812 english | -.006361 .015482 .010274 .002993 -.049239 -.01002 -.000178 -.006541 .019353 white | .0265 -.048419 -.0386 -.038074 .05272 .048003 .005061 .120978 .128698 lwhitemg | -.002886 .002375 -.000636 .000827 .013975 -.002265 -.000834 -.004344 -.016056 _cons | -.106644 .49907 35.8197 -.739781 -131.138 -.348209 .145495 -1.48518 -2.36339</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005827 english | -.000246 .073736 white | .002322 .030484 2.18647 lwhitemg | -.00015 -.005813 -.201567 .020578 _cons | .329738 .238227 -1.96957 -.021896 1267.76</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 564.13 Log likelihood = -128.4198 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0314721 .0292772 1.07 0.282 -.0259102 .0888544 lgdp | .171791 .0605257 2.84 0.005 .0531627 .2904192 lgdpau | .3807668 .4133843 0.92 0.357 -.4294517 1.190985 lgdpdfrati~w | .3612138 .1881799 1.92 0.055 -.0076119 .7300396 lpopau | 2.461914 1.460325 1.69 0.092 -.4002694 5.324098 lpop | .3040772 .0799795 3.80 0.000 .1473203 .4608342 lxrate1 | -.0314361 .0166767 -1.89 0.059 -.0641219 .0012497 lremote | -.0311103 .1294082 -0.24 0.810 -.2847458 .2225251 ldist | -2.253871 .4241343 -5.31 0.000 -3.085159 -1.422583 lopen | .0645203 .0390656 1.65 0.099 -.0120469 .1410875 english | .8908105 .1856868 4.80 0.000 .5268712 1.25475 white | 15.97369 1.216776 13.13 0.000 13.58886 18.35853 lwhitemg | -1.355064 .113581 -11.93 0.000 -1.577679 -1.132449 _cons | -37.68512 15.04473 -2.50 0.012 -67.17225 -8.197997 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000857 lgdp | -.000664 .003663 lgdpau | -.000585 -.000104 .170887 lgdpdfrati~w | -.000745 .000892 -.000414 .035412 lpopau | .001622 .001162 -.573273 .016461 2.13255 lpop | -.000115 -.002621 .000501 .000578 -.005052 .006397 lxrate1 | .00005 .000106 .000199 .000559 -.002708 -.000123 .000278 lremote | .000885 .002024 -.007655 -.003589 .022177 -.001606 .000115 .016746 ldist | .002422 -.004199 -.010484 -.00842 .002874 .008552 .000159 .017423 .17989 lopen | -.000016 -.000058 .000151 .000334 -.004499 .000564 -.000053 .000032 .000318 english | -.001264 -.00049 .003304 .002916 -.016518 .004602 .000136 -.004894 .00468 white | .004194 -.016444 .030482 -.003814 -.27814 .025374 .003565 -.005335 -.026209 lwhitemg | -.000479 .000851 -.003139 .000202 .027481 -.001928 -.000382 .000628 .003539 _cons | -.029604 -.032357 5.1897 -.214638 -20.5181 -.039101 .035103 -.498602 -1.69152</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001526 english | .000134 .03448 white | -.000427 .046712 1.48054 lwhitemg | .000059 -.004057 -.135059 .012901 _cons | .060766 .118189 4.03391 -.396963 226.344</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 260.13 Log likelihood = 134.4335 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0034291 .0195201 -0.18 0.861 -.0416877 .0348296 lgdp | .2938497 .0530992 5.53 0.000 .1897773 .3979222 lgdpau | -.3268804 .354687 -0.92 0.357 -1.022054 .3682934 lgdpdfrati~w | -.0886911 .1445418 -0.61 0.539 -.3719878 .1946056 lpopau | 4.307336 1.293908 3.33 0.001 1.771324 6.843348 lpop | -.0718548 .0620604 -1.16 0.247 -.193491 .0497813 lxrate1 | -.1005787 .0154351 -6.52 0.000 -.130831 -.0703264 lremote | .342049 .1299908 2.63 0.009 .0872718 .5968262 ldist | -1.35531 .2823321 -4.80 0.000 -1.908671 -.801949 lopen | .0309801 .0294369 1.05 0.293 -.0267152 .0886755 english | .2451819 .1692156 1.45 0.147 -.0864747 .5768385 white | 9.362131 2.063638 4.54 0.000 5.317475 13.40679 lwhitemg | -.7937476 .1971663 -4.03 0.000 -1.180187 -.4073087 _cons | -57.45412 13.72973 -4.18 0.000 -84.36389 -30.54434 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000381 lgdp | -.000403 .00282 lgdpau | .000247 -.000738 .125803 lgdpdfrati~w | -.00046 .000517 -.006125 .020892 lpopau | -.002242 .003369 -.432264 .028004 1.6742 lpop | .00003 -.002278 2.9e-06 -.000087 -.000159 .003851 lxrate1 | 5.5e-07 7.2e-06 .00051 .000487 -.004503 -.000115 .000238 lremote | .000323 .001771 -.007858 -.001229 .027512 -.001551 -.000065 .016898 ldist | .001783 -.002061 -.0023 -.001506 .003871 .004579 .000063 .007242 .079711 lopen | -.000018 .000047 .000075 .000199 -.001775 .000188 -.00003 .000079 -.000558 english | -.000467 -.001803 .000234 .000914 .018831 .004788 .000229 -.001454 .015764 white | .002573 -.015669 .018796 -.005182 -.148929 .01628 .001981 -.001005 .015301 lwhitemg | -.000287 .000954 -.0022 .000489 .015221 -.001279 -.000149 .000741 -.002383 _cons | .018246 -.057346 3.98017 -.3106 -16.7875 -.037625 .061385 -.481499 -.864998</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000867 english | -.0003 .028634 white | -.000842 .036019 4.2586 lwhitemg | .000096 -.003367 -.400249 .038875 _cons | .028616 -.496929 1.90893 -.177729 188.505 . xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 563.77 Log likelihood = -668.5284 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1651144 .0516048 3.20 0.001 .0639709 .2662579 lgdp | .7821761 .1025849 7.62 0.000 .5811133 .9832389 lgdpau | -.6495231 .6666129 -0.97 0.330 -1.95606 .6570142 lgdpdfrati~w | -.2547775 .2733009 -0.93 0.351 -.7904374 .2808823 lpopau | 4.16985 2.296307 1.82 0.069 -.3308293 8.670529 lpop | -.2285679 .1479297 -1.55 0.122 -.5185047 .0613689 lxrate1 | -.138375 .0307484 -4.50 0.000 -.1986407 -.0781093 lremote | .1414757 .2314409 0.61 0.541 -.31214 .5950914 ldist | -3.321225 .6859637 -4.84 0.000 -4.665689 -1.97676 lopen | .0351769 .0638595 0.55 0.582 -.0899855 .1603393 english | -.3232806 .4316508 -0.75 0.454 -1.169301 .5227393 white | 21.91289 4.113019 5.33 0.000 13.85152 29.97426 lwhitemg | -1.955874 .3830822 -5.11 0.000 -2.706701 -1.205047 _cons | -33.07745 22.67889 -1.46 0.145 -77.52726 11.37237 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002663 lgdp | -.002254 .010524 lgdpau | .00134 -.001615 .444373 lgdpdfrati~w | -.001681 .002912 -.01097 .074693 lpopau | -.008582 .001061 -1.47854 .060619 5.27303 lpop | -.000229 -.007527 -.001606 -.001496 -.007751 .021883 lxrate1 | .000144 .000451 .001965 .001178 -.010229 -.00076 .000945 lremote | .00098 .004567 -.020454 -.011423 .039326 -.002925 .000487 .053565 ldist | .01022 .013649 -.006774 -.003658 -.048716 .004994 .000419 .03286 .470546 lopen | .000424 -.001012 -.000813 -.000043 -.010331 .001858 -.000182 .00063 .00269 english | -.006155 .003507 .00074 .005671 -.016153 .018283 .000675 -.003048 .132536 white | .006775 -.03445 .104119 .00696 -.357719 .076997 .005971 .031324 .257135 lwhitemg | -.001182 .001409 -.011254 -.001876 .040012 -.005943 -.000648 -.000611 -.039347 _cons | .045232 -.257632 13.1709 -.698146 -48.4684 -.025809 .106057 -.950669 -4.24669</p><p>| lopen english white lwhitemg _cons ------+------lopen | .004078 english | -.001613 .186322 white | .002498 .314861 16.9169 lwhitemg | -.000108 -.033786 -1.54999 .146752 _cons | .156947 -1.37387 -.117805 .091921 514.332</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1434.06 Log likelihood = -546.1796 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1570127 .0416163 3.77 0.000 .0754463 .2385791 lgdp | .863445 .0971554 8.89 0.000 .673024 1.053866 lgdpau | .7860883 .6074044 1.29 0.196 -.4044025 1.976579 lgdpdfrati~w | -.0819898 .260177 -0.32 0.753 -.5919275 .4279478 lpopau | -3.997618 2.096208 -1.91 0.057 -8.10611 .1108734 lpop | .4301801 .1283917 3.35 0.001 .178537 .6818231 lxrate1 | -.0824566 .0281266 -2.93 0.003 -.1375838 -.0273294 lremote | -.1979357 .2156999 -0.92 0.359 -.6206998 .2248283 ldist | -2.165012 .4220219 -5.13 0.000 -2.992159 -1.337864 lopen | -.0647749 .0659007 -0.98 0.326 -.1939378 .0643881 english | 1.23837 .3125406 3.96 0.000 .6258013 1.850938 white | 22.97872 3.130716 7.34 0.000 16.84263 29.11482 lwhitemg | -2.270737 .2765304 -8.21 0.000 -2.812727 -1.728748 _cons | 44.8502 20.22831 2.22 0.027 5.203444 84.49695 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001732 lgdp | -.001631 .009439 lgdpau | -.001825 .003993 .36894 lgdpdfrati~w | -.001403 .001931 -.005554 .067692 lpopau | .005839 -.029651 -1.23024 .021446 4.39409 lpop | .000346 -.007968 -.002921 -.001812 .011931 .016484 lxrate1 | .000048 .000516 .000521 .001137 -.004819 -.000764 .000791 lremote | .000415 .003012 -.019238 -.015385 .047253 -.002344 .000418 .046526 ldist | .006122 -.002024 -.008181 -.001952 -.001072 .016946 .000344 .005893 .178102 lopen | .000202 -.000046 -7.0e-06 .002089 -.009905 .001306 -.000108 .000978 .00159 english | -.003022 .003101 .006225 .005272 -.028127 -.0016 .00079 -.006988 .055546 white | .004943 -.032962 .019992 -.006178 -.019114 .056595 .003592 .020187 .042568 lwhitemg | -.000703 .001083 -.003474 -.000643 .011081 -.003993 -.000343 .000673 -.007717 _cons | -.086581 .298528 10.943 -.134101 -40.5891 -.341746 .055866 -.759654 -1.7754</p><p>| lopen english white lwhitemg _cons ------+------lopen | .004343 english | -.001633 .097682 white | .003873 .004346 9.80139 lwhitemg | -.000441 .000817 -.85088 .076469 _cons | .120949 -.225635 -.998709 .019681 409.184</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1316.20 Log likelihood = -757.9207 Prob > chi2 = 0.0000 ------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0280436 .0339798 0.83 0.409 -.0385556 .0946428 lgdp | 1.133678 .0986977 11.49 0.000 .9402345 1.327122 lgdpau | .9445358 .6883784 1.37 0.170 -.4046611 2.293733 lgdpdfrati~w | -.0329979 .2713651 -0.12 0.903 -.5648637 .4988678 lpopau | 2.443087 2.415357 1.01 0.312 -2.290925 7.177099 lpop | -.290504 .1566031 -1.86 0.064 -.5974405 .0164324 lxrate1 | -.1449933 .0223285 -6.49 0.000 -.1887564 -.1012301 lremote | -.4842136 .1910654 -2.53 0.011 -.858695 -.1097323 ldist | -1.881225 .7249119 -2.60 0.009 -3.302027 -.4604241 lopen | -.0446288 .0724865 -0.62 0.538 -.1866998 .0974421 english | .4136591 .3409878 1.21 0.225 -.2546646 1.081983 white | 29.15519 2.667369 10.93 0.000 23.92725 34.38314 lwhitemg | -2.750922 .2589445 -10.62 0.000 -3.258444 -2.2434 _cons | -61.42955 24.28286 -2.53 0.011 -109.0231 -13.83602 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001155 lgdp | -.002027 .009741 lgdpau | -.000286 .001194 .473865 lgdpdfrati~w | -.002149 .004622 -.014723 .073639 lpopau | -.003045 -.016752 -1.58502 .04826 5.83395 lpop | .000928 -.009294 -.002363 -.001454 .006309 .024525 lxrate1 | .000027 .000373 .000616 .000807 -.009389 -.000569 .000499 lremote | .001496 .003193 -.018094 -.004478 .026229 -.005148 .00028 .036506 ldist | .006802 .011342 -.024878 -.004627 -.037853 .003701 .001235 .064653 .525497 lopen | .000189 -.000565 -.000834 .005081 -.007741 .001869 -.000316 .000781 .000692 english | -.001825 .004631 .003675 .005112 -.030383 .00585 .000985 -.001045 .059174 white | .013364 -.047818 .031643 -.021658 -.430949 .087045 .008737 .028115 .073682</p><p> lwhitemg | -.001127 .002876 -.004493 .001291 .050232 -.007135 -.00087 -.001614 -.013963 _cons | .007961 .040186 14.2803 -.477604 -54.8012 -.21226 .122732 -.891114 -4.66151</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005254 english | -.000772 .116273 white | -.004536 .229937 7.11486 lwhitemg | .000598 -.025776 -.680295 .067052 _cons | .118981 -.357759 4.97091 -.510491 589.657</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 593.14 Log likelihood = -571.2229 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3999803 .058233 6.87 0.000 .2858457 .5141149 lgdp | .3461346 .10084 3.43 0.001 .1484919 .5437773 lgdpau | 1.197142 .7470904 1.60 0.109 -.2671282 2.661412 lgdpdfrati~w | -.5491809 .3179898 -1.73 0.084 -1.172429 .0740676 lpopau | -4.653993 2.578316 -1.81 0.071 -9.707399 .3994127 lpop | .3219479 .1063088 3.03 0.002 .1135865 .5303094 lxrate1 | -.086923 .0342503 -2.54 0.011 -.1540523 -.0197937 lremote | .0284394 .2272612 0.13 0.900 -.4169844 .4738631 ldist | -1.42703 .5818598 -2.45 0.014 -2.567455 -.2866062 lopen | .107202 .0728688 1.47 0.141 -.0356183 .2500222 english | -.0800686 .2810816 -0.28 0.776 -.6309783 .4708411 white | 19.06069 2.060662 9.25 0.000 15.02187 23.09951 lwhitemg | -1.807587 .1976345 -9.15 0.000 -2.194944 -1.420231 _cons | 48.9915 24.40968 2.01 0.045 1.149418 96.83359 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .003391 lgdp | -.003325 .010169 lgdpau | -.002105 .006147 .558144 lgdpdfrati~w | -.002425 .005788 -.01137 .101117 lpopau | .004311 -.032991 -1.86606 .057351 6.64771 lpop | .001238 -.006707 -.00421 -.004318 .010555 .011302 lxrate1 | .00034 .000484 -.000311 .000813 -.003342 -.000654 .001173 lremote | .000188 .002629 -.009641 -.017466 -.001811 .001213 .001525 .051648 ldist | .011107 .000184 -.005452 -.011394 -.068042 .007176 .000627 .036665 .338561 lopen | -.000175 .000495 .0021 .000111 -.022674 .001828 -.00022 .002207 .00318 english | -.003819 .007945 .005982 .002293 -.026314 -.001341 -.001584 .007335 .092398 white | .022981 -.039216 -.001582 -.069966 .062144 .014184 -.001283 .110427 .213784 lwhitemg | -.002573 .002128 -.00172 .004138 .004808 -.000187 -.00021 -.007582 -.030637 _cons | -.087167 .249622 16.4025 -.5432 -60.2008 -.1729 .038663 -.589543 -2.45346</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00531 english | -.000393 .079007 white | -.007246 .135278 4.24633 lwhitemg | .000698 -.016427 -.398266 .039059 _cons | .237265 -.811754 -3.45289 .295018 595.832</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1541.63 Log likelihood = -273.8507 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0011472 .0243965 0.05 0.962 -.046669 .0489634 lgdp | .4757183 .0848026 5.61 0.000 .3095083 .6419284 lgdpau | -.4408496 .4973185 -0.89 0.375 -1.415576 .5338768 lgdpdfrati~w | .189897 .2295308 0.83 0.408 -.2599752 .6397692 lpopau | 1.647135 1.712731 0.96 0.336 -1.709756 5.004026 lpop | -.271799 .1174157 -2.31 0.021 -.5019296 -.0416684 lxrate1 | -.0429294 .0230896 -1.86 0.063 -.0881842 .0023253 lremote | -.0134964 .1703062 -0.08 0.937 -.3472904 .3202977 ldist | -3.807789 .5103731 -7.46 0.000 -4.808102 -2.807476 lopen | .0044683 .0511567 0.09 0.930 -.095797 .1047335 english | .0070483 .2848279 0.02 0.980 -.5512041 .5653007 white | 16.1919 2.614226 6.19 0.000 11.06811 21.31569 lwhitemg | -1.197204 .2806062 -4.27 0.000 -1.747182 -.6472256 _cons | 15.54585 17.13982 0.91 0.364 -18.04759 49.13929 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000595 lgdp | -.000782 .007191 lgdpau | .000208 -.002988 .247326 lgdpdfrati~w | -.00104 .002936 -.010524 .052684 lpopau | -.001495 .00371 -.824352 .054644 2.93345 lpop | .000257 -.006578 .000757 -.001099 -.005216 .013786 lxrate1 | -.000032 .000195 .001391 .001085 -.006557 -.000534 .000533 lremote | .000141 .002464 -.017483 -.003743 .051142 -.002934 -.000135 .029004 ldist | .002392 .003424 -.011714 -.001002 -.010767 .018062 -.000337 .013583 .260481 lopen | .000048 -.000196 -.002264 .001629 .002671 .000926 -.000026 .000012 .000976 english | -.001267 .001102 .001261 .002463 -.002416 .00362 .000586 .000037 .053343 white | .004487 -.038905 .046918 -.015538 -.282191 .062811 .001944 -.002567 .14858 lwhitemg | -.000469 .001642 -.005239 .0007 .033025 -.004909 -.000017 .002705 -.019211 _cons | .007215 -.092624 7.5081 -.690406 -27.416 -.148171 .077282 -.779517 -2.50792</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002617 english | .000268 .081127 white | -.000419 .097536 6.83418 lwhitemg | .000107 -.010003 -.723396 .07874 _cons | -.004939 -.59545 1.90526 -.20861 293.774</p><p>. . . clear</p><p>. insheet using k:\book1.txt (104 vars, 1010 obs)</p><p>. *Dropping Cote de Ivore . drop if ccode==163840 (10 observations deleted)</p><p>. . . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist open english gdpdfration > ew white whitemg, stat(n mean sd median min max) col(stat) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 491153.1 1561197 8397.5 0 1.39e+07 immig | 1000 33461.61 117038.7 2986.5 0 1137050 gdp | 1000 2.79e+11 9.69e+11 1.74e+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 105.7676 16.89278 103.0148 60.87417 207.3465 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.95e+07 1.54e+08 1.02e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1039.919 10901.96 13.89535 .0068 270182.6 remote | 1000 6728.384 4145.027 6764 1293 39620 dist | 1000 13344.76 3523.66 14215 2409 17972 open | 1000 .7080601 .3899473 .63155 .0671 3.2192 english | 1000 .38 .4856293 0 0 1 gdpdfratio~w | 1000 1.053192 .1810264 1.019883 .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" countries)--RHS Variables > : . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist phone open eng > lish 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 404895.7 1597589 3015.5 0 1.39e+07 immig | 870 14896.5 27125.34 1606 0 158613 gdp | 870 2.37e+11 1.00e+12 1.05e+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 | 870 104.9053 17.25217 101.7941 60.87417 207.3465 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.34e+07 1.65e+08 1.03e+07 41000 1.26e+09 popau | 870 1.82e+07 612839.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 870 1179.316 11682.05 19.96485 .0068 270182.6 remote | 870 7153.117 4116.418 6927 1293 39620 dist | 870 13171.45 3410.135 14040 2410 17972 phone | 870 159.1842 241.925 49.84 .54 1449.75 open | 870 .7154501 .4114612 .6248 .0671 3.2192 english | 870 .3908046 .4882114 0 0 1 gdpdfratio~w | 870 1.044857 .1859403 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 lremote 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) = 9776.93 Log likelihood = -549.365 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3664529 .0309534 11.84 0.000 .3057853 .4271204 lgdp | 1.196314 .0330718 36.17 0.000 1.131494 1.261133 lgdpau | -.0135534 .6079785 -0.02 0.982 -1.205169 1.178063 lgdpdfrati~w | -.8930753 .2502681 -3.57 0.000 -1.383592 -.4025588 lpopau | -1.975976 2.098007 -0.94 0.346 -6.087995 2.136043 lpop | .0034818 .0417197 0.08 0.933 -.0782873 .0852508 lxrate1 | -.1292821 .0173264 -7.46 0.000 -.1632412 -.095323 lremote | -.4434918 .0747275 -5.93 0.000 -.589955 -.2970286 ldist | -2.045045 .1542984 -13.25 0.000 -2.347465 -1.742626 lopen | .2500706 .0559284 4.47 0.000 .1404529 .3596882 english | .9379268 .1273008 7.37 0.000 .6884218 1.187432 white | 4.87116 .5657607 8.61 0.000 3.762289 5.980031 lwhitemg | -.4573193 .0508141 -9.00 0.000 -.5569131 -.3577254 _cons | 34.76761 19.31964 1.80 0.072 -3.098175 72.6334 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000958 lgdp | -.000346 .001094 lgdpau | -.000913 .001423 .369638 lgdpdfrati~w | -.000826 .000129 -.008952 .062634 lpopau | .002091 -.008295 -1.25062 .050269 4.40163 lpop | -.000131 -.000722 .000173 .000228 -.000553 .001741 lxrate1 | .000097 .000144 .000429 .000158 -.002733 -.000115 .0003 lremote | .000477 .000052 -.000354 -.001884 -.003406 -.00023 .000064 .005584 ldist | .001637 .000868 .001004 -.001241 -.014943 .00004 .001457 .005077 .023808 lopen | -.000225 .000622 .002625 .000618 -.017379 .000435 .00018 .001337 .001157 english | -.001327 .00277 .003146 .002513 -.011678 -.001191 .000566 -.00339 .001888 white | .004367 -.00162 .003133 -.009107 -.024619 .005508 -.000274 -.001007 .001567 lwhitemg | -.000542 .00016 -.000271 .000844 .002578 -.000456 .000012 .000183 -.000654 _cons | -.026726 .077922 11.0212 -.638567 -39.91 -.002808 .016352 -.027093 -.082917</p><p>| lopen english white lwhitemg _cons ------+------lopen | .003128 english | -.000674 .016205 white | -.000299 .003404 .320085 lwhitemg | -.000046 -.000089 -.028287 .002582 _cons | .178045 .072608 .232989 -.023302 373.248 . . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 71240.44 Log likelihood = -986.2249 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0457391 .0136964 3.34 0.001 .0188947 .0725836 lgdp | 1.617858 .0492426 32.85 0.000 1.521344 1.714371 lgdpau | .9752246 .3506134 2.78 0.005 .2880349 1.662414 lgdpdfrati~w | -.4415212 .1468679 -3.01 0.003 -.7293769 -.1536655 lpopau | -6.717916 1.185354 -5.67 0.000 -9.041167 -4.394664 lpop | -.3595462 .0819893 -4.39 0.000 -.5202423 -.1988501 lxrate1 | -.1188738 .0203621 -5.84 0.000 -.1587827 -.0789649 lremote | -.9905145 .0869162 -11.40 0.000 -1.160867 -.8201618 ldist | -3.263766 .1482926 -22.01 0.000 -3.554415 -2.973118 lopen | -.0605769 .0264192 -2.29 0.022 -.1123576 -.0087961 english | 1.018074 .0856826 11.88 0.000 .8501388 1.186009 white | 4.759102 .7380643 6.45 0.000 3.312523 6.205681 lwhitemg | -.4730298 .0706867 -6.69 0.000 -.6115733 -.3344864 _cons | 99.32734 11.1382 8.92 0.000 77.49687 121.1578 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000188 lgdp | -.000239 .002425 lgdpau | -.001259 .001588 .12293 lgdpdfrati~w | -.000616 .000325 -.011839 .02157 lpopau | .005069 -.006475 -.406436 .023801 1.40506 lpop | .000118 -.003793 -.001095 .000799 .002449 .006722 lxrate1 | -.000036 .000276 -.000026 .000418 -.003252 -.000292 .000415 lremote | .000476 .000653 -.005949 -.003116 .021397 -.001694 .00009 .007554 ldist | .000587 -.000626 -.005916 -.001643 .01545 .00084 .000542 .00387 .021991 lopen | .000051 -.00009 -.000996 .000887 .003739 .000232 -.000076 .000561 .000155 english | -.000448 .000243 .003126 .002729 -.020824 .000367 .001143 -.002572 .001848 white | .001101 -.010747 -.009841 -.00363 .038564 .015848 -.000688 .005865 -.035402 lwhitemg | -.000087 .000553 .000507 .00028 -.002976 -.000706 .000121 -.000198 .004232 _cons | -.057495 .070421 3.62429 -.079556 -12.9112 -.024518 .045275 -.289973 -.350675</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000698 english | -.00042 .007342 white | .001627 -.002415 .544739 lwhitemg | -.000132 .000482 -.050954 .004997 _cons | -.044545 .251778 -.092039 -.005185 124.059</p><p>. . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 7901.27 Log likelihood = -921.1399 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1289637 .0254043 5.08 0.000 .0791721 .1787553 lgdp | 1.752825 .0697381 25.13 0.000 1.616141 1.889509 lgdpau | .0875716 .5759672 0.15 0.879 -1.041303 1.216447 lgdpdfrati~w | -.3818752 .2335095 -1.64 0.102 -.8395454 .0757949 lpopau | -2.840297 2.012793 -1.41 0.158 -6.7853 1.104705 lpop | -.6248885 .0823791 -7.59 0.000 -.7863486 -.4634283 lxrate1 | -.1509317 .0272966 -5.53 0.000 -.2044319 -.0974314 lremote | -.3987688 .1298999 -3.07 0.002 -.653368 -.1441696 ldist | -3.726724 .3349145 -11.13 0.000 -4.383144 -3.070304 lopen | .0835486 .0456088 1.83 0.067 -.0058429 .1729402 english | 1.022919 .1446038 7.07 0.000 .7395007 1.306337 white | 9.668089 1.813232 5.33 0.000 6.114219 13.22196 lwhitemg | -.8473526 .1808257 -4.69 0.000 -1.201764 -.4929406 _cons | 58.24981 19.19814 3.03 0.002 20.62215 95.87746 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000645 lgdp | -.001002 .004863 lgdpau | -.001757 .003362 .331738 lgdpdfrati~w | -.000942 .002577 -.019163 .054527 lpopau | .004764 -.017199 -1.12428 .071176 4.05134 lpop | .000693 -.004191 -.001093 -.002559 .002355 .006786 lxrate1 | .000043 .000464 -.000026 .001065 -.004957 -.000753 .000745 lremote | -.000046 -.000196 -.006629 -.000567 .018795 -.001219 .000133 .016874 ldist | .002865 .005589 -.011869 -.001474 -.006867 -.000652 .001417 .009218 .112168 lopen | .000111 -.000656 .00069 .002023 -.002685 .001203 -.000232 .000505 -.000844 english | -.001072 .002785 .005844 .000691 -.042288 .002075 .001746 -.004808 .003067 white | .001245 -.028169 .01216 -.006276 -.040152 .024308 .003752 .009948 -.143405 lwhitemg | -.000104 .001559 -.002151 .000102 .008679 -.001604 -.000396 .000898 .011968 _cons | -.050258 .103995 10.0902 -.730172 -37.5642 -.004985 .065375 -.350964 -.858443</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00208 english | -.001515 .02091 white | .003011 .020323 3.28781 lwhitemg | -.000187 -.00252 -.32164 .032698 _cons | .025589 .459 1.84894 -.217161 368.568</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 2167.71 Log likelihood = -1131.242 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0873765 .0427434 2.04 0.041 .0036008 .1711521 lgdp | .9574404 .0827431 11.57 0.000 .795267 1.119614 lgdpau | -.463302 .8896144 -0.52 0.603 -2.206914 1.28031 lgdpdfrati~w | -.4243363 .3835944 -1.11 0.269 -1.176167 .3274948 lpopau | .0401554 3.05601 0.01 0.990 -5.949515 6.029825 lpop | .0835811 .1020268 0.82 0.413 -.1163877 .2835499 lxrate1 | -.1227659 .034939 -3.51 0.000 -.1912451 -.0542867 lremote | .6085902 .237208 2.57 0.010 .143671 1.073509 ldist | -1.686396 .3506274 -4.81 0.000 -2.373613 -.9991794 lopen | .349265 .0832493 4.20 0.000 .1860993 .5124307 english | 1.570587 .2421439 6.49 0.000 1.095993 2.04518 white | 1.811885 2.233751 0.81 0.417 -2.566186 6.189955 lwhitemg | .1603009 .1966257 0.82 0.415 -.2250785 .5456802 _cons | 2.220441 29.08163 0.08 0.939 -54.7785 59.21938 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001827 lgdp | -.00175 .006846 lgdpau | -.001971 .002129 .791414 lgdpdfrati~w | -.000665 .001299 -.009272 .147145 lpopau | .004262 -.012939 -2.65419 .036981 9.3392 lpop | .000371 -.006108 -.000423 .00005 .001311 .010409 lxrate1 | .000094 .001032 .000825 .001843 -.009198 -.001255 .001221 lremote | .001242 .000667 -.028202 -.015826 .088298 .000733 -.000834 .056268 ldist | .004521 -.007266 -.020923 -.007653 .069383 .011036 -.000356 .021601 .12294 lopen | .000281 -.001152 .0062 .004224 -.033028 .002999 -.000219 .001967 -.00069 english | -.003847 .001985 .010234 .006827 -.021425 -.001637 .001618 -.014953 .01393 white | .003631 -.024292 .115684 .008705 -.467277 .02247 .000406 .039575 -.036377 lwhitemg | -.000538 .000953 -.012105 -.002145 .050338 -.00032 -.000193 -.000459 .007083 _cons | -.046611 .169825 23.6919 -.3398 -86.5583 -.147131 .131624 -1.43428 -1.99661</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00693 english | -.001984 .058634 white | .006768 .033563 4.98964 lwhitemg | -.000403 -.002387 -.428059 .038662 _cons | .353622 .05668 4.87568 -.593334 845.741</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 57160.32 Log likelihood = -924.2747 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0229903 .0148353 1.55 0.121 -.0060864 .052067 lgdp | 1.715505 .0492965 34.80 0.000 1.618885 1.812124 lgdpau | .8260177 .3731617 2.21 0.027 .0946342 1.557401 lgdpdfrati~w | -.2086071 .1175603 -1.77 0.076 -.4390211 .0218068 lpopau | -7.009096 1.258959 -5.57 0.000 -9.476611 -4.541581 lpop | -.4594871 .0842432 -5.45 0.000 -.6246008 -.2943734 lxrate1 | -.0349038 .0165694 -2.11 0.035 -.0673792 -.0024283 lremote | -.6066407 .1412399 -4.30 0.000 -.8834658 -.3298155 ldist | -2.755267 .1563116 -17.63 0.000 -3.061632 -2.448902 lopen | -.0246816 .0295517 -0.84 0.404 -.0826019 .0332387 english | 1.193891 .1061521 11.25 0.000 .9858368 1.401946 white | 2.892776 .9183538 3.15 0.002 1.092835 4.692716 lwhitemg | -.2379352 .0863359 -2.76 0.006 -.4071505 -.0687199 _cons | 98.71287 11.85974 8.32 0.000 75.46821 121.9575 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .00022 lgdp | -.000214 .00243 lgdpau | -.000777 .001882 .13925 lgdpdfrati~w | -.0002 .000423 -.00405 .01382 lpopau | .002208 -.005932 -.460357 .006067 1.58498 lpop | .000096 -.003872 -.001412 .000025 .002956 .007097 lxrate1 | .000016 .000162 -.000256 .000369 -.001071 -.000225 .000275 lremote | .000073 -.000752 -.015734 -.000091 .05219 .000189 .000104 .019949 ldist | .000952 -.00475 -.003616 .00091 .002347 .00798 .000481 -.000976 .024433 lopen | 8.1e-06 -.000099 -.000337 .001143 .001043 .000345 -.000061 .001145 .000335 english | -.000345 -.000243 .003259 .001366 -.014393 .000068 .000709 -.003625 .004899 white | .00061 -.013324 -.019129 .001443 .049184 .022037 .001096 .018633 .023949 lwhitemg | -.0001 .000601 2.8e-06 -.000142 .001148 -.001053 -.000095 .000479 -.001279 _cons | -.023472 .107527 4.1443 -.025768 -14.6264 -.114157 .017384 -.605322 -.196499</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000873 english | -.000497 .011268 white | .001583 .005764 .843374 lwhitemg | -.000036 -.000339 -.076313 .007454 _cons | -.025579 .137593 -.763182 -.00718 140.653</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 8401.21 Log likelihood = -947.6247 Prob > chi2 = 0.0000</p><p>------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .139637 .0263144 5.31 0.000 .0880616 .1912123 lgdp | 1.740995 .0668487 26.04 0.000 1.609974 1.872016 lgdpau | -.0738769 .5653931 -0.13 0.896 -1.182027 1.034273 lgdpdfrati~w | -.2982797 .2369539 -1.26 0.208 -.7627007 .1661413 lpopau | -1.820599 1.973775 -0.92 0.356 -5.689127 2.047929 lpop | -.570006 .0806911 -7.06 0.000 -.7281577 -.4118543 lxrate1 | -.1330261 .027102 -4.91 0.000 -.186145 -.0799072 lremote | -.3878014 .1243213 -3.12 0.002 -.6314668 -.1441361 ldist | -3.511898 .3205264 -10.96 0.000 -4.140118 -2.883677 lopen | .0868646 .0457882 1.90 0.058 -.0028786 .1766077 english | 1.184646 .1468926 8.06 0.000 .8967417 1.47255 white | 10.53344 1.817261 5.80 0.000 6.971672 14.09521 lwhitemg | -.9394598 .1811616 -5.19 0.000 -1.29453 -.5843897 _cons | 42.49058 18.77493 2.26 0.024 5.692393 79.28878 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000692 lgdp | -.001033 .004469 lgdpau | -.001837 .003408 .319669 lgdpdfrati~w | -.001047 .002245 -.018563 .056147 lpopau | .005096 -.01746 -1.08323 .068979 3.89579 lpop | .000643 -.003968 -.001638 -.001451 .007565 .006511 lxrate1 | .000036 .000391 -.000024 .001068 -.00493 -.000649 .000735 lremote | 7.0e-06 -.000264 -.005198 -.000995 .011624 -.001022 .000078 .015456 ldist | .003147 .003123 -.012141 -.00317 -.005169 .000222 .001074 .009161 .102737 lopen | .000127 -.000698 .00094 .001764 -.004026 .001244 -.000261 .00046 -.000811 english | -.001315 .002563 .003992 .003596 -.026561 .002031 .001893 -.004739 -.001084 white | -.000108 -.024989 .010901 .002402 -.005196 .021741 .004194 .009642 -.153701 lwhitemg | .000027 .001413 -.001889 -.000582 .004525 -.001396 -.000412 .000772 .013829 _cons | -.055352 .137282 9.72383 -.702148 -36.0938 -.089404 .068615 -.257261 -.745086</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002097 english | -.001673 .021577 white | .002779 .026334 3.30244 lwhitemg | -.000168 -.002878 -.32359 .03282 _cons | .042082 .287384 1.36379 -.17118 352.498</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 8213.45 Log likelihood = -1132.995 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .013588 .0153932 0.88 0.377 -.016582 .0437581 lgdp | 1.408814 .0496263 28.39 0.000 1.311549 1.50608 lgdpau | .6778166 .514812 1.32 0.188 -.3311964 1.68683 lgdpdfrati~w | -.0933494 .1708284 -0.55 0.585 -.428167 .2414682 lpopau | -6.016554 1.751378 -3.44 0.001 -9.449192 -2.583917 lpop | .0200596 .0731816 0.27 0.784 -.1233737 .1634928 lxrate1 | -.0618903 .0201358 -3.07 0.002 -.1013557 -.022425 lremote | -.9287355 .1587261 -5.85 0.000 -1.239833 -.6176382 ldist | -3.40279 .2145546 -15.86 0.000 -3.82331 -2.982271 lopen | .0650721 .0422671 1.54 0.124 -.01777 .1479141 english | 2.395512 .1370821 17.48 0.000 2.126836 2.664188 white | 3.590798 1.16112 3.09 0.002 1.315044 5.866551 lwhitemg | -.1791436 .0978133 -1.83 0.067 -.3708542 .0125669 _cons | 93.52617 16.72189 5.59 0.000 60.75186 126.3005 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000237 lgdp | -.000396 .002463 lgdpau | -.00002 .000268 .265031 lgdpdfrati~w | -.000497 .000471 .003398 .029182 lpopau | -.001431 .000843 -.880575 -.008879 3.06732 lpop | .000187 -.002847 -.00062 .000433 -.000982 .005356 lxrate1 | -.000019 .000225 .000475 .000547 -.002789 -.000421 .000405 lremote | .000149 .000371 -.01732 -.000732 .055339 -.000654 -.000267 .025194 ldist | .000524 .000139 -.010477 -.001146 .022431 .00095 .000226 .015492 .046034 lopen | .00005 -.000324 .000051 .002476 .000285 .00075 -.00014 .001004 .000162 english | -.000727 .00062 .002173 .001294 -.009555 .001709 .001077 -.00378 .003183 white | .000379 -.013112 -.00611 -.000117 .013224 .02412 -.000188 .006637 -.006766 lwhitemg | -.000013 .000664 -.000778 .000173 .002738 -.001534 .000076 .001174 .002687 _cons | .02377 -.034987 7.9061 .029238 -28.476 .007703 .033123 -.830052 -.696458</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001787 english | -.001331 .018792 white | .000957 .032228 1.3482 lwhitemg | 3.5e-06 -.002837 -.109834 .009567 _cons | -.021976 .055236 -.155912 -.051354 279.622</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 790.40 Log likelihood = -604.4136 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4438439 .0483086 9.19 0.000 .3491609 .538527 lgdp | .1772667 .0797191 2.22 0.026 .02102 .3335133 lgdpau | -.1689036 .736924 -0.23 0.819 -1.613248 1.275441 lgdpdfrati~w | -.6860996 .2728228 -2.51 0.012 -1.220822 -.1513768 lpopau | -1.468594 2.51844 -0.58 0.560 -6.404646 3.467457 lpop | .3319519 .0901429 3.68 0.000 .1552752 .5086287 lxrate1 | -.1799031 .0243985 -7.37 0.000 -.2277231 -.132083 lremote | .1563052 .2170273 0.72 0.471 -.2690604 .5816708</p><p> ldist | -1.657941 .4371636 -3.79 0.000 -2.514766 -.8011159 lopen | .1052178 .0580036 1.81 0.070 -.0084672 .2189029 english | .6283076 .2080222 3.02 0.003 .2205916 1.036024 white | 10.64208 .7223034 14.73 0.000 9.22639 12.05777 lwhitemg | -1.035365 .0717247 -14.44 0.000 -1.175943 -.894787 _cons | 38.71876 23.78811 1.63 0.104 -7.905068 85.34259 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002334 lgdp | -.001811 .006355 lgdpau | -.00098 -.001095 .543057 lgdpdfrati~w | -.002002 .001706 -.013278 .074432 lpopau | .001129 -.005515 -1.80279 .060882 6.34254 lpop | -.000134 -.004136 .000649 -.000816 -.000039 .008126 lxrate1 | .000137 .000293 .000453 .001112 -.004535 -.00065 .000595 lremote | .004374 .00506 -.01448 -.009404 .014749 -.004906 .000096 .047101 ldist | .007086 -.006845 -.017666 -.007594 -.011368 .013424 .00123 .047706 .191112 lopen | -.000163 .00043 -.001015 -.001136 -.007805 .000566 -.000036 .001706 .000704 english | -.002366 .001216 .001233 .005425 -.012162 .005396 .001539 -.001269 .012147 white | .012834 -.012168 .011842 -.004887 -.058957 .014193 .004017 .011589 -.000962 lwhitemg | -.000977 .000324 -.001672 .000041 .007 -.000572 -.000398 -.000097 .004961 _cons | -.069203 .069483 15.9842 -.6038 -57.8894 -.132794 .0496 -.786445 -1.68742</p><p>| lopen english white lwhitemg _cons ------+------lopen | .003364 english | -.001045 .043273 white | -.000288 .051985 .521722 lwhitemg | .000038 -.002754 -.049024 .005144 _cons | .120975 -.070173 .491319 -.106556 565.874</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 2157.28 Log likelihood = -610.9289 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1721795 .0404534 4.26 0.000 .0928922 .2514667 lgdp | .3535981 .0658867 5.37 0.000 .2244625 .4827336 lgdpau | -.1649445 .1052047 -1.57 0.117 -.371142 .041253 lgdpdfrati~w | -.1656767 .0654607 -2.53 0.011 -.2939774 -.0373761 lpopau | 2.666923 .3989908 6.68 0.000 1.884915 3.448931 lpop | .6855635 .1025953 6.68 0.000 .4844804 .8866466 lxrate1 | -.0232626 .0129192 -1.80 0.072 -.0485839 .0020586 lremote | .1663699 .0480168 3.46 0.001 .0722587 .260481 ldist | -3.242194 .361243 -8.98 0.000 -3.950217 -2.534171 lopen | -.0169975 .0436277 -0.39 0.697 -.1025062 .0685112 english | .6576954 .2784334 2.36 0.018 .1119759 1.203415 white | 23.93384 2.958105 8.09 0.000 18.13606 29.73162 lwhitemg | -2.263548 .2742096 -8.25 0.000 -2.800989 -1.726107 _cons | -24.54274 6.146003 -3.99 0.000 -36.58868 -12.49679 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001636 lgdp | -.001211 .004341 lgdpau | -.001143 -.000183 .011068 lgdpdfrati~w | .000541 -.001553 .002078 .004285 lpopau | .007257 -.001855 -.03651 -.000588 .159194 lpop | -.000044 -.002807 .001171 .000461 -.006023 .010526 lxrate1 | -5.8e-06 .000144 -.000097 .000049 .001365 -.000361 .000167 lremote | -.000578 .001772 -.001578 -.002099 .00066 -.000876 .0001 .002306 ldist | .00539 -.000923 -.005007 -.000332 .028418 -.002171 -.000359 .000088 .130497 lopen | -.000449 -.000355 .000209 -.000989 -.007709 .001601 -.00035 .000516 -.000455 english | -.000655 -.001149 .001038 .000967 -.005597 .001082 .000093 -.000856 .056605 white | .006402 -.009197 .00003 .003368 .002648 .03014 -.000867 -.00392 .016881 lwhitemg | -.000921 .0003 .000294 -.000208 -.002645 -.003038 .000089 .00025 -.005011 _cons | -.119368 -.018709 .368002 -.00361 -1.87078 -.003861 -.015901 -.01139 -1.56532</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001903 english | -.000427 .077525 white | .001887 .033919 8.75039 lwhitemg | -7.9e-06 -.001924 -.798592 .075191 _cons | .111667 -.478418 -.509791 .130402 37.7734</p><p>. . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 637.98 Log likelihood = -563.0368 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5851823 .0486551 12.03 0.000 .4898201 .6805445 lgdp | -.0654265 .0722238 -0.91 0.365 -.2069826 .0761295 lgdpau | 2.140024 .8005474 2.67 0.008 .5709801 3.709068 lgdpdfrati~w | -.7523261 .2895122 -2.60 0.009 -1.31976 -.1848926 lpopau | -10.23047 2.754846 -3.71 0.000 -15.62987 -4.83107 lpop | .3943281 .0851227 4.63 0.000 .2274908 .5611655 lxrate1 | -.1298328 .0265004 -4.90 0.000 -.1817725 -.077893 lremote | .0036399 .2559565 0.01 0.989 -.4980257 .5053055 ldist | -1.534272 .3003505 -5.11 0.000 -2.122948 -.9455956 lopen | .0204672 .0547093 0.37 0.708 -.086761 .1276954 english | -.1721423 .2304909 -0.75 0.455 -.6238961 .2796116 white | 9.96927 1.056005 9.44 0.000 7.899539 12.039 lwhitemg | -.8913602 .0959918 -9.29 0.000 -1.079501 -.7032198 _cons | 126.0504 26.13116 4.82 0.000 74.83431 177.2666 ------. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002367 lgdp | -.001438 .005216 lgdpau | .000296 -.000647 .640876 lgdpdfrati~w | -.001399 .001446 -.019294 .083817 lpopau | -.005697 -.003643 -2.14366 .078183 7.58918 lpop | -.000271 -.002953 .000148 -.000738 -.003199 .007246 lxrate1 | .000206 -.000203 .000612 .000863 -.00496 -.000467 .000702 lremote | .00168 .004246 -.021426 -.013475 .062759 -.003159 .000192 .065514 ldist | .004624 .001658 -.007058 -.003031 -.01302 .00188 .001074 .027074 .09021 lopen | -.00021 .000443 .000562 -.000564 -.011336 .000959 -9.6e-06 .001302 .002053 english | -.002261 -6.1e-06 .003827 .00445 -.01515 .000625 .001087 -.011784 .023169 white | .012633 -.021845 .016577 -.009189 -.085195 .021942 .005354 .017565 .005879</p><p> lwhitemg | -.001285 .001159 -.002835 -9.5e-06 .014905 -.001376 -.00046 .000871 -.000782 _cons | .049715 -.037243 19.0273 -.746086 -70.0056 .013188 .062052 -1.34756 -.789273</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002993 english | -.00063 .053126 white | -.000402 .023867 1.11515 lwhitemg | .000031 -.001024 -.097007 .009214 _cons | .121383 .011373 .7805 -.164867 682.837</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1385.35 Log likelihood = -337.176 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .047192 .0181507 2.60 0.009 .0116172 .0827668 lgdp | .2219195 .0546844 4.06 0.000 .11474 .329099 lgdpau | -.1794171 .3159006 -0.57 0.570 -.7985709 .4397367 lgdpdfrati~w | -.4523377 .1958543 -2.31 0.021 -.8362051 -.0684703 lpopau | 2.343006 1.119331 2.09 0.036 .1491568 4.536856 lpop | .0749168 .0714048 1.05 0.294 -.0650341 .2148676 lxrate1 | -.0694667 .0183411 -3.79 0.000 -.1054145 -.0335188 lremote | -.1469032 .1130952 -1.30 0.194 -.3685658 .0747594 ldist | -1.416065 .2412157 -5.87 0.000 -1.888839 -.943291 lopen | -.0196012 .0247891 -0.79 0.429 -.0681871 .0289846 english | 1.94619 .2152235 9.04 0.000 1.524359 2.36802 white | 9.435099 1.763055 5.35 0.000 5.979574 12.89062 lwhitemg | -.7091188 .1806205 -3.93 0.000 -1.063128 -.3551092 _cons | -24.09276 11.32613 -2.13 0.033 -46.29157 -1.893958 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000329 lgdp | -.000339 .00299 lgdpau | .00017 -.001341 .099793 lgdpdfrati~w | -.000704 -.000019 -.00132 .038359 lpopau | -.000954 .0057 -.340718 .021492 1.2529 lpop | .000077 -.002912 .000767 .000696 -.006557 .005099 lxrate1 | -.000026 .000175 .001177 .00074 -.005616 -.000171 .000336 lremote | .000138 .001078 -.007348 -.003281 .025098 -.000533 -.000321 .012791 ldist | .000969 .000606 -.002581 -.002421 -.000935 .003136 -.000241 .00321 .058185 lopen | .000014 -.000254 -.000053 .001034 -.000979 .000316 -.000017 -.000139 -.000266 english | -.000199 -.003313 .00424 .002781 -.016529 .005058 .000479 -.00282 .020957 white | .001598 -.023369 .013429 .000825 -.072811 .025583 .001145 .009755 -.022728 lwhitemg | -.000171 .001446 -.0012 .000189 .005938 -.001779 -.000086 -.000349 .001168 _cons | .006395 -.093409 3.13611 -.321581 -12.0815 .048432 .06433 -.377004 -.564562</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000615 english | -.000342 .046321 white | .000945 .074292 3.10836 lwhitemg | -.000022 -.006531 -.313983 .032624 _cons | .021453 -.027858 1.0789 -.077767 128.281</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1172.18 Log likelihood = -853.887 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1904149 .0648664 2.94 0.003 .0632791 .3175508 lgdp | .4711332 .1115685 4.22 0.000 .2524629 .6898035 lgdpau | -2.533884 1.130117 -2.24 0.025 -4.748872 -.3188956 lgdpdfrati~w | -1.152522 .4548761 -2.53 0.011 -2.044063 -.2609812 lpopau | 5.778219 3.876053 1.49 0.136 -1.818706 13.37514 lpop | .1752415 .1254506 1.40 0.162 -.0706371 .4211201 lxrate1 | -.1771074 .0398004 -4.45 0.000 -.2551148 -.0991 lremote | 1.699848 .2779056 6.12 0.000 1.155163 2.244533 ldist | -1.6742 .4531954 -3.69 0.000 -2.562446 -.7859529 lopen | -.0378286 .0765824 -0.49 0.621 -.1879274 .1122702 english | .4095296 .2673711 1.53 0.126 -.1145081 .9335672 white | 11.58035 1.521145 7.61 0.000 8.598956 14.56174 lwhitemg | -.8983897 .1445317 -6.22 0.000 -1.181667 -.6151128 _cons | -37.978 36.38152 -1.04 0.297 -109.2845 33.32847 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .004208 lgdp | -.004679 .012448 lgdpau | -.002337 .006121 1.27716 lgdpdfrati~w | -.001821 .004431 -.001096 .206912 lpopau | .0049 -.029839 -4.27312 .056467 15.0238 lpop | .001883 -.010686 -.002533 -.002599 .013108 .015738 lxrate1 | .000033 .001666 .0009 .001474 -.010025 -.00159 .001584 lremote | .001367 -.002618 -.031581 -.021142 .079682 .002609 .000887 .077232 ldist | .012239 -.01115 -.01051 -.010864 .006297 .012331 -.002789 .021569 .205386 lopen | .000297 -.00075 .007758 .001138 -.037554 .002093 -.000353 .002993 .00385 english | -.00634 .011313 .007885 .001887 -.02983 -.008348 -.000525 -.004517 .02685 white | .026905 -.053501 -.044321 -.04249 .081414 .053083 .005441 .130956 .13365 lwhitemg | -.002937 .003278 .000314 .001376 .008575 -.0028 -.00082 -.00549 -.01656 _cons | -.09254 .365542 37.6766 -.884445 -137.581 -.298617 .142423 -1.35116 -1.96392</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005865 english | -.001058 .071487 white | .001164 .036993 2.31388 lwhitemg | .000037 -.005919 -.209891 .020889 _cons | .344413 -.032501 -2.39324 .044415 1323.62</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 572.98 Log likelihood = -117.7724 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0460989 .0292992 1.57 0.116 -.0113265 .1035242 lgdp | .1376572 .0590065 2.33 0.020 .0220066 .2533077 lgdpau | .4258875 .4247807 1.00 0.316 -.4066674 1.258443 lgdpdfrati~w | .335374 .1901866 1.76 0.078 -.0373848 .7081328 lpopau | 2.115495 1.490242 1.42 0.156 -.8053253 5.036315 lpop | .2971284 .0776467 3.83 0.000 .1449437 .4493131 lxrate1 | -.0309619 .0168908 -1.83 0.067 -.0640673 .0021435 lremote | -.0687316 .1318697 -0.52 0.602 -.3271915 .1897284 ldist | -2.208138 .4309676 -5.12 0.000 -3.052819 -1.363457 lopen | .0459279 .0361125 1.27 0.203 -.0248514 .1167072 english | 1.001168 .1871901 5.35 0.000 .6342826 1.368054 white | 16.3146 1.226684 13.30 0.000 13.91035 18.71886 lwhitemg | -1.375896 .1159194 -11.87 0.000 -1.603094 -1.148698 _cons | -32.52084 15.19305 -2.14 0.032 -62.29868 -2.743005 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000858 lgdp | -.000604 .003482 lgdpau | -.000549 -.000149 .180439 lgdpdfrati~w | -.000691 .000716 .000046 .036171 lpopau | .001397 .00147 -.604929 .014358 2.22082 lpop | -.000173 -.002506 .000497 .000645 -.004398 .006029 lxrate1 | .000063 .000068 .000235 .000558 -.002947 -.000088 .000285 lremote | .00093 .002075 -.007888 -.003773 .022479 -.001516 .000043 .01739 ldist | .002566 -.004397 -.010718 -.008404 .002953 .008629 .000259 .018647 .185733 lopen | -.000044 -.000063 .000481 .000356 -.004614 .000518 -.000044 .000104 .000322 english | -.001365 -.000876 .002918 .003501 -.006811 .004292 .000184 -.004876 .006418 white | .003917 -.016276 .030244 -.002144 -.251087 .023473 .003734 -.004423 -.013892 lwhitemg | -.000489 .000902 -.00317 .000066 .02539 -.001775 -.000396 .00058 .002056 _cons | -.028916 -.032843 5.46928 -.188861 -21.1756 -.047628 .037984 -.517602 -1.74939</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001304 english | .000049 .03504 white | -.000602 .040511 1.50475 lwhitemg | .000101 -.003384 -.138968 .013437 _cons | .054095 -.035233 3.49922 -.35095 230.829</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 247.19 Log likelihood = 150.5971 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0133777 .0201353 0.66 0.506 -.0260867 .0528421 lgdp | .2607402 .0497087 5.25 0.000 .1633129 .3581676 lgdpau | -.2786758 .3447375 -0.81 0.419 -.9543488 .3969973 lgdpdfrati~w | -.0881088 .1477496 -0.60 0.551 -.3776928 .2014751 lpopau | 3.783052 1.242191 3.05 0.002 1.348402 6.217701 lpop | -.0859894 .0549481 -1.56 0.118 -.1936857 .0217068 lxrate1 | -.0989467 .0153515 -6.45 0.000 -.1290351 -.0688584 lremote | .2964233 .1196773 2.48 0.013 .06186 .5309865 ldist | -1.484676 .2729385 -5.44 0.000 -2.019626 -.9497268 lopen | .0190139 .0293898 0.65 0.518 -.038589 .0766168 english | .1908224 .1521403 1.25 0.210 -.1073672 .4890119 white | 9.898348 2.054548 4.82 0.000 5.871509 13.92519 lwhitemg | -.8282791 .1970395 -4.20 0.000 -1.214469 -.4420887 _cons | -47.62502 12.9079 -3.69 0.000 -72.92404 -22.32599 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000405 lgdp | -.000418 .002471 lgdpau | .000107 -.000805 .118844 lgdpdfrati~w | -.000442 .000696 -.005816 .02183 lpopau | -.001174 .005566 -.406306 .025483 1.54304 lpop | .000038 -.001765 .000143 -.000207 -.00308 .003019 lxrate1 | -.000011 -.000014 .000571 .000479 -.004684 -.000105 .000236 lremote | .00045 .001594 -.006675 -.001277 .023472 -.001466 -.000209 .014323 ldist | .002097 -.001371 -.001775 -.002398 -.003964 .002548 -.00007 .006981 .074495 lopen | -.000029 .000036 .000158 .000058 -.001974 .000227 -.000022 .000093 -.000273 english | -.000476 -.000693 .000455 .001042 .015299 .002811 .00022 -.001387 .009696 white | .002166 -.013439 .018227 -.003143 -.134878 .012667 .002094 -.000965 .003497 lwhitemg | -.000254 .000809 -.002025 .000272 .013176 -.000983 -.000157 .000571 -.001203 _cons | .000224 -.097741 3.71677 -.271618 -15.192 .027643 .065688 -.418791 -.680352</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000864 english | -.000322 .023147 white | -.00101 .023726 4.22117 lwhitemg | .000114 -.002187 -.398432 .038825 _cons | .026714 -.38055 1.81287 -.159767 166.614</p><p>. xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 509.72 Log likelihood = -700.7318 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1981579 .055697 3.56 0.000 .0889937 .307322 lgdp | .7440117 .1038525 7.16 0.000 .5404645 .9475589 lgdpau | -.7035909 .734082 -0.96 0.338 -2.142365 .7351834 lgdpdfrati~w | -.3647405 .3058585 -1.19 0.233 -.9642122 .2347312 lpopau | 3.723146 2.534817 1.47 0.142 -1.245004 8.691296 lpop | -.2330863 .1407463 -1.66 0.098 -.5089441 .0427714 lxrate1 | -.157483 .0326246 -4.83 0.000 -.2214259 -.09354 lremote | .1455793 .2482692 0.59 0.558 -.3410194 .6321781 ldist | -2.828616 .6637747 -4.26 0.000 -4.12959 -1.527641 lopen | .0384597 .0772234 0.50 0.618 -.1128954 .1898148 english | -.1522678 .4180077 -0.36 0.716 -.9715478 .6670123 white | 21.00983 4.266602 4.92 0.000 12.64745 29.37222 lwhitemg | -1.896056 .3907473 -4.85 0.000 -2.661907 -1.130205 _cons | -28.18039 24.72252 -1.14 0.254 -76.63564 20.27485 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .003102 lgdp | -.00285 .010785 lgdpau | .000952 -.000229 .538876 lgdpdfrati~w | -.001934 .004014 -.013854 .093549 lpopau | -.006991 -.004459 -1.80009 .073685 6.4253 lpop | -.000065 -.007474 -.001542 -.002005 -.004131 .01981 lxrate1 | .000192 .000529 .002069 .001387 -.011446 -.000809 .001064 lremote | .000912 .00358 -.020787 -.014267 .040465 -.00237 .000522 .061638 ldist | .012498 .004213 -.004937 -.00486 -.048938 .005672 .000863 .031716 .440597 lopen | .000365 -.000957 .00027 .000588 -.018813 .002465 -.000144 .000962 .003292 english | -.006705 .002931 .003524 .006999 -.011839 .013874 .000839 -.005685 .104893 white | .008741 -.036721 .150089 .022656 -.408642 .067095 .006122 .032081 .235367 lwhitemg | -.001418 .001807 -.01563 -.003647 .046008 -.004926 -.000705 .000288 -.034712 _cons | .016534 -.10735 15.9836 -.838454 -59.1229 -.066658 .117056 -1.00388 -3.80052</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005963 english | -.001642 .17473 white | .006947 .26097 18.2039 lwhitemg | -.00048 -.028662 -1.63918 .152683 _cons | .250717 -1.14195 -.08731 .032116 611.203</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1456.28 Log likelihood = -595.8156 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2688113 .0509028 5.28 0.000 .1690435 .368579 lgdp | .5620363 .0949592 5.92 0.000 .3759198 .7481528 lgdpau | .7581215 .7024246 1.08 0.280 -.6186054 2.134848 lgdpdfrati~w | -.0684874 .3078109 -0.22 0.824 -.6717857 .5348109 lpopau | -3.182473 2.428559 -1.31 0.190 -7.942361 1.577414 lpop | .5175488 .1130365 4.58 0.000 .2960013 .7390963 lxrate1 | -.1204138 .0308136 -3.91 0.000 -.1808073 -.0600203 lremote | -.3540494 .2440943 -1.45 0.147 -.8324655 .1243667 ldist | -2.080226 .4663512 -4.46 0.000 -2.994258 -1.166195 lopen | -.1586057 .0806475 -1.97 0.049 -.3166718 -.0005395 english | .9685218 .3229212 3.00 0.003 .3356079 1.601436 white | 24.82853 2.957213 8.40 0.000 19.03249 30.62456 lwhitemg | -2.390112 .26284 -9.09 0.000 -2.905269 -1.874955 _cons | 37.52336 23.30223 1.61 0.107 -8.148167 83.19489 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002591 lgdp | -.002324 .009017 lgdpau | -.002506 .004854 .4934 lgdpdfrati~w | -.002007 .003051 -.014967 .094748 lpopau | .007941 -.031823 -1.65142 .055312 5.8979 lpop | .000342 -.005884 -.002315 -.001699 .009106 .012777 lxrate1 | .000093 .000704 .00067 .001459 -.007211 -.000789 .000949 lremote | .000786 .003644 -.016898 -.020278 .033964 -.002223 .000472 .059582 ldist | .00979 -.001018 -.009819 -.001851 -.004464 .01348 .001294 .012724 .217483 lopen | .000311 -.000446 .000598 .002267 -.016684 .002252 -.000098 .001853 .003223 english | -.003651 .00126 .004137 .005929 -.015134 .001572 .001148 -.007071 .06456 white | .00639 -.02573 .024493 -.019223 -.059721 .042603 .006013 .050784 .007811 lwhitemg | -.000932 .000734 -.003828 -.000038 .01402 -.003215 -.000619 -.001357 -.005682 _cons | -.13021 .275763 14.6446 -.460284 -54.3009 -.26589 .076997 -.793236 -2.10012</p><p>| lopen english white lwhitemg _cons ------+------lopen | .006504 english | -.003112 .104278 white | .006762 .00166 8.74511 lwhitemg | -.000628 .001931 -.763231 .069085 _cons | .189491 -.480106 -.320664 -.024855 542.994</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1499.10 Log likelihood = -769.1612 Prob > chi2 = 0.0000</p><p>------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0794332 .0380171 2.09 0.037 .0049211 .1539453 lgdp | 1.142802 .1059317 10.79 0.000 .9351793 1.350424 lgdpau | .6841654 .7994882 0.86 0.392 -.8828026 2.251133 lgdpdfrati~w | -.1687715 .3301547 -0.51 0.609 -.8158627 .4783198 lpopau | 3.528787 2.782413 1.27 0.205 -1.924642 8.982215 lpop | -.6112406 .1538423 -3.97 0.000 -.9127659 -.3097153 lxrate1 | -.1419391 .0292791 -4.85 0.000 -.1993251 -.0845531 lremote | -.2588415 .2068628 -1.25 0.211 -.6642851 .1466021 ldist | -1.22865 .7443537 -1.65 0.099 -2.687557 .230256 lopen | -.0574912 .0809503 -0.71 0.478 -.2161508 .1011685 english | .2013927 .3386111 0.59 0.552 -.4622729 .8650583 white | 27.78724 2.672595 10.40 0.000 22.54905 33.02543 lwhitemg | -2.601266 .2600122 -10.00 0.000 -3.11088 -2.091651 _cons | -76.15892 27.25514 -2.79 0.005 -129.578 -22.73982 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001445 lgdp | -.002482 .011222 lgdpau | -.000165 .000994 .639181 lgdpdfrati~w | -.002967 .004786 -.022937 .109002 lpopau | -.006072 -.013216 -2.14067 .103567 7.74182 lpop | .001934 -.012877 -.003938 -.002662 .026975 .023667 lxrate1 | -.000056 .000809 .001809 .001406 -.013525 -.00126 .000857 lremote | .001768 .004827 -.017579 -.008099 .007332 -.005484 .000307 .042792 ldist | .008094 .01193 -.025353 -.012143 -.082717 .005841 .00155 .078129 .554062 lopen | .000244 -.000353 -.003006 .005489 -.0028 .001189 -.000232 .002383 .003778 english | -.002108 .005371 .006122 .006543 -.014934 -.000988 .001686 -.000494 .05603 white | .018979 -.059917 .072287 -.033634 -.53025 .076974 .009622 .030941 .091376 lwhitemg | -.001653 .004042 -.008187 .002578 .058217 -.005671 -.000948 -.001938 -.014955 _cons | .034085 -.008729 19.1914 -1.09592 -71.7201 -.436345 .155955 -.803793 -4.342</p><p>| lopen english white lwhitemg _cons ------+------lopen | .006553 english | -.000817 .114657 white | -.007595 .192591 7.14276 lwhitemg | .000957 -.021748 -.684545 .067606 _cons | .056581 -.563567 5.77662 -.582326 742.843</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 604.25 Log likelihood = -584.9358 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4855841 .0571107 8.50 0.000 .3736491 .597519 lgdp | .1305529 .0964918 1.35 0.176 -.0585675 .3196734 lgdpau | .9702079 .7449198 1.30 0.193 -.489808 2.430224 lgdpdfrati~w | -.5688177 .321433 -1.77 0.077 -1.198815 .0611794 lpopau | -3.717574 2.576604 -1.44 0.149 -8.767625 1.332477 lpop | .3943367 .1033387 3.82 0.000 .1917965 .5968769 lxrate1 | -.1194857 .0335045 -3.57 0.000 -.1851532 -.0538181 lremote | -.1015412 .2302765 -0.44 0.659 -.5528748 .3497924 ldist | -1.128701 .5926939 -1.90 0.057 -2.29036 .0329577 lopen | .0436836 .0730096 0.60 0.550 -.0994127 .1867798 english | -.0134453 .2830424 -0.05 0.962 -.5681981 .5413075 white | 20.54321 2.231545 9.21 0.000 16.16946 24.91696 lwhitemg | -1.929606 .2124012 -9.08 0.000 -2.345905 -1.513308 _cons | 40.91739 24.38491 1.68 0.093 -6.876161 88.71095 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .003262 lgdp | -.003208 .009311 lgdpau | -.002614 .006724 .554905 lgdpdfrati~w | -.002704 .005958 -.009177 .103319 lpopau | .007143 -.036458 -1.85809 .051205 6.63889 lpop | .001015 -.005656 -.003852 -.003664 .009313 .010679 lxrate1 | .000321 .000386 -.000107 .000742 -.003969 -.000541 .001123 lremote | -.000196 .00347 -.00863 -.017889 -.005256 .000458 .001315 .053027 ldist | .011243 .0034 -.003191 -.010161 -.08247 .005359 .000738 .037071 .351286 lopen | -.000412 .000924 .002312 -.000309 -.024998 .001872 -.000133 .002775 .004993 english | -.003067 .006232 .005194 .001507 -.024822 .000207 -.001218 .00978 .097366 white | .022209 -.040034 -.000024 -.073592 .086401 .0167 .000156 .110014 .197727</p><p> lwhitemg | -.002555 .002426 -.001829 .004484 .002888 -.000746 -.000297 -.007501 -.030526 _cons | -.11664 .256857 16.3069 -.522032 -60.0114 -.15106 .045032 -.578641 -2.44145</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00533 english | .000107 .080113 white | -.00725 .141261 4.97979 lwhitemg | .000643 -.016785 -.464135 .045114 _cons | .239265 -.87477 -3.76048 .329932 594.624</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1610.83 Log likelihood = -240.4782 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0015497 .0214774 0.07 0.942 -.0405451 .0436446 lgdp | .4255325 .0770443 5.52 0.000 .2745283 .5765366 lgdpau | -.245765 .4755556 -0.52 0.605 -1.177837 .6863068 lgdpdfrati~w | .140816 .2103443 0.67 0.503 -.2714513 .5530833 lpopau | 1.063445 1.639436 0.65 0.517 -2.14979 4.27668 lpop | -.2311264 .0998579 -2.31 0.021 -.4268444 -.0354085 lxrate1 | -.0456872 .021734 -2.10 0.036 -.0882851 -.0030894 lremote | -.0911809 .1575457 -0.58 0.563 -.3999648 .217603 ldist | -3.541081 .4800224 -7.38 0.000 -4.481908 -2.600254 lopen | .0197999 .0479265 0.41 0.680 -.0741342 .1137341 english | .0312848 .2994804 0.10 0.917 -.5556861 .6182557 white | 16.23041 2.543575 6.38 0.000 11.2451 21.21573 lwhitemg | -1.180643 .2728075 -4.33 0.000 -1.715336 -.6459504 _cons | 18.65413 16.32791 1.14 0.253 -13.34798 50.65624 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000461 lgdp | -.000649 .005936 lgdpau | .000043 -.001373 .226153 lgdpdfrati~w | -.000922 .002209 -.007875 .044245 lpopau | -.001029 -.00185 -.75498 .039314 2.68775 lpop | .000272 -.004895 -.000155 -.000682 .000677 .009972 lxrate1 | -.000016 .000151 .001253 .000992 -.006008 -.000535 .000472 lremote | .000115 .002228 -.014885 -.003853 .04302 -.003269 -.000226 .024821 ldist | .001897 .003116 -.00797 -.001686 -.011656 .014158 -.000244 .010194 .230422 lopen | .000033 -.000056 -.001858 .00117 .002298 .00072 -.000048 .00026 .000579 english | -.000924 -.000656 .002867 .00187 -.002019 .00524 .000687 -.000638 .057562 white | .004312 -.032881 .044102 -.008677 -.26626 .047905 .002509 -.00555 .13715 lwhitemg | -.000433 .0014 -.005393 .000196 .032854 -.003943 -.000103 .002669 -.017573 _cons | .006027 -.035532 6.83187 -.479474 -25.0377 -.160862 .072937 -.633004 -2.20429</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002297 english | -.000293 .089689 white | -.002757 .11691 6.46977 lwhitemg | .000323 -.011605 -.684923 .074424 _cons | -.007123 -.66729 1.93615 -.22563 266.601</p><p>. . . clear</p><p>. insheet using k:\book1.txt (104 vars, 1010 obs)</p><p>. *Dropping Madagascar . drop if ccode==164500 (10 observations deleted)</p><p>. . . *Descriptive stats after dropping . tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist open english gdpdfration > ew white whitemg, stat(n mean sd median min max) col(stat) </p><p> variable | N mean sd p50 min max ------+------rimp | 1000 491195.3 1561183 8397.5 0 1.39e+07 immig | 1000 33461.85 117038.6 2986.5 0 1137050 gdp | 1000 2.79e+11 9.69e+11 1.74e+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 105.7593 16.9164 103.0148 60.87417 207.3465 gdpdfau | 1000 100.7173 4.633489 100.8223 94.42464 109.9797 pop | 1000 4.95e+07 1.54e+08 1.02e+07 41000 1.26e+09 popau | 1000 1.82e+07 612793.8 1.82e+07 1.73e+07 1.92e+07 xrate1 | 1000 1018.022 10900.66 13.89535 .0068 270182.6 remote | 1000 6698.917 4127.608 6764 1293 39620 dist | 1000 13349.21 3526.543 14215 2409 17972 open | 1000 .7098099 .3896246 .63885 .0671 3.2192 english | 1000 .38 .4856293 0 0 1 gdpdfratio~w | 1000 1.053075 .1810729 1.01867 .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" countries)--RHS Variables > : . by white: tabstat rimp immig gdp gdpau gdpdefnew gdpdfau pop popau xrate1 remote dist phone open eng > lish 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 404944.2 1597577 3443.5 0 1.39e+07 immig | 870 14896.77 27125.19 1606 0 158613 gdp | 870 2.37e+11 1.00e+12 1.09e+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 | 870 104.8959 17.27829 101.7941 60.87417 207.3465 gdpdfau | 870 100.7173 4.633836 100.8223 94.42464 109.9797 pop | 870 5.34e+07 1.65e+08 1.03e+07 41000 1.26e+09 popau | 870 1.82e+07 612839.6 1.82e+07 1.73e+07 1.92e+07 xrate1 | 870 1154.147 11680.96 19.96485 .0068 270182.6 remote | 870 7119.247 4099.743 6927 1293 39620 dist | 870 13176.56 3413.819 14040 2410 17972 phone | 870 159.3281 241.8403 49.865 .54 1449.75 open | 870 .7174614 .4110728 .63875 .0671 3.2192 english | 870 .3908046 .4882114 0 0 1 gdpdfratio~w | 870 1.044723 .1859863 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 lremote 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) = 8905.35 Log likelihood = -523.8448 Prob > chi2 = 0.0000</p><p>------lrimp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .350199 .030944 11.32 0.000 .2895498 .4108482 lgdp | 1.207809 .0326535 36.99 0.000 1.143809 1.271809 lgdpau | .0653656 .6090698 0.11 0.915 -1.128389 1.25912 lgdpdfrati~w | -.9002158 .2478832 -3.63 0.000 -1.386058 -.4143736 lpopau | -2.518097 2.100886 -1.20 0.231 -6.635757 1.599563 lpop | .0077733 .0410088 0.19 0.850 -.0726025 .0881491 lxrate1 | -.1310367 .0178795 -7.33 0.000 -.1660798 -.0959935 lremote | -.4569981 .0722649 -6.32 0.000 -.5986347 -.3153615 ldist | -2.054839 .1589762 -12.93 0.000 -2.366426 -1.743251 lopen | .2785901 .0569423 4.89 0.000 .1669851 .390195 english | .965659 .1219528 7.92 0.000 .726636 1.204682 white | 4.768119 .5534931 8.61 0.000 3.683292 5.852945 lwhitemg | -.4497924 .0496798 -9.05 0.000 -.5471631 -.3524218 _cons | 41.75315 19.37002 2.16 0.031 3.788601 79.7177 ------. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000958 lgdp | -.000329 .001066 lgdpau | -.000908 .00134 .370966 lgdpdfrati~w | -.000812 .000179 -.009364 .061446 lpopau | .001971 -.007984 -1.2546 .049252 4.41372 lpop | -.000124 -.000732 .000085 .000169 -.000072 .001682 lxrate1 | .000087 .000134 .000346 .00017 -.002396 -.000105 .00032 lremote | .000488 .00014 -.000282 -.001654 -.004271 -.000225 .000132 .005222 ldist | .001505 .000658 -.000092 -.001346 -.010278 .000043 .001722 .006117 .025273 lopen | -.000191 .000629 .002472 .000767 -.017308 .000343 .000113 .001353 .000379 english | -.001228 .002521 .002959 .002456 -.010826 -.001127 .000462 -.003088 .000895 white | .004616 -.001189 .002926 -.009226 -.024488 .005011 -.000327 -.002139 .001303 lwhitemg | -.000559 .000129 -.000219 .000874 .00243 -.000396 .000027 .000212 -.000371 _cons | -.024308 .076904 11.0661 -.610794 -40.0571 -.007527 .009917 -.023907 -.149701</p><p>| lopen english white lwhitemg _cons ------+------lopen | .003242 english | -.000577 .014872 white | -.000517 .006552 .306355 lwhitemg | -.000029 -.000349 -.027139 .002468 _cons | .189285 .075268 .242737 -.025085 375.198</p><p>. . **II. Conservative Estimates . *2.1. Aggregate reference priced Imports (conservative) . xtgls lrrefp_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 68190.22 Log likelihood = -958.787 Prob > chi2 = 0.0000</p><p>------lrrefp_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0435297 .0133641 3.26 0.001 .0173366 .0697228 lgdp | 1.622016 .0505591 32.08 0.000 1.522922 1.72111 lgdpau | 1.016962 .3490694 2.91 0.004 .3327987 1.701126 lgdpdfrati~w | -.4265167 .1446203 -2.95 0.003 -.7099672 -.1430662 lpopau | -6.888586 1.177659 -5.85 0.000 -9.196755 -4.580416 lpop | -.3610128 .0842077 -4.29 0.000 -.5260568 -.1959687 lxrate1 | -.115944 .0199146 -5.82 0.000 -.1549758 -.0769121 lremote | -.9858146 .089024 -11.07 0.000 -1.160298 -.8113308 ldist | -3.21118 .1584535 -20.27 0.000 -3.521743 -2.900617 lopen | -.0585401 .0260591 -2.25 0.025 -.1096149 -.0074653 english | 1.029008 .085388 12.05 0.000 .8616508 1.196366 white | 4.604755 .7495728 6.14 0.000 3.13562 6.073891 lwhitemg | -.4562858 .0716333 -6.37 0.000 -.5966845 -.3158871 _cons | 100.4251 11.0421 9.09 0.000 78.78301 122.0672 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000179 lgdp | -.000249 .002556 lgdpau | -.00113 .001568 .121849 lgdpdfrati~w | -.000566 .000414 -.01145 .020915 lpopau | .004488 -.006357 -.402376 .023133 1.38688 lpop | .000157 -.004018 -.001288 .000561 .00321 .007091 lxrate1 | -.000027 .00026 -.000101 .000397 -.002859 -.00028 .000397 lremote | .00042 .000628 -.005915 -.002932 .020846 -.001587 .000099 .007925 ldist | .000589 -.001226 -.005797 -.001244 .013993 .002049 .000542 .003368 .025108 lopen | .000043 -.00008 -.000899 .000893 .003346 .000225 -.000071 .000546 .00017 english | -.000395 .000164 .002752 .002531 -.018768 .000387 .001071 -.002541 .002343 white | .001154 -.012134 -.01004 -.002971 .036795 .018504 -.000545 .004703 -.026058 lwhitemg | -.000089 .000645 .000453 .000177 -.002497 -.0009 .000102 -1.3e-06 .003434 _cons | -.051163 .075629 3.58663 -.08197 -12.7098 -.045475 .040878 -.281136 -.361223</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000679 english | -.000389 .007291 white | .00155 -.001118 .561859 lwhitemg | -.000123 .000339 -.052369 .005131 _cons | -.040672 .224036 -.149808 -.004549 121.928</p><p>. . *2.2. Aggregate Differentiated Imports (conservative) . xtgls lrdiff_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 7836.65 Log likelihood = -920.6673 Prob > chi2 = 0.0000</p><p>------lrdiff_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1938123 .0300463 6.45 0.000 .1349225 .252702 lgdp | 1.647381 .0745003 22.11 0.000 1.501364 1.793399 lgdpau | -.0120089 .6440731 -0.02 0.985 -1.274369 1.250351 lgdpdfrati~w | -.259673 .2592182 -1.00 0.316 -.7677313 .2483853 lpopau | -1.854984 2.240903 -0.83 0.408 -6.247072 2.537105 lpop | -.5871586 .0799982 -7.34 0.000 -.7439523 -.430365 lxrate1 | -.1625528 .0289517 -5.61 0.000 -.2192972 -.1058085 lremote | -.3955792 .1318755 -3.00 0.003 -.6540505 -.137108 ldist | -3.370465 .3446903 -9.78 0.000 -4.046046 -2.694885 lopen | .1108739 .0484189 2.29 0.022 .0159746 .2057732 english | .7808588 .1326405 5.89 0.000 .5208881 1.040829 white | 9.233787 1.849945 4.99 0.000 5.607963 12.85961 lwhitemg | -.8038401 .1854045 -4.34 0.000 -1.167226 -.440454 _cons | 42.45297 21.14235 2.01 0.045 1.014735 83.89121 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000903 lgdp | -.001407 .00555 lgdpau | -.002197 .005307 .41483 lgdpdfrati~w | -.001134 .0027 -.026909 .067194 lpopau | .005818 -.024629 -1.40424 .09586 5.02164 lpop | .000936 -.004459 -.003321 -.001641 .01362 .0064 lxrate1 | .000074 .000503 .000418 .001041 -.006847 -.000796 .000838 lremote | -.000072 -.00045 -.005757 -.00164 .013588 -.001267 .000218 .017391 ldist | .003963 .004228 -.010305 -.003039 -.01819 .000098 .001835 .009233 .118811</p><p> lopen | .000117 -.000625 .000661 .001662 -.003958 .001275 -.000205 .000391 -.000913 english | -.001386 .0042 .005389 .003959 -.027947 -.000695 .001966 -.004628 .003101 white | .002132 -.028092 .00849 -.000526 -.000841 .019776 .004184 .012364 -.136285 lwhitemg | -.000165 .001527 -.002163 -.000512 .006412 -.001285 -.000438 .00092 .011407 _cons | -.062327 .181527 12.5327 -.942329 -46.2084 -.128777 .079613 -.285619 -.761743</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002344 english | -.001398 .017594 white | .003405 .006192 3.4223 lwhitemg | -.000247 -.001515 -.336329 .034375 _cons | .047765 .241429 1.26539 -.177592 446.999</p><p>. . *2.3. Aggregate Homogenous Imports (conservative) . xtgls lrhomo_cm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 2154.99 Log likelihood = -1122.992 Prob > chi2 = 0.0000</p><p>------lrhomo_cm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1127955 .0521967 2.16 0.031 .0104918 .2150992 lgdp | .9180785 .0867671 10.58 0.000 .7480181 1.088139 lgdpau | -.5903831 .857669 -0.69 0.491 -2.271383 1.090617 lgdpdfrati~w | -.4202731 .3552574 -1.18 0.237 -1.116565 .2760186 lpopau | .4577676 2.93612 0.16 0.876 -5.296922 6.212457 lpop | .0723054 .1006758 0.72 0.473 -.1250155 .2696264 lxrate1 | -.1237999 .0336423 -3.68 0.000 -.1897376 -.0578622 lremote | .58095 .2374991 2.45 0.014 .1154603 1.04644 ldist | -1.611617 .3521142 -4.58 0.000 -2.301748 -.9214857 lopen | .3467378 .0806842 4.30 0.000 .1885998 .5048759 english | 1.610031 .250552 6.43 0.000 1.118958 2.101104 white | 1.911109 2.236285 0.85 0.393 -2.471929 6.294147 lwhitemg | .1498662 .1968034 0.76 0.446 -.2358613 .5355937 _cons | -.9037895 27.89859 -0.03 0.974 -55.58402 53.77644 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002724 lgdp | -.0026 .007529 lgdpau | -.003091 .002508 .735596 lgdpdfrati~w | -.001612 .002883 -.009405 .126208 lpopau | .007868 -.013314 -2.4588 .034284 8.6208 lpop | .000427 -.005975 -.000168 -.001292 -.000832 .010136 lxrate1 | .000155 .000869 .000352 .002015 -.007168 -.001152 .001132 lremote | .001379 .000713 -.029935 -.01527 .090666 .000552 -.000677 .056406 ldist | .006485 -.009007 -.023122 -.00956 .071851 .011019 -.000097 .022023 .123984 lopen | .000349 -.001177 .004471 .002184 -.025828 .002912 -.000204 .002077 -.00052 english | -.005537 .003155 .012652 .008498 -.027638 -.001168 .001357 -.015331 .009731 white | .004568 -.025265 .100155 .001906 -.408198 .022056 .000621 .040376 -.03282 lwhitemg | -.000744 .001177 -.010484 -.001419 .0437 -.000345 -.000197 -.000588 .006556 _cons | -.081875 .167585 21.9433 -.268674 -79.7776 -.114237 .108387 -1.43283 -1.96149</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00651 english | -.002115 .062776 white | .006456 .034728 5.00097 lwhitemg | -.000377 -.002203 -.428905 .038732 _cons | .280159 .112498 4.29258 -.524007 778.331</p><p>. . **III. Liberal Estimates . *3.1. Aggregate reference priced Imports (liberal) . xtgls lrrefp_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 62072.36 Log likelihood = -892.5478 Prob > chi2 = 0.0000</p><p>------lrrefp_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0244877 .0139006 1.76 0.078 -.0027569 .0517323 lgdp | 1.492558 .0531501 28.08 0.000 1.388386 1.59673 lgdpau | .5940596 .3666025 1.62 0.105 -.1244682 1.312587 lgdpdfrati~w | -.2519714 .1369028 -1.84 0.066 -.520296 .0163531 lpopau | -6.469706 1.241112 -5.21 0.000 -8.902241 -4.037172 lpop | -.0475321 .0905062 -0.53 0.599 -.2249211 .1298569 lxrate1 | -.0429211 .018396 -2.33 0.020 -.0789766 -.0068656 lremote | -.5376293 .1499508 -3.59 0.000 -.8315276 -.2437311 ldist | -2.357991 .1646637 -14.32 0.000 -2.680726 -2.035256 lopen | -.0370637 .027853 -1.33 0.183 -.0916546 .0175273 english | 1.134968 .1123847 10.10 0.000 .9146979 1.355238 white | 4.17492 .8416499 4.96 0.000 2.525316 5.824523 lwhitemg | -.2972618 .0764272 -3.89 0.000 -.4470563 -.1474673 _cons | 90.08107 11.7197 7.69 0.000 67.11088 113.0513 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000193 lgdp | -.000195 .002825 lgdpau | -.000902 .002015 .134397 lgdpdfrati~w | -.000335 .000813 -.007411 .018742 lpopau | .003212 -.007066 -.446202 .011727 1.54036 lpop | .000104 -.004523 -.001639 -.000191 .003329 .008191 lxrate1 | 4.9e-06 .000211 -.000073 .00045 -.002462 -.000233 .000338 lremote | -.000011 -.000994 -.013909 -.004305 .050307 .000263 -.000196 .022485 ldist | .000858 -.005427 -.004245 .000999 .00406 .009454 .000646 -.002589 .027114 lopen | .000016 -.000088 -.000904 .000907 .00326 .000263 -.000066 .001155 .00026 english | -.000315 -.000467 .003451 .002533 -.017993 .00046 .000913 -.004271 .006698 white | .000425 -.015579 -.017445 -.002431 .032222 .027245 .002107 .019666 .030078 lwhitemg | -.000084 .000683 .000153 -.000239 .002083 -.00139 -.000233 .000661 -.001767 _cons | -.035531 .132305 4.03053 -.004777 -14.2416 -.13156 .035527 -.619199 -.228554</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000776 english | -.000462 .01263 white | .001073 .006418 .708374 lwhitemg | .00001 -.000356 -.0612 .005841 _cons | -.045666 .177591 -.62261 -.019744 137.351</p><p>. . *3.2. Aggregate Differentiated Imports (liberal) . xtgls lrdiff_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 8368.75 Log likelihood = -948.9998 Prob > chi2 = 0.0000</p><p>------lrdiff_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2810862 .0339482 8.28 0.000 .214549 .3476234 lgdp | 1.545115 .0743391 20.78 0.000 1.399413 1.690817 lgdpau | -.1077476 .6450294 -0.17 0.867 -1.371982 1.156487 lgdpdfrati~w | -.119696 .2734465 -0.44 0.662 -.6556413 .4162492 lpopau | -1.257512 2.251181 -0.56 0.576 -5.669746 3.154723 lpop | -.5012245 .0813217 -6.16 0.000 -.6606121 -.3418369 lxrate1 | -.1430531 .0284845 -5.02 0.000 -.1988817 -.0872244 lremote | -.3615209 .1240176 -2.92 0.004 -.6045909 -.118451 ldist | -2.672649 .333724 -8.01 0.000 -3.326736 -2.018562 lopen | .1258376 .0512754 2.45 0.014 .0253395 .2263356 english | .7318637 .1328913 5.51 0.000 .4714016 .9923258 white | 9.641384 1.829814 5.27 0.000 6.055014 13.22775 lwhitemg | -.8544612 .1827213 -4.68 0.000 -1.212588 -.496334 _cons | 28.35034 21.3421 1.33 0.184 -13.47941 70.18009 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001152 lgdp | -.001741 .005526 lgdpau | -.00179 .003573 .416063 lgdpdfrati~w | -.001347 .003102 -.027656 .074773 lpopau | .005081 -.019057 -1.41021 .103823 5.06782 lpop | .001019 -.004519 -.001566 -.001984 .008349 .006613 lxrate1 | .000095 .000379 -.000037 .001193 -.005443 -.000686 .000811 lremote | .00004 -.000454 -.004069 -.001223 .006228 -.001144 .000198 .01538 ldist | .005085 .000098 -.010851 -.003796 -.010191 .001537 .001662 .009759 .111372 lopen | .000134 -.000703 .001511 .001684 -.008625 .001447 -.000253 .000289 -.001201 english | -.001762 .003952 .002813 .004597 -.017207 -.00067 .001921 -.004325 -.00167 white | .000735 -.025285 .015114 .000938 -.006201 .017939 .003891 .011265 -.153246 lwhitemg | .000013 .001426 -.002343 -.000648 .00462 -.001137 -.000371 .000783 .014419 _cons | -.067515 .177189 12.6024 -1.0629 -46.8868 -.104428 .070916 -.197698 -.748257</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002629 english | -.001598 .01766 white | .003797 .01009 3.34822 lwhitemg | -.00029 -.001621 -.328525 .033387 _cons | .106053 .180143 1.32303 -.171466 455.485</p><p>. . *3.3. Aggregate Homogenous Imports (liberal) . xtgls lrhomo_lm limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen eng > lish 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) = 8673.86 Log likelihood = -1099.884 Prob > chi2 = 0.0000</p><p>------lrhomo_lm | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .028666 .0158594 1.81 0.071 -.0024179 .05975 lgdp | 1.349307 .0494881 27.27 0.000 1.252312 1.446302 lgdpau | .6111014 .5139764 1.19 0.234 -.3962739 1.618477 lgdpdfrati~w | -.0559888 .1692802 -0.33 0.741 -.3877719 .2757944 lpopau | -5.909789 1.746988 -3.38 0.001 -9.333823 -2.485755 lpop | .0651657 .0681663 0.96 0.339 -.0684377 .1987691 lxrate1 | -.0656502 .0202449 -3.24 0.001 -.1053295 -.025971 lremote | -.9850661 .1620361 -6.08 0.000 -1.302651 -.6674813 ldist | -3.456394 .2192213 -15.77 0.000 -3.88606 -3.026728 lopen | .077978 .0429973 1.81 0.070 -.0062952 .1622512 english | 2.392756 .1376987 17.38 0.000 2.122871 2.66264 white | 3.892405 1.145717 3.40 0.001 1.64684 6.13797 lwhitemg | -.194354 .0957369 -2.03 0.042 -.3819949 -.006713 _cons | 95.01388 16.61695 5.72 0.000 62.44525 127.5825 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000252 lgdp | -.000412 .002449 lgdpau | -.000229 .000278 .264172 lgdpdfrati~w | -.000494 .00062 .002559 .028656 lpopau | -.001193 .000698 -.878823 -.006995 3.05197 lpop | .000217 -.002581 -.000507 .000139 -.000835 .004647 lxrate1 | -.000027 .000241 .00034 .000599 -.002621 -.00039 .00041 lremote | .000301 .000693 -.017362 -.001787 .053064 -.000837 -.000231 .026256 ldist | .000709 .000704 -.011509 -.001718 .023671 -.000021 .000281 .017176 .048058 lopen | .000088 -.000346 .000142 .002018 -.000052 .000738 -.000131 .000993 .000223 english | -.000825 .000543 .002561 .001812 -.009122 .001522 .001154 -.004228 .002206 white | .000383 -.012948 -.003996 -.000943 .00517 .022929 .000039 .002955 -.004415 lwhitemg | -8.0e-06 .000674 -.00092 .000142 .003391 -.00154 .000058 .00142 .002199 _cons | .022173 -.044879 7.90997 .036096 -28.2609 .018372 .03216 -.819997 -.720962</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001849 english | -.001417 .018961 white | .000805 .033203 1.31267 lwhitemg | 8.3e-06 -.002941 -.106088 .009166 _cons | -.018236 .055731 -.052545 -.056115 276.123</p><p>. . *IV. Aggregate NON-Manufacturing Imports (Sum of Sitc0,1,2,3,4) . xtgls lrmnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 715.04 Log likelihood = -566.4255 Prob > chi2 = 0.0000</p><p>------lrmnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3759706 .0391797 9.60 0.000 .2991798 .4527613 lgdp | .1644133 .0664861 2.47 0.013 .0341029 .2947237 lgdpau | -1.154015 .3543492 -3.26 0.001 -1.848527 -.4595035 lgdpdfrati~w | -.3596475 .1820213 -1.98 0.048 -.7164026 -.0028923 lpopau | 1.678536 1.211905 1.39 0.166 -.696753 4.053826 lpop | .3935006 .085578 4.60 0.000 .2257708 .5612305 lxrate1 | -.1734388 .0227663 -7.62 0.000 -.2180599 -.1288177 lremote | -.0471138 .1117259 -0.42 0.673 -.2660927 .171865 ldist | -1.60118 .380358 -4.21 0.000 -2.346668 -.8556922 lopen | .087382 .0331822 2.63 0.008 .0223461 .152418 english | .5867473 .2067211 2.84 0.005 .1815814 .9919133 white | 9.990434 .7119206 14.03 0.000 8.595095 11.38577 lwhitemg | -.9841776 .0715101 -13.76 0.000 -1.124335 -.8440203 _cons | 13.25128 11.76644 1.13 0.260 -9.810516 36.31308 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001535 lgdp | -.001376 .00442 lgdpau | .000364 .00007 .125563 lgdpdfrati~w | -.000703 .00166 .003123 .033132 lpopau | -.001853 -.002319 -.412655 .010522 1.46871 lpop | .000024 -.003234 -.002105 -.001033 .000785 .007324 lxrate1 | .00005 .000344 .002696 .001141 -.009441 -.000547 .000518 lremote | .001158 .001013 -.005667 -.002812 .011269 -.001183 -.000152 .012483 ldist | .002249 -.00841 .000369 -.003155 -.032081 .017103 .000664 .01251 .144672 lopen | -2.8e-07 -.000284 -.002371 -.000302 .004076 .000569 -.000195 .000247 .000361 english | -.002201 .001234 .007058 .004038 -.031784 .005238 .001369 -.000528 .011358 white | .008759 -.007464 .021047 .005144 -.097691 .012612 .003442 .001578 -.019588 lwhitemg | -.000762 .000019 -.002249 -.000839 .009939 -.000438 -.000384 .000202 .005459 _cons | .011099 .062227 3.6089 -.261169 -13.2442 -.149935 .077562 -.274573 -1.06037</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001101 english | -.000846 .042734 white | -.000886 .052541 .506831 lwhitemg | .000145 -.002741 -.04836 .005114 _cons | -.011158 .106007 1.09441 -.143409 138.449</p><p>. . *V. Aggregate Manufacturing Imports (Sum of Sitc5,6,7,8,9) . xtgls lrmmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote 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) = 2396.18 Log likelihood = -607.164 Prob > chi2 = 0.0000</p><p>------lrmmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1948488 .0420923 4.63 0.000 .1123494 .2773483 lgdp | .2872809 .0625682 4.59 0.000 .1646495 .4099124 lgdpau | -.1516053 .0914356 -1.66 0.097 -.3308159 .0276052 lgdpdfrati~w | -.135572 .0567492 -2.39 0.017 -.2467985 -.0243456 lpopau | 2.908666 .359743 8.09 0.000 2.203583 3.613749 lpop | .744204 .1053639 7.06 0.000 .5376947 .9507134 lxrate1 | -.0207572 .0109476 -1.90 0.058 -.0422141 .0006998 lremote | .1423179 .0418729 3.40 0.001 .0602485 .2243873 ldist | -3.11409 .3628592 -8.58 0.000 -3.825281 -2.402899 lopen | -.0188349 .0381191 -0.49 0.621 -.0935468 .0558771 english | .5538998 .2767138 2.00 0.045 .0115508 1.096249 white | 23.80502 2.98186 7.98 0.000 17.96068 29.64936 lwhitemg | -2.264446 .2770674 -8.17 0.000 -2.807488 -1.721404 _cons | -29.22616 5.950128 -4.91 0.000 -40.88819 -17.56412 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001772 lgdp | -.001134 .003915 lgdpau | -.001292 -.000061 .00836 lgdpdfrati~w | .000511 -.001465 .001457 .00322 lpopau | .008129 -.002827 -.028602 .0001 .129415 lpop | -.0002 -.002978 .001333 .000711 -.005572 .011102 lxrate1 | -9.9e-06 .000094 -.000075 .00002 .000964 -.000282 .00012 lremote | -.000545 .001564 -.001047 -.001639 -.00026 -.000964 .000077 .001753 ldist | .006254 -.001745 -.005312 .000305 .033223 -.00151 -.000269 -.000491 .131667 lopen | -.000499 -.000199 .000328 -.000708 -.006482 .001428 -.000247 .000391 -.001053 english | -.000771 .000211 .000771 .000299 -.00572 .000302 .000045 -.000241 .054286 white | .006711 -.009155 -.000791 .003465 .008476 .030129 -.000818 -.003946 .029685 lwhitemg | -.00105 .000469 .000436 -.000252 -.003465 -.002996 .000086 .000301 -.006372 _cons | -.138312 .015705 .30221 -.012966 -1.60992 -.025597 -.010289 .00557 -1.64243</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001453 english | -.000227 .076571</p><p> white | .001597 .035606 8.89149 lwhitemg | .000017 -.002729 -.813441 .076766 _cons | .093253 -.466906 -.704274 .148896 35.404</p><p>. . **VI. SITC-1 Digit Level Disaggregate Imports . xtgls lrmsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 563.08 Log likelihood = -546.5859 Prob > chi2 = 0.0000</p><p>------lrmsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .6021546 .0502521 11.98 0.000 .5036624 .7006469 lgdp | -.0204965 .07796 -0.26 0.793 -.1732953 .1323022 lgdpau | 1.903633 .7892457 2.41 0.016 .3567401 3.450526 lgdpdfrati~w | -.7180214 .2839261 -2.53 0.011 -1.274506 -.1615365 lpopau | -9.416815 2.711026 -3.47 0.001 -14.73033 -4.103302 lpop | .2985048 .0954696 3.13 0.002 .1113878 .4856218 lxrate1 | -.1216981 .0257698 -4.72 0.000 -.172206 -.0711901 lremote | -.0812113 .2534956 -0.32 0.749 -.5780535 .4156309 ldist | -1.447337 .309285 -4.68 0.000 -2.053524 -.841149 lopen | .0322873 .0544637 0.59 0.553 -.0744596 .1390341 english | -.0983058 .2196202 -0.45 0.654 -.5287535 .3321419 white | 9.592884 1.096593 8.75 0.000 7.443601 11.74217 lwhitemg | -.8840321 .0987096 -8.96 0.000 -1.077499 -.6905647 _cons | 119.0635 25.70289 4.63 0.000 68.68673 169.4402 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002525 lgdp | -.00153 .006078 lgdpau | .000101 .000057 .622909 lgdpdfrati~w | -.001384 .001829 -.016325 .080614 lpopau | -.004508 -.007263 -2.07948 .066425 7.34966 lpop | -.000104 -.004363 -.000982 -.000905 .002021 .009114 lxrate1 | .000169 -.000169 .00053 .000777 -.004686 -.000435 .000664 lremote | .001466 .004258 -.021889 -.011897 .061038 -.002757 .000379 .06426 ldist | .00457 .001204 -.009255 -.002447 -.010337 .004263 .001002 .028976 .095657 lopen | -.000338 .000872 5.6e-06 -.000783 -.009471 .000513 -7.3e-06 .001357 .002082 english | -.002157 .001658 .004908 .005068 -.021777 -.000523 .000965 -.011498 .020164 white | .015054 -.026927 .013865 -.008735 -.0665 .028456 .005162 .017981 .013902 lwhitemg | -.001488 .001408 -.002728 -.000051 .013718 -.001609 -.000426 .000819 -.001077 _cons | .035017 .012161 18.4586 -.651186 -67.7214 -.068985 .057833 -1.32137 -.874443</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002966 english | -.000057 .048233 white | -.002831 .018525 1.20252 lwhitemg | .000162 -.001115 -.103657 .009744 _cons | .102858 .099715 .451044 -.144681 660.639</p><p>. xtgls lrmsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1386.54 Log likelihood = -359.8087 Prob > chi2 = 0.0000</p><p>------lrmsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0552502 .0219676 2.52 0.012 .0121945 .098306 lgdp | .1892549 .0569126 3.33 0.001 .0777083 .3008015 lgdpau | -.2457003 .3087686 -0.80 0.426 -.8508757 .3594751 lgdpdfrati~w | -.4715472 .2041965 -2.31 0.021 -.871765 -.0713294 lpopau | 2.58224 1.099992 2.35 0.019 .4262942 4.738185 lpop | .1313005 .0703873 1.87 0.062 -.006656 .269257 lxrate1 | -.0797041 .0184615 -4.32 0.000 -.1158879 -.0435202 lremote | -.1355521 .1105648 -1.23 0.220 -.3522551 .0811509 ldist | -1.303289 .2075981 -6.28 0.000 -1.710174 -.8964038 lopen | .0075245 .0254376 0.30 0.767 -.0423322 .0573812 english | 1.988783 .2136642 9.31 0.000 1.570009 2.407557 white | 9.768106 1.781166 5.48 0.000 6.277084 13.25913 lwhitemg | -.7346536 .1834589 -4.00 0.000 -1.094226 -.3750807 _cons | -27.64365 11.15703 -2.48 0.013 -49.51102 -5.776282 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000483 lgdp | -.000487 .003239 lgdpau | .000326 -.001695 .095338 lgdpdfrati~w | -.001069 .000272 -.001211 .041696 lpopau | -.00138 .007327 -.326286 .022917 1.20998 lpop | .000107 -.002959 .001052 .00083 -.008332 .004954 lxrate1 | -.000026 .000184 .001207 .000772 -.005756 -.000162 .000341 lremote | .000201 .00096 -.007048 -.003655 .024832 -.000567 -.000354 .012225 ldist | .001181 .000507 -.001626 -.002696 -.000828 .002277 -.00035 .000717 .043097 lopen | .000025 -.000266 -.000155 .001051 -.00083 .000333 -9.6e-06 -.000126 -.000082 english | -.000464 -.002413 .003988 .004111 -.013966 .00456 .000308 -.004273 .013742 white | .002284 -.023748 .01531 .000415 -.083445 .025938 .000983 .009947 -.025201 lwhitemg | -.000244 .001424 -.001269 .000241 .006365 -.001771 -.000076 -.00041 .00113 _cons | .009211 -.113522 3.0041 -.352784 -11.7536 .081825 .066845 -.348064 -.408887</p><p>| lopen english white lwhitemg _cons ------+------lopen | .000647 english | -.000052 .045652 white | .001351 .070648 3.17255 lwhitemg | -.000068 -.006722 -.322314 .033657 _cons | .01973 .008008 1.2304 -.081651 124.479</p><p>. xtgls lrmsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1183.45 Log likelihood = -847.9559 Prob > chi2 = 0.0000</p><p>------lrmsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1868559 .0668312 2.80 0.005 .0558692 .3178425 lgdp | .5213881 .1117315 4.67 0.000 .3023984 .7403778 lgdpau | -2.199055 1.101452 -2.00 0.046 -4.357861 -.0402486 lgdpdfrati~w | -1.036328 .444208 -2.33 0.020 -1.90696 -.1656963 lpopau | 4.76751 3.774754 1.26 0.207 -2.630872 12.16589 lpop | .1357876 .1248829 1.09 0.277 -.1089784 .3805537 lxrate1 | -.1740134 .0396279 -4.39 0.000 -.2516826 -.0963442 lremote | 1.512144 .2812475 5.38 0.000 .9609089 2.063379 ldist | -1.627806 .4698912 -3.46 0.001 -2.548776 -.7068363 lopen | -.0208115 .0768937 -0.27 0.787 -.1715204 .1298975 english | .4041462 .2643323 1.53 0.126 -.1139357 .9222281 white | 11.0421 1.531712 7.21 0.000 8.040001 14.0442 lwhitemg | -.8805987 .146174 -6.02 0.000 -1.167095 -.5941028 _cons | -29.3637 35.47905 -0.83 0.408 -98.90137 40.17397 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .004466 lgdp | -.004856 .012484 lgdpau | -.002818 .00671 1.2132 lgdpdfrati~w | -.002089 .004847 .003108 .197321 lpopau | .006581 -.031348 -4.05509 .039074 14.2488 lpop | .001911 -.010586 -.003214 -.00292 .014599 .015596 lxrate1 | .000055 .001604 .000782 .001386 -.009287 -.001519 .00157 lremote | .001381 -.003112 -.034183 -.02295 .088282 .003279 .000916 .0791 ldist | .013062 -.011583 -.012177 -.011608 .009034 .013757 -.002517 .021631 .220798 lopen | .000324 -.000792 .006679 .000946 -.034241 .002121 -.000361 .002932 .004123 english | -.006562 .011759 .008571 .002167 -.032272 -.0091 -.000542 -.004206 .025029 white | .028387 -.05472 -.05149 -.047572 .103522 .052718 .005581 .135185 .136333 lwhitemg | -.003137 .003401 .000778 .001681 .007096 -.002746 -.000821 -.005522 -.017163 _cons | -.113429 .38199 35.772 -.675653 -130.523 -.324957 .130704 -1.4407 -2.12998</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005913 english | -.000943 .069872 white | .001471 .027636 2.34614 lwhitemg | -.000014 -.004862 -.21349 .021367 _cons | .316369 .007358 -2.60479 .059901 1258.76</p><p>. xtgls lrmsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 563.44 Log likelihood = -122.3243 Prob > chi2 = 0.0000</p><p>------lrmsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0407938 .031646 1.29 0.197 -.0212311 .1028188 lgdp | .1479184 .0598462 2.47 0.013 .030622 .2652148 lgdpau | .3688056 .4053562 0.91 0.363 -.4256779 1.163289 lgdpdfrati~w | .3406944 .1843902 1.85 0.065 -.0207037 .7020926 lpopau | 2.621244 1.433388 1.83 0.067 -.1881449 5.430634 lpop | .2914027 .079473 3.67 0.000 .1356385 .447167 lxrate1 | -.0309259 .0164493 -1.88 0.060 -.063166 .0013141 lremote | -.0193124 .1266686 -0.15 0.879 -.2675782 .2289534 ldist | -2.235456 .4203903 -5.32 0.000 -3.059406 -1.411506 lopen | .0578229 .0380933 1.52 0.129 -.0168387 .1324845 english | .8318357 .187174 4.44 0.000 .4649814 1.19869 white | 15.78097 1.212367 13.02 0.000 13.40478 18.15717 lwhitemg | -1.335253 .1128702 -11.83 0.000 -1.556474 -1.114031 _cons | -39.54008 14.78613 -2.67 0.007 -68.52037 -10.55979 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001001 lgdp | -.000769 .003582 lgdpau | -.00075 5.6e-06 .164314 lgdpdfrati~w | -.000928 .00093 -.000135 .034 lpopau | .002286 .001004 -.551103 .014925 2.0546 lpop | -.000145 -.002533 .000535 .00066 -.005422 .006316 lxrate1 | .000055 .000092 .000174 .00053 -.002611 -.000115 .000271 lremote | .000966 .00193 -.007475 -.003516 .021523 -.001634 .000119 .016045 ldist | .002709 -.004021 -.010287 -.008058 .001441 .008568 .000097 .016271 .176728 lopen | -.000018 -.000054 .000176 .000295 -.004427 .000531 -.000052 .000014 .000289 english | -.001437 -.000527 .003463 .00301 -.017136 .004777 .000152 -.004953 .006941 white | .004743 -.017131 .029244 -.004571 -.273214 .025238 .003674 -.004621 -.020159 lwhitemg | -.000549 .000968 -.002969 .000323 .026703 -.001922 -.00039 .000504 .002849 _cons | -.037558 -.032293 4.98866 -.199933 -19.7795 -.03458 .034887 -.473435 -1.64114</p><p>| lopen english white lwhitemg _cons ------+------lopen | .001451 english | .000114 .035034 white | -.000428 .04477 1.46983 lwhitemg | .00006 -.00382 -.133782 .01274 _cons | .05978 .102199 3.93608 -.383378 218.63</p><p>. xtgls lrmsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 261.69 Log likelihood = 153.9842 Prob > chi2 = 0.0000</p><p>------lrmsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0013743 .0188678 -0.07 0.942 -.0383546 .0356059 lgdp | .2720122 .0506651 5.37 0.000 .1727104 .3713139 lgdpau | -.3285709 .3471327 -0.95 0.344 -1.008939 .3517968 lgdpdfrati~w | -.0908437 .1420242 -0.64 0.522 -.3692061 .1875186 lpopau | 4.427438 1.268455 3.49 0.000 1.941312 6.913564 lpop | -.0577724 .0604291 -0.96 0.339 -.1762113 .0606666 lxrate1 | -.098184 .015179 -6.47 0.000 -.1279343 -.0684336 lremote | .3552437 .1294301 2.74 0.006 .1015653 .6089221 ldist | -1.294612 .2806333 -4.61 0.000 -1.844644 -.7445812 lopen | .0267607 .0282771 0.95 0.344 -.0286615 .0821828 english | .2413245 .1656533 1.46 0.145 -.08335 .565999 white | 9.364656 2.052629 4.56 0.000 5.341576 13.38774 lwhitemg | -.7891813 .1959034 -4.03 0.000 -1.173145 -.4052178 _cons | -59.83748 13.52568 -4.42 0.000 -86.34732 -33.32764 ------</p><p>. vce | limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000356 lgdp | -.000363 .002567 lgdpau | .000294 -.000668 .120501 lgdpdfrati~w | -.000452 .000436 -.005832 .020171 lpopau | -.00265 .003948 -.414611 .026878 1.60898 lpop | .000048 -.002179 -.000182 -.000018 .001127 .003652 lxrate1 | 2.6e-06 5.4e-06 .000482 .000469 -.004351 -.000114 .00023 lremote | .000271 .001729 -.007779 -.001096 .027739 -.001367 -.000043 .016752 ldist | .001628 -.001673 -.002188 -.001365 .002363 .004672 .000091 .00722 .078755 lopen | -6.7e-06 6.5e-06 .000028 .000214 -.001344 .000172 -.000028 .000083 -.000497 english | -.00043 -.001813 -.000249 .000843 .021138 .004721 .000201 -.00095 .016339 white | .002555 -.01524 .016904 -.004946 -.138565 .015474 .001856 -.000537 .016031 lwhitemg | -.000292 .000965 -.002047 .000493 .014118 -.001221 -.000137 .000693 -.00253 _cons | .024643 -.068114 3.82564 -.300532 -16.1872 -.055807 .05921 -.487756 -.843336</p><p>| lopen english white lwhitemg _cons ------+------lopen | .0008 english | -.000296 .027441 white | -.000736 .034291 4.21329 lwhitemg | .000094 -.003194 -.395571 .038378 _cons | .023147 -.530774 1.77958 -.162885 182.944</p><p>. xtgls lrmsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 464.26 Log likelihood = -671.0474 Prob > chi2 = 0.0000</p><p>------lrmsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2070721 .0565753 3.66 0.000 .0961865 .3179576 lgdp | .7376085 .1060865 6.95 0.000 .5296827 .9455343 lgdpau | -.6517823 .6793523 -0.96 0.337 -1.983288 .6797236 lgdpdfrati~w | -.3917346 .2881181 -1.36 0.174 -.9564357 .1729665 lpopau | 3.639588 2.341626 1.55 0.120 -.9499136 8.22909 lpop | -.3132206 .1497 -2.09 0.036 -.6066273 -.0198139 lxrate1 | -.1514017 .0326068 -4.64 0.000 -.2153098 -.0874936 lremote | .119182 .2411646 0.49 0.621 -.3534918 .5918559 ldist | -3.03174 .6926704 -4.38 0.000 -4.389349 -1.674131 lopen | .0403269 .0670511 0.60 0.548 -.0910909 .1717446 english | -.4732403 .4330632 -1.09 0.274 -1.322029 .375548 white | 20.36441 4.116803 4.95 0.000 12.29562 28.4332 lwhitemg | -1.840837 .3789518 -4.86 0.000 -2.583569 -1.098105 _cons | -24.31554 23.0565 -1.05 0.292 -69.50545 20.87437 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .003201 lgdp | -.002623 .011254 lgdpau | .001339 -.001287 .461519 lgdpdfrati~w | -.002025 .003791 -.0113 .083012 lpopau | -.008988 -.000896 -1.53637 .06596 5.48321 lpop | -.000168 -.008203 -.001657 -.001916 -.006016 .02241 lxrate1 | .000141 .000542 .002057 .001282 -.010893 -.000755 .001063 lremote | .000777 .004331 -.020636 -.012748 .039716 -.002146 .000747 .05816 ldist | .012872 .009783 -.005558 -.004722 -.057101 .005715 .00063 .032794 .479792 lopen | .000485 -.001104 -.000874 -.000137 -.011619 .002002 -.000198 .000692 .003494 english | -.00675 .003055 .001656 .006267 -.016099 .018334 .000476 -.004329 .124876 white | .008625 -.036519 .127604 .018423 -.373686 .077245 .005516 .032142 .259099 lwhitemg | -.001502 .001626 -.013428 -.00302 .042809 -.00585 -.000624 -.000272 -.039584 _cons | .033128 -.199463 13.6633 -.777188 -50.3497 -.05936 .107915 -.996302 -4.16208</p><p>| lopen english white lwhitemg _cons ------+------lopen | .004496 english | -.001495 .187544 white | .005033 .292919 16.9481 lwhitemg | -.000348 -.031578 -1.53328 .143604 _cons | .171664 -1.3026 -.473676 .098249 531.602</p><p>. xtgls lrmsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1178.41 Log likelihood = -564.1089 Prob > chi2 = 0.0000</p><p>------lrmsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2305849 .0486089 4.74 0.000 .1353132 .3258567 lgdp | .6444952 .1024041 6.29 0.000 .4437869 .8452035 lgdpau | .7776032 .644203 1.21 0.227 -.4850114 2.040218 lgdpdfrati~w | .0035669 .2818617 0.01 0.990 -.548872 .5560058 lpopau | -3.362473 2.22778 -1.51 0.131 -7.72884 1.003895 lpop | .4318276 .1304898 3.31 0.001 .1760723 .6875829 lxrate1 | -.100631 .0298928 -3.37 0.001 -.1592199 -.0420422 lremote | -.3592211 .2301287 -1.56 0.119 -.810265 .0918229 ldist | -2.218963 .4492226 -4.94 0.000 -3.099423 -1.338502 lopen | -.0896501 .0737484 -1.22 0.224 -.2341942 .0548941 english | 1.103799 .3261657 3.38 0.001 .4645265 1.743072 white | 23.79746 3.01195 7.90 0.000 17.89414 29.70077 lwhitemg | -2.309896 .2679935 -8.62 0.000 -2.835154 -1.784639 _cons | 41.10498 21.50627 1.91 0.056 -1.04654 83.2565 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .002363 lgdp | -.002099 .010487 lgdpau | -.002455 .005435 .414997 lgdpdfrati~w | -.00187 .003363 -.008713 .079446 lpopau | .007648 -.035931 -1.38772 .030772 4.963 lpop | .000371 -.008726 -.003894 -.002782 .018146 .017028 lxrate1 | .000053 .000673 .000588 .00132 -.006093 -.000818 .000894 lremote | .00045 .003559 -.018027 -.01722 .040369 -.002087 .000573 .052959 ldist | .008398 -.003663 -.010928 -.003154 .005696 .016845 .000509 .008442 .201801 lopen | .000253 -.000022 .000536 .002096 -.014344 .001329 -.000074 .001512 .001712 english | -.003668 .003206 .00671 .006394 -.027179 -.001437 .000723 -.008608 .05734 white | .006435 -.036085 .015038 -.01678 -.008741 .060383 .00461 .036039 .038068 lwhitemg | -.000946 .001278 -.003157 -.000111 .01085 -.004117 -.000473 -.000449 -.007456 _cons | -.114942 .365088 12.3525 -.20571 -45.8816 -.410502 .069166 -.772093 -2.03734</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005439 english | -.001966 .106384 white | .004142 -.000773 9.07184 lwhitemg | -.000472 .001505 -.792267 .071821 _cons | .174299 -.261535 -1.12506 .020942 462.52</p><p>. xtgls lrmsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1839.61 Log likelihood = -747.5652 Prob > chi2 = 0.0000</p><p>------lrmsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0737752 .0348527 2.12 0.034 .0054653 .1420852 lgdp | .9643866 .0961118 10.03 0.000 .7760109 1.152762 lgdpau | .9559258 .6896655 1.39 0.166 -.3957937 2.307645 lgdpdfrati~w | -.0868805 .2746232 -0.32 0.752 -.6251321 .451371 lpopau | 3.308764 2.398676 1.38 0.168 -1.392555 8.010084 lpop | -.3539617 .1436115 -2.46 0.014 -.6354351 -.0724883 lxrate1 | -.1544945 .0219454 -7.04 0.000 -.1975068 -.1114822 lremote | -.3670914 .1900582 -1.93 0.053 -.7395987 .0054159 ldist | -1.586715 .7396276 -2.15 0.032 -3.036358 -.1370715 lopen | -.053701 .0726372 -0.74 0.460 -.1960673 .0886652 english | .0961114 .3349293 0.29 0.774 -.5603381 .7525608 white | 28.76997 2.650678 10.85 0.000 23.57474 33.9652 lwhitemg | -2.676275 .2568915 -10.42 0.000 -3.179773 -2.172776 _cons | -75.12673 24.16309 -3.11 0.002 -122.4855 -27.76794 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .001215 lgdp | -.001922 .009237 lgdpau | -.000641 .002193 .475638 lgdpdfrati~w | -.002065 .004248 -.014371 .075418 lpopau | -.004818 -.011415 -1.58516 .053987 5.75365 lpop | .001729 -.011489 -.00564 -.004165 .031018 .020624 lxrate1 | .000051 .000294 .00034 .000758 -.008302 -.00063 .000482 lremote | .001433 .003353 -.017654 -.004825 .018275 -.001915 .000343 .036122 ldist | .007008 .010404 -.027763 -.00551 -.038256 .014643 .001243 .066443 .547049 lopen | .000325 -.000904 -.000151 .004296 -.00857 .001227 -.000325 .000978 .001369 english | -.00114 .002752 .002399 .002906 -.006481 .00012 .000769 .000995 .064803 white | .017859 -.057709 .010546 -.032259 -.307242 .071262 .008313 .039849 .111427 lwhitemg | -.001616 .00398 -.002489 .002352 .036361 -.005172 -.000813 -.002877 -.017608 _cons | .029288 -.020159 14.2924 -.520263 -53.914 -.555882 .114139 -.839463 -4.95542</p><p>| lopen english white lwhitemg _cons ------+------lopen | .005276 english | -.001515 .112178 white | -.006461 .20878 7.02609 lwhitemg | .000837 -.023368 -.67076 .065993 _cons | .125017 -.657442 3.48105 -.342874 583.855</p><p>. xtgls lrmsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 545.64 Log likelihood = -568.0191 Prob > chi2 = 0.0000</p><p>------lrmsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3808947 .0580618 6.56 0.000 .2670956 .4946937 lgdp | .304148 .0994075 3.06 0.002 .1093128 .4989832 lgdpau | 1.086271 .7386554 1.47 0.141 -.3614669 2.534009 lgdpdfrati~w | -.5116418 .3139552 -1.63 0.103 -1.126983 .1036991 lpopau | -4.502784 2.550657 -1.77 0.078 -9.50198 .4964118 lpop | .316336 .1058409 2.99 0.003 .1088916 .5237803 lxrate1 | -.0984265 .0339469 -2.90 0.004 -.1649612 -.0318918 lremote | -.0387952 .2270752 -0.17 0.864 -.4838543 .406264 ldist | -1.429592 .5807754 -2.46 0.014 -2.567891 -.291293 lopen | .0870983 .0729378 1.19 0.232 -.0558571 .2300538 english | -.0076502 .2791975 -0.03 0.978 -.5548672 .5395669 white | 19.19328 2.102043 9.13 0.000 15.07335 23.31321 lwhitemg | -1.808922 .1994223 -9.07 0.000 -2.199782 -1.418061 _cons | 51.19611 24.16472 2.12 0.034 3.83413 98.5581 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .003371 lgdp | -.003273 .009882 lgdpau | -.002313 .006339 .545612 lgdpdfrati~w | -.00247 .005654 -.008638 .098568 lpopau | .005399 -.034294 -1.82453 .046922 6.50585 lpop | .001122 -.006377 -.004124 -.003914 .010583 .011202 lxrate1 | .000324 .000433 -.000235 .000806 -.003534 -.000603 .001152 lremote | .000051 .00297 -.010227 -.016951 .001043 .000933 .001405 .051563 ldist | .011221 .000873 -.006021 -.010952 -.068632 .007051 .000708 .036621 .3373 lopen | -.000286 .000708 .00231 .000245 -.023571 .001765 -.000185 .002323 .003625 english | -.003735 .007165 .005471 .001993 -.025134 -.000394 -.00137 .007733 .089475 white | .022673 -.040398 -.007111 -.069702 .097306 .016178 .000032 .110766 .204127 lwhitemg | -.002571 .002328 -.001168 .004234 .00171 -.000474 -.000318 -.007706 -.029941 _cons | -.098741 .258281 16.0458 -.450965 -58.9247 -.177659 .040577 -.622868 -2.4301</p><p>| lopen english white lwhitemg _cons ------+------lopen | .00532 english | -.000165 .077951 white | -.007788 .1366 4.41859 lwhitemg | .000732 -.016355 -.410098 .039769 _cons | .238001 -.791702 -3.81267 .326819 583.934</p><p>. xtgls lrmsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremote ldist lopen engl > ish 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) = 1468.09 Log likelihood = -270.0867 Prob > chi2 = 0.0000</p><p>------lrmsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0031183 .0274636 -0.11 0.910 -.0569459 .0507094 lgdp | .420183 .0851208 4.94 0.000 .2533494 .5870166 lgdpau | -.4190583 .4910948 -0.85 0.393 -1.381586 .5434698 lgdpdfrati~w | .1988839 .2306985 0.86 0.389 -.2532769 .6510447 lpopau | 1.49543 1.691885 0.88 0.377 -1.820604 4.811463 lpop | -.1610926 .1262926 -1.28 0.202 -.4086216 .0864365 lxrate1 | -.0346209 .0231868 -1.49 0.135 -.0800662 .0108245 lremote | .0638175 .1763873 0.36 0.717 -.2818953 .4095303 ldist | -3.846984 .5236704 -7.35 0.000 -4.87336 -2.820609 lopen | -.0029923 .04968 -0.06 0.952 -.1003633 .0943787 english | -.0473416 .2930698 -0.16 0.872 -.6217477 .5270646 white | 16.73522 2.624619 6.38 0.000 11.59106 21.87937 lwhitemg | -1.218746 .281282 -4.33 0.000 -1.770049 -.6674437 _cons | 16.69449 17.04596 0.98 0.327 -16.71497 50.10396 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 lremote ldist ------+------limmig | .000754 lgdp | -.000892 .007246 lgdpau | .000232 -.002241 .241174 lgdpdfrati~w | -.001342 .003015 -.009794 .053222 lpopau | -.001434 .001663 -.802952 .053746 2.86247 lpop | .0001 -.006908 -.000589 -.000747 -.003179 .01595 lxrate1 | -.000047 .00014 .001282 .001037 -.006294 -.000337 .000538 lremote | -.000025 .001847 -.018229 -.003176 .052045 -.000577 .000077 .031112 ldist | .002853 .001951 -.012231 -.002009 -.010347 .020871 -.000161 .016152 .274231 lopen | .000062 -.000218 -.002071 .001422 .002023 .000845 -.000018 -6.7e-06 .000852 english | -.001501 .001076 .001618 .002777 -.003887 .004359 .000614 -.000019 .056073 white | .004512 -.040539 .038897 -.016146 -.265882 .072702 .002649 .006914 .166938 lwhitemg | -.000525 .001808 -.004814 .000906 .032259 -.005519 -.000046 .002233 -.020672 _cons | .007071 -.054513 7.32983 -.696156 -26.7985 -.220225 .070572 -.840824 -2.66777</p><p>| lopen english white lwhitemg _cons ------+------lopen | .002468 english | .000119 .08589 white | -.000184 .105374 6.88862 lwhitemg | .00009 -.010681 -.727705 .07912 _cons | .003889 -.61734 1.46806 -.182918 290.565 closed on: 25 Jul 2006, 20:22:56</p>