<p>------log: K:\Roger-Australia\Robustness-1\South Africa-Sweden_Exports.log log type: text opened on: 18 Aug 2006, 19:09:45</p><p>. clear</p><p>. *Estimating the Australian Immigration Trade relationship; . insheet using k:\book2.txt (54 vars, 11640 obs)</p><p>. drop if ccode ==. (10630 observations deleted)</p><p>. . **Dropping South Africa . drop if ccode==167060 (10 observations deleted)</p><p>. . ** Estimation Results . **Regression of Exports without Distinction between "white" and "non-white Aus > tralia" . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Exports . xtgls lrexp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote 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) = 7149.99 Log likelihood = -1023.826 Prob > chi2 = 0.0000</p><p>------lrexp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .54303 .0373098 14.55 0.000 .4699041 .6161559 lgdp | 1.055833 .0385101 27.42 0.000 .9803545 1.131311 lgdpau | -3.123804 .8818864 -3.54 0.000 -4.85227 -1.395338 lgdpdfrati~w | -1.814222 .3387715 -5.36 0.000 -2.478202 -1.150242 lpopau | 3.763105 3.077719 1.22 0.221 -2.269113 9.795324 lpop | -.0039828 .0412464 -0.10 0.923 -.0848244 .0768587 lxrate1 | .0008586 .0148314 0.06 0.954 -.0282104 .0299277 lremote | .157128 .0950801 1.65 0.098 -.0292256 .3434817 ldist | -1.365147 .1479018 -9.23 0.000 -1.655029 -1.075264 lopen | .8932523 .0806707 11.07 0.000 .7351407 1.051364 english | .1922103 .0979698 1.96 0.050 .0001929 .3842276 white | 3.267963 .5826911 5.61 0.000 2.125909 4.410016 lwhitemg | -.3982225 .05225 -7.62 0.000 -.5006305 -.2958144 _cons | 13.74723 28.59455 0.48 0.631 -42.29706 69.79153 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001392 lgdp | -.000767 .001483 lgdpau | -.003141 .002628 .777724 lgdpdfrati~w | .000817 -.001238 -.025389 .114766 lpopau | .012082 -.011033 -2.67077 .139828 9.47235 lpop | .000076 -.000771 .000764 -.000033 -.006137 .001701 lxrate1 | 2.6e-06 .00018 -.000021 1.5e-06 -.000262 -.000042 .00022 lremote | -.000356 .001607 .0042 -.003004 -.023679 -.000102 .000026 ldist | .003406 -.001457 -.005114 .003587 .010076 .001761 .000557 lopen | -.000595 .00037 .011072 -.001285 -.060141 .000888 -.000056 english | -.000608 .001792 -.002387 .000292 .015043 -.001126 .000531 white | .007208 -.000351 -.008608 -.010243 .010085 .008849 .00177 lwhitemg | -.000798 .000077 .000942 .0006 -.001501 -.000787 -.000151 _cons | -.143184 .097228 23.9042 -1.76145 -86.9341 .057209 -.005213</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .00904 ldist | .003373 .021875 lopen | .002222 .00083 .006508 english | .001264 .002912 -.00281 .009598 white | .020498 .036276 -.001038 .006528 .339529 lwhitemg | -.001493 -.003636 .000088 -.000376 -.030003 .00273 _cons | .141045 -.29762 .670399 -.254165 -.67184 .066486 817.648</p><p>. **II. Conservative Estimates . *2.1. Aggregate reference priced Exports (conservative) . xtgls lrrefp_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 5925.88 Log likelihood = -1430.609 Prob > chi2 = 0.0000</p><p>------lrrefp_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3371876 .0459661 7.34 0.000 .2470957 .4272795 lgdp | 1.091004 .0682321 15.99 0.000 .9572714 1.224736 lgdpau | -.3466232 .5120142 -0.68 0.498 -1.350153 .6569063 lgdpdfrati~w | -.2361685 .2980343 -0.79 0.428 -.820305 .347968 lpopau | 3.038812 1.845144 1.65 0.100 -.5776044 6.655227 lpop | .0365628 .0950704 0.38 0.701 -.1497717 .2228973 lxrate1 | -.0382733 .0301916 -1.27 0.205 -.0974478 .0209013 lremote | -.234556 .1708941 -1.37 0.170 -.5695022 .1003903 ldist | -3.149092 .39233 -8.03 0.000 -3.918044 -2.380139 lopen | -.0761672 .0548452 -1.39 0.165 -.1836618 .0313273 english | .6434384 .1843573 3.49 0.000 .2821048 1.004772 white | 7.761789 1.077722 7.20 0.000 5.649493 9.874086 lwhitemg | -.8374793 .1149682 -7.28 0.000 -1.062813 -.6121459 _cons | -31.78962 18.58909 -1.71 0.087 -68.22356 4.644316 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002113 lgdp | -.00161 .004656 lgdpau | .001122 -.001378 .262159 lgdpdfrati~w | -.001831 .003122 -.024573 .088824 lpopau | -.005097 .003687 -.909251 .10881 3.40456 lpop | -.000125 -.004848 .003607 -.001373 -.019748 .009038 lxrate1 | .000148 .000374 .000621 .002642 -.006435 -.000556 .000912 lremote | .000187 .000257 -.022954 .002793 .097274 -.003679 .000628 ldist | .008972 -.010415 .004392 .002464 -.034193 .00552 .002214 lopen | .000038 -.000241 .002572 .00111 -.01199 .001148 -.000366 english | -.001231 -.001273 .005778 .004246 -.044898 .0032 .001589 white | .01056 -.025867 .021875 -.003418 -.153462 .032712 .001864 lwhitemg | -.001524 .001985 -.004643 .000537 .023479 -.002099 -.000152 _cons | -.003367 .047163 8.35996 -1.34958 -32.9982 .183922 .05738</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .029205 ldist | .002942 .153923 lopen | -.002075 .000878 .003008 english | -.00473 .001765 -.000685 .033988 white | -.011668 .056627 .002673 .038983 1.16148 lwhitemg | .004253 -.007151 -.000597 -.001783 -.118454 .013218 _cons | -1.25209 -.952056 .130575 .579786 1.52672 -.240459 345.554</p><p>. *2.2. Aggregate Differentiated Exports (conservative) . xtgls lrdiff_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3367.22 Log likelihood = -1540.469 Prob > chi2 = 0.0000</p><p>------lrdiff_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4814274 .0530426 9.08 0.000 .3774658 .585389 lgdp | 1.090984 .061772 17.66 0.000 .9699136 1.212055 lgdpau | 2.482932 2.045506 1.21 0.225 -1.526186 6.492051 lgdpdfrati~w | -2.182785 .819762 -2.66 0.008 -3.789489 -.5760811 lpopau | -9.376886 7.041076 -1.33 0.183 -23.17714 4.42337 lpop | -.1870014 .078283 -2.39 0.017 -.3404333 -.0335694 lxrate1 | -.0632974 .0277489 -2.28 0.023 -.1176841 -.0089106 lremote | .2173643 .2037696 1.07 0.286 -.1820167 .6167453 ldist | -2.160107 .2347042 -9.20 0.000 -2.620119 -1.700095 lopen | .1294742 .0935696 1.38 0.166 -.0539189 .3128674 english | .6806297 .1784298 3.81 0.000 .3309137 1.030346 white | 2.907102 1.15414 2.52 0.012 .6450282 5.169175 lwhitemg | -.2833805 .1039047 -2.73 0.006 -.4870299 -.0797311 _cons | 91.73485 64.80949 1.42 0.157 -35.28941 218.7591 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002814 lgdp | -.001896 .003816 lgdpau | -.00268 .005346 4.1841 lgdpdfrati~w | -.003216 .001043 -.204929 .67201 lpopau | .008945 -.026619 -14.1849 .951073 49.5768 lpop | .000163 -.003237 -.000648 .001255 .005 .006128 lxrate1 | .000231 .000456 .00072 -.000527 -.006481 -.000865 .00077 lremote | .004201 -.002094 .002544 -.006546 -.031345 -.000179 .001118 ldist | .006485 -.005268 -.007186 .011452 .016254 .00224 .00274 lopen | -.000424 .00076 .014961 .002646 -.078435 .001315 -.000158 english | -.003111 .002475 -.000511 .009272 .01262 -.003038 .00104 white | .018533 -.016978 .042036 -.116371 -.18309 .008459 .002087 lwhitemg | -.001667 .001082 -.003553 .010105 .015161 -.000049 -.000125 _cons | -.151932 .343382 125.723 -11.186 -450.909 -.107592 .052263</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .041522 ldist | .024606 .055086 lopen | .004483 .000596 .008755 english | -.013895 .001601 -.003752 .031837 white | .075801 .021194 -.002956 -.016481 1.33204 lwhitemg | -.004502 .000356 .000421 .001529 -.116718 .010796 _cons | -.110062 -.798088 .834762 -.104607 1.29868 -.144045 4200.27</p><p>. *2.3. Aggregate Homogenous Exports (conservative) . xtgls lrhomo_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1994.96 Log likelihood = -1595.213 Prob > chi2 = 0.0000</p><p>------lrhomo_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4687246 .0548149 8.55 0.000 .3612894 .5761599 lgdp | .8842444 .0988432 8.95 0.000 .6905153 1.077974 lgdpau | .1788104 1.172192 0.15 0.879 -2.118645 2.476265 lgdpdfrati~w | -.4144929 .4844397 -0.86 0.392 -1.363977 .5349915 lpopau | -7.357522 4.008256 -1.84 0.066 -15.21356 .4985161 lpop | .2066428 .1082124 1.91 0.056 -.0054496 .4187351 lxrate1 | .0706104 .0377533 1.87 0.061 -.0033846 .1446055 lremote | -1.440253 .2385934 -6.04 0.000 -1.907887 -.9726181 ldist | -1.569266 .5113156 -3.07 0.002 -2.571427 -.5671061 lopen | .0689261 .0975915 0.71 0.480 -.1223498 .2602021 english | .9638281 .3021378 3.19 0.001 .3716488 1.556007 white | 13.74928 2.631433 5.23 0.000 8.591765 18.90679 lwhitemg | -1.617039 .2817156 -5.74 0.000 -2.169191 -1.064886 _cons | 124.1534 37.70413 3.29 0.001 50.25465 198.0521 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003005 lgdp | -.003233 .00977 lgdpau | .005997 -.011919 1.37404 lgdpdfrati~w | -.003787 .007955 -.064983 .234682 lpopau | -.022883 .026722 -4.5663 .315992 16.0661 lpop | .000387 -.00586 .000628 -.002734 -.000537 .01171 lxrate1 | -.000117 .00118 .002759 .002687 -.018731 -.001474 .001425 lremote | .000243 .011338 -.040045 .01477 .100849 -.007765 .000803 ldist | .015871 -.011036 .019327 -.005924 -.136169 .013236 .001969 lopen | -.000047 -.001078 -.019896 .007285 .047863 .002192 -.000235 english | -.00274 .004398 .015382 .00521 -.074622 .004911 .002825 white | .011447 -.024764 .105245 -.012764 -.455912 .034138 .003327 lwhitemg | -.001347 .001856 -.011596 .001664 .049532 -.002955 -.000147 _cons | .123391 -.245517 40.1241 -3.9808 -147.052 -.113982 .202101</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .056927 ldist | .032503 .261444 lopen | .002209 -.001866 .009524 english | -.011992 .014689 -.003809 .091287 white | -.022747 .06067 -.000335 .129832 6.92444 lwhitemg | .003134 -.008083 .000476 -.013421 -.737061 .079364 _cons | -1.56741 -1.06986 -.282005 .601871 4.34622 -.453723 1421.6</p><p>. **III. Liberal Estimates . *3.1. Aggregate reference priced Exports (liberal) . xtgls lrrefp_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2328.91 Log likelihood = -1440.679 Prob > chi2 = 0.0000</p><p>------lrrefp_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3099867 .0456214 6.79 0.000 .2205705 .3994029 lgdp | 1.028198 .0812599 12.65 0.000 .8689311 1.187464 lgdpau | .0755175 .5429164 0.14 0.889 -.9885792 1.139614 lgdpdfrati~w | -.0040179 .2750896 -0.01 0.988 -.5431837 .5351479 lpopau | -3.872385 1.917706 -2.02 0.043 -7.63102 -.1137511 lpop | .0837422 .1035566 0.81 0.419 -.119225 .2867095 lxrate1 | .0142988 .0298944 0.48 0.632 -.0442931 .0728907 lremote | -.2589018 .1654106 -1.57 0.118 -.5831006 .0652969 ldist | -2.374994 .4675011 -5.08 0.000 -3.29128 -1.458709 lopen | .0039206 .0561039 0.07 0.944 -.106041 .1138821 english | 1.042218 .2449441 4.25 0.000 .5621364 1.5223 white | 10.87638 2.048336 5.31 0.000 6.861717 14.89104 lwhitemg | -1.091664 .2003221 -5.45 0.000 -1.484288 -.6990399 _cons | 64.87235 19.02292 3.41 0.001 27.58811 102.1566 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002081 lgdp | -.002256 .006603 lgdpau | .001345 -.002608 .294758 lgdpdfrati~w | -.001748 .003741 -.027364 .075674 lpopau | -.007947 .010996 -1.01147 .122976 3.6776 lpop | .000796 -.006249 .003977 -.003084 -.022416 .010724 lxrate1 | .000087 .000231 .001617 .00179 -.008416 -.0004 .000894 lremote | .000554 .000563 -.021714 .003625 .082468 -.003503 .000051 ldist | .006776 -.011915 .003772 .000705 -.030683 .009501 .002864 lopen | -2.1e-06 -.000098 .00185 .00135 -.009271 .000963 -.000246 english | -.001625 -.000806 .010108 .004341 -.032391 .000907 .002504 white | .008762 -.025423 .015894 -.000392 -.123308 .033391 .01117 lwhitemg | -.001049 .001578 -.003177 .000199 .018095 -.002024 -.001003 _cons | .056377 -.049418 9.21139 -1.47549 -34.8618 .179951 .06395</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .027361 ldist | .007925 .218557 lopen | -.001112 -.000354 .003148 english | -.007727 .027315 -.000765 .059998 white | .03796 -.161409 -.005137 .023263 4.19568 lwhitemg | -.001447 .017699 .000277 -.000185 -.405966 .040129 _cons | -1.07785 -1.68807 .107163 .058507 2.78046 -.367762 361.872</p><p>. *3.2. Aggregate Differentiated Exports (liberal) . xtgls lrdiff_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3368.02 Log likelihood = -1557.56 Prob > chi2 = 0.0000</p><p>------lrdiff_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4434003 .0555128 7.99 0.000 .3345971 .5522034 lgdp | 1.178864 .068477 17.22 0.000 1.044651 1.313076 lgdpau | 2.161729 2.128605 1.02 0.310 -2.010259 6.333718 lgdpdfrati~w | -2.372315 .8226297 -2.88 0.004 -3.98464 -.7599906 lpopau | -8.507315 7.325608 -1.16 0.246 -22.86524 5.850613 lpop | -.2830922 .0795269 -3.56 0.000 -.4389621 -.1272223 lxrate1 | -.0281447 .0277342 -1.01 0.310 -.0825028 .0262134 lremote | .3304789 .1951034 1.69 0.090 -.0519168 .7128747 ldist | -2.136054 .2318427 -9.21 0.000 -2.590457 -1.681651 lopen | .1564733 .1023403 1.53 0.126 -.0441099 .3570566 english | .8006001 .1928014 4.15 0.000 .4227163 1.178484 white | 3.174803 1.156595 2.74 0.006 .9079187 5.441686 lwhitemg | -.2967086 .1045118 -2.84 0.005 -.5015479 -.0918693 _cons | 84.23781 67.3881 1.25 0.211 -47.84045 216.3161 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003082 lgdp | -.002486 .004689 lgdpau | -.003381 .006152 4.53096 lgdpdfrati~w | -.003469 .002338 -.21369 .67672 lpopau | .012521 -.031147 -15.3614 .968349 53.6645 lpop | .000985 -.004022 -.000869 -.000924 .006093 .006325 lxrate1 | .00004 .000655 .00071 .000345 -.006823 -.001 .000769 lremote | .003829 -.002238 .000281 -.003676 -.023248 .001332 .000803 ldist | .00664 -.005743 -.008818 .012623 .022549 .003133 .002129 lopen | -.000521 .000818 .015584 .003179 -.086137 .001727 -.000223 english | -.004597 .004401 .001421 .011997 .003723 -.004618 .00134 white | .017441 -.018448 .036726 -.10981 -.143962 .011856 -.000169 lwhitemg | -.001557 .001213 -.003153 .009722 .011833 -.000362 .000083 _cons | -.19105 .396883 136.175 -11.2795 -487.958 -.128266 .064616</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .038065 ldist | .023277 .053751 lopen | .00502 .000662 .010474 english | -.015575 -.00031 -.004303 .037172 white | .067437 .00011 -.00423 -.025073 1.33771 lwhitemg | -.003962 .002357 .000571 .002362 -.117802 .010923 _cons | -.161684 -.837887 .935014 .009442 1.05021 -.122143 4541.16 . *3.3. Aggregate Homogenous Exports (liberal) . xtgls lrhomo_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2852.54 Log likelihood = -1514.268 Prob > chi2 = 0.0000</p><p>------lrhomo_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5579087 .0449155 12.42 0.000 .4698759 .6459415 lgdp | 1.096089 .071017 15.43 0.000 .9568984 1.23528 lgdpau | -.503168 .6578349 -0.76 0.444 -1.792501 .7861648 lgdpdfrati~w | -.5355091 .4796883 -1.12 0.264 -1.475681 .4046626 lpopau | 1.921257 2.360785 0.81 0.416 -2.705797 6.548312 lpop | -.16348 .0851865 -1.92 0.055 -.3304424 .0034824 lxrate1 | -.04333 .0306191 -1.42 0.157 -.1033424 .0166824 lremote | -.7131806 .2005785 -3.56 0.000 -1.106307 -.3200541 ldist | -2.025019 .3163476 -6.40 0.000 -2.645049 -1.404989 lopen | .0336908 .0714142 0.47 0.637 -.1062785 .17366 english | .7163412 .2366032 3.03 0.002 .2526076 1.180075 white | 5.939094 2.05901 2.88 0.004 1.903509 9.974679 lwhitemg | -.8247732 .2113489 -3.90 0.000 -1.239009 -.4105369 _cons | -12.94788 23.75858 -0.54 0.586 -59.51384 33.61808 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002017 lgdp | -.002064 .005043 lgdpau | .000018 -.003795 .432747 lgdpdfrati~w | -.003601 .004221 -.056844 .230101 lpopau | .000569 .007642 -1.49801 .295358 5.57331 lpop | .000192 -.003464 .004475 .000687 -.0228 .007257 lxrate1 | -.000377 .000725 .001321 .002882 -.009723 -.000319 .000938 lremote | .001771 .001794 -.030344 .001783 .126743 -.004723 .000205 ldist | .00651 -.009996 -.004958 -.000424 -.000485 .012107 .0005 lopen | .000082 -.000915 .000358 .005188 -.006131 .001806 -.00034 english | -.001146 .001393 .015067 .007946 -.093863 .003296 .002945 white | .009956 -.013993 .036263 -.010068 -.235398 .020993 .00635 lwhitemg | -.000869 .000989 -.004624 .001524 .02743 -.001779 -.00041 _cons | -.051716 -.003058 13.8782 -3.76171 -54.3577 .150997 .103993</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .040232 ldist | .017172 .100076 lopen | -.002628 .000812 .0051 english | -.013018 .017622 -.001233 .055981 white | .009715 .077356 -.002102 .071761 4.23952 lwhitemg | .001433 -.005585 .00006 -.007088 -.429621 .044668 _cons | -1.79964 -.974653 .098335 1.00032 2.01983 -.279917 564.47</p><p>. *IV. Aggregate NON-Manufacturing Exports (Sum of Sitc0,1,2,3,4) . xtgls lrxnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1480.53 Log likelihood = -1099.162 Prob > chi2 = 0.0000</p><p>------lrxnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .480353 .0563726 8.52 0.000 .3698648 .5908413 lgdp | .4872888 .0992525 4.91 0.000 .2927576 .68182 lgdpau | -5.205336 1.276245 -4.08 0.000 -7.70673 -2.703943 lgdpdfrati~w | -2.622431 .548226 -4.78 0.000 -3.696934 -1.547928 lpopau | 14.88814 4.409333 3.38 0.001 6.246009 23.53028 lpop | .0948535 .0844998 1.12 0.262 -.0707631 .26047 lxrate1 | -.0720675 .0359228 -2.01 0.045 -.1424749 -.0016601 lremote | .6005073 .2622352 2.29 0.022 .0865358 1.114479 ldist | -1.152594 .2429733 -4.74 0.000 -1.628813 -.6763747 lopen | .0963956 .1101244 0.88 0.381 -.1194442 .3122354 english | 1.32973 .2266807 5.87 0.000 .8854436 1.774016</p><p> white | 15.02659 1.020276 14.73 0.000 13.02688 17.02629 lwhitemg | -1.584868 .0921326 -17.20 0.000 -1.765445 -1.404292 _cons | -110.2445 41.12043 -2.68 0.007 -190.8391 -29.64997 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003178 lgdp | -.003643 .009851 lgdpau | -.001717 .003546 1.6288 lgdpdfrati~w | -.002784 .004885 -.109698 .300552 lpopau | .01184 -.032573 -5.50595 .453896 19.4422 lpop | .001093 -.006327 .000567 -.002823 .005767 .00714 lxrate1 | -.000624 .001904 .001005 .001776 -.009444 -.001627 .00129 lremote | .000119 .000184 .001235 -.023835 -.01804 .001021 -.00097 ldist | .00933 -.014347 -.004616 -.009447 .0276 .010123 -.003249 lopen | -.000161 -.000599 .009288 .003017 -.058118 .002878 -.00033 english | -.00516 .004723 .003889 .011729 -.020498 .001228 .002941 white | .015857 -.043107 .017926 -.051938 .014521 .041279 -.008167 lwhitemg | -.001796 .003207 -.001887 .002199 .000818 -.003084 .000712 _cons | -.190148 .468168 48.6768 -4.72417 -178.173 -.18068 .14905</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .068767 ldist | .014338 .059036 lopen | .003503 .004329 .012127 english | -.014103 -.007943 -.003103 .051384 white | .026684 .097686 -.002181 .079168 1.04096 lwhitemg | .003968 -.008973 .000287 -.006716 -.087424 .008488 _cons | -.462431 -.889244 .626608 .296832 -1.62299 .07306 1690.89</p><p>. *V. Aggregate Manufacturing Exports (Sum of Sitc5,6,7,8,9) . xtgls lrxmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1152.00 Log likelihood = -968.8814 Prob > chi2 = 0.0000</p><p>------lrxmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2404777 .0497646 4.83 0.000 .1429409 .3380146 lgdp | .4127711 .0996971 4.14 0.000 .2173684 .6081739 lgdpau | -2.627736 1.141729 -2.30 0.021 -4.865483 -.3899885 lgdpdfrati~w | -4.535703 .4774986 -9.50 0.000 -5.471583 -3.599823 lpopau | 10.66951 3.939911 2.71 0.007 2.947428 18.3916 lpop | .0985644 .0912755 1.08 0.280 -.0803323 .277461 lxrate1 | -.0812966 .0269118 -3.02 0.003 -.1340428 -.0285504 lremote | .6656785 .2082351 3.20 0.001 .2575452 1.073812 ldist | -2.434051 .2539923 -9.58 0.000 -2.931866 -1.936235 lopen | -.0825433 .0507806 -1.63 0.104 -.1820714 .0169847 english | .3586313 .1958335 1.83 0.067 -.0251954 .7424579 white | 9.481918 .8211615 11.55 0.000 7.872471 11.09137 lwhitemg | -.8678913 .0692495 -12.53 0.000 -1.003618 -.7321647 _cons | -90.92761 36.75729 -2.47 0.013 -162.9706 -18.88465 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002477 lgdp | -.003119 .00994 lgdpau | -.003617 .007765 1.30354 lgdpdfrati~w | -.003409 .005067 -.046656 .228005 lpopau | .01522 -.037667 -4.40805 .234184 15.5229 lpop | .001461 -.007504 -.003691 -.002461 .017521 .008331 lxrate1 | -.000106 .00099 .000799 .000633 -.006038 -.000888 .000724 lremote | .004336 -.004485 -.007883 -.019861 .005065 .000369 .000028 ldist | .007715 -.011154 -.015342 -.012842 .064033 .005834 -.00023 lopen | -.000067 .000065 .004809 .002065 -.023188 .000509 -.000061 english | -.002106 .002919 .002672 .003246 -.002109 -.001053 .0007 white | .01753 -.039996 -.031557 -.040212 .101769 .043675 -.005479 lwhitemg | -.001249 .001741 .00135 .001475 -.004378 -.002599 .000409 _cons | -.233188 .470097 39.0958 -2.66144 -142.344 -.218341 .070488</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .043362 ldist | .02925 .064512 lopen | .000814 .000508 .002579 english | -.000344 .016359 -.000373 .038351 white | .064444 .076054 .001433 .003246 .674306 lwhitemg | -.002672 -.004358 -.000155 .00044 -.052745 .004795 _cons | -.443354 -1.40741 .237682 -.243508 -2.00433 .110397 1351.1</p><p>. . **VI. SITC-1 Digit Level Disaggregate Exports . xtgls lrxsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 887.00 Log likelihood = -1421.267 Prob > chi2 = 0.0000</p><p>------lrxsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3544488 .08408 4.22 0.000 .1896551 .5192425 lgdp | .3779936 .1397592 2.70 0.007 .1040706 .6519167 lgdpau | -1.71765 1.718305 -1.00 0.317 -5.085466 1.650167 lgdpdfrati~w | -1.868919 .774894 -2.41 0.016 -3.387683 -.3501546 lpopau | 12.01064 5.861653 2.05 0.040 .5220097 23.49927 lpop | .0189555 .1342147 0.14 0.888 -.2441004 .2820114 lxrate1 | -.1874872 .0468076 -4.01 0.000 -.2792283 -.095746 lremote | .984438 .2874446 3.42 0.001 .421057 1.547819 ldist | -1.842973 .4324007 -4.26 0.000 -2.690463 -.9954829 lopen | -.3808094 .1744686 -2.18 0.029 -.7227616 -.0388571 english | 1.436953 .3097783 4.64 0.000 .8297989 2.044107 white | 20.23822 1.814516 11.15 0.000 16.68184 23.79461 lwhitemg | -1.946955 .1705828 -11.41 0.000 -2.281291 -1.612619 _cons | -149.8183 54.26518 -2.76 0.006 -256.1761 -43.46052 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .007069 lgdp | -.009121 .019533 lgdpau | -.008899 .011012 2.95257 lgdpdfrati~w | -.003081 -.000337 .105263 .600461 lpopau | .027031 -.0307 -9.81083 -.109348 34.359 lpop | .003556 -.012589 -.000389 .000818 -.020946 .018014 lxrate1 | .000311 .00119 .000417 .001498 -.000255 -.001839 .002191 lremote | .003497 -.000764 -.035026 -.055494 -.02467 .000957 -.002123 ldist | .019692 -.024183 -.038044 -.024401 .051989 .021089 .000777 lopen | -.000655 -.000461 .016721 -.000168 -.121943 .007135 -.001093 english | -.009227 .006568 .013818 .011307 -.054469 .004645 .003488 white | .0349 -.081173 -.005142 -.062903 -.04189 .084361 .001158 lwhitemg | -.003069 .005587 -.002607 .001701 .001181 -.006122 -.000268 _cons | -.319576 .260144 85.652 -.85895 -312.093 .136881 -.00688</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .082624 ldist | .046217 .18697 lopen | .012315 .006583 .030439 english | -.010979 .01101 -.005447 .095963 white | .050454 .158495 .001818 .118645 3.29247 lwhitemg | .000729 -.012046 .000588 -.008985 -.300246 .029098 _cons | .232613 -1.92713 1.34151 .307479 -.810989 .149312 2944.71</p><p>. xtgls lrxsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 931.92 Log likelihood = -278.8354 Prob > chi2 = 0.0000</p><p>------lrxsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0156039 .0168831 0.92 0.355 -.0174864 .0486942 lgdp | .0514808 .0412113 1.25 0.212 -.0292918 .1322535 lgdpau | -.057266 .3057844 -0.19 0.851 -.6565924 .5420603 lgdpdfrati~w | -.1048626 .1599552 -0.66 0.512 -.4183691 .2086438 lpopau | 3.292454 1.089435 3.02 0.003 1.1572 5.427708 lpop | .2004089 .0513098 3.91 0.000 .0998435 .3009743 lxrate1 | -.0426789 .0146412 -2.91 0.004 -.0713751 -.0139826 lremote | .0892196 .1003407 0.89 0.374 -.1074446 .2858838 ldist | -3.430377 .3369389 -10.18 0.000 -4.090765 -2.769989 lopen | -.0298864 .0281227 -1.06 0.288 -.0850059 .0252331 english | 1.32982 .1619715 8.21 0.000 1.012361 1.647278 white | 19.56623 1.367629 14.31 0.000 16.88573 22.24674 lwhitemg | -1.578605 .1252942 -12.60 0.000 -1.824177 -1.333033 _cons | -24.60161 11.84464 -2.08 0.038 -47.81667 -1.386556 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000285 lgdp | -.000201 .001698 lgdpau | .000281 -.001386 .093504 lgdpdfrati~w | -.00027 .000403 -.006564 .025586 lpopau | -.001773 .006714 -.317496 .034264 1.18687 lpop | -.000044 -.00144 .000433 -.000013 -.004361 .002633 lxrate1 | .000023 -8.9e-06 .000441 .000335 -.003396 .000016 .000214 lremote | .000284 .001268 -.006476 -.001302 .017014 -.000571 .000054 ldist | .001352 .002967 -.007907 -.001971 .033816 -.001516 -.000398 lopen | .000039 -.000103 -.000034 -.000152 -.001784 .000152 -.000022 english | -.000532 .000495 -.000533 -.000417 .008999 .001548 .000082 white | .000923 -.006536 .005905 -.005327 -.042746 .010938 .000297 lwhitemg | -.000127 .000244 -.000542 .000377 .002488 -.000796 .000014 _cons | .010709 -.129539 2.974 -.401068 -11.9312 .072108 .046833</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .010068 ldist | .012632 .113528 lopen | .000056 -.000106 .000791 english | .000614 .025134 -.000467 .026235 white | .005024 .035762 -8.4e-06 .040062 1.87041 lwhitemg | -.000319 -.005494 .000046 -.004388 -.166788 .015699 _cons | -.34081 -1.6025 .031468 -.418833 .134796 .03612 140.295</p><p>. xtgls lrxsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1079.38 Log likelihood = -1318.218 Prob > chi2 = 0.0000</p><p>------lrxsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3022904 .0594172 5.09 0.000 .1858348 .4187459 lgdp | .7529058 .1174641 6.41 0.000 .5226804 .9831311 lgdpau | -5.482432 1.916773 -2.86 0.004 -9.239238 -1.725626 lgdpdfrati~w | -.3445875 .8313767 -0.41 0.679 -1.974056 1.284881 lpopau | 16.72621 6.634317 2.52 0.012 3.723185 29.72923 lpop | -.0227202 .1223966 -0.19 0.853 -.2626131 .2171727 lxrate1 | -.055559 .0367458 -1.51 0.131 -.1275794 .0164614 lremote | -.2077371 .3412296 -0.61 0.543 -.8765348 .4610605 ldist | -2.683376 .4061992 -6.61 0.000 -3.479512 -1.88724 lopen | -.1457665 .1755956 -0.83 0.406 -.4899276 .1983945 english | .0923799 .2658729 0.35 0.728 -.4287214 .6134812 white | 10.4849 1.55216 6.76 0.000 7.442724 13.52708 lwhitemg | -1.208217 .1587799 -7.61 0.000 -1.51942 -.8970143 _cons | -119.7441 61.73904 -1.94 0.052 -240.7504 1.26215 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00353 lgdp | -.00442 .013798 lgdpau | -.003512 .010616 3.67402 lgdpdfrati~w | -.005694 .008128 -.083483 .691187 lpopau | .010714 -.070533 -12.4263 .589883 44.0142 lpop | .001988 -.010331 -.00064 -.005551 .010932 .014981 lxrate1 | -.000353 .002467 .000749 .003151 -.009196 -.001971 .00135 lremote | .00716 -.008501 -.005061 -.053103 -.058775 -.0007 -.003264 ldist | .016073 -.019182 -.010535 -.042413 -.025914 .010384 -.002724 lopen | .000778 .001881 .022455 -.009633 -.173036 .003797 -.001183 english | -.002438 .004485 -.004892 .013358 .049848 -.000881 .002065 white | .029406 -.066665 -.045737 -.044963 .333159 .060455 -.007727 lwhitemg | -.002402 .003903 .001636 -.000721 -.018228 -.004476 .000078 _cons | -.246079 1.01127 109.791 -7.53469 -402.954 -.257133 .157157</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .116438 ldist | .056165 .164998 lopen | .025372 .011726 .030834 english | -.018043 .011926 -.015076 .070688 white | .067473 .170872 -.023851 .105178 2.4092 lwhitemg | .003599 -.014764 .002839 -.01259 -.236058 .025211 _cons | -.210439 -1.11908 1.88208 -.772229 -6.16028 .370695 3811.71</p><p>. xtgls lrxsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 313.48 Log likelihood = -729.3527 Prob > chi2 = 0.0000</p><p>------lrxsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0623045 .0471886 1.32 0.187 -.0301835 .1547925 lgdp | .2653581 .1029164 2.58 0.010 .0636456 .4670706 lgdpau | -.1524024 .8547578 -0.18 0.858 -1.827697 1.522892 lgdpdfrati~w | .2085438 .2893004 0.72 0.471 -.3584745 .7755621 lpopau | -1.6344 2.936325 -0.56 0.578 -7.389491 4.12069 lpop | .5604125 .1148447 4.88 0.000 .335321 .7855041 lxrate1 | .0340186 .0307648 1.11 0.269 -.0262793 .0943164 lremote | .158784 .2839244 0.56 0.576 -.3976976 .7152656 ldist | -1.658349 .548349 -3.02 0.002 -2.733093 -.5836045 lopen | .0214049 .0593605 0.36 0.718 -.0949395 .1377493 english | 1.591309 .3601525 4.42 0.000 .885423 2.297195 white | 14.1344 2.7122 5.21 0.000 8.818582 19.45021 lwhitemg | -1.145175 .2452109 -4.67 0.000 -1.625779 -.6645703 _cons | 31.42677 28.1644 1.12 0.264 -23.77444 86.62797 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002227 lgdp | -.001627 .010592 lgdpau | .002334 -.001158 .730611 lgdpdfrati~w | -.001311 .002628 -.019275 .083695 lpopau | -.014651 -.001622 -2.4439 .070096 8.622 lpop | -.00008 -.00767 -.001627 -.000436 .00433 .013189 lxrate1 | .000166 .000364 .001511 .001729 -.010046 -.000448 .000946 lremote | .001481 .00436 -.041402 -.013749 .133023 -.00375 -.000936 ldist | .007601 -.000257 -.001395 -.00223 -.054617 .007684 .001908 lopen | .00018 -.000536 -.002108 .003869 .003172 .00115 -.000077 english | -.004997 -.005337 .003369 .006496 -.004577 .009745 .001806 white | .004946 -.052606 .061698 -.007275 -.235705 .063947 .001204 lwhitemg | -.000845 .002484 -.009408 -.000556 .039232 -.004464 -.000218 _cons | .125855 -.086868 21.8046 -.650525 -79.6101 -.10454 .109929</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .080613 ldist | .025307 .300687 lopen | -7.1e-06 .000555 .003524 english | -.018128 .050597 -.000533 .12971 white | -.013044 .113086 .004298 .181359 7.35603 lwhitemg | .005192 -.015277 -.000344 -.016831 -.641865 .060128 _cons | -2.09439 -2.31492 -.011233 -.386849 1.4299 -.282146 793.233</p><p>. xtgls lrxsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 262.89 Log likelihood = -834.3199 Prob > chi2 = 0.0000</p><p>------lrxsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0245301 .0429261 0.57 0.568 -.0596036 .1086638 lgdp | .1147569 .0820467 1.40 0.162 -.0460517 .2755654 lgdpau | .0122753 .7696406 0.02 0.987 -1.496193 1.520743 lgdpdfrati~w | -.0184722 .2680807 -0.07 0.945 -.5439008 .5069564 lpopau | .0909823 2.65071 0.03 0.973 -5.104314 5.286279 lpop | .4997694 .10042 4.98 0.000 .3029499 .6965889 lxrate1 | -.0046401 .023067 -0.20 0.841 -.0498506 .0405704 lremote | .7551387 .2198947 3.43 0.001 .324153 1.186124 ldist | -2.484231 .4093117 -6.07 0.000 -3.286468 -1.681995 lopen | .035161 .0544371 0.65 0.518 -.0715336 .1418557 english | .7996364 .3310625 2.42 0.016 .1507658 1.448507 white | -.1738732 1.796653 -0.10 0.923 -3.695249 3.347503 lwhitemg | .1064392 .1830797 0.58 0.561 -.2523904 .4652688 _cons | 5.932634 25.54532 0.23 0.816 -44.13527 56.00054 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001843 lgdp | -.001584 .006732 lgdpau | -.001003 .001566 .592347 lgdpdfrati~w | -.000569 .001053 -.038326 .071867 lpopau | -.00263 -.005104 -1.98058 .125181 7.02626 lpop | .000052 -.004626 -.000124 -.000905 -.009966 .010084 lxrate1 | .000163 .000036 .00008 .00154 -.004687 -.000235 .000532 lremote | .002897 .002544 -.021502 -.008524 .074359 -.003455 -.001009 ldist | .005687 -.004893 -.014144 -.001899 .035178 .002197 .000227 lopen | -.000139 .000268 .002729 .000531 -.011796 .000766 -.000022 english | -.003577 -.003151 .003363 .004497 .00766 .001193 .000723 white | .007368 -.034194 .015912 -.009555 -.130852 .041097 .001593 lwhitemg | -.000736 .001994 -.003544 .000263 .020715 -.002836 -.000203 _cons | .017064 -.002565 17.6457 -1.06259 -65.4366 .123643 .081142</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .048354 ldist | .02512 .167536 lopen | .000623 -.000806 .002963 english | -.018136 .042982 -.001571 .109602 white | -.00055 .063586 -.00069 .124855 3.22796 lwhitemg | .001708 -.006497 .000115 -.012132 -.319781 .033518 _cons | -1.33051 -1.9894 .109984 -.425305 1.21044 -.197678 652.563</p><p>. xtgls lrxsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 820.05 Log likelihood = -1051.134 Prob > chi2 = 0.0000</p><p>------lrxsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2032269 .0679654 2.99 0.003 .0700171 .3364366 lgdp | .6017123 .1207253 4.98 0.000 .3650951 .8383295 lgdpau | -.8101206 .7876398 -1.03 0.304 -2.353866 .7336251 lgdpdfrati~w | -.9887524 .3587895 -2.76 0.006 -1.691967 -.2855379 lpopau | 7.952775 2.665562 2.98 0.003 2.728369 13.17718 lpop | .1000975 .1024533 0.98 0.329 -.1007073 .3009022 lxrate1 | -.1085842 .03275 -3.32 0.001 -.172773 -.0443953 lremote | .7555037 .2001417 3.77 0.000 .3632331 1.147774 ldist | -2.94672 .3143065 -9.38 0.000 -3.562749 -2.33069 lopen | .1617985 .0986544 1.64 0.101 -.0315605 .3551576 english | .9348958 .2640495 3.54 0.000 .4173682 1.452423 white | 12.90671 1.928953 6.69 0.000 9.126027 16.68738 lwhitemg | -1.203031 .1767256 -6.81 0.000 -1.549407 -.8566556 _cons | -100.9164 25.17091 -4.01 0.000 -150.2504 -51.58228 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004619 lgdp | -.005597 .014575 lgdpau | -.004978 .006744 .620377 lgdpdfrati~w | -.000587 -.000375 .036289 .12873 lpopau | .015998 -.022979 -2.01846 -.051996 7.10522 lpop | .002407 -.009086 -.002934 .000339 .001705 .010497 lxrate1 | .000052 .000897 .000583 .000107 -.003708 -.000795 .001073 lremote | .000381 .003097 -.02594 -.022687 .012166 -.001496 .001063 ldist | .010533 -.010631 -.020976 -.006155 .061896 .002785 -.001205 lopen | -.000235 .000308 .002056 .001076 -.032728 .002044 -.000541 english | -.007858 .014983 .007618 .000651 -.024497 -.007074 .000248 white | .022457 -.03916 -.042309 -.025518 .042312 .040845 -.000949 lwhitemg | -.001921 .001841 .001405 .000454 -.002721 -.002415 .000138 _cons | -.176894 .116522 17.5181 .041173 -65.1934 .066794 .036117</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .040057 ldist | .013677 .098789 lopen | .003369 .000996 .009733 english | -.000385 .011213 -.004681 .069722 white | .029894 .050287 -.006663 .04038 3.72086 lwhitemg | -.000095 -.004749 .000555 -.005128 -.331277 .031232 _cons | -.02889 -1.39462 .422169 -.105205 -.244042 .066518 633.575</p><p>. xtgls lrxsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 858.05 Log likelihood = -1132.084 Prob > chi2 = 0.0000</p><p>------lrxsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2958965 .0719711 4.11 0.000 .1548357 .4369574 lgdp | .5898611 .1108013 5.32 0.000 .3726946 .8070276 lgdpau | -.0710792 1.301331 -0.05 0.956 -2.621641 2.479483 lgdpdfrati~w | -1.542605 .6041507 -2.55 0.011 -2.726718 -.358491 lpopau | 3.216231 4.440445 0.72 0.469 -5.486882 11.91934 lpop | .0075974 .1219964 0.06 0.950 -.2315111 .2467059 lxrate1 | -.0711298 .0339438 -2.10 0.036 -.1376584 -.0046012 lremote | 1.15668 .2745008 4.21 0.000 .6186684 1.694692 ldist | -2.035378 .4257915 -4.78 0.000 -2.869914 -1.200842 lopen | -.0916374 .0798516 -1.15 0.251 -.2481438 .0648689 english | 1.39691 .3001377 4.65 0.000 .8086507 1.985169 white | 12.68056 1.518123 8.35 0.000 9.705088 15.65602 lwhitemg | -1.222859 .139619 -8.76 0.000 -1.496507 -.9492108 _cons | -51.48661 41.47314 -1.24 0.214 -132.7725 29.79924 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00518 lgdp | -.005176 .012277 lgdpau | -.006224 .009044 1.69346 lgdpdfrati~w | -.004371 .005062 .037434 .364998 lpopau | .017508 -.028576 -5.61313 .087692 19.7176 lpop | .001539 -.010061 -.003653 -.001637 .004362 .014883 lxrate1 | 5.7e-06 .000682 .001809 .001179 -.010331 -.000628 .001152 lremote | .004109 -.002811 -.030205 -.048884 -.006223 -.000826 .000209 ldist | .01481 -.014228 -.029206 -.023728 .062206 .007906 -.000727 lopen | -.000468 .000517 .003459 .001363 -.027515 .00108 -.000175 english | -.007857 .008602 .01036 .00821 -.032048 -.000126 .000759 white | .025085 -.055608 -.047166 -.042871 .035753 .065301 -.001158 lwhitemg | -.002301 .003487 .001844 -.000132 -.004674 -.004357 .000246 _cons | -.237526 .299547 49.0714 -2.24045 -180.053 -.05697 .117837 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .075351 ldist | .038303 .181298 lopen | .002625 .001021 .006376 english | -.00378 .033416 -.001396 .090083 white | .072391 .121049 -.003788 .047025 2.3047 lwhitemg | -.001083 -.01085 .000301 -.00446 -.203977 .019493 _cons | -.023555 -2.2005 .31216 -.202877 -1.05122 .14776 1720.02</p><p>. xtgls lrxsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 452.24 Log likelihood = -1195.732 Prob > chi2 = 0.0000</p><p>------lrxsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2441514 .0514854 4.74 0.000 .1432419 .3450609 lgdp | .3296667 .0939244 3.51 0.000 .1455782 .5137552 lgdpau | -2.542793 1.514078 -1.68 0.093 -5.510331 .4247451 lgdpdfrati~w | -2.644245 .6714795 -3.94 0.000 -3.960321 -1.32817 lpopau | 7.917048 5.179871 1.53 0.126 -2.235312 18.06941 lpop | .1428397 .0758686 1.88 0.060 -.0058601 .2915395 lxrate1 | -.1072327 .0371768 -2.88 0.004 -.1800979 -.0343676 lremote | 1.562587 .2362191 6.61 0.000 1.099606 2.025568 ldist | -.6834555 .2906372 -2.35 0.019 -1.253094 -.1138171 lopen | .0821467 .1193843 0.69 0.491 -.1518422 .3161356 english | .6000499 .1870372 3.21 0.001 .2334637 .9666362 white | 7.089776 1.148162 6.17 0.000 4.83942 9.340132 lwhitemg | -.5565431 .1147117 -4.85 0.000 -.7813739 -.3317124 _cons | -73.92699 47.82328 -1.55 0.122 -167.6589 19.80492 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002651 lgdp | -.002427 .008822 lgdpau | -.004124 .00723 2.29243 lgdpdfrati~w | -.001729 .00123 .061581 .450885 lpopau | .014891 -.038155 -7.67038 -.024028 26.8311 lpop | -.000068 -.00425 .000575 .000183 .000073 .005756 lxrate1 | .000204 .001355 .000988 .000578 -.006887 -.001562 .001382 lremote | .000659 -.000451 -.017611 -.03586 .017068 -.000975 -.000844 ldist | .005884 -.003169 -.004954 -.000281 .015632 .004679 -.000474 lopen | -.000409 .000945 .011156 .002357 -.071346 .002617 -.000397 english | -.003919 .007168 .009509 .008984 -.030931 -.000378 .001093 white | .00997 -.021261 -.016302 -.033326 .052037 .020571 -.004643 lwhitemg | -.001083 .000406 -.000922 -.000623 .002906 -.001284 .000161 _cons | -.159126 .3518 67.0899 -1.39788 -243.503 -.039141 .087713</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .055799 ldist | -.005727 .08447 lopen | .004589 .002158 .014253 english | -.011804 -.001911 -.001996 .034983 white | .022389 .035265 .001509 .025365 1.31828 lwhitemg | .003058 -.006775 -.000291 -.003621 -.12352 .013159 _cons | -.187915 -.917355 .780387 .222687 -.845146 .03355 2287.07</p><p>. xtgls lrxsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 650.80 Log likelihood = -975.6998 Prob > chi2 = 0.0000</p><p>------lrxsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2195433 .0548988 4.00 0.000 .1119436 .3271429 lgdp | .5436705 .0934338 5.82 0.000 .3605437 .7267972 lgdpau | -1.111581 1.307677 -0.85 0.395 -3.674581 1.451419 lgdpdfrati~w | -1.399282 .5453073 -2.57 0.010 -2.468064 -.3304988 lpopau | 3.528831 4.48859 0.79 0.432 -5.268645 12.32631 lpop | .0064285 .1019866 0.06 0.950 -.1934616 .2063187 lxrate1 | -.0620488 .0355615 -1.74 0.081 -.1317482 .0076505 lremote | .2148491 .2732615 0.79 0.432 -.3207337 .7504319 ldist | -2.266736 .4818035 -4.70 0.000 -3.211054 -1.322419 lopen | .0099982 .1004493 0.10 0.921 -.1868789 .2068752 english | .5094262 .1962514 2.60 0.009 .1247806 .8940718 white | 11.60113 1.701913 6.82 0.000 8.265442 14.93682 lwhitemg | -1.142506 .1522805 -7.50 0.000 -1.440971 -.8440417 _cons | -17.52056 42.11804 -0.42 0.677 -100.0704 65.02928 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003014 lgdp | -.003009 .00873 lgdpau | -.003758 .007087 1.71002 lgdpdfrati~w | -.001776 .002092 -.024617 .29736 lpopau | .013545 -.030954 -5.73384 .17375 20.1474 lpop | -.000114 -.00567 -.001764 -.000187 .004157 .010401 lxrate1 | .000023 .001328 .001752 .000851 -.009367 -.001501 .001265 lremote | .0053 -.006141 -.018409 -.029056 .039653 .00082 -.000898 ldist | .013037 -.011999 -.025342 -.019242 .073037 .007753 -.001286 lopen | -.000225 .00022 .004812 .00343 -.042249 .002199 -.000286 english | -.001594 .004388 .004022 .000679 -.010063 -.002348 .00194 white | .016465 -.037385 .005821 -.027646 .011225 .041249 -.005001 lwhitemg | -.001332 .001778 -.002214 -.000093 .00488 -.00281 .000299 _cons | -.242674 .398207 50.5685 -2.14172 -184.558 -.133585 .117907</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .074672 ldist | .053179 .232135 lopen | .00551 .000997 .01009 english | -.004928 .017686 -.002993 .038515 white | .061089 .159392 .000058 .038254 2.89651 lwhitemg | -.000264 -.014711 .00005 -.004009 -.250914 .023189 _cons | -1.20457 -3.1381 .485236 -.138779 -2.28568 .13353 1773.93</p><p>. xtgls lrxsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 918.08 Log likelihood = -1566.352 Prob > chi2 = 0.0000</p><p>------lrxsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4712881 .067569 6.97 0.000 .3388552 .603721 lgdp | .1973692 .1245384 1.58 0.113 -.0467215 .4414599 lgdpau | -2.945893 1.792394 -1.64 0.100 -6.458921 .5671351 lgdpdfrati~w | -1.326158 .6104553 -2.17 0.030 -2.522629 -.129688 lpopau | 20.71871 6.122 3.38 0.001 8.719812 32.71761 lpop | .4930216 .1225043 4.02 0.000 .2529175 .7331257 lxrate1 | -.1446367 .0443715 -3.26 0.001 -.2316033 -.0576701 lremote | .8182386 .3102645 2.64 0.008 .2101314 1.426346 ldist | -1.66294 .4355229 -3.82 0.000 -2.516549 -.8093311 lopen | -.1050184 .1367173 -0.77 0.442 -.3729795 .1629426 english | .2316968 .2724813 0.85 0.395 -.3023568 .7657504 white | 17.77087 2.663555 6.67 0.000 12.5504 22.99134 lwhitemg | -1.676958 .2591213 -6.47 0.000 -2.184826 -1.169089 _cons | -267.3569 56.67847 -4.72 0.000 -378.4447 -156.2692 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004566 lgdp | -.005135 .01551 lgdpau | -.006184 .007594 3.21268 lgdpdfrati~w | -.001857 .002555 -.035447 .372656 lpopau | .017964 -.031869 -10.7297 .151636 37.4789 lpop | .001518 -.010606 -.002089 -.001277 -.000331 .015007 lxrate1 | .000051 .001662 -.000921 .003335 -.005576 -.001519 .001969 lremote | .004994 .000421 -.042742 -.017827 .026932 -.000767 .001712 ldist | .015049 -.010219 -.032899 -.002248 .083388 .008609 -.000873 lopen | -.000413 -.000583 .007432 .008526 -.048827 .00385 -.000232 english | -.005592 .010395 .012096 -.000077 -.055101 -.004869 .000803 white | .015612 -.041709 -.054114 -.044179 -.174649 .053477 .009376 lwhitemg | -.001244 .001525 .000681 .001302 .019282 -.002722 -.000899 _cons | -.255598 .259231 94.3299 -1.81831 -340.944 -.012896 .085088</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .096264 ldist | .04585 .18968 lopen | .00585 .005009 .018692 english | -.014637 .016666 -.003793 .074246 white | .128979 -.059717 -.003118 -.025313 7.09453 lwhitemg | -.004968 .006347 .000568 .002118 -.680411 .067144 _cons | -.604787 -2.71848 .476579 .411955 3.76471 -.336228 3212.45</p><p>. clear</p><p>. *Estimating the Australian Immigration Trade relationship; . insheet using k:\book2.txt (54 vars, 11640 obs)</p><p>. drop if ccode ==. (10630 observations deleted)</p><p>. </p><p>. **Dropping Spain . drop if ccode==117100 (10 observations deleted)</p><p>. ** Estimation Results . **Regression of Exports without Distinction between "white" and "non-white Aus > tralia" . tsset ccode year panel variable: ccode, 130120 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Exports . xtgls lrexp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote 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) = 6784.09 Log likelihood = -1026.242 Prob > chi2 = 0.0000</p><p>------lrexp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5440067 .0380616 14.29 0.000 .4694074 .618606 lgdp | 1.049129 .0378771 27.70 0.000 .9748914 1.123367 lgdpau | -3.395767 .8967897 -3.79 0.000 -5.153443 -1.638092 lgdpdfrati~w | -1.886306 .3450712 -5.47 0.000 -2.562633 -1.209979 lpopau | 4.670997 3.125022 1.49 0.135 -1.453933 10.79593 lpop | .0002082 .0412672 0.01 0.996 -.0806741 .0810905 lxrate1 | -.0008828 .0146479 -0.06 0.952 -.0295922 .0278266 lremote | .1292543 .0850121 1.52 0.128 -.0373662 .2958749 ldist | -1.369566 .1434194 -9.55 0.000 -1.650663 -1.088469 lopen | .8870095 .0800376 11.08 0.000 .7301387 1.04388 english | .1880924 .0953372 1.97 0.049 .001235 .3749499 white | 3.212747 .6023321 5.33 0.000 2.032198 4.393296 lwhitemg | -.393954 .0538731 -7.31 0.000 -.4995433 -.2883648 _cons | 6.264952 28.97925 0.22 0.829 -50.53334 63.06325 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001449 lgdp | -.000819 .001435 lgdpau | -.003191 .002775 .804232 lgdpdfrati~w | .000685 -.000994 -.026576 .119074 lpopau | .01223 -.011542 -2.75834 .145961 9.76576 lpop | .000049 -.000721 .000735 -.000228 -.006026 .001703 lxrate1 | 8.4e-06 .000178 -5.2e-07 .000031 -.000361 -.000042 .000215 lremote | -.000404 .0013 .004742 -.002476 -.025399 .000031 .000076 ldist | .00347 -.001885 -.005245 .003505 .011561 .001816 .000571 lopen | -.000605 .000397 .010984 -.001256 -.059031 .000863 -.000057 english | -.000725 .001542 -.002526 .000639 .016397 -.000998 .000485 white | .006939 -.00108 -.007218 -.012342 .006999 .008461 .002062 lwhitemg | -.000779 .000141 .000847 .000806 -.001297 -.000745 -.00018 _cons | -.143037 .10922 24.6563 -1.84231 -89.4994 .053578 -.004642</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .007227 ldist | .002222 .020569 lopen | .002334 .000677 .006406 english | .000298 .001734 -.002988 .009089 white | .014466 .031038 -.001892 .004298 .362804 lwhitemg | -.001012 -.003168 .000161 -.000161 -.032019 .002902 _cons | .187842 -.286792 .654578 -.248609 -.525847 .054308 839.797</p><p>. **II. Conservative Estimates . *2.1. Aggregate reference priced Exports (conservative) . xtgls lrrefp_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 6879.56 Log likelihood = -1462.905 Prob > chi2 = 0.0000</p><p>------lrrefp_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3516599 .0461572 7.62 0.000 .2611935 .4421263 lgdp | 1.084302 .06756 16.05 0.000 .9518869 1.216717 lgdpau | -.4171246 .4981709 -0.84 0.402 -1.393522 .5592724 lgdpdfrati~w | -.26198 .3002394 -0.87 0.383 -.8504383 .3264784 lpopau | 3.41142 1.799027 1.90 0.058 -.1146086 6.937449 lpop | .0232747 .094473 0.25 0.805 -.161889 .2084383 lxrate1 | -.0448421 .0299872 -1.50 0.135 -.103616 .0139318 lremote | -.2567403 .1655337 -1.55 0.121 -.5811804 .0676998 ldist | -3.162508 .3843054 -8.23 0.000 -3.915732 -2.409283 lopen | -.0729427 .0544189 -1.34 0.180 -.1796017 .0337163 english | .5889125 .1803005 3.27 0.001 .23553 .942295 white | 7.614282 1.439839 5.29 0.000 4.79225 10.43631 lwhitemg | -.8368683 .1468353 -5.70 0.000 -1.12466 -.5490763 _cons | -35.46279 18.18627 -1.95 0.051 -71.10723 .1816469 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00213 lgdp | -.001642 .004564 lgdpau | .001159 -.001489 .248174 lgdpdfrati~w | -.001979 .003287 -.024519 .090144 lpopau | -.00514 .004285 -.86231 .109955 3.2365 lpop | -.000071 -.004804 .003686 -.001494 -.019734 .008925 lxrate1 | .000134 .000377 .000579 .002688 -.006187 -.000551 .000899 lremote | .000122 .000273 -.021768 .002882 .092601 -.00351 .000642 ldist | .009122 -.010568 .00389 .00178 -.029084 .005195 .002031 lopen | .000045 -.000254 .002533 .001121 -.011588 .001154 -.000384 english | -.001185 -.001323 .00601 .004146 -.045341 .003037 .001577 white | .010406 -.026587 .022081 -.008318 -.153583 .03343 .001479 lwhitemg | -.001517 .002094 -.004506 .001007 .022745 -.002176 -.000108 _cons | -.004568 .042884 7.94363 -1.36666 -31.4643 .183875 .055899</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .027401 ldist | .003451 .147691 lopen | -.002122 .000868 .002961 english | -.00472 .000198 -.000677 .032508 white | -.009335 .052829 .002196 .044347 2.07314 lwhitemg | .003858 -.006716 -.000561 -.002318 -.206008 .021561 _cons | -1.19759 -.959691 .125607 .60015 1.548 -.234117 330.74</p><p>. *2.2. Aggregate Differentiated Exports (conservative) . xtgls lrdiff_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3559.96 Log likelihood = -1570.867 Prob > chi2 = 0.0000</p><p>------lrdiff_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4543023 .0543294 8.36 0.000 .3478186 .560786 lgdp | 1.100545 .0630238 17.46 0.000 .9770201 1.224069 lgdpau | 2.092585 2.134759 0.98 0.327 -2.091466 6.276636 lgdpdfrati~w | -2.680077 .8526034 -3.14 0.002 -4.351149 -1.009005 lpopau | -8.180239 7.353562 -1.11 0.266 -22.59296 6.232479 lpop | -.1839565 .0799315 -2.30 0.021 -.3406194 -.0272936 lxrate1 | -.0710878 .0281759 -2.52 0.012 -.1263115 -.0158642 lremote | -.0306959 .1998851 -0.15 0.878 -.4224634 .3610716 ldist | -2.337047 .2348963 -9.95 0.000 -2.797435 -1.876659 lopen | .0868625 .0896679 0.97 0.333 -.0888834 .2626083 english | .694919 .1810427 3.84 0.000 .3400818 1.049756 white | 1.948514 1.079101 1.81 0.071 -.1664853 4.063512 lwhitemg | -.2097123 .0983609 -2.13 0.033 -.4024961 -.0169285 _cons | 86.42827 67.64437 1.28 0.201 -46.15226 219.0088 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002952 lgdp | -.002038 .003972 lgdpau | -.002592 .005951 4.5572 lgdpdfrati~w | -.003609 .001506 -.232868 .726933 lpopau | .008392 -.028244 -15.4735 1.09539 54.0749 lpop | .000208 -.003387 -.001027 .001336 .006726 .006389 lxrate1 | .000202 .000475 .001061 -.000562 -.00789 -.000818 .000794 lremote | .004116 -.002548 .005602 -.004301 -.036142 -.000217 .000917 ldist | .006586 -.005941 -.005194 .01357 .011364 .002816 .002887 lopen | -.000398 .000734 .017154 .003673 -.082129 .001149 -.000125 english | -.003146 .00249 -.001296 .009734 .013178 -.003214 .001256 white | .019052 -.019472 .021944 -.101684 -.10574 .0124 .001851 lwhitemg | -.001744 .001297 -.001583 .008863 .0078 -.000387 -.000098 _cons | -.143035 .363933 137.289 -12.9581 -491.785 -.132784 .06589 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .039954 ldist | .021378 .055176 lopen | .004006 .000612 .00804 english | -.014354 .001935 -.003242 .032776 white | .065246 .028963 -.003124 -.012959 1.16446 lwhitemg | -.003492 -.000506 .000413 .001157 -.102751 .009675 _cons | -.057131 -.739498 .843425 -.090551 .53578 -.072013 4575.76</p><p>. *2.3. Aggregate Homogenous Exports (conservative) . xtgls lrhomo_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1859.13 Log likelihood = -1618.966 Prob > chi2 = 0.0000</p><p>------lrhomo_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4533009 .0523657 8.66 0.000 .3506661 .5559357 lgdp | .9544054 .0960758 9.93 0.000 .7661002 1.142711 lgdpau | -.0516536 1.079143 -0.05 0.962 -2.166734 2.063427 lgdpdfrati~w | -.2706382 .4595492 -0.59 0.556 -1.171338 .6300616 lpopau | -5.975261 3.694478 -1.62 0.106 -13.21631 1.265783 lpop | .1547662 .1080043 1.43 0.152 -.0569184 .3664508 lxrate1 | .0518746 .0371946 1.39 0.163 -.0210254 .1247746 lremote | -1.075712 .2306394 -4.66 0.000 -1.527757 -.6236668 ldist | -1.772528 .4894612 -3.62 0.000 -2.731855 -.8132018 lopen | .0467989 .0950196 0.49 0.622 -.1394361 .233034 english | .9700463 .296094 3.28 0.001 .3897128 1.55038 white | 12.8321 2.552164 5.03 0.000 7.829951 17.83425 lwhitemg | -1.510331 .2723173 -5.55 0.000 -2.044063 -.9765991 _cons | 105.2357 34.81346 3.02 0.003 37.00263 173.4689 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002742 lgdp | -.002951 .009231 lgdpau | .005866 -.010875 1.16455 lgdpdfrati~w | -.003599 .007565 -.054577 .211185 lpopau | -.022902 .024325 -3.86803 .277312 13.6492 lpop | .000337 -.005835 .000531 -.002933 -.001764 .011665 lxrate1 | -.000122 .001173 .003016 .002741 -.019323 -.001356 .001383 lremote | .000315 .008378 -.036587 .012082 .101018 -.006642 .000567 ldist | .014159 -.010524 .023696 -.005132 -.15144 .013514 .002343 lopen | .000015 -.001115 -.01988 .006478 .048843 .002158 -.000299 english | -.00238 .00358 .01802 .004442 -.088708 .005153 .003025 white | .010857 -.025909 .096071 -.012324 -.417103 .03127 .00387 lwhitemg | -.001251 .001726 -.010535 .001408 .045782 -.002413 -.000241 _cons | .138577 -.20167 33.9328 -3.56139 -125.005 -.103247 .201986</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .053195 ldist | .024642 .239572 lopen | .001488 -.001478 .009029 english | -.01461 .017408 -.003656 .087672 white | -.014587 .048091 -.000216 .112684 6.51354 lwhitemg | .003201 -.006483 .000337 -.011526 -.689663 .074157 _cons | -1.50439 -.662569 -.294496 .77638 4.06237 -.44098 1211.98</p><p>. **III. Liberal Estimates . *3.1. Aggregate reference priced Exports (liberal) . xtgls lrrefp_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1770.98 Log likelihood = -1461.692 Prob > chi2 = 0.0000</p><p>------lrrefp_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3809152 .0479895 7.94 0.000 .2868575 .4749728 lgdp | .8909148 .0822246 10.84 0.000 .7297576 1.052072 lgdpau | -.3569238 .466389 -0.77 0.444 -1.271029 .557182 lgdpdfrati~w | .1603397 .2419484 0.66 0.508 -.3138705 .6345499 lpopau | -1.993673 1.656688 -1.20 0.229 -5.240722 1.253375 lpop | .1675935 .0998013 1.68 0.093 -.0280134 .3632004 lxrate1 | -.0175293 .0273206 -0.64 0.521 -.0710767 .036018 lremote | -.2246127 .1559531 -1.44 0.150 -.5302751 .0810497 ldist | -2.303494 .471905 -4.88 0.000 -3.228411 -1.378577 lopen | .0308987 .0487068 0.63 0.526 -.0645649 .1263623 english | .9670643 .2446549 3.95 0.000 .4875494 1.446579 white | 10.34878 2.145873 4.82 0.000 6.142943 14.55461 lwhitemg | -1.048854 .2103642 -4.99 0.000 -1.46116 -.636548 _cons | 45.46898 16.74026 2.72 0.007 12.65868 78.27928 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002303 lgdp | -.002451 .006761 lgdpau | .001327 -.003917 .217519 lgdpdfrati~w | -.001904 .004459 -.022614 .058539 lpopau | -.006275 .013584 -.749971 .096852 2.74461 lpop | .000658 -.00572 .005024 -.003464 -.025321 .00996 lxrate1 | .000125 .00005 .001482 .001539 -.007958 -.0002 .000746 lremote | .000802 .000176 -.019943 .001789 .07645 -.00301 .000099 ldist | .007215 -.010475 .001605 -.00159 -.023601 .00891 .00233 lopen | -.000041 -.000024 .002001 .000963 -.008914 .000709 -.000152 english | -.002036 .000541 .008533 .004157 -.033153 .001368 .001855 white | .010164 -.030569 .024777 -.00599 -.135878 .035332 .010011 lwhitemg | -.001152 .002003 -.003486 .000458 .017594 -.002242 -.000874 _cons | .027955 -.079396 6.9147 -1.11904 -26.2533 .202347 .066415</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .024321 ldist | .010458 .222694 lopen | -.00161 -.000702 .002372 english | -.006579 .026884 -.000352 .059856 white | .031498 -.156925 -.00416 .018541 4.60477 lwhitemg | -.001036 .017238 .000184 .000027 -.446001 .044253 _cons | -1.0213 -1.83192 .106935 .073945 2.85963 -.357002 280.236 . *3.2. Aggregate Differentiated Exports (liberal) . xtgls lrdiff_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3311.03 Log likelihood = -1587.921 Prob > chi2 = 0.0000</p><p>------lrdiff_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4143933 .0573828 7.22 0.000 .3019251 .5268615 lgdp | 1.199314 .0696658 17.22 0.000 1.062772 1.335857 lgdpau | 1.708753 2.225432 0.77 0.443 -2.653013 6.07052 lgdpdfrati~w | -2.82231 .855549 -3.30 0.001 -4.499155 -1.145464 lpopau | -7.1469 7.663954 -0.93 0.351 -22.16797 7.874175 lpop | -.2917183 .0816648 -3.57 0.000 -.4517784 -.1316581 lxrate1 | -.0342717 .0283782 -1.21 0.227 -.089892 .0213486 lremote | .0935894 .195622 0.48 0.632 -.2898228 .4770015 ldist | -2.299945 .2342985 -9.82 0.000 -2.759161 -1.840728 lopen | .1159482 .0989866 1.17 0.241 -.078062 .3099584 english | .8304276 .1969713 4.22 0.000 .4443708 1.216484 white | 1.894978 1.061692 1.78 0.074 -.1859003 3.975857 lwhitemg | -.1980939 .0972524 -2.04 0.042 -.3887052 -.0074827 _cons | 77.52723 70.48387 1.10 0.271 -60.61862 215.6731 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003293 lgdp | -.002629 .004853 lgdpau | -.003451 .006951 4.95255 lgdpdfrati~w | -.00398 .002725 -.243004 .731964 lpopau | .012196 -.033378 -16.8102 1.11305 58.7362 lpop | .000918 -.004124 -.001149 -.000802 .00771 .006669 lxrate1 | .000033 .000664 .001014 .000295 -.008334 -.000989 .000805 lremote | .003762 -.002508 .003041 -.00258 -.027812 .001182 .000643 ldist | .006799 -.006111 -.006678 .013713 .014882 .003328 .002305 lopen | -.000518 .000805 .018309 .004142 -.091198 .001541 -.000175 english | -.00479 .004661 .001098 .012949 .001385 -.004832 .001602 white | .018592 -.021172 .008766 -.090974 -.039565 .015382 -.000337 lwhitemg | -.001725 .001458 -.000543 .008154 .002275 -.000619 .000103 _cons | -.180977 .41696 149.124 -13.0002 -534.11 -.151473 .080932</p><p>| lremote ldist lopen english white lwhitemg _cons</p><p>------+------lremote | .038268 ldist | .021669 .054896 lopen | .004523 .000677 .009798 english | -.015359 .000607 -.00361 .038798 white | .05996 .011345 -.004233 -.022286 1.12719 lwhitemg | -.003222 .001238 .00055 .002159 -.099895 .009458 _cons | -.137487 -.761597 .952729 .043032 -.01085 -.0268 4967.98</p><p>. *3.3. Aggregate Homogenous Exports (liberal) . xtgls lrhomo_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2987.44 Log likelihood = -1555.152 Prob > chi2 = 0.0000</p><p>------lrhomo_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5614843 .0439744 12.77 0.000 .4752962 .6476725 lgdp | 1.090749 .0683784 15.95 0.000 .9567298 1.224768 lgdpau | -.3999709 .6630786 -0.60 0.546 -1.699581 .8996393 lgdpdfrati~w | -.5237668 .4949771 -1.06 0.290 -1.493904 .4463705 lpopau | 1.92806 2.39012 0.81 0.420 -2.75649 6.61261 lpop | -.1704265 .0833386 -2.04 0.041 -.3337672 -.0070858 lxrate1 | -.0448918 .0302735 -1.48 0.138 -.1042267 .0144432 lremote | -.7045044 .1931615 -3.65 0.000 -1.083094 -.3259149 ldist | -2.051287 .3106605 -6.60 0.000 -2.66017 -1.442404 lopen | .0246605 .0711225 0.35 0.729 -.114737 .164058 english | .7340104 .2331157 3.15 0.002 .2771121 1.190909 white | 5.70156 2.066753 2.76 0.006 1.650797 9.752322 lwhitemg | -.8000026 .2115898 -3.78 0.000 -1.214711 -.3852944 _cons | -15.45662 24.09741 -0.64 0.521 -62.68668 31.77344 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001934 lgdp | -.001885 .004676 lgdpau | .000168 -.003404 .439673 lgdpdfrati~w | -.003575 .004166 -.062621 .245002 lpopau | -.000344 .006426 -1.52701 .328063 5.71268 lpop | .000088 -.003244 .004085 .00063 -.021445 .006945 lxrate1 | -.000344 .000703 .001341 .002851 -.010003 -.000312 .000916 lremote | .001574 .00148 -.028716 .004517 .123721 -.004369 .000169 ldist | .006426 -.009058 -.003432 .001111 -.006632 .010714 .000726 lopen | .000077 -.000838 -.000044 .005644 -.004054 .001737 -.000326 english | -.001228 .001277 .015829 .006852 -.099069 .003357 .002973 white | .008389 -.012688 .029555 -.008317 -.207335 .019632 .005788 lwhitemg | -.000769 .000867 -.003858 .001394 .024367 -.001605 -.000393 _cons | -.039857 .00458 14.1514 -4.20491 -55.8466 .14942 .106582</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .037311 ldist | .015123 .09651 lopen | -.002178 .001014 .005058 english | -.013518 .015875 -.001264 .054343 white | .00348 .062586 -.001866 .068657 4.27147 lwhitemg | .001827 -.004678 .000049 -.006741 -.431806 .04477 _cons | -1.74737 -.860283 .067396 1.09161 1.92746 -.26194 580.685</p><p>. *IV. Aggregate NON-Manufacturing Exports (Sum of Sitc0,1,2,3,4) . xtgls lrxnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1190.84 Log likelihood = -1127.405 Prob > chi2 = 0.0000</p><p>------lrxnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4053538 .0581863 6.97 0.000 .2913108 .5193968 lgdp | .6229132 .0986724 6.31 0.000 .4295188 .8163075 lgdpau | -5.0378 1.300958 -3.87 0.000 -7.587631 -2.487969 lgdpdfrati~w | -2.272772 .5555174 -4.09 0.000 -3.361566 -1.183977 lpopau | 14.35527 4.496228 3.19 0.001 5.542822 23.16771 lpop | -.0397074 .0903535 -0.44 0.660 -.216797 .1373821 lxrate1 | -.046974 .0350992 -1.34 0.181 -.1157671 .0218192 lremote | -.1105986 .2908993 -0.38 0.704 -.6807507 .4595536 ldist | -1.738066 .2502982 -6.94 0.000 -2.228641 -1.24749 lopen | .0458922 .1126628 0.41 0.684 -.1749228 .2667072 english | 1.25365 .2244616 5.59 0.000 .8137139 1.693587 white | 12.63631 1.033962 12.22 0.000 10.60979 14.66284 lwhitemg | -1.428486 .092803 -15.39 0.000 -1.610377 -1.246596 _cons | -95.00072 41.96567 -2.26 0.024 -177.2519 -12.74951 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003386 lgdp | -.003612 .009736 lgdpau | -.002077 .004823 1.69249 lgdpdfrati~w | -.002728 .005133 -.110646 .3086 lpopau | .012164 -.037316 -5.71751 .46011 20.2161 lpop | .000647 -.006033 -.000285 -.002514 .007394 .008164 lxrate1 | -.000544 .001924 .000931 .001103 -.009052 -.001695 .001232 lremote | .001133 -.001164 .001865 -.027731 -.027196 .001091 .000366 ldist | .009679 -.012671 -.005609 -.009386 .026647 .00702 -.002717 lopen | .000139 -.000424 .009185 .002736 -.060805 .002905 -.000433 english | -.005276 .007625 .003362 .008894 -.016877 -.001466 .002532 white | .015532 -.036751 .014048 -.062786 .015919 .038376 -.007723 lwhitemg | -.001702 .002436 -.00168 .002335 .001169 -.002649 .000738 _cons | -.193578 .506371 50.5072 -4.78328 -185.309 -.176783 .128854</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .084622 ldist | .018556 .062649 lopen | .006257 .004733 .012693 english | -.010935 -.005504 -.005776 .050383 white | .055117 .094278 -.00342 .065785 1.06908 lwhitemg | .003574 -.008707 .000467 -.006385 -.087615 .008612 _cons | -.486765 -.912498 .64155 .182643 -1.84868 .07245 1761.12</p><p>. *V. Aggregate Manufacturing Exports (Sum of Sitc5,6,7,8,9)</p><p>. xtgls lrxmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1129.27 Log likelihood = -975.1693 Prob > chi2 = 0.0000</p><p>------lrxmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2383561 .043321 5.50 0.000 .1534485 .3232638 lgdp | .3553888 .0919308 3.87 0.000 .1752078 .5355698 lgdpau | -2.514708 1.125919 -2.23 0.026 -4.72147 -.307947 lgdpdfrati~w | -4.611649 .4692608 -9.83 0.000 -5.531383 -3.691914 lpopau | 9.215033 3.889169 2.37 0.018 1.592401 16.83767 lpop | .1285924 .0765284 1.68 0.093 -.0214004 .2785853 lxrate1 | -.07681 .0280597 -2.74 0.006 -.1318059 -.0218141 lremote | .5464808 .1745202 3.13 0.002 .2044276 .888534 ldist | -2.424396 .2227633 -10.88 0.000 -2.861004 -1.987788 lopen | -.0845064 .0519694 -1.63 0.104 -.1863646 .0173518 english | .4348486 .1683291 2.58 0.010 .1049296 .7647676 white | 9.132958 1.007786 9.06 0.000 7.157734 11.10818 lwhitemg | -.8212941 .090769 -9.05 0.000 -.999198 -.6433901 _cons | -67.76106 36.21924 -1.87 0.061 -138.7495 3.227336 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001877 lgdp | -.00272 .008451 lgdpau | -.002756 .006301 1.26769 lgdpdfrati~w | -.002292 .005573 -.049639 .220206 lpopau | .012602 -.034072 -4.29228 .245197 15.1256 lpop | .001862 -.00613 -.00285 -.004535 .015521 .005857 lxrate1 | -.000164 .001202 .000865 .000859 -.007167 -.000979 .000787 lremote | .001673 -.003983 -.003188 -.0144 -.011167 .004685 -.00043 ldist | .005283 -.009211 -.011386 -.009359 .051446 .008097 -.001003 lopen | -.000122 .000277 .005064 .002139 -.023883 .000511 -.000082 english | -.002569 .003768 .001782 .002536 -.001191 -.000375 .000098 white | .016236 -.034852 -.021496 -.040845 .083411 .037734 -.006118 lwhitemg | -.001257 .001621 .000953 .001176 -.00452 -.002217 .000363 _cons | -.179023 .434807 38.056 -2.8232 -138.573 -.258372 .095722</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .030457 ldist | .018291 .049623 lopen | .00081 .000199 .002701 english | -.002651 .00796 -.000887 .028335 white | .066193 .076724 .001133 .010531 1.01563 lwhitemg | -.003002 -.005214 -.000205 -.000833 -.087275 .008239 _cons | -.150069 -1.13164 .241278 -.158156 -2.00143 .131666 1311.83</p><p>. . **VI. SITC-1 Digit Level Disaggregate Exports . xtgls lrxsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 754.23 Log likelihood = -1438.98 Prob > chi2 = 0.0000 ------lrxsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3181441 .0870506 3.65 0.000 .1475281 .48876 lgdp | .3903041 .1427682 2.73 0.006 .1104835 .6701247 lgdpau | -.9206505 1.278501 -0.72 0.471 -3.426467 1.585166 lgdpdfrati~w | -.9107606 .6176078 -1.47 0.140 -2.12125 .2997284 lpopau | 10.30774 4.334067 2.38 0.017 1.813123 18.80235 lpop | -.0870173 .1375084 -0.63 0.527 -.3565289 .1824942 lxrate1 | -.1030819 .0471413 -2.19 0.029 -.1954772 -.0106866 lremote | .3690192 .2613591 1.41 0.158 -.1432352 .8812736 ldist | -2.220281 .4536562 -4.89 0.000 -3.109431 -1.331131 lopen | -.3195844 .1722869 -1.85 0.064 -.6572605 .0180918 english | 1.494248 .31349 4.77 0.000 .879819 2.108677 white | 18.73434 1.829578 10.24 0.000 15.14843 22.32024 lwhitemg | -1.833821 .1734161 -10.57 0.000 -2.173711 -1.493932 _cons | -133.3087 40.42503 -3.30 0.001 -212.5403 -54.07708 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .007578 lgdp | -.009744 .020383 lgdpau | -.009874 .010918 1.63457 lgdpdfrati~w | -.002722 -.0022 .130309 .381439 lpopau | .030725 -.029632 -5.35661 -.234667 18.7841 lpop | .003399 -.012324 -.001645 .001664 -.016639 .018909 lxrate1 | .000501 .00105 .000083 .000375 .002257 -.002073 .002222 lremote | .002779 .001883 -.041251 -.056212 -.00288 -.000562 -.000865 ldist | .019412 -.022351 -.047415 -.034937 .074604 .022144 .001991 lopen | -.000662 -.000367 .008948 -.00514 -.094815 .006939 -.001072 english | -.010802 .009478 .010468 .003446 -.057114 .003398 .003234 white | .0355 -.076456 -.039301 -.047478 .047834 .082156 .001963 lwhitemg | -.00311 .005322 .000492 .000882 -.006816 -.006261 -.000247 _cons | -.333741 .185764 46.4815 .926733 -170.894 .083183 -.055701</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .068309 ldist | .046656 .205804 lopen | .01159 .005141 .029683 english | -.003566 .013678 -.006611 .098276 white | .036106 .16457 .000773 .10468 3.34736 lwhitemg | .000432 -.012909 .000585 -.00728 -.308615 .030073 _cons | .118245 -2.29277 1.12147 .320269 -1.42335 .220163 1634.18</p><p>. xtgls lrxsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 798.18 Log likelihood = -216.597 Prob > chi2 = 0.0000</p><p>------lrxsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0039771 .0157929 0.25 0.801 -.0269765 .0349306 lgdp | .0411233 .0400878 1.03 0.305 -.0374473 .119694 lgdpau | .050804 .2721273 0.19 0.852 -.4825556 .5841637 lgdpdfrati~w | -.0957384 .1492469 -0.64 0.521 -.388257 .1967801 lpopau | 2.515586 .9715461 2.59 0.010 .6113909 4.419782 lpop | .2307163 .0508842 4.53 0.000 .1309851 .3304475 lxrate1 | -.0273061 .0134328 -2.03 0.042 -.0536338 -.0009784 lremote | -.0440164 .0946962 -0.46 0.642 -.2296176 .1415848 ldist | -3.253715 .345817 -9.41 0.000 -3.931504 -2.575926 lopen | -.0408537 .0269288 -1.52 0.129 -.0936332 .0119259 english | 1.398975 .1620265 8.63 0.000 1.081409 1.716541 white | 20.0574 1.324948 15.14 0.000 17.46055 22.65425 lwhitemg | -1.611068 .1223321 -13.17 0.000 -1.850834 -1.371301 _cons | -15.34682 10.69988 -1.43 0.151 -36.3182 5.624565 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000249 lgdp | -.000137 .001607 lgdpau | .000227 -.000887 .074053 lgdpdfrati~w | -.000279 .000501 -.005143 .022275 lpopau | -.001019 .004644 -.251231 .028465 .943902 lpop | -.000104 -.001356 .000101 -.000087 -.003397 .002589 lxrate1 | .000018 -.000013 .000378 .000305 -.002871 .000038 .00018 lremote | .000216 .000768 -.005747 -.000813 .015449 -.000166 .000094 ldist | .001122 .002576 -.007201 -.000094 .024623 -.000302 -.000357 lopen | .000024 -.000058 -.000091 -.000014 -.00138 .000093 -.000014 english | -.000307 .000517 -.000986 .000131 .009709 .00115 -4.4e-07 white | .000651 -.006756 .002412 -.003395 -.033912 .012248 .000673 lwhitemg | -.000112 .000187 -.000326 .000233 .001866 -.000808 -.00001 _cons | .002058 -.099637 2.36536 -.36204 -9.5047 .048561 .039009</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .008967 ldist | .010184 .119589 lopen | .000028 -.000084 .000725 english | .001167 .022876 -.000278 .026253 white | .007158 .035828 -.0001 .038067 1.75549 lwhitemg | -.000361 -.005443 .000043 -.004272 -.156791 .014965 _cons | -.296821 -1.51555 .026 -.39648 .043722 .042128 114.487</p><p>. xtgls lrxsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 681.78 Log likelihood = -1323.332 Prob > chi2 = 0.0000</p><p>------lrxsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2247421 .057995 3.88 0.000 .111074 .3384101 lgdp | .6897918 .1158512 5.95 0.000 .4627277 .9168559 lgdpau | -5.090628 1.88995 -2.69 0.007 -8.794862 -1.386395 lgdpdfrati~w | -.102542 .8495871 -0.12 0.904 -1.767702 1.562618 lpopau | 14.91537 6.543282 2.28 0.023 2.09077 27.73996 lpop | .1299275 .1284207 1.01 0.312 -.1217724 .3816275 lxrate1 | -.0704952 .0372846 -1.89 0.059 -.1435717 .0025813 lremote | -.6913502 .3442129 -2.01 0.045 -1.365995 -.0167053 ldist | -2.876393 .4331283 -6.64 0.000 -3.725308 -2.027477 lopen | -.2293025 .1830047 -1.25 0.210 -.587985 .1293801 english | .2742756 .2681092 1.02 0.306 -.2512089 .79976 white | 11.12705 1.874103 5.94 0.000 7.45387 14.80022 lwhitemg | -1.269268 .1788468 -7.10 0.000 -1.619801 -.9187351 _cons | -94.68374 61.18489 -1.55 0.122 -214.6039 25.23645 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003363 lgdp | -.004785 .013421 lgdpau | -.00418 .00859 3.57191 lgdpdfrati~w | -.005469 .006564 -.075752 .721798 lpopau | .018164 -.05377 -12.0674 .569993 42.8145 lpop | .002074 -.009626 .00257 -.0036 -.017415 .016492 lxrate1 | -.000519 .001818 .001595 .004296 -.010124 -.001379 .00139 lremote | .004801 -.0095 -.017609 -.062775 .023873 .001884 -.006182 ldist | .015887 -.020108 -.012209 -.040734 -.021469 .013774 -.002872 lopen | -.000267 -.000161 .022236 -.004174 -.171572 .007735 -.001247 english | -.001732 .006066 .003386 .016538 -.014087 -.000429 .003668 white | .031645 -.066342 -.006062 -.078248 .081014 .071644 -.005823 lwhitemg | -.002622 .003905 -.001881 .001614 .003507 -.005608 -.000089 _cons | -.32294 .804474 106.626 -7.36855 -393.168 .03351 .181694</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .118483 ldist | .050633 .1876 lopen | .018038 .011754 .033491 english | -.016558 .017359 -.008067 .071883 white | .097588 .210832 .001332 .111759 3.51226 lwhitemg | .002156 -.019015 .000932 -.013745 -.322037 .031986 _cons | -1.21255 -1.35138 1.91078 -.042654 -3.81445 .171533 3743.59</p><p>. xtgls lrxsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 242.33 Log likelihood = -697.7804 Prob > chi2 = 0.0000</p><p>------lrxsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .059524 .0434964 1.37 0.171 -.0257274 .1447754 lgdp | .1075453 .1060581 1.01 0.311 -.1003247 .3154154 lgdpau | -.037841 .8689165 -0.04 0.965 -1.740886 1.665204 lgdpdfrati~w | .2245118 .3007408 0.75 0.455 -.3649294 .813953 lpopau | -1.844084 2.985795 -0.62 0.537 -7.696135 4.007967 lpop | .6085048 .1167665 5.21 0.000 .3796467 .8373628 lxrate1 | .0405179 .0323475 1.25 0.210 -.0228821 .103918 lremote | -.2179319 .2846337 -0.77 0.444 -.7758037 .33994 ldist | -1.94905 .5584774 -3.49 0.000 -3.043646 -.8544546 lopen | .0132978 .059426 0.22 0.823 -.1031751 .1297707 english | 1.569829 .3622066 4.33 0.000 .8599172 2.279741 white | 8.97634 3.045758 2.95 0.003 3.006764 14.94592 lwhitemg | -.7372435 .2651131 -2.78 0.005 -1.256856 -.2176313 _cons | 40.6748 28.66948 1.42 0.156 -15.51634 96.86594 ------</p><p>. vce | limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001892 lgdp | -.001544 .011248 lgdpau | .002251 -.002035 .755016 lgdpdfrati~w | -.001597 .002571 -.025609 .090445 lpopau | -.013941 -.000402 -2.52573 .090535 8.91497 lpop | .000123 -.008586 -.00062 -.000081 .003551 .013634 lxrate1 | .000144 .000409 .001436 .001963 -.010575 -.000523 .001046 lremote | .000928 .006422 -.04229 -.013491 .137164 -.006055 -.000863 ldist | .007003 -.00155 -.001605 -.00372 -.053974 .009894 .002015 lopen | .000128 -.000563 -.002806 .004393 .006722 .001129 -.000088 english | -.003805 -.008048 .00532 .00791 -.018746 .013749 .002255 white | .006024 -.06038 .104262 .001591 -.35362 .074094 .000741 lwhitemg | -.000865 .003189 -.012278 -.001037 .047101 -.005509 -.000167 _cons | .123469 -.090213 22.5416 -.822045 -82.3994 -.107198 .118713</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .081016 ldist | .024485 .311897 lopen | -.000282 -.000049 .003531 english | -.020532 .062225 -.000439 .131194 white | -.08131 .122706 .005223 .179298 9.27664 lwhitemg | .01029 -.016397 -.000383 -.017126 -.785485 .070285 _cons | -2.14276 -2.42645 -.043186 -.305944 2.77545 -.369951 821.939</p><p>. xtgls lrxsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 229.52 Log likelihood = -779.9108 Prob > chi2 = 0.0000</p><p>------lrxsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | -.0013765 .0404107 -0.03 0.973 -.0805801 .0778271 lgdp | .0953348 .0798853 1.19 0.233 -.0612374 .251907 lgdpau | .0802995 .701925 0.11 0.909 -1.295448 1.456047 lgdpdfrati~w | .0224218 .244397 0.09 0.927 -.4565875 .5014311 lpopau | .0923345 2.419794 0.04 0.970 -4.650375 4.835044 lpop | .4707403 .1003731 4.69 0.000 .2740128 .6674679 lxrate1 | -.0070955 .0222141 -0.32 0.749 -.0506344 .0364434 lremote | .4138038 .2367166 1.75 0.080 -.0501522 .8777598 ldist | -2.647617 .3974967 -6.66 0.000 -3.426696 -1.868538 lopen | .0314161 .0511233 0.61 0.539 -.0687836 .1316159 english | .8005888 .3328286 2.41 0.016 .1482567 1.452921 white | -.808981 1.426998 -0.57 0.571 -3.605845 1.987883 lwhitemg | .1352244 .1526783 0.89 0.376 -.1640196 .4344685 _cons | 9.665245 23.57293 0.41 0.682 -36.53685 55.86734 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001633 lgdp | -.001271 .006382 lgdpau | -.000499 .000929 .492699 lgdpdfrati~w | -.000325 .000536 -.033912 .05973 lpopau | -.004293 -.003471 -1.6452 .111156 5.8554 lpop | -.000046 -.004547 -.000241 -.000896 -.010348 .010075 lxrate1 | .000154 .00002 -.000294 .001366 -.003001 -.00022 .000493 lremote | .0024 .003163 -.02659 -.007888 .083731 -.003201 -.000287 ldist | .004717 -.00328 -.015197 -.001076 .04055 .001187 .000443 lopen | -.000112 .000322 .002424 .000475 -.010737 .000609 -.000018 english | -.003174 -.003054 .000917 .003641 .012677 .001778 .000751 white | .005872 -.030369 -.001985 -.006883 -.082426 .039353 .001849 lwhitemg | -.000645 .001691 -.002316 .000081 .016972 -.002683 -.000169 _cons | .040143 -.028401 14.7629 -.935302 -54.9545 .140057 .055011</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .056035 ldist | .027523 .158004 lopen | .000399 -.000817 .002614 english | -.013174 .047003 -.001404 .110775 white | .009683 .041258 -.000928 .115109 2.03632 lwhitemg | .001585 -.003708 .000095 -.011012 -.210232 .023311 _cons | -1.46455 -2.00042 .103441 -.539159 .947401 -.189701 555.683</p><p>. xtgls lrxsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 569.96 Log likelihood = -1061.218 Prob > chi2 = 0.0000</p><p>------lrxsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1249476 .0746962 1.67 0.094 -.0214542 .2713494 lgdp | .5760661 .1360289 4.23 0.000 .3094544 .8426779 lgdpau | -.7124054 .81671 -0.87 0.383 -2.313128 .8883167 lgdpdfrati~w | -.6606359 .3728485 -1.77 0.076 -1.391406 .0701338 lpopau | 7.458894 2.758708 2.70 0.007 2.051925 12.86586 lpop | .2452249 .1251488 1.96 0.050 -.0000621 .490512 lxrate1 | -.1579266 .0345994 -4.56 0.000 -.2257402 -.0901129 lremote | .2186277 .2306808 0.95 0.343 -.2334983 .6707537 ldist | -3.067496 .4359882 -7.04 0.000 -3.922017 -2.212975 lopen | .1105758 .0913625 1.21 0.226 -.0684914 .289643 english | .6968574 .2625241 2.65 0.008 .1823195 1.211395 white | 11.22773 2.103493 5.34 0.000 7.104965 15.3505 lwhitemg | -1.107177 .1925461 -5.75 0.000 -1.48456 -.7297932 _cons | -90.75504 26.17859 -3.47 0.001 -142.0641 -39.44595 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00558 lgdp | -.006226 .018504 lgdpau | -.004926 .005659 .667015 lgdpdfrati~w | -.000171 -.001444 .038112 .139016 lpopau | .015408 -.026705 -2.17265 -.051774 7.61047 lpop | .00141 -.011638 -.000923 .001979 .002359 .015662 lxrate1 | .000476 .000983 .000438 .000424 -.003233 -.001273 .001197 lremote | .000931 .006156 -.0319 -.027402 .025557 -.006051 .001781 ldist | .014426 -.009718 -.024812 -.004857 .076699 .002095 .000654 lopen | -.000118 .000111 .001959 .001944 -.027724 .001803 -.000518 english | -.005736 .016552 .000529 -.003976 -.006925 -.011291 -.000455 white | .030683 -.055487 -.053289 -.030624 .091542 .05188 -.00271 lwhitemg | -.002758 .002577 .001989 .00049 -.004329 -.002651 .000145 _cons | -.188407 .127963 18.9359 .005396 -69.7204 .02979 .011154</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .053214 ldist | .022168 .190086 lopen | .002296 -.000126 .008347 english | .00775 .026378 -.003906 .068919 white | .033329 .100974 -.003531 .03005 4.42468 lwhitemg | -.000018 -.011365 .000244 -.005725 -.391724 .037074 _cons | -.293156 -2.53328 .367057 -.39493 -1.12487 .13195 685.318</p><p>. xtgls lrxsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 727.87 Log likelihood = -1141.024 Prob > chi2 = 0.0000</p><p>------lrxsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .243846 .075006 3.25 0.001 .0968369 .3908551 lgdp | .6055607 .112544 5.38 0.000 .3849785 .8261428 lgdpau | .0527784 1.156244 0.05 0.964 -2.213418 2.318975 lgdpdfrati~w | -1.056324 .5628778 -1.88 0.061 -2.159544 .0468961 lpopau | 2.984712 3.933118 0.76 0.448 -4.724058 10.69348 lpop | -.0403469 .1205203 -0.33 0.738 -.2765624 .1958686 lxrate1 | -.0437941 .0378998 -1.16 0.248 -.1180764 .0304881 lremote | .4363809 .2772202 1.57 0.115 -.1069607 .9797225 ldist | -2.676976 .4274972 -6.26 0.000 -3.514855 -1.839097 lopen | -.0959768 .0929297 -1.03 0.302 -.2781157 .0861621 english | 1.211033 .287842 4.21 0.000 .646873 1.775193 white | 10.2197 2.13242 4.79 0.000 6.040236 14.39917 lwhitemg | -1.038285 .1905271 -5.45 0.000 -1.411711 -.6648589 _cons | -38.41518 36.80935 -1.04 0.297 -110.5602 33.72982 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005626 lgdp | -.005558 .012666 lgdpau | -.005503 .008669 1.3369 lgdpdfrati~w | -.003528 .004335 .051755 .316831 lpopau | .013766 -.029915 -4.40558 .018781 15.4694 lpop | .001259 -.009286 -.004154 -.000784 .009343 .014525 lxrate1 | .000568 .000738 .001585 .000307 -.010186 -.001215 .001436 lremote | .004293 -.001698 -.031238 -.048895 -.007045 -.001594 .001791 ldist | .014516 -.009782 -.028321 -.024965 .054439 .004062 .000636 lopen | -.000396 .000902 .001145 .000863 -.025434 .00089 -.000353 english | -.006662 .011217 .005125 .00001 -.006525 -.006324 -.00082 white | .030204 -.055579 -.045564 -.053933 .069838 .053544 -.001048 lwhitemg | -.002624 .003382 .001456 .000606 -.005282 -.003417 .000094 _cons | -.186339 .262104 38.3937 -1.40527 -141.129 -.091386 .099948</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .076851 ldist | .043965 .182754 lopen | .003881 .001125 .008636 english | .001515 .031493 -.003246 .082853 white | .070477 .104496 -.009054 .043174 4.54721 lwhitemg | -.001262 -.010228 .000695 -.005842 -.396435 .036301 _cons | -.069298 -2.19871 .324175 -.46941 -1.32504 .153736 1354.93</p><p>. xtgls lrxsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 468.20 Log likelihood = -1201.15 Prob > chi2 = 0.0000</p><p>------lrxsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2172844 .0507655 4.28 0.000 .1177859 .3167829 lgdp | .2989395 .1018071 2.94 0.003 .0994013 .4984778 lgdpau | -2.151649 1.391003 -1.55 0.122 -4.877965 .5746659 lgdpdfrati~w | -2.212943 .6313871 -3.50 0.000 -3.450439 -.9754475 lpopau | 6.76154 4.753666 1.42 0.155 -2.555475 16.07856 lpop | .1195573 .0768974 1.55 0.120 -.0311589 .2702735 lxrate1 | -.1106866 .0380527 -2.91 0.004 -.1852685 -.0361047 lremote | 1.098909 .2620436 4.19 0.000 .5853131 1.612505 ldist | -1.24417 .4045925 -3.08 0.002 -2.037156 -.451183 lopen | .0026455 .1164793 0.02 0.982 -.2256497 .2309408 english | .6027124 .1833153 3.29 0.001 .243421 .9620037 white | 6.0712 .9881982 6.14 0.000 4.134367 8.008033 lwhitemg | -.4996346 .1077479 -4.64 0.000 -.7108166 -.2884527 _cons | -54.82972 44.04015 -1.24 0.213 -141.1468 31.48739 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002577 lgdp | -.002503 .010365 lgdpau | -.003744 .006413 1.93489 lgdpdfrati~w | -.001432 .000704 .085383 .39865 lpopau | .013872 -.038634 -6.46601 -.135359 22.5973 lpop | .000563 -.005373 -.000773 -.001414 .004402 .005913 lxrate1 | .00021 .001573 .001047 .00074 -.007374 -.001545 .001448 lremote | .000401 .000458 -.027379 -.045999 .046034 .001917 -.000952 ldist | .012212 -.00569 -.025479 -.026262 .043173 .005138 .001892 lopen | -.00017 .000344 .009483 .001259 -.062546 .003038 -.000394 english | -.002879 .005247 .007107 .006456 -.025432 .000852 .000799 white | .014049 -.030326 -.035401 -.035865 .124456 .027449 -.004434 lwhitemg | -.001552 .000931 .000212 -.000617 -.000476 -.00152 -7.6e-06 _cons | -.218788 .381517 56.7868 .254426 -205.301 -.084879 .067321</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .068667 ldist | .041598 .163695 lopen | .004913 .007982 .013567 english | -.007541 -.000923 -.001519 .033604 white | .035188 .098248 .004019 .035019 .976536 lwhitemg | .002244 -.010434 -.000406 -.004271 -.098323 .01161 _cons | -1.03325 -1.97375 .625591 .170536 -2.18815 .09717 1939.53 . xtgls lrxsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 490.82 Log likelihood = -990.5819 Prob > chi2 = 0.0000</p><p>------lrxsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .135785 .0510829 2.66 0.008 .0356645 .2359056 lgdp | .5081705 .0982386 5.17 0.000 .3156264 .7007145 lgdpau | -1.108529 1.361158 -0.81 0.415 -3.77635 1.559292 lgdpdfrati~w | -1.101414 .5590909 -1.97 0.049 -2.197212 -.0056157 lpopau | 3.524647 4.6777 0.75 0.451 -5.643476 12.69277 lpop | .0542965 .098553 0.55 0.582 -.1388638 .2474568 lxrate1 | -.0459639 .0388525 -1.18 0.237 -.1221134 .0301857 lremote | -.755864 .3032222 -2.49 0.013 -1.350168 -.1615595 ldist | -2.902398 .4530037 -6.41 0.000 -3.790269 -2.014527 lopen | -.0283833 .105455 -0.27 0.788 -.2350713 .1783047 english | .6208592 .1966695 3.16 0.002 .235394 1.006324 white | 9.398209 1.585022 5.93 0.000 6.291624 12.50479 lwhitemg | -.970163 .1416272 -6.85 0.000 -1.247747 -.6925787 _cons | -2.844565 43.87246 -0.06 0.948 -88.833 83.14387 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002609 lgdp | -.002394 .009651 lgdpau | -.003139 .005997 1.85275 lgdpdfrati~w | -.001188 .000155 -.029664 .312583 lpopau | .010831 -.0294 -6.22139 .18939 21.8809 lpop | -.000449 -.005751 -.001279 .00084 .005333 .009713 lxrate1 | .000061 .001477 .002273 .001612 -.013347 -.001571 .00151 lremote | .004088 .000434 -.019174 -.034788 .046996 -.003382 -.001271 ldist | .011075 -.007744 -.02213 -.013721 .059872 .003667 -.000708 lopen | -.000259 -.000102 .006394 .005236 -.049432 .002143 -.000089 english | -.002551 .003342 .00671 .005766 -.023235 -.001336 .002133 white | .011114 -.034251 .004742 -.023189 .01443 .037799 -.005803 lwhitemg | -.000911 .001134 -.001975 -.000368 .004673 -.002437 .000318 _cons | -.191556 .283152 54.9059 -2.26561 -200.516 -.077656 .164313</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .091944 ldist | .047908 .205212 lopen | .003423 .000564 .011121 english | -.018342 .007686 -.002634 .038679 white | .032809 .111693 -.000494 .026849 2.51229 lwhitemg | .001616 -.010772 .000185 -.002866 -.215733 .020058 _cons | -1.47241 -2.72702 .59145 .228213 -1.59944 .083148 1924.79</p><p>. xtgls lrxsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 837.34 Log likelihood = -1581.911 Prob > chi2 = 0.0000</p><p>------lrxsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4348159 .0683537 6.36 0.000 .3008451 .5687867 lgdp | .2049382 .1265154 1.62 0.105 -.0430274 .4529037 lgdpau | -2.078786 1.746691 -1.19 0.234 -5.502238 1.344666 lgdpdfrati~w | -1.00007 .5908201 -1.69 0.091 -2.158056 .1579162 lpopau | 17.57969 5.965386 2.95 0.003 5.887753 29.27163 lpop | .4775787 .1209165 3.95 0.000 .2405867 .7145707 lxrate1 | -.1349214 .0427536 -3.16 0.002 -.2187168 -.0511259 lremote | .3449334 .3072613 1.12 0.262 -.2572877 .9471544 ldist | -1.896925 .4458906 -4.25 0.000 -2.770855 -1.022996 lopen | -.1174609 .137234 -0.86 0.392 -.3864345 .1515128 english | .240744 .2775798 0.87 0.386 -.3033023 .7847904 white | 15.12324 2.676332 5.65 0.000 9.877723 20.36875 lwhitemg | -1.448457 .2589285 -5.59 0.000 -1.955948 -.9409667 _cons | -231.7192 55.27728 -4.19 0.000 -340.0606 -123.3777 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004672 lgdp | -.005402 .016006 lgdpau | -.006175 .008858 3.05093 lgdpdfrati~w | -.002096 .002719 -.031693 .349068 lpopau | .019353 -.039765 -10.1865 .130433 35.5858 lpop | .001777 -.010755 -.003421 -.001359 .00626 .014621 lxrate1 | -.000081 .001595 -.000751 .003284 -.005587 -.001327 .001828 lremote | .00497 -.001653 -.04313 -.018233 .039528 .001339 .00133 ldist | .016246 -.011621 -.032565 -.001462 .087299 .009464 -.000571 lopen | -.000455 -.000294 .007281 .008607 -.047296 .003737 -.000306 english | -.004703 .011243 .009505 .000944 -.053644 -.005914 .0015 white | .015153 -.042287 -.084572 -.059995 -.054045 .057716 .006103 lwhitemg | -.001114 .001351 .003148 .002862 .010571 -.003042 -.000543 _cons | -.288957 .381342 89.5524 -1.54428 -323.841 -.106006 .080872</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .094409 ldist | .04583 .198818 lopen | .005878 .004815 .018833 english | -.01096 .026214 -.004393 .077051 white | .155425 -.033772 -.005442 -.021223 7.16275 lwhitemg | -.006811 .003989 .000715 .001463 -.682624 .067044 _cons | -.77654 -2.87417 .452195 .32147 2.05153 -.21172 3055.58 . clear</p><p>. *Estimating the Australian Immigration Trade relationship; . insheet using k:\book2.txt (54 vars, 11640 obs)</p><p>. drop if ccode ==. (10630 observations deleted)</p><p>. . **Dropping Sri Lanka . drop if ccode==537240 (10 observations deleted)</p><p>. . . ** Estimation Results . **Regression of Exports without Distinction between "white" and "non-white Aus > tralia" . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Exports . xtgls lrexp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote 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) = 6759.84 Log likelihood = -1021.332 Prob > chi2 = 0.0000</p><p>------lrexp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5091474 .0409895 12.42 0.000 .4288094 .5894853 lgdp | 1.080645 .0400898 26.96 0.000 1.00207 1.15922 lgdpau | -3.225787 .8732505 -3.69 0.000 -4.937326 -1.514247 lgdpdfrati~w | -1.789545 .3321993 -5.39 0.000 -2.440644 -1.138447 lpopau | 3.948981 3.045712 1.30 0.195 -2.020505 9.918467 lpop | .0083733 .0418231 0.20 0.841 -.0735985 .090345 lxrate1 | .0037768 .0148191 0.25 0.799 -.0252681 .0328217 lremote | .1579675 .0812438 1.94 0.052 -.0012673 .3172024 ldist | -1.43944 .1492034 -9.65 0.000 -1.731873 -1.147007 lopen | .9203559 .0781918 11.77 0.000 .7671028 1.073609 english | .1832183 .0948812 1.93 0.053 -.0027455 .3691821 white | 3.232643 .5693552 5.68 0.000 2.116727 4.348559 lwhitemg | -.3924102 .0515492 -7.61 0.000 -.4934448 -.2913757 _cons | 13.49428 28.25078 0.48 0.633 -41.87623 68.8648 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00168 lgdp | -.001023 .001607 lgdpau | -.00367 .00314 .762566 lgdpdfrati~w | .000734 -.001073 -.024442 .110356 lpopau | .014031 -.01276 -2.61837 .132176 9.27636 lpop | 7.8e-06 -.000693 .00095 -.000019 -.007098 .001749 lxrate1 | 4.7e-06 .000184 .000011 -.000059 -.000355 -.000069 .00022 lremote | -.000434 .001289 .004636 -.002089 -.024643 .000113 .000069 ldist | .004157 -.002611 -.006518 .00386 .0163 .00185 .000477 lopen | -.000637 .000415 .010583 -.000898 -.057144 .000947 -.000054 english | -.000749 .001487 -.002443 .000422 .016336 -.000992 .000464 white | .007128 -.001423 -.006189 -.008221 -.000729 .009587 .001572 lwhitemg | -.000813 .000191 .000765 .000452 -.000601 -.000852 -.000132 _cons | -.162833 .123778 23.4291 -1.66818 -85.053 .063481 -.003659</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .006601 ldist | .001983 .022262 lopen | .002233 .000646 .006114 english | .000124 .001587 -.00293 .009002 white | .015233 .03378 .000098 .002601 .324165 lwhitemg | -.001139 -.003476 -.000027 -4.6e-06 -.028959 .002657 _cons | .184626 -.334259 .632678 -.245074 -.46966 .049831 798.107</p><p>. **II. Conservative Estimates . *2.1. Aggregate reference priced Exports (conservative) . xtgls lrrefp_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7182.55 Log likelihood = -1455.551 Prob > chi2 = 0.0000</p><p>------lrrefp_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3224132 .0451953 7.13 0.000 .233832 .4109943 lgdp | 1.104634 .0670646 16.47 0.000 .9731901 1.236079 lgdpau | -.3048993 .5199816 -0.59 0.558 -1.324045 .7142459 lgdpdfrati~w | -.198085 .2923124 -0.68 0.498 -.7710067 .3748368 lpopau | 3.153323 1.868843 1.69 0.092 -.509542 6.816187 lpop | .0315556 .0937109 0.34 0.736 -.1521145 .2152256 lxrate1 | -.0412151 .02984 -1.38 0.167 -.0997005 .0172703 lremote | -.2693608 .1661672 -1.62 0.105 -.5950424 .0563209 ldist | -3.156368 .3878728 -8.14 0.000 -3.916584 -2.396151 lopen | -.0739728 .0555351 -1.33 0.183 -.1828197 .034874 english | .6093738 .1807404 3.37 0.001 .2551291 .9636185 white | 7.579502 1.098569 6.90 0.000 5.426347 9.732656 lwhitemg | -.8202572 .1170146 -7.01 0.000 -1.049602 -.5909128 _cons | -34.61736 18.79134 -1.84 0.065 -71.44772 2.213 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002043 lgdp | -.001557 .004498 lgdpau | .001122 -.001289 .270381 lgdpdfrati~w | -.001845 .003059 -.024049 .085447 lpopau | -.005207 .003486 -.935341 .105486 3.49257 lpop | -.000104 -.004753 .003418 -.001328 -.018699 .008782 lxrate1 | .000136 .000381 .000569 .002587 -.006158 -.000558 .00089 lremote | .000092 .000367 -.021662 .002789 .091734 -.003615 .000615 ldist | .008715 -.010319 .0032 .002441 -.027062 .005021 .00206 lopen | .000036 -.000208 .002483 .00104 -.011896 .001116 -.000357 english | -.001119 -.001656 .006004 .004007 -.04491 .003448 .00155 white | .01024 -.025421 .021643 -.004118 -.152598 .03218 .001657 lwhitemg | -.001488 .001982 -.00449 .000629 .022758 -.002078 -.000131 _cons | .000678 .048166 8.57739 -1.30328 -33.8014 .17741 .055791</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .027612 ldist | .003541 .150445 lopen | -.001861 .000849 .003084 english | -.005022 .000265 -.000637 .032667 white | -.012391 .052881 .002624 .040138 1.20685 lwhitemg | .004138 -.006634 -.000577 -.001899 -.123269 .013692 _cons | -1.18845 -1.00348 .129606 .596039 1.56254 -.237028 353.115</p><p>. *2.2. Aggregate Differentiated Exports (conservative) . xtgls lrdiff_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100</p><p>Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3564.29 Log likelihood = -1561.677 Prob > chi2 = 0.0000</p><p>------lrdiff_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4412932 .0569132 7.75 0.000 .3297454 .5528409 lgdp | 1.109353 .0649038 17.09 0.000 .9821437 1.236562 lgdpau | 2.010263 2.047657 0.98 0.326 -2.00307 6.023596 lgdpdfrati~w | -2.157281 .8231956 -2.62 0.009 -3.770714 -.5438471 lpopau | -7.658347 7.049787 -1.09 0.277 -21.47568 6.158981 lpop | -.1676285 .0800777 -2.09 0.036 -.324578 -.0106791 lxrate1 | -.0657984 .0281478 -2.34 0.019 -.120967 -.0106297 lremote | -.0018336 .2018267 -0.01 0.993 -.3974066 .3937395 ldist | -2.293191 .2354416 -9.74 0.000 -2.754648 -1.831734 lopen | .099355 .0910152 1.09 0.275 -.0790316 .2777416 english | .6692971 .1815411 3.69 0.000 .3134831 1.025111 white | 2.428585 1.161045 2.09 0.036 .152979 4.70419 lwhitemg | -.2379867 .1059174 -2.25 0.025 -.4455811 -.0303924 _cons | 78.29808 64.88359 1.21 0.228 -48.87143 205.4676 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003239 lgdp | -.00231 .004212 lgdpau | -.003089 .005902 4.1929 lgdpdfrati~w | -.004187 .00206 -.207839 .677651 lpopau | .010524 -.028307 -14.2201 .969723 49.6995 lpop | .000202 -.003374 -.000874 .001404 .005758 .006412 lxrate1 | .000195 .000484 .000879 -.000535 -.007066 -.000834 .000792 lremote | .004514 -.002924 .002602 -.008799 -.02873 -.00029 .000918 ldist | .006928 -.006223 -.007115 .010733 .017388 .002704 .002865 lopen | -.000397 .00074 .015219 .002897 -.078253 .001198 -.000138 english | -.003125 .00255 .00008 .010488 .009509 -.003369 .001264 white | .022928 -.022024 .034512 -.128274 -.161012 .00988 .002444 lwhitemg | -.002101 .001553 -.002842 .010934 .012977 -.000203 -.000149 _cons | -.166876 .367529 126.07 -11.4198 -452.056 -.119578 .057236 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .040734 ldist | .021548 .055433 lopen | .004022 .000514 .008284 english | -.014415 .001882 -.00331 .032957 white | .082837 .033329 -.002513 -.014162 1.34802 lwhitemg | -.004961 -.000977 .000357 .001214 -.119592 .011218 _cons | -.097462 -.783625 .831121 -.064772 1.02967 -.116266 4209.88</p><p>. *2.3. Aggregate Homogenous Exports (conservative) . xtgls lrhomo_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1984.37 Log likelihood = -1625.251 Prob > chi2 = 0.0000</p><p>------lrhomo_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4495579 .0526567 8.54 0.000 .3463527 .5527631 lgdp | .9531016 .0963636 9.89 0.000 .7642323 1.141971 lgdpau | .2609162 1.106498 0.24 0.814 -1.907781 2.429613 lgdpdfrati~w | -.279302 .4598232 -0.61 0.544 -1.180539 .6219349 lpopau | -7.078351 3.786912 -1.87 0.062 -14.50056 .3438607 lpop | .1843638 .1076238 1.71 0.087 -.0265751 .3953027 lxrate1 | .0630007 .0369367 1.71 0.088 -.0093939 .1353953 lremote | -1.143311 .2309216 -4.95 0.000 -1.595909 -.6907126 ldist | -1.648242 .4916105 -3.35 0.001 -2.611781 -.6847029 lopen | .0342733 .0949788 0.36 0.718 -.1518818 .2204283 english | 1.020113 .2967989 3.44 0.001 .4383983 1.601829 white | 12.32592 2.586412 4.77 0.000 7.256648 17.3952 lwhitemg | -1.452571 .2762629 -5.26 0.000 -1.994036 -.9111055 _cons | 114.2747 35.64286 3.21 0.001 44.41596 184.1334 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002773 lgdp | -.003008 .009286 lgdpau | .005916 -.01106 1.22434 lgdpdfrati~w | -.003552 .007415 -.056587 .211437 lpopau | -.023291 .02539 -4.06905 .281394 14.3407 lpop | .000357 -.005824 .000624 -.002873 -.001687 .011583 lxrate1 | -.000111 .00116 .002857 .002677 -.018519 -.001425 .001364 lremote | .000298 .008765 -.037322 .012317 .101676 -.006926 .00062 ldist | .01441 -.010713 .022347 -.005492 -.14592 .013024 .00204 lopen | .000016 -.001112 -.019638 .006818 .048141 .002152 -.000271 english | -.002483 .003748 .017474 .004197 -.085426 .005077 .002869 white | .009923 -.02403 .099382 -.01421 -.445136 .034425 .004204 lwhitemg | -.001148 .001585 -.011098 .0017 .049336 -.002861 -.000274 _cons | .142253 -.217061 35.7234 -3.57233 -131.295 -.098685 .196741</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .053325 ldist | .025521 .241681 lopen | .001665 -.001381 .009021 english | -.014334 .015709 -.003697 .08809 white | -.011337 .053296 -.000677 .121907 6.68953 lwhitemg | .002802 -.007239 .000434 -.012613 -.709613 .076321 _cons | -1.5096 -.734376 -.292115 .748822 4.27732 -.464959 1270.41</p><p>. **III. Liberal Estimates . *3.1. Aggregate reference priced Exports (liberal) . xtgls lrrefp_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1999.71 Log likelihood = -1456.462 Prob > chi2 = 0.0000</p><p>------lrrefp_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3531986 .0469553 7.52 0.000 .2611679 .4452292 lgdp | .9212996 .0836013 11.02 0.000 .7574442 1.085155 lgdpau | -.2669597 .4793071 -0.56 0.578 -1.206384 .6724649 lgdpdfrati~w | .1560568 .2439116 0.64 0.522 -.3220012 .6341147 lpopau | -2.26837 1.698708 -1.34 0.182 -5.597775 1.061036 lpop | .1670026 .0999014 1.67 0.095 -.0288006 .3628057 lxrate1 | -.0113488 .0275387 -0.41 0.680 -.0653237 .0426262 lremote | -.2238222 .156229 -1.43 0.152 -.5300255 .082381 ldist | -2.27826 .4815149 -4.73 0.000 -3.222012 -1.334508 lopen | .02598 .049786 0.52 0.602 -.0715988 .1235588 english | .984553 .2509877 3.92 0.000 .4926262 1.47648 white | 10.96774 2.073983 5.29 0.000 6.902803 15.03267 lwhitemg | -1.093309 .2029694 -5.39 0.000 -1.491122 -.6954963 _cons | 46.85391 17.16049 2.73 0.006 13.21997 80.48785 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002205 lgdp | -.002413 .006989 lgdpau | .001423 -.004056 .229735 lgdpdfrati~w | -.001817 .004345 -.023327 .059493 lpopau | -.006732 .013599 -.790393 .099351 2.88561 lpop | .000677 -.005816 .00484 -.003372 -.024463 .00998 lxrate1 | .000123 .000059 .001489 .001554 -.007955 -.000235 .000758 lremote | .00065 .000493 -.020059 .002213 .076239 -.003103 .000094 ldist | .006582 -.009321 -.000214 -.000985 -.018249 .008348 .00216 lopen | -.000026 -.000061 .001979 .000948 -.009019 .000745 -.000156 english | -.002054 .000833 .007783 .004057 -.031064 .001601 .001819 white | .01023 -.031002 .025778 -.00503 -.143105 .034598 .010399 lwhitemg | -.001177 .002054 -.003616 .000372 .018248 -.002171 -.000921 _cons | .039711 -.093752 7.28956 -1.15167 -27.5959 .201007 .068208</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .024408 ldist | .01115 .231857 lopen | -.001501 -.000801 .002479 english | -.006207 .030627 -.00046 .062995 white | .029506 -.185403 -.004079 .013135 4.30141 lwhitemg | -.000915 .019485 .000175 .000535 -.416659 .041197 _cons | -1.02743 -1.98125 .109587 .009535 3.26447 -.389062 294.482 . *3.2. Aggregate Differentiated Exports (liberal) . xtgls lrdiff_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3320.28 Log likelihood = -1578.905 Prob > chi2 = 0.0000</p><p>------lrdiff_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3992161 .0594316 6.72 0.000 .2827323 .5156999 lgdp | 1.209689 .0709266 17.06 0.000 1.070676 1.348703 lgdpau | 1.676088 2.133949 0.79 0.432 -2.506375 5.85855 lgdpdfrati~w | -2.299319 .8283764 -2.78 0.006 -3.922907 -.6757314 lpopau | -6.712267 7.344135 -0.91 0.361 -21.10651 7.681974 lpop | -.2780442 .08224 -3.38 0.001 -.4392317 -.1168567 lxrate1 | -.0279326 .028364 -0.98 0.325 -.083525 .0276598 lremote | .1161227 .1969262 0.59 0.555 -.2698455 .502091 ldist | -2.260217 .2354207 -9.60 0.000 -2.721633 -1.798801 lopen | .1197312 .099404 1.20 0.228 -.075097 .3145593 english | .8141478 .19731 4.13 0.000 .4274274 1.200868 white | 2.629105 1.171069 2.25 0.025 .3338524 4.924357 lwhitemg | -.2450199 .1071913 -2.29 0.022 -.4551109 -.0349289 _cons | 69.63509 67.57644 1.03 0.303 -62.8123 202.0825 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003532 lgdp | -.002841 .005031 lgdpau | -.003902 .006889 4.55374 lgdpdfrati~w | -.00433 .00305 -.214456 .686207 lpopau | .014192 -.033375 -15.4365 .977842 53.9363 lpop | .000912 -.004138 -.001273 -.000727 .007689 .006763 lxrate1 | .000023 .000674 .000883 .000349 -.007652 -.001003 .000805 lremote | .004078 -.002791 .000307 -.006569 -.021136 .001019 .000633 ldist | .007089 -.006336 -.009005 .01153 .022789 .003175 .002276 lopen | -.000487 .00078 .015945 .003288 -.085889 .001572 -.000186 english | -.004862 .004805 .002742 .013944 -.003442 -.004967 .001626 white | .021401 -.022594 .029178 -.122211 -.126857 .012632 .000312 lwhitemg | -.001999 .001622 -.002467 .010623 .010197 -.000417 .000049 _cons | -.203809 .420185 136.816 -11.4068 -490.509 -.146084 .073388</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .03878 ldist | .021668 .055423 lopen | .00445 .000549 .009881 english | -.01553 .000391 -.003622 .038931 white | .078452 .01108 -.003275 -.024413 1.3714 lwhitemg | -.004768 .00116 .000454 .002307 -.122178 .01149 _cons | -.169287 -.828389 .92971 .081594 .833934 -.101296 4566.58</p><p>. *3.3. Aggregate Homogenous Exports (liberal) . xtgls lrhomo_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2990.65 Log likelihood = -1549.256 Prob > chi2 = 0.0000</p><p>------lrhomo_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5364716 .043986 12.20 0.000 .4502606 .6226825 lgdp | 1.108844 .0686518 16.15 0.000 .974289 1.243399 lgdpau | -.3336391 .6774529 -0.49 0.622 -1.661422 .9941443 lgdpdfrati~w | -.4603536 .4784846 -0.96 0.336 -1.398166 .477459 lpopau | 1.835831 2.428735 0.76 0.450 -2.924403 6.596065 lpop | -.1503886 .0841604 -1.79 0.074 -.31534 .0145627 lxrate1 | -.0352782 .0302469 -1.17 0.243 -.094561 .0240046 lremote | -.7698883 .1923749 -4.00 0.000 -1.146936 -.3928406 ldist | -2.073894 .3139321 -6.61 0.000 -2.68919 -1.458599 lopen | .0300761 .0722468 0.42 0.677 -.111525 .1716772 english | .7263208 .2355674 3.08 0.002 .2646171 1.188024 white | 5.636189 2.049665 2.75 0.006 1.618919 9.653458 lwhitemg | -.7797452 .2097247 -3.72 0.000 -1.190798 -.3686923 _cons | -15.57653 24.31888 -0.64 0.522 -63.24067 32.08761 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001935 lgdp | -.001892 .004713 lgdpau | .000184 -.003327 .458942 lgdpdfrati~w | -.003416 .003886 -.057322 .228948 lpopau | -.00053 .006153 -1.58628 .298 5.89876 lpop | .000097 -.003318 .003931 .000743 -.020863 .007083 lxrate1 | -.000345 .000711 .001331 .00273 -.010011 -.000335 .000915 lremote | .00152 .001528 -.027897 .002432 .118896 -.004298 .00017 ldist | .006472 -.009298 -.003187 .00049 -.00878 .011066 .000754 lopen | .000097 -.000835 -.000244 .005177 -.00453 .00176 -.000322 english | -.001023 .001146 .015841 .007173 -.098808 .003146 .00295 white | .008257 -.012003 .036376 -.009866 -.241212 .019074 .00649 lwhitemg | -.000747 .000788 -.004612 .001467 .028006 -.001558 -.000462 _cons | -.0373 .009636 14.6142 -3.7998 -57.2857 .139298 .10701</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .037008 ldist | .015245 .098553 lopen | -.002047 .001039 .00522 english | -.013567 .01487 -.001249 .055492 white | .008549 .061686 -.002355 .07038 4.20113 lwhitemg | .001398 -.004496 .000116 -.006984 -.424211 .043984 _cons | -1.68676 -.851208 .079237 1.10163 2.2687 -.299472 591.408</p><p>. *IV. Aggregate NON-Manufacturing Exports (Sum of Sitc0,1,2,3,4) . xtgls lrxnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1220.08 Log likelihood = -1130.568 Prob > chi2 = 0.0000</p><p>------lrxnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3093172 .0581791 5.32 0.000 .1952883 .4233461 lgdp | .8568764 .0884067 9.69 0.000 .6836024 1.03015 lgdpau | -4.476761 1.260324 -3.55 0.000 -6.94695 -2.006572 lgdpdfrati~w | -1.845635 .5221195 -3.53 0.000 -2.86897 -.8222991 lpopau | 12.50644 4.357434 2.87 0.004 3.966024 21.04685 lpop | -.1873426 .0871417 -2.15 0.032 -.3581372 -.016548 lxrate1 | -.0094593 .0345149 -0.27 0.784 -.0771073 .0581886 lremote | -.1679246 .2880761 -0.58 0.560 -.7325433 .3966942 ldist | -2.27878 .2449199 -9.30 0.000 -2.758814 -1.798746 lopen | .0146029 .1144977 0.13 0.899 -.2098085 .2390143 english | 1.049284 .2280143 4.60 0.000 .6023841 1.496184 white | 13.09733 .9194628 14.24 0.000 11.29522 14.89945 lwhitemg | -1.438397 .086192 -16.69 0.000 -1.60733 -1.269464 _cons | -76.39889 40.68553 -1.88 0.060 -156.1411 3.343273 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003385 lgdp | -.002987 .007816 lgdpau | -.00279 .00539 1.58842 lgdpdfrati~w | -.002067 .003059 -.09291 .272609 lpopau | .012988 -.034717 -5.36451 .389912 18.9872 lpop | -.000036 -.004603 .000029 -.001012 .002377 .007594 lxrate1 | -.000379 .001496 .000572 .000915 -.006449 -.001479 .001191 lremote | .00132 -.000037 .001054 -.032172 -.026385 -.000674 .000157 ldist | .009131 -.00858 -.007353 -.006928 .02398 .002879 -.001921 lopen | .000097 -.000032 .010269 .002014 -.069782 .002658 -.000373 english | -.005541 .008209 .003023 .010622 -.011301 -.002747 .002724 white | .013631 -.024642 .009474 -.038949 .014965 .024273 -.003872 lwhitemg | -.001589 .001543 -.001322 .000197 .001066 -.0016 .000445 _cons | -.18945 .420278 47.3753 -4.0111 -174.089 -.068559 .094862</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .082988 ldist | .016618 .059986 lopen | .005501 .003814 .01311 english | -.014285 -.007528 -.006415 .051991 white | .0345 .06502 -.006644 .053474 .845412 lwhitemg | .004788 -.006927 .000651 -.005683 -.071277 .007429 _cons | -.439092 -.809173 .773976 .151835 -1.3318 .043493 1655.31</p><p>. *V. Aggregate Manufacturing Exports (Sum of Sitc5,6,7,8,9) . xtgls lrxmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1158.04 Log likelihood = -972.9312 Prob > chi2 = 0.0000</p><p>------lrxmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2405063 .0432385 5.56 0.000 .1557605 .3252521 lgdp | .3372077 .0915607 3.68 0.000 .157752 .5166633 lgdpau | -3.051336 1.120451 -2.72 0.006 -5.247379 -.8552932 lgdpdfrati~w | -4.415471 .4635196 -9.53 0.000 -5.323953 -3.506989 lpopau | 11.42035 3.869151 2.95 0.003 3.836949 19.00374 lpop | .1497084 .0756836 1.98 0.048 .0013714 .2980455 lxrate1 | -.0743411 .0279066 -2.66 0.008 -.1290369 -.0196452 lremote | .5140195 .1727913 2.97 0.003 .1753548 .8526842 ldist | -2.410535 .234805 -10.27 0.000 -2.870744 -1.950325 lopen | -.0835662 .0528137 -1.58 0.114 -.1870791 .0199467 english | .4147795 .1643268 2.52 0.012 .0927049 .736854 white | 9.304176 .814602 11.42 0.000 7.707585 10.90077 lwhitemg | -.8384032 .0714879 -11.73 0.000 -.978517 -.6982894 _cons | -90.29218 36.0243 -2.51 0.012 -160.8985 -19.68586 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00187 lgdp | -.002648 .008383 lgdpau | -.002843 .006632 1.25541 lgdpdfrati~w | -.002376 .005256 -.045209 .21485 lpopau | .012408 -.033573 -4.25114 .224021 14.9703 lpop | .001699 -.005962 -.003204 -.003459 .015637 .005728 lxrate1 | -.000148 .001228 .000943 .000671 -.007083 -.000983 .000779 lremote | .002104 -.003753 -.004578 -.013188 -.006365 .003183 -4.8e-06 ldist | .00586 -.009104 -.012811 -.008975 .054388 .007193 -.000543 lopen | -.000099 .000221 .004806 .002066 -.02391 .000558 -.000069 english | -.002079 .003515 .001751 .002911 -.000261 -.000757 .000374 white | .015976 -.032872 -.02713 -.032347 .092823 .03522 -.00569 lwhitemg | -.001216 .001427 .001214 .000635 -.00458 -.002098 .000346 _cons | -.181708 .413409 37.7155 -2.6056 -137.136 -.230923 .083613</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .029857 ldist | .019461 .055133 lopen | .000732 .000234 .002789 english | -.002161 .009043 -.000848 .027003 white | .059167 .077351 .001666 .007022 .663576 lwhitemg | -.00256 -.005397 -.000262 -.000506 -.05442 .005111 _cons | -.185039 -1.199 .249463 -.17942 -1.96362 .126196 1297.75</p><p>. . **VI. SITC-1 Digit Level Disaggregate Exports . xtgls lrxsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 769.14 Log likelihood = -1439.407 Prob > chi2 = 0.0000 ------lrxsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2908004 .0880423 3.30 0.001 .1182408 .4633601 lgdp | .4401966 .1426486 3.09 0.002 .1606105 .7197826 lgdpau | -.6783911 1.119398 -0.61 0.544 -2.87237 1.515588 lgdpdfrati~w | -.7452741 .5539818 -1.35 0.179 -1.831059 .3405103 lpopau | 9.824362 3.785955 2.59 0.009 2.404026 17.2447 lpop | -.1197619 .1383992 -0.87 0.387 -.3910193 .1514955 lxrate1 | -.0883878 .0461722 -1.91 0.056 -.1788836 .002108 lremote | .2933509 .2480629 1.18 0.237 -.1928435 .7795453 ldist | -2.244327 .462363 -4.85 0.000 -3.150542 -1.338112 lopen | -.3460413 .1730126 -2.00 0.045 -.6851399 -.0069428 english | 1.494562 .3160181 4.73 0.000 .8751779 2.113946 white | 19.04976 1.831972 10.40 0.000 15.45916 22.64036 lwhitemg | -1.858773 .1756437 -10.58 0.000 -2.203028 -1.514518 _cons | -131.4906 35.52501 -3.70 0.000 -201.1184 -61.86287 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .007751 lgdp | -.009769 .020349 lgdpau | -.010156 .010648 1.25305 lgdpdfrati~w | -.002544 -.002962 .119296 .306896 lpopau | .03214 -.028036 -4.08096 -.218129 14.3335 lpop | .003336 -.012332 -.001401 .002549 -.017255 .019154 lxrate1 | .00055 .000989 -.000465 -.000276 .00371 -.002001 .002132 lremote | .002622 .002531 -.040644 -.053773 .003189 -.001536 -.000097 ldist | .019257 -.021101 -.046952 -.034053 .082022 .021856 .002601 lopen | -.000662 -.000418 .006846 -.006358 -.087719 .007096 -.001112 english | -.010998 .009611 .010917 .003557 -.058969 .003095 .00305 white | .036009 -.076929 -.044691 -.040245 .029144 .081906 .00263 lwhitemg | -.003306 .005517 .000955 .000286 -.005988 -.006254 -.000295 _cons | -.346706 .150539 35.336 .993331 -130.684 .093848 -.076936</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .061535 ldist | .04251 .21378 lopen | .011057 .004657 .029933 english | -.0038 .015201 -.006924 .099867 white | .031349 .162247 .000262 .109511 3.35612 lwhitemg | .000599 -.013363 .000582 -.007429 -.313991 .030851 _cons | .095787 -2.496 1.06861 .329744 -.90361 .194295 1262.03</p><p>. xtgls lrxsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 889.77 Log likelihood = -241.551 Prob > chi2 = 0.0000</p><p>------lrxsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0052184 .0175149 0.30 0.766 -.0291102 .0395469 lgdp | .0459426 .0432277 1.06 0.288 -.0387821 .1306673 lgdpau | .0510482 .3004185 0.17 0.865 -.5377612 .6398576 lgdpdfrati~w | -.1449691 .1626895 -0.89 0.373 -.4638346 .1738965 lpopau | 3.313587 1.083928 3.06 0.002 1.189127 5.438046 lpop | .2264899 .0523394 4.33 0.000 .1239066 .3290732 lxrate1 | -.0366003 .0145678 -2.51 0.012 -.0651527 -.0080478 lremote | -.0555736 .1051064 -0.53 0.597 -.2615783 .1504312 ldist | -3.481215 .3361983 -10.35 0.000 -4.140152 -2.822279 lopen | -.0418763 .0289241 -1.45 0.148 -.0985664 .0148138 english | 1.27983 .1521134 8.41 0.000 .9816932 1.577967 white | 19.6514 1.272229 15.45 0.000 17.15788 22.14493 lwhitemg | -1.5849 .1202631 -13.18 0.000 -1.820612 -1.349189 _cons | -26.32216 11.9218 -2.21 0.027 -49.68846 -2.955854 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000307 lgdp | -.000189 .001869 lgdpau | .00038 -.001107 .090251 lgdpdfrati~w | -.00031 .000625 -.007668 .026468 lpopau | -.001821 .005462 -.308477 .03626 1.1749 lpop | -.000102 -.001451 .000076 -.000015 -.003831 .002739 lxrate1 | .000027 -3.4e-06 .000445 .000383 -.003646 .000036 .000212 lremote | .000228 .000916 -.006925 -.000492 .020626 -.000188 .00007 ldist | .001285 .002386 -.007008 -.000384 .030515 -.000613 -.000379 lopen | .000038 -.000084 .000077 -.00014 -.002137 .000151 -.000015 english | -.000398 .000489 -.000663 -.000538 .01439 .001017 .000014 white | .000906 -.007111 .002917 -.004823 -.032926 .01144 .000503 lwhitemg | -.000143 .000188 -.000475 .000326 .002089 -.000748 -6.7e-06 _cons | .01062 -.111325 2.90569 -.433193 -11.9518 .059376 .050115</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .011047 ldist | .010981 .113029 lopen | .000061 -.000379 .000837 english | .000883 .018498 -.000565 .023138 white | .008033 .025021 -.000139 .03163 1.61857 lwhitemg | -.000317 -.004382 .000062 -.003498 -.148241 .014463 _cons | -.381142 -1.55355 .036494 -.434991 .131118 .030903 142.129</p><p>. xtgls lrxsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 744.09 Log likelihood = -1323.583 Prob > chi2 = 0.0000</p><p>------lrxsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2003436 .0597551 3.35 0.001 .0832257 .3174616 lgdp | .7534363 .1150676 6.55 0.000 .527908 .9789647 lgdpau | -5.22219 1.90406 -2.74 0.006 -8.954079 -1.490302 lgdpdfrati~w | -.0545144 .8506253 -0.06 0.949 -1.721709 1.612681 lpopau | 15.40276 6.590729 2.34 0.019 2.485171 28.32036 lpop | .0925543 .1313673 0.70 0.481 -.1649208 .3500294 lxrate1 | -.0549924 .0368589 -1.49 0.136 -.1272346 .0172497 lremote | -.8083149 .3409637 -2.37 0.018 -1.476591 -.1400384 ldist | -2.762544 .5481653 -5.04 0.000 -3.836928 -1.68816 lopen | -.2378789 .1837269 -1.29 0.195 -.597977 .1222193 english | .1732244 .2667838 0.65 0.516 -.3496623 .696111 white | 10.28688 1.531258 6.72 0.000 7.285671 13.28809 lwhitemg | -1.189152 .1596818 -7.45 0.000 -1.502122 -.8761813 _cons | -100.1961 61.5765 -1.63 0.104 -220.8838 20.49166 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003571 lgdp | -.004637 .013241 lgdpau | -.004588 .00904 3.62544 lgdpdfrati~w | -.005036 .005267 -.075268 .723563 lpopau | .01849 -.055874 -12.2528 .550891 43.4377 lpop | .002045 -.009817 .00263 -.001558 -.019442 .017257 lxrate1 | -.000341 .001647 .001723 .00425 -.010744 -.001121 .001359 lremote | .005015 -.008262 -.019643 -.060426 .023943 -.000497 -.005988 ldist | .020338 -.019848 -.017276 -.034904 -.035139 .015486 -.000593 lopen | -.00053 .000504 .02128 -.003882 -.175337 .007738 -.0011 english | -.001543 .004798 .004547 .018221 -.016216 .001529 .00332 white | .032447 -.064609 -.029068 -.025093 .174815 .069672 -.003123 lwhitemg | -.002828 .003824 -.000259 -.002978 -.002916 -.005616 -.000399 _cons | -.36738 .823272 108.355 -7.14577 -398.412 .059168 .164397</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .116256 ldist | .052698 .300485 lopen | .018489 .012125 .033756 english | -.019336 .019983 -.006951 .071174 white | .053461 .233246 -.006703 .112354 2.34475 lwhitemg | .005753 -.02384 .001592 -.013937 -.233904 .025498 _cons | -1.15313 -2.15976 1.97662 -.041206 -4.67129 .259128 3791.67</p><p>. xtgls lrxsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 269.18 Log likelihood = -705.4602 Prob > chi2 = 0.0000</p><p>------lrxsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0540964 .0426626 1.27 0.205 -.0295208 .1377135 lgdp | .1580006 .1055358 1.50 0.134 -.0488457 .364847 lgdpau | -.0867983 .8419276 -0.10 0.918 -1.736946 1.56335 lgdpdfrati~w | .2200323 .2944277 0.75 0.455 -.3570355 .7971001 lpopau | -1.476704 2.892364 -0.51 0.610 -7.145632 4.192225 lpop | .5927943 .1137193 5.21 0.000 .3699086 .81568 lxrate1 | .0386696 .032069 1.21 0.228 -.0241844 .1015237 lremote | -.1723493 .2847408 -0.61 0.545 -.7304309 .3857323 ldist | -1.843624 .5741587 -3.21 0.001 -2.968954 -.7182932 lopen | .0069852 .0605511 0.12 0.908 -.1116928 .1256633 english | 1.591084 .3753257 4.24 0.000 .8554591 2.326709 white | 14.55172 2.421437 6.01 0.000 9.805792 19.29765 lwhitemg | -1.141535 .2220397 -5.14 0.000 -1.576725 -.706345 _cons | 33.52394 27.90491 1.20 0.230 -21.16867 88.21656 ------</p><p>. vce | limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00182 lgdp | -.0015 .011138 lgdpau | .001702 -.001468 .708842 lgdpdfrati~w | -.001517 .002353 -.02379 .086688 lpopau | -.011812 -.003663 -2.36847 .084769 8.36577 lpop | .000273 -.008171 -.000966 -.000306 .004193 .012932 lxrate1 | .000134 .000356 .001315 .001946 -.009552 -.000458 .001028 lremote | .000838 .006052 -.041702 -.013169 .132477 -.004461 -.000767 ldist | .006845 -.001147 -.003474 -.002465 -.038076 .007426 .001981 lopen | .000144 -.000493 -.002432 .004219 .0047 .00106 -.000094 english | -.00405 -.007548 .007059 .008385 -.021407 .011709 .002267 white | .005079 -.056024 .046001 -.006425 -.174675 .068182 .001226 lwhitemg | -.000779 .002771 -.007792 -.000437 .033123 -.004995 -.000184 _cons | .10171 -.05547 21.1504 -.77653 -77.4635 -.097958 .104693</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .081077 ldist | .024977 .329658 lopen | 9.4e-06 .00015 .003666 english | -.021892 .064485 -.00079 .140869 white | -.023501 .127059 .003574 .211424 5.86336 lwhitemg | .0062 -.017172 -.000253 -.019859 -.516554 .049302 _cons | -2.10265 -2.78383 -.024066 -.298859 .781061 -.2112 778.684</p><p>. xtgls lrxsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 234.10 Log likelihood = -769.6612 Prob > chi2 = 0.0000</p><p>------lrxsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0175372 .0422221 0.42 0.678 -.0652165 .100291 lgdp | .0779503 .0817131 0.95 0.340 -.0822045 .2381051 lgdpau | .1481157 .7024295 0.21 0.833 -1.228621 1.524852 lgdpdfrati~w | .0224132 .2536527 0.09 0.930 -.474737 .5195634 lpopau | -.2461605 2.422132 -0.10 0.919 -4.993452 4.501131 lpop | .5194275 .0989398 5.25 0.000 .325509 .7133461 lxrate1 | -.0046211 .0215759 -0.21 0.830 -.0469091 .0376668 lremote | .2790427 .2425167 1.15 0.250 -.1962813 .7543667 ldist | -2.657897 .3974228 -6.69 0.000 -3.436832 -1.878963 lopen | .0265541 .0523308 0.51 0.612 -.0760124 .1291205 english | .6964992 .3387091 2.06 0.040 .0326415 1.360357 white | -.6038455 1.810748 -0.33 0.739 -4.152846 2.945155 lwhitemg | .1152444 .1792043 0.64 0.520 -.2359896 .4664783 _cons | 14.39321 23.67652 0.61 0.543 -32.01191 60.79834 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001783 lgdp | -.001316 .006677 lgdpau | -.00068 .001055 .493407 lgdpdfrati~w | -.000398 .000714 -.033968 .06434 lpopau | -.0038 -.004317 -1.64732 .113925 5.86672 lpop | -.000084 -.004622 -.000294 -.000844 -.009343 .009789 lxrate1 | .000151 .000029 -.000331 .001318 -.003219 -.000169 .000466 lremote | .002295 .003177 -.030037 -.008307 .093934 -.003102 -.000197 ldist | .004837 -.003445 -.01795 -.002023 .048164 .001055 .000513 lopen | -.000118 .000348 .002312 .00053 -.010776 .000652 -.000044 english | -.00371 -.003152 .000711 .002543 .013375 .001724 .000717 white | .005258 -.031948 -.007673 -.014306 -.061165 .037729 .002226 lwhitemg | -.000635 .001747 -.002081 .00073 .015659 -.002424 -.000185 _cons | .037693 -.021871 14.8356 -.976038 -55.2524 .131483 .057286</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .058814 ldist | .029957 .157945 lopen | .000373 -.001015 .002739 english | -.010691 .044799 -.001617 .114724 white | .033487 .031671 -.00126 .138707 3.27881 lwhitemg | -.000183 -.001793 .000122 -.012399 -.314262 .032114 _cons | -1.5937 -2.06935 .107961 -.541045 .690702 -.182544 560.578</p><p>. xtgls lrxsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 562.10 Log likelihood = -1047.562 Prob > chi2 = 0.0000</p><p>------lrxsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1072438 .0754199 1.42 0.155 -.0405765 .2550642 lgdp | .601214 .1369363 4.39 0.000 .3328238 .8696042 lgdpau | -.6103028 .8271108 -0.74 0.461 -2.23141 1.010805 lgdpdfrati~w | -.6872462 .3743247 -1.84 0.066 -1.420909 .0464167 lpopau | 6.926127 2.797327 2.48 0.013 1.443467 12.40879 lpop | .2575047 .1255429 2.05 0.040 .011445 .5035644 lxrate1 | -.1558771 .0347139 -4.49 0.000 -.2239151 -.087839 lremote | .1793591 .233467 0.77 0.442 -.2782278 .6369461 ldist | -3.020695 .4611856 -6.55 0.000 -3.924602 -2.116788 lopen | .1061424 .0913435 1.16 0.245 -.0728876 .2851725 english | .664464 .2623453 2.53 0.011 .1502766 1.178651 white | 12.70483 1.948146 6.52 0.000 8.886532 16.52312 lwhitemg | -1.217417 .1847231 -6.59 0.000 -1.579468 -.8553661 _cons | -85.31569 26.59217 -3.21 0.001 -137.4354 -33.19599 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005688 lgdp | -.00628 .018752 lgdpau | -.004937 .005804 .684112 lgdpdfrati~w | -.000149 -.001295 .03614 .140119 lpopau | .015539 -.028832 -2.23314 -.047965 7.82504 lpop | .001397 -.011748 -.000992 .001995 .004106 .015761 lxrate1 | .000504 .000975 .000521 .000532 -.003612 -.001294 .001205 lremote | .00112 .005905 -.032007 -.027183 .027838 -.006114 .00175 ldist | .014777 -.009566 -.025302 -.004418 .079401 .00346 .000834 lopen | -.000101 .000094 .001833 .002105 -.02742 .001777 -.000508 english | -.005328 .016254 .000331 -.003867 -.007917 -.01126 -.000333 white | .031256 -.05405 -.058885 -.037448 .099547 .049908 -.002136 lwhitemg | -.002853 .002464 .002223 .000813 -.003997 -.002545 .000085 _cons | -.194722 .156664 19.4962 -.017121 -71.7225 -.008848 .014051</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054507 ldist | .023721 .212692 lopen | .002248 -.000587 .008344 english | .008017 .028315 -.003888 .068825 white | .047343 .109524 -.004148 .040557 3.79527 lwhitemg | -.000819 -.012433 .000269 -.006351 -.348822 .034123 _cons | -.349284 -2.82466 .370669 -.390718 -1.31888 .139059 707.144</p><p>. xtgls lrxsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 800.69 Log likelihood = -1134.066 Prob > chi2 = 0.0000</p><p>------lrxsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .232069 .0760681 3.05 0.002 .0829782 .3811598 lgdp | .6264859 .1132875 5.53 0.000 .4044465 .8485253 lgdpau | .1581944 1.156113 0.14 0.891 -2.107745 2.424134 lgdpdfrati~w | -1.075225 .5612491 -1.92 0.055 -2.175253 .0248033 lpopau | 2.597857 3.936566 0.66 0.509 -5.11767 10.31338 lpop | -.0442624 .1193397 -0.37 0.711 -.278164 .1896392 lxrate1 | -.0349215 .0379696 -0.92 0.358 -.1093406 .0394976 lremote | .3590699 .2795137 1.28 0.199 -.1887669 .9069066 ldist | -2.697316 .4411208 -6.11 0.000 -3.561897 -1.832735 lopen | -.109198 .0940351 -1.16 0.246 -.2935034 .0751074 english | 1.159093 .2885311 4.02 0.000 .5935827 1.724604 white | 11.46825 1.338226 8.57 0.000 8.845379 14.09113 lwhitemg | -1.130247 .1291182 -8.75 0.000 -1.383314 -.87718 _cons | -34.24157 36.86677 -0.93 0.353 -106.4991 38.01598 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005786 lgdp | -.00575 .012834 lgdpau | -.005534 .008536 1.3366 lgdpdfrati~w | -.003567 .004274 .045765 .315001 lpopau | .013829 -.030988 -4.41293 .029805 15.4965 lpop | .001433 -.009314 -.003997 -.000562 .010776 .014242 lxrate1 | .00058 .000742 .001656 .000336 -.010561 -.001218 .001442 lremote | .004777 -.002062 -.031072 -.047777 -.002182 -.001747 .001865 ldist | .01533 -.010106 -.028699 -.024871 .056574 .004174 .000838 lopen | -.00029 .000802 .000461 .000836 -.024964 .00087 -.000358 english | -.005565 .010486 .004379 -.000247 -.004634 -.006528 -.000553 white | .03167 -.05553 -.057159 -.040681 .106682 .056604 -.001296 lwhitemg | -.002678 .003383 .002335 -.000754 -.00744 -.003949 .000155 _cons | -.198114 .287686 38.5327 -1.44105 -141.459 -.115126 .101513</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .078128 ldist | .046091 .194588 lopen | .004059 .001044 .008843 english | .002362 .033417 -.003358 .08325 white | .076679 .118335 -.007773 .027625 1.79085 lwhitemg | -.001415 -.011413 .000494 -.004009 -.165305 .016672 _cons | -.180127 -2.35665 .335933 -.493779 -1.88591 .188486 1359.16</p><p>. xtgls lrxsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 415.10 Log likelihood = -1193.443 Prob > chi2 = 0.0000</p><p>------lrxsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2131652 .0515112 4.14 0.000 .112205 .3141253 lgdp | .3172457 .1035501 3.06 0.002 .1142913 .5202002 lgdpau | -2.334992 1.391383 -1.68 0.093 -5.062052 .3920683 lgdpdfrati~w | -2.288022 .629347 -3.64 0.000 -3.52152 -1.054525 lpopau | 7.03519 4.754555 1.48 0.139 -2.283567 16.35395 lpop | .1045119 .0797669 1.31 0.190 -.0518284 .2608522 lxrate1 | -.1024023 .0385219 -2.66 0.008 -.1779038 -.0269007 lremote | 1.110083 .2650279 4.19 0.000 .5906377 1.629528 ldist | -1.225194 .4146246 -2.95 0.003 -2.037844 -.4125448 lopen | -.0073595 .117368 -0.06 0.950 -.2373965 .2226775 english | .5998388 .1868319 3.21 0.001 .233655 .9660225 white | 7.59367 1.346802 5.64 0.000 4.953986 10.23335 lwhitemg | -.6049949 .1303437 -4.64 0.000 -.8604638 -.3495259 _cons | -54.91236 44.1072 -1.24 0.213 -141.3609 31.53616 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002653 lgdp | -.002636 .010723 lgdpau | -.003881 .00648 1.93595 lgdpdfrati~w | -.001469 .00044 .082653 .396078 lpopau | .014114 -.038971 -6.46414 -.130793 22.6058 lpop | .000635 -.005694 -.000693 -.001199 .004125 .006363 lxrate1 | .000204 .00162 .000918 .000648 -.007049 -.001604 .001484 lremote | .000557 .000609 -.027974 -.046935 .048468 .001571 -.000763 ldist | .012235 -.005821 -.025591 -.026137 .0432 .005746 .001804 lopen | -.000079 .000173 .009269 .000981 -.063646 .003153 -.000444 english | -.002906 .005277 .007089 .006177 -.025031 .001011 .000918 white | .013867 -.0312 -.029306 -.059674 .087098 .031927 -.005422 lwhitemg | -.00153 .001002 -.000495 .001072 .003596 -.001909 .000098 _cons | -.219202 .382815 56.7348 .26379 -205.509 -.085221 .064267</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .07024 ldist | .04106 .171914 lopen | .004931 .007952 .013775 english | -.007024 .000575 -.001851 .034906 white | .051321 .112791 .005086 .046624 1.81388 lwhitemg | .001179 -.011749 -.000541 -.005061 -.166069 .016989 _cons | -1.0659 -2.05192 .652051 .141925 -2.03367 .072421 1945.44 . xtgls lrxsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 494.40 Log likelihood = -987.4104 Prob > chi2 = 0.0000</p><p>------lrxsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1261383 .0484066 2.61 0.009 .0312631 .2210136 lgdp | .5206402 .0962362 5.41 0.000 .3320207 .7092597 lgdpau | -1.234674 1.351728 -0.91 0.361 -3.884011 1.414664 lgdpdfrati~w | -1.123268 .5533535 -2.03 0.042 -2.207821 -.0387154 lpopau | 3.90189 4.645 0.84 0.401 -5.202144 13.00592 lpop | .0355666 .0887775 0.40 0.689 -.1384341 .2095673 lxrate1 | -.0414284 .0383462 -1.08 0.280 -.1165856 .0337288 lremote | -.7060725 .2924576 -2.41 0.016 -1.279279 -.1328662 ldist | -2.895546 .444906 -6.51 0.000 -3.767546 -2.023547 lopen | -.0324256 .1056596 -0.31 0.759 -.2395147 .1746634 english | .6133946 .1928456 3.18 0.001 .2354242 .9913651 white | 10.87994 1.694602 6.42 0.000 7.558584 14.2013 lwhitemg | -1.083428 .1510259 -7.17 0.000 -1.379433 -.7874225 _cons | -6.207056 43.5548 -0.14 0.887 -91.5729 79.15878 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002343 lgdp | -.002285 .009261 lgdpau | -.003003 .005765 1.82717 lgdpdfrati~w | -.000951 8.7e-06 -.028511 .3062 lpopau | .010562 -.028404 -6.13584 .182079 21.576 lpop | -.000098 -.005231 -.001479 .00049 .00521 .007881 lxrate1 | 6.3e-06 .001439 .002242 .00171 -.012939 -.001393 .00147 lremote | .002903 .00068 -.020375 -.035283 .050369 -.001259 -.001594 ldist | .011113 -.006875 -.022946 -.014402 .06097 .001298 -.000498 lopen | -.000326 -.000093 .00578 .005245 -.048543 .002252 -.000105 english | -.002496 .003423 .007481 .006396 -.024802 -.001686 .002125 white | .011262 -.031725 .018408 -.020855 -.015507 .030776 -.005429 lwhitemg | -.000974 .000961 -.003237 -.000593 .007717 -.001774 .000268 _cons | -.187534 .262527 54.1825 -2.14965 -197.754 -.05062 .157512</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .085531 ldist | .048244 .197941 lopen | .002999 .000722 .011164 english | -.019305 .006168 -.002765 .037189 white | .02842 .105742 -.002182 .029136 2.87167 lwhitemg | .001776 -.010126 .000315 -.003165 -.247188 .022809 _cons | -1.47563 -2.63901 .593652 .259936 -1.31987 .05259 1897.02</p><p>. xtgls lrxsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 828.13 Log likelihood = -1582.769 Prob > chi2 = 0.0000</p><p>------lrxsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4209204 .068571 6.14 0.000 .2865239 .555317 lgdp | .2232178 .1268896 1.76 0.079 -.0254812 .4719169 lgdpau | -2.710492 1.782687 -1.52 0.128 -6.204494 .7835104 lgdpdfrati~w | -1.142633 .5957429 -1.92 0.055 -2.310268 .0250014 lpopau | 19.63254 6.081428 3.23 0.001 7.713166 31.55192 lpop | .4787969 .1185701 4.04 0.000 .2464037 .7111901 lxrate1 | -.1284497 .0429727 -2.99 0.003 -.2126746 -.0442247 lremote | .3725748 .3112344 1.20 0.231 -.2374334 .9825831 ldist | -1.922553 .4443271 -4.33 0.000 -2.793418 -1.051687 lopen | -.1362005 .1363005 -1.00 0.318 -.4033446 .1309436 english | .2301661 .2776604 0.83 0.407 -.3140383 .7743705 white | 16.99448 2.545067 6.68 0.000 12.00624 21.98272 lwhitemg | -1.620527 .2466579 -6.57 0.000 -2.103967 -1.137086 _cons | -249.4382 56.35812 -4.43 0.000 -359.8981 -138.9783 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004702 lgdp | -.005401 .016101 lgdpau | -.00655 .009256 3.17797 lgdpdfrati~w | -.002304 .003038 -.037522 .35491 lpopau | .020469 -.042388 -10.5939 .143458 36.9838 lpop | .00181 -.010702 -.003732 -.001745 .008984 .014059 lxrate1 | -.000113 .001667 -.001028 .00333 -.00502 -.001409 .001847 lremote | .00513 -.002002 -.046937 -.019799 .05241 .001978 .00129 ldist | .016516 -.011748 -.034238 -.002326 .092478 .009752 -.000634 lopen | -.00042 -.000249 .007028 .008245 -.0465 .003617 -.000309 english | -.004617 .011211 .009261 .001899 -.054317 -.005747 .001695 white | .01873 -.047341 -.063231 -.049275 -.064062 .055835 .00518 lwhitemg | -.001439 .001779 .000755 .001615 .01306 -.002853 -.000459 _cons | -.302124 .415205 93.0305 -1.59077 -336.515 -.143149 .079418</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .096867 ldist | .046249 .197427 lopen | .006059 .004776 .018578 english | -.011444 .027366 -.004593 .077095 white | .138562 -.008967 -.00081 -.021816 6.47736 lwhitemg | -.00493 .001656 .000263 .00149 -.61653 .06084 _cons | -.917751 -2.90916 .44529 .327975 1.68343 -.194182 3176.24 . . clear</p><p>. *Estimating the Australian Immigration Trade relationship; . insheet using k:\book2.txt (54 vars, 11640 obs)</p><p>. drop if ccode ==. (10630 observations deleted)</p><p>. . **Dropping st Kittis . drop if ccode== 451440 (10 observations deleted)</p><p>. . ** Estimation Results . **Regression of Exports without Distinction between "white" and "non-white Aus > tralia" . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Exports . xtgls lrexp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote 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) = 5815.49 Log likelihood = -998.6398 Prob > chi2 = 0.0000</p><p>------lrexp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5450866 .0371692 14.67 0.000 .4722363 .6179369 lgdp | 1.072972 .034714 30.91 0.000 1.004934 1.14101 lgdpau | -3.386017 .8883463 -3.81 0.000 -5.127143 -1.64489 lgdpdfrati~w | -1.914984 .3493125 -5.48 0.000 -2.599624 -1.230344 lpopau | 5.358801 3.095774 1.73 0.083 -.7088037 11.42641 lpop | .0252105 .0390603 0.65 0.519 -.0513462 .1017672 lxrate1 | .0195736 .0162942 1.20 0.230 -.0123624 .0515095 lremote | .0504308 .0864071 0.58 0.559 -.118924 .2197856 ldist | -1.698728 .17031 -9.97 0.000 -2.032529 -1.364926 lopen | .7901952 .0818627 9.65 0.000 .6297472 .9506431 english | .3111868 .085326 3.65 0.000 .1439509 .4784227 white | 3.702642 .6888007 5.38 0.000 2.352618 5.052667 lwhitemg | -.4315249 .0682377 -6.32 0.000 -.5652684 -.2977815 _cons | -2.873595 28.82638 -0.10 0.921 -59.37227 53.62508 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001382 lgdp | -.000799 .001205 lgdpau | -.00284 .002074 .789159 lgdpdfrati~w | .000869 -.001014 -.02879 .122019 lpopau | .010482 -.007861 -2.69909 .152028 9.58381 lpop | .000074 -.000583 .000853 .000263 -.006454 .001526 lxrate1 | -.000049 .000227 -.000106 -.000177 .000371 -.000085 .000265 lremote | -.000255 .000838 .004247 -.001735 -.025105 .000324 -.000056 ldist | .003603 -.002975 -.005196 .004998 .003529 .002362 .000156 lopen | -.000483 .000181 .010254 -.001282 -.057995 .000872 -.00019 english | -.000751 .000982 -.003991 .001721 .025468 -.000493 .000583 white | .007599 -.002147 -.014519 -.001023 .052278 .006626 .001707 lwhitemg | -.000845 .000281 .001687 -.000267 -.006345 -.000529 -.000144 _cons | -.126104 .083788 24.0864 -1.9175 -88.0432 .048601 -.009041</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .007466 ldist | .004808 .029006 lopen | .002783 .002493 .006702 english | -.0013 -.003359 -.003686 .007281 white | .007215 .024245 -.005928 .007883 .474446 lwhitemg | -.000212 -.002324 .000605 -.000485 -.046276 .004656 _cons | .175171 -.237614 .640585 -.294873 -.923327 .09623 830.96</p><p>. **II. Conservative Estimates . *2.1. Aggregate reference priced Exports (conservative) . xtgls lrrefp_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 7460.43 Log likelihood = -1439.321 Prob > chi2 = 0.0000</p><p>------lrrefp_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3597329 .043278 8.31 0.000 .2749095 .4445563 lgdp | 1.061791 .0658046 16.14 0.000 .9328161 1.190765 lgdpau | -.4698944 .4795166 -0.98 0.327 -1.40973 .4699409 lgdpdfrati~w | -.2436122 .3002837 -0.81 0.417 -.8321575 .344933 lpopau | 3.317167 1.741025 1.91 0.057 -.0951798 6.729514 lpop | .1507333 .0800853 1.88 0.060 -.0062309 .3076976 lxrate1 | -.0431776 .0282941 -1.53 0.127 -.098633 .0122777 lremote | -.2263633 .1612456 -1.40 0.160 -.5423989 .0896723 ldist | -3.081047 .3877976 -7.94 0.000 -3.841116 -2.320978 lopen | -.0598596 .0544339 -1.10 0.271 -.1665481 .0468289 english | .3651913 .1774023 2.06 0.040 .0174891 .7128934 white | 8.153683 1.090071 7.48 0.000 6.017184 10.29018 lwhitemg | -.867727 .1169445 -7.42 0.000 -1.096934 -.63852 _cons | -35.1945 17.74629 -1.98 0.047 -69.97659 -.4123991 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001873 lgdp | -.001492 .00433 lgdpau | .000771 -.001047 .229936 lgdpdfrati~w | -.001966 .003198 -.023244 .09017 lpopau | -.002904 -.000987 -.801897 .103997 3.03117 lpop | -.000164 -.00384 .003282 -.001183 -.013609 .006414 lxrate1 | .000026 .00045 .000518 .002503 -.006116 -.000563 .000801 lremote | .000304 -.000247 -.020787 .00154 .091314 -.003158 .000493 ldist | .009973 -.013455 .006588 .001555 -.027328 .006835 .002166 lopen | .000111 -.000284 .002603 .001397 -.011437 .001061 -.000354 english | -.000594 -.002714 .006366 .004602 -.044897 .004567 .001755 white | .009152 -.021435 .019131 -.003314 -.118743 .022831 .001089 lwhitemg | -.001303 .001616 -.004043 .000442 .01971 -.001456 -.000051 _cons | -.041777 .140103 7.38226 -1.29007 -29.6295 .092256 .055733</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .026 ldist | .002748 .150387 lopen | -.002224 .001161 .002963 english | -.003788 .006687 -.000585 .031472 white | -.009404 .067284 .002723 .044578 1.18825 lwhitemg | .003727 -.008047 -.000653 -.002311 -.122669 .013676 _cons | -1.17557 -1.0417 .120884 .518049 .96673 -.183385 314.931</p><p>. *2.2. Aggregate Differentiated Exports (conservative) . xtgls lrdiff_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3789.58 Log likelihood = -1548.294 Prob > chi2 = 0.0000</p><p>------lrdiff_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4851612 .0517517 9.37 0.000 .3837297 .5865928 lgdp | 1.044456 .061335 17.03 0.000 .9242414 1.16467 lgdpau | 2.135056 2.045189 1.04 0.297 -1.87344 6.143552 lgdpdfrati~w | -2.253863 .8265485 -2.73 0.006 -3.873868 -.6338572 lpopau | -8.311631 7.041447 -1.18 0.238 -22.11261 5.489352 lpop | -.0269566 .0810048 -0.33 0.739 -.185723 .1318098 lxrate1 | -.0645498 .0282021 -2.29 0.022 -.119825 -.0092746 lremote | .1248451 .207982 0.60 0.548 -.2827921 .5324823 ldist | -2.210719 .2391094 -9.25 0.000 -2.679365 -1.742073 lopen | .1470198 .0983795 1.49 0.135 -.0458006 .3398401 english | .4100213 .1789204 2.29 0.022 .0593437 .7606988 white | 2.752046 1.152113 2.39 0.017 .4939468 5.010146 lwhitemg | -.2383717 .1083186 -2.20 0.028 -.4506723 -.0260712 _cons | 83.03155 64.81733 1.28 0.200 -44.00808 210.0712 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002678 lgdp | -.001831 .003762 lgdpau | -.002463 .005483 4.1828 lgdpdfrati~w | -.003519 .000968 -.204591 .683182 lpopau | .008529 -.027227 -14.1841 .967811 49.582 lpop | -.000023 -.00323 -.000658 .002798 .004352 .006562 lxrate1 | .000185 .000459 .000968 -.000476 -.007476 -.000737 .000795 lremote | .004135 -.002461 .001325 -.008334 -.026352 -.000918 .000814 ldist | .006113 -.005621 -.006313 .013096 .013411 .003156 .002848 lopen | -.000433 .000884 .015528 .002583 -.084766 .001347 -.000083 english | -.002595 .002312 .001085 .009643 .00664 -.002844 .001202 white | .018506 -.0191 .031409 -.093681 -.136031 .010005 .001629 lwhitemg | -.001675 .001296 -.002711 .007692 .011193 -.000283 -.000099 _cons | -.143697 .357391 125.739 -11.5084 -451.025 -.106799 .061892 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .043257 ldist | .019892 .057173 lopen | .004636 .001002 .009679 english | -.016304 .001609 -.003479 .032013 white | .065964 .02881 -.002534 -.007103 1.32736 lwhitemg | -.003157 -.000943 .000385 .000197 -.121258 .011733 _cons | -.106358 -.758657 .917047 -.030235 .812706 -.098333 4201.29</p><p>. *2.3. Aggregate Homogenous Exports (conservative) . xtgls lrhomo_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1981.62 Log likelihood = -1606.368 Prob > chi2 = 0.0000</p><p>------lrhomo_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4521384 .0529584 8.54 0.000 .3483418 .5559349 lgdp | .9474598 .0967832 9.79 0.000 .7577683 1.137151 lgdpau | -.0975392 1.102913 -0.09 0.930 -2.25921 2.064132 lgdpdfrati~w | -.3326295 .4658966 -0.71 0.475 -1.24577 .5805111 lpopau | -6.206418 3.774691 -1.64 0.100 -13.60468 1.19184 lpop | .2755954 .1071883 2.57 0.010 .0655103 .4856806 lxrate1 | .0651411 .036965 1.76 0.078 -.0073089 .1375911 lremote | -1.134495 .2327208 -4.87 0.000 -1.590619 -.6783702 ldist | -1.451425 .4804366 -3.02 0.003 -2.393063 -.5097867 lopen | .0481781 .0970163 0.50 0.619 -.1419704 .2383266 english | 1.077202 .2878046 3.74 0.000 .5131155 1.641289 white | 12.52898 2.577039 4.86 0.000 7.478075 17.57988 lwhitemg | -1.464724 .274554 -5.33 0.000 -2.00284 -.9266081 _cons | 105.9403 35.55548 2.98 0.003 36.25282 175.6278 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002805 lgdp | -.003019 .009367 lgdpau | .005948 -.010714 1.21642 lgdpdfrati~w | -.003574 .007476 -.057868 .21706 lpopau | -.023079 .023574 -4.04184 .289863 14.2483 lpop | .000267 -.005889 .00026 -.003051 .000945 .011489 lxrate1 | -.000107 .001196 .002925 .002683 -.01864 -.001534 .001366 lremote | .000323 .008324 -.036686 .011715 .101763 -.007139 .000578 ldist | .013771 -.010137 .022308 -.005171 -.13966 .011733 .001904 lopen | .000028 -.001186 -.020197 .006845 .04907 .002235 -.000286 english | -.002298 .00403 .016412 .004153 -.081989 .00457 .002738 white | .009848 -.023503 .091572 -.016183 -.417749 .031883 .004129 lwhitemg | -.00113 .001475 -.010388 .001782 .047261 -.002615 -.000303 _cons | .145262 -.19883 35.474 -3.68159 -130.548 -.11441 .199588</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054159 ldist | .023574 .230819 lopen | .001542 -.001623 .009412 english | -.013379 .017658 -.003762 .082831 white | -.003952 .040808 -.000171 .112608 6.64113 lwhitemg | .002325 -.006127 .00039 -.011813 -.702386 .07538 _cons | -1.50316 -.705556 -.288823 .694052 4.11512 -.457203 1264.19</p><p>. **III. Liberal Estimates . *3.1. Aggregate reference priced Exports (liberal) . xtgls lrrefp_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 2461.78 Log likelihood = -1442.112 Prob > chi2 = 0.0000</p><p>------lrrefp_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4403214 .0493024 8.93 0.000 .3436905 .5369524 lgdp | .826214 .0791184 10.44 0.000 .6711448 .9812832 lgdpau | -.3633832 .4895078 -0.74 0.458 -1.322801 .5960346 lgdpdfrati~w | .2950421 .2161624 1.36 0.172 -.1286285 .7187127 lpopau | -2.257986 1.732674 -1.30 0.193 -5.653964 1.137993 lpop | .2863786 .0839119 3.41 0.001 .1219143 .450843 lxrate1 | -.0187097 .0257184 -0.73 0.467 -.0691169 .0316975 lremote | -.2687707 .1611535 -1.67 0.095 -.5846259 .0470844 ldist | -2.269754 .440807 -5.15 0.000 -3.13372 -1.405788 lopen | .0758982 .0482411 1.57 0.116 -.0186527 .1704491 english | .6827997 .2354134 2.90 0.004 .2213979 1.144201 white | 11.46532 1.958518 5.85 0.000 7.626698 15.30395 lwhitemg | -1.151814 .1921626 -5.99 0.000 -1.528446 -.7751822 _cons | 49.21408 17.27212 2.85 0.004 15.36134 83.06683 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002431 lgdp | -.002502 .00626 lgdpau | .001356 -.003959 .239618 lgdpdfrati~w | -.00186 .004444 -.022822 .046726 lpopau | -.00637 .01279 -.824041 .088204 3.00216 lpop | .000508 -.004493 .004927 -.002947 -.022412 .007041 lxrate1 | .000144 -.000012 .001593 .001244 -.008883 -.000102 .000661 lremote | .001064 -.00019 -.020792 .001011 .079041 -.00306 .000015 ldist | .007791 -.011988 .004937 -.003238 -.030893 .008313 .00247 lopen | -.000152 .000326 .001918 .000961 -.009098 .000363 -.000017 english | -.001568 -.000985 .009907 .002107 -.034578 .002923 .001604 white | .008958 -.0216 .017484 -.00622 -.120595 .020041 .008586 lwhitemg | -.001076 .00132 -.002824 .000347 .01636 -.001103 -.000764 _cons | .0236 -.054801 7.54073 -.941493 -28.5516 .181319 .078858</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .02597 ldist | .01014 .194311 lopen | -.001444 -.000695 .002327 english | -.006927 .031509 .000021 .055419 white | .034978 -.147746 -.004512 .005715 3.83579 lwhitemg | -.001349 .016016 .000196 .001486 -.372409 .036926 _cons | -1.0436 -1.47978 .108123 .031111 2.7361 -.343161 298.326 . *3.2. Aggregate Differentiated Exports (liberal) . xtgls lrdiff_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3461.06 Log likelihood = -1565.773 Prob > chi2 = 0.0000</p><p>------lrdiff_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4563838 .0560761 8.14 0.000 .3464767 .5662908 lgdp | 1.124628 .0692203 16.25 0.000 .9889584 1.260297 lgdpau | 1.840671 2.116364 0.87 0.384 -2.307327 5.988668 lgdpdfrati~w | -2.494503 .8270921 -3.02 0.003 -4.115574 -.8734323 lpopau | -7.357733 7.282089 -1.01 0.312 -21.63037 6.9149 lpop | -.1270657 .0854377 -1.49 0.137 -.2945206 .0403891 lxrate1 | -.0355302 .0287498 -1.24 0.217 -.0918788 .0208184 lremote | .2145838 .2026879 1.06 0.290 -.1826771 .6118448 ldist | -2.176069 .2401949 -9.06 0.000 -2.646843 -1.705296 lopen | .1387432 .0995797 1.39 0.164 -.0564295 .3339158 english | .5288159 .1950392 2.71 0.007 .146546 .9110858 white | 2.764168 1.164121 2.37 0.018 .4825341 5.045803 lwhitemg | -.2335251 .1092397 -2.14 0.033 -.447631 -.0194192 _cons | 73.76181 66.99146 1.10 0.271 -57.53904 205.0627 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003145 lgdp | -.002477 .004791 lgdpau | -.003066 .006334 4.479 lgdpdfrati~w | -.003882 .002257 -.210554 .684081 lpopau | .011017 -.031615 -15.1783 .961071 53.0288 lpop | .000604 -.004146 -.001202 .000509 .008058 .0073 lxrate1 | .000042 .000672 .000908 .000265 -.008173 -.001 .000827 lremote | .003904 -.002419 .000179 -.00619 -.020601 .000268 .000609 ldist | .006631 -.005723 -.006434 .01302 .009374 .003656 .00255 lopen | -.000439 .000798 .015877 .003578 -.085648 .001495 -.000124 english | -.004281 .004791 .002792 .011845 -.00564 -.00484 .001552 white | .018988 -.021528 .024242 -.09419 -.095956 .01246 -.0005 lwhitemg | -.001795 .001527 -.002093 .007981 .00775 -.000386 .000099 _cons | -.168526 .400652 134.471 -11.2497 -482.108 -.160098 .079014</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .041082 ldist | .020564 .057694 lopen | .004504 .001149 .009916 english | -.015913 .001108 -.003339 .03804 white | .06698 .01659 -.003242 -.017935 1.35518 lwhitemg | -.003573 .000211 .000455 .001432 -.123595 .011933 _cons | -.179359 -.705844 .921204 .109942 .466291 -.068958 4487.86</p><p>. *3.3. Aggregate Homogenous Exports (liberal) . xtgls lrhomo_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3284.06 Log likelihood = -1528.93 Prob > chi2 = 0.0000</p><p>------lrhomo_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5710499 .0439589 12.99 0.000 .4848921 .6572078 lgdp | 1.062736 .0666829 15.94 0.000 .93204 1.193432 lgdpau | -.4175937 .6793334 -0.61 0.539 -1.749063 .9138752 lgdpdfrati~w | -.4533446 .487715 -0.93 0.353 -1.409248 .5025593 lpopau | 1.649573 2.435586 0.68 0.498 -3.124087 6.423233 lpop | -.0778631 .0807683 -0.96 0.335 -.2361659 .0804398 lxrate1 | -.0263975 .0301231 -0.88 0.381 -.0854377 .0326426 lremote | -.7541357 .1937434 -3.89 0.000 -1.133866 -.3744056 ldist | -1.855269 .2978927 -6.23 0.000 -2.439128 -1.27141 lopen | .0446621 .072284 0.62 0.537 -.0970119 .1863361 english | .7175206 .2264254 3.17 0.002 .2737349 1.161306 white | 5.943262 2.058041 2.89 0.004 1.909576 9.976948 lwhitemg | -.7961752 .2097127 -3.80 0.000 -1.207205 -.3851458 _cons | -12.86482 24.40776 -0.53 0.598 -60.70314 34.9735 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001932 lgdp | -.001874 .004447 lgdpau | .000136 -.003217 .461494 lgdpdfrati~w | -.003177 .003173 -.059458 .237866 lpopau | -.000096 .005684 -1.5963 .30907 5.93208 lpop | .000042 -.002974 .004043 .001482 -.020804 .006524 lxrate1 | -.000234 .000475 .001553 .002535 -.01063 -.000144 .000907 lremote | .00187 .000936 -.027985 .00139 .119125 -.004117 .000115 ldist | .005386 -.006804 -.006362 .003809 .002752 .009192 .001123 lopen | .000015 -.00065 -.000053 .00548 -.005207 .001596 -.000309 english | -.001518 .002614 .013493 .00825 -.089779 .002161 .002855 white | .009192 -.012464 .036494 -.009295 -.234385 .017355 .007866 lwhitemg | -.000792 .00081 -.004619 .001403 .027402 -.001421 -.000575 _cons | -.035881 -.002432 14.7429 -3.95624 -57.6935 .151812 .110343</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .037537 ldist | .017194 .08874 lopen | -.002171 .000565 .005225 english | -.012604 .012878 -.001255 .051268 white | .013416 .053026 -.003459 .058304 4.23553 lwhitemg | .001031 -.003697 .000198 -.005954 -.425925 .043979 _cons | -1.70187 -.908119 .089502 1.00807 2.22196 -.295811 595.739</p><p>. *IV. Aggregate NON-Manufacturing Exports (Sum of Sitc0,1,2,3,4) . xtgls lrxnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1409.53 Log likelihood = -1124.778 Prob > chi2 = 0.0000</p><p>------lrxnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2201004 .0547604 4.02 0.000 .1127719 .3274288 lgdp | .9502257 .0767228 12.39 0.000 .7998519 1.1006 lgdpau | -4.263008 1.1562 -3.69 0.000 -6.529117 -1.996898 lgdpdfrati~w | -1.394312 .4751422 -2.93 0.003 -2.325574 -.4630508 lpopau | 11.27033 4.014976 2.81 0.005 3.401118 19.13954 lpop | -.0071212 .0902638 -0.08 0.937 -.184035 .1697925 lxrate1 | .0165818 .0334455 0.50 0.620 -.0489702 .0821338 lremote | -.0281053 .3010764 -0.09 0.926 -.6182041 .5619935 ldist | -2.712573 .2454368 -11.05 0.000 -3.19362 -2.231526 lopen | .0858307 .1182234 0.73 0.468 -.145883 .3175443 english | .97468 .2241874 4.35 0.000 .5352807 1.414079 white | 13.08017 .8920998 14.66 0.000 11.33169 14.82865 lwhitemg | -1.406987 .0854557 -16.46 0.000 -1.574477 -1.239497 _cons | -63.58038 37.66016 -1.69 0.091 -137.3929 10.23218 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002999 lgdp | -.002054 .005886 lgdpau | -.003712 .005516 1.3368 lgdpdfrati~w | -.00091 .00072 -.059692 .22576 lpopau | .015285 -.031099 -4.5283 .273512 16.12 lpop | -.000591 -.003916 .002066 .000023 -.008598 .008148 lxrate1 | -.000303 .001155 .000205 .000158 -.003833 -.001325 .001119 lremote | .001564 -.000179 .003614 -.040273 -.031105 -.000314 -.000024 ldist | .00838 -.005586 -.008375 -.004421 .023811 .000987 -.001457 lopen | -.000132 .000281 .015461 .001233 -.09216 .002983 -.000303 english | -.004211 .006492 .000171 .009335 .003525 -.003375 .002964 white | .011687 -.018504 -.00311 -.023666 .052352 .020987 -.002354 lwhitemg | -.001491 .001088 .000088 -.001788 -.003137 -.001209 .000342 _cons | -.210384 .360818 40.0349 -2.82377 -148.244 .052751 .063866</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .090647 ldist | .01734 .060239 lopen | .005397 .003077 .013977 english | -.016542 -.005358 -.006662 .05026 white | .029318 .054506 -.008782 .054853 .795842 lwhitemg | .005675 -.006516 .000806 -.005937 -.068157 .007303 _cons | -.496864 -.825865 1.00778 .021486 -1.57415 .070568 1418.29</p><p>. *V. Aggregate Manufacturing Exports (Sum of Sitc5,6,7,8,9) . xtgls lrxmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1284.60 Log likelihood = -961.8988 Prob > chi2 = 0.0000</p><p>------lrxmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2697305 .0428386 6.30 0.000 .1857685 .3536926 lgdp | .2788842 .0861478 3.24 0.001 .1100376 .4477307 lgdpau | -2.501479 1.115774 -2.24 0.025 -4.688356 -.3146025 lgdpdfrati~w | -4.451854 .4662978 -9.55 0.000 -5.36578 -3.537927 lpopau | 9.945126 3.85153 2.58 0.010 2.396266 17.49399 lpop | .2369152 .0720822 3.29 0.001 .0956367 .3781937 lxrate1 | -.0932609 .026619 -3.50 0.000 -.1454333 -.0410886 lremote | .414723 .1941828 2.14 0.033 .0341317 .7953143 ldist | -2.409012 .246972 -9.75 0.000 -2.893068 -1.924955 lopen | -.0769926 .0536293 -1.44 0.151 -.1821041 .0281188 english | .2561573 .1509766 1.70 0.090 -.0397514 .552066 white | 9.932389 .7794869 12.74 0.000 8.404622 11.46015 lwhitemg | -.9034206 .068868 -13.12 0.000 -1.038399 -.7684417 _cons | -79.60961 35.86685 -2.22 0.026 -149.9074 -9.311877 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001835 lgdp | -.002223 .007421 lgdpau | -.002458 .005573 1.24495 lgdpdfrati~w | -.002585 .004547 -.045471 .217434 lpopau | .0109 -.028821 -4.21451 .227812 14.8343 lpop | .001108 -.00509 -.002412 -.002195 .012469 .005196 lxrate1 | -.000118 .001085 .000829 .000337 -.006161 -.000987 .000709 lremote | .003069 -.004011 -.005282 -.016025 -.004339 .001691 .000423 ldist | .006703 -.008511 -.012301 -.008905 .048289 .00621 .000181 lopen | -.000037 .000039 .004474 .001815 -.022954 .000705 -.000085 english | -.000558 .002139 -.000134 .002328 .003807 -.000781 .000688 white | .014464 -.027455 -.023396 -.029826 .077354 .029768 -.005572 lwhitemg | -.001073 .000984 .000925 .000399 -.003432 -.001779 .000402 _cons | -.183511 .365539 37.3935 -2.64232 -135.856 -.185687 .064311</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .037707 ldist | .023813 .060995 lopen | .000921 .000675 .002876 english | .000703 .012308 -.00057 .022794 white | .061756 .082476 .002696 .010467 .6076 lwhitemg | -.002331 -.005902 -.000323 -.000664 -.049679 .004743 _cons | -.284727 -1.21083 .238294 -.230875 -1.90729 .121903 1286.43</p><p>. . **VI. SITC-1 Digit Level Disaggregate Exports . xtgls lrxsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 735.62 Log likelihood = -1444.518 Prob > chi2 = 0.0000 ------lrxsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3650861 .0865006 4.22 0.000 .195548 .5346243 lgdp | .2923158 .1406021 2.08 0.038 .0167407 .5678908 lgdpau | -.8533963 1.244454 -0.69 0.493 -3.292481 1.585689 lgdpdfrati~w | -.7984442 .6053725 -1.32 0.187 -1.984952 .3880641 lpopau | 9.682235 4.211967 2.30 0.022 1.426932 17.93754 lpop | .0773838 .140511 0.55 0.582 -.1980127 .3527803 lxrate1 | -.0886445 .0467915 -1.89 0.058 -.1803542 .0030652 lremote | .2665413 .2695352 0.99 0.323 -.261738 .7948205 ldist | -2.054953 .49754 -4.13 0.000 -3.030113 -1.079793 lopen | -.3277618 .174326 -1.88 0.060 -.6694344 .0139108 english | 1.499644 .3299268 4.55 0.000 .8529991 2.146288 white | 20.23788 1.843009 10.98 0.000 16.62564 23.85011 lwhitemg | -1.958938 .1770216 -11.07 0.000 -2.305894 -1.611982 _cons | -126.2054 39.43346 -3.20 0.001 -203.4936 -48.91728 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .007482 lgdp | -.009263 .019769 lgdpau | -.009305 .011064 1.54867 lgdpdfrati~w | -.002058 -.001967 .131537 .366476 lpopau | .031437 -.029462 -5.05976 -.236929 17.7407 lpop | .003038 -.01218 -.001813 .001903 -.018412 .019743 lxrate1 | .000442 .001032 -.000186 .000089 .00259 -.001768 .002189 lremote | .002081 .001358 -.045822 -.060744 .00294 -.000463 -.000553 ldist | .020888 -.019985 -.045883 -.033125 .090887 .018662 .001939 lopen | -.00066 -.000251 .007946 -.005238 -.091856 .007062 -.001214 english | -.009689 .011343 .012501 .004342 -.049561 -.001291 .003307 white | .034834 -.074821 -.039072 -.049363 .02339 .082017 .002875 lwhitemg | -.003321 .005118 -.000773 -.00029 -.004475 -.005916 -.000314 _cons | -.374302 .17029 43.832 .958619 -161.554 .133171 -.060111</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .072649 ldist | .04445 .247546 lopen | .011076 .005707 .03039 english | -.004116 .025427 -.006891 .108852 white | .041724 .173731 -.001125 .112729 3.39668 lwhitemg | .001385 -.015987 .000586 -.00924 -.316766 .031337 _cons | .14199 -2.99432 1.09477 .058924 -1.199 .2381 1555</p><p>. xtgls lrxsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 762.31 Log likelihood = -244.942 Prob > chi2 = 0.0000</p><p>------lrxsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0164844 .0172495 0.96 0.339 -.0173239 .0502927 lgdp | .0112795 .0426655 0.26 0.791 -.0723432 .0949023 lgdpau | .0465013 .2615899 0.18 0.859 -.4662056 .5592082 lgdpdfrati~w | -.078103 .1547412 -0.50 0.614 -.3813902 .2251841 lpopau | 3.060671 .9553157 3.20 0.001 1.188287 4.933056 lpop | .2916956 .052546 5.55 0.000 .1887074 .3946837 lxrate1 | -.0266846 .0140562 -1.90 0.058 -.0542343 .0008652 lremote | -.0644208 .0944101 -0.68 0.495 -.2494612 .1206197 ldist | -3.425821 .3349521 -10.23 0.000 -4.082315 -2.769327 lopen | -.0347571 .0257089 -1.35 0.176 -.0851455 .0156314 english | 1.024831 .1333548 7.68 0.000 .7634602 1.286201 white | 19.22744 1.363453 14.10 0.000 16.55512 21.89976 lwhitemg | -1.536676 .1254731 -12.25 0.000 -1.782599 -1.290753 _cons | -22.84545 10.77977 -2.12 0.034 -43.97341 -1.717486 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000298 lgdp | -.000199 .00182 lgdpau | .000379 -.001392 .068429 lgdpdfrati~w | -.000358 .000667 -.005478 .023945 lpopau | -.00154 .006316 -.23546 .028486 .912628 lpop | -.000073 -.001454 .000386 .000059 -.004262 .002761 lxrate1 | .000027 -5.3e-06 .000444 .000366 -.003427 .000023 .000198 lremote | .000159 .000902 -.005886 -.000534 .018403 -.000256 .000072 ldist | .001336 .001779 -.007087 -.000597 .025039 .00016 -.000347 lopen | .000028 -.000056 .000058 -.000076 -.00132 .000091 -.000027 english | -.000238 -.000057 -.000483 -.000478 .011114 .001349 .000043 white | .001144 -.008022 .004907 -.005342 -.033534 .011579 .000379 lwhitemg | -.000171 .000309 -.00049 .00038 .001729 -.000804 -2.3e-07 _cons | .005931 -.110723 2.2578 -.358502 -9.449 .05101 .046477</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .008913 ldist | .009876 .112193 lopen | -.000047 -.000379 .000661 english | .000932 .013069 -.0006 .017783 white | .005983 .022708 -.000596 .029145 1.859 lwhitemg | -.000257 -.004017 .000086 -.003039 -.166178 .015743 _cons | -.340564 -1.44086 .024649 -.3268 .146795 .031425 116.203</p><p>. xtgls lrxsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 882.24 Log likelihood = -1312.091 Prob > chi2 = 0.0000</p><p>------lrxsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2316819 .0580437 3.99 0.000 .1179183 .3454454 lgdp | .6587369 .1101855 5.98 0.000 .4427773 .8746966 lgdpau | -4.591221 1.835576 -2.50 0.012 -8.188883 -.993559 lgdpdfrati~w | .0410704 .8236905 0.05 0.960 -1.573333 1.655474 lpopau | 12.80139 6.35658 2.01 0.044 .3427214 25.26006 lpop | .2881799 .1230482 2.34 0.019 .0470098 .5293499 lxrate1 | -.0518483 .0356937 -1.45 0.146 -.1218067 .0181101 lremote | -.8802338 .3279973 -2.68 0.007 -1.523097 -.2373708 ldist | -2.569092 .5431923 -4.73 0.000 -3.633729 -1.504455 lopen | -.139583 .1824527 -0.77 0.444 -.4971837 .2180176 english | .3262743 .2567076 1.27 0.204 -.1768634 .8294119 white | 11.28273 1.476336 7.64 0.000 8.38916 14.17629 lwhitemg | -1.287784 .1561653 -8.25 0.000 -1.593862 -.9817052 _cons | -75.97934 59.40543 -1.28 0.201 -192.4118 40.45315 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003369 lgdp | -.004333 .012141 lgdpau | -.004849 .009084 3.36934 lgdpdfrati~w | -.005041 .005759 -.056701 .678466 lpopau | .019584 -.053185 -11.3918 .464911 40.4061 lpop | .001582 -.008359 .002698 -.002308 -.023877 .015141 lxrate1 | -.000373 .001664 .001758 .003911 -.011084 -.001094 .001274 lremote | .005289 -.009758 -.020392 -.056786 .034933 .001735 -.0056 ldist | .020163 -.019987 -.017962 -.033399 -.034272 .015894 -.000187 lopen | -.000589 .000238 .020187 -.004284 -.17118 .00834 -.000985 english | -.001463 .005104 .00569 .016499 -.02698 .001198 .003377 white | .029765 -.056861 -.032609 -.020461 .168716 .057735 -.002472 lwhitemg | -.002564 .00313 .000083 -.003053 -.002121 -.004462 -.000432 _cons | -.377689 .791316 100.783 -6.2032 -370.704 .111719 .161767</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .107582 ldist | .048629 .295058 lopen | .017231 .012239 .033289 english | -.017056 .020937 -.005598 .065899 white | .058066 .23147 -.005602 .10383 2.17957 lwhitemg | .004705 -.023968 .001444 -.012979 -.220703 .024388 _cons | -1.20976 -2.07285 1.94273 .079418 -4.47485 .243123 3529</p><p>. xtgls lrxsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 321.39 Log likelihood = -675.9096 Prob > chi2 = 0.0000</p><p>------lrxsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .065456 .0437886 1.49 0.135 -.0203682 .1512802 lgdp | .1582997 .1003081 1.58 0.115 -.0383006 .3549 lgdpau | -.0577646 .7913023 -0.07 0.942 -1.608689 1.493159 lgdpdfrati~w | .2276743 .2783155 0.82 0.413 -.317814 .7731626 lpopau | -1.679031 2.72428 -0.62 0.538 -7.018521 3.66046 lpop | .6572046 .1008485 6.52 0.000 .4595451 .8548641 lxrate1 | .042196 .0307405 1.37 0.170 -.0180543 .1024463 lremote | -.0708114 .2708757 -0.26 0.794 -.601718 .4600953 ldist | -1.929845 .542293 -3.56 0.000 -2.99272 -.8669704 lopen | .0148728 .0533183 0.28 0.780 -.0896291 .1193747 english | 1.663624 .339652 4.90 0.000 .9979184 2.32933 white | 14.50214 2.501213 5.80 0.000 9.599857 19.40443 lwhitemg | -1.161988 .2298253 -5.06 0.000 -1.612437 -.7115382 _cons | 34.99235 26.30579 1.33 0.183 -16.56604 86.55075 ------</p><p>. vce | limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001917 lgdp | -.001486 .010062 lgdpau | .002326 -.001763 .626159 lgdpdfrati~w | -.001186 .002119 -.01969 .077459 lpopau | -.014273 .000097 -2.09776 .075042 7.4217 lpop | .000173 -.007045 -.001008 -.000432 .004996 .01017 lxrate1 | .000154 .000325 .001515 .001679 -.00975 -.000466 .000945 lremote | .000796 .005212 -.037454 -.010368 .120152 -.00356 -.000727 ldist | .007907 -.001014 -.001146 -.001562 -.046956 .00427 .0023 lopen | .000144 -.000584 -.001808 .003375 .003216 .000952 -.000086 english | -.004196 -.006447 .002277 .00653 -.009708 .013905 .002086 white | .004902 -.049571 .044986 -.005201 -.174124 .058808 .001107 lwhitemg | -.000833 .002461 -.007329 -.000393 .031637 -.004375 -.000191 _cons | .117024 -.098449 18.7701 -.740999 -68.7865 -.068551 .100551</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .073374 ldist | .027131 .294082 lopen | -.000407 .00027 .002843 english | -.014658 .052401 -.00017 .115364 white | -.018216 .099248 .004094 .179247 6.25607 lwhitemg | .005014 -.014499 -.00031 -.016487 -.554005 .05282 _cons | -1.96189 -2.33238 -.009268 -.364083 1.03831 -.217772 691.994</p><p>. xtgls lrxsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 384.82 Log likelihood = -785.277 Prob > chi2 = 0.0000</p><p>------lrxsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0281988 .0393518 0.72 0.474 -.0489294 .105327 lgdp | -.0228608 .0740472 -0.31 0.758 -.1679905 .122269 lgdpau | .063737 .7094982 0.09 0.928 -1.326854 1.454328 lgdpdfrati~w | .0416546 .2499384 0.17 0.868 -.4482156 .5315248 lpopau | -.1167047 2.424591 -0.05 0.962 -4.868816 4.635406 lpop | .5934908 .0772241 7.69 0.000 .4421344 .7448473 lxrate1 | .0022447 .0207373 0.11 0.914 -.0383996 .042889 lremote | .3006615 .2200988 1.37 0.172 -.1307242 .7320473 ldist | -2.424368 .3685411 -6.58 0.000 -3.146696 -1.702041 lopen | .01272 .05351 0.24 0.812 -.0921576 .1175976 english | .7914926 .241159 3.28 0.001 .3188296 1.264156 white | -.0278579 1.740736 -0.02 0.987 -3.439638 3.383922 lwhitemg | .0788399 .1734834 0.45 0.650 -.2611813 .4188611 _cons | 13.05102 23.27853 0.56 0.575 -32.57407 58.6761 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001549 lgdp | -.001279 .005483 lgdpau | -.000172 -.001365 .503388 lgdpdfrati~w | -.00034 .001013 -.033971 .062469 lpopau | -.004364 .005396 -1.67489 .109744 5.87864 lpop | .000075 -.004139 .000863 -.000818 -.002582 .005964 lxrate1 | .000116 .000082 -.000482 .001282 -.002375 -.000238 .00043 lremote | .001164 .004246 -.024235 -.005972 .076601 -.003407 -.000243 ldist | .00466 -.003375 -.013828 -.00153 .015942 .005606 .000572 lopen | -.000117 .000168 .002111 .000688 -.008782 .000385 -.000073 english | -.002359 -.005417 -.001388 .003005 -.002251 .009836 .000953 white | .005439 -.031517 .004015 -.009395 -.064663 .032833 .0018 lwhitemg | -.000657 .002105 -.00214 .000383 .01282 -.002353 -.000164 _cons | .042656 -.10938 14.9762 -.937416 -54.595 -.004464 .047291</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .048443 ldist | .023866 .135823 lopen | .000668 -.000188 .002863 english | -.007999 .024223 -.000739 .058158 white | .016625 .021217 -.001283 .100674 3.03016 lwhitemg | .000446 -.00073 .000152 -.007511 -.293463 .030096 _cons | -1.32532 -1.45133 .078186 -.130353 .7592 -.159182 541.89</p><p>. xtgls lrxsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 679.67 Log likelihood = -1041.455 Prob > chi2 = 0.0000</p><p>------lrxsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1523254 .0727728 2.09 0.036 .0096933 .2949575 lgdp | .5306592 .1300282 4.08 0.000 .2758087 .7855097 lgdpau | -.6676752 .7823695 -0.85 0.393 -2.201091 .8657408 lgdpdfrati~w | -.5865269 .3544245 -1.65 0.098 -1.281186 .1081323 lpopau | 7.094986 2.642828 2.68 0.007 1.915139 12.27483 lpop | .4019738 .1122358 3.58 0.000 .1819958 .6219518 lxrate1 | -.1326022 .0325225 -4.08 0.000 -.1963453 -.0688592 lremote | .1676083 .2237968 0.75 0.454 -.2710253 .6062419 ldist | -3.122562 .4634382 -6.74 0.000 -4.030884 -2.21424 lopen | .0970849 .0871401 1.11 0.265 -.0737066 .2678763 english | .5102849 .2432317 2.10 0.036 .0335596 .9870103 white | 13.34274 1.892159 7.05 0.000 9.634174 17.0513 lwhitemg | -1.264587 .180044 -7.02 0.000 -1.617467 -.9117077 _cons | -86.75456 25.19997 -3.44 0.001 -136.1456 -37.36353 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005296 lgdp | -.005787 .016907 lgdpau | -.004232 .004877 .612102 lgdpdfrati~w | .000039 -.001442 .033956 .125617 lpopau | .013577 -.025206 -1.99386 -.044866 6.98454 lpop | .001139 -.009959 -.00067 .002036 .004396 .012597 lxrate1 | .000421 .000867 .00067 .000406 -.004027 -.001139 .001058 lremote | .000724 .00541 -.029807 -.025954 .024488 -.00533 .001483 ldist | .014582 -.010988 -.023158 -.002985 .075807 .006122 .000384 lopen | -.000092 3.1e-06 .001152 .002107 -.023004 .001558 -.000453 english | -.004884 .014569 -.00053 -.004021 -.00866 -.00842 -.000236 white | .027786 -.045321 -.051464 -.031979 .085757 .038982 -.002068 lwhitemg | -.002604 .002004 .001855 .000438 -.003605 -.001964 .000094 _cons | -.179906 .149625 17.3893 -.01901 -64.0634 -.043248 .024706</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .050085 ldist | .019466 .214775 lopen | .001935 -.000486 .007593 english | .008198 .022884 -.00327 .059162 white | .042306 .111072 -.00397 .041602 3.58027 lwhitemg | -.000562 -.012666 .000254 -.005868 -.330485 .032416 _cons | -.271332 -2.81225 .321866 -.314481 -1.26029 .141867 635.038</p><p>. xtgls lrxsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 890.54 Log likelihood = -1129.598 Prob > chi2 = 0.0000</p><p>------lrxsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2634903 .0729514 3.61 0.000 .1205082 .4064724 lgdp | .4974147 .1077421 4.62 0.000 .286244 .7085854 lgdpau | .3990559 1.198351 0.33 0.739 -1.949669 2.747781 lgdpdfrati~w | -1.098956 .575334 -1.91 0.056 -2.22659 .0286782 lpopau | 1.528148 4.086278 0.37 0.708 -6.48081 9.537106 lpop | .1906202 .110048 1.73 0.083 -.0250701 .4063104 lxrate1 | -.0249313 .0375282 -0.66 0.506 -.0984852 .0486226 lremote | .2733737 .2862384 0.96 0.340 -.2876433 .8343907 ldist | -2.79813 .4690536 -5.97 0.000 -3.717458 -1.878802 lopen | -.10015 .0967023 -1.04 0.300 -.289683 .0893831 english | 1.10561 .2899142 3.81 0.000 .5373888 1.673832 white | 12.42683 1.210471 10.27 0.000 10.05435 14.79931 lwhitemg | -1.211777 .117885 -10.28 0.000 -1.442827 -.9807261 _cons | -22.02483 38.31779 -0.57 0.565 -97.12633 53.07666 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005322 lgdp | -.005363 .011608 lgdpau | -.005112 .007993 1.43605 lgdpdfrati~w | -.003622 .004998 .038921 .331009 lpopau | .011958 -.028612 -4.75523 .053746 16.6977 lpop | .0016 -.008151 -.003573 -.001217 .009315 .012111 lxrate1 | .000536 .000568 .001863 .000717 -.011225 -.00089 .001408 lremote | .004983 -.003649 -.031405 -.048179 .003806 -.000305 .001395 ldist | .016277 -.01128 -.031127 -.02644 .070826 .004492 -.000499 lopen | -.000255 .000828 -.000096 .000722 -.025063 .000827 -.000379 english | -.005181 .010074 .004319 .000661 .000357 -.006671 -.001011 white | .030812 -.050915 -.054711 -.038136 .110817 .051138 -.000853 lwhitemg | -.002536 .002964 .002094 -.001198 -.007238 -.003629 .000138 _cons | -.197902 .295254 41.6385 -1.66349 -152.646 -.111707 .122821</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .081932 ldist | .047116 .220011 lopen | .004345 .00156 .009351 english | .001223 .037875 -.003317 .08405 white | .083621 .131239 -.008062 .02112 1.46524 lwhitemg | -.001373 -.013137 .000468 -.003743 -.135251 .013897 _cons | -.301042 -2.76015 .345683 -.596158 -2.22048 .211572 1468.25</p><p>. xtgls lrxsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 391.16 Log likelihood = -1203.291 Prob > chi2 = 0.0000</p><p>------lrxsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2355665 .0534871 4.40 0.000 .1307336 .3403993 lgdp | .2827858 .1032419 2.74 0.006 .0804354 .4851361 lgdpau | -2.160103 1.360107 -1.59 0.112 -4.825865 .5056581 lgdpdfrati~w | -2.196599 .6213841 -3.54 0.000 -3.414489 -.9787081 lpopau | 6.422455 4.642734 1.38 0.167 -2.677136 15.52205 lpop | .2036091 .0893958 2.28 0.023 .0283966 .3788217 lxrate1 | -.0995597 .0387391 -2.57 0.010 -.1754869 -.0236325 lremote | 1.065753 .2694693 3.96 0.000 .5376033 1.593903 ldist | -1.266919 .4505252 -2.81 0.005 -2.149932 -.3839057 lopen | .0223471 .1203216 0.19 0.853 -.2134789 .258173 english | .5813336 .196772 2.95 0.003 .1956676 .9669995 white | 7.848763 1.29828 6.05 0.000 5.304181 10.39334 lwhitemg | -.6322639 .1255754 -5.03 0.000 -.8783871 -.3861407 _cons | -49.59868 43.15447 -1.15 0.250 -134.1799 34.98252 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002861 lgdp | -.002703 .010659 lgdpau | -.004346 .006504 1.84989 lgdpdfrati~w | -.001625 .000083 .085897 .386118 lpopau | .015348 -.03702 -6.1632 -.150777 21.555 lpop | .000454 -.006086 -.000311 .000103 .001479 .007992 lxrate1 | .000267 .001424 .000762 .000529 -.006452 -.001478 .001501 lremote | .001045 .000457 -.030503 -.049377 .05403 .000206 -.00054 ldist | .011326 -.002818 -.024827 -.02501 .044038 .002592 .000803 lopen | -.000059 -.000099 .008568 .001042 -.064125 .003489 -.000362 english | -.003285 .007093 .007535 .005756 -.024226 -.001768 .000635 white | .014244 -.03056 -.034055 -.054051 .098256 .03329 -.004819 lwhitemg | -.001511 .000848 -.000204 .000496 .002451 -.00191 .000123 _cons | -.220133 .331338 54.0074 .521118 -196.02 -.026594 .068261</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .072614 ldist | .036462 .202973 lopen | .005151 .006984 .014477 english | -.007297 .008931 -.002843 .038719 white | .0511 .099998 .005168 .034912 1.68553 lwhitemg | .001337 -.012204 -.000474 -.004525 -.153393 .015769 _cons | -1.04481 -2.35502 .687336 .044719 -2.01771 .090881 1862.31 . xtgls lrxsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 591.08 Log likelihood = -979.5565 Prob > chi2 = 0.0000</p><p>------lrxsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .160872 .0481519 3.34 0.001 .0664961 .2552479 lgdp | .475085 .0956409 4.97 0.000 .2876322 .6625378 lgdpau | -1.586411 1.355788 -1.17 0.242 -4.243706 1.070883 lgdpdfrati~w | -1.125285 .5591662 -2.01 0.044 -2.22123 -.0293394 lpopau | 4.801036 4.659651 1.03 0.303 -4.331713 13.93378 lpop | .0928005 .0843935 1.10 0.271 -.0726078 .2582088 lxrate1 | -.0430943 .0378502 -1.14 0.255 -.1172793 .0310908 lremote | -.7019914 .2943387 -2.38 0.017 -1.278885 -.1250981 ldist | -2.987523 .4247421 -7.03 0.000 -3.820002 -2.155044 lopen | -.0260644 .1062397 -0.25 0.806 -.2342905 .1821617 english | .6234611 .1944633 3.21 0.001 .24232 1.004602 white | 11.28117 1.688126 6.68 0.000 7.972502 14.58983 lwhitemg | -1.122407 .1508677 -7.44 0.000 -1.418102 -.8267113 _cons | -11.10146 43.69419 -0.25 0.799 -96.7405 74.53757 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002319 lgdp | -.002461 .009147 lgdpau | -.00285 .005341 1.83816 lgdpdfrati~w | -.000939 .000354 -.030034 .312667 lpopau | .010334 -.026921 -6.17393 .186915 21.7124 lpop | .000348 -.005322 -.001596 -.000435 .005656 .007122 lxrate1 | -.000082 .001355 .002334 .001949 -.013292 -.001263 .001433 lremote | .002438 .000076 -.021353 -.036032 .055606 .00116 -.001978 ldist | .011315 -.008662 -.022944 -.013565 .060422 .003603 -.000738 lopen | -.00024 -.00034 .005713 .005279 -.048377 .002453 -.000122 english | -.002494 .002335 .007221 .007574 -.025015 -.000343 .002348 white | .012727 -.034334 .015601 -.023706 -.0104 .032226 -.005008 lwhitemg | -.001148 .001344 -.00293 -.000387 .007092 -.00185 .000257 _cons | -.188194 .276097 54.5465 -2.19233 -199.101 -.085515 .166647</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .086635 ldist | .048342 .180406 lopen | .003122 .002005 .011287 english | -.018358 .004017 -.002639 .037816 white | .039084 .111873 -.000778 .035505 2.84977 lwhitemg | .001129 -.01019 .000221 -.003337 -.245887 .022761 _cons | -1.56854 -2.45914 .581394 .28376 -1.45022 .054126 1909.18</p><p>. xtgls lrxsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 973.82 Log likelihood = -1562.085 Prob > chi2 = 0.0000</p><p>------lrxsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .45059 .0606093 7.43 0.000 .3317981 .569382 lgdp | .1922324 .114357 1.68 0.093 -.0319032 .416368 lgdpau | -2.197241 1.730995 -1.27 0.204 -5.589929 1.195447 lgdpdfrati~w | -1.136008 .5765241 -1.97 0.049 -2.265974 -.0060412 lpopau | 17.72324 5.902939 3.00 0.003 6.153692 29.29279 lpop | .5468998 .1072321 5.10 0.000 .3367287 .757071 lxrate1 | -.1103688 .040537 -2.72 0.006 -.1898199 -.0309176 lremote | .3889619 .312606 1.24 0.213 -.2237347 1.001658 ldist | -2.069434 .4490339 -4.61 0.000 -2.949524 -1.189343 lopen | -.122898 .1451333 -0.85 0.397 -.407354 .161558 english | .1559467 .2466019 0.63 0.527 -.3273841 .6392774 white | 17.56814 2.688601 6.53 0.000 12.29858 22.8377 lwhitemg | -1.667658 .2629446 -6.34 0.000 -2.18302 -1.152296 _cons | -230.6075 54.77791 -4.21 0.000 -337.9702 -123.2448 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003673 lgdp | -.003837 .013078 lgdpau | -.005012 .006583 2.99634 lgdpdfrati~w | -.002464 .003951 -.038504 .33238 lpopau | .016002 -.034254 -9.98723 .141722 34.8447 lpop | .001003 -.00865 -.002122 -.002034 .006421 .011499 lxrate1 | -.000338 .002048 -.000628 .003047 -.006445 -.00166 .001643 lremote | .004822 -.002033 -.04837 -.018761 .068413 .002009 .001246 ldist | .016968 -.011776 -.038213 -.000743 .10998 .008822 .000143 lopen | -.000047 -.001284 .005222 .00998 -.038405 .004595 -.000181 english | -.002315 .007235 .007029 .003013 -.051258 -.002459 .002537 white | .009191 -.031825 -.037443 -.047468 -.108332 .039384 .001961 lwhitemg | -.000663 .000611 -.001526 .001335 .018085 -.001625 -.0002 _cons | -.285889 .376267 87.8072 -1.55142 -317.355 -.134198 .083008</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .097723 ldist | .050552 .201631 lopen | .006125 .006023 .021064 english | -.010864 .013596 -.004278 .060812 white | .125785 -.028579 .002261 .012372 7.22858 lwhitemg | -.003522 .003633 .000057 -.001487 -.695602 .06914 _cons | -1.19409 -3.16083 .351023 .486624 2.01066 -.246863 3000.62 . . clear</p><p>. *Estimating the Australian Immigration Trade relationship; . insheet using k:\book2.txt (54 vars, 11640 obs)</p><p>. drop if ccode ==. (10630 observations deleted)</p><p>. . **Dropping Sweden . drop if ccode== 557520 (10 observations deleted)</p><p>. . . . ** Estimation Results . **Regression of Exports without Distinction between "white" and "non-white Aus > tralia" . tsset ccode year panel variable: ccode, 117100 to 725980 time variable: year, 1991 to 2000</p><p>. . **I. Aggregate Exports . xtgls lrexp limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote 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) = 6951.03 Log likelihood = -1022.856 Prob > chi2 = 0.0000</p><p>------lrexp | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5456542 .0383277 14.24 0.000 .4705332 .6207751 lgdp | 1.045737 .037949 27.56 0.000 .9713581 1.120115 lgdpau | -3.222486 .8675337 -3.71 0.000 -4.922821 -1.522152 lgdpdfrati~w | -1.641868 .3372741 -4.87 0.000 -2.302913 -.980823 lpopau | 4.245881 3.026814 1.40 0.161 -1.686565 10.17833 lpop | -.0067007 .0416941 -0.16 0.872 -.0884198 .0750183 lxrate1 | -.0010432 .0150604 -0.07 0.945 -.0305611 .0284748 lremote | .1101648 .0825921 1.33 0.182 -.0517127 .2720423 ldist | -1.376053 .145042 -9.49 0.000 -1.66033 -1.091776 lopen | .8960963 .0792455 11.31 0.000 .740778 1.051415 english | .1798232 .0952413 1.89 0.059 -.0068464 .3664928 white | 2.713596 .6272784 4.33 0.000 1.484153 3.943039 lwhitemg | -.3511574 .0560101 -6.27 0.000 -.4609352 -.2413796 _cons | 8.928215 28.10346 0.32 0.751 -46.15356 64.00999 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001469 lgdp | -.000839 .00144 lgdpau | -.003231 .002695 .752615 lgdpdfrati~w | .0009 -.001285 -.022894 .113754 lpopau | .012314 -.011061 -2.58339 .131101 9.1616 lpop | .00006 -.000732 .000819 -.000092 -.006506 .001738 lxrate1 | -.00001 .0002 -5.2e-07 -.000141 -.000293 -.000066 .000227 lremote | -.000365 .001241 .00457 -.002574 -.024894 .000098 .000086 ldist | .003551 -.002015 -.005078 .003919 .010232 .001956 .00046 lopen | -.000562 .000352 .010894 -.001213 -.058639 .000908 -.000068 english | -.000789 .001565 -.002524 .000295 .016592 -.000978 .000496 white | .006825 -.000865 -.006117 -.015054 -.004836 .009738 .002009 lwhitemg | -.000777 .000135 .000745 .001005 -.000229 -.000866 -.000167 _cons | -.144489 .105436 23.105 -1.68606 -84.0464 .05695 -.004668</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .006821 ldist | .002461 .021037 lopen | .002327 .000952 .00628 english | .000215 .001408 -.002994 .009071 white | .01702 .034359 .000129 .0044 .393478 lwhitemg | -.001277 -.003494 -.00003 -.000158 -.034721 .003137 _cons | .185408 -.275206 .647769 -.248147 -.432936 .046408 789.805</p><p>. **II. Conservative Estimates . *2.1. Aggregate reference priced Exports (conservative) . xtgls lrrefp_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 6998.04 Log likelihood = -1456.825 Prob > chi2 = 0.0000</p><p>------lrrefp_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3526368 .0461213 7.65 0.000 .2622406 .4430329 lgdp | 1.087399 .0672102 16.18 0.000 .95567 1.219129 lgdpau | -.3576417 .5094949 -0.70 0.483 -1.356233 .6409499 lgdpdfrati~w | -.2035654 .3007162 -0.68 0.498 -.7929583 .3858276 lpopau | 3.403582 1.83706 1.85 0.064 -.1969897 7.004153 lpop | .0191166 .0937022 0.20 0.838 -.1645364 .2027695 lxrate1 | -.0370901 .0299593 -1.24 0.216 -.0958093 .021629 lremote | -.2633171 .1661903 -1.58 0.113 -.589044 .0624098 ldist | -3.137468 .3840608 -8.17 0.000 -3.890214 -2.384723 lopen | -.0745789 .0546577 -1.36 0.172 -.1817061 .0325483 english | .599665 .1800798 3.33 0.001 .246715 .9526149 white | 7.075624 1.390546 5.09 0.000 4.350205 9.801044 lwhitemg | -.7871959 .141457 -5.56 0.000 -1.064446 -.5099453 _cons | -37.19282 18.524 -2.01 0.045 -73.4992 -.8864431 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002127 lgdp | -.001626 .004517 lgdpau | .001154 -.001359 .259585 lgdpdfrati~w | -.00196 .0032 -.024594 .09043 lpopau | -.005215 .003683 -.900639 .109468 3.37479 lpop | -.000094 -.004727 .003498 -.001347 -.01886 .00878 lxrate1 | .000133 .000384 .000609 .002673 -.006415 -.000556 .000898 lremote | .000097 .000262 -.021866 .002571 .092944 -.003465 .000594 ldist | .009139 -.010515 .003836 .002125 -.029415 .00507 .002095 lopen | .000047 -.000233 .002506 .001135 -.011753 .001131 -.00036 english | -.001164 -.00135 .006071 .004353 -.046038 .003087 .00162 white | .010129 -.026508 .021617 -.008044 -.154226 .033699 .001424 lwhitemg | -.001499 .002094 -.004519 .000981 .023073 -.00221 -.00011 _cons | -.003121 .048912 8.28143 -1.35792 -32.7514 .17562 .058651</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .027619 ldist | .003308 .147503 lopen | -.001997 .000879 .002987 english | -.004826 .000384 -.000664 .032429 white | -.008887 .05263 .002274 .044056 1.93362 lwhitemg | .003858 -.006749 -.000556 -.002302 -.191321 .02001 _cons | -1.20103 -.949644 .127681 .608696 1.56454 -.238434 343.139</p><p>. *2.2. Aggregate Differentiated Exports (conservative) . xtgls lrdiff_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3527.84 Log likelihood = -1564.257 Prob > chi2 = 0.0000</p><p>------lrdiff_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4563005 .0545833 8.36 0.000 .3493192 .5632817 lgdp | 1.101518 .0630326 17.48 0.000 .977976 1.225059 lgdpau | 2.683343 2.074796 1.29 0.196 -1.383182 6.749868 lgdpdfrati~w | -1.990084 .8327127 -2.39 0.017 -3.622171 -.3579974 lpopau | -10.25662 7.142974 -1.44 0.151 -24.2566 3.743347 lpop | -.1764348 .0797597 -2.21 0.027 -.332761 -.0201086 lxrate1 | -.0649504 .0283753 -2.29 0.022 -.120565 -.0093358 lremote | .0096092 .2005294 0.05 0.962 -.3834212 .4026395 ldist | -2.249135 .2351119 -9.57 0.000 -2.709946 -1.788325 lopen | .1137021 .0925872 1.23 0.219 -.0677655 .2951697 english | .6965304 .181184 3.84 0.000 .3414163 1.051645 white | 1.34412 .8840517 1.52 0.128 -.388589 3.07683 lwhitemg | -.1525254 .0830094 -1.84 0.066 -.3152209 .0101701 _cons | 103.3297 65.72753 1.57 0.116 -25.49388 232.1533 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002979 lgdp | -.002049 .003973 lgdpau | -.003016 .005756 4.30478 lgdpdfrati~w | -.003578 .00155 -.200799 .69341 lpopau | .010102 -.027933 -14.6015 .958654 51.0221 lpop | .000185 -.003346 -.000539 .001083 .004709 .006362 lxrate1 | .000217 .000471 .00074 -.000539 -.006776 -.000832 .000805 lremote | .004138 -.002599 .000506 -.006213 -.02131 -.000026 .000943 ldist | .006649 -.005812 -.007173 .011607 .01683 .002579 .002954 lopen | -.000423 .00077 .015745 .003116 -.080086 .00125 -.000145 english | -.003178 .002574 .000251 .010293 .008849 -.003352 .001247 white | .017772 -.019743 -.009278 -.060353 .02418 .014783 .000464 lwhitemg | -.001649 .001343 .000807 .005247 -.002437 -.000607 .000015 _cons | -.160709 .362478 129.473 -11.4558 -464.036 -.111473 .055137 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .040212 ldist | .022127 .055278 lopen | .004194 .000539 .008572 english | -.014209 .001592 -.003462 .032828 white | .047729 .028381 -.003389 -.008945 .781547 lwhitemg | -.001953 -.000591 .000443 .000741 -.070171 .006891 _cons | -.17878 -.783374 .844573 -.057644 -.70504 .027832 4320.11</p><p>. *2.3. Aggregate Homogenous Exports (conservative) . xtgls lrhomo_cx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1972.90 Log likelihood = -1616.342 Prob > chi2 = 0.0000</p><p>------lrhomo_cx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .446677 .0521212 8.57 0.000 .3445212 .5488327 lgdp | .9611333 .0957755 10.04 0.000 .7734167 1.14885 lgdpau | -.1810943 1.077836 -0.17 0.867 -2.293615 1.931426 lgdpdfrati~w | -.2226945 .4588748 -0.49 0.627 -1.122073 .6766836 lpopau | -5.227534 3.690029 -1.42 0.157 -12.45986 2.00479 lpop | .1801734 .1072209 1.68 0.093 -.0299758 .3903225 lxrate1 | .0610568 .0369252 1.65 0.098 -.0113153 .1334289 lremote | -1.094657 .2320988 -4.72 0.000 -1.549563 -.6397521 ldist | -1.675532 .4835421 -3.47 0.001 -2.623257 -.7278064 lopen | .0448177 .0941469 0.48 0.634 -.1397069 .2293423 english | 1.033835 .2937687 3.52 0.000 .458059 1.609611 white | 11.76113 2.742108 4.29 0.000 6.386698 17.13557 lwhitemg | -1.389895 .2903912 -4.79 0.000 -1.959051 -.8207389 _cons | 94.82158 34.77479 2.73 0.006 26.66423 162.9789 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002717 lgdp | -.002944 .009173 lgdpau | .005733 -.010757 1.16173 lgdpdfrati~w | -.003556 .007389 -.053299 .210566 lpopau | -.02249 .024255 -3.85946 .273518 13.6163 lpop | .000352 -.005812 .000513 -.00292 -.001442 .011496 lxrate1 | -.000128 .00119 .00286 .002692 -.018512 -.001432 .001363 lremote | .000242 .00863 -.03702 .012076 .101365 -.006827 .000702 ldist | .01411 -.010667 .022604 -.005546 -.144862 .012958 .00201 lopen | .000023 -.001102 -.019398 .006614 .047544 .002144 -.000271 english | -.00234 .003561 .017915 .004071 -.088048 .004789 .002933 white | .008125 -.017984 .080355 -.013644 -.434516 .032593 .007517 lwhitemg | -.00097 .000979 -.009172 .001649 .048243 -.002667 -.000606 _cons | .136081 -.203459 33.8768 -3.52359 -124.755 -.098816 .195588</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .05387 ldist | .023958 .233813 lopen | .00161 -.001248 .008864 english | -.014219 .015924 -.003599 .0863 white | .022445 .055085 .001931 .126237 7.51916 lwhitemg | -.000439 -.007403 .00016 -.012999 -.791089 .084327 _cons | -1.50075 -.668169 -.289362 .785949 4.18575 -.457375 1209.29</p><p>. **III. Liberal Estimates . *3.1. Aggregate reference priced Exports (liberal) . xtgls lrrefp_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1740.95 Log likelihood = -1463.817 Prob > chi2 = 0.0000</p><p>------lrrefp_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3685219 .0475939 7.74 0.000 .2752396 .4618042 lgdp | .9062195 .0827255 10.95 0.000 .7440805 1.068358</p><p> lgdpau | -.2696137 .480338 -0.56 0.575 -1.211059 .6718315 lgdpdfrati~w | .1416375 .2469575 0.57 0.566 -.3423903 .6256653 lpopau | -2.358768 1.703705 -1.38 0.166 -5.697968 .9804315 lpop | .1688682 .0997964 1.69 0.091 -.0267291 .3644656 lxrate1 | -.0083309 .027701 -0.30 0.764 -.062624 .0459621 lremote | -.2450162 .1572872 -1.56 0.119 -.5532935 .063261 ldist | -2.246218 .4692124 -4.79 0.000 -3.165858 -1.326579 lopen | .0261051 .0500316 0.52 0.602 -.071955 .1241652 english | 1.014204 .2467207 4.11 0.000 .5306404 1.497768 white | 9.529853 1.995324 4.78 0.000 5.619089 13.44062 lwhitemg | -.9695186 .1961332 -4.94 0.000 -1.353933 -.5851046 _cons | 48.53195 17.15827 2.83 0.005 14.90237 82.16154 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002265 lgdp | -.002441 .006844 lgdpau | .001365 -.003784 .230725 lgdpdfrati~w | -.001867 .004329 -.023381 .060988 lpopau | -.006619 .013085 -.794241 .10087 2.90261 lpop | .000681 -.005775 .004752 -.003388 -.024312 .009959 lxrate1 | .000128 .000062 .001506 .001577 -.008063 -.00023 .000767 lremote | .000716 .000298 -.020267 .002088 .077394 -.003009 .000087 ldist | .007023 -.010282 .001476 -.000972 -.023573 .008847 .002441 lopen | -.000033 -.000034 .002002 .00101 -.008996 .000731 -.00016 english | -.0021 .000702 .008377 .004343 -.03193 .001141 .001908 white | .010245 -.030185 .024184 -.007179 -.135857 .034932 .009108 lwhitemg | -.001151 .001945 -.00352 .000635 .018114 -.002218 -.000792 _cons | .034951 -.078569 7.30845 -1.17525 -27.7288 .194542 .066671</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .024739 ldist | .010469 .22016 lopen | -.001529 -.000683 .002503 english | -.006589 .027974 -.000439 .060871 white | .026925 -.138028 -.003639 .015426 3.98132 lwhitemg | -.000546 .015537 .000144 .000316 -.385685 .038468 _cons | -1.03473 -1.80791 .107302 .046942 2.73688 -.352373 294.406</p><p>. *3.2. Aggregate Differentiated Exports (liberal) . xtgls lrdiff_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3263.39 Log likelihood = -1581.006 Prob > chi2 = 0.0000</p><p>------lrdiff_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4173582 .0576337 7.24 0.000 .3043983 .5303181 lgdp | 1.199152 .0696678 17.21 0.000 1.062606 1.335699 lgdpau | 2.353425 2.159865 1.09 0.276 -1.879832 6.586683 lgdpdfrati~w | -2.210264 .8379873 -2.64 0.008 -3.852689 -.5678392 lpopau | -9.489702 7.43501 -1.28 0.202 -24.06205 5.08265 lpop | -.2799381 .0815085 -3.43 0.001 -.4396918 -.1201844 lxrate1 | -.0263222 .0285417 -0.92 0.356 -.082263 .0296186 lremote | .1248092 .1970316 0.63 0.526 -.2613656 .5109839 ldist | -2.197273 .2341967 -9.38 0.000 -2.656291 -1.738256 lopen | .1374433 .1012824 1.36 0.175 -.0610666 .3359532 english | .8360951 .1977315 4.23 0.000 .4485485 1.223642 white | 1.26571 .8901593 1.42 0.155 -.4789703 3.01039 lwhitemg | -.1360729 .0840425 -1.62 0.105 -.3007931 .0286473 _cons | 97.40136 68.40553 1.42 0.154 -36.67102 231.4737 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003322 lgdp | -.002641 .004854 lgdpau | -.003694 .006639 4.66502 lgdpdfrati~w | -.003989 .002751 -.210322 .702223 lpopau | .013407 -.03274 -15.8203 .976644 55.2794 lpop | .000884 -.004069 -.000839 -.001 .006317 .006644 lxrate1 | .000041 .000659 .000797 .000314 -.00755 -.001 .000815 lremote | .003805 -.002542 -.001314 -.004674 -.015429 .001321 .000661 ldist | .006803 -.005906 -.008081 .011647 .018822 .003034 .002341 lopen | -.000534 .00082 .016653 .003688 -.088214 .00165 -.000197 english | -.004861 .004817 .002628 .013573 -.003262 -.005017 .00161 white | .018327 -.021917 -.017358 -.060063 .065869 .017223 -.001313 lwhitemg | -.001718 .001549 .001467 .005414 -.006073 -.000801 .000185 _cons | -.19445 .412083 140.264 -11.5211 -502.729 -.135198 .073311</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .038821 ldist | .022593 .054848 lopen | .004649 .000568 .010258 english | -.015163 .000351 -.003806 .039098 white | .047998 .014757 -.004 -.018997 .792384 lwhitemg | -.002139 .000828 .000533 .001815 -.071623 .007063 _cons | -.241691 -.795702 .945769 .079517 -1.04234 .056793 4679.32</p><p>. *3.3. Aggregate Homogenous Exports (liberal) . xtgls lrhomo_lx limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 3061.88 Log likelihood = -1544.198 Prob > chi2 = 0.0000</p><p>------lrhomo_lx | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .5476604 .0436759 12.54 0.000 .4620572 .6332635 lgdp | 1.095652 .0679376 16.13 0.000 .9624963 1.228807 lgdpau | -.4842262 .6668864 -0.73 0.468 -1.7913 .8228472 lgdpdfrati~w | -.4065451 .4822572 -0.84 0.399 -1.351752 .5386617 lpopau | 2.620204 2.397025 1.09 0.274 -2.077877 7.318286 lpop | -.1491649 .0830568 -1.80 0.073 -.3119533 .0136234 lxrate1 | -.0365492 .0301805 -1.21 0.226 -.0957018 .0226034 lremote | -.7407223 .1920156 -3.86 0.000 -1.117066 -.3643787 ldist | -2.044919 .3100401 -6.60 0.000 -2.652586 -1.437251 lopen | .0385244 .071533 0.54 0.590 -.1016778 .1787265 english | .7646377 .2320682 3.29 0.001 .3097923 1.219483 white | 5.601831 2.213769 2.53 0.011 1.262923 9.940739 lwhitemg | -.7694203 .2214571 -3.47 0.001 -1.203468 -.3353723 _cons | -25.03624 24.08395 -1.04 0.299 -72.2399 22.16743 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001908 lgdp | -.001846 .004616 lgdpau | .000181 -.003306 .444738 lgdpdfrati~w | -.003379 .003804 -.057592 .232572 lpopau | -.000475 .005942 -1.53998 .301488 5.74573 lpop | .00008 -.003228 .003878 .000801 -.020562 .006898 lxrate1 | -.000328 .000686 .00136 .002728 -.010192 -.000318 .000911 lremote | .001519 .001507 -.02775 .002527 .119022 -.004234 .000177 ldist | .006337 -.008797 -.003419 .000932 -.007583 .010475 .000779 lopen | .000084 -.000823 -.000181 .005292 -.004492 .001733 -.000317 english | -.001223 .001408 .015359 .007467 -.097675 .003056 .002945 white | .007676 -.010544 .03082 -.014081 -.228579 .018189 .007896 lwhitemg | -.00069 .000654 -.004094 .001848 .026873 -.001486 -.000592 _cons | -.037511 .008634 14.2206 -3.8589 -55.978 .141623 .109212</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .03687 ldist | .015141 .096125 lopen | -.002123 .001025 .005117 english | -.013228 .015023 -.00125 .053856 white | .021367 .061884 -.003305 .067012 4.90077 lwhitemg | .000269 -.004594 .000204 -.006653 -.483733 .049043 _cons | -1.69136 -.842545 .077784 1.08775 2.07573 -.281925 580.036</p><p>. *IV. Aggregate NON-Manufacturing Exports (Sum of Sitc0,1,2,3,4) . xtgls lrxnmf limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 l > remote ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1150.44 Log likelihood = -1134.889 Prob > chi2 = 0.0000</p><p>------lrxnmf | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .383796 .0571056 6.72 0.000 .2718711 .495721 lgdp | .706263 .0954982 7.40 0.000 .51909 .893436 lgdpau | -5.368687 1.319668 -4.07 0.000 -7.955188 -2.782186 lgdpdfrati~w | -2.261532 .5646265 -4.01 0.000 -3.36818 -1.154884 lpopau | 15.57145 4.564957 3.41 0.001 6.624295 24.5186 lpop | -.1200941 .0899326 -1.34 0.182 -.2963589 .0561706 lxrate1 | -.0289263 .035184 -0.82 0.411 -.0978857 .0400332 lremote | -.3702193 .3002287 -1.23 0.218 -.9586567 .2182182 ldist | -1.965712 .2509887 -7.83 0.000 -2.457641 -1.473783 lopen | .0113691 .1144196 0.10 0.921 -.2128892 .2356274 english | 1.16618 .224138 5.20 0.000 .7268775 1.605482 white | 10.61783 1.08433 9.79 0.000 8.49258 12.74308 lwhitemg | -1.291884 .0954841 -13.53 0.000 -1.479029 -1.104738 _cons | -102.6176 42.65181 -2.41 0.016 -186.2136 -19.0216 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003261 lgdp | -.003295 .00912 lgdpau | -.002287 .005311 1.74152 lgdpdfrati~w | -.002472 .004402 -.116001 .318803 lpopau | .012452 -.038374 -5.88773 .488541 20.8388 lpop | .000374 -.005597 -.000406 -.001996 .00715 .008088 lxrate1 | -.000555 .001876 .001051 .001006 -.009455 -.001662 .001238 lremote | .001296 -.000953 .002616 -.028515 -.02811 .000925 .00034 ldist | .009504 -.011321 -.006505 -.008033 .027675 .005565 -.002553 lopen | .000124 -.000332 .009987 .003537 -.063604 .002918 -.0004 english | -.004992 .007584 .002974 .008899 -.016197 -.002061 .002856 white | .014196 -.033032 .015435 -.066599 .001939 .036256 -.006969 lwhitemg | -.001596 .002109 -.001684 .002579 .002206 -.00242 .000688 _cons | -.195149 .502851 52.0449 -5.12424 -191.185 -.162126 .131649</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .090137 ldist | .019127 .062995 lopen | .006481 .004512 .013092 english | -.013211 -.006133 -.00608 .050238 white | .063202 .086352 -.002799 .060353 1.17577 lwhitemg | .003369 -.008172 .00045 -.006141 -.094547 .009117 _cons | -.547267 -.922979 .664073 .215025 -1.69096 .055189 1819.18</p><p>. *V. Aggregate Manufacturing Exports (Sum of Sitc5,6,7,8,9) . xtgls lrxmfn limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lremot > e ldist lopen english white lwhitemg, igls panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1) Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 1129.89 Log likelihood = -968.1228 Prob > chi2 = 0.0000</p><p>------lrxmfn | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2460644 .0425943 5.78 0.000 .1625811 .3295477 lgdp | .3322839 .0909142 3.65 0.000 .1540954 .5104724</p><p> lgdpau | -2.673927 1.113522 -2.40 0.016 -4.856391 -.4914643 lgdpdfrati~w | -4.363588 .4665615 -9.35 0.000 -5.278032 -3.449144 lpopau | 10.24796 3.846444 2.66 0.008 2.709069 17.78685 lpop | .152672 .0744784 2.05 0.040 .006697 .298647 lxrate1 | -.0763373 .0277449 -2.75 0.006 -.1307164 -.0219583 lremote | .5394838 .1734035 3.11 0.002 .199619 .8793485 ldist | -2.377755 .2315444 -10.27 0.000 -2.831573 -1.923936 lopen | -.0803098 .0533961 -1.50 0.133 -.1849641 .0243445 english | .4279658 .1616453 2.65 0.008 .1111467 .7447848 white | 9.51916 .9210721 10.33 0.000 7.713892 11.32443 lwhitemg | -.8567374 .0801531 -10.69 0.000 -1.013834 -.6996403 _cons | -81.31127 35.81229 -2.27 0.023 -151.5021 -11.12047 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001814 lgdp | -.002601 .008265 lgdpau | -.002731 .006362 1.23993 lgdpdfrati~w | -.002284 .005226 -.043621 .21768 lpopau | .012241 -.032994 -4.19998 .222282 14.7951 lpop | .001728 -.005868 -.003008 -.003843 .014827 .005547 lxrate1 | -.000167 .001215 .000954 .000765 -.006987 -.000973 .00077 lremote | .001847 -.003739 -.004249 -.014134 -.008143 .003906 -.0002 ldist | .005627 -.009012 -.01227 -.009208 .052201 .007529 -.000662 lopen | -.000104 .000189 .0048 .001993 -.023818 .000642 -.000082 english | -.002076 .003493 .0016 .002917 -.000686 -.000749 .000356 white | .015963 -.033246 -.025743 -.047659 .073182 .037882 -.00676 lwhitemg | -.001231 .001473 .00115 .001933 -.003026 -.002303 .000437 _cons | -.178702 .410985 37.2658 -2.60505 -135.533 -.231239 .084803</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .030069 ldist | .019078 .053613 lopen | .000806 .000307 .002851 english | -.002285 .008684 -.000787 .026129 white | .076561 .085271 .002952 .008955 .848374 lwhitemg | -.004075 -.006096 -.000366 -.000678 -.070001 .006425 _cons | -.171218 -1.16457 .246278 -.163359 -1.91779 .122813 1282.52</p><p>. . **VI. SITC-1 Digit Level Disaggregate Exports . xtgls lrxsitc0 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 744.68 Log likelihood = -1444.101 Prob > chi2 = 0.0000</p><p>------lrxsitc0 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .3160094 .0871469 3.63 0.000 .1452047 .4868142 lgdp | .387482 .1420892 2.73 0.006 .1089924 .6659716 lgdpau | -.8546879 1.218147 -0.70 0.483 -3.242213 1.532837 lgdpdfrati~w | -.7974676 .5950918 -1.34 0.180 -1.963826 .3688909 lpopau | 10.29891 4.125379 2.50 0.013 2.213316 18.38451 lpop | -.0643328 .137648 -0.47 0.640 -.334118 .2054523 lxrate1 | -.0897273 .0467747 -1.92 0.055 -.1814041 .0019495 lremote | .3232571 .2563048 1.26 0.207 -.1790911 .8256053 ldist | -2.189206 .4606173 -4.75 0.000 -3.091999 -1.286412 lopen | -.3109182 .1730291 -1.80 0.072 -.650049 .0282125 english | 1.555377 .3138059 4.96 0.000 .9403284 2.170425 white | 19.84002 1.983557 10.00 0.000 15.95232 23.72772 lwhitemg | -1.924299 .187002 -10.29 0.000 -2.290816 -1.557782 _cons | -135.2704 38.55099 -3.51 0.000 -210.8289 -59.71183 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .007595 lgdp | -.009676 .020189 lgdpau | -.010013 .01078 1.48388 lgdpdfrati~w | -.002647 -.00252 .127866 .354134 lpopau | .031226 -.029133 -4.85161 -.232688 17.0188 lpop | .003297 -.012147 -.001505 .001816 -.017068 .018947 lxrate1 | .000497 .001087 -.000079 .000141 .002795 -.002078 .002188 lremote | .002747 .002109 -.041181 -.055666 -.000377 -.000775 -.000584 ldist | .019379 -.021909 -.048483 -.036116 .078639 .022286 .002141 lopen | -.000719 -.000321 .007979 -.005883 -.092025 .007112 -.001118 english | -.010996 .009867 .01027 .002317 -.05754 .003156 .003172 white | .0313 -.070647 -.045776 -.069691 .026718 .085023 .001004 lwhitemg | -.00282 .004924 .000974 .002697 -.005253 -.006516 -.000181 _cons | -.337979 .176163 42.0715 .998155 -154.919 .083093 -.064642</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .065692 ldist | .046437 .212168 lopen | .011669 .005015 .029939 english | -.002771 .013777 -.00678 .098474 white | .04997 .168865 .004509 .121566 3.9345 lwhitemg | -.000778 -.013426 .00026 -.008502 -.362673 .03497</p><p>_cons | .09621 -2.40272 1.09893 .322143 -1.1917 .206372 1486.18</p><p>. xtgls lrxsitc1 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 568.33 Log likelihood = -239.8758 Prob > chi2 = 0.0000</p><p>------lrxsitc1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0061314 .0157835 0.39 0.698 -.0248037 .0370666 lgdp | .0474349 .0400538 1.18 0.236 -.031069 .1259388 lgdpau | .0396912 .2709724 0.15 0.884 -.4914049 .5707873 lgdpdfrati~w | -.0847518 .1492824 -0.57 0.570 -.3773399 .2078363 lpopau | 3.098813 .9800291 3.16 0.002 1.177991 5.019635 lpop | .2359788 .0500976 4.71 0.000 .1377893 .3341684 lxrate1 | -.0299055 .0138376 -2.16 0.031 -.0570267 -.0027843 lremote | -.0719915 .0952807 -0.76 0.450 -.2587382 .1147552 ldist | -3.337012 .3320588 -10.05 0.000 -3.987836 -2.686189 lopen | -.0380775 .0262427 -1.45 0.147 -.0895123 .0133573 english | 1.192904 .1443258 8.27 0.000 .9100309 1.475778 white | 15.59212 2.001871 7.79 0.000 11.66852 19.51571 lwhitemg | -1.266166 .176166 -7.19 0.000 -1.611445 -.920887 _cons | -23.9606 10.9323 -2.19 0.028 -45.38752 -2.533677 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .000249 lgdp | -.000161 .001604 lgdpau | .000324 -.001096 .073426 lgdpdfrati~w | -.000251 .000455 -.00568 .022285 lpopau | -.001511 .005229 -.250897 .027599 .960457 lpop | -.000074 -.001257 .000109 .000101 -.003422 .00251 lxrate1 | .000025 -5.6e-06 .000388 .000349 -.003232 .000037 .000191 lremote | .000168 .000904 -.00584 -.000588 .0172 -.000163 .000082 ldist | .001102 .002112 -.007071 -.00067 .027714 -.000374 -.000366 lopen | .000029 -.000071 .000057 -.000046 -.00162 .000131 -.000019 english | -.000303 .000379 -.000643 -.000657 .012718 .000847 -4.2e-06 white | .000959 -.005176 .005813 -.005778 -.013615 .005577 -.000512 lwhitemg | -.000137 .000102 -.000618 .000402 .000505 -.000342 .000067 _cons | .008373 -.102091 2.38063 -.331821 -9.84181 .048169 .044634</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .009078 ldist | .010388 .110263 lopen | -.000012 -.000361 .000689 english | .000879 .016311 -.000553 .02083 white | .006744 .019217 -.000171 .032862 4.00749 lwhitemg | -.000351 -.00359 .000056 -.003455 -.346689 .031034 _cons | -.329627 -1.47005 .028825 -.381221 -.146337 .048891 119.515</p><p>. xtgls lrxsitc2 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 685.74 Log likelihood = -1324.777 Prob > chi2 = 0.0000</p><p>------lrxsitc2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2203668 .0578373 3.81 0.000 .1070078 .3337259 lgdp | .693775 .1147901 6.04 0.000 .4687906 .9187594 lgdpau | -5.525915 1.892194 -2.92 0.003 -9.234548 -1.817282 lgdpdfrati~w | -.2522162 .8555319 -0.29 0.768 -1.929028 1.424595 lpopau | 15.94141 6.555506 2.43 0.015 3.092851 28.78996 lpop | .158561 .1285217 1.23 0.217 -.0933369 .4104589 lxrate1 | -.0599824 .0372998 -1.61 0.108 -.1330887 .0131238 lremote | -.7280438 .344435 -2.11 0.035 -1.403124 -.0529637 ldist | -2.85027 .4408735 -6.47 0.000 -3.714367 -1.986174 lopen | -.2038434 .1838988 -1.11 0.268 -.5642784 .1565915 english | .3226479 .2668073 1.21 0.227 -.2002849 .8455807 white | 13.80032 2.219513 6.22 0.000 9.450157 18.15049 lwhitemg | -1.476773 .2031419 -7.27 0.000 -1.874924 -1.078623 _cons | -100.5607 61.35199 -1.64 0.101 -220.8084 19.687 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .003345 lgdp | -.004678 .013177 lgdpau | -.004355 .008852 3.5804 lgdpdfrati~w | -.005537 .006543 -.071688 .731935 lpopau | .018484 -.054362 -12.1008 .566107 42.9747 lpop | .001913 -.009364 .002832 -.003911 -.019768 .016518 lxrate1 | -.00048 .001767 .001724 .004234 -.010954 -.001411 .001391 lremote | .005035 -.009872 -.017696 -.062385 .02635 .002586 -.006319 ldist | .016119 -.019997 -.012874 -.041164 -.023861 .014015 -.002631 lopen | -.00037 -.000028 .023459 -.003711 -.177152 .007964 -.001171 english | -.001554 .005552 .003674 .01564 -.017461 -2.6e-06 .003598 white | .03419 -.074637 -.012553 -.170109 .023237 .084991 -.008905 lwhitemg | -.002805 .004513 -.00141 .009121 .009007 -.006639 .000144 _cons | -.327919 .810996 106.953 -7.41507 -394.897 .052159 .192647</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .118635 ldist | .051528 .194369 lopen | .018452 .011529 .033819 english | -.01699 .018251 -.007505 .071186 white | .168913 .250729 .02048 .121262 4.92624 lwhitemg | -.003459 -.02229 -.000585 -.014447 -.436189 .041267 _cons | -1.26494 -1.37509 1.96283 .007014 -3.61879 .142956 3764.07</p><p>. xtgls lrxsitc3 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 259.91 Log likelihood = -722.0268 Prob > chi2 = 0.0000</p><p>------lrxsitc3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .058905 .0445113 1.32 0.186 -.0283356 .1461455 lgdp | .1213641 .1064109 1.14 0.254 -.0871975 .3299256 lgdpau | -.0798677 .8673386 -0.09 0.927 -1.77982 1.620085 lgdpdfrati~w | .2232906 .3022891 0.74 0.460 -.3691851 .8157663 lpopau | -1.492309 2.97991 -0.50 0.617 -7.332824 4.348207 lpop | .6266062 .1142091 5.49 0.000 .4027606 .8504519 lxrate1 | .0452596 .0325427 1.39 0.164 -.018523 .1090421 lremote | -.1918048 .2913684 -0.66 0.510 -.7628764 .3792669 ldist | -1.79727 .5645831 -3.18 0.001 -2.903832 -.6907074 lopen | .0088712 .0619077 0.14 0.886 -.1124656 .1302081 english | 1.66809 .3659562 4.56 0.000 .9508294 2.385351 white | 7.363284 3.096768 2.38 0.017 1.29373 13.43284 lwhitemg | -.5881447 .2587863 -2.27 0.023 -1.095357 -.0809328 _cons | 33.64263 28.63247 1.17 0.240 -22.47597 89.76124 ------. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001981 lgdp | -.001581 .011323 lgdpau | .002054 -.001748 .752276 lgdpdfrati~w | -.001497 .002426 -.024809 .091379 lpopau | -.013419 -.001792 -2.51587 .087785 8.87986 lpop | .000146 -.008378 -.000855 -.000158 .00465 .013044 lxrate1 | .000151 .000374 .0015 .001989 -.010483 -.000498 .001059 lremote | .000966 .006531 -.043236 -.01301 .138875 -.005437 -.000944 ldist | .007448 -.000212 -.001794 -.00304 -.055075 .008222 .002096 lopen | .000155 -.000527 -.002343 .00442 .004135 .001119 -.000102 english | -.004167 -.00737 .00577 .008173 -.018493 .012889 .00239 white | .006393 -.062155 .102771 -.009761 -.369058 .073961 .000145 lwhitemg | -.000916 .003276 -.01204 -.000088 .047655 -.005529 -.000099 _cons | .115319 -.093031 22.4572 -.805179 -82.0654 -.103814 .11564</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .084896 ldist | .026144 .318754 lopen | -.000044 .000142 .003833 english | -.021056 .063775 -.000672 .133924 white | -.089342 .154554 .003696 .205285 9.58997 lwhitemg | .011377 -.020435 -.000267 -.019598 -.780962 .06697 _cons | -2.2087 -2.48978 -.016886 -.333169 2.88728 -.35863 819.818</p><p>. xtgls lrxsitc4 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 229.38 Log likelihood = -775.1753 Prob > chi2 = 0.0000</p><p>------lrxsitc4 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .0098472 .0410209 0.24 0.810 -.0705522 .0902467 lgdp | .0682492 .0799128 0.85 0.393 -.0883769 .2248754 lgdpau | .0538861 .6828489 0.08 0.937 -1.284473 1.392245 lgdpdfrati~w | .0086487 .2443547 0.04 0.972 -.4702778 .4875752 lpopau | -.1664601 2.351246 -0.07 0.944 -4.774818 4.441898 lpop | .5283226 .0978034 5.40 0.000 .3366314 .7200138 lxrate1 | -.0029528 .0211706 -0.14 0.889 -.0444464 .0385409 lremote | .3147309 .2366404 1.33 0.184 -.1490758 .7785376 ldist | -2.637359 .3937224 -6.70 0.000 -3.40904 -1.865677 lopen | .0244552 .0511858 0.48 0.633 -.0758672 .1247776 english | .7005106 .3341357 2.10 0.036 .0456166 1.355405 white | .2971079 2.137766 0.14 0.889 -3.892836 4.487052 lwhitemg | .0435147 .2040782 0.21 0.831 -.3564712 .4435006 _cons | 15.16607 22.94294 0.66 0.509 -29.80127 60.1334 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .001683 lgdp | -.001199 .006386 lgdpau | -.000447 .000792 .466283 lgdpdfrati~w | -.000297 .000589 -.033065 .059709 lpopau | -.00452 -.003183 -1.55559 .109693 5.52836 lpop | -.000055 -.004625 -.000451 -.000834 -.007619 .009566 lxrate1 | .000142 .000029 -.000318 .001264 -.002996 -.000171 .000448 lremote | .002201 .003239 -.027755 -.008006 .085807 -.002981 -.000195 ldist | .004555 -.003136 -.016652 -.002111 .04127 .001469 .000474 lopen | -.000093 .000308 .002169 .000452 -.009952 .000573 -.000033 english | -.003739 -.003131 .000539 .002295 .01107 .002704 .00066 white | .004974 -.031854 -.004821 -.016683 -.071385 .038196 .00253 lwhitemg | -.00059 .001753 -.002112 .000975 .015887 -.002468 -.000209 _cons | .044227 -.031031 13.9992 -.924363 -51.9529 .105341 .053822</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .055999 ldist | .029043 .155017 lopen | .000405 -.000867 .00262 english | -.011142 .044344 -.001488 .111647 white | .044709 .021272 -.001207 .1433 4.57004 lwhitemg | -.001461 -.000382 .000118 -.012512 -.425065 .041648</p><p>_cons | -1.48804 -1.96473 .098372 -.505044 .77827 -.187492 526.378</p><p>. xtgls lrxsitc5 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 555.34 Log likelihood = -1053.64 Prob > chi2 = 0.0000</p><p>------lrxsitc5 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1222841 .075 1.63 0.103 -.0247132 .2692815 lgdp | .5944689 .1370878 4.34 0.000 .3257818 .863156 lgdpau | -.7247424 .8292963 -0.87 0.382 -2.350133 .9006485 lgdpdfrati~w | -.6904444 .3750205 -1.84 0.066 -1.425471 .0445823 lpopau | 7.279445 2.804397 2.60 0.009 1.782927 12.77596 lpop | .250871 .1245825 2.01 0.044 .0066938 .4950483 lxrate1 | -.1491111 .0345652 -4.31 0.000 -.2168576 -.0813645 lremote | .1961435 .2342885 0.84 0.402 -.2630535 .6553406 ldist | -3.094593 .4443017 -6.97 0.000 -3.965408 -2.223778 lopen | .1087849 .0910271 1.20 0.232 -.0696249 .2871948 english | .6857382 .2620249 2.62 0.009 .1721788 1.199298 white | 11.64816 2.351784 4.95 0.000 7.038749 16.25757 lwhitemg | -1.136143 .2118302 -5.36 0.000 -1.551322 -.7209631 _cons | -87.46675 26.60711 -3.29 0.001 -139.6157 -35.31777 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005625 lgdp | -.006299 .018793 lgdpau | -.004844 .005829 .687732 lgdpdfrati~w | -.000105 -.001401 .036711 .14064 lpopau | .015526 -.029074 -2.24443 -.048557 7.86464 lpop | .001441 -.011698 -.001113 .001933 .004075 .015521 lxrate1 | .000478 .000981 .000538 .000498 -.003688 -.001271 .001195 lremote | .000916 .006017 -.032237 -.027798 .02723 -.005916 .001716 ldist | .014668 -.01028 -.02485 -.004563 .078271 .002826 .000616 lopen | -.000124 .000126 .001958 .002161 -.02754 .001807 -.0005 english | -.005532 .016525 .000297 -.004127 -.008018 -.011553 -.000377 white | .029107 -.052023 -.059596 -.045647 .091179 .05139 -.002581 lwhitemg | -.002654 .002282 .002298 .001513 -.003401 -.002622 .000126 _cons | -.193926 .164251 19.5866 -.012641 -72.0601 .00166 .016976</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .054891 ldist | .022229 .197404 lopen | .00223 -.000458 .008286 english | .008246 .027598 -.003878 .068657 white | .053345 .106486 -.002783 .042129 5.53089 lwhitemg | -.001312 -.011827 .000169 -.006481 -.484803 .044872 _cons | -.326162 -2.62977 .367063 -.383109 -1.23279 .129125 707.938</p><p>. xtgls lrxsitc6 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 726.32 Log likelihood = -1135.859 Prob > chi2 = 0.0000</p><p>------lrxsitc6 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2498051 .0745189 3.35 0.001 .1037508 .3958594 lgdp | .5966373 .1120665 5.32 0.000 .3769909 .8162836 lgdpau | .0911493 1.133113 0.08 0.936 -2.129712 2.312011 lgdpdfrati~w | -1.125451 .5538726 -2.03 0.042 -2.211021 -.0398802 lpopau | 2.688735 3.854831 0.70 0.485 -4.866595 10.24406 lpop | -.017097 .1192646 -0.14 0.886 -.2508513 .2166573 lxrate1 | -.032553 .0377391 -0.86 0.388 -.1065202 .0414143 lremote | .399143 .2760041 1.45 0.148 -.141815 .940101 ldist | -2.664705 .4366279 -6.10 0.000 -3.52048 -1.80893 lopen | -.1043257 .093396 -1.12 0.264 -.2873786 .0787271 english | 1.229429 .2869487 4.28 0.000 .6670199 1.791838 white | 12.83692 2.67474 4.80 0.000 7.594528 18.07932 lwhitemg | -1.245992 .2322128 -5.37 0.000 -1.701121 -.7908632 _cons | -34.45201 36.12659 -0.95 0.340 -105.2588 36.3548 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .005553 lgdp | -.005523 .012559 lgdpau | -.005429 .008461 1.28395 lgdpdfrati~w | -.003479 .004254 .049529 .306775 lpopau | .013789 -.030292 -4.23168 .017326 14.8597 lpop | .001332 -.009185 -.004017 -.000651 .010136 .014224 lxrate1 | .000539 .000755 .00163 .00031 -.010305 -.001214 .001424 lremote | .004401 -.001855 -.031229 -.04799 -.001487 -.001639 .00177 ldist | .015002 -.01028 -.028956 -.025173 .05887 .004387 .000575 lopen | -.000362 .000856 .000712 .000926 -.024598 .000893 -.000363 english | -.00615 .010885 .004894 -.000347 -.00648 -.006369 -.000654 white | .02772 -.053589 -.034973 -.070674 .034545 .054878 -.002276 lwhitemg | -.002358 .003218 .00048 .001819 -.001589 -.00373 .000232 _cons | -.19595 .280753 36.9085 -1.31811 -135.668 -.108894 .101256 | lremote ldist lopen english white lwhitemg _cons ------+------lremote | .076178 ldist | .044393 .190644 lopen | .003828 .000986 .008723 english | .002117 .032646 -.003326 .08234 white | .075571 .10635 -.007894 .061627 7.15424 lwhitemg | -.001461 -.010388 .000526 -.006961 -.611707 .053923 _cons | -.157904 -2.3317 .324435 -.474922 -1.11276 .126789 1305.13</p><p>. xtgls lrxsitc7 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 436.75 Log likelihood = -1196.241 Prob > chi2 = 0.0000</p><p>------lrxsitc7 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .2165027 .0512099 4.23 0.000 .1161331 .3168723 lgdp | .315293 .1027394 3.07 0.002 .1139275 .5166586 lgdpau | -2.098713 1.385178 -1.52 0.130 -4.813613 .6161866 lgdpdfrati~w | -2.162755 .6297187 -3.43 0.001 -3.396981 -.9285287 lpopau | 6.464583 4.733427 1.37 0.172 -2.812764 15.74193 lpop | .1132565 .0774451 1.46 0.144 -.038533 .265046 lxrate1 | -.1015419 .0383533 -2.65 0.008 -.176713 -.0263709 lremote | 1.091796 .2639381 4.14 0.000 .5744868 1.609105 ldist | -1.240897 .408511 -3.04 0.002 -2.041563 -.4402296 lopen | .0071914 .1180251 0.06 0.951 -.2241334 .2385163 english | .6170806 .1855664 3.33 0.001 .2533771 .9807841 white | 6.025571 1.040568 5.79 0.000 3.986096 8.065047 lwhitemg | -.4922947 .1102249 -4.47 0.000 -.7083315 -.2762579 _cons | -51.59758 43.88999 -1.18 0.240 -137.6204 34.42522 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .002622 lgdp | -.002591 .010555 lgdpau | -.00375 .006287 1.91872 lgdpdfrati~w | -.001313 .000166 .085473 .396546 lpopau | .014066 -.038616 -6.40855 -.136597 22.4053 lpop | .000583 -.005444 -.000638 -.001101 .003965 .005998 lxrate1 | .000202 .001557 .000962 .000703 -.006949 -.001548 .001471 lremote | .000326 .000943 -.028221 -.047055 .047431 .001543 -.000842 ldist | .01231 -.00588 -.025911 -.025932 .045614 .0051 .001857 lopen | -.000157 .000347 .009621 .001121 -.064488 .003066 -.000456 english | -.002944 .005395 .006837 .006399 -.023802 .000727 .000926 white | .014076 -.030214 -.033755 -.036515 .11628 .027804 -.004509 lwhitemg | -.001551 .000943 -.000026 -.000666 .000552 -.001578 .000032 _cons | -.220815 .379867 56.2701 .287875 -203.655 -.077543 .062183</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .069663 ldist | .041162 .166881 lopen | .00496 .007809 .01393 english | -.007292 -.000541 -.002036 .034435 white | .035822 .099694 .003895 .035679 1.08278 lwhitemg | .002277 -.010564 -.000423 -.004242 -.106147 .01215 _cons | -1.04318 -2.02589 .655715 .142766 -2.12255 .087807 1926.33</p><p>. xtgls lrxsitc8 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog</p><p>Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 468.83 Log likelihood = -984.5645 Prob > chi2 = 0.0000</p><p>------lrxsitc8 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .1347076 .0501959 2.68 0.007 .0363255 .2330897 lgdp | .5004814 .0982001 5.10 0.000 .3080128 .6929499 lgdpau | -1.416528 1.351408 -1.05 0.295 -4.065239 1.232183 lgdpdfrati~w | -1.093459 .5578126 -1.96 0.050 -2.186752 -.0001669 lpopau | 4.493575 4.644366 0.97 0.333 -4.609214 13.59636 lpop | .0654407 .0948023 0.69 0.490 -.1203684 .2512498 lxrate1 | -.0405272 .0385106 -1.05 0.293 -.1160066 .0349521 lremote | -.7490996 .3005592 -2.49 0.013 -1.338185 -.1600144 ldist | -2.92902 .4530034 -6.47 0.000 -3.81689 -2.041149 lopen | -.0411491 .1069811 -0.38 0.701 -.2508282 .1685299 english | .6497035 .1966899 3.30 0.001 .2641984 1.035209 white | 9.245326 2.005891 4.61 0.000 5.313852 13.1768 lwhitemg | -.9564102 .1733056 -5.52 0.000 -1.296083 -.6167375 _cons | -10.66235 43.59736 -0.24 0.807 -96.1116 74.78691 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .00252 lgdp | -.002421 .009643 lgdpau | -.003099 .005772 1.8263 lgdpdfrati~w | -.001145 .000106 -.028979 .311155 lpopau | .01086 -.028753 -6.13123 .183859 21.5701 lpop | -.000218 -.00566 -.001357 .000608 .00523 .008987 lxrate1 | .00002 .001449 .002283 .001713 -.013253 -.001477 .001483 lremote | .003662 .000346 -.021445 -.036117 .053971 -.002073 -.001454 ldist | .011545 -.008022 -.023482 -.01464 .062757 .002867 -.000646 lopen | -.000252 -.000209 .00596 .005413 -.049642 .002309 -.000087 english | -.002451 .003049 .007456 .006275 -.02533 -.00114 .002199 white | .012424 -.037228 .029055 -.026618 -.0366 .036197 -.005354 lwhitemg | -.00104 .001382 -.004074 -.000103 .009427 -.002239 .00028 _cons | -.196409 .280785 54.1418 -2.1654 -197.822 -.069295 .162801</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .090336 ldist | .049695 .205212 lopen | .003291 .001129 .011445 english | -.018573 .007176 -.00264 .038687 white | .027663 .11894 .000066 .040197 4.0236 lwhitemg | .002004 -.0112 .000155 -.003936 -.338363 .030035</p><p>_cons | -1.54622 -2.73742 .601996 .252399 -1.33538 .052461 1900.73</p><p>. xtgls lrxsitc9 limmig lgdp lgdpau lgdpdfrationew lpopau lpop lxrate1 lr > emote ldist lopen english white lwhitemg, panels(hetero)corr(psar1)nolog Cross-sectional time-series FGLS regression</p><p>Coefficients: generalized least squares Panels: heteroskedastic Correlation: panel-specific AR(1)</p><p>Estimated covariances = 100 Number of obs = 1000 Estimated autocorrelations = 100 Number of groups = 100 Estimated coefficients = 14 Time periods = 10 Wald chi2(13) = 829.27 Log likelihood = -1576.058 Prob > chi2 = 0.0000</p><p>------lrxsitc9 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------+------limmig | .4328379 .0676923 6.39 0.000 .3001634 .5655124 lgdp | .2064774 .1257627 1.64 0.101 -.0400129 .4529678 lgdpau | -2.194494 1.739165 -1.26 0.207 -5.603194 1.214206 lgdpdfrati~w | -1.027448 .5807702 -1.77 0.077 -2.165737 .1108405 lpopau | 18.11086 5.930198 3.05 0.002 6.487887 29.73384 lpop | .4956545 .1185095 4.18 0.000 .2633802 .7279288 lxrate1 | -.1254214 .042463 -2.95 0.003 -.2086473 -.0421956 lremote | .3978871 .3115938 1.28 0.202 -.2128256 1.0086 ldist | -1.862036 .4460463 -4.17 0.000 -2.736271 -.9878015 lopen | -.1071395 .138117 -0.78 0.438 -.3778439 .1635649 english | .2501511 .2738397 0.91 0.361 -.2865649 .7868672 white | 17.73801 2.317862 7.65 0.000 13.19509 22.28094 lwhitemg | -1.677799 .2262906 -7.41 0.000 -2.121321 -1.234278 _cons | -238.6157 55.03871 -4.34 0.000 -346.4895 -130.7418 ------</p><p>. vce</p><p>| limmig lgdp lgdpau lgdpdf~w lpopau lpop lxrate1 ------+------limmig | .004582 lgdp | -.005236 .015816 lgdpau | -.006106 .008645 3.02469 lgdpdfrati~w | -.002207 .003195 -.039543 .337294 lpopau | .019283 -.041798 -10.0707 .142015 35.1672 lpop | .00167 -.010477 -.003457 -.001806 .009079 .014044 lxrate1 | -.00013 .001672 -.000956 .003454 -.005526 -.001412 .001803 lremote | .005074 -.00192 -.047789 -.018142 .061032 .001879 .001238 ldist | .016406 -.011658 -.034297 -.001885 .096178 .009356 -.000624 lopen | -.000437 -.000298 .007124 .008731 -.04477 .003784 -.000312 english | -.004349 .010658 .008621 .001569 -.053932 -.00557 .001669 white | .020199 -.049173 -.062407 -.034605 -.016379 .055846 .004629 lwhitemg | -.001543 .001909 .001006 .000509 .008749 -.00288 -.000411 _cons | -.293552 .422006 88.3879 -1.51744 -320.216 -.151506 .086407</p><p>| lremote ldist lopen english white lwhitemg _cons ------+------lremote | .097091 ldist | .047113 .198957 lopen | .00594 .004359 .019076 english | -.011492 .024858 -.004809 .074988 white | .115576 .004095 .001791 -.021805 5.37248 lwhitemg | -.003166 .000735 .000026 .001531 -.51205 .051207 _cons | -1.05078 -2.98707 .417236 .372118 .966195 -.136912 3029.26</p><p> log: K:\Roger-Australia\Robustness-1\South Africa-Sweden_Exports.log log type: text closed on: 18 Aug 2006, 19:22:47 ------</p>