------------------------------------------------------------------------------------------------ log: C:\Henderson\china\Restud_final\table4.log log type: text opened on: 28 Sep 2005, 14:27:02 . . ********************************************************************** . * . * Sept 28, 2005 . * . * REStud . * Au and Henderson, "Are Chinese Cities Too Small?" . * STATA program for regressions in Table 4 . * . * Prefecture level cities 1997 on 1990 instruments . * . * 1. Table 4, 1st col. - IV Estimation Generalized Leontief . * 2. Table 4, 2nd col. - IV Estimation Regular Taylor Series . * . ********************************************************************** . . insheet using restud.csv, comma (27 vars, 205 obs) . . gen lnlna = ln(lna) . gen lnrylna = lnyna - lnlna . gen lnrklna = lnk - lnlna . gen lna2 = lna^2 . gen mslna = ryms*lna . gen ms90ar90 = ryms90*area90 . gen area902 = area90^2 . gen ryms902 = ryms90^2 . gen ryms2 = ryms^2 . gen lna5 = lna^.5 . gen ryms5 = ryms^.5 . gen ms5lna5 = ryms5*lna5 . gen ryms905 = ryms90^5 . gen area905 = area90^5 . gen ms5area905 = ryms905*area905 . . ************************************************************* . * 1. Table 4, 1st col. - IV Estimation Generalized Leontief * . ************************************************************* . global iv "area90 book90 doctor90 tel90 lnroad90 drw drc agn90 lnrkl90 nofdi90 lnisiv90 ms5are > a905 rfdln90 lmp6_906 tnt6m906 pshs90 area905 ryms90 ryms905" . ivreg lnrylna (lnrklna lna5 lna ms5lna5 ryms5 ryms rfdlnan lmp6_976 tcint6m6 pshs90 = $iv) Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 205 -------------+------------------------------ F( 10, 194) = 24.28 Model | 26.3242315 10 2.63242315 Prob > F = 0.0000 Residual | 19.7318793 194 .101710718 R-squared = 0.5716 -------------+------------------------------ Adj R-squared = 0.5495 Total | 46.0561108 204 .225765249 Root MSE = .31892 ------------------------------------------------------------------------------ lnrylna | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lnrklna | .362179 .0915536 3.96 0.000 .1816107 .5427472 lna5 | .3658275 .1158685 3.16 0.002 .1373039 .5943512 lna | -.00805 .002542 -3.17 0.002 -.0130636 -.0030364 ms5lna5 | -.1843588 .0871792 -2.11 0.036 -.3562996 -.0124181 ryms5 | .2179159 1.932978 0.11 0.910 -3.594434 4.030266 ryms | .2055478 .6148737 0.33 0.739 -1.007148 1.418243 rfdlnan | .0683004 .0285892 2.39 0.018 .0119149 .1246859 lmp6_976 | .6803608 .1167027 5.83 0.000 .4501919 .9105298 tcint6m6 | 3.943772 3.161234 1.25 0.214 -2.291028 10.17857 pshs90 | .0014206 .0049121 0.29 0.773 -.0082674 .0111087 _cons | .0057463 1.354983 0.00 0.997 -2.666643 2.678135 ------------------------------------------------------------------------------ Instrumented: lnrklna lna5 lna ms5lna5 ryms5 ryms rfdlnan lmp6_976 tcint6m6 pshs90 Instruments: area90 book90 doctor90 tel90 lnroad90 drw drc agn90 lnrkl90 nofdi90 lnisiv90 ms5area905 rfdln90 lmp6_906 tnt6m906 pshs90 area905 ryms90 ryms905 ------------------------------------------------------------------------------ . predict res1, residual . reg res1 $iv Source | SS df MS Number of obs = 205 -------------+------------------------------ F( 19, 185) = 0.54 Model | 1.04381638 19 .054937704 Prob > F = 0.9392 Residual | 18.6880631 185 .101016557 R-squared = 0.0529 -------------+------------------------------ Adj R-squared = -0.0444 Total | 19.7318795 204 .096724899 Root MSE = .31783 ------------------------------------------------------------------------------ res1 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- area90 | -.0008233 .000844 -0.98 0.331 -.0024883 .0008418 book90 | .0004774 .00052 0.92 0.360 -.0005485 .0015032 doctor90 | -.0006742 .3044456 -0.00 0.998 -.6013057 .5999573 tel90 | .0053467 .0099061 0.54 0.590 -.0141968 .0248901 lnroad90 | .0429288 .0415563 1.03 0.303 -.0390563 .1249139 drw | -.0092926 .1109458 -0.08 0.933 -.2281741 .209589 drc | -.0874995 .0830413 -1.05 0.293 -.2513291 .0763301 agn90 | .0089704 .0238716 0.38 0.708 -.0381252 .056066 lnrkl90 | -.0178831 .0661988 -0.27 0.787 -.1484848 .1127186 nofdi90 | -.0137306 .0638644 -0.21 0.830 -.1397267 .1122656 lnisiv90 | -.0473761 .1755981 -0.27 0.788 -.3938083 .299056 ms5area905 | 5.84e-15 3.78e-15 1.54 0.124 -1.62e-15 1.33e-14 rfdln90 | -.1828663 .2745091 -0.67 0.506 -.7244369 .3587044 lmp6_906 | -.0358415 .1087276 -0.33 0.742 -.2503468 .1786638 tnt6m906 | -.4749147 .7594065 -0.63 0.532 -1.973125 1.023296 pshs90 | -.0029045 .006292 -0.46 0.645 -.0153177 .0095087 area905 | -2.28e-14 4.44e-14 -0.51 0.609 -1.10e-13 6.49e-14 ryms90 | -.0076408 .0290331 -0.26 0.793 -.0649194 .0496378 ryms905 | 2.85e-06 5.75e-06 0.50 0.620 -8.48e-06 .0000142 _cons | .4156079 .7787698 0.53 0.594 -1.120804 1.952019 ------------------------------------------------------------------------------ . . ************************************************************** . * 2. Table 4, 2nd col. - IV Estimation Regular Taylor Series * . ************************************************************** . global iv "area90 book90 doctor90 tel90 lnroad90 drw drc agn90 lnrkl90 nofdi90 lnisiv90 ms90ar > 90 rfdln90 lmp6_906 tnt6m906 pshs90 area902 ryms90 ryms902" . ivreg lnrylna (lnrklna lna lna2 mslna rfdlnan lmp6_976 tcint6m6 pshs90 ryms ryms2 = $iv) Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 205 -------------+------------------------------ F( 10, 194) = 23.48 Model | 25.4715002 10 2.54715002 Prob > F = 0.0000 Residual | 20.5846106 194 .10610624 R-squared = 0.5531 -------------+------------------------------ Adj R-squared = 0.5300 Total | 46.0561108 204 .225765249 Root MSE = .32574 ------------------------------------------------------------------------------ lnrylna | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lnrklna | .3625104 .089726 4.04 0.000 .1855468 .5394739 lna | .010187 .0029983 3.40 0.001 .0042735 .0161004 lna2 | -.000014 3.94e-06 -3.55 0.000 -.0000218 -6.22e-06 mslna | -.0047407 .0019906 -2.38 0.018 -.0086668 -.0008147 rfdlnan | .0652003 .0291052 2.24 0.026 .0077971 .1226035 lmp6_976 | .7456295 .1086081 6.87 0.000 .5314253 .9598337 tcint6m6 | 3.943126 3.279667 1.20 0.231 -2.525254 10.41151 ryms | -.1282483 .2784367 -0.46 0.646 -.6774 .4209034 ryms2 | .0507644 .0521118 0.97 0.331 -.052014 .1535427 pshs90 | .0020891 .0045214 0.46 0.645 -.0068284 .0110066 _cons | .5932165 1.012462 0.59 0.559 -1.40363 2.590063 ------------------------------------------------------------------------------ Instrumented: lnrklna lna lna2 mslna rfdlnan lmp6_976 tcint6m6 pshs90 ryms ryms2 Instruments: area90 book90 doctor90 tel90 lnroad90 drw drc agn90 lnrkl90 nofdi90 lnisiv90 ms90ar90 rfdln90 lmp6_906 tnt6m906 pshs90 area902 ryms90 ryms902 ------------------------------------------------------------------------------ . predict res2, residual . reg res2 $iv Source | SS df MS Number of obs = 205 -------------+------------------------------ F( 19, 185) = 0.52 Model | 1.0340908 19 .054425832 Prob > F = 0.9537 Residual | 19.55052 185 .105678486 R-squared = 0.0502 -------------+------------------------------ Adj R-squared = -0.0473 Total | 20.5846108 204 .100904955 Root MSE = .32508 ------------------------------------------------------------------------------ res2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- area90 | -.0025433 .0021526 -1.18 0.239 -.0067902 .0017036 book90 | .000484 .0005292 0.91 0.362 -.0005601 .0015281 doctor90 | .0741951 .3111338 0.24 0.812 -.5396315 .6880217 tel90 | -.0006758 .0101381 -0.07 0.947 -.0206769 .0193253 lnroad90 | .0482503 .0426193 1.13 0.259 -.035832 .1323325 drw | .048313 .1145272 0.42 0.674 -.1776344 .2742603 drc | -.068779 .0858659 -0.80 0.424 -.2381814 .1006233 agn90 | -.0008606 .0245585 -0.04 0.972 -.0493112 .0475901 lnrkl90 | .0038425 .0680563 0.06 0.955 -.1304237 .1381086 nofdi90 | -.0454967 .0662233 -0.69 0.493 -.1761466 .0851531 lnisiv90 | -.0522515 .1803933 -0.29 0.772 -.4081439 .303641 ms90ar90 | .0005751 .0007141 0.81 0.422 -.0008337 .0019839 rfdln90 | -.1586565 .2837592 -0.56 0.577 -.7184765 .4011635 lmp6_906 | -.0036298 .116049 -0.03 0.975 -.2325795 .2253198 tnt6m906 | -.2715671 .7812446 -0.35 0.729 -1.812861 1.269727 pshs90 | -.003736 .0064266 -0.58 0.562 -.0164148 .0089429 area902 | 4.03e-06 4.15e-06 0.97 0.332 -4.15e-06 .0000122 ryms90 | -.0387388 .0743094 -0.52 0.603 -.1853415 .1078639 ryms902 | .0017156 .0080697 0.21 0.832 -.0142049 .0176361 _cons | .1441888 .7986366 0.18 0.857 -1.431417 1.719795 ------------------------------------------------------------------------------ . . log close log: C:\Henderson\china\Restud_final\table4.log log type: text closed on: 28 Sep 2005, 14:27:02 ------------------------------------------------------------------------------------------------