___ ____ ____ ____ ____ (R) /__ / ____/ / ____/ ___/ / /___/ / /___/ 14.2 Copyright 1985-2015 StataCorp LLC Statistics/Data Analysis StataCorp 4905 Lakeway Drive Special Edition College Station, Texas 77845 USA 800-STATA-PC http://www.stata.com 979-696-4600 stata@stata.com 979-696-4601 (fax) Single-user Stata perpetual license: Serial number: 10699393 Licensed to: Andrey Notes: 1. Unicode is supported; see help unicode_advice. 2. Maximum number of variables is set to 5000; see help set_maxvar. . . use "C:\Users\503\Desktop\Pfinal\willingness\rotation fallow papers\Data_cmp_wta_Guangxi_Guilin_May > 2017.dta", clear . cmp(PGM=per sex age educ Household_size work agri_laborforce log_agrifield log_income) (per=suppol > subfun training substarec Log_gmcost Log_distance Farming_experience sex age educ Household_size wo > rk agri_laborforce log_agrifield log_income), ind(\$cmp_probit \$cmp_probit)technique(dfp)qui robust Fitting individual models as starting point for full model fit. Note: For programming reasons, these initial estimates may deviate from your specification. For exact fits of each equation alone, run cmp separately on each. Fitting full model. Mixed-process regression Number of obs = 336 Wald chi2(24) = 192.92 Log pseudolikelihood = -216.50697 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------------ | Robust | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------------+---------------------------------------------------------------- PGM | per | -1.427822 .2461268 -5.80 0.000 -1.910221 -.945422 sex | .000995 .1546313 0.01 0.995 -.3020768 .3040668 age | -.0110981 .0081922 -1.35 0.176 -.0271545 .0049582 educ | .0065714 .1380495 0.05 0.962 -.2640006 .2771435 Household_size | -.0605965 .0486446 -1.25 0.213 -.1559382 .0347452 work | .7167621 .5112532 1.40 0.161 -.2852757 1.7188 agri_laborforce | .2769086 .0862091 3.21 0.001 .1079419 .4458754 log_agrifield | .8405942 .1669238 5.04 0.000 .5134296 1.167759 log_income | -.4500774 .0990332 -4.54 0.000 -.6441789 -.2559759 _cons | .0011159 .6450184 0.00 0.999 -1.263097 1.265329 -------------------+---------------------------------------------------------------- per | suppol | -.7304955 .2201504 -3.32 0.001 -1.161982 -.2990087 subfun | .0914278 .6052602 0.15 0.880 -1.09486 1.277716 training | .373606 .3144559 1.19 0.235 -.2427163 .9899282 substarec | -.0061738 .1518042 -0.04 0.968 -.3037045 .2913569 Log_gmcost | .006838 .082042 0.08 0.934 -.1539614 .1676373 Log_distance | .1418383 .0714008 1.99 0.047 .0018953 .2817812 Farming_experience | -.0228821 .0071081 -3.22 0.001 -.0368136 -.0089506 sex | -.0322994 .1681107 -0.19 0.848 -.3617903 .2971915 age | -.0018197 .0082286 -0.22 0.825 -.0179474 .014308 educ | .1069333 .1754056 0.61 0.542 -.2368554 .4507221 Household_size | -.0891372 .0644118 -1.38 0.166 -.2153821 .0371076 work | .4689756 .4779899 0.98 0.327 -.4678675 1.405819 agri_laborforce | .3055715 .0936262 3.26 0.001 .1220674 .4890755 log_agrifield | .6822785 .1526292 4.47 0.000 .3831308 .9814262 log_income | -.3484402 .1404614 -2.48 0.013 -.6237394 -.0731409 _cons | -.9625016 .71848 -1.34 0.180 -2.370696 .4456932 -------------------+---------------------------------------------------------------- /atanhrho_12 | 7.66269 2.181888 3.51 0.000 3.386268 11.93911 -------------------+---------------------------------------------------------------- rho_12 | .9999996 1.93e-06 .997713 1 ------------------------------------------------------------------------------------ . cmp(PGM=per sex age educ Household_size work agri_laborforce log_agrifield log_income) (per=suppol > subfun substarec sex age educ Household_size work agri_laborforce log_agrifield log_income), ind(\$c > mp_probit \$cmp_probit)technique(dfp)qui robust Fitting individual models as starting point for full model fit. Note: For programming reasons, these initial estimates may deviate from your specification. For exact fits of each equation alone, run cmp separately on each. Fitting full model. Mixed-process regression Number of obs = 336 Wald chi2(20) = 310.61 Log pseudolikelihood = -227.77038 Prob > chi2 = 0.0000 --------------------------------------------------------------------------------- | Robust | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- PGM | per| 1.61742 .3283409 4.93 0.000 .9738832 2.260956 sex | .0797005 .2658756 0.30 0.764 -.441406 .6008071 age | -.011893 .0097077 -1.23 0.221 -.0309198 .0071338 educ | -.1983302 .2235062 -0.89 0.375 -.6363944 .239734 Household_size | -.0279909 .0491038 -0.57 0.569 -.1242326 .0682508 work | -.2051442 .4138275 -0.50 0.620 -1.016231 .6059427 agri_laborforce | .1076249 .0697434 1.54 0.123 -.0290697 .2443195 log_agrifield | .6930375 .1953829 3.55 0.000 .310094 1.075981 log_income | -.4617292 .1821793 -2.53 0.011 -.8187941 -.1046644 _cons | .2771271 .7558825 0.37 0.714 -1.204375 1.75863 ----------------+---------------------------------------------------------------- per | suppol | 1.448768 .3735824 3.88 0.000 .7165603 2.180976 subfun | .1639442 .5251728 0.31 0.755 -.8653756 1.193264 substarec | .0168626 .1167632 0.14 0.885 -.2119891 .2457143 sex | -.0886886 .2493817 -0.36 0.722 -.5774678 .4000906 age | .0147974 .0116126 1.27 0.203 -.0079628 .0375577 educ | .3319688 .2624947 1.26 0.206 -.1825113 .846449 Household_size | -.0218363 .0482596 -0.45 0.651 -.1164233 .0727508 work | .4085358 .4170006 0.98 0.327 -.4087704 1.225842 agri_laborforce | .1928555 .0690099 2.79 0.005 .0575985 .3281125 log_agrifield | -.1050426 .1793575 -0.59 0.558 -.4565767 .2464916 log_income | .2157635 .2749644 0.78 0.433 -.3231568 .7546838 _cons | -3.314865 .7972313 -4.16 0.000 -4.87741 -1.75232 ----------------+---------------------------------------------------------------- /atanhrho_12 | -8.508997 17.76741 -0.48 0.632 -43.33249 26.31449 ----------------+---------------------------------------------------------------- rho_12 | -.9999999 2.89e-06 -1 1 --------------------------------------------------------------------------------- . ivregress 2sls PGM sex age educ Household_size work agri_laborforce log_agrifield log_income (per=s > uppol subfun training substarec Log_gmcost Log_distance Farming_experience sex age educ Household_s > ize work agri_laborforce log_agrifield log_income), robust Instrumental variables (2SLS) regression Number of obs = 336 Wald chi2(9) = 215.61 Prob > chi2 = 0.0000 R-squared = 0.2934 Root MSE = .40941 --------------------------------------------------------------------------------- | Robust PGM | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- per | -.3006113 .3729177 -0.81 0.420 -1.031517 .430294 sex | .0131189 .0478138 0.27 0.784 -.0805944 .1068322 age | -.004128 .0022089 -1.87 0.062 -.0084575 .0002014 educ | -.0132484 .0455463 -0.29 0.771 -.1025176 .0760207 Household_size | -.0040057 .0075408 -0.53 0.595 -.0187855 .010774 work | .1493238 .1707971 0.87 0.382 -.1854323 .4840799 agri_laborforce | .0724525 .026324 2.75 0.006 .0208583 .1240466 log_agrifield | .252722 .0391368 6.46 0.000 .1760154 .3294287 log_income | -.1515533 .0281346 -5.39 0.000 -.2066961 -.0964104 _cons | .5174392 .177623 2.91 0.004 .1693046 .8655738 --------------------------------------------------------------------------------- Instrumented: per Instruments: sex age educ Household_size work agri_laborforce log_agrifield log_income suppol subfun training substarec Log_gmcost Log_distance Farming_experience . estat endogenous Tests of endogeneity Ho: variables are exogenous Robust score chi2(1) = .577826 (p = 0.4472) Robust regression F(1,325) = .533861 (p = 0.4655) . estat firststage First-stage regression summary statistics -------------------------------------------------------------------------- | Adjusted Partial Robust Variable | R-sq. R-sq. R-sq. F(7,320) Prob > F -------------+------------------------------------------------------------ per | 0.2206 0.1840 0.0663 3.09395 0.0036 -------------------------------------------------------------------------- . estat overid Test of overidentifying restrictions: Score chi2(6) = 142.022 (p = 0.0000) . ivregress gmm PGM sex age educ Household_size work agri_laborforce log_agrifield log_income (per=su > ppol subfun training substarec Log_gmcost Log_distance Farming_experience sex age educ Household_si > ze work agri_laborforce log_agrifield log_income), robust Instrumental variables (GMM) regression Number of obs = 336 Wald chi2(9) = 407.49 Prob > chi2 = 0.0000 R-squared = 0.0117 GMM weight matrix: Robust Root MSE = .48419 --------------------------------------------------------------------------------- | Robust PGM | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- per | -.8885762 .4371479 -2.03 0.042 -1.74537 -.031782 sex | .007425 .0556691 0.13 0.894 -.1016844 .1165343 age | -.005652 .0026984 -2.09 0.036 -.0109408 -.0003632 educ | .0121974 .0576106 0.21 0.832 -.1007172 .125112 Household_size | .0023269 .0082693 0.28 0.778 -.0138806 .0185344 work | .3069179 .2203144 1.39 0.164 -.1248904 .7387262 agri_laborforce | .1088148 .0322992 3.37 0.001 .0455095 .1721201 log_agrifield | .395875 .0488979 8.10 0.000 .3000369 .4917132 log_income | -.2045809 .0310325 -6.59 0.000 -.2654034 -.1437583 _cons | .4593834 .2180448 2.11 0.035 .0320234 .8867434 --------------------------------------------------------------------------------- Instrumented: per Instruments: sex age educ Household_size work agri_laborforce log_agrifield log_income suppol subfun training substarec Log_gmcost Log_distance Farming_experience . estat endogenous Test of endogeneity (orthogonality conditions) Ho: variables are exogenous GMM C statistic chi2(1) = 1.91429 (p = 0.1665) . estat firststage First-stage regression summary statistics -------------------------------------------------------------------------- | Adjusted Partial Robust Variable | R-sq. R-sq. R-sq. F(7,320) Prob > F -------------+------------------------------------------------------------ per | 0.2206 0.1840 0.0663 3.09395 0.0036 -------------------------------------------------------------------------- . estat overid Test of overidentifying restriction: Hansen's J chi2(6) = 142.022 (p = 0.0000) . cmp PGM sex age educ Household_size work agri_laborforce log_agrifield log_income (per=suppol subfu > n substarec sex age educ Household_size work agri_laborforce log_agrifield log_income), robust option indicators() required invalid syntax r(198); . ivregress 2sls PGM sex age educ Household_size work agri_laborforce log_agrifield log_income (WTA=s > uppol subfun substarec sex age educ Household_size work agri_laborforce log_agrifield log_income), > robust Instrumental variables (2SLS) regression Number of obs = 336 Wald chi2(9) = 30.82 Prob > chi2 = 0.0003 R-squared = . Root MSE = 1.083 --------------------------------------------------------------------------------- | Robust PGM | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- per | 3.426142 2.044385 1.68 0.094 -.5807797 7.433063 sex | .0769105 .1310652 0.59 0.557 -.1799726 .3337937 age | -.0065149 .0077197 -0.84 0.399 -.0216452 .0086154 educ | -.2561034 .1825819 -1.40 0.161 -.6139572 .1017505 Household_size | .0103424 .0175411 0.59 0.555 -.0240375 .0447223 work | -.929019 .7584054 -1.22 0.221 -2.415466 .5574282 agri_laborforce | -.1055424 .1149593 -0.92 0.359 -.3308586 .1197738 log_agrifield | .0812741 .1359918 0.60 0.550 -.185265 .3478131 log_income | -.1767416 .0785401 -2.25 0.024 -.3306774 -.0228058 _cons | .9623253 .6316896 1.52 0.128 -.2757636 2.200414 --------------------------------------------------------------------------------- Instrumented: per Instruments: sex age educ Household_size work agri_laborforce log_agrifield log_income suppol subfun substarec . estat endogenous Tests of endogeneity Ho: variables are exogenous Robust score chi2(1) = 21.8118 (p = 0.0000) Robust regression F(1,325) = 40.5941 (p = 0.0000) . estat firststage First-stage regression summary statistics -------------------------------------------------------------------------- | Adjusted Partial Robust Variable | R-sq. R-sq. R-sq. F(3,324) Prob > F -------------+------------------------------------------------------------ per | 0.1772 0.1493 0.0144 1.16491 0.3232 -------------------------------------------------------------------------- . estat overid Test of overidentifying restrictions: Score chi2(2) = 25.0673 (p = 0.0000) . ivregress gmm PGM sex age educ Household_size work agri_laborforce log_agrifield log_income (per=su > ppol subfun substarec sex age educ Household_size work agri_laborforce log_agrifield log_income), r > obust Instrumental variables (GMM) regression Number of obs = 336 Wald chi2(9) = 199.59 Prob > chi2 = 0.0000 R-squared = . GMM weight matrix: Robust Root MSE = .5397 --------------------------------------------------------------------------------- | Robust PGM | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- per | 1.142869 .915765 1.25 0.212 -.6519975 2.937735 sex | -.0643407 .0659536 -0.98 0.329 -.1936073 .064926 age | -.0091299 .0036999 -2.47 0.014 -.0163816 -.0018782 educ | -.1003574 .0813416 -1.23 0.217 -.2597841 .0590692 Household_size | .0126696 .0090883 1.39 0.163 -.005143 .0304823 work | -.3536951 .3205711 -1.10 0.270 -.982003 .2746128 agri_laborforce | .0315056 .051486 0.61 0.541 -.0694052 .1324163 log_agrifield | .2206937 .0692698 3.19 0.001 .0849274 .35646 log_income | -.2462427 .0399601 -6.16 0.000 -.324563 -.1679224 _cons | .9161424 .2966071 3.09 0.002 .3348031 1.497482 --------------------------------------------------------------------------------- Instrumented: per Instruments: sex age educ Household_size work agri_laborforce log_agrifield log_income suppol subfun substarec . estat endogenous Test of endogeneity (orthogonality conditions) Ho: variables are exogenous GMM C statistic chi2(1) = 7.84354 (p = 0.0051) . estat firststage First-stage regression summary statistics -------------------------------------------------------------------------- | Adjusted Partial Robust Variable | R-sq. R-sq. R-sq. F(3,324) Prob > F -------------+------------------------------------------------------------ per | 0.1772 0.1493 0.0144 1.16491 0.3232 -------------------------------------------------------------------------- . estat overid Test of overidentifying restriction: Hansen's J chi2(2) = 25.0673 (p = 0.0000) .