-------------------------------------------------------------------------------------------------------------------------------------------- name: log: G:\Quien Importa - undocCITIZ.log log type: text opened on: 23 Dec 2022, 23:50:49 . do "C:\Users\ljzig\AppData\Local\Temp\STD1b88_000000.tmp" . import excel "G:\sj-xls-3-prq-10.1177_10659129221137825.xls", sheet("Sheet1") firstrow . end of do-file . do "C:\Users\ljzig\AppData\Local\Temp\STD1b88_000000.tmp" . * Run the commands from the ¿Quien Importa? do file for the "red" predictor . end of do-file . do "C:\Users\ljzig\AppData\Local\Temp\STD1b88_000000.tmp" . *States that voted for Romney in 2012 electoral college . gen red = 0 . replace red = 1 if State == "AZ" (90 real changes made) . replace red = 1 if State == "UT" (104 real changes made) . replace red = 1 if State == "Montana" (68 real changes made) . replace red = 1 if State == "Wyoming" (90 real changes made) . replace red = 1 if State == "North Dakota" (140 real changes made) . replace red = 1 if State == "South Dakota" (0 real changes made) . replace red = 1 if State == "Nebraska" (48 real changes made) . replace red = 1 if State == "Kansas" (165 real changes made) . replace red = 1 if State == "Oklahoma" (146 real changes made) . replace red = 1 if State == "Missouri" (167 real changes made) . replace red = 1 if State == "Arkansas" (135 real changes made) . replace red = 1 if State == "Indiana" (149 real changes made) . replace red = 1 if State == "West Virginia" (134 real changes made) . replace red = 1 if State == "TN" (131 real changes made) . replace red = 1 if State == "GA" (233 real changes made) . replace red = 1 if State == "FL" (160 real changes made) . replace red = 1 if State == "Louisiana" (143 real changes made) . replace red = 1 if State == "Mississippi" (164 real changes made) . replace red = 1 if State == "North Carolina" (172 real changes made) . replace red = 1 if State == "Alaska" (0 real changes made) . end of do-file . do "C:\Users\ljzig\AppData\Local\Temp\STD1b88_000000.tmp" . . * Back from the ¿Quien Importa? do file . . tab TreatmentMod TreatmentMod | Freq. Percent Cum. ----------------------+----------------------------------- Citizen East European | 1,018 16.78 16.78 Citizen Latina | 1,035 17.06 33.84 Control East Europe | 991 16.34 50.18 Control Latina | 991 16.34 66.52 Undoc East European | 1,021 16.83 83.35 Undoc Latina | 1,010 16.65 100.00 ----------------------+----------------------------------- Total | 6,066 100.00 . tab TreatmentMod, gen(TR) TreatmentMod | Freq. Percent Cum. ----------------------+----------------------------------- Citizen East European | 1,018 16.78 16.78 Citizen Latina | 1,035 17.06 33.84 Control East Europe | 991 16.34 50.18 Control Latina | 991 16.34 66.52 Undoc East European | 1,021 16.83 83.35 Undoc Latina | 1,010 16.65 100.00 ----------------------+----------------------------------- Total | 6,066 100.00 . tab Chamber Chamber | Freq. Percent Cum. ----------------+----------------------------------- Assembly Member | 257 4.24 4.24 House | 4,129 68.07 72.30 House | 31 0.51 72.82 Representative | 68 1.12 73.94 SEnator | 2 0.03 73.97 Senate | 1,421 23.43 97.40 Senator | 158 2.60 100.00 ----------------+----------------------------------- Total | 6,066 100.00 . gen senator = 0 . replace senator = 1 if Chamber=="SEnator" | Chamber=="Senate" | Chamber=="Senator" (1,581 real changes made) . tab Chamber senator | senator Chamber | 0 1 | Total ----------------+----------------------+---------- Assembly Member | 257 0 | 257 House | 4,129 0 | 4,129 House | 31 0 | 31 Representative | 68 0 | 68 SEnator | 0 2 | 2 Senate | 0 1,421 | 1,421 Senator | 0 158 | 158 ----------------+----------------------+---------- Total | 4,485 1,581 | 6,066 . tab State State | Freq. Percent Cum. ---------------+----------------------------------- AK | 60 0.99 0.99 AZ | 90 1.48 2.47 Alabama | 99 1.63 4.10 Arkansas | 135 2.23 6.33 CA | 115 1.90 8.23 CT | 176 2.90 11.13 Colorado | 99 1.63 12.76 Delaware | 62 1.02 13.78 FL | 160 2.64 16.42 GA | 233 3.84 20.26 Georgia | 1 0.02 20.28 Georgia | 1 0.02 20.29 Hawaii | 77 1.27 21.56 IA | 150 2.47 24.04 IL | 177 2.92 26.95 Indiana | 149 2.46 29.41 Kansas | 165 2.72 32.13 Louisiana | 143 2.36 34.49 MIchigan | 108 1.78 36.27 MO | 1 0.02 36.28 Maine | 179 2.95 39.24 Maryland | 173 2.85 42.09 Massachusetts | 194 3.20 45.29 Mew Mexico | 1 0.02 45.30 Michigan | 2 0.03 45.33 Minnesota | 176 2.90 48.24 Mississippi | 164 2.70 50.94 Missouri | 167 2.75 53.69 Montana | 68 1.12 54.81 NY | 198 3.26 58.08 Nebraska | 48 0.79 58.87 Nevada | 61 1.01 59.87 New Hampshire | 377 6.21 66.09 New Jersey | 117 1.93 68.02 New Mexico | 108 1.78 69.80 North Carolina | 172 2.84 72.63 North Dakota | 140 2.31 74.94 Oklahoma | 146 2.41 77.35 Pennsylvania | 35 0.58 77.93 RI | 113 1.86 79.79 TN | 131 2.16 81.95 TX | 178 2.93 84.88 UT | 104 1.71 86.60 Vermont | 176 2.90 89.50 Virginia | 135 2.23 91.72 WA | 147 2.42 94.15 West Virginia | 134 2.21 96.36 Wisconsin | 131 2.16 98.52 Wyoming | 90 1.48 100.00 ---------------+----------------------------------- Total | 6,066 100.00 . encode State, generate(STATE) . tab Party Party | Freq. Percent Cum. ------------+----------------------------------- 0 | 3,080 50.77 50.77 1 | 2,916 48.07 98.85 2 | 70 1.15 100.00 ------------+----------------------------------- Total | 6,066 100.00 . gen GOP = Party . recode GOP (0 2=0) (GOP: 70 changes made) . . * Close to Table 1 Model 1 . logit Response TR5 TR4 TR1 TR2 TR3 Iteration 0: log likelihood = -3152.7727 Iteration 1: log likelihood = -3103.8565 Iteration 2: log likelihood = -3103.298 Iteration 3: log likelihood = -3103.2979 Logistic regression Number of obs = 6,064 LR chi2(5) = 98.95 Prob > chi2 = 0.0000 Log likelihood = -3103.2979 Pseudo R2 = 0.0157 ------------------------------------------------------------------------------ Response | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- TR5 | -.0801356 .1223214 -0.66 0.512 -.3198811 .1596098 TR4 | .2038365 .1177075 1.73 0.083 -.0268659 .4345389 TR1 | .393924 .1140307 3.45 0.001 .1704279 .6174202 TR2 | .6657923 .1104071 6.03 0.000 .4493984 .8821862 TR3 | .7520758 .110555 6.80 0.000 .535392 .9687596 _cons | -1.64795 .0855313 -19.27 0.000 -1.815589 -1.480312 ------------------------------------------------------------------------------ . . * Results close to Table 1 Model 2 . codebook STATE -------------------------------------------------------------------------------------------------------------------------------------------- STATE State -------------------------------------------------------------------------------------------------------------------------------------------- type: numeric (long) label: STATE range: [1,49] units: 1 unique values: 49 missing .: 0/6,066 examples: 10 GA 22 Maryland 33 New Hampshire 41 TN . logit Response TR5 TR4 TR1 TR2 TR3 Latino percent_latino GOP red Professionalism senator STATE Iteration 0: log likelihood = -3152.2896 Iteration 1: log likelihood = -3077.7352 Iteration 2: log likelihood = -3076.6605 Iteration 3: log likelihood = -3076.6602 Logistic regression Number of obs = 6,062 LR chi2(12) = 151.26 Prob > chi2 = 0.0000 Log likelihood = -3076.6602 Pseudo R2 = 0.0240 --------------------------------------------------------------------------------- Response | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- TR5 | -.0793846 .1228241 -0.65 0.518 -.3201154 .1613462 TR4 | .1905768 .1183024 1.61 0.107 -.0412917 .4224452 TR1 | .3993972 .1145804 3.49 0.000 .1748236 .6239707 TR2 | .6741898 .1109713 6.08 0.000 .45669 .8916896 TR3 | .7471075 .1111388 6.72 0.000 .5292794 .9649355 Latino | -.1156706 .193063 -0.60 0.549 -.494067 .2627258 percent_latino | -.0014899 .0027547 -0.54 0.589 -.0068889 .0039092 GOP | -.1259998 .066661 -1.89 0.059 -.2566529 .0046533 red | .0665127 .0717485 0.93 0.354 -.0741117 .2071372 Professionalism | 1.649369 .2774576 5.94 0.000 1.105562 2.193176 senator | .1698638 .0706338 2.40 0.016 .031424 .3083036 STATE | .0071643 .0023206 3.09 0.002 .002616 .0117126 _cons | -2.137793 .1379076 -15.50 0.000 -2.408087 -1.867499 --------------------------------------------------------------------------------- . . * Attempt at Table 1 Model 1 w/ fixed effects . logit Response TR5 TR4 TR1 TR2 TR3 Latino percent_latino GOP red Professionalism senator i.STATE note: 11.STATE != 0 predicts failure perfectly 11.STATE dropped and 1 obs not used note: 12.STATE != 0 predicts failure perfectly 12.STATE dropped and 1 obs not used note: 13.STATE != 0 predicts failure perfectly 13.STATE dropped and 77 obs not used note: 20.STATE != 0 predicts failure perfectly 20.STATE dropped and 1 obs not used note: 24.STATE != 0 predicts failure perfectly 24.STATE dropped and 1 obs not used note: 48.STATE omitted because of collinearity note: 49.STATE omitted because of collinearity Iteration 0: log likelihood = -3132.5721 Iteration 1: log likelihood = -2924.6463 Iteration 2: log likelihood = -2912.7659 Iteration 3: log likelihood = -2912.571 Iteration 4: log likelihood = -2912.5702 Iteration 5: log likelihood = -2912.5702 Logistic regression Number of obs = 5,981 LR chi2(52) = 440.00 Prob > chi2 = 0.0000 Log likelihood = -2912.5702 Pseudo R2 = 0.0702 --------------------------------------------------------------------------------- Response | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------+---------------------------------------------------------------- TR5 | -.0866335 .1255936 -0.69 0.490 -.3327925 .1595255 TR4 | .1756694 .1214366 1.45 0.148 -.062342 .4136808 TR1 | .4460604 .117674 3.79 0.000 .2154237 .6766972 TR2 | .7287197 .114158 6.38 0.000 .5049741 .9524654 TR3 | .780306 .1145834 6.81 0.000 .5557266 1.004885 Latino | -.1047428 .1966987 -0.53 0.594 -.4902652 .2807796 percent_latino | -.0032519 .003559 -0.91 0.361 -.0102273 .0037235 GOP | .0006536 .0714652 0.01 0.993 -.1394157 .1407229 red | -1.440479 .5713028 -2.52 0.012 -2.560212 -.3207461 Professionalism | -.3374218 1.501499 -0.22 0.822 -3.280307 2.605463 senator | .1563087 .0759257 2.06 0.040 .0074971 .3051203 | STATE | AZ | .528748 .4652709 1.14 0.256 -.3831661 1.440662 Alabama | -1.4685 .5457692 -2.69 0.007 -2.538188 -.3988121 Arkansas | -.0591732 .3760699 -0.16 0.875 -.7962567 .6779103 CA | -1.242449 .4923672 -2.52 0.012 -2.207471 -.2774268 CT | -1.610437 .3798259 -4.24 0.000 -2.354882 -.8659917 Colorado | -1.008101 .3854688 -2.62 0.009 -1.763606 -.2525956 Delaware | -.4842734 .4567932 -1.06 0.289 -1.379572 .4110249 FL | 1.018996 .4153676 2.45 0.014 .20489 1.833101 GA | -.0093135 .3438256 -0.03 0.978 -.6831994 .6645723 Georgia | 0 (empty) Georgia | 0 (empty) Hawaii | 0 (empty) IA | -1.559718 .4070965 -3.83 0.000 -2.357612 -.7618232 IL | -.8245247 .2836852 -2.91 0.004 -1.380537 -.268512 Indiana | -.5621165 .3919053 -1.43 0.151 -1.330237 .2060038 Kansas | .0480895 .3624555 0.13 0.894 -.6623102 .7584892 Louisiana | .6914394 .3545319 1.95 0.051 -.0034303 1.386309 MIchigan | -.9425577 .2790127 -3.38 0.001 -1.489412 -.3957028 MO | 0 (empty) Maine | -1.711441 .5000355 -3.42 0.001 -2.691492 -.7313891 Maryland | -.3517349 .3454914 -1.02 0.309 -1.028886 .3254159 Massachusetts | -2.899651 .3928863 -7.38 0.000 -3.669694 -2.129608 Mew Mexico | 0 (empty) Michigan | .6748511 1.424533 0.47 0.636 -2.117182 3.466884 Minnesota | -.6094693 .3766121 -1.62 0.106 -1.347615 .1286768 Mississippi | -.9853852 .4190942 -2.35 0.019 -1.806795 -.1639757 Missouri | .7676945 .3744966 2.05 0.040 .0336945 1.501694 Montana | -.2915103 .4572727 -0.64 0.524 -1.187748 .6047278 NY | -.2910424 .2701689 -1.08 0.281 -.8205637 .2384788 Nebraska | .1287606 .4848604 0.27 0.791 -.8215483 1.079069 Nevada | -1.513424 .529966 -2.86 0.004 -2.552138 -.4747092 New Hampshire | -1.546697 .5577775 -2.77 0.006 -2.639921 -.4534731 New Jersey | -.7649148 .3241277 -2.36 0.018 -1.400193 -.1296362 New Mexico | -1.190753 .503037 -2.37 0.018 -2.176687 -.2048186 North Carolina | 1.077703 .3875757 2.78 0.005 .3180691 1.837338 North Dakota | .0592241 .3552804 0.17 0.868 -.6371127 .755561 Oklahoma | .4103561 .3967406 1.03 0.301 -.3672412 1.187953 Pennsylvania | -.222454 .3867279 -0.58 0.565 -.9804268 .5355187 RI | -1.584102 .4711901 -3.36 0.001 -2.507617 -.6605858 TN | .5915875 .3553306 1.66 0.096 -.1048476 1.288023 TX | -1.156251 .3686819 -3.14 0.002 -1.878854 -.4336479 UT | .446549 .3629556 1.23 0.219 -.264831 1.157929 Vermont | -2.09477 .4535107 -4.62 0.000 -2.983635 -1.205906 Virginia | -.7689577 .4356767 -1.76 0.078 -1.622868 .0849531 WA | -.4736694 .349051 -1.36 0.175 -1.157797 .210458 West Virginia | -.4383805 .403147 -1.09 0.277 -1.228534 .351773 Wisconsin | 0 (omitted) Wyoming | 0 (omitted) | _cons | -.5070308 .5853277 -0.87 0.386 -1.654252 .6401905 --------------------------------------------------------------------------------- . . * Check for Republicans for each treatment . encode TreatmentMod, gen(TM) . gen undocCITIZ = 0 if TreatmentMod=="Citizen Latina" | TreatmentMod=="Citizen East European" (4,013 missing values generated) . replace undocCITIZ=1 if TreatmentMod=="Undoc Latina" | TreatmentMod=="Undoc East European" (2,031 real changes made) . tab TreatmentMod undocCITIZ | undocCITIZ TreatmentMod | 0 1 | Total ----------------------+----------------------+---------- Citizen East European | 1,018 0 | 1,018 Citizen Latina | 1,035 0 | 1,035 Undoc East European | 0 1,021 | 1,021 Undoc Latina | 0 1,010 | 1,010 ----------------------+----------------------+---------- Total | 2,053 2,031 | 4,084 . . reg Response undocCITIZ if GOP==1, level(83.4) Source | SS df MS Number of obs = 1,951 -------------+---------------------------------- F(1, 1949) = 16.21 Model | 2.56891996 1 2.56891996 Prob > F = 0.0001 Residual | 308.870342 1,949 .158476317 R-squared = 0.0082 -------------+---------------------------------- Adj R-squared = 0.0077 Total | 311.439262 1,950 .159712442 Root MSE = .39809 ------------------------------------------------------------------------------ Response | Coef. Std. Err. t P>|t| [83.4% Conf. Interval] -------------+---------------------------------------------------------------- undocCITIZ | -.072574 .0180255 -4.03 0.000 -.0975518 -.0475962 _cons | .2358393 .0127753 18.46 0.000 .2181367 .253542 ------------------------------------------------------------------------------ . reg Response undocCITIZ if GOP==0, level(83.4) Source | SS df MS Number of obs = 2,133 -------------+---------------------------------- F(1, 2131) = 39.25 Model | 6.27325127 1 6.27325127 Prob > F = 0.0000 Residual | 340.605324 2,131 .159833563 R-squared = 0.0181 -------------+---------------------------------- Adj R-squared = 0.0176 Total | 346.878575 2,132 .16270102 Root MSE = .39979 ------------------------------------------------------------------------------ Response | Coef. Std. Err. t P>|t| [83.4% Conf. Interval] -------------+---------------------------------------------------------------- undocCITIZ | -.1084743 .0173147 -6.26 0.000 -.1324663 -.0844823 _cons | .2578558 .012154 21.22 0.000 .2410146 .274697 ------------------------------------------------------------------------------ . . prop Response if GOP==1, over(TM) Proportion estimation Number of obs = 2,915 _prop_1: Response = 0 _prop_2: Response = 1 _subpop_1: TM = Citizen East European _subpop_2: TM = Citizen Latina _subpop_3: TM = Control East Europe _subpop_4: TM = Control Latina _subpop_5: TM = Undoc East European _subpop_6: TM = Undoc Latina -------------------------------------------------------------- | Logit Over | Proportion Std. Err. [95% Conf. Interval] -------------+------------------------------------------------ _prop_1 | _subpop_1 | .7845528 .0185353 .7459989 .8186772 _subpop_2 | .743215 .0199606 .7021733 .7803701 _subpop_3 | .7479508 .0196548 .7075026 .7845093 _subpop_4 | .8214286 .0175545 .7843839 .853299 _subpop_5 | .8224852 .0169698 .7867386 .8533569 _subpop_6 | .8520085 .0163271 .8170585 .8812518 -------------+------------------------------------------------ _prop_2 | _subpop_1 | .2154472 .0185353 .1813228 .2540011 _subpop_2 | .256785 .0199606 .2196299 .2978267 _subpop_3 | .2520492 .0196548 .2154907 .2924974 _subpop_4 | .1785714 .0175545 .146701 .2156161 _subpop_5 | .1775148 .0169698 .1466431 .2132614 _subpop_6 | .1479915 .0163271 .1187482 .1829415 -------------------------------------------------------------- . prop Response if GOP==0, over(TM) Proportion estimation Number of obs = 3,149 _prop_1: Response = 0 _prop_2: Response = 1 _subpop_1: TM = Citizen East European _subpop_2: TM = Citizen Latina _subpop_3: TM = Control East Europe _subpop_4: TM = Control Latina _subpop_5: TM = Undoc East European _subpop_6: TM = Undoc Latina -------------------------------------------------------------- | Logit Over | Proportion Std. Err. [95% Conf. Interval] -------------+------------------------------------------------ _prop_1 | _subpop_1 | .7718631 .0182968 .7340232 .8057443 _subpop_2 | .7140288 .0191638 .6750279 .7500819 _subpop_3 | .6733068 .0209327 .6310189 .7129528 _subpop_4 | .7976654 .01772 .7606951 .830199 _subpop_5 | .8754864 .014563 .844017 .901349 _subpop_6 | .8268156 .0163294 .7924285 .8565374 -------------+------------------------------------------------ _prop_2 | _subpop_1 | .2281369 .0182968 .1942557 .2659768 _subpop_2 | .2859712 .0191638 .2499181 .3249721 _subpop_3 | .3266932 .0209327 .2870472 .3689811 _subpop_4 | .2023346 .01772 .169801 .2393049 _subpop_5 | .1245136 .014563 .098651 .155983 _subpop_6 | .1731844 .0163294 .1434626 .2075715 -------------------------------------------------------------- . prop Response if GOP==1 Proportion estimation Number of obs = 2,915 -------------------------------------------------------------- | Logit | Proportion Std. Err. [95% Conf. Interval] -------------+------------------------------------------------ Response | 0 | .7951973 .0074746 .7801517 .8094646 1 | .2048027 .0074746 .1905354 .2198483 -------------------------------------------------------------- . prop Response if GOP==0 Proportion estimation Number of obs = 3,149 -------------------------------------------------------------- | Logit | Proportion Std. Err. [95% Conf. Interval] -------------+------------------------------------------------ Response | 0 | .776437 .0074245 .7615431 .7906563 1 | .223563 .0074245 .2093437 .2384569 -------------------------------------------------------------- . end of do-file . log close name: log: G:\Quien Importa - undocCITIZ.log log type: text closed on: 23 Dec 2022, 23:51:20 --------------------------------------------------------------------------------------------------------------------------------------------