------------------------------------------------------------------------------------------------------------------------------ name: log: /accounts/fac/card/gradlab/250a/ps3/mroz2.log log type: text opened on: 25 Sep 2013, 22:33:08 . use mroz; . summ; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- state | 4066 52.93778 26.29072 11 95 hhnum | 4066 46720.86 27864.72 5 95984 cbsa_size | 4066 3.575996 2.540933 0 7 famnum | 4066 1 0 1 1 himm | 4066 .1633055 .3696896 0 1 -------------+-------------------------------------------------------- hgen2 | 4066 .0536153 .2252848 0 1 heduc | 4066 14.02779 2.865233 0 20 htwage | 3789 29.49427 29.48436 4 400 hannhrs | 4066 2023.881 779.647 0 5148 hfamearn | 4066 94954.48 84785.71 0 1379999 -------------+-------------------------------------------------------- h_age | 4066 46.05411 10.33781 24 64 hrace | 4066 1.339154 1.068768 1 18 hwagesal | 4066 60047.99 71998.9 0 1099999 hwage_ogr | 3281 27.31807 25.59534 .02 1154 hselfinc | 4066 2213.234 20961.01 -9999 1000000 -------------+-------------------------------------------------------- hfarminc | 4066 431.3874 7155.457 -9999 300000 hclassly | 4066 1.646335 1.492534 0 6 hhealth | 4066 2.107723 .9515725 1 5 hweeksly | 4066 46.36645 14.47371 0 52 hhrswkly | 4066 40.46335 14.24178 0 99 -------------+-------------------------------------------------------- hogrflag | 4066 .8285785 .3769233 0 1 hrgroup | 4066 1.52607 1.025353 1 5 ownkidsu6 | 4066 .2909493 .6152644 0 5 ownkidsu18 | 4066 .9584358 1.160012 0 9 wimm | 4066 .1650271 .3712506 0 1 -------------+-------------------------------------------------------- wgen2 | 4066 .0577964 .2333867 0 1 weduc | 4066 14.17609 2.701005 0 20 wtwage | 3265 21.70395 21.57611 4 400 wannhrs | 4066 1464.556 926.4915 0 4653 wfamearn | 4066 94954.48 84785.71 0 1379999 -------------+-------------------------------------------------------- w_age | 4066 44.24127 10.34809 24 64 wrace | 4066 1.361535 1.10912 1 18 wwagesal | 4066 31840.38 41224.53 0 1099999 wwage_ogr | 2906 21.29521 14.07471 .04 260 wselfinc | 4066 1090.773 11644.49 -9999 450000 -------------+-------------------------------------------------------- wfarminc | 4066 28.13822 1368.477 -4000 84400 wclassly | 4066 1.453517 1.480311 0 7 wweeksly | 4066 38.71864 21.09423 0 52 whrswkly | 4066 29.90113 17.61405 0 99 whealth | 4066 2.107723 .9487245 1 5 -------------+-------------------------------------------------------- wogrflag | 4066 .7316773 .443141 0 1 wrgroup | 4066 1.549434 1.051276 1 5 mergestat | 0 wifework | 4066 .8030005 .3977809 0 1 husbandwork | 4066 .9318741 .2519929 0 1 -------------+-------------------------------------------------------- age_gap | 4066 1.812838 4.754866 -31 27 wagesalgap | 4066 28207.61 81644.56 -911488 1099999 educgap | 4066 -.148303 2.435064 -16 12 hlogwage | 3789 3.118612 .7264443 1.386294 5.991465 wlogwage | 3265 2.833157 .6825152 1.386294 5.991465 -------------+-------------------------------------------------------- hexp | 4066 26.02632 10.73865 0 55 hexp2 | 4066 7.926594 5.549561 0 30.25 hexp3 | 4066 26.44724 24.85961 0 166.375 hblack | 4066 .0568126 .2315126 0 1 wblack | 4066 .0518938 .2218398 0 1 -------------+-------------------------------------------------------- hhispanic | 4066 .110182 .313155 0 1 whispanic | 4066 .1121495 .3155891 0 1 wife_wage_~r | 4066 .7147073 .4516093 0 1 husband_wa~r | 4066 .8069356 .3947517 0 1 missing_ww~r | 4066 .0969011 .2958595 0 1 -------------+-------------------------------------------------------- wlogwage_ogr | 2906 2.896271 .5723385 -3.218876 5.560682 any_under6 | 4066 .2166749 .4120299 0 1 . tab state; state | Freq. Percent Cum. ------------+----------------------------------- 11 | 89 2.19 2.19 12 | 87 2.14 4.33 13 | 59 1.45 5.78 14 | 58 1.43 7.21 15 | 69 1.70 8.90 16 | 101 2.48 11.39 21 | 155 3.81 15.20 22 | 95 2.34 17.54 23 | 126 3.10 20.63 31 | 121 2.98 23.61 32 | 78 1.92 25.53 33 | 125 3.07 28.60 34 | 99 2.43 31.04 35 | 98 2.41 33.45 41 | 124 3.05 36.50 42 | 84 2.07 38.56 43 | 69 1.70 40.26 44 | 61 1.50 41.76 45 | 67 1.65 43.41 46 | 72 1.77 45.18 47 | 59 1.45 46.63 51 | 67 1.65 48.28 52 | 99 2.43 50.71 53 | 34 0.84 51.55 54 | 93 2.29 53.84 55 | 46 1.13 54.97 56 | 68 1.67 56.64 57 | 60 1.48 58.12 58 | 79 1.94 60.06 59 | 141 3.47 63.53 61 | 75 1.84 65.37 62 | 56 1.38 66.75 63 | 37 0.91 67.66 64 | 34 0.84 68.49 71 | 30 0.74 69.23 72 | 23 0.57 69.80 73 | 35 0.86 70.66 74 | 209 5.14 75.80 81 | 32 0.79 76.59 82 | 61 1.50 78.09 83 | 51 1.25 79.34 84 | 103 2.53 81.87 85 | 30 0.74 82.61 86 | 48 1.18 83.79 87 | 51 1.25 85.05 88 | 54 1.33 86.37 91 | 80 1.97 88.34 92 | 59 1.45 89.79 93 | 314 7.72 97.52 94 | 42 1.03 98.55 95 | 59 1.45 100.00 ------------+----------------------------------- Total | 4,066 100.00 . tab cbsa_size; cbsa_size | Freq. Percent Cum. ------------+----------------------------------- 0 | 1,070 26.32 26.32 2 | 349 8.58 34.90 3 | 343 8.44 43.33 4 | 432 10.62 53.96 5 | 682 16.77 70.73 6 | 655 16.11 86.84 7 | 535 13.16 100.00 ------------+----------------------------------- Total | 4,066 100.00 . corr weduc heduc w_age h_age wtwage htwage; (obs=2988) | weduc heduc w_age h_age wtwage htwage -------------+------------------------------------------------------ weduc | 1.0000 heduc | 0.6139 1.0000 w_age | -0.0569 0.0126 1.0000 h_age | -0.0825 -0.0035 0.8925 1.0000 wtwage | 0.3360 0.2231 0.0441 0.0317 1.0000 htwage | 0.1742 0.2977 0.0829 0.0657 0.1510 1.0000 . *from now on drop if wife is under 25 or over 55; . drop if w_age<25; (47 observations deleted) . drop if w_age>55; (679 observations deleted) . table w_age , c (n weduc mean h_age mean weduc ); ------------------------------------------------- w_age | N(weduc) mean(h_age) mean(weduc) ----------+-------------------------------------- 25 | 42 28.381 13.3333 26 | 55 29.3455 14.0727 27 | 66 28.7576 15 28 | 79 30.6456 14.3038 29 | 79 32.5823 14.5063 30 | 91 33.2198 14.1538 31 | 106 34.2547 14.7264 32 | 107 34.514 14.3271 33 | 106 35.8208 14.7358 34 | 117 36.3504 14.3761 35 | 95 38.2 14.2105 36 | 111 38.3964 14.3874 37 | 108 39.5 14.1111 38 | 127 40.8898 14.4488 39 | 98 42.0204 14.4388 40 | 122 42.4426 14.2705 41 | 111 42.9189 14.5856 42 | 118 44.2627 14.3983 43 | 116 44.569 13.9828 44 | 110 45.9636 14.3727 45 | 119 46.9496 14.0084 46 | 120 48.6083 13.3167 47 | 112 50.0982 14.6339 48 | 123 50.3333 14.1301 49 | 123 50.5935 13.8862 50 | 161 51.8137 13.882 51 | 148 52.2162 13.473 52 | 110 53.8364 14.2545 53 | 137 54.146 14.2774 54 | 107 55.0467 13.8879 55 | 116 55.9828 14.1034 ------------------------------------------------- . *some H-W diffs; . tab wifework husbandwork, row col; +-------------------+ | Key | |-------------------| | frequency | | row percentage | | column percentage | +-------------------+ | husbandwork wifework | 0 1 | Total -----------+----------------------+---------- 0 | 0 646 | 646 | 0.00 100.00 | 100.00 | 0.00 20.48 | 19.34 -----------+----------------------+---------- 1 | 185 2,509 | 2,694 | 6.87 93.13 | 100.00 | 100.00 79.52 | 80.66 -----------+----------------------+---------- Total | 185 3,155 | 3,340 | 5.54 94.46 | 100.00 | 100.00 100.00 | 100.00 . gen agegap=h_age-w_age; . gen edgap=heduc-weduc; . gen paygap=hwagesal-wwagesal; . gen wagegap=htwage-wtwage; (831 missing values generated) . gen hrsgap=hannhrs-wannhrs; . sum agegap edgap paygap hrsgap wagegap; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- agegap | 3340 2.253293 4.658628 -21 27 edgap | 3340 -.2083832 2.421141 -16 12 paygap | 3340 28914.39 81394.45 -911488 1099999 hrsgap | 3340 594.479 1247.845 -3900 5148 wagegap | 2509 6.471194 31.28789 -391.1 389.4231 . corr agegap edgap paygap hrsgap wagegap; (obs=2509) | agegap edgap paygap hrsgap wagegap -------------+--------------------------------------------- agegap | 1.0000 edgap | 0.0429 1.0000 paygap | 0.0071 0.2247 1.0000 hrsgap | 0.0005 0.0986 0.3489 1.0000 wagegap | 0.0022 0.2035 0.8091 0.0321 1.0000 . *age profiles; . table w_age, c( n wifework mean wifework mean wannhrs mean ownkidsu6 > mean ownkidsu18); -------------------------------------------------------------------------------- w_age | N(wifework) mean(wife~k) mean(wann~s) mean(ownk~6) mean(own~18) ----------+--------------------------------------------------------------------- 25 | 42 .690476 1149.36 .785714 .857143 26 | 55 .818182 1402.55 .709091 1.07273 27 | 66 .80303 1490.55 .787879 1.16667 28 | 79 .810127 1352.72 .924051 1.27848 29 | 79 .734177 1381.87 .746835 1.26582 30 | 91 .802198 1362.89 1.02198 1.64835 31 | 106 .830189 1521.45 .858491 1.43396 32 | 107 .82243 1456.17 .897196 1.73832 33 | 106 .764151 1309.57 .650943 1.5566 34 | 117 .786325 1533.15 .726496 1.63248 35 | 95 .8 1293.28 .705263 1.66316 36 | 111 .756757 1330.41 .63964 1.82883 37 | 108 .740741 1236.43 .416667 1.85185 38 | 127 .732283 1236.92 .456693 1.64567 39 | 98 .795918 1377.79 .387755 1.56122 40 | 122 .860656 1587.26 .385246 1.68852 41 | 111 .810811 1480.41 .369369 1.64865 42 | 118 .872881 1685.39 .177966 1.42373 43 | 116 .827586 1637.72 .155172 1.31897 44 | 110 .781818 1372.89 .145455 1.42727 45 | 119 .815126 1418.13 .109244 1.21008 46 | 120 .841667 1523.03 .066667 .983333 47 | 112 .883929 1695.35 .008929 .857143 48 | 123 .796748 1454.67 .02439 .699187 49 | 123 .845528 1585.28 .03252 .715447 50 | 161 .813665 1538.07 .006211 .583851 51 | 148 .810811 1512.76 .006757 .405405 52 | 110 .818182 1493.11 0 .281818 53 | 137 .810219 1446.75 .021898 .357664 54 | 107 .785047 1551.61 .018692 .17757 55 | 116 .836207 1656.62 0 .12931 -------------------------------------------------------------------------------- . table w_age if wifework==1, c( n wifework mean wannhrs mean wtwage mean wlogwage); -------------------------------------------------------------------------- w_age | N(wifework) mean(wannhrs) mean(wtwage) mean(wlogwage) ----------+--------------------------------------------------------------- 25 | 29 1664.59 14.5282 2.580028 26 | 45 1714.22 18.52726 2.744507 27 | 53 1856.15 18.15164 2.779815 28 | 64 1669.77 15.96412 2.622462 29 | 58 1882.21 20.33297 2.799663 30 | 73 1698.95 21.82377 2.836552 31 | 88 1832.66 22.26627 2.935779 32 | 88 1770.57 20.48781 2.794204 33 | 81 1713.75 20.83592 2.878471 34 | 92 1949.76 23.93525 2.854227 35 | 76 1616.61 19.89842 2.738653 36 | 84 1758.05 24.65296 2.95121 37 | 80 1669.18 27.07425 3.012369 38 | 93 1689.13 21.15484 2.787447 39 | 78 1731.06 23.57314 2.918575 40 | 105 1844.25 19.88931 2.796478 41 | 90 1825.84 21.48627 2.8329 42 | 103 1930.83 21.9728 2.913223 43 | 96 1978.91 23.29489 2.77265 44 | 86 1756.02 20.09465 2.853459 45 | 97 1739.77 22.26389 2.811879 46 | 101 1809.53 19.82169 2.803668 47 | 99 1917.97 20.89202 2.823513 48 | 98 1825.76 20.21237 2.810964 49 | 104 1874.9 20.81946 2.771729 50 | 131 1890.3 20.2019 2.790731 51 | 120 1865.73 23.4013 2.909495 52 | 90 1824.91 21.04315 2.791311 53 | 111 1785.63 24.3777 2.897235 54 | 84 1976.45 27.19242 2.985523 55 | 97 1981.11 27.33866 2.945165 -------------------------------------------------------------------------- . *some new vars; . gen wcollege=(weduc>=16); . gen hcollege=(heduc>=16); . tab wrgroup hrgroup, row col; +-------------------+ | Key | |-------------------| | frequency | | row percentage | | column percentage | +-------------------+ | hrgroup wrgroup | 1 2 3 4 5 | Total -----------+-------------------------------------------------------+---------- 1 | 2,352 17 53 16 30 | 2,468 | 95.30 0.69 2.15 0.65 1.22 | 100.00 | 94.57 9.39 13.15 8.25 40.00 | 73.89 -----------+-------------------------------------------------------+---------- 2 | 8 155 2 0 1 | 166 | 4.82 93.37 1.20 0.00 0.60 | 100.00 | 0.32 85.64 0.50 0.00 1.33 | 4.97 -----------+-------------------------------------------------------+---------- 3 | 61 6 339 2 4 | 412 | 14.81 1.46 82.28 0.49 0.97 | 100.00 | 2.45 3.31 84.12 1.03 5.33 | 12.34 -----------+-------------------------------------------------------+---------- 4 | 38 1 2 171 3 | 215 | 17.67 0.47 0.93 79.53 1.40 | 100.00 | 1.53 0.55 0.50 88.14 4.00 | 6.44 -----------+-------------------------------------------------------+---------- 5 | 28 2 7 5 37 | 79 | 35.44 2.53 8.86 6.33 46.84 | 100.00 | 1.13 1.10 1.74 2.58 49.33 | 2.37 -----------+-------------------------------------------------------+---------- Total | 2,487 181 403 194 75 | 3,340 | 74.46 5.42 12.07 5.81 2.25 | 100.00 | 100.00 100.00 100.00 100.00 100.00 | 100.00 . tab wblack hblack , row col; +-------------------+ | Key | |-------------------| | frequency | | row percentage | | column percentage | +-------------------+ | hblack wblack | 0 1 | Total -----------+----------------------+---------- 0 | 3,148 26 | 3,174 | 99.18 0.82 | 100.00 | 99.65 14.36 | 95.03 -----------+----------------------+---------- 1 | 11 155 | 166 | 6.63 93.37 | 100.00 | 0.35 85.64 | 4.97 -----------+----------------------+---------- Total | 3,159 181 | 3,340 | 94.58 5.42 | 100.00 | 100.00 100.00 | 100.00 . tab whispanic hhispanic, row col; +-------------------+ | Key | |-------------------| | frequency | | row percentage | | column percentage | +-------------------+ | hhispanic whispanic | 0 1 | Total -----------+----------------------+---------- 0 | 2,864 64 | 2,928 | 97.81 2.19 | 100.00 | 97.51 15.88 | 87.66 -----------+----------------------+---------- 1 | 73 339 | 412 | 17.72 82.28 | 100.00 | 2.49 84.12 | 12.34 -----------+----------------------+---------- Total | 2,937 403 | 3,340 | 87.93 12.07 | 100.00 | 100.00 100.00 | 100.00 . tab wcollege hcollege , row col; +-------------------+ | Key | |-------------------| | frequency | | row percentage | | column percentage | +-------------------+ | hcollege wcollege | 0 1 | Total -----------+----------------------+---------- 0 | 1,620 331 | 1,951 | 83.03 16.97 | 100.00 | 78.07 26.17 | 58.41 -----------+----------------------+---------- 1 | 455 934 | 1,389 | 32.76 67.24 | 100.00 | 21.93 73.83 | 41.59 -----------+----------------------+---------- Total | 2,075 1,265 | 3,340 | 62.13 37.87 | 100.00 | 100.00 100.00 | 100.00 . gen wexp=w_age-weduc-6; . replace wexp=0 if wexp<0; (1 real change made) . gen wexp2=wexp*wexp/100; . gen wexp3=wexp*wexp*wexp/1000; . drop wlogwage_ogr; . replace wwage_ogr=4 if wwage_ogr>0 & wwage_ogr<4; (13 real changes made) . replace wwage_ogr=400 if wwage_ogr>400; (938 real changes made) . gen wlogwage_ogr=log(wwage_ogr); . gen work_and_wage=0; . replace work_and_wage=1 if wifework==1 & wife_wage_ogr==1; (2373 real changes made) . sum wwage_ogr wlogwage_ogr wlogwage wannhrs hwagesal wtwage weduc if wifework==1; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- wwage_ogr | 2694 66.609 123.3931 4 400 wlogwage_ogr | 2694 3.275662 1.125811 1.386294 5.991465 wlogwage | 2694 2.839735 .6805533 1.386294 5.991465 wannhrs | 2694 1819.085 642.3766 1 4653 hwagesal | 2694 57311.69 64385.31 0 1099999 -------------+-------------------------------------------------------- wtwage | 2694 21.83915 22.01362 4 400 weduc | 2694 14.42613 2.638147 0 20 . sum wwage_ogr wlogwage_ogr wlogwage wannhrs hwagesal wtwage weduc if work_and_wage==1; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- wwage_ogr | 2373 21.51059 14.48744 4 260 wlogwage_ogr | 2373 2.908291 .5530135 1.386294 5.560682 wlogwage | 2373 2.904924 .6092024 1.386294 5.991465 wannhrs | 2373 1880.812 585.2939 1 4653 hwagesal | 2373 55808.26 63944.42 0 1099999 -------------+-------------------------------------------------------- wtwage | 2373 22.3412 20.27238 4 400 weduc | 2373 14.48968 2.642483 0 20 . sum wwage_ogr wlogwage_ogr wlogwage wannhrs hwagesal wtwage weduc if wifework==1 & wife_wage_ogr==0; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- wwage_ogr | 321 400 0 400 400 wlogwage_ogr | 321 5.991465 0 5.991465 5.991465 wlogwage | 321 2.35782 .9392848 1.386294 5.991465 wannhrs | 321 1362.76 834.4202 5 3640 hwagesal | 321 68425.9 66611.9 0 600000 -------------+-------------------------------------------------------- wtwage | 321 18.1277 31.87802 4 400 weduc | 321 13.95639 2.561365 3 20 . *probit model of work+validOGR wage; . probit work_and_wage weduc wcollege wexp wexp2 wexp3 wblack whispanic wimm > wgen2 ownkidsu6 any_under6 hwagesal heduc hcollege himm hgen2 h_age; Iteration 0: log likelihood = -2009.7521 Iteration 1: log likelihood = -1877.9991 Iteration 2: log likelihood = -1877.4315 Iteration 3: log likelihood = -1877.4314 Probit regression Number of obs = 3340 LR chi2(17) = 264.64 Prob > chi2 = 0.0000 Log likelihood = -1877.4314 Pseudo R2 = 0.0658 ------------------------------------------------------------------------------- work_and_wage | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- weduc | .0938225 .0195166 4.81 0.000 .0555708 .1320743 wcollege | .1033206 .0929739 1.11 0.266 -.078905 .2855462 wexp | .0022788 .0356355 0.06 0.949 -.0675656 .0721231 wexp2 | -.1408701 .1798662 -0.78 0.434 -.4934014 .2116612 wexp3 | .0313744 .0279593 1.12 0.262 -.0234247 .0861736 wblack | .0655658 .1111192 0.59 0.555 -.1522238 .2833555 whispanic | -.1113965 .0855296 -1.30 0.193 -.2790314 .0562385 wimm | -.2642558 .0989723 -2.67 0.008 -.458238 -.0702736 wgen2 | .0707645 .1082958 0.65 0.513 -.1414914 .2830203 ownkidsu6 | -.1809219 .0790833 -2.29 0.022 -.3359224 -.0259214 any_under6 | -.1394665 .1233409 -1.13 0.258 -.3812102 .1022771 hwagesal | -2.54e-06 3.51e-07 -7.25 0.000 -3.23e-06 -1.86e-06 heduc | -.0155962 .0165285 -0.94 0.345 -.0479915 .016799 hcollege | -.1455138 .0901809 -1.61 0.107 -.322265 .0312374 himm | -.0282757 .1013865 -0.28 0.780 -.2269897 .1704382 hgen2 | .0293868 .1107491 0.27 0.791 -.1876774 .2464509 h_age | .0081855 .0051216 1.60 0.110 -.0018526 .0182236 _cons | -.3201643 .3615624 -0.89 0.376 -1.028814 .3884851 ------------------------------------------------------------------------------- . predict pwork1; (option pr assumed; Pr(work_and_wage)) . gen lambda1 = normalden(invnormal(pwork1))/pwork1; . sum lambda1 if work_and_wage==0; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- lambda1 | 967 .5696497 .2315655 .1492069 2.621254 . sum lambda1 if work_and_wage==1; Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- lambda1 | 2373 .4478074 .1834445 .1115173 2.562097 . corr work_and_wage pwork1 lambda1; (obs=3340) | work_a~e pwork1 lambda1 -------------+--------------------------- work_and_w~e | 1.0000 pwork1 | 0.2855 1.0000 lambda1 | -0.2682 -0.9842 1.0000 . reg wlogwage weduc wcollege wexp wexp2 wexp3 wblack whispanic wimm > ownkidsu6 any_under6 ; Source | SS df MS Number of obs = 2694 -------------+------------------------------ F( 10, 2683) = 69.95 Model | 257.938169 10 25.7938169 Prob > F = 0.0000 Residual | 989.332427 2683 .368741121 R-squared = 0.2068 -------------+------------------------------ Adj R-squared = 0.2038 Total | 1247.2706 2693 .463152839 Root MSE = .60724 ------------------------------------------------------------------------------ wlogwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- weduc | .1151357 .0089395 12.88 0.000 .0976067 .1326647 wcollege | .067602 .043784 1.54 0.123 -.0182519 .1534559 wexp | .0610294 .017046 3.58 0.000 .0276048 .094454 wexp2 | -.3097726 .0887194 -3.49 0.000 -.483738 -.1358071 wexp3 | .0521198 .014022 3.72 0.000 .0246248 .0796147 wblack | -.0369857 .0535813 -0.69 0.490 -.1420505 .068079 whispanic | -.0383646 .0422138 -0.91 0.364 -.1211395 .0444103 wimm | -.02029 .0356972 -0.57 0.570 -.0902869 .0497068 ownkidsu6 | -.0391381 .046216 -0.85 0.397 -.1297606 .0514844 any_under6 | .1289473 .0685195 1.88 0.060 -.005409 .2633036 _cons | .728168 .1689047 4.31 0.000 .3969715 1.059365 ------------------------------------------------------------------------------ . reg wlogwage weduc wcollege wexp wexp2 wexp3 wblack whispanic wimm > ownkidsu6 any_under6 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 10, 2362) = 78.24 Model | 219.035376 10 21.9035376 Prob > F = 0.0000 Residual | 661.279208 2362 .279965795 R-squared = 0.2488 -------------+------------------------------ Adj R-squared = 0.2456 Total | 880.314583 2372 .371127565 Root MSE = .52912 ------------------------------------------------------------------------------ wlogwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- weduc | .1186135 .0083 14.29 0.000 .1023376 .1348894 wcollege | .0371441 .0406441 0.91 0.361 -.0425577 .1168459 wexp | .078094 .0155888 5.01 0.000 .0475247 .1086632 wexp2 | -.3750109 .0812144 -4.62 0.000 -.5342699 -.215752 wexp3 | .0594979 .0128444 4.63 0.000 .0343106 .0846853 wblack | -.0550525 .0496942 -1.11 0.268 -.1525012 .0423963 whispanic | -.0201261 .039523 -0.51 0.611 -.0976295 .0573773 wimm | -.0216589 .03298 -0.66 0.511 -.0863316 .0430139 ownkidsu6 | -.0048804 .0446087 -0.11 0.913 -.0923566 .0825958 any_under6 | .1005767 .0654636 1.54 0.125 -.0277953 .2289488 _cons | .6216571 .1564038 3.97 0.000 .3149541 .9283601 ------------------------------------------------------------------------------ . reg wlogwage weduc wcollege wexp wexp2 wexp3 wblack whispanic wimm > ownkidsu6 any_under6 lambda1 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 11, 2361) = 71.48 Model | 219.931008 11 19.993728 Prob > F = 0.0000 Residual | 660.383575 2361 .27970503 R-squared = 0.2498 -------------+------------------------------ Adj R-squared = 0.2463 Total | 880.314583 2372 .371127565 Root MSE = .52887 ------------------------------------------------------------------------------ wlogwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- weduc | .1252457 .0090864 13.78 0.000 .1074277 .1430638 wcollege | .0368313 .0406255 0.91 0.365 -.0428342 .1164967 wexp | .0787635 .0155861 5.05 0.000 .0481997 .1093274 wexp2 | -.3857926 .0813999 -4.74 0.000 -.5454153 -.2261699 wexp3 | .0619385 .0129106 4.80 0.000 .0366212 .0872558 wblack | -.0503364 .0497409 -1.01 0.312 -.1478768 .047204 whispanic | -.0297947 .0398724 -0.75 0.455 -.1079832 .0483938 wimm | -.047949 .0360904 -1.33 0.184 -.1187212 .0228232 ownkidsu6 | -.0190525 .0452858 -0.42 0.674 -.1078566 .0697516 any_under6 | .0892655 .0657377 1.36 0.175 -.0396441 .2181751 lambda1 | .1686261 .0942345 1.79 0.074 -.0161649 .3534171 _cons | .4688927 .1781221 2.63 0.009 .1196007 .8181846 ------------------------------------------------------------------------------ . reg wlogwage_ogr weduc wcollege wexp wexp2 wexp3 wblack whispanic wimm > ownkidsu6 any_under6 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 10, 2362) = 77.52 Model | 179.246168 10 17.9246168 Prob > F = 0.0000 Residual | 546.168194 2362 .231231242 R-squared = 0.2471 -------------+------------------------------ Adj R-squared = 0.2439 Total | 725.414362 2372 .30582393 Root MSE = .48087 ------------------------------------------------------------------------------ wlogwage_ogr | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- weduc | .0914047 .007543 12.12 0.000 .076613 .1061963 wcollege | .1196028 .0369376 3.24 0.001 .0471694 .1920363 wexp | .0519063 .0141672 3.66 0.000 .0241248 .0796878 wexp2 | -.2250964 .0738081 -3.05 0.002 -.3698317 -.080361 wexp3 | .0337882 .011673 2.89 0.004 .0108978 .0566786 wblack | -.065481 .0451623 -1.45 0.147 -.1540429 .023081 whispanic | -.0011531 .0359187 -0.03 0.974 -.0715885 .0692824 wimm | -.0699302 .0299724 -2.33 0.020 -.1287051 -.0111553 ownkidsu6 | -.0421012 .0405406 -1.04 0.299 -.1216001 .0373976 any_under6 | .1041021 .0594936 1.75 0.080 -.012563 .2207673 _cons | 1.13297 .1421406 7.97 0.000 .8542366 1.411703 ------------------------------------------------------------------------------ . reg wlogwage_ogr weduc wcollege wexp wexp2 wexp3 wblack whispanic wimm > ownkidsu6 any_under6 lambda1 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 11, 2361) = 72.00 Model | 182.221612 11 16.5656011 Prob > F = 0.0000 Residual | 543.19275 2361 .230068933 R-squared = 0.2512 -------------+------------------------------ Adj R-squared = 0.2477 Total | 725.414362 2372 .30582393 Root MSE = .47966 ------------------------------------------------------------------------------ wlogwage_ogr | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- weduc | .1034931 .0082408 12.56 0.000 .0873332 .1196531 wcollege | .1190327 .036845 3.23 0.001 .0467809 .1912845 wexp | .0531267 .0141356 3.76 0.000 .0254071 .0808463 wexp2 | -.2447479 .0738249 -3.32 0.001 -.3895162 -.0999796 wexp3 | .0382366 .0117092 3.27 0.001 .0152753 .0611979 wblack | -.056885 .0451121 -1.26 0.207 -.1453484 .0315784 whispanic | -.0187758 .0361619 -0.52 0.604 -.0896881 .0521366 wimm | -.1178488 .0327319 -3.60 0.000 -.182035 -.0536626 ownkidsu6 | -.0679326 .0410715 -1.65 0.098 -.1484726 .0126075 any_under6 | .0834854 .0596202 1.40 0.162 -.033428 .2003987 lambda1 | .3073518 .0854651 3.60 0.000 .1397573 .4749463 _cons | .8545289 .1615462 5.29 0.000 .5377419 1.171316 ------------------------------------------------------------------------------ . reg wannhrs wlogwage hwagesal if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 2, 2370) = 15.40 Model | 10427324.8 2 5213662.4 Prob > F = 0.0000 Residual | 802146347 2370 338458.374 R-squared = 0.0128 -------------+------------------------------ Adj R-squared = 0.0120 Total | 812573672 2372 342569.001 Root MSE = 581.77 ------------------------------------------------------------------------------ wannhrs | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wlogwage | 108.0204 19.8114 5.45 0.000 69.17092 146.8699 hwagesal | -.0003412 .0001887 -1.81 0.071 -.0007113 .000029 _cons | 1586.06 58.24411 27.23 0.000 1471.846 1700.275 ------------------------------------------------------------------------------ . reg wannhrs wlogwage hwagesal lambda1 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 3, 2369) = 22.52 Model | 22527451.1 3 7509150.37 Prob > F = 0.0000 Residual | 790046220 2369 333493.55 R-squared = 0.0277 -------------+------------------------------ Adj R-squared = 0.0265 Total | 812573672 2372 342569.001 Root MSE = 577.49 ------------------------------------------------------------------------------ wannhrs | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wlogwage | 64.19953 20.96805 3.06 0.002 23.0819 105.3172 hwagesal | .0002773 .0002136 1.30 0.194 -.0001416 .0006962 lambda1 | -458.5541 76.12711 -6.02 0.000 -607.8368 -309.2714 _cons | 1884.186 76.10663 24.76 0.000 1734.944 2033.429 ------------------------------------------------------------------------------ . reg wannhrs wlogwage_ogr hwagesal if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 2, 2370) = 45.03 Model | 29747878.8 2 14873939.4 Prob > F = 0.0000 Residual | 782825793 2370 330306.242 R-squared = 0.0366 -------------+------------------------------ Adj R-squared = 0.0358 Total | 812573672 2372 342569.001 Root MSE = 574.72 ------------------------------------------------------------------------------ wannhrs | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wlogwage_ogr | 203.9122 21.62004 9.43 0.000 161.516 246.3083 hwagesal | -.0004777 .000187 -2.55 0.011 -.0008444 -.000111 _cons | 1314.436 63.17109 20.81 0.000 1190.56 1438.313 ------------------------------------------------------------------------------ . reg wannhrs wlogwage_ogr hwagesal lambda1 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 3, 2369) = 37.34 Model | 36688425.4 3 12229475.1 Prob > F = 0.0000 Residual | 775885246 2369 327515.933 R-squared = 0.0452 -------------+------------------------------ Adj R-squared = 0.0439 Total | 812573672 2372 342569.001 Root MSE = 572.29 ------------------------------------------------------------------------------ wannhrs | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wlogwage_ogr | 166.9391 22.97792 7.27 0.000 121.8802 211.998 hwagesal | -2.64e-06 .0002129 -0.01 0.990 -.0004201 .0004148 lambda1 | -347.646 75.51906 -4.60 0.000 -495.7363 -199.5557 _cons | 1551.131 81.24404 19.09 0.000 1391.814 1710.448 ------------------------------------------------------------------------------ . reg wannhrs wlogwage_ogr hwagesal weduc if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 3, 2369) = 31.13 Model | 30814979.2 3 10271659.7 Prob > F = 0.0000 Residual | 781758692 2369 329995.227 R-squared = 0.0379 -------------+------------------------------ Adj R-squared = 0.0367 Total | 812573672 2372 342569.001 Root MSE = 574.45 ------------------------------------------------------------------------------ wannhrs | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wlogwage_ogr | 183.8367 24.32322 7.56 0.000 136.1397 231.5337 hwagesal | -.0005225 .0001885 -2.77 0.006 -.0008922 -.0001528 weduc | 9.204194 5.118432 1.80 0.072 -.8328766 19.24126 _cons | 1241.955 74.90963 16.58 0.000 1095.06 1388.85 ------------------------------------------------------------------------------ . reg wannhrs wlogwage_ogr hwagesal weduc lambda1 if work_and_wage==1; Source | SS df MS Number of obs = 2373 -------------+------------------------------ F( 4, 2368) = 28.98 Model | 37920032.1 4 9480008.02 Prob > F = 0.0000 Residual | 774653639 2368 327134.138 R-squared = 0.0467 -------------+------------------------------ Adj R-squared = 0.0451 Total | 812573672 2372 342569.001 Root MSE = 571.96 ------------------------------------------------------------------------------ wannhrs | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wlogwage_ogr | 181.8804 24.22118 7.51 0.000 134.3835 229.3773 hwagesal | .0002577 .0002515 1.02 0.306 -.0002355 .0007509 weduc | -13.75246 7.087732 -1.94 0.052 -27.65126 .1463443 lambda1 | -489.1987 104.9698 -4.66 0.000 -695.041 -283.3563 _cons | 1755.805 133.1162 13.19 0.000 1494.768 2016.841 ------------------------------------------------------------------------------ . end of do-file . exit, clear