------------------------------------------------------------------------------ log: d:\bill\spring2009\card_et_al.log log type: text opened on: 27 Apr 2009, 10:07:47 . *read in raw data; . use card_et_al; . * get list of variables; . describe; Contains data from card_et_al.dta obs: 46,950 vars: 14 21 Aug 2006 08:28 size: 3,004,800 (93.3% of memory free) ------------------------------------------------------------------------------ > - storage display value variable name type format label variable label ------------------------------------------------------------------------------ > - educ_r1 float %9.0g education recode, 1=<8, 8=adv degree phstat float %9.0g self reported health, 5=excellent, 1=poor age_qtr float %9.0g age in quarters age_yrs float %9.0g age in years black float %9.0g =1 if black, =otherwise delayed_med float %9.0g has delayed medical care because of cost hispanic float %9.0g =1 if hispanic, =0 otherwise hosp_12m float %9.0g ever hospitalized past 12 months insured float %9.0g =1 if has health insurance, =0 otherwise male float %9.0g =1 if male, =0 female md_2wks float %9.0g visited doctor past 2 weeks not_get_med float %9.0g have not received care because of cost white float %9.0g =1 if white, 0=otherwise year float %9.0g year of survey ------------------------------------------------------------------------------ > - Sorted by: . * get tables of self reported health status; . tab phstat; self | reported | health, | 5=excellent | , 1=poor | Freq. Percent Cum. ------------+----------------------------------- 1 | 8,131 17.32 17.32 2 | 12,613 26.86 44.18 3 | 15,241 32.46 76.65 4 | 7,800 16.61 93.26 5 | 3,165 6.74 100.00 ------------+----------------------------------- Total | 46,950 100.00 . * generate some new variables; . gen good_health=phstat<4; . label var good_health "=1 if report,good,vgood,excel health"; . * eligible for Medicare after quarter 259; . gen age65=age_qtr>259; . * scale the age in quarters index so that it equals 0; . * in the month you become eligible for Medicare; . gen index=age_qtr-260; . gen index2=index*index; . gen index_age65=index*age65; . gen index2_age65=index2*age65; . * generate dummy variables for years of education; . * and the year of the survey; . xi i.educ_r1 i.year; i.educ_r1 _Ieduc_r1_1-8 (naturally coded; _Ieduc_r1_1 omitted) i.year _Iyear_1998-2001 (naturally coded; _Iyear_1998 omitted) . * 1st stage results. Impact of Medicare on insurance coverage; . * basic results in the paper. the index (running variable) is; . * entered as a quartic; . reg insured male white black hispanic _Ie* _Iyear* > index index2 index_age65 index2_age65 age65; Source | SS df MS Number of obs = 46950 -------------+------------------------------ F( 19, 46930) = 260.17 Model | 334.010957 19 17.5795241 Prob > F = 0.0000 Residual | 3170.9949 46930 .067568611 R-squared = 0.0953 -------------+------------------------------ Adj R-squared = 0.0949 Total | 3505.00586 46949 .074655602 Root MSE = .25994 ------------------------------------------------------------------------------ insured | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- male | .0077525 .0024253 3.20 0.001 .0029988 .0125062 white | .039912 .0053348 7.48 0.000 .0294557 .0503682 black | .004996 .0063545 0.79 0.432 -.0074589 .017451 hispanic | .0999943 .003956 25.28 0.000 .0922405 .107748 _Ieduc_r1_2 | .0477623 .0045912 10.40 0.000 .0387636 .0567611 _Ieduc_r1_3 | .0851812 .0040895 20.83 0.000 .0771657 .0931966 _Ieduc_r1_4 | .0780332 .0082227 9.49 0.000 .0619167 .0941498 _Ieduc_r1_5 | .0970506 .0046304 20.96 0.000 .087975 .1061262 _Ieduc_r1_6 | .101996 .0065035 15.68 0.000 .089249 .114743 _Ieduc_r1_7 | .1109833 .0088811 12.50 0.000 .0935763 .1283904 _Ieduc_r1_8 | .1124369 .0050158 22.42 0.000 .1026059 .1222678 _Iyear_1999 | -.000224 .0034016 -0.07 0.947 -.0068912 .0064432 _Iyear_2000 | -.0079039 .0033842 -2.34 0.020 -.014537 -.0012708 _Iyear_2001 | -.0002411 .0033937 -0.07 0.943 -.0068928 .0064105 index | .0008314 .0005825 1.43 0.153 -.0003102 .001973 index2 | .0000103 .0000137 0.76 0.449 -.0000164 .0000371 index_age65 | .0009125 .0008376 1.09 0.276 -.0007292 .0025542 index2_age65 | -.0000391 .0000204 -1.91 0.056 -.0000791 9.55e-07 age65 | .0910622 .0072477 12.56 0.000 .0768565 .1052678 _cons | .6820244 .0079575 85.71 0.000 .6664276 .6976211 ------------------------------------------------------------------------------ . * Reduced form results. Impact of Medicare coverage on health outcomes; . * Outcomes are good_health, delayed_med, not_get_med, hosp_12m; . * Note that age65 is small and stat insign in all except the hospitalization > equation; . * implying that although Medicare has increased insurance coverage it has no > t changed outcomes much; . reg good_health male white black hispanic _Ie* _Iyear* > index index2 index_age65 index2_age65 age65; Source | SS df MS Number of obs = 46950 -------------+------------------------------ F( 19, 46930) = 217.81 Model | 681.040956 19 35.8442608 Prob > F = 0.0000 Residual | 7723.12358 46930 .164566878 R-squared = 0.0810 -------------+------------------------------ Adj R-squared = 0.0807 Total | 8404.16454 46949 .179006252 Root MSE = .40567 ------------------------------------------------------------------------------ good_health | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- male | -.0012598 .003785 -0.33 0.739 -.0086785 .0061589 white | .0438366 .0083256 5.27 0.000 .0275183 .0601548 black | -.0927649 .009917 -9.35 0.000 -.1122024 -.0733274 hispanic | .025925 .0061738 4.20 0.000 .0138242 .0380257 _Ieduc_r1_2 | .0803402 .0071651 11.21 0.000 .0662966 .0943838 _Ieduc_r1_3 | .2211995 .0063821 34.66 0.000 .2086904 .2337086 _Ieduc_r1_4 | .1133665 .0128325 8.83 0.000 .0882146 .1385184 _Ieduc_r1_5 | .2486983 .0072263 34.42 0.000 .2345347 .2628619 _Ieduc_r1_6 | .240662 .0101496 23.71 0.000 .2207687 .2605554 _Ieduc_r1_7 | .2925821 .01386 21.11 0.000 .2654162 .3197479 _Ieduc_r1_8 | .315219 .0078277 40.27 0.000 .2998766 .3305615 _Iyear_1999 | .0051162 .0053086 0.96 0.335 -.0052887 .0155212 _Iyear_2000 | .0026664 .0052815 0.50 0.614 -.0076854 .0130182 _Iyear_2001 | -.0058921 .0052963 -1.11 0.266 -.0162729 .0044887 index | -.0000385 .000909 -0.04 0.966 -.0018202 .0017431 index2 | .000021 .0000213 0.99 0.323 -.0000207 .0000628 index_age65 | .0002947 .0013072 0.23 0.822 -.0022673 .0028568 index2_age65 | -.0000676 .0000319 -2.12 0.034 -.0001301 -5.18e-06 age65 | .0070009 .011311 0.62 0.536 -.0151688 .0291705 _cons | .5326211 .0124186 42.89 0.000 .5082803 .5569618 ------------------------------------------------------------------------------ . reg delayed_med male white black hispanic _Ie* _Iyear* > index index2 index_age65 index2_age65 age65; Source | SS df MS Number of obs = 46950 -------------+------------------------------ F( 19, 46930) = 40.40 Model | 47.859748 19 2.5189341 Prob > F = 0.0000 Residual | 2926.261 46930 .06235374 R-squared = 0.0161 -------------+------------------------------ Adj R-squared = 0.0157 Total | 2974.12075 46949 .063347904 Root MSE = .24971 ------------------------------------------------------------------------------ delayed_med | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- male | -.0220104 .0023299 -9.45 0.000 -.0265769 -.0174438 white | -.0061438 .0051248 -1.20 0.231 -.0161885 .0039008 black | -.0011039 .0061044 -0.18 0.856 -.0130686 .0108607 hispanic | .0030924 .0038003 0.81 0.416 -.0043562 .0105409 _Ieduc_r1_2 | -.0109521 .0044104 -2.48 0.013 -.0195966 -.0023076 _Ieduc_r1_3 | -.0460547 .0039285 -11.72 0.000 -.0537546 -.0383548 _Ieduc_r1_4 | -.0139309 .007899 -1.76 0.078 -.029413 .0015513 _Ieduc_r1_5 | -.0335417 .0044481 -7.54 0.000 -.04226 -.0248234 _Ieduc_r1_6 | -.0425928 .0062475 -6.82 0.000 -.054838 -.0303475 _Ieduc_r1_7 | -.0453161 .0085315 -5.31 0.000 -.0620379 -.0285943 _Ieduc_r1_8 | -.0618797 .0048183 -12.84 0.000 -.0713237 -.0524357 _Iyear_1999 | .0023618 .0032677 0.72 0.470 -.0040429 .0087665 _Iyear_2000 | .0040252 .003251 1.24 0.216 -.0023468 .0103972 _Iyear_2001 | .0053107 .0032601 1.63 0.103 -.0010792 .0117005 index | -.0015644 .0005595 -2.80 0.005 -.0026611 -.0004677 index2 | -.000021 .0000131 -1.60 0.109 -.0000468 4.66e-06 index_age65 | -.0002938 .0008046 -0.37 0.715 -.0018709 .0012832 index2_age65 | .000051 .0000196 2.60 0.009 .0000126 .0000895 age65 | -.0047972 .0069624 -0.69 0.491 -.0184437 .0088492 _cons | .1097541 .0076442 14.36 0.000 .0947713 .124737 ------------------------------------------------------------------------------ . reg not_get_med male white black hispanic _Ie* _Iyear* > index index2 index_age65 index2_age65 age65; Source | SS df MS Number of obs = 46950 -------------+------------------------------ F( 19, 46930) = 47.13 Model | 40.6149019 19 2.13762642 Prob > F = 0.0000 Residual | 2128.66305 46930 .045358258 R-squared = 0.0187 -------------+------------------------------ Adj R-squared = 0.0183 Total | 2169.27796 46949 .046204987 Root MSE = .21297 ------------------------------------------------------------------------------ not_get_med | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- male | -.0158153 .0019871 -7.96 0.000 -.0197101 -.0119205 white | -.0013835 .0043709 -0.32 0.752 -.0099506 .0071835 black | .0200642 .0052064 3.85 0.000 .0098596 .0302688 hispanic | -.0032694 .0032412 -1.01 0.313 -.0096223 .0030834 _Ieduc_r1_2 | -.0088871 .0037616 -2.36 0.018 -.0162599 -.0015142 _Ieduc_r1_3 | -.0456555 .0033506 -13.63 0.000 -.0522227 -.0390883 _Ieduc_r1_4 | -.0191441 .006737 -2.84 0.004 -.0323488 -.0059395 _Ieduc_r1_5 | -.0392033 .0037938 -10.33 0.000 -.0466391 -.0317674 _Ieduc_r1_6 | -.0414814 .0053285 -7.78 0.000 -.0519254 -.0310375 _Ieduc_r1_7 | -.0539067 .0072765 -7.41 0.000 -.0681687 -.0396447 _Ieduc_r1_8 | -.0603897 .0041095 -14.70 0.000 -.0684445 -.052335 _Iyear_1999 | .0037696 .002787 1.35 0.176 -.001693 .0092322 _Iyear_2000 | .0046364 .0027728 1.67 0.095 -.0007983 .010071 _Iyear_2001 | .0068705 .0027805 2.47 0.013 .0014206 .0123204 index | -.0014545 .0004772 -3.05 0.002 -.0023898 -.0005191 index2 | -.000022 .0000112 -1.96 0.050 -.0000439 -4.45e-08 index_age65 | -.0001714 .0006863 -0.25 0.803 -.0015165 .0011736 index2_age65 | .0000499 .0000167 2.98 0.003 .0000171 .0000827 age65 | -.0012621 .0059382 -0.21 0.832 -.0129011 .0103769 _cons | .0848953 .0065198 13.02 0.000 .0721165 .0976742 ------------------------------------------------------------------------------ . reg hosp_12m male white black hispanic _Ie* _Iyear* > index index2 index_age65 index2_age65 age65; Source | SS df MS Number of obs = 46950 -------------+------------------------------ F( 19, 46930) = 32.12 Model | 69.4070966 19 3.65300508 Prob > F = 0.0000 Residual | 5336.84517 46930 .113719266 R-squared = 0.0128 -------------+------------------------------ Adj R-squared = 0.0124 Total | 5406.25227 46949 .115151596 Root MSE = .33722 ------------------------------------------------------------------------------ hosp_12m | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- male | .0146667 .0031464 4.66 0.000 .0084997 .0208337 white | .0129684 .0069209 1.87 0.061 -.0005966 .0265334 black | .034299 .0082438 4.16 0.000 .0181411 .050457 hispanic | .0178585 .0051321 3.48 0.001 .0077994 .0279176 _Ieduc_r1_2 | -.0022616 .0059562 -0.38 0.704 -.0139357 .0094126 _Ieduc_r1_3 | -.0393039 .0053053 -7.41 0.000 -.0497024 -.0289054 _Ieduc_r1_4 | .0150464 .0106674 1.41 0.158 -.0058618 .0359546 _Ieduc_r1_5 | -.0238885 .006007 -3.98 0.000 -.0356624 -.0121146 _Ieduc_r1_6 | -.0326953 .0084371 -3.88 0.000 -.0492322 -.0161585 _Ieduc_r1_7 | -.0368846 .0115215 -3.20 0.001 -.0594669 -.0143022 _Ieduc_r1_8 | -.0561876 .006507 -8.63 0.000 -.0689415 -.0434338 _Iyear_1999 | -.0040603 .0044129 -0.92 0.358 -.0127097 .0045891 _Iyear_2000 | -.0008291 .0043904 -0.19 0.850 -.0094343 .0077761 _Iyear_2001 | -.0013709 .0044027 -0.31 0.756 -.0100002 .0072584 index | .0005039 .0007556 0.67 0.505 -.0009771 .001985 index2 | -4.88e-06 .0000177 -0.28 0.783 -.0000396 .0000298 index_age65 | -.000714 .0010866 -0.66 0.511 -.0028438 .0014157 index2_age65 | .0000438 .0000265 1.65 0.098 -8.11e-06 .0000957 age65 | .0253064 .0094025 2.69 0.007 .0068772 .0437355 _cons | .1134856 .0103233 10.99 0.000 .0932517 .1337195 ------------------------------------------------------------------------------ . log close; log: d:\bill\spring2009\card_et_al.log log type: text closed on: 27 Apr 2009, 10:07:50 ------------------------------------------------------------------------------