--------------------------------------------------------------------------------- log: J:\Lobby\Agendas_Project\Death_Penalty\book\chapters\current\ch6_Sen > tences\analysis2007\sentences.log log type: text opened on: 13 Aug 2007, 12:28:52 . *log using S:\Lobby\Agendas_Project/death_penalty/book/chapters\current\ch6_sen > tences\run_sent_regress2_homSDB.log, replace . . . #delimit ; delimiter now ; . set more off ; . * ***********************************************************************; . * Path Name: J:\Lobby\Agendas_Project\Death_Penalty\book\chapters\current\ > ch6_Sentences\analysis2007; . * File-Name: sentences.do > *; . * Date: May 15, 2007 *; . * Author: sdb *; . * Purpose: 1) Replicate sentencing model from book > *; . * 2) Estimate with exonerations > *; . * 3) Estimate with exonerations and execu > tions *; . * Data Used: yrlyopinion.dta *; . * Output File: sentences.log > *; . * Data Output: none *; . * Previous File: None *; . * Machine: mac *; . * ***********************************************************************; . *use /projects/death_penalty/book/chapters/current/ch6_sentences/analysis2007/a > ll_yrly_data.dta; . use all_yrly_data.dta; . tset year; time variable: year, 1930 to 2006 . replace hom=hom/1000; hom was int now float (57 real changes made) . *****************************************; . *Replicate model of sentences in book *; . *****************************************; . regress sentences L.sentences L.net_tone L.netpsm L.hom d1973 d1975 if tin(1962 > ,2005); Source | SS df MS Number of obs = 44 -------------+------------------------------ F( 6, 37) = 82.30 Model | 283603.446 6 47267.2411 Prob > F = 0.0000 Residual | 21250.4627 37 574.336828 R-squared = 0.9303 -------------+------------------------------ Adj R-squared = 0.9190 Total | 304853.909 43 7089.62579 Root MSE = 23.965 ------------------------------------------------------------------------------ sentences | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- sentences | L1. | .316286 .0966195 3.27 0.002 .1205162 .5120558 net_tone | L1. | .4530761 .137001 3.31 0.002 .1754858 .7306665 netpsm | L1. | 5.059413 1.068856 4.73 0.000 2.893705 7.225122 hom | L1. | .8174102 1.437605 0.57 0.573 -2.095454 3.730275 d1973 | -67.80436 25.87929 -2.62 0.013 -120.2408 -15.36793 d1975 | 129.4905 25.33956 5.11 0.000 78.14763 180.8333 _cons | 22.92232 19.20006 1.19 0.240 -15.9807 61.82535 ------------------------------------------------------------------------------ . predict repl, resid; (33 missing values generated) . wntestq repl, lags(8); Portmanteau test for white noise --------------------------------------- Portmanteau (Q) statistic = 11.0835 Prob > chi2(8) = 0.1970 . *****************************************; . *Add exonerations *; . *****************************************; . regress sentences L.sentences L.net_tone L.netpsm L.hom L.exonerations d1973 d1 > 975 if tin(1962,2005); Source | SS df MS Number of obs = 30 -------------+------------------------------ F( 6, 23) = 26.77 Model | 102832.124 6 17138.6873 Prob > F = 0.0000 Residual | 14726.6763 23 640.290275 R-squared = 0.8747 -------------+------------------------------ Adj R-squared = 0.8420 Total | 117558.8 29 4053.75172 Root MSE = 25.304 ------------------------------------------------------------------------------ sentences | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- sentences | L1. | .3493745 .1093135 3.20 0.004 .1232423 .5755066 net_tone | L1. | .4611299 .2238684 2.06 0.051 -.0019771 .9242369 netpsm | L1. | 4.717441 1.399573 3.37 0.003 1.822204 7.612679 hom | L1. | 1.71539 2.938294 0.58 0.565 -4.362935 7.793714 exonerations | L1. | -.5780604 1.90361 -0.30 0.764 -4.515978 3.359857 d1973 | (dropped) d1975 | 127.0208 28.31749 4.49 0.000 68.44156 185.6 _cons | 7.257401 61.06811 0.12 0.906 -119.0716 133.5864 ------------------------------------------------------------------------------ . predict withexon, resid; (47 missing values generated) . wntestq withexon, lags(8); (note: time series has 1 gap) Portmanteau test for white noise --------------------------------------- Portmanteau (Q) statistic = 10.4000 Prob > chi2(8) = 0.2381 . *****************************************; . *Add executions *; . *****************************************; . regress sentences L.sentences L.net_tone L.netpsm L.hom L.exonerations L.execut > ions d1973 d1975 if tin(1962,2005); Source | SS df MS Number of obs = 30 -------------+------------------------------ F( 7, 22) = 27.53 Model | 105512.907 7 15073.2724 Prob > F = 0.0000 Residual | 12045.8935 22 547.540613 R-squared = 0.8975 -------------+------------------------------ Adj R-squared = 0.8649 Total | 117558.8 29 4053.75172 Root MSE = 23.4 ------------------------------------------------------------------------------ sentences | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- sentences | L1. | .3285991 .1015217 3.24 0.004 .1180561 .5391422 net_tone | L1. | .6063936 .2171802 2.79 0.011 .1559895 1.056798 netpsm | L1. | 3.582115 1.392239 2.57 0.017 .6947888 6.469441 hom | L1. | 4.527472 2.999682 1.51 0.145 -1.693488 10.74843 exonerations | L1. | -2.298531 1.924419 -1.19 0.245 -6.289531 1.692469 executions | L1. | .5760852 .2603539 2.21 0.038 .0361443 1.116026 d1973 | (dropped) d1975 | 120.5944 26.34689 4.58 0.000 65.95434 175.2345 _cons | -25.8876 58.42504 -0.44 0.662 -147.0537 95.27851 ------------------------------------------------------------------------------ . predict withexec, resid; (47 missing values generated) . wntestq withexec, lags(8); (note: time series has 1 gap) Portmanteau test for white noise --------------------------------------- Portmanteau (Q) statistic = 7.5388 Prob > chi2(8) = 0.4798 . exit; end of do-file