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Econometrics-I-12

501.390.368 1969 195.8 1.047 7891 1.044 1.031

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Unformatted text preview: 501 .390 .368 1969 195.8 1.047 7891 1.044 1.031 1.127 .514 .409 .386 1970 207.4 1.056 8134 1.076 1.043 1.285 .527 .427 .407 1971 218.3 1.063 8322 1.120 1.102 1.377 .547 .442 .431 1972 226.8 1.076 8562 1.110 1.105 1.434 .555 .458 .451 1973 237.9 1.181 9042 1.111 1.176 1.448 .566 .497 .474 1974 225.8 1.599 8867 1.175 1.226 1.480 .604 .572 .513 1975 232.4 1.708 8944 1.276 1.464 1.586 .659 .615 .556 1976 241.7 1.779 9175 1.357 1.679 1.742 .695 .638 .598 1977 249.2 1.882 9381 1.429 1.828 1.824 .727 .671 .648 1978 261.3 1.963 9735 1.538 1.865 1.878 .769 .719 .698 1979 248.9 2.656 9829 1.660 2.010 2.003 .821 .800 .756 1980 226.8 3.691 9722 1.793 2.081 2.516 .892 .894 .839 1981 225.6 4.109 9769 1.902 2.569 3.120 .957 .969 .926 1982 228.8 3.894 9725 1.976 2.964 3.460 1.000 1.000 1.000 1983 239.6 3.764 9930 2.026 3.297 3.626 1.041 1.021 1.062 1984 244.7 3.707 10421 2.085 3.757 3.852 1.038 1.050 1.117 1985 245.8 3.738 10563 2.152 3.797 4.028 1.045 1.075 1.173 1986 269.4 2.921 10780 2.240 3.632 4.264 1.053 1.069 1.224 ˜˜˜™™ ™ 24/38 Part 12: Asymptotics for the Regression Model Data Setup Create; G=log(G); Pg=log(PG); y=log(y); pnc=log(pnc); puc=log(puc); ppt=log(ppt); pd=log(pd); pn=log(pn); ps=log(ps); t=year-1960$ Namelist; X=one,y,pg,pnc,puc,ppt,pd,pn,ps,t$ Regress; lhs=g;rhs=X;PrintVC$ ˜˜˜™™ ™ 25/38 Part 12: Asymptotics for the Regression Model Regression Model Based on the gasoline data: The regression equation is g =1 + 2y + 3pg + 4pnc + 5puc + 6ppt + 7pd + 8pn + 9ps + 10t + All variables are logs of the raw variables, so that coefficients are elasticities. The new variable, t, is a time trend, 0,1,…,26, so that 10 is the autonomous yearly proportional growth in G. ˜˜˜™ ™ 26/38 Part 12: Asymptotics for the Regression Model Least Squares Results +----------------------------------------------------+ | Ordinary least squares regression | | LHS=G Mean = 5.308616 | | Standard deviation = .2313508 | | Model size Parameters = 10 | | Degrees of freedom = 17 | | Residuals Sum of squares = .003776938 | | Standard error of e = .01490546 | | Fit R-squared = .9972859 | | Adjusted R-squared = .9958490 | | Model test F[ 9, 17] (prob) = 694.07 (.0000) | | Chi-sq [ 9] (prob) = 159.55 (.0000) | +----------------------------------------------------+ +---------+--------------+----------------+--------+---------+----------+ |Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X| +---------+--------------+----------------+--------+---------+----------+ Constant -5.97984140 2.50176400 -2.390 .0287 Y 1.39438363 .27824509 5.011 .0001 9.03448264 PG -.58143705 .06111346 -9.514 .0000 .47679491 PNC -.29476979 .25797920 -1.143 .2690 .28100132 PUC -.20153591 .07415599 -2.718 .0146 .40523616 PPT .08050720 .08706712 .925 .3681 .47071442 PD 1.50606609 .29745626 5.063 .0001 -.44279509 PN .99947385 .27032812 3.697 .0018 -.58532943 PS -.81789420 .46197918 ....
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501.390.368 1969 195.8 1.047 7891 1.044 1.031...

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