1) coefplot based on the following regressions:
Code:
. reg fertility lngdpper Unemployment WPUI StringencyIndex Source | SS df MS Number of obs = 130 -------------+---------------------------------- F(4, 125) = 54.44 Model | 43.5590529 4 10.8897632 Prob > F = 0.0000 Residual | 25.0034792 125 .200027834 R-squared = 0.6353 -------------+---------------------------------- Adj R-squared = 0.6236 Total | 68.5625321 129 .531492497 Root MSE = .44724 --------------------------------------------------------------------------------- fertility | Coefficient Std. err. t P>|t| [95% conf. interval] ----------------+---------------------------------------------------------------- lngdpper | -.3097261 .0322072 -9.62 0.000 -.3734681 -.2459841 Unemployment | -.0069286 .0077619 -0.89 0.374 -.0222904 .0084332 WPUI | -.0007319 .0003823 -1.91 0.058 -.0014886 .0000247 StringencyIndex | -.0151191 .0058869 -2.57 0.011 -.0267701 -.0034681 _cons | 5.534372 .2454153 22.55 0.000 5.048665 6.020079 ---------------------------------------------------------------------------------
Code:
estimates store D
Code:
. reg fertility lngdpper Unemployment WPUI schoolclosing Source | SS df MS Number of obs = 130 -------------+---------------------------------- F(4, 125) = 53.58 Model | 43.3045478 4 10.826137 Prob > F = 0.0000 Residual | 25.2579843 125 .202063874 R-squared = 0.6316 -------------+---------------------------------- Adj R-squared = 0.6198 Total | 68.5625321 129 .531492497 Root MSE = .44952 ------------------------------------------------------------------------------- fertility | Coefficient Std. err. t P>|t| [95% conf. interval] --------------+---------------------------------------------------------------- lngdpper | -.3234715 .0316028 -10.24 0.000 -.3860173 -.2609257 Unemployment | -.0068205 .0078007 -0.87 0.384 -.0222591 .0086181 WPUI | -.0008157 .0003773 -2.16 0.033 -.0015625 -.000069 schoolclosing | -.2478858 .1079816 -2.30 0.023 -.4615948 -.0341769 _cons | 5.546419 .247489 22.41 0.000 5.056608 6.036231 -------------------------------------------------------------------------------
Code:
estimates store E
Code:
. reg fertility lngdpper Unemployment WPUI Cancelpubliceven Source | SS df MS Number of obs = 130 -------------+---------------------------------- F(4, 125) = 52.25 Model | 42.902468 4 10.725617 Prob > F = 0.0000 Residual | 25.660064 125 .205280512 R-squared = 0.6257 -------------+---------------------------------- Adj R-squared = 0.6138 Total | 68.5625321 129 .531492497 Root MSE = .45308 ---------------------------------------------------------------------------------- fertility | Coefficient Std. err. t P>|t| [95% conf. interval] -----------------+---------------------------------------------------------------- lngdpper | -.3184778 .0322615 -9.87 0.000 -.3823274 -.2546282 Unemployment | -.0070328 .0078681 -0.89 0.373 -.0226049 .0085392 WPUI | -.0008469 .0003845 -2.20 0.029 -.0016079 -.0000858 Cancelpubliceven | -.3190479 .1775599 -1.80 0.075 -.6704609 .0323652 _cons | 5.499037 .2478894 22.18 0.000 5.008433 5.989641 ----------------------------------------------------------------------------------
Code:
estimates store F
Code:
coefplot D E coefplot D F E, vertical drop(_cons) yline(0)
but when I did the coefplot , it is not so clear and I think there is a mistake.
2) just scatter plot among the fertility and my variables without doing a regression.
I did this command which the results are not clear:
Code:
twoway (scatter fertility gdpgrowth,mcolor(blue) msymbol(t))(scatter fertility StringencyIndex ,mcolor(red) msymbol(D)) (scatter fertility schoolclosing , msymbol(S))
I hope I receive your advice so soon. thank you so much in advance.
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