Hi Statalisters,
I have a question about using the -gmm- command to replicate OLS estimation. Things work fine up until I introduce a dummy variable, and I have no idea why that would be troublesome. Consider the following example:
The two commands give identical point estimates, but slightly different SEs (but that's to be expected). Now I add a dummy variable (and post output rather than source code):
Does anyone have any idea what might be going on here?
I have a question about using the -gmm- command to replicate OLS estimation. Things work fine up until I introduce a dummy variable, and I have no idea why that would be troublesome. Consider the following example:
Code:
sysuse auto local rhs turn length headroom trunk reg mpg `rhs', r gmm (mpg -({xb:`rhs'}+{b0})), instruments(`rhs') winitial(identity) vce(robust) iterate(5)
Code:
. local rhs turn length headroom trunk foreign . reg mpg `rhs', r Linear regression Number of obs = 74 F(5, 68) = 32.94 Prob > F = 0.0000 R-squared = 0.6473 Root MSE = 3.5602 ------------------------------------------------------------------------------ | Robust mpg | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- turn | -.2573714 .1737776 -1.48 0.143 -.6041391 .0893963 length | -.1812296 .0578863 -3.13 0.003 -.2967399 -.0657193 headroom | -.0759515 .4046498 -0.19 0.852 -.8834176 .7315147 trunk | .004777 .1751617 0.03 0.978 -.3447527 .3543068 foreign | -1.632016 1.264629 -1.29 0.201 -4.155544 .8915119 _cons | 66.20747 4.938808 13.41 0.000 56.35223 76.0627 ------------------------------------------------------------------------------ . gmm (mpg -({xb:`rhs'}+{b0})), instruments(`rhs') winitial(identity) vce(robust) iterate(5) Step 1 Iteration 0: GMM criterion Q(b) = 15985229 (not concave) Iteration 1: GMM criterion Q(b) = 1253436 (not concave) Iteration 2: GMM criterion Q(b) = 98463.417 (not concave) Iteration 3: GMM criterion Q(b) = 7913.7578 (not concave) Iteration 4: GMM criterion Q(b) = 817.35425 (not concave) Iteration 5: GMM criterion Q(b) = 162.62732 (not concave) convergence not achieved note: model is exactly identified GMM estimation Number of parameters = 6 Number of moments = 6 Initial weight matrix: Identity Number of obs = 74 GMM weight matrix: Robust ------------------------------------------------------------------------------ | Robust | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- turn | .0861536 .3691139 0.23 0.815 -.6372964 .8096036 length | .0181301 .0977029 0.19 0.853 -.1733641 .2096244 headroom | 1.134376 1.059623 1.07 0.284 -.9424463 3.211198 trunk | .2445109 .3016458 0.81 0.418 -.346704 .8357258 foreign | 12.96847 3.387061 3.83 0.000 6.329955 19.60699 -------------+---------------------------------------------------------------- /b0 | 3.45462 15.98317 0.22 0.829 -27.87182 34.78106 ------------------------------------------------------------------------------ Instruments for equation 1: turn length headroom trunk foreign _cons Warning: convergence not achieved
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