Hi everyone!
I have a question about GMM command of Stata
Following Choi,Hiriki, Takezawa(1998), I utilize the conditional pricing model and pricing error and innovation.
Three equation is as follow:
1.Conditional model: E(Ri,tlomegat-1)=lamda0(omegat-1)+gammaLMcov(Ri,t,RLMtㅣomegat-1)+gammaWMcov(Ri,t,RWMtㅣomegat-1)+gammaFXcov(Ri,t,RFXtㅣomegat-1)
2.pricing error: ut=-Zt-1r0+Zt-1rLMRLM,t+Zt-1rWMRWM,t+Zt-1rFXRFX,t
3.innovation: hi,t=Ri,t-Ri,tut
,where Z is instumental variables. The pricing error should be zero and the expected value of innovations is zero. Choi,Hiriki, Takezawa(1998) used GMM method to the set of equations in pricing error and innovation.So they obtained estimates of r0,rLM,rWM,rFX. I want to analyze conditional model following them.
I use Hansen(1982)’s GMM method aplying pricing kernel.
So the STATA code I executed is as follows.
[CODE]
.gmm(eq1:rit_a-{a0}-{a1}*cov1-{a2}*cov2-{a3}*cov3)
(eq2:rit_a-{a0}-{a1}*cov1-{a2}*cov2-{a3}*cov3), instruments(eq1:lag1 lag2 lag3 Jandum) instruments(eq2:lag1) winitial(identity)
warning: 359978 missing values returned for equation 1 at initial values
warning: 359978 missing values returned for equation 2 at initial values
Step 1
Iteration 0: GMM criterion Q(b) = 1.9949011
Iteration 1: GMM criterion Q(b) = 1.537e-06
Iteration 2: GMM criterion Q(b) = 1.537e-06
Step 2
Iteration 0: GMM criterion Q(b) = 8.837e-07
Iteration 1: GMM criterion Q(b) = 7.546e-07
Iteration 2: GMM criterion Q(b) = 7.546e-07
GMM estimation
Number of parameters = 4
Number of moments = 7
Initial weight matrix: Identity Number of obs = 575207
GMM weight matrix: Robust
------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
/a0 | -.4532532 .0876545 -5.17 0.000 -.6250529 -.2814535
/a1 | -.0992952 .0192035 -5.17 0.000 -.1369334 -.061657
/a2 | .0293273 .005053 5.80 0.000 .0194235 .039231
/a3 | -64.23148 9.697605 -6.62 0.000 -83.23844 -45.22452
------------------------------------------------------------------------------
Instruments for equation 1: lag1 lag2 lag3 Jandum _cons
Instruments for equation 2: lag1 _cons
. estat overid
Test of overidentifying restriction:
Hansen's J chi2(3) = .434048 (p = 0.9331)
But I'm not sure if this is done right.
I want to analyze all the above three equations.
Any help is highly appreciated.
Thank you for your time.
Related Posts with conditional pricing model using GMM
spmap - how to create dot mapsHi again, I am attempting to plot a dot map using spmap, where the map is meant to show Kenya with …
Sorting by one variable seems to affect other variables in my data sheetHi there, I'm trying to flip my datasheet to that the top answer is the bottom answer. The datashee…
Trim-and-fill Method for Publication BiasHello! I am conducting a meta-analysis on the prevalence of depression and would like some help und…
Wondering if ppmlhdfe command already removes autocorrelation? Knowing that it already fixes heteroscedasticity.Hello, I am considering using ppmlhdfe command for my gravity model analysis. Found out that it has …
Multilevel mediation sem question (really need help)I am doing multilevel mediation analysis for clustering data (hierarchical) the mediation variable …
Subscribe to:
Post Comments (Atom)
0 Response to conditional pricing model using GMM
Post a Comment