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cc1
2024 Apr 23
1
System GMM yields identical results for any weighting matrix
...uot;, data=data1)
OLSmat <- diag(diag(m0$residCov)); Wmat <- solve(OLSmat)
# Choose the type of covariance matrix in GMM
vc1 <- "MDS"
vc1 <- "CondHom"
vc1 <- "HAC"
#vc1 <- "TrueFixed"
# Choose between restricted and unrestricted estimation
cec1=NULL # unrestricted
cec1=3 # restrict the coefficient on the dummy to be equal across
equations
# Estimate the model with `sysGmm` using different weighting matrices:
identity, "optimal" and manually specified
m1a <- sysGmm(g=ES_g, h=ES_h, wmatrix="ident" , weightsMatrix...
2024 Apr 23
1
System GMM yields identical results for any weighting matrix
...$residCov)); Wmat <- solve(OLSmat)
>
> # Choose the type of covariance matrix in GMM
> vc1 <- "MDS"
> vc1 <- "CondHom"
> vc1 <- "HAC"
> #vc1 <- "TrueFixed"
>
> # Choose between restricted and unrestricted estimation
> cec1=NULL # unrestricted
> cec1=3 # restrict the coefficient on the dummy to be equal across
> equations
>
> # Estimate the model with `sysGmm` using different weighting matrices:
> identity, "optimal" and manually specified
> m1a <- sysGmm(g=ES_g, h=ES_h, wmatrix="...