Displaying 3 results from an estimated 3 matches for "es_g".
Did you mean:
e_g
2024 Apr 23
1
System GMM yields identical results for any weighting matrix
...y[,i] <- i + sqrt(i)*x[,i] - i*dummy + y[,i]*15*sqrt(i)
# y[,i] is a linear function of x[,i] and dummy,
# plus an error term with equation-specific variance
}
data1 <- as.data.frame(cbind(y,x)) # create a data frame of all data (y and
x)
# Create the model equations and moment conditions
ES_g = ES_h <- list() # ES ~ equation system
for(i in 1:N){
ES_g[[i]] <- as.formula(assign(paste0("eq",i), value=paste0("y",i," ~
x",i," + dummy"))) # define linear equations of SUR
ES_h[[i]] <- as.formula(assign(paste0("eq",i), value=paste0(...
2024 Apr 23
1
System GMM yields identical results for any weighting matrix
...y + y[,i]*15*sqrt(i)
> # y[,i] is a linear function of x[,i] and dummy,
> # plus an error term with equation-specific variance
> }
> data1 <- as.data.frame(cbind(y,x)) # create a data frame of all data (y and
> x)
>
> # Create the model equations and moment conditions
> ES_g = ES_h <- list() # ES ~ equation system
> for(i in 1:N){
> ES_g[[i]] <- as.formula(assign(paste0("eq",i), value=paste0("y",i," ~
> x",i," + dummy"))) # define linear equations of SUR
> ES_h[[i]] <- as.formula(assign(paste0("eq"...
2024 Apr 23
0
System GMM fails due to computationally singular system. Why?
...y[,i] <- i + sqrt(i)*x[,i] - i*dummy + y[,i]*15*sqrt(i)
# y[,i] is a linear function of x[,i] and dummy,
# plus an error term with equation-specific variance
}
data1 <- as.data.frame(cbind(y,x)) # create a data frame of all data (y and
x)
# Create the model equations and moment conditions
ES_g = eqSystem_h <- list()
for(i in 1:N){
ES_g[[i]] <- as.formula(assign(paste0("eq",i), value=paste0("y",i," ~
x",i," + dummy"))) # define linear equations of SUR
ES_h[[i]] <- as.formula(assign(paste0("eq",i), value=paste0( "~
x&q...