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May 1, 2011 20:26
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## ----------------------------------- ## | |
## A homegrown IV regression command ## | |
## that handles the case where there ## | |
## is one endogenous variable and many ## | |
## (or one) instrument. ## | |
## ## | |
## Disadvantage: The command doesn't ## | |
## handle multiple endogenous vars ## | |
## ## | |
## Advantage: testing for relevance, ## | |
## displaying the first stage and ## | |
## conducting overidentification tests ## | |
## are natural and easy. ## | |
## ----------------------------------- ## | |
ivregress = function(second, first, data){ | |
s.names = all.vars(second) | |
f.names = all.vars(first) | |
data.names = names(data) | |
N = length(data[,1]) | |
all.names = c(s.names,f.names) | |
resp = s.names[1] | |
endog = f.names[1] | |
inst = f.names[-1] | |
explan = s.names[-1] | |
exog = explan[explan!=endog] | |
exog.f = paste(exog,collapse="+") | |
inst.f = paste(inst, collapse="+") | |
RHS = paste(exog.f, inst.f, sep="+") | |
first.form = as.formula( paste(endog, "~", RHS)) | |
first.lm = lm(first.form, data) | |
ftest = linearHypothesis(first.lm, inst, rep(0,length(inst))) | |
x.hat = fitted(first.lm) | |
data2 = cbind(data,x.hat) | |
iname = paste(endog,".hat",sep="") | |
names(data2) = c(names(data), iname) | |
data2.names = names(data2) | |
RHS2 = paste(exog.f,iname,sep="+") | |
second.form = as.formula(paste(resp, "~", RHS2)) | |
second.lm = lm(second.form, data2) | |
Xmat = data2[c(exog,endog)] | |
Xmat2 = data2[c(exog,iname)] | |
z = summary(second.lm) | |
X = as.matrix(cbind(1,Xmat)) | |
X2 = as.matrix(cbind(1,Xmat2)) | |
Y = data[resp] | |
fit = X%*%second.lm$coefficients | |
res = Y - fit | |
## Tests for overidentifying restrictions ## | |
data3 = cbind(data2, res) | |
names(data3) = c(names(data2), "res") | |
## J test | |
J.test = as.data.frame(matrix(c(1,2),nrow=1)) | |
names(J.test) = c("J.stat","P[J > J.stat ]") | |
## Sargan's Test | |
S.test = as.data.frame(matrix(c(1,2),nrow=1)) | |
names(S.test) = c("S.stat","P[S > S.stat ]") | |
if(length(inst)>1){ | |
J.form = as.formula(paste("res", "~", RHS)) | |
J.lm = lm(J.form, data3) | |
f.test = linearHypothesis(J.lm,inst, rep(0,length(inst))) | |
J.stat = length(inst)*f.test$F[2] | |
S.stat = N*summary(J.lm)$r.squared | |
} | |
J.test[1,1] = J.stat | |
J.test[1,2] = 1-pchisq(J.stat, length(inst)-1) | |
S.test[1,1] = S.stat | |
S.test[1,2] = 1-pchisq(S.stat, length(inst)-1) | |
xPx = t(X2)%*%X2 | |
xPx.inv = solve(xPx) | |
z$cov.unscaled = xPx.inv | |
z$residuals = res | |
z$sigma = sqrt(mean(res^2)) | |
varcovmat = z$cov.unscaled*z$sigma | |
coef = z$coefficients[,1] | |
IV.SE = z$sigma*sqrt(diag(xPx.inv)) | |
t.iv = coef/IV.SE | |
p.val = 2*(1-pnorm(abs(t.iv))) | |
z$coefficients[,2] = IV.SE | |
z$coefficients[,3] = t.iv | |
z$coefficients[,4] = p.val | |
result = list(summary(first.lm),z,ftest,J.test, S.test) | |
names(result) = c("first", "second", "ftest", "Jtest", "Sargan") | |
print("IV object successfully created. Use sum.iv() on object") | |
print("to learn about your 2SLS Regression") | |
return(invisible(result)) | |
} | |
sum.iv = function(reg.iv, first=FALSE, | |
second=TRUE, ftest=FALSE, overid=FALSE) { | |
x= rep(0,5) | |
if(first==TRUE) x[1] = 1 | |
if(second==TRUE) x[2]= 2 | |
if(ftest==TRUE) x[3]= 3 | |
if(overid==TRUE) x[4:5] = 4:5 | |
print(reg.iv[x]) | |
} |
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Hi! How to add interaction term in equations. I make x1:x2 but this don't run. I need help.
Thanks.