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np (version 0.40-13)

Engel95: 1995 British Family Expenditure Survey

Description

British cross-section data consisting of a random sample taken from the British Family Expenditure Survey for 1995. The households consist of married couples with an employed head-of-household between the ages of 25 and 55 years. There are 1655 household-level observations in total.

Usage

data("Engel95")

Arguments

source

Richard Blundell and Dennis Kristensen

References

Blundell, R. and X. Chen and D. Kristensen (2007), Semi-Nonparametric IV Estimation of Shape-Invariant Engel Curves, Econometrica, 75, 1613-1669. Li, Q. and J.S. Racine (2007), Nonparametric Econometrics: Theory and Practice, Princeton University Press.

Examples

Run this code
## Example - compute nonparametric instrumental regression using
## Landweber-Fridman iteration of Fredholm integral equations of the
## first kind.

## We consider an equation with an endogenous regressor (`z') and an
## instrument (`w'). Let y = phi(z) + u where phi(z) is the function of
## interest. Here E(u|z) is not zero hence the conditional mean E(y|z)
## does not coincide with the function of interest, but if there exists
## an instrument w such that E(u|w) = 0, then we can recover the
## function of interest by solving an ill-posed inverse problem.

data(Engel95)

## Sort on logexp (the endogenous regressor) for plotting purposes

Engel95 <- Engel95[order(Engel95$logexp),] 

attach(Engel95)

model.iv <- npregiv(y=food,z=logexp,w=logwages,method="Landweber-Fridman")
phihat <- model.iv$phihat

## Compute the non-IV regression (i.e. regress y on z)

ghat <- npreg(food~logexp,regtype="ll")

## For the plots, restrict focal attention to the bulk of the data
## (i.e. for the plotting area trim out 1/4 of one percent from each
## tail of y and z)

trim <- 0.0025

plot(logexp,food,
     ylab="Food Budget Share",
     xlab="log(Total Expenditure)",
     xlim=quantile(logexp,c(trim,1-trim)),
     ylim=quantile(food,c(trim,1-trim)),
     main="Nonparametric Instrumental Kernel Regression",
     type="p",
     cex=.5,
     col="lightgrey")

lines(logexp,phihat,col="blue",lwd=2,lty=2)

lines(logexp,fitted(ghat),col="red",lwd=2,lty=4)

legend(quantile(logexp,trim),quantile(food,1-trim),
       c(expression(paste("Nonparametric IV: ",hat(varphi)(logexp))),
         "Nonparametric Regression: E(food | logexp)"),
       lty=c(2,4),
       col=c("blue","red"),
       lwd=c(2,2))

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