Engel95 {npiv} | R Documentation |
1995 British Family Expenditure Survey
Description
This dataset is based on a sample taken from the British Family Expenditure Survey for 1995. It includes households consisting of married or cohabiting couples with an employed head of household, aged between 25 and 55 years, and with at most two children. There are 1655 household-level observations in total.
Usage
data("Engel95")
Format
A data frame with 10 columns, and 1655 rows.
- food
expenditure share on food, of type
numeric
- catering
expenditure share on catering, of type
numeric
- alcohol
expenditure share on alcohol, of type
numeric
- fuel
expenditure share on fuel, of type
numeric
- motor
expenditure share on motor, of type
numeric
- fares
expenditure share on fares, of type
numeric
- leisure
expenditure share on leisure, of type
numeric
- logexp
logarithm of total expenditure, of type
numeric
- logwages
logarithm of total earnings, of type
numeric
- nkids
'0' indicates no children, '1' indicates 1-2 children, of type
numeric
Source
Richard Blundell and Dennis Kristensen
References
Blundell, R., X. Chen and D. Kristensen (2007). “Semi-Nonparametric IV Estimation of Shape-Invariant Engel Curves.” Econometrica, 75(6), 1613-1669. doi:10.1111/j.1468-0262.2007.00808.x
Chen, X. and T. Christensen (2018). “Optimal Sup-norm Rates and Uniform Inference on Nonlinear Functionals of Nonparametric IV Regression.” Quantitative Economics, 9(1), 39-85. doi:10.3982/QE722
Chen, X., T. Christensen and S. Kankanala (2024). “Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities.” Review of Economic Studies, forthcoming. doi:10.1093/restud/rdae025
Examples
## Load data
data("Engel95", package = "npiv")
## Sort on logexp (the regressor) for plotting purposes
Engel95 <- Engel95[order(Engel95$logexp),]
attach(Engel95)
logexp.eval <- seq(4.5,6.5,length=100)
## Estimate the Engel curve for food using logwages as an instrument
food_engel <- npiv(food, logexp, logwages, X.eval = logexp.eval)
## Plot the estimated function and uniform confidence bands
plot(food_engel, showdata = TRUE)