Instrumental regression techniques have played a key role in both the theory and practice of econometrics. There is a growing literature on the nonparametric treatment of this topic. The basic framework involves a response variable denoted Y and a vector of explanatory variables denoted Z. The variables in Z can be endogenous or exogenous and the relationship of interest is given by Y = φ(Z) + U where φ(·) is the function of interest but will not, in the present setting, coincide with the conditional expectation function E(Y|Z) hence requires special treatment (the exception being when all variables contained in Z are in fact exogenous). This talk outlines recent advances in nonparametric instrumental regression methods and discuss potential application in the health arena.
￼￼￼￼￼￼￼Recent Advances in Nonparametric Instrumental Regression (.pdf file)
By: Jeffrey S. Racine (McMaster University)
2014 Annual Health Econometrics Workshop (AHEW)
R code to replicate examples in slides is available for download. Users are required to:
a) Install R (if not already installed)
b) install the np package via the R command install.packages (“np”)
Note: Code is numerically intensive and can take 1/2 an hour on a modern desktop/laptop.
R Code for Slides (.zip file)