This is the third part of the series on Instrumental Variables. For other parts of the series follow the tag instrumental variables. In this exercise set we will use Generalized Method of Moments (GMM) estimation technique using the examples from part-1 and part-2. Recall that GMM estimation relies on the relevant moment conditions. For OLS […]

# instrumental variables

## Instrumental Variables in R exercises (Part-2)

This is the second part of the series on Instrumental Variables. For other parts of the series follow the tag instrumental variables. In this exercise set we will build on the example from part-1. We will now consider an over-identified case i.e. we have multiple IVs for an endogenous variable. We will also look at […]

## Instrumental Variables in R exercises (Part-2) Solutions

Below are the solutions to these exercises on Instrumental Variables (Part-2). ############### # # # Exercise 1 # # # ############### library(AER) ## Warning: package ‘lmtest’ was built under R version 3.3.3 ## Warning: package ‘zoo’ was built under R version 3.3.3 data("PSID1976") df <- subset(PSID1976, participation=="yes") ############### # # # Exercise 2 # # […]

## Instrumental Variables in R exercises (Part-1)

One of the most frequently encountered issues in econometrics is endogeneity. Consider the simple Ordinary Least Squares (OLS) regression setting in which we model wages as a function of years of schooling (education): One of the main assumption of OLS is that the independent variables are not correlated with the error term. However, this is […]