Downloads
CWP551818.pdf
PDF | 625.76 KB
Control variables provide an important means of controlling for endogeneity in econometric models with nonseparable and/or multidimensional heterogeneity. We allow for discrete instruments, giving identication results under a variety of restrictions on the way the endogenous variable and the control variables affect the outcome. We consider many structural objects of interest, such as average or quantile treatment effects. We illustrate our results with an empirical application to Engel curve estimation.
Authors
Whitney K. Newey
Working Paper details
- DOI
- 10.1920/wp.cem.2018.5518
- Publisher
- The IFS
Suggested citation
Newey, W. (2018). Control variables, discrete instruments, and identification of structural functions. London: The IFS. Available at: https://ifs.org.uk/publications/control-variables-discrete-instruments-and-identification-structural-functions (accessed: 25 April 2024).
More from IFS
Understand this issue
Gender norms, violence and adolescent girls’ trajectories: Evidence from India
24 October 2022
Public investment: what you need to know
25 April 2024
The £600 billion problem awaiting the next government
25 April 2024
Policy analysis
IFS Deputy Director Carl Emmerson appointed to the UK Statistics Authority Methodological Assurance Review Panel
14 April 2023
ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models
We develop novel methods for estimation and filtering of continuous-time models with stochastic volatility and jumps using so-called Approximate Bayesian Compu- tation which build likelihoods based on limited information.
12 August 2014
Is there really an NHS productivity crisis?
17 November 2023
Academic research
Sample composition and representativeness on Understanding Society
2 February 2024
Understanding Society: minimising selection biases in data collection using mobile apps
2 February 2024
Robust analysis of short panels
8 January 2024