We propose a nonparametric test of the hypothesis of conditional independence between variables of interest based on a generalization of the empirical distribution function. This hypothesis is of interest both for model specification purposes, parametric and semiparametric, and for nonmodel-based testing of economic hypotheses. We allow for both discrete variables and estimated parameters. The asymptotic null distribution of the test statistic is a functional of a Gaussian process. A bootstrap procedure is proposed for calculating the critical values. Our test has power against alternatives at distance n −1/2from the null; this result holding independently of dimension. Monte Carlo simulations provide evidence on size and power.
Authors
Oliver Linton
Pedro Gozalo
Journal article details
- DOI
- 10.1080/07474938.2013.825135
- Publisher
- Taylor & Francis Online
- JEL
- C12, C14, C15, C52
- Issue
- November 2013
Suggested citation
Gozalo, P and Linton, O. (2013). 'Testing Conditional Independence Restrictions' (2013)
More from IFS
Understand this issue
Gender norms, violence and adolescent girls’ trajectories: Evidence from India
24 October 2022
What are the challenges in getting debt on a falling path?
28 June 2024
Election Special: Your questions answered
27 June 2024
Policy analysis
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
Assessing the economic benefits of education: reconciling microeconomic and macroeconomic approaches
This CAYT report discusses the strengths and limitations of several approaches to assessing the effect of education on productivity.
14 March 2013
Misreported schooling, multiple measures and returns to educational qualifications
We provide a number of contributions of policy, practical and methodological interest to the study of the returns to educational qualifications in the presence of misreporting.
1 February 2012
Academic research
Inference for rank-rank regressions
28 May 2024
Understanding Society: minimising selection biases in data collection using mobile apps
2 February 2024
The impact of labour demand shocks when occupational labour supplies are heterogeneous
28 June 2024