Instrumental Variables Regressions with Honestly Uncertain Exclusion Restrictions

42 Pages Posted: 20 Apr 2016  

Aart Kraay

World Bank - Development Research Group (DECRG)

Date Written: May 1, 2008


The validity of instrumental variables (IV) regression models depends crucially on fundamentally untestable exclusion restrictions. Typically exclusion restrictions are assumed to hold exactly in the relevant population, yet in many empirical applications there are reasonable prior grounds to doubt their literal truth. In this paper I show how to incorporate prior uncertainty about the validity of the exclusion restriction into linear IV models, and explore the consequences for inference. In particular I provide a mapping from prior uncertainty about the exclusion restriction into increased uncertainty about parameters of interest. Moderate prior uncertainty about exclusion restrictions can lead to a substantial loss of precision in estimates of structural parameters. This loss of precision is relatively more important in situations where IV estimates appear to be more precise, for example in larger samples or with stronger instruments. The author illustrates these points using several prominent recent empirical papers that use linear IV models.

Keywords: Economic Theory & Research, Statistical & Mathematical Sciences, Currencies and Exchange Rates, Econometrics, Access to Finance

Suggested Citation

Kraay, Aart, Instrumental Variables Regressions with Honestly Uncertain Exclusion Restrictions (May 1, 2008). World Bank Policy Research Working Paper Series, Vol. , pp. -, 2008. Available at SSRN:

Aart Kraay (Contact Author)

World Bank - Development Research Group (DECRG) ( email )

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Washington, DC 20433
United States
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