How Much Should We Trust Linear Instrumental Variables Estimators? An Application to Family Size and Children's Education

56 Pages Posted: 17 Nov 2009

See all articles by Magne Mogstad

Magne Mogstad

University of Chicago

Matthew Wiswall

University of Wisconsin - Madison - Department of Economics; National Bureau of Economic Research (NBER)

Abstract

Many empirical studies specify outcomes as a linear function of endogenous regressors when conducting instrumental variable (IV) estimation. We show that tests for treatment effects, selection bias, and treatment effect heterogeneity are biased if the true relationship is non-linear. These results motivate a re-examination of recent evidence suggesting no causal effect of family size on children's education. Following common practice, a linear IV estimator has been used, assuming constant marginal effects of additional children across family sizes. We find that the conclusion of no effect of family size is an artifact of the linear specification, which masks substantial marginal family size effects.

Keywords: instrumental variables, variable treatment intensity, treatment effect heterogeneity, selection bias, quantity-quality, family size, child outcome

JEL Classification: C31, C14, J13

Suggested Citation

Mogstad, Magne and Wiswall, Matthew, How Much Should We Trust Linear Instrumental Variables Estimators? An Application to Family Size and Children's Education. IZA Discussion Paper No. 4562, Available at SSRN: https://ssrn.com/abstract=1506314 or http://dx.doi.org/10.2139/ssrn.1506314

Magne Mogstad (Contact Author)

University of Chicago ( email )

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Matthew Wiswall

University of Wisconsin - Madison - Department of Economics ( email )

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National Bureau of Economic Research (NBER) ( email )

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