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

Magne Mogstad and Matthew Wiswall ()

No 4562, IZA Discussion Papers from Institute of Labor Economics (IZA)

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 (search for similar items in EconPapers)
JEL-codes: C14 C31 J13 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2009-11
New Economics Papers: this item is included in nep-ecm and nep-edu
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Citations: View citations in EconPapers (4)

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Related works:
Working Paper: What Linear Estimators Miss: Re-Examining the Effects of Family Income on Child Outcomes (2010)
Working Paper: Linearity in Instrumental Variables Estimation: Problems and Solutions (2010)
Working Paper: How Linear Models Can Mask Non-Linear Causal Relationships. An Application to Family Size and Children's Education (2009)
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