Identifying Structural Effects in Nonseparable Systems Using Covariates

Halbert White and Karim Chalak ()

No 734, Boston College Working Papers in Economics from Boston College Department of Economics

Abstract: This paper demonstrates the extensive scope of an alternative to standard instrumental variables methods, namely covariate-based methods, for identifying and estimating effects of interest in general structural systems. As we show, commonly used econometric methods, specifically parametric, semi-parametric, and nonparametric extremum or moment-based methods, can all exploit covariates to estimate well-identified structural e§ects. The systems we consider are general, in that they need not impose linearity, separability, or monotonicity restrictions on the structural relations. We consider effects of multiple causes; these may be binary, categorical, or continuous. For continuous causes, we examine both marginal and non-marginal effects. We analyze effects on aspects of the response distribution generally, designed by explicit or implicit moments or as optimizers (e.g., quantiles). Key for identification is a specific conditional exogeneity relation. We examine what happens in its absence and find that identification generally fails. Nevertheless, local and near identification results hold in its absence, as we show.

Keywords: conditional exogeneity; extremum estimator; identification; method of moments; nonparametric estimation; structural equations. (search for similar items in EconPapers)
JEL-codes: C10 C20 C30 C50 (search for similar items in EconPapers)
Date: 2008-10-16
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Citations: View citations in EconPapers (7)

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