Identification of a triangular random coefficient model using a correction function

Alyssa Carlson

No 2409, Working Papers from Department of Economics, University of Missouri

Abstract: Previously, identification of triangular random coefficient models required a restriction on the dimension of the first stage heterogeneity or independence assumptions across the different sources of the heterogeneity. This note proposes a new identification strategy that does not rely on either of these restrictions but rather assumes conditional means have a conditional linear projection representation in order to construct “correction functions†to address endogeneity and gain identification of the average partial effect. This identification strategy allows for both continuous and discrete instruments. Finally, the proposed identification method is illustrated in estimating the returns to education.

Keywords: Endogeneity; Control Function; Random Coefficient; Conditional Linear Projection (search for similar items in EconPapers)
JEL-codes: C3 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2024-09
New Economics Papers: this item is included in nep-dcm, nep-inv and nep-ipr
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Related works:
Working Paper: Identification of a triangular random coefficient model using a correction function (2024)
Working Paper: Identification of a triangular random coefficient model using a correction function (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:umc:wpaper:2409

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