ivcrc: An Instrumental Variables Estimator for the Correlated Random Coefficients Model

David Benson, Matthew Masten and Alexander Torgovitsky

No 2020-046r1, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We discuss the ivcrc module, which implements an instrumental variables (IV) estimator for the linear correlated random coefficients (CRC) model. The CRC model is a natural generalization of the standard linear IV model that allows for endogenous, multivalued treatments and unobserved heterogeneity in treatment effects. The estimator implemented by ivcrc uses recent semiparametric identification results that allow for flexible functional forms and permit instruments that may be binary, discrete, or continuous. The ivcrc module also allows for the estimation of varying coefficients regressions, which are closely related in structure to the proposed IV estimator. We illustrate use of ivcrc by estimating the returns to education in the National Longitudinal Survey of Young Men.

Keywords: ivregress; Instrumental variables; Correlated random coefficients; Heterogeneous treatment effects; Varying coefficient models; Returns to schooling (search for similar items in EconPapers)
JEL-codes: C14 C26 C51 I26 (search for similar items in EconPapers)
Pages: 29
Date: 2020-06-16, Revised 2022-04-04
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-ore
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: ivcrc: An instrumental-variables estimator for the correlated random-coefficients model (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2020-46

DOI: 10.17016/FEDS.2020.046r1

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