Nonparametric Instrumental Variable Estimation in Practice

Michael Cohen, Philip Shaw () and Tao Chen

No 149936, Research Reports from University of Connecticut, Food Marketing Policy Center

Abstract: In this paper we examine the finite sample performance of two estimators one developed by Blundell, Chen, and Kristensen (2007) (BCK) and the other by Gagliardini and Scaillet (2007) (TIR). This paper focuses on the generalization and expansion of these estimators to a full nonparametric specification with multiple regressors. In relation to the classic weak instruments literature, we provide intuition on the examination of instruments relevance when the structural function is assumed to be unknown. Simulations indicate that both estimators perform quite well in higher dimensions. This research also provides insights on the performance of bootstrapped confidence intervals for both estimators. We document that the BCK estimator's coverage probabilities are near their nominal levels even in small samples as long as the sieve order of expansion is restricted. The coverage probability for the TIR estimator's bootstrapped confidence intervals are near their nominal levels even when the order of sieve approximation is large. These results suggest that in small samples the TIR estimator has a much smaller bias then the BCK estimator but its variance is much larger. We provide two empirical examples. One is the classic wage returns to education example and the other looks at the relationship of corruption and GDP to economic growth. Results here suggests that the impact of corruption on growth depends nonlinearly on a countries level of development.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 35
Date: 2008-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ageconsearch.umn.edu/record/149936/files/rr111.pdf (application/pdf)

Related works:
Journal Article: Nonparametric Instrumental Variable Estimation in Practice (2016)
Working Paper: Nonparametric Instrumental Variable Estimation in Practice (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:uconnr:149936

DOI: 10.22004/ag.econ.149936

Access Statistics for this paper

More papers in Research Reports from University of Connecticut, Food Marketing Policy Center Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().