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Average Marginal Effects in One-Step Partially Linear Instrumental Regressions

Lucas Girard, Elia Lapenta

arXiv 13 Apr 2026 · Econometrics

arXiv:2604.11393 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose a novel procedure for estimating and conducting inference on average marginal effects in partially linear instrumental regressions using Reproducing Kernel Hilbert Space methods. Our procedure relies on a single regularization parameter. We obtain the consistency and asymptotic normality of our estimator. Since the variance of the limiting distribution has a complex analytical form, we propose a Bayesian bootstrap method to conduct inference and establish its validity. Our procedure is easy to implement and exhibits good finite-sample performance in simulations. Three empirical applications illustrate its implementation on real data, showing that it yields economically meaningful results.

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47
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133
in-text mentions
47
distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Florens, J.-P., Johannes, J., and Van Bellegem, S (2012) Instrumental regression in partially linear models1.00063100%
2Steinwart, I. and Christmann, A (2008) Support vector machines0.9568488%
3Sokullu, S (2016) A semi-parametric analysis of two-sided markets: An application to the local daily newspapers in the usa0.874112100%
4Frankel, J. A. and Romer, D. H (1999) Does trade cause growth?0.87472100%
5Angrist, J. D. and Lavy, V (1999) Using maimonides' rule to estimate the effect of class size on scholastic achievement0.87452100%
6Wainwright, M. J (2019) High-dimensional statistics: A non-asymptotic viewpoint0.7948450%
7Ai, C. and Chen, X (2007) Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables0.73732100%
8Berlinet, A. and Thomas-Agnan, C (2011) Reproducing kernel Hilbert spaces in probability and statistics0.73732100%
9Beyhum, J., Lapenta, E., and Lavergne, P (2024) One-step smoothing splines instrumental regression self0.7218438%
10Kreyszig, E (1991) Introductory functional analysis with applications0.6597329%

Showing the top 10 of 47 scored citations.