Matsushita, Yukitoshi and Otsu, Taisuke ORCID: 0000-0002-2307-143X (2018) Likelihood inference on semiparametric models: average derivative and treatment effect. Japanese Economic Review, 69 (2). pp. 133-155. ISSN 1352-4739
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Abstract
In the past few decades, much progress has been made in semiparametric modeling and estimation methods for econometric analysis. This paper is concerned with inference (i.e., confidence intervals and hypothesis testing) in semiparametric models. In contrast to the conventional approach based on t-ratios, we advocate likelihood-based inference. In particular, we study two widely applied semiparametric problems, weighted average derivatives and treatment effects, and propose semiparametric empirical likelihood and jackknife empirical likelihood methods. We derive the limiting behavior of these empirical likelihood statistics and investigate their finite sample performance via Monte Carlo simulation. Furthermore, we extend the (delete-1) jackknife empirical likelihood toward the delete-d version with growing d and establish general asymptotic theory. This extension is crucial to deal with non-smooth objects, such as quantiles and quantile average derivatives or treatment effects, due to the well-known inconsistency phenomena of the jackknife under non-smoothness.
Item Type: | Article |
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Official URL: | http://onlinelibrary.wiley.com/journal/10.1111/(IS... |
Additional Information: | © 2017 Japanese Economic Association |
Divisions: | Economics |
Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HB Economic Theory Q Science > Q Science (General) |
JEL classification: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C12 - Hypothesis Testing C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods |
Date Deposited: | 29 Nov 2017 09:57 |
Last Modified: | 01 Nov 2024 05:09 |
Projects: | SNP 615882 |
Funders: | Economic Research Council |
URI: | http://eprints.lse.ac.uk/id/eprint/85870 |
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