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Inference based on Kotlarski's Identity

Kengo Kato, Yuya Sasaki, Takuya Ura

arXiv 28 Aug 2018 · Econometrics · 5 citations (OpenAlex)

arXiv:1808.09375 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Kotlarski's identity has been widely used in applied economic research. However, how to conduct inference based on this popular identification approach has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski's identity as a system of linear moment restrictions. The confidence band controls the asymptotic size uniformly over a class of data generating processes, and it is consistent against all fixed alternatives. Simulation studies support our theoretical results.

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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
1Bonhomme, S. and J.-M. Robin (2010) Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics1.00053100%
2Li, T. and Q. Vuong (1998) Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators0.92314679%
3Kotlarski, I (1967) On Characterizing the Gamma and the Normal Distribution0.84333100%
4Rao, B (1992) Identifiability in Stochastic Models: Characterization of Probability Distributions0.84333100%
5Chernozhukov, V., D. Chetverikov, and K. Kato (2018) Inference on causal and structural parameters using many moment inequalities0.7946350%
6Evdokimov, K (2010) Identification and Estimation of a Nonparametric Panel Data Model with Unobserved Heterogeneity, Working Paper0.73732100%
7Li, T (2002) Robust and Consistent Estimation of Nonlinear Errors-in-Variables Models0.73732100%
8Adusumilli, K., T. Otsu, and Y.-J. Whang (2017) Inference on Distribution Functions under Measurement Error, STICERD - Econometrics Paper Series 5940.73732100%
9Bissantz, N., L. Dümbgen, H. Holzmann, and A. Munk (2007) Nonparametric Confidence Bands in Deconvolution Density Estimation0.73732100%
10Chen, X (2007) Large Sample Sieve Estimation of Semi-Nonparametric Models, in0.73732100%

Showing the top 10 of 64 scored citations.