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Kotlarski's lemma for dyadic models

Grigory Franguridi, Hyungsik Roger Moon

arXiv 4 Feb 2025 · Econometrics

arXiv:2502.02734 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We show how to identify the distributions of the error components in the two-way dyadic model $y_{ij}=c+\alpha_i+\eta_j+\varepsilon_{ij}$. To this end, we extend the lemma of Kotlarski (1967), mimicking the arguments of Evdokimov and White (2012). We allow the characteristic functions of the error components to have real zeros, as long as they do not overlap with zeros of their first derivatives.

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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
1Evdokimov, Kirill and White, Halbert (2012) Some extensions of a lemma of Kotlarski1.00084100%
2Kotlarski, Ignacy (1967) On characterizing the gamma and the normal distribution0.84333100%
3Andreyanov, Pasha and Caoui, El Hadi (2022) Secret reserve prices by uninformed sellers0.40511100%
4Bonhomme, Stéphane and Robin, Jean-Marc (2010) Generalized non-parametric deconvolution with an application to earnings dynamics0.40511100%
5Bonhomme, Stéphane (2020) Econometric analysis of bipartite networks0.40511100%
6Botosaru, Irene and Sasaki, Yuya (2018) Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics0.40511100%
7Grundl, Serafin and Zhu, Yu (2019) Identification and estimation of risk aversion in first-price auctions with unobserved auction heterogeneity0.40511100%
8Hu, Yingyao and Moffitt, Robert and Sasaki, Yuya (2019) Semiparametric estimation of the canonical permanent-transitory model of earnings dynamics0.40511100%
9Kato, Kengo and Sasaki, Yuya and Ura, Takuya (2021) Robust inference in deconvolution0.40511100%
10Krasnokutskaya, Elena (2011) Identification and estimation of auction models with unobserved heterogeneity0.40511100%

Showing the top 10 of 20 scored citations.