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researcher

J. Gu

15 papers hereh-index 16752 citations44 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author8
  • middle author5
  • last author1

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • econ.EM8
  • stat.ME4
  • stat.ML2
  • math.ST1
same name
  • J. Gu — 21 papers, h 45
  • J. Gu — 12 papers, h 17
  • J. Gu — 10 papers, h 0
  • J. Gu — 9 papers, h 22
  • J. Gu — 7 papers, h 8
  • J. Gu — 7 papers, h 45

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132026
most citedLearning Large-Scale Bayesian Networks with the sparsebn Package

46 citations · 100 across the 14 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

econ.EM2018★ 1 cited

Nonparametric maximum likelihood methods for binary response models with random coefficients

Jiaying Gu, Roger Koenker

Single index linear models for binary response with random coefficients have been extensively employed in many econometric settings under various parametric specifications of the d…

econ.EM2018

On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects

Antonio F. Galvao, Jiaying Gu, Stanislav Volgushev

Nonlinear panel data models with fixed individual effects provide an important set of tools for describing microeconometric data. In a large class of such models (including probit,…

econ.EM2018

Sufficient Statistics for Unobserved Heterogeneity in Structural Dynamic Logit Models

Victor Aguirregabiria, Jiaying Gu, Yao Luo

We study the identification and estimation of structural parameters in dynamic panel data logit models where decisions are forward-looking and the joint distribution of unobserved…

econ.EM2018★ 3 cited

Panel Data Quantile Regression with Grouped Fixed Effects

Jiaying Gu, Stanislav Volgushev

This paper introduces estimation methods for grouped latent heterogeneity in panel data quantile regression. We assume that the observed individuals come from a heterogeneous popul…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.