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pro vyhledávání: '"Yap, Luther"'
Autor:
Yap, Luther
This paper considers inference in a linear instrumental variable regression model with many potentially weak instruments and heterogeneous treatment effects. I first show that existing test procedures, including those that are robust to only either w
Externí odkaz:
http://arxiv.org/abs/2408.11193
Autor:
Dorn, Jacob, Yap, Luther
We propose a novel sensitivity analysis framework for linear estimators with identification failures that can be viewed as seeing the wrong outcome distribution. Our approach measures the degree of identification failure through the change in measure
Externí odkaz:
http://arxiv.org/abs/2309.06305
Autor:
Yap, Luther
This paper extends the design-based framework to settings with multi-way cluster dependence, and shows how multi-way clustering can be justified when clustered assignment and clustered sampling occurs on different dimensions, or when either sampling
Externí odkaz:
http://arxiv.org/abs/2309.01658
Autor:
Yap, Luther
This paper proves a new central limit theorem for a sample that exhibits two-way dependence and heterogeneity across clusters. Statistical inference for situations with both two-way dependence and cluster heterogeneity has thus far been an open issue
Externí odkaz:
http://arxiv.org/abs/2301.03805
Publikováno v:
NBER Working Papers; Nov2023, Issue 31821-31910, p1-42, 43p
Autor:
Yap, Luther
This paper proves a new central limit theorem for a sample that exhibits multi-way dependence and heterogeneity across clusters. Statistical inference for situations where there is both multi-way dependence and cluster heterogeneity has thus far been
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64bff21b971a49ef9e3142d102960fae