arbiter
JournalsPricingAccount

Heckman sample-selection estimators under heteroskedasticity

Alyssa Carlson & Wei Zhao

Stata Journal2025https://doi.org/10.1177/1536867x251322971article
AJG 2
Weight
0.41

What the paper says

Abstract. This article provides a practical guide for Stata users on the consequences of heteroskedasticity in sample-selection models. We review the properties of two Heckman sample-selection estimators, full-information maximum likelihood and limited-information maximum likelihood (LIML), under heteroskedasticity. In this case, full-information maximum likelihood is inconsistent, while LIML can be consistent in certain settings. For the LIML estimator under heteroskedasticity, we show that standard Stata commands are unable to produce correct standard errors and instead suggest the community-contributed command gtsheckman (Carlson 2022, Statistical Software Components S459109, Department of Economics, Boston College; 2024, Stata Journal 24: 687–710). Because heteroskedasticity affects the performance of these two estimators, we also offer guidance on how to test for heteroskedasticity and the conditions needed for the LIML estimator to be consistent. The Monte Carlo simulations illustrate that the suggested testing procedures perform well in terms of appropriate size and power.

2 citations

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1177/1536867x251322971

Or copy a formatted citation

@article{alyssa2025,
  title        = {{Heckman sample-selection estimators under heteroskedasticity}},
  author       = {Alyssa Carlson & Wei Zhao},
  journal      = {Stata Journal},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/1536867x251322971},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Heckman sample-selection estimators under heteroskedasticity

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.