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A Monte Carlo study of bias corrections for panel probit models

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Alexander, Blair; Breunig, Robert

Description

We examine bias corrections which have been proposed for the fixed effects panel probit model with exogenous regressors, using several different data generating processes to evaluate the performance of the estimators in different situations. We find a best estimator across all cases for coefficient estimates, but when the marginal effects are the quantity of interest no analytical correction is able to outperform the uncorrected maximum-likelihood estimator.

dc.contributor.authorAlexander, Blair
dc.contributor.authorBreunig, Robert
dc.date.accessioned2015-12-07T22:25:11Z
dc.identifier.issn0094-9655
dc.identifier.urihttp://hdl.handle.net/1885/21151
dc.description.abstractWe examine bias corrections which have been proposed for the fixed effects panel probit model with exogenous regressors, using several different data generating processes to evaluate the performance of the estimators in different situations. We find a best estimator across all cases for coefficient estimates, but when the marginal effects are the quantity of interest no analytical correction is able to outperform the uncorrected maximum-likelihood estimator.
dc.publisherTaylor & Francis Group
dc.sourceJournal of Statistical Computation and Simulation
dc.titleA Monte Carlo study of bias corrections for panel probit models
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolumeonline
dc.date.issued2014
local.identifier.absfor140104 - Microeconomic Theory
local.identifier.ariespublicationu5651450xPUB15
local.type.statusPublished Version
local.contributor.affiliationAlexander, Blair, College of Asia and the Pacific, ANU
local.contributor.affiliationBreunig, Robert, College of Asia and the Pacific, ANU
local.description.embargo2037-12-31
local.identifier.doi10.1080/00949655.2014.994516
local.identifier.absseo910208 - Micro Labour Market Issues
dc.date.updated2015-12-07T09:32:57Z
local.identifier.scopusID2-s2.0-84919935859
CollectionsANU Research Publications

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