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Estimating Two-Sided Logit Models

Bibliographic Data

ID6169732
AuthorsJohn Allen Logan (University of Wisconsin–Madison, corresponding author)
Year1998
Volume28
Issue1
Pages139-173
Publication date1998-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSociological Methodology (JOURNAL)
Journal identifiersISSN: 0081-1750 • E-ISSN: 1467-9531
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1111/0081-1750.00044
OpenAlexW2040015461
LanguageEN
Citations received10
References cited19

Logan (1996a) introduced a new micro-behavioral model of employment opportunity and choice, and a multivariate statistical method based on the micro-behavioral model. This article considers the connection between the behavioral model and the two-sided logit (TSL) statistical method in more detail than the original paper, discussing issues of parameter identification, model constraints, data reduction, and practical estimation. The article compares the EM gradient algorithm used in Logan (1996a) with an accelerated EM gradient algorithm and with a public-domain quasi-Newton algorithm. The latter two algorithms, now incorporated in a single program, greatly enhance the practicality of TSL modeling. Strategies for further development of TSL methods are also considered

Algorithm · Data mining · Domain (mathematical analysis · Econometrics · Estimation theory · Identification (biology · Logistic regression · Logit · Machine learning · Mathematical optimization · Maximum likelihood · Mixed logit · Multivariate statistics · Statistics · Computer Science · Economic and Environmental Valuation · Gender, Labor, and Family Dynamics · Mathematics · Spatial and Panel Data Analysis

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Unique citing works10
Citations per year0,48
Citation span2005 - 2021 (17)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 10

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