Arbeitspapier

Estimating interdependence across space, time and outcomes in binary choice models using pseudo maximum likelihood estimators

Binary outcome models are frequently used in Political Science. However, such models have proven particularly dicult in dealing with interdependent data structures, including spatial autocorrelation, temporal autocorrelation, as well as simultaneity arising from endogenous binary regressors. In each of these cases, the primary source of the estimation challenge is the fact that jointly determined error terms in the reduced-form specication are analytically intractable due to a high-dimensional integral. To deal with this problem, simulation approaches have been proposed, but these are computationally intensive and impractical for datasets with thousands of observations. As a way forward, in this paper we demonstrate how to reduce the computational burder signicantly by (i) introducing analytically tractable pseudo maximum likelihoodestimators for latent binary choice models that exhibit interdependence across space, time and/or outcomes, and by (ii) proposing an implementation strategy that increases computational eciency considerably. Monte-Carlo experiments demonstrate that our estimators perform similarly to existing alternatives in terms of error, but require only a fraction of the computational cost.

Language
Englisch

Bibliographic citation
Series: WWZ Working Paper ; No. 2018/11

Classification
Wirtschaft

Event
Geistige Schöpfung
(who)
Wucherpfennig, Julian
Kachi, Aya
Bormann, Nils-Christian
Hunziker, Philipp
Event
Veröffentlichung
(who)
University of Basel, Center of Business and Economics (WWZ)
(where)
Basel
(when)
2018

DOI
doi:10.5451/unibas-ep63425
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Wucherpfennig, Julian
  • Kachi, Aya
  • Bormann, Nils-Christian
  • Hunziker, Philipp
  • University of Basel, Center of Business and Economics (WWZ)

Time of origin

  • 2018

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