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A dynamic hurdle model for zeroinflated panel count data created by Filippo Belloc , Mauro Bernardi , Antonello Maruotti and Lea Petrella

By: Contributor(s): Material type: TextTextSeries: Applied economics letters ; Volume 20, number 9New York: Taylor and Francis, 2013Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 13504851
Subject(s): LOC classification:
  • HB1.A666 APP
Online resources: Abstract: This article proposes an approximate conditional dynamic finite mixture hurdle model for panel count data with excess of zeros and endogenous initial conditions. We provide parameter estimates by using the Expectation-Maximization (EM) algorithm in a Nonparametric Maximum Likelihood (NPML) framework. An application to a unique data set on traffic violation counts of a subpopulation of Italian drivers is given.
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Holdings
Item type Current library Call number Vol info Copy number Status Notes Date due Barcode
Journal Article Journal Article Main Library - Special Collections HB1.A666 APP (Browse shelf(Opens below)) Vol. 20, no 9 (pages 837-841) SP17975 Not for loan For In House Use Only

This article proposes an approximate conditional dynamic finite mixture hurdle model for panel count data with excess of zeros and endogenous initial conditions. We provide parameter estimates by using the Expectation-Maximization (EM) algorithm in a Nonparametric Maximum Likelihood (NPML) framework. An application to a unique data set on traffic violation counts of a subpopulation of Italian drivers is given.

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