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Models for truncated counts

Models for truncated counts This paper examines a class of maximum‐likelihood regression estimators for count data from truncated samples. Estimators for the truncated Poisson and negative binomial distributions are illustrated. Simulation results are given to illustrate the magnitude of the bias that may result from the failure to account for overdispersion in truncated samples. An empirical application based upon the number of recreational fishing trips taken by a sample of Alaskan fishermen is provided. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Econometrics Wiley

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References (28)

Publisher
Wiley
Copyright
Copyright © 1991 John Wiley & Sons, Ltd.
ISSN
0883-7252
eISSN
1099-1255
DOI
10.1002/jae.3950060302
Publisher site
See Article on Publisher Site

Abstract

This paper examines a class of maximum‐likelihood regression estimators for count data from truncated samples. Estimators for the truncated Poisson and negative binomial distributions are illustrated. Simulation results are given to illustrate the magnitude of the bias that may result from the failure to account for overdispersion in truncated samples. An empirical application based upon the number of recreational fishing trips taken by a sample of Alaskan fishermen is provided.

Journal

Journal of Applied EconometricsWiley

Published: Jul 1, 1991

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