A count data model with endogenous household specific censoring: the number of nights to stay
Empirical EconomicsPublished 4 September 2007
Jörgen Hellström, Jonas Nordström
Citations13
SJR quartileQ1
SJR score0.76
SNIP1.35
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
In this paper a count data regression model accounting for endogenous censoring with household specific censoring thresholds is presented. The presented modelling approach is utilized in an analysis of household choice of total number of nights to spend on monthly recreational trips. The empirical study reveals that the suggested approach is feasible and that accounting for endogenous censoring gives a better fit to the data.
Keywords
Social SciencesMathematicsEconomics, Econometrics and Finance
Journal of EconometricsSpecification and testing of some modified count data models
1,822 Citations1986John Mullahy
These alternatives permit more flexible specification of the data-generating process (dgp) than do familiar count data models, and provide a natural means for modeling data that are over- or underdispersed by the standards of the basic models.
Econometric Analysis of Count Data
961 Citations2003Rainer Winkelmann
Journal of EconometricsEstimating count data models with endogenous switching: Sample selection and endogenous treatment effects
310 Citations1998Joseph V. Terza
American Economic ReviewVerifying the Solution from a Nonlinear Solver: A Case Study
222 Citations2003B. D. McCullough, Hrishikesh D. Vinod
The article was to provide a four-part methodology for verifying the solution from a nonlinear solver: check the gradient, examine the trace, analyze the Hessian, and profile the likelihood, and concluded that the solution found was, at best, a tentative solution.
2004): Health Care Reform and the Number of Doctor Visits - An Econometric Analysis
177 Citations2014Rainer Winkelmann, Rainer Winkelmann
American Journal of Agricultural EconomicsOn‐Site Time in the Demand for Recreation
175 Citations1992Kenneth E. McConnell
American Journal of Agricultural EconomicsThe Dual Structure of Incomplete Demand Systems
138 Citations1989Jeffrey T. LaFrance, W. Michael Hanemann
Econometric Analysis of Count Data
119 Citations2000Rainer Winkelmann
Land EconomicsPossibilities for Including the Opportunity Cost of Time in Recreation Demand Systems
95 Citations1999W. Douglass Shaw, Peter Feather
Economics LettersA Tobit-type estimator for the censored Poisson regression model
84 Citations1985Joseph V. Terza
Journal of Applied EconometricsA bivariate count data model for household tourism demand
84 Citations2005Jörgen Hellström
Empirical EconomicsModeling household fertility decisions: Estimation and testing of censored regression models for count data
57 Citations1995Steven B. Caudill, Franklin G. Mixon
The censored models employed in this study are estimated using panel data collected from the Consumer Expenditure Survey compiled by the Bureau of Labor Statistics and support the fertility hypothesis of Becker and Lewis (1965-70).
American Journal of Agricultural EconomicsSeparability and the Shadow Value of Leisure Time
43 Citations1993Douglas M. Larson
Land EconomicsEndogenous On-Site Time in the Recreation Demand Model
34 Citations1999Matthew Berman, Han Jo Kim
AgEcon Search (University of Minnesota, USA)ENDOGENOUS ON-SITE TIME IN THE RECREATION DEMAND MODEL
21 Citations1999Matthew Berman, Han Jo Kim +2 more
Australian & New Zealand Journal of StatisticsTheory & Methods: Fisher’s Information on the Correlation Coefficient in Bivariate Logistic Models
21 Citations1999Murray Smith, Peter G. Moffatt
RePEc: Research Papers in EconomicsDemand and Welfare Effects in Recreational Travel Models: A Bivariate Count Data Approach
1 Citations2005Jörgen Hellström, Jonas Nordström
