Arbeitspapier
Modelling zero-inflated count data when exposure varies: With an application to sick leave
This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a new zero-inflated count data model that is based on two homogeneous Poisson processes and accounts for exposure time in a theory consistent way. The new model is used in an application to the effect of insurance generosity on the number of absent days.
- Language
-
Englisch
- Bibliographic citation
-
Series: Working Paper ; No. 61
- Classification
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Wirtschaft
Time Allocation, Work Behavior, and Employment Determination: Other
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
- Subject
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exposure
Poisson regression
complementary log-log link
Zähldatenmodell
Stochastischer Prozess
Regression
Theorie
- Event
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Geistige Schöpfung
- (who)
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Baetschmann, Gregori
Winkelmann, Rainer
- Event
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Veröffentlichung
- (who)
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University of Zurich, Department of Economics
- (where)
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Zurich
- (when)
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2012
- DOI
-
doi:10.5167/uzh-59265
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
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
- Baetschmann, Gregori
- Winkelmann, Rainer
- University of Zurich, Department of Economics
Time of origin
- 2012
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Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals
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Robust estimation of zero-inflated count models
A comparison of zero-inflated and hurdle models for modeling zero-inflated count data
Unemployment, Sick Leave and Health
On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
Effect of Partial Sick Leave on Sick Leave Duration in Employees with Musculoskeletal Disorders
Sick leave patterns in common musculoskeletal disorders – a study of doctor prescribed sick leave
Being on Sick Leave: Possible Explanations for Differences of Sick-leave Days Across Countries Privatization
Multiple inflated negative binomial regression for correlated multivariate count data
The Market for Paid Sick Leave
Profiling the US Sick Leave Landscape
Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals
Intergenerational transmission of long-term sick leave
Robust estimation of zero-inflated count models
A comparison of zero-inflated and hurdle models for modeling zero-inflated count data
Unemployment, Sick Leave and Health
On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
Effect of Partial Sick Leave on Sick Leave Duration in Employees with Musculoskeletal Disorders
Sick leave patterns in common musculoskeletal disorders – a study of doctor prescribed sick leave
Being on Sick Leave: Possible Explanations for Differences of Sick-leave Days Across Countries Privatization
Multiple inflated negative binomial regression for correlated multivariate count data
The Market for Paid Sick Leave
Profiling the US Sick Leave Landscape
Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals