Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/314131 
Authors: 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Applied Economics [ISSN:] 1667-6726 [Volume:] 24 [Issue:] 1 [Year:] 2021 [Pages:] 297-317
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
The exact linear dependency among age, period and birth cohort makes it impossible to recover the true parameters of Age-Period-Cohort (APC) models. We then propose to extract reliable information from APC models via the Shapley decomposition, a model-agnostic procedure from game theory that allows to pin down the most likely contribution of each regressor in explaining the variance of the depen- dent variable. The rationale is that the predicted values of APC models are estimable and the allocation of the R2 to the APC regressors - interpreted here as the APC "effects" - satisfies desirable properties and produces robust estimates, in that complementing existing methods. We apply the method to the U.S. unemployment rate.
Subjects: 
Shapley value
estimability
age-period-cohort model
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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