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Age-Period-Cohort Models
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Age-Period-Cohort Models : Approaches and Analyses with Aggregate Data

Book Details

Format Paperback / Softback
ISBN-10 0367576082
ISBN-13 9780367576080
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Jun 30th, 2020
Print length 216 Pages
Weight 400 grams
Ksh 9,200.00
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This book presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include constrained estimation, the use of age and/or period and/or cohort characteristics, estimable functions, variance decomposition, and a new technique called the s-constraint approa

Develop a Deep Understanding of the Statistical Issues of APC Analysis



Age–Period–Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include constrained estimation, the use of age and/or period and/or cohort characteristics, estimable functions, variance decomposition, and a new technique called the s-constraint approach.



See How Common Methods Are Related to Each Other





After a general and wide-ranging introductory chapter, the book explains the identification problem from algebraic and geometric perspectives and discusses constrained regression. It then covers important strategies that provide information that does not directly depend on the constraints used to identify the APC model. The final chapter presents a specific empirical example showing that a combination of the approaches can make a compelling case for particular APC effects.



Get Answers to Questions about the Relationships of Ages, Periods, and Cohorts to Important Substantive Variables





This book incorporates several APC approaches into one resource, emphasizing both their geometry and algebra. This integrated presentation helps researchers effectively judge the strengths and weaknesses of the methods, which should lead to better future research and better interpretation of existing research.


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