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Structural econometric modeling in industrial organization and quantitative marketing : theory and applications
Author
Title
Structural econometric modeling in industrial organization and quantitative marketing : theory and applications / Ali Hortaçsu and Joonhwi Joo.
ISBN
9780691251004
0691251002
9780691243467
0691243468
Publication
Princeton : Princeton University Press, [2023]
Physical Description
1 online resource.
Local Notes
Access is available to the Yale community.
Notes
Electronic reproduction. Berlin Available via World Wide Web.
Description based on online resource; title from digital title page (viewed on November 03, 2023).
Access and use
Access restricted by licensing agreement.
Other formats
Print version: Hortaçsu, Ali. Structural econometric modeling in industrial organization and quantitative marketing Princeton : Princeton University Press, [2023]
Format
Books / Online
Language
English
Added to Catalog
November 06, 2023
Bibliography
Includes bibliographical references and index.
Contents
Cover
Contents
Preface
1. Introduction: Structural Econometric Modeling
1.1 Model
1.1.1 Scientific Model and Economic Model
1.1.2 Predictive Model and Causal Model
1.2 Econometrics
1.3 Structure
1.4 Debate around the Structural Econometric Modeling Approach
1.5 Outline of This Book
2. Static and Dynamic Discrete Choice
2.1 Binary Choice
2.1.1 Motivation: Linear Probability Model
2.1.2 Binary Logit and Binary Probit Model
2.1.3 Marginal Effects
2.2 Multiple Choice: Random Utility Maximization Framework
2.2.1 Preliminary Results: Type I Extreme Value Distribution and Its Properties
2.2.2 The Simple Logit Model
2.2.3 Independence of Irrelevant Alternatives and the Nested Logit Model
2.2.4 Discussion
2.3 Single-Agent Dynamic Discrete Choice
2.3.1 Full-Solution Method with Fixed-Point Iteration
2.3.2 Estimation with Conditional Choice Probability Inversion
2.3.3 Nested Pseudo-Likelihood Estimation
2.3.4 Extension to Incorporate Unobserved State Variables
2.3.5 (Non)-identification of the Discount Factor
3. Demand Estimation Using Market-Level Data
3.1 Product-Space Approach
3.1.1 Linear and Log-Linear Demand Model
3.1.2 The Almost Ideal Demand System
3.1.3 Further Discussion of the Product-Space Approach
3.2 Characteristics-Space Approach I: Static Logit Demand Models
3.2.1 Microfoundation: Discrete-Choice Random Utility Maximization
3.2.2 Logit Demand Models with Aggregate Market Data
3.2.3 Further Discussion of the Static Logit Demand Models
3.3 Characteristics-Space Approach II: Extensions of the Static Logit Demand Models
3.3.1 Accommodating Zero Market Shares
3.3.2 Characteristics-Space Approach without Random Utility Shocks
4. Estimation of Discrete-Game Models
4.1 Estimation of Discrete-Game Models with Cross-Sectional Data
4.1.1 Static Discrete Games with Complete Information
4.1.2 Static Discrete Games with Incomplete Information
4.1.3 Further Discussion of the Estimation of Game Models with Cross-Sectional Data
4.2 Estimation of Dynamic Discrete-Game Models
4.2.1 Industry Dynamics in an Oligopolistic Market and the Markov Perfect Equilibrium
4.2.2 Estimation Frameworks of Dynamic Discrete Games
4.2.3 Further Issues and Discussion of Dynamic Game Models Estimation
5. Empirical Frameworks of Consumer Search
5.1 Utility Specification and Some Preliminary Results
5.1.1 Utility Specification in Consumer Search Models
5.1.2 Some Preliminary Results on Stochastic Dominance
5.2 Classical Search-Theoretic Models: Sequential Search and Simultaneous Search
5.2.1 Sequential Search
5.2.2 Simultaneous Search
5.3 Price Dispersion in the Market Equilibrium and Search Cost Identification with Price Data
Subjects
Also listed under
Walter de Gruyter & Co.
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