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Record Nr. |
UNINA9910364956303321 |
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Autore |
Miyawaki Koji |
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Titolo |
Bayesian Analysis of Demand Under Block Rate Pricing / / by Koji Miyawaki |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (120 pages) |
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Collana |
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JSS Research Series in Statistics, , 2364-0057 |
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Disciplina |
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Soggetti |
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Statistics |
Financial engineering |
Economic policy |
Statistics for Business, Management, Economics, Finance, Insurance |
Statistical Theory and Methods |
Bayesian Inference |
Financial Engineering |
R & D/Technology Policy |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1. Introduction -- 2. Demand under Increasing Block Rate Pricing -- 3. Demand under Decreasing Block Rate Pricing -- 4. Extensions to Panel Data -- 5. Extensions to Areal Data -- 6. Block Normal Simulator. |
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Sommario/riassunto |
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This book focuses on the structural analysis of demand under block rate pricing, a type of nonlinear pricing used mainly in public utility services. In this price system, consumers are presented with several unit prices, which makes a naive analysis biased. However, the response to the price schedule is often of interest in economics and plays an important role in policymaking. To address this issue, the book adopts a structural approach, referred to as the discrete/continuous choice approach in the literature, to develop corresponding statistical models for analysis.The resulting models are extensions of the Tobit model, a well-known statistical model in econometrics, and their hierarchical structure fits well in Bayesian methodology. Thus, the book takes the Bayesian approach and develops the Markov chain Monte Carlo method to conduct statistical |
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inferences. The methodology derived is then applied to real-world datasets, microdata collected in Tokyo and the neighboring Chiba Prefecture, as a useful empirical analysis for prediction as well as policymaking. |
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