Bayesian Analysis of Demand Under Block Rate Pricing

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 schedul...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Miyawaki, Koji (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:JSS Research Series in Statistics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Bayesian Analysis of Demand Under Block Rate Pricing  |h [electronic resource] /  |c by Koji Miyawaki. 
250 |a 1st ed. 2019. 
264 1 |a Singapore :  |b Springer Singapore :  |b Imprint: Springer,  |c 2019. 
300 |a IX, 112 p. 33 illus., 11 illus. in color.  |b online resource. 
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490 1 |a JSS Research Series in Statistics,  |x 2364-0057 
505 0 |a 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. 
520 |a 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 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. 
650 0 |a Statistics . 
650 0 |a Financial engineering. 
650 0 |a Economic policy. 
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650 2 4 |a Statistical Theory and Methods.  |0 http://scigraph.springernature.com/things/product-market-codes/S11001 
650 2 4 |a Bayesian Inference.  |0 http://scigraph.springernature.com/things/product-market-codes/S18000 
650 2 4 |a Financial Engineering.  |0 http://scigraph.springernature.com/things/product-market-codes/612020 
650 2 4 |a R & D/Technology Policy.  |0 http://scigraph.springernature.com/things/product-market-codes/W43000 
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