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Estimating End-Use Demand: A Bayesian Approach

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  • Bauwens, Luc
  • Fiebig, Denzil G
  • Steel, Mark F J

Abstract

Eliminating negative end-use or appliance-consumption estimates and incorporating direct-metering information into the process of generating these estimates--these are two important aspects of conditional demand analysis that will be the focus of this paper. In both cases, a Bayesian approach seems a natural way of proceeding. What needs to be investigated is whether it is also a viable and effective approach. The authors' application involves the estimation of electrical-appliance consumptions for a sample of Australian households. This application is designed to illustrate the viability of a full Bayesian analysis of the problem.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 12 (1994)
Issue (Month): 2 (April)
Pages: 221-31

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Handle: RePEc:bes:jnlbes:v:12:y:1994:i:2:p:221-31

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Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main

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Cited by:
  1. Brencic, Vera & Young, Denise, 2009. "Time-saving innovations, time allocation, and energy use: Evidence from Canadian households," Ecological Economics, Elsevier, vol. 68(11), pages 2859-2867, September.
  2. Muhammad Akmal & David I. Stern, 2001. "The structure of Australian residential energy demand," Working Papers in Ecological Economics 0101, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
  3. Bodil M. Larsen & Runa Nesbakken, 2003. "How to quantify household electricity end-use consumption," Discussion Papers 346, Research Department of Statistics Norway.
  4. Muhammad Akmal & David I. Stern, 2001. "Residential energy demand in Australia: an application of dynamic OLS," Working Papers in Ecological Economics 0104, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.

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