:: Volume 13, Issue 55 (Winter 1396 2018) ::
QEER 2018, 13(55): 133-159 Back to browse issues page
Dynamic efficiency in the regulation of electricity distribution companies (Bayesian Approach)
Farhad Khodadad kashi1 , Mohamad sadegh Ghazi zadeh2 , Mohamad Oshani *3
1- Payame noor university
2- Niroo Research Instute
3- Payame noor university , Oshani.ff@gmail.com
Abstract:   (6264 Views)

Electricity is one of the most important infrastructure of the country. After the successful experience of industrialized countries for separate different parts and privatization  in electricity industry, Iran since 1382 has begun to privatize the electricity industry. The electricity distribution sector is natural monopoly and, according to economic theory must operate under regulation for quantity of supply, price and quality to protect social welfare. There are various methods for regulation such as rate of return and incentive regulation, in many of these methods foucus on efficiency and productivity of firms. But the conventional static efficiency methods mainly reflecting short-run performance, and only show a close view of the long-run equilibrium path. When componis investment, the behavior of short-term factors that affecting the company may not be adjusted immediately, so short-run inefficiency will be transferred to subsequent periods. This effect caused by the the adjustment costs of capital and production capacity and in short run reduce efficiency in firms and should be considered in the regulation. In this paper, the dynamic efficiency of 39 electricity distribution companies during the period 2009-2015 was calculated using distance function. To estimate the the posterior distribution of model parameters, the simulation based on Markov chain Monte Carlo (MCMC) was used. The results show that environmental factors affect the efficiency in firms. The industry average efficiency increased from 67% to 70% and consistency for inefficiency was 92% during the period.

Keywords: dynamic efficiency, Monte Carlo simulation, Bayesian maximum likelihood estimation, power distribution, market regulation
Full-Text [PDF 443 kb]   (2424 Downloads)    
Type of Study: paper | Subject: E.Economic
Received: 2017/05/21 | Accepted: 2017/09/17 | Published: 2018/03/19 | ePublished: 2018/03/19


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Volume 13, Issue 55 (Winter 1396 2018) Back to browse issues page