Captive Power, Market Access and Macroeconomic Performance: Reforming the Bangladesh Electricity Sector

Amin, S.; Jamasb, T.; Llorca, M.; Marsiliani, L.; Renström, T.I.; Sarkar, A.

Abstract

Integrating the captive capacity with the on-grid supply has been advocated as a way to improve resource utilization in the electricity market in developing and emerging countries. Despite many countries granting Captive Power Plants (CPPs) access to the grid, integration may still be hindered by other barriers to entry. In Bangladesh, CPPs are required to sell their electricity surplus, but there is no evidence of trading with the national grid, mostly due to high connectivity costs. In this paper we develop and estimate a fit-for purpose Dynamic Stochastic General Equilibrium (DSGE) model to examine the effects of the Bangladeshi CPPs connecting to the national grid and selling their surplus at regulated prices. The model parameters are set through a combination of calibration and Bayesian estimation. We find that if CPPs are connected to the national grid, steady-state industrial output, GDP, and household consumption decrease due to pre-existing energy price distortions. These results support the second-best theory, which implies that merely connecting the CPPs to the national grid without firstly removing market distortions can lead to economically inefficient outcomes. Instead, government should first consider alternative reforms such as phasing out subsidised tariffs and enabling a competitive market environment.

Citation

Amin, S., Jamasb, T., Llorca, M., Marsiliani, L., Renström, T., & Sarkar, A. (2021). Captive Power, Market Access and Macroeconomic Performance: Reforming the Bangladesh Electricity Sector. Energy Economics, 102, Article 105468. https://doi.org/10.1016/j.eneco.2021.105468

• Journal Article Type: Article
• Acceptance Date: Jul 12, 2021
• Online Publication Date: Jul 27, 2021
• Publication Date: 2021-10
• Deposit Date: Aug 2, 2021
• Publicly Available Date: Jul 28, 2023
• Journal: Energy Economics
• Print ISSN: 0140-9883
• Electronic ISSN: 1873-6181
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 102
• Article Number: 105468
• DOI: https://doi.org/10.1016/j.eneco.2021.105468
• Public URL: https://durham-repository.worktribe.com/output/1244559