Abstract
Vietnam’s electricity consumption has increased more than 20 times over the last 3 decades. As a consequence of the low energy price policy, the demand for electricity in both the residential and industrial sectors has risen at twice the rate of annual economic growth. Thus, there is an urgent need to characterize the properties of this demand and its determinants. This study presents a first household-level estimate of the demand for residential electricity in Vietnam using a 2015 World Bank household registration survey. Estimating a demand function with instrumental variables to address the simultaneity of price and quantity demanded due to an increasing-block-rate pricing policy, we find that the demand for electricity is almost unitarily elastic to average price and even more so to marginal price. Both income and substitution elasticities are low but positive, indicating that electricity is a necessity and that there is limited substitutability between electricity and other sources of energy. This finding implies that pricing instruments could be very effective for demand side management in Vietnam.
Similar content being viewed by others
Notes
In a simplified framework of one endogenous variable X and one instrument Z, the limiting distribution of the instrumental variable estimator is:
$$\begin{aligned} {\text {plim}} \hat{\beta }_{IV} = \beta + \frac{{\text {corr}}(Z,u)}{{\text {corr}}(Z,X)}\cdot \frac{\sigma _u}{\sigma _X}. \end{aligned}$$A weak correlation between the endogenous variable and the instrument would result in a large bias, especially in a small sample, even if the exclusion condition is satisfied (Sovey and Green 2011).
According to the Government of Vietnam (2009), a commune must have a population of 4000 or more, with an average population density of 2000 people/km\(^2\) or higher, and the ratio of non-agricultural labor must be at least 65% of the total labor force to obtain type V urban status, which is the lowest classification in the five urban levels. Additionally, there are vague administrative requirements, such as the commune must have an appropriate planning and a clean production slate.
References
Angrist JD, Krueger AB (2001) Instrumental variables and the search for identification: from supply and demand to natural experiments. J Econ Perspect 15(4):69–85
Asian Development Bank (2016) Vietnam Energy Sector Assessment, Strategy, and Road Map. Metro Manila, Philippines (ISBN 978-92-9257-312-6)
Auffhammer M, Rubin E (2018) Natural gas price elasticities and optimal cost recovery under consumer heterogeneity: evidence from 300 million natural gas bills. Haas Working Paper 287, University of California at Berkeley
Borenstein S (2009) To what electricity price do consumers respond? Residential demand elasticity under increasing-block pricing. http://faculty.haas.berkeley.edu/borenste/download/NBER_SI_2009.pdf
Burke P, Abayasekara A (2018) The price elasticity of electricity demand in the United States: a three-dimensional analysis. Energy J 39(2):123–45
Cao J, Ho MS, Liang H (2016) Household energy demand in urban China: accounting for regional prices and rapid income change. Energy J 37:87–109
Dapice D (2018) Vietnam’s crisis of success in electricity options for a successful clean energy mix. Ash Center for Democratic Governance and Innovation, John F. Kennedy School of Government, Harvard University
Dapice D, Le P (2018) Counting all of the costs: choosing the right mix of electricity sources in Vietnam to 2025. In: Agriculture, Livelihoods, and the Environment in the Lower Mekong Basin, SIRD, Malaysia (upcoming)
Dubin JA (1985) Consumer durable choice and the demand for electricity, vol 155. North-Holland (1985) (ISBN: 0444877665)
Electricity of Vietnam (2016) Forecasting electricity consumption in the summer (in Vietnamese). http://www.evnhanoi.com.vn/tin-tuc-evnhanoi/tin-trong-nganh-dien/2054-du-bao-tinh-hinh-va-nhu-cau-su-dung-dien-trong-thang-he-nam-2016. Accessed 3 June 2017
Espey J, Espey M (2004) Turning on the lights: a meta-analysis of residential electricity demand elasticities. J Agric Appl Econ 36(1):65–81
Fan J-L et al (2015) Impacts of socio-economic factors on monthly electricity consumption of China’s sectors. Nat Hazards 75:2039–47
Fell H, Li S, Paul A (2010) A new look at residential electricity demand using household expenditure data. Discussion Paper 10-57, Resources for the Future
Filippini M, Pachauri S (2004) Elasticities of electricity demand in urban Indian households. Energy Policy 32:429–36
FPT Securities Electricity Sector Report (2015) Bao cao Nganh dien: Thong diep tu Thi truong Canh tranh. http://fpts.com.vn/FileStore2/File/2015/07/20/VietnamPowerReport2015(2).pdf. Accessed 30 May 2017
Government of Vietnam (2009) Decree on urban classification, 42/2009/ND-CP
Hartman RS (1979) Frontiers in energy demand modeling. Annu Rev Energy 4:433–66
Henson SE (1984) Electricity demand estimates under increasing block rates. South Econ J 51(1):147–56
Ito K (2014) Do consumers respond to marginal or average price? Evidence from nonlinear electricity pricing. Am Econ Rev 104(2):537–63
Krishnamurthy ChK, Kristrom B (2013) Energy demand and income elasticity: a cross-country analysis. CERE Working Paper 5, Umea University, Sweden
Labrecque J, Swanson SA (2018) Understanding the assumptions underlying instrumental variable analyses: a brief review of falsification strategies and related tools. Curr Epidemiol Rep 5:214–220
Lin Q, Rizov M, Wong M (2014) Residential electricity pricing in China. Chin Econ 47(2):41–74
McKenzie D, Sasin MJ (2007) Migration, remittances, poverty, and human capital: conceptual and empirical challenges. World Bank Policy Research Working Paper 4272
McClellan M, McNeil BJ, Newhouse JP (1994) Does more intensive treatment of acute myocardial infarction in the elderly reduce mortality? Analysis using instrumental variables. J Am Med Assoc 272(11):859–66
McLoughlin F, Duffy A, Conlon M (2012) Characterizing domestic electricity consumption patterns by dwelling and occupant socio-economic variables: an Irish case study. Energy Build 48:240–48
Miguel E, Satyanath S, Sergenti E (2004) Economic shocks and civil conflict: an instrumental variables approach. J Polit Econ 112(4):725–53
Millien A (2017) Electricity supply reliability and households decision to connect to the grid, CES Working Papers, 2017.31
Ministry of Industry and Trade (2015) Regulation on electricity price. Decision No. 2256/QD-BCT. Hanoi, Vietnam
Olmstead SM (2009) Reduced-form versus structural models of water demand under nonlinear prices. J Bus Econ Stat 27(1):84–94
Romero-JD, del Rio P, Penasco C (2014). Household electricity demand in Spanish Regions, Public Policy Implications. Working Papers from Institut d’Economia de Barcelona (IEB), 24
Shi G, Zheng X, Song F (2012) Estimating elasticity for residential electricity demand in China. Sci World J Article ID, p 395629
Shin J-S (1985) Perception of price when price information is costly: evidence from residential electricity demand. Rev Econ Stat 67(4):591–98
Son NH (2019) Exploring the determinants of household electricity demand in Vietnam in the period 2012–2016. Doctoral Thesis, Université Paris-Saclay. https://tel.archives-ouvertes.fr/tel-02294630/document
Stern DI, Burke PJ, Bruns SB (2016) The impact of electricity on economic development: a macroeconomic perspective. EEG State-of-Knowledge Paper Series
Stock JH (2015) Instrumental variables in statistics and econometrics. Int Encyclop Soc Behav Sci 12:205–09
Stock JH, Yogo M (2004) Testing for weak instruments in linear IV regression. Identification and inference for econometric models: essays in honor of Thomas Rothenberg, 2005. https://ssrn.com/abstract=1734933
Sovey AJ, Green DP (2011) Instrumental variables estimation in political science: a readers’ guide. Am J Polit Sci 55(1):188–200
Sun Y (2015) Electricity prices, income and residential electricity consumption. Working Paper, School of Urban and Regional Science, East China Normal University
Yin H, Zhou H, Zhu K (2015) Long- and short-run elasticities of residential electricity consumption in China: a partial adjustment model with panel data. Appl Econ. https://doi.org/10.1080/00036846.2015.1125436
Wiesmann D, Azevedo IL, Ferrao P, Fernandez J (2011) Residential electricity consumption in Portugal: findings from top-down and bottom-up models. Energy Policy 39:2772–79
Wooldridge JM (2004) Econometric analysis of cross section and panel data. The MIT Press, Cambridge
Wooldridge JM (2012) Introductory econometrics: a modern approach, 5th edn. South-Western, Ohio (ISBN 13: 978-1-111-53104-1)
World Bank (2016) Vietnam-Household Registration Study 2015. http://microdata.worldbank.org/index.php/catalog/2729
World Bank and Vietnam Academy of Social Sciences (2016) Vietnam’s household registration system (ISBN: 978-604-948-153-6)
Acknowledgements
I thank seminar participants at the Fulbright School of Public Policy and Management (FSPPM), the Environment for Development (EfD) Initiative’s annual meeting, the Vietnam Economist Annual Meeting (VEAM), and the Southeast Asia Research Group (SEAREG) meeting for many helpful comments. Particularly, I am indebted to the three anonymous reviewers for invaluable feedbacks on an earlier draft of this paper. All remaining errors are my own.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
About this article
Cite this article
Phu, L.V. Electricity price and residential electricity demand in Vietnam. Environ Econ Policy Stud 22, 509–535 (2020). https://doi.org/10.1007/s10018-020-00267-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10018-020-00267-6