Abstract
In this paper, we estimate the price and income elasticities for gasoline demand in selected energy gluttons—China, India, USA, Russia, and Japan. Specifically, we employ a time-varying parameter approach which adequately deals with potential parameter instabilities and nonlinearities and effectively captures price and income elasticity variations over time, with each time period having its own set of coefficients. Our empirical findings reveal the following: gasoline consumption is price-inelastic and income-inelastic, there are movements in both the price and income elasticities, and the movements generally correspond with business cycle patterns of each of the countries; overall, sensitivity to price and income changes increase during periods of economic crises. Constant elasticity models overestimate price and income elasticities, and income is predominantly more elastic than price. Our conclusion is that policy mechanisms that are price-based such as gasoline taxes are likely to be unsuccessful in achieving consumption-cum-pollution reduction objectives in the energy gluttons. Such policies may, however, be effective if they ensure that gasoline prices rise at a greater rate than income. Such policies may also be useful for revenue-raising purposes.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Akinboade OA, Ziramba E, Kumo WL (2008) The demand for gasoline in South Africa: an empirical analysis using co-integration techniques. Energy Econ 30(6):3222–3229
Algunaibet IM, Matar W (2018) The responsiveness of fuel demand to gasoline price change in passenger transport: a case study of Saudi Arabia. Energy Efficiency 11(6):1341–1358
Alves DC, da Silveira Bueno RDL (2003) Short-run, long-run and cross elasticities of gasoline demand in Brazil. Energy Econ 25(2):191–199
Arisoy I, Ozturk I (2014) Estimating industrial and residential electricity demand in Turkey: a time varying parameter approach. Energy 66:959–964
Atalla TN, Gasim AA, Hunt LC (2018) Gasoline demand, pricing policy, and social welfare in Saudi Arabia: a quantitative analysis. Energy Policy 114:123–133
Bakhat M, Rosselló J (2013) Evaluating a seasonal fuel tax in a mass tourism destination: a case study for the Balearic Islands. Energy Econ 38:12–18
Baltagi BH, Bresson G, Griffin JM, Pirotte A (2003) Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption. Empir Econ 28(4):795–811
Cassidy ES (2019). Which countries use the most fossil fuels? Resource Watch. https://blog.resourcewatch.org/2019/05/02/which-countries-use-the-most-fossil-fuels/. Accessed 10, August 2020
Chang Y, Kim CS, Miller JI, Park JY, Park S (2014) Time-varying long-run income and output elasticities of electricity demand with an application to Korea. Energy Econ 46:334–347
Cooper JC (2003) Price elasticity of demand for crude oil: estimates for 23 countries. OPEC Rev 27(1):1–8
Dahl CA (2012) Measuring global gasoline and diesel price and income elasticities. Energy Policy 41:2–13
Danesin A, Linares P (2015) An estimation of fuel demand elasticities for Spain an aggregated panel approach accounting for diesel share. Journal of Transport Economics and Policy 49(1):1–16
Dogan E, Smyth R, & Zhang, X. (2018). A Nonparametric Panel Data Model for Examining the Contribution of Tourism to Economic Growth. Preprint. Available online: https://www.researchgate.net/publication/328758783. Accessed 12 Mar 2020
Dillon HS, Saphores JD, Boarnet MG (2015) The impact of urban form and gasoline prices on vehicle usage: evidence from the 2009 National Household Travel Survey. Res Transp Econ 52:23–33
Durbin J, Koopman SJ (2012) Time series analysis by state space methods. Oxford University Press
EIA (2017) Country analysis brief: Russia. Retrieved from https://www.eia.gov/international/content/analysis/countries_long/Russia/russia.pdf
EIA (2020a) Country analysis executive summary: China. Retrieved from https://www.eia.gov/international/content/analysis/countries_long/China/china.pdf
EIA (2020b) Country analysis executive summary: India. Retrieved from https://www.eia.gov/international/content/analysis/countries_long/India/india.pdf
EIA (2020c) Oil and petroleum products explained. Retrieved from https://www.eia.gov/energyexplained/oil-and-petroleum-products/use-of-oil.php
EIA (2020d) Country analysis executive summary: India. Retrieved from https://www.eia.gov/international/content/analysis/countries_long/Japan/japan.pdf
EIA (2021). Annual energy outlook 2021: with projections to 2050. Retrieved from https://www.eia.gov/outlooks/aeo/pdf/AEO_Narrative_2021.pdf
Eltony MN (1996) Demand for gasoline in the GCC: an application of pooling and testing procedures. Energy Econ 18(3):203–209
Eltony MN, Al-Mutairi NH (1995) Demand for gasoline in Kuwait: an empirical analysis using cointegration techniques. Energy Econ 17(3):249–253
Galli R (1998) The relationship between energy intensity and income levels: forecasting long term energy demand in Asian emerging countries. Energy J 19(4):85–106
Goodwin P, Dargay J, Hanly M (2004) Elasticities of road traffic and fuel consumption with respect to price and income: a review. Transp Rev 24(3):275–292
Graham DJ, Glaister S (2004) Road traffic demand elasticity estimates: a review. Transp Rev 24(3):261–274
Harvey AC (1990) Forecasting, structural time series models and the Kalman filter. Cambridge University Press, Cambridge, UK
Houthakker HS (1965) New evidence on demand elasticities. Econometrica: Journal of the Econometric Society 33:277–288
Husaini DH, Puah CH, Lean HH (2019) Energy subsidy and oil price fluctuation, and price behavior in Malaysia: a time series analysis. Energy 171:1000–1008
India’s Ministry of Petroleum and Natural Gas, Petroleum Planning and Analysis Cell, Petroleum Consumption (2019) FACTS global energy, Asia Pacific petroleum databook 3: oil product balances and prices. Retrieved from https://www.ppac.gov.in/content/147_1_ConsumptionPetroleum.aspx.
Inglesi-Lotz R (2011) The evolution of price elasticity of electricity demand in South Africa: a Kalman filter application. Energy Policy 39(6):3690–3696
Kalman RE (1960) A new approach to linear filtering and prediction problems. J Basic Eng 82(1):35–45
Kalman RE, Bucy RS (1961) New results in linear filtering and prediction theory. J Basic Eng 83(1):95–108
Kanjilal K, Ghosh S (2018) Revisiting income and price elasticity of gasoline demand in India: new evidence from cointegration tests. Empir Econ 55(4):1869–1888
Karimu A, Brännlund R (2013) Functional form and aggregate energy demand elasticities: a nonparametric panel approach for 17 OECD countries. Energy Econ 36:19–27
Koshal RK, Koshal M, Yamamoto K, Miyazima S, Yamada Y (2007) Demand for gasoline in Japan. Demand for Gasoline in Japan:1000–1017
Lean HH, Smyth R (2014a) Disaggregated energy demand by fuel type and economic growth in Malaysia. Appl Energy 132(C):168–177
Lean HH, Smyth R (2014b) Will initiatives to promote hydroelectricity consumption be effective? Evidence from univariate and panel LM unit root tests with structural breaks. Energy Policy 68(C):102–115
Lee CC, Lee JD (2010) A panel data analysis of the demand for total energy and electricity in OECD countries. Energy J 31(1):1–24
Lee CC, Wang CW, Ho SJ, Wu TP (2020) The impact of natural disaster on energy consumption: international evidence. Energy Econ 97:105021
Lee J, Robinson PM (2015) Panel nonparametric regression with fixed effects. Journal of Econometrics, 188(2), 346-362
Li S, Linn J, Muehlegger E (2014) Gasoline taxes and consumer behavior. American Economic Journal. Econ Policy 6(4):302–342
Liddle B (2012) The systemic, long-run relation among gasoline demand, gasoline price, income, and vehicle ownership in OECD countries: evidence from panel cointegration and causality modeling. Transp Res Part D: Transp Environ 17(4):327–331
Liddle B, Huntington H (2020) Revisiting the income elasticity of energy consumption: a heterogeneous, common factor, dynamic OECD & non-OECD country panel analysis. Energy J 41(3):207–229
Liddle B, Smyth R, Zhang X (2020) Time-varying income and price elasticities for energy demand: evidence from a middle-income panel. Energy Econ 86:104681
Lin CYC, Zeng JJ (2013) The elasticity of demand for gasoline in China. Energy Policy 59:189–197
Liu G (2004) Estimating energy demand elasticities for OECD countries: a dynamic panel data approach. Discussion Papers No. 373, March 2004, Statistics Norway, Research Department
Liu W (2014) Modeling gasoline demand in the United States: a flexible semiparametric approach. Energy Econ 45:244–253
Liu TY, Lee CC (2020) Convergence of the world’s energy use. Resour Energy Econ 62:101199
Mikayilov J, Hasanov F, Bollino C, Mahmudlu C (2017) Modeling of electricity demand for Azerbaijan: time-varying coefficient cointegration approach. Energies 10(11):1918
Mikayilov JI, Mukhtarov S, Mammadov J (2019) Income and price elasticities of gasoline demand: an empirical analysis for Russia. file:///C:/Users/DC/Downloads/59ccff_33ce15124d96489bb47895dc0d27a318%20(1).pdf
Mikayilov JI, Joutz FL, Hasanov FJ (2020a) Gasoline demand in Saudi Arabia: are the price and income elasticities constant? Energy Sources, Part B: Economics, Planning, and Policy 15(4):211–229
Mikayilov JI, Mukhtarov S, Dinçer H, Yüksel S, Aydın R (2020b) Elasticity analysis of fossil energy sources for sustainable economies: a case of gasoline consumption in Turkey. Energies 13(3):731
Mikayilov JI, Mukhtarov S, Mammadov J (2020c) Gasoline demand elasticities at the backdrop of lower oil prices: fuel-subsidizing country case. Energies 13(24):6752
Miller M, Alberini A (2016) Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: evidence from US data. Energy Policy 97:235–249
Narayan PK, Gupta R (2015) Has oil price predicted stock returns for over a century? Energy Econ 48(C):18–23
Narayan PK, Sharma S, Poon WC, Westerlund J (2014) Do oil prices predict economic growth? New global evidence. Energy Econ 41(C):137–146
Oil and Gas UK (2015) Economic report. Oil and gas UK (Aberdeen). https://cld.bz/bookdata/TYrkA5w/basic-html/page-88.html. Accessed 10, August 2020
Ozturk I, Arisoy I (2016) An estimation of crude oil import demand in Turkey: evidence from time-varying parameters approach. Energy Policy 99:174–179
Park SY, Zhao G (2010) An estimation of US gasoline demand: a smooth time-varying cointegration approach. Energy Econ 32(1):110–120
Phoumin H, Kimura S (2014) Analysis on price elasticity of energy demand in East Asia: empirical evidence and policy implications for ASEAN and East Asia. ERIA Discussion Paper Series, April
Polemis ML (2006) Empirical assessment of the determinants of road energy demand in Greece. Energy Econ 28(3):385–403
Ramanathan R (1999) Short-and long-run elasticities of gasoline demand in India: an empirical analysis using cointegration techniques. Energy Econ 21(4):321–330
Rentziou A, Gkritza K, Souleyrette RR (2012) VMT, energy consumption, and GHG emissions forecasting for passenger transportation. Transp Res A Policy Pract 46(3):487–500
Richmond AK, Kaufmann RK (2006) Energy prices and turning points: the relationship between income and energy use/carbon emissions. Energy J 27(4):157–181
Scott KR (2015) Demand and price uncertainty: rational habits in international gasoline demand. Energy 79:40–49
Tanizaki H (1999) The time-varying parameter model revisited. Kobe University Economic Review 45:41–58
Van Benthem AA (2015) Energy leapfrogging. J Assoc Environ Resour Econ 2(1):93–132
Van Benthem A, Romani M (2009) Fuelling growth: what drives energy demand in developing countries? Energy J 30(3):91–114
Wang N, Mogi G (2017) Industrial and residential electricity demand dynamics in Japan: how did price and income elasticities evolve from 1989 to 2014? Energy Policy 106:233–243
Wen H, Lee CC (2020) Impact of fiscal decentralization on firm environmental performance: evidence from a county-level fiscal reform in China. Environ Sci Pollut Res 27:36147–36159
Zeleke A (2016) Gasoline and diesel demand elasticities: a consistent estimate across the EU-28 (No. 2016: 12). Swedish University of Agricultural Sciences, Department Economics
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This study received funding from the Jiangxi Humanities and Social Sciences Project of University (No. JJ20125).
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Chien-Chiang Lee: conceptualization, supervision, project administration, and resources.
Godwin Olasehinde-Williams: original draft, methodology, formal analysis, and software.
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Lee, C., Olasehinde-Williams, G. Gasoline demand elasticities in the world’s energy gluttons: a time-varying coefficient approach. Environ Sci Pollut Res 28, 64830–64847 (2021). https://doi.org/10.1007/s11356-021-15615-6
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DOI: https://doi.org/10.1007/s11356-021-15615-6