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The Demand For Gasoline: Evidence From Household Survey Data*

* This paper has been replicated

Author

Listed:
  • Dongfeng Chang
  • Apostolos Serletis

Abstract

SUMMARY In this paper we investigate the demand for gasoline in Canada using recent annual expenditure data from the Canadian Survey of Household Spending, over a 13‐year period from 1997 to 2009, on three expenditure categories in the transportation sector: gasoline, local transportation, and intercity transportation. In doing so, we use three of the most widely used locally flexible functional forms, the Almost Ideal Demand System (AIDS) of Deaton and Muellbauer (1980), the quadratic AIDS (QUAIDS) of Banks et al. (1997)—an extension of the simple AIDS model that can generate quadratic Engel curves—and the Minflex Laurent model of Barnett (1983), which can also generate quadratic Engel curves. We pay explicit attention to economic regularity, argue that unless regularity is attained by luck, flexible functional forms should always be estimated subject to regularity as suggested by Barnett (2002), and impose local curvature to produce inference consistent with neoclassical microeconomic theory. Our findings indicate that the curvature‐constrained Minflex Laurent model is the only model that is able to provide theoretically consistent estimates of the Canadian demand for gasoline. Our estimates show that the own‐price elasticity for gasoline demand in Canada is between − 0.738 and − 0.570 —less elastic than previously reported in the literature. Copyright © 2013 John Wiley & Sons, Ltd.

Suggested Citation

  • Dongfeng Chang & Apostolos Serletis, 2014. "The Demand For Gasoline: Evidence From Household Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 291-313, March.
  • Handle: RePEc:wly:japmet:v:29:y:2014:i:2:p:291-313
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    Cited by:

    1. Ali Jadidzadeh & Apostolos Serletis, 2016. "Sectoral Interfuel Substitution in Canada: An Application of NQ Flexible Functional Forms," The Energy Journal, , vol. 37(2), pages 181-200, April.
    2. José M. Labeaga & Xavier Labandeira & Xiral López-Otero, 2018. "Energy Tax Reform and Poverty Alleviation in Mexico," Working Papers 1801, Universidade de Vigo, Departamento de Economía Aplicada.
    3. Mir Hossein Mousavi, 2015. "An Estimation of Natural Gas Demand in Household Sector of Iran; the Structural Time Series Approach," Proceedings of International Academic Conferences 2804383, International Institute of Social and Economic Sciences.
    4. Mateo Velásquez‐Giraldo & Gustavo Canavire‐Bacarreza & Kim P. Huynh & David T. Jacho‐Chavez, 2018. "Flexible Estimation of Demand Systems: A Copula Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1109-1116, November.
    5. Sheng Yang & Ling-Yun He, 2015. "Oil price shocks, road transport pollution emissions and residents' health losses in China," Papers 1512.01742, arXiv.org.
    6. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    7. Haotian Chen & Xibin Zhang, 2014. "Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption," Monash Econometrics and Business Statistics Working Papers 28/14, Monash University, Department of Econometrics and Business Statistics.
    8. Yingheng Zhang & Haojie Li & Gang Ren, 2025. "Data-driven exploration of heterogeneous gasoline price elasticities using generalized random forests," Transportation, Springer, vol. 52(1), pages 215-237, February.
    9. Ling-Yun He & Sheng Yang & Dongfeng Chang, 2017. "Oil Price Uncertainty, Transport Fuel Demand and Public Health," IJERPH, MDPI, vol. 14(3), pages 1-19, March.
    10. Chen, Haotian & Smyth, Russell & Zhang, Xibin, 2017. "A Bayesian sampling approach to measuring the price responsiveness of gasoline demand using a constrained partially linear model," Energy Economics, Elsevier, vol. 67(C), pages 346-354.
    11. Brad R. Humphreys & Jane E. Ruseski & Jie Yang, 2020. "Household consumption decisions: will expanding sports betting impact health?," Review of Economics of the Household, Springer, vol. 18(4), pages 1079-1100, December.
    12. Nurul Hossain, A.K.M. & Serletis, Apostolos, 2017. "A century of interfuel substitution," Journal of Commodity Markets, Elsevier, vol. 8(C), pages 28-42.
    13. Bigerna, S. & Bollino, C.A. & Micheli, S. & Polinori, P., 2017. "Revealed and stated preferences for CO2 emissions reduction: The missing link," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1213-1221.
    14. Senia, Mark & Dharmasena, Senarath, 2017. "Pre-Determined Demand and Theoretical Regularity Conditions: Their Importance for Consumer Food Demand Using AIDS and Policy Analysis Implications," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252740, Southern Agricultural Economics Association.

    Replication

    This item has been replicated by:
  • Mateo Velásquez‐Giraldo & Gustavo Canavire‐Bacarreza & Kim P. Huynh & David T. Jacho‐Chavez, 2018. "Flexible Estimation of Demand Systems: A Copula Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1109-1116, November.
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