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Testing and estimating time-varying elasticities of Swiss gasoline demand

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  • Neto, David

Abstract

This paper is intended to test and estimate time-varying elasticities for gasoline demand in Switzerland. For this purpose, a smooth time-varying cointegrating parameters model is investigated in order to describe smooth mutations of the Swiss gasoline demand. The methodology, based on Chebyshev polynomials, is rigorously outlined. Our empirical finding states that the time-invariance assumption does not hold for long-run price and income elasticities. Furthermore they highlight that gasoline demand passed through some periods of sensitivity and non sensitivity with respect to the price. Our empirical statements are of great importance to assess the performance of a gasoline tax as an instrument for CO2 reduction policy. Indeed, such an instrument can contribute to reduce emissions of greenhouse gases only if the demand is not fully inelastic with respect to the price. Our results suggest that such a carbon-tax would not be always suitable since the price elasticity is found not stable over time and not always significant.

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  • Neto, David, 2012. "Testing and estimating time-varying elasticities of Swiss gasoline demand," Energy Economics, Elsevier, vol. 34(6), pages 1755-1762.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:6:p:1755-1762
    DOI: 10.1016/j.eneco.2012.07.009
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    Cited by:

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    2. Barrientos, Jorge & Velilla, Esteban & Tobón Orozco, David & Villada, Fernando & López Lezama, Jesús M., 2018. "On the estimation of the price elasticity of electricity demand in the manufacturing industry of Colombia," Revista Lecturas de Economía, Universidad de Antioquia - CIE, issue 88, pages 155-182, January.
    3. Deepankar Sinha & Virupaxi Bagodi & Debasri Dey, 2020. "The Supply Chain Disruption Framework Post COVID-19: A System Dynamics Model," Foreign Trade Review, , vol. 55(4), pages 511-534, November.
    4. Scott, K. Rebecca, 2015. "Demand and price uncertainty: Rational habits in international gasoline demand," Energy, Elsevier, vol. 79(C), pages 40-49.
    5. Eleyan, Mohammed I.Abu & Çatık, Abdurrahman Nazif & Balcılar, Mehmet & Ballı, Esra, 2021. "Are long-run income and price elasticities of oil demand time-varying? New evidence from BRICS countries," Energy, Elsevier, vol. 229(C).
    6. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    7. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    8. Neto, David, 2014. "The FMLS-based CUSUM statistic for testing the null of smooth time-varying cointegration in the presence of a structural break," Economics Letters, Elsevier, vol. 125(2), pages 208-211.
    9. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    10. David Neto, 2015. "Testing for and dating structural break in smooth time-varying cointegration parameters, with an application to retail gasoline price and crude oil price long-run relationship," Empirical Economics, Springer, vol. 49(3), pages 909-928, November.
    11. Jeyhun Mikayilov & Fred Joutz & Fakhri Hasanov, 2019. "Gasoline Demand in Saudi Arabia: Are the Price and Income Elasticities Constant?," Discussion Papers ks--2019-dp81, King Abdullah Petroleum Studies and Research Center.

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    More about this item

    Keywords

    Demand for gasoline; Time-varying cointegration; Chebyshev polynomials; Price elasticity; Income elasticity; Fully modified least-squared estimator; Fully modified Wald test;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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