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How does fuel demand respond to price changes? Quasi-experimental evidence based on high-frequency data
[L’ajustement de court terme de la consommation de carburant à des changements de prix. Des estimations menées à partir de données à haute fréquence]

Author

Listed:
  • Marine Adam

    (INSEE - Institut national de la statistique et des études économiques (INSEE))

  • Odran Bonnet

    (INSEE - Institut national de la statistique et des études économiques (INSEE))

  • Etienne Fize

    (CAE - Conseil d'analyse économique)

  • Marion Rault

    (CAE - Conseil d'analyse économique)

  • Tristan Loisel

    (CREST-INSEE - Centre de Recherche en Economie et en Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - INSEE - Institut national de la statistique et des études économiques (INSEE))

  • Lionel Wilner

    (CREST-INSEE - Centre de Recherche en Economie et en Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - INSEE - Institut national de la statistique et des études économiques (INSEE))

Abstract

This article exploits quasi-natural experiments provided by both the 2022 crude oil price surge consecutive to the Russo-Ukrainian war and fuel excise tax cuts in France to infer the price sensitivity of fuel demand. The granularity of bank account data available at the transaction level permits to shed new insights on how to properly disentangle anticipation effects from price effects. After controlling for anticipatory behavior, we obtain a price-elasticity comprised between -0.4 and -0.21. The average elasticity exhibits sizeable dispersion with respect to fuel spending, but varies little with income and location. Counterfactual simulations enable us to assess both financial and distributive impacts of the tax policy at stake as well as its effect on CO2 emissions.

Suggested Citation

  • Marine Adam & Odran Bonnet & Etienne Fize & Marion Rault & Tristan Loisel & Lionel Wilner, 2023. "How does fuel demand respond to price changes? Quasi-experimental evidence based on high-frequency data [L’ajustement de court terme de la consommation de carburant à des changements de prix. Des e," Working Papers hal-05354063, HAL.
    • Handle: RePEc:hal:wpaper:hal-05354063
    Note: View the original document on HAL open archive server: https://insee.hal.science/hal-05354063v1
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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • Q35 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Hydrocarbon Resources
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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