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A study of petrol consumption using Spanish panel data

Author

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  • Jose Labeaga
  • Angel Lopez

Abstract

Methods are proposed for the estimation of equations for consumption categories subject to non-participation and other types of censoring using an unbalanced panel data set on petrol expenditures from the Spanish Continuous Family Expenditure Survey. The use of panel data allows one to deal with two issues that pose econometric problems when dealing with individual budget data. On one hand, unobserved time invariant heterogeneity is controlled for. On the other hand, the problem of censoring in the dependent variable is addressed and the measurement error induced by infrequent purchases is corrected. Results suggest the use of probabilities of purchase estimated from the temporal pattern of expenditure records in order to carry out this correction. The estimated demand system is subsequently used to simulate the effects of changes in the taxation of petrol.

Suggested Citation

  • Jose Labeaga & Angel Lopez, 1997. "A study of petrol consumption using Spanish panel data," Applied Economics, Taylor & Francis Journals, vol. 29(6), pages 795-802.
    • Handle: RePEc:taf:applec:v:29:y:1997:i:6:p:795-802
    DOI: 10.1080/000368497326714
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    Cited by:

    1. Bakhat, Mohcine & Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "Elasticities of transport fuels at times of economic crisis: An empirical analysis for Spain," Energy Economics, Elsevier, vol. 68(S1), pages 66-80.
    2. Xavier Labandeira & José M. Labeaga & Miguel Rodríguez, 2006. "A Residential Energy Demand System for Spain," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 87-112.
    3. Nicholas Bardsley & Milena Büchs & Sylke V Schnepf, 2017. "Something from nothing: Estimating consumption rates using propensity scores, with application to emissions reduction policies," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-23, October.
    4. Mohcine Bakhat & Jaume Roselló, 2011. "Tourism Induced Contribution to Diesel Oil and Gasoline Consumption," Working Papers 05-2011, Economics for Energy.
    5. Silvana Mima & Patrick Criqui, 2009. "Assessment of the impacts under future climate change on the energy systems with the POLES model," Post-Print halshs-00452948, HAL.
    6. Rosa M. González-Marrero & Rosa M. Lorenzo-Alegría & Gustavo A. Marrero, 2011. "Gasoline and Diesel Consumption for Road Transport in Spain: a Dynamic Panel Data Approach," Economic Reports 04-2011, FEDEA.
    7. Neuwahl, Frederik & Löschel, Andreas & Mongelli, Ignazio & Delgado, Luis, 2008. "Employment impacts of EU biofuels policy: Combining bottom-up technology information and sectoral market simulations in an input-output framework," Ecological Economics, Elsevier, vol. 68(1-2), pages 447-460, December.
    8. Mohcine Bakhat & José M. Labeaga & Xavier Labandeira & Xiral Lñpez, 2013. "Economic Crisis and Elasticities of Car Fuels: Evidence for Spain," Working Papers fa15-2013, Economics for Energy.
    9. González, Rosa Marina & Marrero, Gustavo A., 2012. "Induced road traffic in Spanish regions: A dynamic panel data model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 435-445.
    10. Olympia Bover & José María Casado & Esteban García-Miralles & Roberto Ramos & José María Labeaga, 2017. "Microsimulation tools for the evaluation of fiscal policy reforms at the Banco de España," Occasional Papers 1707, Banco de España.
    11. Romero-Jordán, Desiderio & del Río, Pablo & Jorge-García, Marta & Burguillo, Mercedes, 2010. "Price and income elasticities of demand for passenger transport fuels in Spain. Implications for public policies," Energy Policy, Elsevier, vol. 38(8), pages 3898-3909, August.

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