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Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach

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  • Eshagh Mansourkiaee

    (NIOC (Economic Assessment and Research Department))

Abstract

This paper estimates the price and GDP/income elasticities of residential sector gas demand in the number of gas exporting countries over 1990–2019 by applying the homogenous OLS, TSLS and GMM methods to a panel data set. The energy demand is specified by a simple partial adjustment model. The study finds that gas exporting countries are nonresponsive to price changes either in a short or long-term period. Although the results for income elasticity are not conclusive in terms of magnitude and sign, they show that short-run income elasticity is inelastic and smaller than that of long-run. The study also provides results of heterogeneous 2SLS estimators for individual countries. Comparing these results with the results of the previous similar study using the ARDL bounds testing approach shows that while there is wide variability between individual estimations, both studies have found almost similar long-run income elasticity on average. For the long-run price elasticity, however, the ARDL model seems to give more intuitive results in terms of sign and magnitude.

Suggested Citation

  • Eshagh Mansourkiaee, 2023. "Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.
    • Handle: RePEc:spr:snbeco:v:3:y:2023:i:1:d:10.1007_s43546-022-00373-5
    DOI: 10.1007/s43546-022-00373-5
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    More about this item

    Keywords

    Residential sector; Gas demand; Price elasticity; Income elasticity; Gas exporting; Panel data;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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