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Dynamics of U.S. State Cigarette Consumption: Evidence from Panel Error Correction Modeling

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  • Nicholas Apergis
  • Rajeev Goel
  • James Payne

Abstract

This study uses state-level data for nearly four decades to study the dynamic demand for cigarettes, focusing especially on the long-run equilibrium relationship between cigarette consumption and its determinants as well as the short-run and long-run causal dynamics. We find the presence of cointegration with the long-run equilibrium, indicating the price elasticity of cigarette demand to be negative and inelastic, the income elasticity is positive and the border smuggling effects are significant, with substantial variations across individual states. Of the various smoking control policies considered, questions remain as to the effectiveness of aggregate anti-smoking initiatives that treat all states alike. Furthermore, the causal dynamics reveal bi-directional causality between cigarette consumption and its determinants. Some policy implications are discussed. Copyright International Atlantic Economic Society 2014

Suggested Citation

  • Nicholas Apergis & Rajeev Goel & James Payne, 2014. "Dynamics of U.S. State Cigarette Consumption: Evidence from Panel Error Correction Modeling," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 42(1), pages 3-20, March.
  • Handle: RePEc:kap:atlecj:v:42:y:2014:i:1:p:3-20
    DOI: 10.1007/s11293-013-9401-3
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    Cited by:

    1. Rajeev K. Goel & James W. Saunoris, 2019. "Cigarette smuggling: using the shadow economy or creating its own?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 582-593, July.

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    More about this item

    Keywords

    Cigarettes; Panel error correction; Demand; Smuggling; Long-run equilibrium; I18; C22;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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