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Natural Disaster, Government Revenues and Expenditures: Evidence from High and Middle-Income Countries

Author

Listed:
  • Nadia Benali

    (University of Sfax)

  • Mounir Ben Mbarek

    (University of Sfax)

  • Rochdi Feki

    (Business School of Sfax)

Abstract

This paper examines the dynamic links between government budgets (government expenditures and revenues), natural disaster, and three key macroeconomic indicators; economic growth, inflation rate, and government debt. By studying the annual data for high- and middle-income countries over 1990–2013 and employing a panel vector autoregressive model for detecting Granger causality, we find that there is a big correlation between these variables, including unidirectional causality between natural disasters and government debt. For middle-income countries there is a unidirectional causality from natural disasters to government expenditures. Thus, there is a unidirectional causality between natural disasters and economic growth and government revenues for high- and middle-income countries.

Suggested Citation

  • Nadia Benali & Mounir Ben Mbarek & Rochdi Feki, 2019. "Natural Disaster, Government Revenues and Expenditures: Evidence from High and Middle-Income Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(2), pages 695-710, June.
  • Handle: RePEc:spr:jknowl:v:10:y:2019:i:2:d:10.1007_s13132-017-0484-y
    DOI: 10.1007/s13132-017-0484-y
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    More about this item

    Keywords

    Government expenditures; Government revenues; Natural disasters; Economic growth; Panel VAR; Panel unit roots; Granger causality;
    All these keywords.

    JEL classification:

    • H61 - Public Economics - - National Budget, Deficit, and Debt - - - Budget; Budget Systems
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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