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Tourism Demand in Tunisia: A VECM Approach

Author

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  • Dekkiche Djamal

    (Relizane University, BP 48000 Relizane, Algeria)

Abstract

This research aimed to study the determinants of tourism demand in Tunisia from 1995 to 2019 with four independent variables: gross domestic product, consumer price index, the real exchange rate, and air transport passengers carried. The research employed the Unit root test, Co-integration test, and Vector Error Correction model (VECM) to examine the variables’ short- and long-run relationship dynamics. The results show that co-integrating relations exist among the variables; all independent variables negatively impact tourism demand except Air transport. Depending on the results obtained, policymakers should be aware of the negative effect of the country’s political instability on the extent of external tourism demand. In this sense, the government must restore political stability to encourage tourists to visit Tunisia. Future studies should consider factors such as the economy’s trade openness and oil prices.

Suggested Citation

  • Dekkiche Djamal, 2023. "Tourism Demand in Tunisia: A VECM Approach," Naše gospodarstvo/Our economy, Sciendo, vol. 69(2), pages 50-59, June.
    • Handle: RePEc:vrs:ngooec:v:69:y:2023:i:2:p:50-59:n:4
    DOI: 10.2478/ngoe-2023-0011
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    More about this item

    Keywords

    Tourism industry; Tourism demand; VECM; Co-integration; Tunisia;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • P24 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - National Income, Product, and Expenditure; Money; Inflation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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