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Khadem Nematollahy, Mahboobeh, Mohammadi, Teymour. (1404). Investigating The Impact of Political Risk On Tourism Demand: Applying Dynamic ARDL Simulation Method. نشریه علمی دانشگاه سیستان و بلوچستان, 17(1), 169-187. doi: 10.22111/ijbds.2025.51380.2213
Mahboobeh Khadem Nematollahy; Teymour Mohammadi. "Investigating The Impact of Political Risk On Tourism Demand: Applying Dynamic ARDL Simulation Method". نشریه علمی دانشگاه سیستان و بلوچستان, 17, 1, 1404, 169-187. doi: 10.22111/ijbds.2025.51380.2213
Khadem Nematollahy, Mahboobeh, Mohammadi, Teymour. (1404). 'Investigating The Impact of Political Risk On Tourism Demand: Applying Dynamic ARDL Simulation Method', نشریه علمی دانشگاه سیستان و بلوچستان, 17(1), pp. 169-187. doi: 10.22111/ijbds.2025.51380.2213
Khadem Nematollahy, Mahboobeh, Mohammadi, Teymour. Investigating The Impact of Political Risk On Tourism Demand: Applying Dynamic ARDL Simulation Method. نشریه علمی دانشگاه سیستان و بلوچستان, 1404; 17(1): 169-187. doi: 10.22111/ijbds.2025.51380.2213

Investigating The Impact of Political Risk On Tourism Demand: Applying Dynamic ARDL Simulation Method

International Journal of Business and Development Studies
مقاله 9، دوره 17، شماره 1، تیر 2025، صفحه 169-187    اصل مقاله (693.22 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/ijbds.2025.51380.2213
نویسندگان
Mahboobeh Khadem Nematollahy* 1؛ Teymour Mohammadi2
1economics faculty. Allameh Tabatabai university, Tehran, Iran
2Economics Faculty, Allameh Tabataba'i university, Tehran, Iran
چکیده
Objective:
The tourism sector, a significant component of the global service industry, is vital for a nation’s economic development and income generation. Therefore, it is essential to ascertain the factors influencing the demand for this type of service. The main aim of this study is to examine the impact of exchange rates on tourism demand in Iran.
Methods:
This study examined the long-term and short-term relationships between Iran’s tourism arrivals and variables such as the exchange rate, political risk, and other factors influencing tourism demand, including inflation, foreign investment, oil revenue, GDP, and population, employing time series data from 1995 to 2024 and the Dynamic ARDL simulation method. Results:
The results indicate that political risk significantly detrimentally affects Iran’s tourism demand, whereas the exchange rate has a notable positive influence. Since 2010, when the fourth round of sanctions began, political risk has escalated owing to internal and external conflicts, negatively impacting international tourism demand.
Conclusions:
The interplay between exchange rate variables and political risk was found to positively influence tourism demand. The increase in the exchange rate decreases the costs of tourism services, and also stimulates creative business endeavors in the tourism industry.
کلیدواژه‌ها
Dynamic ARDL simulation method؛ exchange rate؛ political risk؛ tourism demand؛ time series
مراجع
  1. A tisdell, C. (2013). Handbook of tourism economics: analysis, new applications, and case studies, university of Queensland, Australia, 1-1001.
  2. Akadiri, S. S., Eluwole, K. K., Akadidi, C. A., & Avci, T. (2020). Dose Causality Between Geopolitical Risk, Tourism and Economic Growth Matter? Evidence from Turkey. Journal of Hospitality and Tourism Management, 43, 273-277.
  3. Arellano, M. and Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Review of Economic Studies, 58, 277–297.
  4. Asadpour Kordi, M., Amirnejad, H., Nasseri Ojaki, S. H., & Shirzadi Laskookalayeh, S. (2023). The Effect of Economic, Social, and Natural Factors on the Efficiency of Iran's Tourism Industry. Iranian Economic Review, 27(2), 425-446.‏
  5. Behbudi, Davod, & Bastan, Faranak. (2010). Foreign Direct Investment and Tourism in Developing Countries: Evidence From Panel Causality Tests. Journal of Financial Economics (Financial Economics and Development), 4(11), 1-17.
  6. Brooks, C. (2014). introductory econometrics for finance, Cambridge University Press, The ICMA Centre, Henley Business School, University of Reading, 3rd, 1-744.
  7. Calderwood, L. U. and Soshkin, M. (2019). the Travel and Tourism Competitiveness Report 2019, World Economic Forum, 1-129.
  8. Copeland, BR. (1991). Tourism, welfare and de-industrialization in a small open economy, Economica, 58, 515–529.
  9. Cox, D.R. (1984). Interaction, International Statistical Review, 52 (1), 1–25. 
  10. Crotti, R. and Misrahi, T. (2017). The Travel and Tourism Competitiveness Report 2017, World Economic Forum, 1-371.
  11. Bond, B. Cohen and Schachter, G. (1977). The spatial distribution of tourism demand and exchange rate variation: OECD European countries, The Tourist Review, Emerald, vol. 32, 13-17.
  12. Dashtban Farooji, Majid, Eliaspour, Behnam and Dashtban Farooji, Sahar. (2019). The effect of exchange rate uncertainty on tourism flows in Iran: A stochastic turbulence model approach with leverage effects and mixed data with different frequencies (MIDAS), Quarterly Journal of Tourism Planning and Development, 2, 173-190. (in Persian).
  13. De Vita, G. (2014). The long-run impact of exchange rate regimes on international tourism flows, Tourism management, 45, 226-233.
  14. Divisekera, S. (1995). An econometric model of economic determinants of international visitor flows to Australia, Australian Economic Papers, 34, 291–308.
  15. Divisekera, S. (2003). A model of demand for international tourism, Annals of Tourism Research, 30, 31–49.
  16. Dogru, T., C. Isik and Sirakaya-Turk, E. (2019). The balance of trade and exchange rates: Theory and contemporary evidence from tourism, Tourism management, 74, 12-23.
  17. Durbarry, R. (2008). Tourism Taxes: Implications for Tourism Demand in the UK, Review of Development Economics, 12(1), 21–36.
  18. Habibi, F. (2015). Iranian Tourism demand for Malaysia: a bound test approach. Iranian Economic Review, 19(1), 63-80.‏
  19. Habibi, F., & Amani, R. (2022). The impact of geopolitical risk, world economic policy uncertainty on tourism demand: evidence from Malaysia. Iranian Economic Review, 26(2), 477-488.‏
  20. Hashem Pesaran, M. (1997). An autoregressive distributed lag modelling approach to cointegration analysis, Department of Applied Economics, University of Cambridge, England, 1-33.
  21. https://www.world bank.org, information of different indicators.
  22. International country risk guide (ICRG), (2019), Country Data Online, https://www.prsgroup.com/about-us/our-two-methodologies/icrg.
  23. Irandoust, M. (2019). On the relation between exchange rates and tourism demand: A nonlinear and asymmetric analysis, the journal of economic asymmetries, 1-10.
  24. Kamali, M., Asayesh, H., & Lotfi, H. (2022). Estimating the Sensitivity of Foreign Health Tourism Demand to a Variety of Expenditures (In 5 advantageous land management areas). Journal of Tourism & Hospitality Research, 1, 15-36.
  25. Khan, H. (1998). The tourism explosion: Policy decisions facing Singapore. In Managing Tourism in Cities: Policy, Process, and Practice, New York: John Wiley and Sons, pp. 65–88.
  26. Khoshnevis Yazdi, S. & Gomami, M. (2016) Estimating the Function of Tourism Demand in Iran, Journal of Economics and Business research,12 ,1-12. (in Persian).
  27. Lancaster, K. J. (1971). Consumer Demand: A New Approach, New York: Columbia University Press,
  28. Martin, CA. and Witt, SF. (1988). Substitute prices in models of tourism demand, Annals of Tourism Research, 15(2), 255–268.
  29. Masoomzadeh, S. & Shirafkan Lemsoo, M. (2018). The Exchange Regime’s Effect on International Tourism Flow in Selected Islamic Countries (Gravity Approach). urban tourism, 4(4), 73-89. (in Persian).
  30. Mohd Hanafiah, M. H. and Mohd Harun, M. F. (2010). Tourism Demand in Malaysia: A cross-sectional pool time-series analysis, International Journal of Trade, Economics and Finance, Vol. 1, 1-5.
  31. Muzindutsi, P. F. and Manaliyo, J. C. (2016). effect of political risk shocks on tourism revenue in South Africa: Time series analysis, international journal of business and management studies, 2, 1-18.
  32. Seifollahi and A. Dehghani Ghahnavieh (2024) Examining the role of brand value congruence, dimensions of brand experience in the influence of customer-brand identification on tourism brand productivity, 16 (1), 101-122
  33. O’Donnell, R. (1987). Real and Nominal Quantities, The New Palgrave: A Dictionary of Economics, 4, 97–98.
  34. Pesaran, M. H., Y. Shin and Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships, Journal of Applied Econometrics, 3, 289-326.
  35. rafiy, H. , heydarian, S. , A., Rahnama , & etehadi, S. (2018). Impact of oil price on tourism demand: Comparison of OECD and Middle Eastern countries. Journal of Tourism and Development, 7(2), 1-17. (in Persian).
  36. Sarkodie, S. A., & Owusu, P. A. (2020). How to apply the novel dynamic ARDL simulations (dynardl) and Kernel-based regularized least squares (krls). MethodsX, 7, 101-160.‏
  37. Schmidt, D. A. (1986). Analyzing political risks, Business Horizons, 4, 43-50.
  38. Seifollahi, Naser, Hazeri, Hatef, and Janabi-Eskoi, Rosita. (2016). Studying the relationship between the tourism industry and per capita income, exchange rate and inflation in selected OECD countries, Fifth International Conference on Modern Research in Management, Economics and Accounting, St. Petersburg-Russia, 1-6. (in Persian).
  39. Soofi, A. A., Rafsanjani, SH. and Zamanian, GH. (2018). Factors Affecting Tourism Demands in Selected OIC Countries, Environmental Energy and Economic Research, 2(4), 229-236.
  40. tamizi, A., & Shahbazi, S. (2019). Check effect the volatility exchange rate on the tourism sector Iran. Journal of Tourism and Development, 7(4), 1-17. (in Persian). Witt, SF and Witt, CA. (1992). Modeling and Forecasting Demand in Tourism London: Academic Press.
  41. Zeki Dincer, M., F. Istanbullu Dincer and Ustaoglu, M. (2015). Reel effective exchange rate volatilities impact on tourism Sector in Turkey: An empirical analysis of 2003-2014, Procedia Economics and Finance, Scienedirect, 23, 1000-1008.
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