Macroeconomic Determinants of Tourism Demand Toward Emerging Markets

Öz

This research provides valuable insights into the intricate dynamics influencing tourism demand in Turkey. By delving into the relationships between transportation costs, tourists’ income levels, prices, the COVID-19 pandemic, and exchange rates, the study sheds light on the multifaceted nature of the tourism industry. The findings underscore the significance of various factors in shaping the tourism demand. Transportation costs and exchange rates are identified as critical determinants, exerting adverse effects on tourism demand. Higher transportation costs and unfavorable exchange rates can deter potential tourists However, income and prices emerged as positive influencers of tourism demand, suggesting that higher incomes and favorable price levels can stimulate tourist activity. The study’s investigation of causal relationships through advanced statistical techniques revealed valuable insights. The unidirectional causality from transportation costs and income to tourism demand highlighted the pivotal role of these factors in driving tourist behavior. Additionally, the causal relationship between prices and the exchange rate signifies the interplay between economic conditions and pricing strategies in shaping tourism demand. Overall, this research provides a deeper understanding of the complex dynamics in the Turkish tourism market, offering valuable insights for industry stakeholders and policymakers alike. JEL Classification : C13 , C33 , L83 , Z30

Anahtar Kelimeler

• Tourism demand
• Price levels
• Exchange rate
• Income
• Transportation costs
• Panel data
• Poisson-Negative binomial regression
• Panel causality

Kaynakça

1. Akis, S. (1998). A compact econometric model of tourism demand for Turkey, Tourism Management. 19 (I), 99-102. google scholar
2. Akova, O., Sarıışık, M. & Dönmez, D. (12-14 October 2011). Strategies for tourism industry under the global economic crisis: a SWOT analysis for Turkish tourism. International Conference on Eurasian Economies, Kyrgyzstan, 382-389. google scholar
3. Alegre, J., & Pou, L. (2006). The length of stay in the demand for tourism, Tourism Management. 27, 1343-1355. google scholar
4. Allen, D., Yap, G., & Shareef, R. (2009). Modelling interstate tourism demand in Australia: A cointegration approach. Mathematics and Computers in Simulation, 79, 2733-2740. google scholar
5. Assaf, A.G.; Li, G.; Song, H.; & Tsionas, M.G. (2019). Modeling and forecasting regional tourism demand using the bayesian global vector autoregressive (BGVAR) model, Journal of Travel Research. 58(3), 383-397. google scholar
6. Ayhan, F. (2019). The analysis for the impacts of exchange rate volatility on the Turkish economy’s foreign trade, Business and Economics Research Journal. 30(3), 629-647. google scholar
7. Baltagi, B.H. (2008). Econometric analysis of panel data. Chichester, UK: Fourth ed. John Wiley and Sons. google scholar
8. Baltagi, B. H. (2013). Econometric analysis of panel data. Chichester, UK: Fifth ed. John Wiley & Sons. google scholar

9. Bianchi, G., and Che, Y. (2020). The short and long-run hotel demand in Switzerland: A weighted macroeconomic approach, Journal of Hospitality & Tourism Research. 44(5), 835-857. google scholar
10. Breusch, T. S., & Pagan, A. R. (1980). The lagrange multiplier test and its applications to model specification in econometrics, The Review of Economic Studies. 47(1), 239-253. https://doi. org/10.2307/2297111 google scholar
11. Brida, J.G., & Risso, W.A. (2009). A dynamic panel data study of the German demand for Tourism in South Tyrol, Tourism and Hospitality Research. 9, 305-313. google scholar
12. Cameron, A.C. & Trivedi, P.K. (1998). Regression analysis of count data. New York: Cambridge University Press. google scholar
13. Cheng, K.M. (2012). Tourism demand in Hong Kong: income, prices, and visa restrictions, Current Issues in Tourism. 15(3), 167-181. google scholar
14. Crepon, B., Duguet, E. & Mairesse, J. (1998). Research innovation and productivity: an econometric analysis at firm level, NBER Working Paper. 6696. Cambridge, MA, p. 02138. google scholar
15. Crouch, G. (1995). A meta-analysis of tourism demand, Annals of Tourism Research. 22(1), 103-118. google scholar
16. Demirhan, E. & Demirhan, B. (2015). The dynamic effect of exchange- rate volatility on Turkish exports: parsimonious error-correction model approach, Panoeconomicus. 62(4), 429-451. google scholar
17. Divisekera, S. & Kulendran, N. (2006). Economic effects of advertising on tourism demand: a case study, Tourism Economics. 12(2), 187-205. google scholar
18. Dritsakis, N. (2004). Cointegration analysis of German and British tourism demand for Greece, Tourism Management. 25(1), 111-119. google scholar
19. Dritsakis, N., & Spiros, A. (2000). An econometric model of tourist demand: the case of Greece, Journal of Hospitality & Leisure Marketing. 7(2), 39-49. http://dx.doi.org/10.1300/J150v07n02_03. google scholar
20. Dumitrescu, E.I., & Hurlin, C. (2012). Testing for granger non-causality in heterogeneous panels, Economic Modelling. 29(4), 1450-1460. google scholar
21. Durbarry, R. & Sinclair, T.M. (2003). Market shares analysis the case of French tourism demand, Annals of Tourism Research. 30(4), 927-941. google scholar
22. Eurostat (2021a). Consumer Price Indices. Accessed at http://ec.europa.eu/eurostat/web/hicp/ data/ database (accessed October 14, 2021). google scholar
23. Eurostat (2021b). National Accounts. Accessed at http://epp.eurostat.ec.europa.eu/portal/page/ portal/statistics/search_database (accessed October 14, 2021). google scholar
24. Federal Reserve Bank of St. Louis (2021). Economic data-consumer price index of all items index 2010=100, Economic Research Division. Accessed at http://research.stlouisfed.org/fred2 (accessed October 17, 2021). google scholar
25. Martins, L.F., Yi, G. & Alexandra, F.L. (2017). An empirical analysis of the influence of macroeconomic determinants on world tourism demand, Tourism Management. 61, 248-260. google scholar
26. Fourie J., Rossell’o-Nadal J. & Santana-Gallego, M. (2019). Fatal attraction: how security threats hurt tourism, Journal of Travel Research. 58, 1-11. google scholar
27. Gasmi, A., & Sassi, S. (2015). International tourism demand in Tunisia: evidence from dynamic panel data model, Economics Bulletin. 35(1), 507-518. google scholar
28. Granger, C.W. (1969). Investigating causal relations by econometric models and cross-spectral methods, Econometrica: Journal of the Econometric Society. 37(3), 424-438. google scholar
29. Greene, W. (2008). Econometric Analysis. New Jersey: sixth ed. Pearson International Edition. google scholar
30. Habibi, F., & Rahim, K.A. (2009). A bound test approach to cointegration of tourism demand, American Journal ofApplied Sciences. 6(11), 1924-1931. google scholar
31. Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal. 3(2), 148-161. https://doi.org/10.1111/1368-423x.00043 google scholar
32. Hadri, K., & Kurozumi, E. (2012). A simple panel stationarity test in the presence of serial correlation and a common factor, Economics Letters. 1 15, 31-34. https://doi.org/10.1016/j. econlet.2011.11.036 google scholar
33. Henseler, M., Maisonnave, H.& Maskaeva, A. (2021). Economic impacts of covid-19 on the tourism sector in Tanzania, Working Papers hal-03501722. HAL. google scholar
34. Huyugüzel Kışla, G. Ş., Türkcan, B. & Ince Yenilmez, M. (2023). How covid-19 has affected supply and demand within tourism industry, Journal of Multidisciplinary Academic Tourism. 8(1), 39-49. google scholar
35. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels, Journal of Econometrics. 115(1), 53-74. https://doi.org/10.1016/S0304-4076(03)00092-7 google scholar
36. Jintanee, J., Sriboonchitta, S., Calkins, P. & Chaiboonsri, C. (2011). Thailand’s international tourism demand: seasonal panel unit roots and the related cointegration model, Review of Economics & Finance. 1, 63-76. google scholar
37. Kulendran, N. & Witt, S.F. (2001). Cointegration versus least squares regression, Annals of Tourism Research. 28(2), 291-311. google scholar
38. Lejarraga, I., & Walkenhorst, P. (2013). Economic policy, tourism trade and productive diversification. International Economics, 135, 1-12. google scholar
39. Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties, Journal of Econometrics. 108(1), 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7 google scholar
40. Lim, C. (1997). Review of international tourism demand models, Annals of Tourism Research. 24(4), 835-849. google scholar
41. Lim, C., & McAleer, M. (2000). A seasonal analysis of Asian tourist arrivals to Australia, Applied Economics. 32(4), 499-509. google scholar
42. Lim, C., & McAleer, M. (2002). Time series forecasts of international travel demand for Australia, Tourism Management. 23, 389-396. google scholar
43. Meo, M.S., Chowdhury, M.A.F., Shaikh, G.M., Ali, M. & Sheikh, S.M. (2018) Asymmetric impact of oil prices, exchange rate, and inflation on tourism demand in Pakistan: new evidence from nonlinear ARDL, Asia Pacific Journal of Tourism Research. 23(4), 408-422, doi: 10.1080/10941665.2018.1445652 google scholar
44. Munoz, G.T. (2007). German demand for tourism in Spain, Tourism Management. 28, 12-22. google scholar
45. Nadal, J.R. & He, J. (2020). Tourist arrivals versus tourist expenditures in modelling tourism demand, Tourism Economics. 26(8), 1311-1326. google scholar
46. O’Connell, P. (1998). The overvaluation of purchasing power parity, Journal of International Economics. 44, 1-19. google scholar
47. OECD (2021a). Main Economic Indicators-Complete Database. Main Economic Indicators (database), Accessed at http://www.oecd-ilibrary.org/economics/data/main-economic-indicators/main-economic-indicators-complete-database_data-00052-en (accessed October 14, 2021). google scholar
48. OECD (2021b). Aggregate National Accounts: Gross Domestic Product. OECD National Accounts Statistics (database), Accessed at: http://www.oecd-ilibrary.org/economics/data/aggregate-national-accounts/gross-domestic-product_data-00001-en (accessed October 14, 2021). google scholar
49. OECD (2021c). National Income. Accessed at http://stats.oecd.org/Index.aspx?DataSetCode= SNA_ TABLE2 (accessed October 14, 2021). google scholar
50. Ouerfelli, C. (2008). Cointegration analysis of quarterly European tourism demand in Tunisia, Tourism Management. 29, 127-137. google scholar
51. Petrovic, P., & Gligoric, M. (2010). Exchange rate and trade balance: j-curve effect, Panoeconomicus. 1, 23-41. Doi: 10.2298/PAN1001023P google scholar
52. Republic of Turkey Ministry of Culture and Tourism. 2022. “General Tourism Statistics for 2021.” http:// yigm.kulturturizm.gov.tr/TR-232959/arastirma-ve-raporlar.html (accessed March 12, 2022). google scholar
53. Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels, Cambridge Working Papers, Economics. 1240(1), 1. google scholar
54. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence, Journal of Applied Econometrics. 22, 265-312. https://doi.org/10.1002/jae google scholar
55. Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias-adjusted LM test of error cross-section independence, Econometrics Journal. 11(1), 105-127. https://doi.org/10.1111/j.1368-423X.2007.00227.x google scholar
56. Salleh, H.M.N., Othman, R. & Ramachandran, S. (2007). Malaysia’s tourism demand from selected countries: the ARDL approach to cointegration, International Journal of Economics and Management. 1(3), 345-363. google scholar
57. Schiff, A., & Becken, S. (2011). Demand elasticity estimates for New Zealand tourism, Tourism Management. 32, 564-575. google scholar
58. Shafiullah, M.O. Emeka, O.L. & Usman, K. (2019). Determinants of international tourism demand: evidence from Australian states and territories, Tourism Economics. 25(2), 274-296. google scholar
59. Sharma, C. and Pal, D. (2020). Exchange rate volatility and tourism demand in India: unraveling the asymmetric relationship, Journal of Travel Research. 59(7), 1282-1297. google scholar
60. Song, H., Li, G., Witt, S.F., & Baogang, F. (2010). Tourism demand modelling and forecasting: how should demand be measured?, Tourism Economics. 16 (1), 63-81 google scholar
61. Song, H., Gao, B.Z., & Lin, V.R. (2013). Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system, International Journal of Forecasting. 29(2), 295-310. google scholar
62. Tang, J., Sriboonchitta, S., Ramos, V. & Wong, W.-K. (2016). Modeling dependence between tourism demand and exchange rate using the copula-based GARCH model, Current Issues in Tourism. 19(9), 876-894. google scholar
63. Tatoğlu, F.Y. & Gül, H. (2020). Analysis of tourism demand using a multi-dimensional panel gravity model, Tourism Review. 75(2), 433-447. google scholar
64. Tavares, J.M. & Leitao, N.C. (2017). The determinants of international tourism demand for Brazil, Tourism Economics. 23(4), 834-845. google scholar
65. The Bulgarian National Bank (2021). Macroeconomic Indicators. Accessed at http://www.bnb.bg/ Statistics/index.htm (accessed October 14, 2021). google scholar
66. The Central Bank of The Russian Federation (2021). Consumer Price Index: All Items. Accessed at http://www.cbr.ru/eng/ (accessed October 14, 2021). google scholar
67. The European Central Bank (2021). Statistical Data Warehouse. Accessed at http://sdw.ecb.europa. eu/ (accessed October 14, 2021). google scholar
68. The National Bank of Georgia (2021). Consumer Price Index. Accessed at https://www.nbg.gov.ge/ index.php?m=306 (accessed October 13, 2021). google scholar
69. The U.S. Energy Information Administration-EIA (2021). Imported Crude Oil Price (real, $/barrel). Accessed at http://www.eia.gov/forecasts/steo/realprices/real_ prices.xlsx (accessed August 13, 2021). google scholar
70. The World Bank (2021). Global Economic Monitor. Accessed at http://data.worldbank.org/ data-catalog/global-economic-monitor (accessed October 13, 2021). google scholar
71. Travelmath (2021). Distance Calculator. Accessed at http://www.travelmath.com/distance/ (accessed November 19, 2021). google scholar
72. TUIK (2022). Turkish Statistical Institute Tourism Statistics: The Number of Foreigners Arriving in Turkey by Nationalities According to Term. Accessed at http://tuikapp.tuik.gov.tr/turizmapp/ menuturizm.zul (accessed March 12, 2022). google scholar
73. Tunçsiper, Ç., & Horoz, İ. (2023). The effect of exports on economic growth Türkiye 1980-2021, Journal of Emerging Economies and Policy. 8(1), 65-72. google scholar
74. Ulucak, R., Yücel, A.G. & İlkay, S.C. (2020). Dynamics of tourism demand in Turkey: panel data analysis using gravity model, Tourism Economics. 26(8), 1394-1414. google scholar
75. UNCTAD (2013). United Nations Conference on Trade and Development-UNCTAD Handbook of Statistics 2013. New York: UN Publications. google scholar
76. UNWTO (2021). United Nations World Tourism Organisation Tourism Highlights 2020 Edition. Accessed at http://dtxtq4w60xqpw.cloudfront.net/sites/all/files/pdf/unwto_ highlights14_en. pdf (accessed Mar 5, 2022). google scholar
77. UNWTO (2022). World Tourism Barometer. Accessed at https://www.e-unwto.org/loi/ wtobarometereng (accessed March 5, 2022). google scholar
78. Vanegas, M.S. (2009). Tourism demand response by residents of Latin American countries, International Journal of Tourism Research. 11, 17-29. google scholar
79. Wang, Y. (2009). The Impact of crisis events and macroeconomic activity on Taiwan’s international inbound tourism demand, Tourism Management. 30, 75-82. google scholar
80. Webber, G.A. (2001). Exchange rate volatility and cointegration in tourism demand, Journal of Travel Research. 39(4), 398-405. google scholar
81. Westerlund, J. (2008). Panel cointegration tests of the fisher effect, Journal of Applied Econometrics. 23(2), 193-233. https://doi.org/10.1002/jae google scholar
82. Witt, F.S., & Witt, C. (1995). Forecasting tourism demand: a review of empirical research, International Journal of Forecasting. 11(3), 447-475. google scholar
83. Yamaura, K., & Thompson, A. (2015). Analysis of tourism demand model across European source countries, Tourism Planning & Development. 12(2), 145-154. Doi:10.1080/21568316.2014.925487 google scholar
84. Yazdi, S.K. & Khanalizadeh, B. (2017). Tourism demand: a panel data approach, Current Issues in Tourism. 20(8), 787-800, doi: 10.1080/13683500.2016.1170772 google scholar