Predicting The Share of Tourism Revenues In Total Exports
Predicting The Share of Tourism Revenues In Total Exports
Tourism revenues are a significant source of income under the current account service item of countries. These revenues are not included in exports, despite being compared with the export revenues of the countries and in economics the ratio of tourism revenues to export revenues is used as an indicator. In developing economies, tourism revenues play a role in closing the current account deficit. The prediction of this rate in countries with foreign trade deficit is important in developing tourism, export and import policies for the future. In this study, multiple linear regression method (MLR), one of the traditional methods, and the artificial neural network method (ANN), one of the machine learning methods were used to estimate the rate of tourism revenues of the sample country Turkey to its export revenues. In the model of the study covering 2004-2020 period, the number of tourists received, total income from tourism, average expenditure by tourists per capita, population, total export revenue, growth rate, Euro/TL and US Dollar/TL rates were chosen as independent variables. As a result of the study, the R2 value was found to be 91.7% for ANN and 90.8% for MLR which were very close to the ideal value. According to the predicts made on the model developed based on this, the rate of Turkey's tourism income to total export income in 2025 is estimated as 31.83% according to ANN; 32.73% according to MLR while in 2030, it is estimated to be 33.25% according to ANN and 36.78% according to MLR.
Keywords:
Tourism, export foreign exchange, machine learning, Turkey,
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- Altındağ, İ., & Özlem, A. (2021). Determining the Importance Levels of Factors Affecting Tourism Income in Turkey. Adiyaman University Journal of Social Sciences(37), 397-426.
- Bingöl, N., Pehlivan, C., & Han, A. (2020). Empirical Investigation of the Relationship Between Tourism Receipts and Macro Variables for Turkey. Ekev Akademi Journal, 24(82), 245-262.
- Bishop, C. M. (1995). Neural networks for pattern recognition. Oxford university press.
- Bozkurt, K. (2021). The Effect of International Tourism Expenditures on Foreign Trade Volume in OECD Countries Karamanoğlu Mehmetbey University].
- Cinel, E. A., & Yolcu, U. (2021). The Effect of Tourism Revenues on Foreign Trade Balance in Turkey: The Comparison of Forecasts Obtained Via Different Neural Networks Journal of Social Sciences And Education, 4(1), 98-118.
- Çuhadar, M. (2020). A comparative study on modelling and forecasting tourism revenues: The case of Turkey. Advances in Hospitality and Tourism Research (AHTR), 8(2), 235-255.
- Demir, E., & Bahar, O. (2022). The relationship between tourism revenues and external borrowing: an empirical analysis on Turkey. International Journal of Social Sciences and Education Research, 8(1), 87-98.
- Kutlu, B., & Badur, B. (2009). Stock market index prediction with artificıal neural networks. Istanbul Management Journal, 20(63), 25-40.
- Nguyen, L. Q., Fernandes, P. O., & Teixeira, J. P. (2021). Analyzing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks. Forecasting, 4(1), 36-50.
- Özkurt, İ. C., & Bilgir, B. (2022). The Relationship of Tourism Revenues and Economic Growth in Turkey: The Ardl Approach. International Journal of Management Economics and Business, 18(1), 277-303.
- Öztemel, E. (2012). Artificial neural networks. Papatya.
- Palmer, A., Montano, J. J., & Sesé, A. (2006). Designing an artificial neural network for forecasting tourism time series. Tourism management, 27(5), 781-790.
- Republic of Turkiye Ministry of Culture and Tourism. (2007). Turkey Tourism Strategy Action Plan. https://www.ktb.gov.tr/Eklenti/906,ttstratejisi2023pdf.pdf?0
- Şen, A., & Şit, M. (2015a). The Empirical Analysis of Real Exchange Rate Impact on Turkey’s Tourism Receipts. Journal of Yaşar University, 10(40), 6752-6762.
- Şen, A., & Şit, M. (2015b). Role and Importance of Tourısm Receipts in Turkish Economy. Dicle University Journal of Economics and Administrative Sciences, 5(8), 30-45.
- Temel, G. O., Erdogan, S., & Ankaralı, H. (2012). Usage of Resampling Methods for Evaluating the Performance of Classification Model International Journal of Informatics Technologies Bilişim Teknolojileri Dergisi, 5(3), 1-8.
- Usmani, G., Akram, V., & Praveen, B. (2021). Tourist arrivals, international tourist expenditure, and economic growth in BRIC countries. Journal of Public Affairs, 21(2), e2202.
- Yayın Aralığı: Yılda 2 Sayı
- Başlangıç: 2013
- Yayıncı: Bahadır Fatih YILDIRIM
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