Long-Run Nexus Between Tourism Receipts And Economic Growth: Empirical Evidence from Turkey

Tourism is the most affected sector positively and negatively from globalization. With globalization, communication and information transfer have gained an extraordinary speed. Being aware of the world has increased the curiosity of the people and the desire to see the places they have not seen before, to know the cultures they do not know and to try the foods and drinks they have never tasted. Developments in transportation technology have facilitated the satisfaction of these requests. In parallel with these developments, increasing tourism activities contribute positively to the economy. However, all kinds of natural disasters, wars, epidemics, terrorist incidents, political tensions and financial crises negatively affect the tourism sector. This negation has a negative effect on the economy. Tourism, which is the lowest cost way to earn foreign exchange revenue compared to other sectors, is also the most fragile sector of the economy due to the risks mentioned above.

Tourism is a constantly evolving sector in Turkey as it is in the entire world. Turkey became a member of UNWTO (United Nations World Tourism Organisation) in 1975 to develop tourism. UNWTO is the united nations agengy, which promotes tourism as a driver of economic growth, is responsible the sustainable and universally accesible tourism (UNWTO). Turkey has also made arrangements at the national level to improve the tourism industry. The first important regulation is the Tourism Incentive Law, which was enacted in 1982 (mevzuat.gov.tr). With this law, it has been aimed to increase the investments to be made in tourism. While the number of tourists coming to Turkey in the early 1990s was 5.3 million people, it exceeded 30 million people in 2001 (TUROFED,2018:18) In 2018, Turkey ranked 6th in the world in the category of countries preferred by tourists as destinations with approximately 46 million people. In the European rankings at the same year, ranked in the 4th place. The top five countries sending the most tourists to Turkey are, respectively, Russia, Germany, Bulgaria, England and Iran (wikivisually).

Tourism is an invisible export item in the services section of the current account of the balance of payments. Tourism accounts for 40% of all services trade worldwide and makes a significant contribution to economic growth. The following table shows the share of tourism revenues in exports over the years.

In addition to its positive impact on national income, tourism is an important sector as it also provides foreign currency income. As seen in Table-1, tourism revenues are constantly increasing.

The tourism sector also contributes to the elimination of external deficits and the improvement of the balance of payments.

The ratio of tourism revenues to meet the foreign trade deficit in 2018 was 53.64%.

In 2018, Turkey's tourism revenues totaled $ 34.5 billion and the average expenditure of tourists was $666. The circulation of tourism revenues within the country creates a multiplier effect, stimulating other investments and expenditures and contributing to economic growth.

The tourism sector is also very important in terms of employment. Nowadays, tourism contributing %9 of the global GDP and accounts for one in eleven jobs worldwide (wwtc). The share of tourism in Turkey's total employment is 7% (Resort, 2020:10).

The objective of the empirical analysis is to reveal the relationship between economic growth and tourism revenues of Turkey for the period 1995-2018. The variables used in the research are gross domestic product ( constant 2010, US $) and international tourism receipts (current, US $). International tourism receipts are expenditures by international inbound visitors, including payments to national carriers for international transport. These receipts include any other prepayment made for goods or services received in the destination country. They also may include receipts from same-day visitors, except when these are important enough to justify separate calssification.

The data used in the research were obtained from World Bank and OECD. In the analysis, E-Views package program was used.

The analysis was started by performing stationary testing. Stability was tested by Augmented Dickey-Fuller (1979) method. Johansen Cointegration Test was conducted to determine the existence of long-term relationship between variables. Finally, the model was estimated by the Least Squares method.

Working with non-stationary series causes two fundamental problems. The first of these is that the predictions to be made with the obtained regression models are not reliable. The other is the false regression problem. False regression does not reflect the true degree of relationship between two variables, but rather the common tendency found within them. The following graphs show that the variables are not stationary and have an increasing trend.

As seen in Table-4, LOGGDP became stationary after taking the second difference and LOGRECEIPTS after taking the first difference. The Ho hypothesis that the series have a unit root is rejected. The graphics below confirm that the series are stationary. The next step is to determine whether there is a long-term relationship between the two series with the help of cointegration analysis.

Cointegration analysis provides an investigation into whether linear combinations of those variables are static if the integration degrees of non-stationary time series variables are the same. In this study, the presence of co-integration between variables was investigated using the Johansen co-integration test.

Johansen and Juselius (1990) developed the Maximum Likelihood Estimation and Likehood Ratio tests to test the cointegration hypothesis. Johansen test the ECM (Error Corection Model) form of the first differences is as follows:

ΔX1 = Γ t ΔXt-1 + …+ Γ k+1 ΔXt-k + ΠXt-k + μ + εt ve εt ~ N (0, Λ) t = 1, . . . , T.

Here Π, (nXn) matrix, Γ t , . . . , Γ k+1 parameter’s matrix, , Xt (nXn) is first level unit root vector, μ (nX1) is vector constant value, εt is error term vector and Λ (nXn) is covariance matrix. Since ΔX1 I (0) in the equation, the right side is stationary only if ΠXt-k is stationary.

In the cointegration test, the Johansen approach is based on the Likelihood Ratio test and is tested according to the n-r unit root hypothesis versus the n-r-1 unit root alternative hypothesis. Two separate tests, Trace and max statistical test, are used.

Λmax = -T Σi = r +1 ln (1- Λi), r = 0, . . . ,n-1.

where Λi is maximum eigenvalue . And Max statistic test is as fallows,

Λmax =-T ln(1- Λi )

Both Trace Test and Maximum Eigenvalue Test statistics have detected two cointegrator equations between variables. It is understood that there is a long-term positive relationship between the series.

The probability of the coefficients and the probability of the F statistic confirm that the model is statistically significant in the %95 confidence interval. So we can estimate the model as;

ln GDP= 23.25824 + 0.211720 ln RECEIPTS

There is a positive relation between economic growth and tourism receipts. If tourism receipts increases %1, GDP will increase %0.21.

The need to increase income level, employment and foreign exchange reserves is a common problem of developing economies. To overcome this problem, the contribution of each sector to the economy needs to be known clearly. In this study, the contribution of tourism sector to Turkish economy was examined. According to the study's findings, tourism is very important for Turkey in terms of increasing employment and foreign exchange reserves. According to empirical analysis findings, there is a positive relationship between economic growth and tourism revenues in the long run. For this reason, increasing the tourism investments will be beneficial for the country's economy. Another finding of the research is that every 1% increase in tourism revenues contributes 0.21% to economic growth. Each investment in tourism, with its multiplier effect, will generate more revenue growth than the investment made.