This study analyzed the effect of tourism on Turkey's economic performance from 2003-2014. Tourism receipts and real exchange rates were examined as independent variables impacting GDP as the dependent variable. The results showed: 1) A positive linear relationship between tourism receipts and GDP, indicating a 1% increase in receipts increases GDP by 0.1%. 2) A negative linear relationship between real exchange rates and GDP, as a 1% increase in rates decreases GDP by 0.47%. 3) No omitted variables, multicollinearity, heteroskedasticity, autocorrelation issues in the model. Tourism receipts can thus be considered an important factor for Turkey's economic growth.

1. THE EFFECT OF TOURISM ON ECONOMIC PERFORMANCE IN TURKEY (2003-2014)
Uğur Aras,Tolga Nehariye,Rümeysa Danışman and Meziyet Metin
Department of Econometrics,Cukurova University,Adana,Turkey
Abstract: Thisstudyaimsto investigate the effectof tourismon economicperformance inTurkey
overthe periodof 2003-2014.In thisstudyGDP isa dependentvariableasaneconomicperformance
indicator.The explanatoryvariablesare TR(Total TourismReceipts) andREER (real effective exchange
rate).All datahasbeen takenfromWorldDevelopmentIndicators- WorldBankandRepublicof
TurkeyMinistryCulture andTourism. The STATA 11 programme isusedfor analyses.TheOLSmethod
isusedto analyze the data and the relationshipbetweenindependentvariablesandthe dependent
variable is examinedbasedonthe valuesof parameters.Inaddition,testresultsshow the positive
significantlinearrelationshipbetweentourismandgrossdomesticproductaltoughthe relationship
betweenreal effectiveexchangerate andgrossdomesticproductislinearnegative significantlyin
Turkeyas expected.
Key words: TourismReceipts,EconomicPerformance,Real EffectiveExchange Rate,GrossDomestic
Product,OrdinaryLeastSquares,Turkey
LITERATURE RESEARCH
Tourism is travel for pleasure; also the theory and practice of touring, the business of attracting,
accommodating, and entertaining tourists, and the business of operating tours. Tourism may be
international,orwithinthe traveler'scountry.The WorldTourismOrganizationdefinestourism more
generally,intermswhichgo"beyondthe commonperceptionof tourism as being limited to holiday
activityonly",as people "traveling to and staying in places outside their usual environment for not
more than one consecutive year for leisure, business and other purposes". The tourism is the forth
sector of the world economy.
Eventhoughthe domestictourismwithregardtopilgrimages,spatourismand summerresortshas a
longtraditioninTurkey(Seckalman(2002)), Turkey has entered the intemational tourism market in
Iate 1980s. Afterthe Turkish govemmentbegantoregardthe importance of intemational tourismfor
economic development and as a source of foreign exchange, it established some tourism facilities
and provided incentives for private investment.
Tourism has a positive effects on domestic and external trade, development of various sectors
(transportation,construction,furniture,souveniretc.) andcurrencyinput.Investmentsfortourismin
the country is increasing every day due to these effects.
Although the tourism sector has grown rapidly in Turkey. Three sides of Turkey is covered by sea.
Climate issuitable forfourmonths for winter sports. Also South part of Turkey ‘s climate is suitable
for six months for summer tourism.

2. EMPIRICAL ANALYSIS AND DISCUSSION
Variables subject to empirical analysis in this study based on the previous empirical works on the
relationshipbetweentourism and economic growth.The data is annual data on real Gross Domestic
Product(GDP),real Effective Exchange Rate (REER) andreal total Tourism Receipts (TR) covering the
period2003-2014.All data has beenobtained from World Development Indicators- World Bank and
Republic of Turkey Ministry Culture and Tourism.All variables used in the empirical analysis are
transformed variables by the use of natural logarithms.Logarithmic transformations are also a
conveniant means of transforming a highly skewed variable into one that is more approximetly
normal also using the logarithm of one or more variables instead of the un-logged form makes the
effective relationship non-linear,while still preserving the linear model (K.Benoit,2011).
Table 1: OLS estimation of the model
The OLS estimation shows the linear relationship between dependent variable LNGDP and the
independentvariablesLNREERandLNTR.In thisanalysisalphalevel isdeterminedas5%.According to
estimationoutput all t-statisticsprobabilityvaluesare less thanalpha level (0.05) , it proofs that the
null hypothesiswhich indicates βi isequal tozerois rejectedforthe each coefficients that means all
of the coefficients are significant.The overall significancy of the model is based on f-statistics
test.According to f-statistics ,the probability value is less than alpha level which means the null
hypothesisthatall βisare equal tozero is rejected so the model is overall significant.R-squared and
adj R-squaredare the statistical measure of how close the dataare to the fittedregressionline.Based
on the R-squaredandadj R-squared valuesonoutput,the goodnessof fitfor this model is about 66%
which means the dependent variable is well-explained by independent variables.
LNGDP = 2.71974 + 0.449767 LNTR -0.4725022 LNREER (1)
Accordingtoequationabove, there isalinearpositiverelationshipbetweengrossdomestic product
and total tourismreceiptsso a 1% increase in tourism receipts will increase gross domestic product
by nearly 0.10%.There is a linear negative relationship between gross domestic product and real
effectiveexchangerate so a 1% increase inreal effective exchange rate will decrease gross domestic
product by nearly 0.47%.The coefficients of independent variables are also known as elasticity of
each independent variables in double-log models.
_cons 2.71974 .4433676 6.13 0.000 1.716773 3.722708
LNTR .449767 .1064686 4.22 0.002 .2089183 .6906158
LNREER -.4725022 .1252003 -3.77 0.004 -.755725 -.1892794
LNGDP Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total .00749908 11 .000681735 Root MSE = .01661
Adj R-squared = 0.5953
Residual .002482787 9 .000275865 R-squared = 0.6689
Model .005016293 2 .002508147 Prob > F = 0.0069
F( 2, 9) = 9.09
Source SS df MS Number of obs = 12

3. THE MODEL SPECIFICATION TESTS
In thispart the model specificationtestsare examinedtocheckvalidityof the model.
Table 2: Ramsey RESET Test
AccordingtoRamseyRESET Testresult,probabilityvalueof the testisgreaterthan 0.05 alphalevel
whichmeansthe null hypothesisthat shownabove isacceptedsothere isnoomittedvariable inthe
model.
Table 3:Variance Inflation Factor (VIF) for Multicollinearity
The formulaof VIF iscalculatedas VIF=1/(1-RK
2
) andexpectedtobe lessthan 10.Accordingto table
above,the VIFvalue islessthan10 whichmeansthere isnomulticollinearitybetweenindependent
variables.
Table 4: Breusch-Pagan and Cook-Weisberg Test for Heteroskedasticity
Accordingtotable 4, probabilityvalue of chi-square testisgreaterthan0.05 alphalevel itmeans
that the null hypothesishasgivenabove isacceptedso there isnoheteroskedasticityerrortermof
everyith
observationhasaconstant variance.
Prob > F = 0.3451
F(3, 6) = 1.35
Ho: model has no omitted variables
Ramsey RESET test using powers of the fitted values of LNGDP
Mean VIF 8.63
LNTR 8.63 0.115935
LNREER 8.63 0.115935
Variable VIF 1/VIF
Prob > chi2 = 0.9095
chi2(1) = 0.01
Variables: fitted values of LNGDP
Ho: Constant variance
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity

4. Table 5: Breusch-Godfrey LM Test for Autocorrelation
According to table above, probability value of chi-square is greater than 0.05 alpha level which
meansthe null hypothesishasgivenabove isacceptedso there is no autocorrelation between error
terms of ith
observations.
Table 6:Skewness / Kurtosis Tests for Normality and Distribution Graph
Accordingto normalitytestthe probabilityvalue of the chi-square isgreaterthan0.05 alphalevel it
meansthe null hypothesiswhichindicatesthatthe residualsare normallydistributedisacceptedso
our model holdsfornormality.The graphhasgivenbelow alsoshowsthe normal distributionof
residuals.
H0: no serial correlation
1 0.147 1 0.7015
lags(p) chi2 df Prob > chi2
Breusch-Godfrey LM test for autocorrelation
myResiduals 12 0.8289 0.1277 2.81 0.2455
Variable Obs Pr(Skewness) Pr(Kurtosis) adj chi2(2) Prob>chi2
joint
Skewness/Kurtosis tests for Normality
-.02-.01
0
.01.02.03
Residuals
3.08 3.1 3.12 3.14 3.16
Fitted values

5. CONCLUSION
The main goal of this study was to asses the relationship between total tourism receipts and
economic performance with using Turkish data over the period of 2003-2014.The model was
estimated with OLS method and the empirical results shows that there is a linear positive
relationshipbetweenTourismReceiptsandGDP.Obviously,these findings and literature researches
showthe importance of tourismin Turkish economy.In this sense, it can be argued that the tourism
receipts can be regarded as a powerful factor for economic growth and economic policies directed
the developtourism have importantrolesforthe growthof the economyandthe appreciationof the
local currency.
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