This article was downloaded by: [Beijing Normal University]On: 13 March 2015, At: 23:54Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UKClick for updatesCurrent Issues in T ourismPublication details, including instructions for authors and subscription information:/loi/rcit20The interaction between tourism and FDI in real estate in OECD countriesHassan Gholipour Fereidouni a& Usama Al-mulalibaSchool of Management, Universiti Sains Malaysia, Penang,MalaysiabEconomic Programe, Universiti Sains Malaysia, Penang, Malaysia Published online: 30 Oct 2012.PLEASE SCROLL DOWN FOR ARTICLETaylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However , Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,D o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015CURRENT ISSUES IN TOURISM LETTERThe interaction between tourism and FDI in real estate in OECD countriesHassan Gholipour Fereidouni a ∗and Usama Al-mulali baSchool of Management,Universiti Sains Malaysia,Penang,Malaysia;b Economic Programe,Universiti Sains Malaysia,Penang,Malaysia(Received 17July 2012;final version received 5September 2012)The purpose of this article is to investigate the empirical link between foreign direct investment (FDI)in real estate sector (FDIRE)and international tourism (TOUR).Panel co-integration and panel Granger causality techniques are applied to analyse both long-and short-run relationships for the case study of selected OECD countries.Our empirical results show the existence of the long-run and a bi-directional causal relationship between FDIRE and TOUR.The results provide some implications for policy-makers.Keywords:FDI in real estate;tourism flows;panel cointegration;OECD countriesIntroductionIn recent years,there has been a growing interest in analysing the relationship between foreign direct investments (FDI)and tourism (Craigwell &Moore,2007;Kundu &Con-tractor,1999;Sanford &Dong,2000;Selvanathan,Selvanathan,&Viswanathan,2009;Tang,Selvanathan,&Selvanathan,2007).This literature proposes several explanations for the links between these variables.On the one hand,the relationship by which tourism affects FDI can be explained as follows.International tourism (TOUR)allows potential investors to experience first-hand the environment of the country being visited and to obtain information about the available investment opportunities.By experiencing the country’s goods and services,opportunities for investment may be identified (Sanford &Dong,2000).Moreover,firms’FDI decisions require detailed information about the host country’s competitors,regulatory environment,work ethic,and culture.Tourism improves on existing research into FDI and as a result it can contribute to the expansion of new FDI in host country (Sanford &Dong,2000).On the other side,the causality nexus in the sense FDI causes tourism can appear since foreign investors provide the tourism capacity that the country is lacking,by building more hotels and tourism attractions (such as theme park)and improving the transport facilities,which then stimulates or allows the country to accommodate a larger number of visitors (Craigwell &Moore,2007;Tang et al.,2007).Another link from FDI to tourism is through business tourists.Business tourists are entrepreneurs and managers from other countries who,while looking for opportunities to invest in host country as well as to promote and sustain business in host country,visit several tourist destinations (Selvanathan et al.,2009).In fact,more FDI inflow could generate a cyclical effect of investigative business and holiday travel,resulting in greater tourism (Tang et al.,2007).Current Issues in Tourism ,2014V ol.17,No.2,105–113,/10.1080/13683500.2012.733359D o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015While there has been a series of articles that examined the relationship between tourism and aggregate FDI,very few empirical studies have examined the relationship between FDI in real estate (FDIRE)and tourism.In fact,the question of the relationship between tourism and FDIRE has only recently started to be addressed in the empiricalliterature.For example,Gholipour and Masron (2011)and Rodrı´guez and Bustillo (2010)found that tourism agglomeration in a host country is a significant and major determinant of FDIRE.In another study,Sanford and Dong (2000)showed that tourism has a positive and significant impact on new FDI.However,no empirical studies have examined the direction of causality between FDIRE and tourism.To address the knowledge gap,this study investigates the short-run and the long-run dynamic interactions between FDREI and TOUR in OECD countries using cointegration and Granger causality tests.OECD countries have been chosen for the present study due to the availability of data for FDIRE and low restriction on foreign investment in real estate sectors.In addition,OECD countries are among the most important tourism des-tinations in the world.There are two ways that tourism can cause FDIRE.First,investment in real estate by foreigners in a host country is influenced by the acquisition of information about the attrac-tiveness of host country as a holiday destination.Thus,tourism can be considered as the firststep before acquiring a property abroad (Rodrı´guez &Bustillo,2010)because foreign investors may identify property investment opportunities that could lead to property trans-actions in following periods.Second,FDI in real estate development and investment follows their customers (international tourists)when choosing locations for investments (He,Wang,&Cheng,2009).On the other hand,the increased FDIRE (in particular foreign investment in residential properties)raises tourism in the host countries becausetourism is the next step after acquiring a property in a foreign country (Rodrı´guez &Bus-tillo,2010).Moreover,foreign real estate foreign investors provide tourism capacity such as hotels and tourism attractions and improve the transport facilities,which then stimulates or allows the country to accommodate a larger number of visitors (Craigwell &Moore,2007;Tang et al.,2007).The analysis of the relationship between tourism and FDIRE is relevant for at least two reasons.First,recent research finds that FDIRE and tourism have encouraged the economic development in many countries (Cortes-Jimenez &Pulina,2010;Ning &Yu,2009).For that reason,the study of the potential complementary relationship between flows of investments in real estate and TOUR is of major interest,as it can promote economic growth.Second,this relationship is of particular relevance for policy-makers since several observers suggest that one of the main requirements of real estate recovery after 2008financial crisis is tourism recovery (Jones Lang LaSalle,2009).Our article also contributes to the literature in two ways.First,although several articles provide evidence supporting a relationship between FDIRE and tourism,these articles focus their analyses on FDIRE inflows (FDIREI).However,there are no articles that study this relationship considering FDIREI,FDIRE outflows (FDIREO)and tourism arrival and departure at the same time.Second,previous studies used time-series analyses to investigate the causality between FDIRE and tourism.In the present study,we apply panel cointegration techniques to study the short-and long-run nexus between two flows.The article is organised as follows.Section 2presents some facts for the tourism and FDIRE in OECD countries.Section 3explains the data and the source of data.Section 4discusses the methodology and presents the empirical results.Finally,in Section 5,some 106H.G.Fereidouni and U.Al-mulaliD o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015Tourism and FDI in real estate in OECD countriesThis section presents some facts for the tourism and FDIRE in OECD countries.Tourism is a key component of the service economy,which is growing in most OECD countries as these societies become more mobile and prosperous.During the period from 1995to 2009,the number of international tourist arrival and departure increased across much of the OECD countries.Figures 1and 2illustrate the evolution of international tourist arrival and departure for a set of OECD countries.In terms of revenues,OECD countries generate about 70%ofworld tourism activity (Santana-Gallego,Ledesma-Rodrı´guez,&Pe ´rez-Rodrı´guez,2011).Moreover,tourism GDP accounts for up to 11%of GDP and even more in terms of employment in 2010in the OECD area (OECD,2010).Table 1shows the evolution of FDIRE (FDIREI and FDIREO)for a set of OECD countries.The last two decades have witnessed a growth in FDIRE across much of OECD countries.It is largely due to the regional and international economic integration,continued privatisation,liberalisation of investment regimes,protection and promotion of FDI as well as maturity of their real estate markets (in terms of higher levels of liquidity,superior return,and diversification).The growth is more apparent in less-developed OECD countries such as South Korea,Turkey,Hungary,and Poland.DataThe analysis comprises the period 1995–2009for a sample of 24OECD countries.OECD countries have been chosen for the present study due to the availability of data forFDIREFigure 1.Evolution of tourist arrivals,1995–2009(millions).Source:World Development Indicators of the WorldBank.Figure 2.Evolution of tourist departures,1995–2009(millions).Current Issues in Tourism 107D o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015and low restriction on foreign investment in real estate sectors.Moreover,OECD countries are among the most important tourism destinations in the world.The choice of the sample period and country is mainly conditioned by the availability of FDI in real estate data.We use annual data for the following countries:Austria,Belgium,Czech,Denmark,Estonia,Finland,France,Germany,Greece,Hungary,Japan,Luxembourg,Mexico,Netherland,Norway,Poland,Slovakia,Slovenia,South Korea,Spain,Sweden,Turkey,UK,and USA.Data relating to the FDI in real estate inflows and outflows are obtained from the OECD Inter-national Direct Investment Database.Tourism data (annual international tourist arrivals and departures)are obtained from World Development Indicators of the World Bank.Methodology and resultsThe purpose of this study is to investigate the relationship between FDI in real estate (FDIRE),FDIREI and FDIREO and international tourist (TOUR),international tourist arri-vals (TOURA)and international tourist departures (TOURD)amongst the OECD countries.With this objective,first we analyse cointegration and then the short-run causality between variables is explored using the Granger causality test.The specification for the variables can be written as follows:FDIRE it =a it +b 1TOUR it +1it ,(1)TOUR it =a it +b 2FDIRE it +1it ,(2)FDIREI it =a it +b 3TOURA it +1it ,(3)TOURA it =a it +b 4FDIREI it +1it ,(4)FDIREO it =a it +b 5TOURD it +1it ,(5)TOURD it =a it +b 6FDIREO it +1it ,(6)Table 1.Evolution of FDIREI and FDIREO a (millions of US$).Country199720022007FDIREIFDIREO FDIREIFDIREO FDIREI FDIREO France 3849.76367.601724.622407.1220,091.7118,590Germany 2596.8076.652125.341088.493849.4121867.21Japan398.345611.57232.321403.531440.23156.25South Korea 4193.11108.7n.a.729.81355.91Netherland 1059.52823.452186.411991.3321107.46533.88Spain 445.45254.541456.97303.452042.436403.83UK 2131.042321.042180.01127.512590.351600.96USA39622571987227626694160a“Negative values of FDI net inflows for a particular year show that the value of disinvestment by foreign investors was more than the value of capital newly invested in the reporting economy.Negative values of FDI net outflows show that the value of direct investment made by domestic investors to external economies was less than the value of repatriated (disinvested)direct investment from external economies”.Retrieved from:/esa/sustdev/natlinfo/indicators/methodology_sheets/global_econ_partnership/fdi.pdf.Source:OECD International Direct Investment Database.108H.G.Fereidouni and U.Al-mulaliD o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015where FDIRE is the sum of inflows and outflows of FDI in and to real estate,1FDIREI is FDI inflows to real estate,FDIREO is FDI outflows to real estate,TOUR denotes the total number of international tourists,TOURA represents the international tourist arrival,and TOURD is the international tourist departure.b 1,b 2,b 3,b 4,b 5,and b 6are the slope coefficients of the model,t is time,i is the cross-sectional unit (i th country)and a is a scalar.Panel unit root testsPanel unit root tests are a generalisation of the augmented Dickey–Fuller (ADF)individual country unit root tests to a common panel unit root test.The basic panel unit root test regression can be written as follows:y it =r i y it −1+X it d i +1it ,(7)where i ¼1,2,.....,N cross-section units or series that are observed over periods t ¼1,2,....,T i .The X it is the exogenous variables in the model,including any fixed effects or individual trend,r i are the autoregressive coefficients,and the error 1it are assumed to be mutually independent of individual disturbance.Two types of panel unit root tests,namely Im,Pesaran and Shin (IPS)and the ADF–Fisher chi-square are used in this study.IPS devised a testing method based on the aver-aging individual unit root test ADF test statistics.The null hypothesis of this test is that each series in the panel contains a unit root test,while the alternative hypothesis allows for some of the individual time series to have unit roots.The ADF–Fisher chi-square pro-posed by Wu and Choi combines the p -values from unit root tests.In this way,the cross-section dimension N can be either finite or infinite.Each group can have different types of non-stochastic components.The time-series dimension T can be different for each I ,and the alternative hypothesis would allow some groups to have unit roots while others would not (Baltagi,2009).Both unit root tests work on the assumption that allows r i to vary freely across cross-section.Table 2shows the panel unit root test results for the IPS and ADF–Fisher chi-square.The results reveal that all the variables are not stationary at levels but they are stationary at the first difference,rejecting the null hypothesis indicating that the variables contain a panel unit root.Panel cointegration testSimilar to the panel unit root test,the panel cointegration tests became popular among researchers due to its high power compared to the individual time-series cointegration tests.It can also work with data sets with short T and short span because the panel models add the cross-sectional variation to the data which in turn increases the power of the panel cointegration tests.In the present study,the Kao panel cointegration test is employed to examine the long-run relationship between variables.Kao transformed the Engle and the Granger cointegration test from individual time series to a panel.The idea of this test is to examine two I (1)series and see if the residuals of the spurious regression involving these I (1)series are I (0).If this is so,then the series are cointegrated.If the residuals are I (1)then the variables are not cointegrated.The null hypothesis of no coin-Current Issues in Tourism 109D o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015Table 3summarises the Kao cointegration test results,which clearly show that the t -stat-istics for the ADF test for each model are significant rejecting the null hypothesis of no cointegration,indicating the bi-directional long-run relationship between the variables is present.Panel Granger causality testSince the variables are cointegrated,the Granger causality based on the vector error cor-rection model is employed to show the short-run causal relationship based on the F -test and x 2test as well as the long-run causal relationship based on the error correction term ect(21).The Granger causality equations can be specified as follows:Table 3.Kao panel cointegration test results.FDIRE TOURTOUR FDIREt -Statistic Prob.t -Statistic Prob.22.0567∗∗0.0199 1.2968∗0.0973FDIREI TOURA TOURA FDIREI 3.1504∗∗∗0.0008 1.3806∗0.0837FDIREO TOURD TOURD FDIREO2.8297∗∗0.00233.1394∗∗∗0.0009Note:We use the automatic selection based on the Schwarz to choose the optimal lag length.∗∗∗Denotes significance at 1%.∗∗Denotes significance at 5%.Table 2.Panel unit root test.VariableIPS W -statLevelFirst differenceInterceptIntercept and trendIntercept Intercept and trendFDIRE 0.317880.709372.04497∗∗0.61645TOUR 1.51399 1.80361 2.57142∗∗0.17099FDIREI 1.918320.876793.50118∗∗∗ 1.91984∗∗TOURA 0.657250.53258 2.64277∗∗ 5.56077∗∗∗FDIREO 0.017550.11395 3.88952∗∗∗ 1.78136∗∗TOURD 0.98339 1.59002 2.30652∗∗ 5.30863∗∗∗ADF–Fisher chi-square FDIRE 40.767428.985260.4870∗∗∗46.1109∗∗TOUR 41.792338.669678.6036∗∗∗48.4624∗∗FDIREI 35.720723.649588.7331∗∗∗65.1952∗∗∗TOURA 46.600344.309376.0384∗∗∗119.846∗∗∗FDIREO 45.128222.374397.3892∗∗∗81.6640∗∗∗TOURD 44.958141.976977.6100∗∗∗122.448∗∗∗Note:We used the Schwarz automatic selection of the lag length for the unit root test.∗∗∗Donates statistical significance at 1%level.∗∗Donates statistical significance 5%level.110H.G.Fereidouni and U.Al-mulaliD o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015D FDIRE it =a it +b it ect it −1+l i =1j it D FDIRE it −1+l i =1w it D (TOUR)it −1+m it ,(8)D TOUR it =a it +b it ect it −1+l i =1j it D TOUR it −1+l i =1w it D (FDIRE)it −1+m it ,(9)D FDIREI it =a it +b it ect it −1+l i =1j it D FDIREI it −1+l i =1w it D (TOURA)it −1+m it ,(10)D TOURA it =a it +b it ect it −1+l i =1j it D TOURA it −1+l i =1w it D (FDIREI)it −1+m it ,(11)D FDIREO it =a it +b it ect it −1+l i =1j it D FDIREO it −1+l i =1w it D (TOURD)it −1+m it ,(12)D TOURD it =a it +b it ect it −1+l i =1j it D TOURD it −1+l i =1w it D (FDIREO)it −1+m it ,(13)where D is the difference,a it is the constant term,b it ,j it ,and w it are the parameters,ect isthe error correction term,and m it is white-noise error.Table 4.Panel Granger causality test results.Short-run causal relationship Long-run causalrelationshipThe independent variablesThe independent variablesD FDIRE D TOUR ect (21)D FDIRE – 1.2558 1.8552∗∗D TOUR 1.9856– 1.9202∗∗D FDIREID TOURA ect(21)D FDIREI – 2.6209∗∗2.8158∗∗D TOURA3.4115∗∗∗–0.7805D FDIREOD TOURD ect(21)D FDIREO – 2.1807∗∗0.7947D TOURD0.8743–1.6282∗Note:The null hypothesis is that there is no causal relationship between variables.Values in parentheses are p-values for Wald tests with a x 2distribution.D is the first difference operator.ect(21)represents the error correction term lagged one period.∗∗∗Denotes significance at 1%.∗∗Denotes significance at 5%.Current Issues in Tourism 111D o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015As can be seen in Table 4,the Granger causality test results show the existence of bi-directional causal relationship between FDIRE and TOUR in the long-run based on the error correction term (ect).On the other hand,there is no evidence of the short-run causal relationship between FDIRE and TOUR.In addition,TOURA has a long-run and a positive short-run causal relationship with FDIREI,while there is only a positive short-run causal relationship from FDIREI to TOURA.Thus,there is a bi-directional causal relationship between FDIREI and TOURA.Moreover,it is found that TOURD has a short-run positive causal relationship with FDIREO,while TOURD has a long-run causal relationship with FDIREO.Therefore,there is a bi-directional causal relationship between FDIREO and TOURD.These results suggest that the development of a tourist industry in a destination country could increase FDI inflows to real estate.On the other hand,greater amount of FDI inflows to real estate could promote the tourism industry.In summary,our results provide strong empirical support for the complementaritybetween FDIRE and TOUR argument (He et al.,2009;Rodrı´guez &Bustillo,2010).ConclusionThis study investigates the relationship between FDIRE and TOUR in a set of OECD countries over the period 1995–2009.Panel co-integration and panel Granger causality techniques are applied to analyse both long-and short-run relationship between flows.The empirical results show the existence of the long-run and bi-directional causal relation-ship between FDIRE and TOUR,FDIREI and TOURA,and between FDIREO and TOURD.These findings are significant since they mean that a complementary link seems to exist between FDIRE and tourism.The relevance of these results for policy-makers is clear because this complementary association between flows of FDIRE and international tourism could promote economic growth in OECD countries.In particular,policy-makers need to pay more attention to their tourism sector and try to attract more inter-national tourists in order to develop and recover their real estate sectors which were hit by the recent global financial crisis.For example,it is needed to make appropriate policies to provide information about existing property investment opportunities through property site visits for international tourists as well as international property exhibitions.To achieve this goal,the role of travel agents and conference organisers would be very crucial and significant because they have a direct interaction with international tourists.On the other hand,OECD countries should attract more international real estate inves-tors to develop their property sectors which can result in higher number of international tourist inbound.The successful example is Singapore.This country could increase the number of international tourist inbound by developing their residential and commercial property sectors through foreign real estate developers such as Las Vegas Sands Corporation.Finally,the findings of this article should be considered in light of its limitations,which also point to some issues for future studies.First,in this study we test our hypothesis using data from OECD countries.For future research,it may be useful to examine the inter-relationship between tourism and FDIRE using data from developing or fast-growing econ-omies.Second,the present study only considered the aggregate FDIRE for analysis.For future research,it may be interesting to investigate the relationship of FDIRE–tourism by using disaggregate data for various types of properties such as residential,commercial,112H.G.Fereidouni and U.Al-mulaliD o w n l o a d e d b y [B e i j i n g N o r m a l U n i v e r s i t y ] a t 23:54 13 M a r c h 2015Note1.The figures are in millions of US dollars.ReferencesBaltagi,B.(2009).Econometric analysis of panel data.England:John Wiley and Sons,Ltd.Cortes-Jimenez,I.,&Pulina,M.(2010).Inbound tourism and long-run economic growth.CurrentIssues in Tourism ,13(1),61–74.Craigwell,R.,&Moore,W.(2007).Foreign direct investment and tourism in SIDS:Evidence frompanel causality tests.Tourism Analysis ,13(4),427–432.Gholipour,H.F.,&Masron,T.A.(2011).The effect of tourism agglomeration on foreign real estatein-vestment.International Journal of Strategic Property Management ,15(3),222–230.He,C.,Wang,J.,&Cheng,S.(2009).What attracts foreign direct investment in China’s real estatedevelopment?The Annals of Regional Science 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