This article explores whether the determinants of international tourism demand differ by states and territories in Australia. This is the first attempt at econometric modelling of international tourism demand in the states and territories of Australia. A demand model is specified where international visits to states and territories is a function of world income, state-level transportation costs, stock of foreign-born residents, the Australian real exchange rate and the price levels of international and domestic substitutes. Panel and time series econometric techniques are employed to test the model variables for stationarity, cointegration and direction of causality. Panel and time series cointegration tests show that the model is cointegrated. The causality analysis indicates that all explanatory variables Granger cause international visits to the Australian states and territories. Further, we show that the impacts of the determinants of international tourism vary by states and territories. The results underscore the importance of targeted policymaking that takes into account the economic and social structure of each state and territory instead of designing tourism policies on the basis of one-size-fits-all approach.
ABS (2007) Statistical Implications of Improved Methods for Estimating Net Overseas Migration, ABS Cat. No. 3107.0.55.005. Australian Bureau of Statistics, Canberra, May 2007.
2.
ABS (2016) Migration, Australia, ABS Cat. No. 3412.0. Australian Bureau of Statistics, Canberra, March 2016.
3.
ABS (2017a) Overseas Arrivals and Departures, Australia, ABS Cat. No. 3401.0. Australian Bureau of Statistics, Canberra, December 2016.
4.
ABS (2017b) Consumer Price Index, Australia, ABS Cat. No. 6401.0. Australian Bureau of Statistics, Canberra, December 2016.
5.
ABS (2017c) Deaths, Australia, 2016, ABS Cat. No. 3302.0. Australian Bureau of Statistics, Canberra, September 2017.
6.
ABS (2017d) Australian National Accounts: State Accounts, ABS Cat. No. 5220.0. Australian Bureau of Statistics, Canberra, November 2017.
7.
AkbariAHMacDonaldM (2014) Immigration policy in Australia, Canada, New Zealand, and the United States: an overview of recent trends. International Migration Review48(3): 801–822.
8.
AllenDYapGShareefR (2009) Modelling interstate tourism demand in Australia: a cointegration approach. Mathematics and Computers in Simulation79(9): 2733–2740.
9.
AsteriouDMasatciKPılbeamK (2016) Exchange rate volatility and international trade: international evidence from the MINT countries. Economic Modelling58: 133–140.
10.
BaltagiBHFengQKaoC (2012) A Lagrange multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics170(1): 164–177.
11.
BreuschTSPaganAR (1980) The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies47(1): 239–253.
12.
CrouchGI (1994) The study of international tourism demand: a survey of practice. Journal of Travel Research32(4): 41–55.
13.
CucciaTGuccioCRizzoI (2016) The effects of UNESCO World Heritage List inscription on tourism destinations performance in Italian regions. Economic Modelling53: 494–508.
14.
DickeyDAFullerWA (1979) Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association74(366): 427–431.
15.
DivisekeraS (2003) A model of demand for international tourism. Annals of Tourism Research30(1): 31–49.
16.
DivisekeraSNguyenV (2014) Regional variations in tourist consumption patterns: a model of demand for domestic tourism in Australia. In: The Nara Tourism Statistics Week: 13th Global Forum on Tourism Statistics, Nara, Japan, 17–21 November 2014.
17.
DumitrescuEIHurlinC (2012) Testing for Granger non-causality in heterogeneous panels. Economic Modelling29(4): 1450–1460.
18.
DwyerLForsythPSpurrR. (2003) The contribution of tourism to a state and national economy: a multi-regional general equilibrium analysis. Tourism Economics9(4): 431–448.
19.
FreesEW (1995) Assessing cross-sectional correlation in panel data. Journal of Econometrics69(2): 393–414.
20.
HollanderG (1982) Determinants of demand for travel to and from Australia. Working Paper No. 26, Bureau of Industry Economics, Canberra, Australia.
21.
HugoG (2014) Change and continuity in Australian international migration policy. International Migration Review48(3): 868–890.
22.
ImKSPesaranMHShinY (2003) Testing for unit roots in heterogeneous panels. Journal of Econometrics115(1): 53–74.
KhadarooJSeetanahB (2008) The role of transport infrastructure in international tourism development: a gravity model approach. Tourism Management29(5): 831–840.
25.
KulendranN (1996) Modelling quarterly tourist flows to Australia using cointegration analysis. Tourism Economics2(3): 203–222.
26.
KulendranNDivisekeraS (2007) Measuring the economic impact of Australian tourism marketing expenditure. Tourism Economics13(2): 261–274.
27.
KwiatkowskiDPhillipsPCBSchmidtP. (1992) Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?Journal of Econometrics54(1–3): 159–178.
28.
LevinALinCFChuCSJ (2002) Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics108(1): 1–24.
29.
LiGSongHWittSF (2005) Recent developments in econometric modeling and forecasting. Journal of Travel Research44(1): 82–99.
30.
LimC (1997) Review of international tourism demand models. Annals of Tourism Research24: 835–849.
31.
LimC (1999) A meta-analytic review of international tourism demand. Journal of Travel Research37: 273–284.
32.
LimCMcAleerM (2000) A seasonal analysis of Asian tourist arrivals to Australia. Applied Economics32(4): 499–509.
33.
LimCMcAleerM (2001a) Cointegration analysis of quarterly tourism demand by Hong Kong and Singapore for Australia. Applied Economics33(12): 1599–1619.
34.
LimCMcAleerM (2001b) Monthly seasonal variations: Asian tourism to Australia. Annals of Tourism Research28(1): 68–82.
35.
LimCMcAleerM (2002) A cointegration analysis of annual tourism demand by Malaysia for Australia. Mathematics and Computers in Simulation59(1–3): 197–205.
36.
LimCMcAleerM (2005) Analyzing the behavioral trends in tourist arrivals from Japan to Australia. Journal of Travel Research43(4): 414–421.
37.
López-VillavicencioASaglioS (2014) Is globalization weakening the inflation–output relationship?Review of International Economics22(4): 744–758.
38.
MorleyCL (1998) A dynamic international demand model. Annals of Tourism Research25(1): 70–84.
39.
OkaforLEKhalidUThenT (2018) Common unofficial language, development and international tourism. Tourism Management67: 127–138.
40.
PesaranHShinY (1999) An autoregressive distributed-lag modelling approach to cointegration analysis. In: StrømS (ed) Econometrics and Economic Theory in the 20th. Century: The Ragner Frisch Centenniel Symposium. Cambridge: Cambridge University Press, pp. 371–413.
41.
PesaranMH (2004) General diagnostic tests for cross section dependence in panels (Cambridge Working Papers in Economics No. 0435). Faculty of Economics, University of Cambridge, Cambridge.
42.
PesaranMH (2007) A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics22(2): 265–312.
43.
PesaranMH (2015) Testing weak cross-sectional dependence in large panels. Econometric Reviews34(6–10): 1089–1117.
44.
PesaranMHShinYSmithRJ (2001) Bounds testing approaches to the analysis of level relationship. Journal of Applied Econometrics16(3): 289–326.
45.
PhillipsPCBPerronP (1988) Testing for a unit root in time series regression. Biometrika75(2): 335–346.
RBA (2017) Real Exchange Rates Measures, October 2017. Sydney: Reserve Bank of Australia.
49.
SantanaMLedesmaFJPérezJV (2010a) Exchange rate regimes and tourism. Tourism Economics16(1): 25–43.
50.
SantanaMLedesmaFJPérezJV. (2010b) Does a common currency promote countries’ growth via trade and tourism?The World Economy33(12): 1811–1835.
51.
SarafidisVWansbeekT (2012) Cross-sectional dependence in panel data analysis. Econometric Reviews31(5): 483–531.
52.
SbiaRShahbazMHamdiH (2014) A contribution of foreign direct investment, clean energy, trade openness, carbon emissions and economic growth to energy demand in UAE. Economic Modelling36: 191–197.
53.
SeetaramN. (2010) Use of dynamic panel cointegration approach to model international arrivals to Australia. Journal of Travel Research49(4): 414–422.
54.
SeetaramN (2012) Immigration and international inbound tourism: Empirical evidence from Australia. Tourism Management33(6): 1535–1543.
55.
SeetaramNForsythPDwyerL (2016) Measuring price elasticities of demand for outbound tourism using competitiveness indices. Annals of Tourism Research56: 65–79.
56.
SerraJCorreiaARodriguesPM (2014) A comparative analysis of tourism destination demand in Portugal. Journal of Destination Marketing & Management2(4): 221–227.
57.
SmithABTomJN (1978). Factors affecting demand for international travel to and from Australia. Occasional Paper No. 11., Canberra: Bureau of Transport and Communications Economics.
58.
SongHLiG (2008) Tourism demand modelling and forecasting – a review of recent research. Tourism Management29(2): 203–220.
59.
WesterlundJEdgertonDL (2008) A simple test for cointegration in dependent panels with structural breaks. Oxford Bulletin of Economics and Statistics70(5): 665–704.
60.
WhiteR (2007) Immigrant-trade links, transplanted home bias and network effects. Applied Economics39(7): 839–852.
WrightCF (2017). Employer organizations and labour immigration policy in Australia and the United Kingdom: the power of political salience and social institutional legacies. British Journal of Industrial Relations55(2): 347–371.
64.
WTTC (2017) Economic Impact 2017 Australia. London: World Travel and Tourism Council.
ZivotEAndrewsD (1992) Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business and Economic Statistics10(3): 251–270.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
