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Modelling the Growth and Volatility in Daily International Mass Tourism to Peru

Divino, Jose Angelo and McAleer, Michael (2009) Modelling the Growth and Volatility in Daily International Mass Tourism to Peru. [ Documentos de trabajo del Instituto Complutense de Análisis Económico (ICAE); nº 15, 2009, ] (Unpublished)

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Abstract

Peru is a South American country that is divided into two parts by the Andes Mountains. The rich historical, cultural and geographic diversity has led to the inclusion of ten
Peruvian sites on UNESCO’s World Heritage List. For the potential negative impacts of mass tourism on the environment, and hence on future international tourism demand, to be managed appropriately require modelling growth rates and volatility adequately. The paper models the growth rate and volatility (or the variability in the growth rate) in daily international tourist arrivals to Peru from 1997 to 2007. The empirical results show that international tourist arrivals and their growth rates are stationary, and that the estimated symmetric and asymmetric conditional volatility models all fit the data extremely well. Moreover, the estimates resemble those arising from financial time series data, with both short and long run persistence of shocks to the growth rate in international tourist arrivals.


Item Type:Working Paper or Technical Report
Additional Information:

JEL codes: C51; C53.
The authors are most grateful to Chialin Chang, Abdul Hakim, Christine Lim, and participants at the First Conference of the International Association for Tourism
Economics, Palma de Mallorca, Spain, in October 2007 for helpful comments and suggestions, and to Marli Divino for organizing the data set. The second author wishes to
acknowledge the financial support of the Australian Research Council.

Uncontrolled Keywords:Daily International Tourim; Conditional Mean Models; Conditional Volatility Models.
Subjects:Social sciences > Economics > World economy
Series Name:Documentos de trabajo del Instituto Complutense de Análisis Económico (ICAE)
Volume:2009
Number:15
ID Code:8696
References:

Athanasopoulos G, Ahmed RA, Hyndman RJ. Hierarchical forecasts for Australian domestic tourism. International Journal of Forecasting 2009; 25: 146–166.

Bollerslev T. Generalised autoregressive conditional heteroscedasticity. Journal of Econometrics 1986; 31: 307-327.

Bonhama C, Gangnesa B, Zhoub T. Modeling tourism: A fully identified VECM approach. International Journal of Forecasting 2009; (Forthcoming).

Boussama F. Asymptotic normality for the quasi-maximum likelihood estimator of a GARCH model. Comptes Rendus de l’Academie des Sciences Serie I 2000; 331: 81-84.

Chan F, Lim C, McAleer M. Modelling multivariate international tourism demand and volatility. Tourism Management 2005; 26: 459-471.

Dickey DA, Fuller WA. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 1979; 74: 427-431.

Dickey DA, Fuller WA. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 1981; 49: 1057-1072.

Divino JA, Farias A, Takasago M, Teles VK. Tourism and economic development in Brazil. Mimeo 2007; Centro de Excelencia em Turismo, University of Brasilia.

Divino JA, McAleer M. Modelling and forecasting sustainable international tourism demand for the Brazilian Amazon. Environmental Modelling & Software 2008; (forthcoming).

Elie L, Jeantheau T. Consistency in heteroskedastic models. Comptes Rendus de l’Académie des Sciences Série I 1995; 320: 1255-1258.

Elliott G, Rothenberg TJ, Stock JH. Efficient tests for an autoregressive unit root, Econometrica 1996; 64: 813-836.

Engle RF. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 1982; 50: 987-1007.

Gil-Alana LA, Cunado J, Gracia FP. Tourism in the Canary Islands: forecasting using several seasonal time series models. Journal of Forecasting 2008; 27: 621 – 636.

Glosten L, Jagannathan R, Runkle D. On the relation between the expected value and volatility of nominal excess return on stocks. Journal of Finance 1992; 46: 1779-1801.

Hoti S, McAleer M, Shareef R. Modelling country risk and uncertainty in small island tourism economies. Tourism Economics 2005; 11: 159-183.

Hoti S, McAleer M, Shareef R. Modelling international tourism and country risk spillovers for Cyprus and Malta. Tourism Management 2007; 28: 1472-84.

Jeantheau T. Strong consistency of estimators for multivariate ARCH models. Econometric Theory 1998; 14: 70-86.

Lee SW, Hansen BE. Asymptotic theory for the GARCH(1,1) quasi-maximum likelihood estimator. Econometric Theory 1994; 10: 29-52.

Li WK, Ling S, McAleer M. Recent theoretical results for time series models with GARCH errors. Journal of Economic Surveys 2002; 16: 245-269. Reprinted in M. McAleer and L. Oxley (eds.), Contributions to Financial Econometrics: Theoretical and Practical Issues, Blackwell, Oxford, 2002, pp. 9-33.

Ling S, Li WK. On fractionally integrated autoregressive moving-average models with conditional heteroskedasticity. Journal of the American Statistical Association 1997; 92: 1184-1194.

Ling S, McAleer M. Stationarity and the existence of moments of a family of GARCH processes. Journal of Econometrics 2002a; 106: 109-117.

Ling S, McAleer M. Necessary and sufficient moment conditions for the GARCH(r,s) and asymmetric power GARCH(r,s) models. Econometric Theory 2002b; 18: 722-729.

Ling S, McAleer M. Asymptotic theory for a vector ARMA-GARCH model. Econometric Theory 2003a; 19: 278-308.

Ling S, McAleer M. On adaptive estimation in nonstationary ARMA models with GARCH errors. Annals of Statistics 2003b; 31: 642-674.

McAleer M. Automated inference and learning in modeling financial volatility. Econometric Theory 2005; 21: 232-261.

McAleer M. The Ten Commandments for optimizing value-at-risk and daily capital charges. Journal of Economic Surveys 2008; (forthcoming).

McAleer M, Chan F, Hoti S, Lieberman O. Generalized autoregressive conditional correlation. Econometric Theory 2008; (forthcoming).

McAleer M, Chan F, Marinova D. An econometric analysis of asymmetric volatility: theory and application to patents. Journal of Econometrics 2007; 139: 259-284.

McAleer M, Veiga B. Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model. Journal of Forecasting 2008a; 27: 1-19.

McAleer M, Veiga B. Single-index and portfolio models for forecasting value-at-risk thresholds. Journal of Forecasting 2008b; 27: 217-235.

Nelson DB. Conditional heteroscedasticity in asset returns: a new approach. Econometrica 1991; 59: 347-370.

Ng S, Perron P. Lag length selection and the construction of unit root tests with good size and power. Econometrica 2001; 69: 1519-1554.

Perron P, Ng S. Useful modifications to some unit root tests with dependent errors and their local asymptotic properties. Review of Economic Studies 1996; 63: 435-463.

Phillips PCB, Perron P. Testing for a unit root in time series regression. Biometrika 1988; 75: 335-346.

Shareef R, McAleer M. Modelling international tourism demand and volatility in small island tourism economies. International Journal of Tourism Research 2005; 7: 313-333.

Shareef R, McAleer M. Modelling the uncertainty in International tourist arrivals to the Maldives. Tourism Management 2007; 28: 23-45.

Shareef R, McAleer M. Modelling international tourism demand and uncertainty in Maldives and Seychelles: a portfolio approach. Mathematics and Computers in Simulation 2008; 78: 459-68.

Shephard N. Statistical aspects of ARCH and stochastic volatility. In Barndorff-Nielsen OE, Cox DR, Hinkley DV. (eds.) Statistical Models in Econometrics, Finance and Other Fields, Chapman & Hall: London, 1996; 1-67.

Deposited On:24 Mar 2009 12:06
Last Modified:06 Feb 2014 08:12

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