The general-to-specific approach to econometric modeling and forecasting has a clear strategy in model specification, estimation, and selection and is demonstrated in the context of international tourism demand. A general autoregressive distributed lag model is reduced to various specific models by imposing parameter restrictions, and model selection is based on restriction tests, consistency with economic theory, and diagnostic statistics. The models are estimated using data on inbound tourism to South Korea from its four major generating countries: Germany, Japan, the United Kingdom, and the United States. Statistical tests show that a unique model specification across origin countries is not appropriate.
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References
1.
Box, G. E. P., and G. M. Jenkins (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day.
2.
Breusch, T. (1978). “Testing for Autocorrelation in Dynamic Linear Models.” Journal of Australian Economic Papers, 17: 334-355.
3.
Davidson, J., D. F. Hendry, F. Saba, and S. Yeo (1978). “Econometric Modelling of the Aggregate Time Series Relationships between Consumers Expenditure and Income in the United Kingdom.” Economic Journal, 88: 661-692.
4.
Dickey, D. A., and W. A. Fuller (1979). “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association, 74: 427-431.
5.
Engle, R. F., and C. W. J. Granger (1987). “Cointegration and Error Correction: Representation, Estimation and Testing.” Econometrica, 55: 251-276.
6.
Gilbert, C. (1986). “Professor Hendry's Methodology.” Oxford Bulletin of Economics and Statistics, 48: 283-307.
7.
Godfrey, L. G. (1978). “Testing for Higher Order Serial Correlation in Regression Equations when the Regressors Contain Lagged Dependent Variables.” Econometrica, 46: 1303-1310.
8.
Hendry, D. F. (1995). Dynamic Econometrics: Advanced Text in Econometrics. Oxford, UK: Oxford University Press.
9.
Hendry, D. F., and T. von Ungern-Sternberg (1981). “Liquidity and Inflation Effects on Consumers Expenditure.” In Essays on the Theory and Measurement of Consumer Behaviour, edited by A. S. Deaton. Cambridge, UK: Cambridge University Press, pp. 237-260.
10.
Huang, H., and C. Xu (1999). “Financial Institutions and the Financial Crisis.” European Economic Review, 43: 903-914.
11.
International Monetary Fund (1999). International Financial Statistics Yearbook. Washington, DC: International Monetary Fund.
12.
Jarque, C. M., and A. K. Bera (1980). “Efficient Tests for Normality, Homoskedasticity and Serial Independence of Regression Residuals.” Economics Letters, 6: 255-259.
13.
Johansen, S. (1988). “A Statistical Analysis of Cointegration Vectors.” Journal of Economic Dynamics and Control, 12: 231-254.
14.
Johansen, S. (1991). “Estimation and Hypothesis Testing of Cointegrating Vectors in Gaussian Vector Autoregressive Models.” Econometrica, 59: 1551-1580.
15.
Johansen, S., and K. Juselius (1990). “Maximum Likelihood Estimation and Inference on Cointegration—with Application to the Demand for Money.” Oxford Bulletin of Economics and Statistics, 52: 169-210.
16.
Kim, S., and H. Song (1998). “An Empirical Analysis of Demand for Korean Tourism: A Cointegration and Error Correction Approach.” Tourism Analysis, 3: 25-41.
17.
Kulendran, N., and M. L. King (1997). “Forecasting International Quarterly Tourist Flows Using Error Correction and Time Series Models.” International Journal of Forecasting, 13: 319-327.
18.
Kulendran, N., and S. F. Witt (2001). “Cointegration versus Least Squares Regression.” Annals of Tourism Research, 28: 291-311.
19.
Leamer, E. E. (1996). “Questions, Theory and Data.” In Foundations of Research in Economics: How Do Economists Do Economics, edited by S. J. Medema and W. J. Samuels. Cheltenham, UK: Elgar, pp. 175-190.
20.
Maddala, G. S., and I. M. Kim (1998). Unit Roots, Cointegration and Structural Change. Cambridge, UK: Cambridge University Press.
21.
Mizon, G. E., and J. F. Richard (1986). “The Encompassing Principle and Its Application to Testing Non-Nested Hypotheses.” Econometrica, 54: 657-678.
22.
Perron, P. (1989). “The Great Crash, the Oil Shock and the Unit Root Hypothesis.” Econometrica, 57: 1361-1402.
23.
Ramsey, J. B. (1969). “Test for Specification Errors in Classical Linear Test Squares Regression Analysis.” Journal of the Royal Statistical Society, Series B, 31: 350-371.
24.
Song, H., P. Romilly, and X. Liu (2000). “An Empirical Study of UK Outbound Tourism Demand.” Applied Economics, 32: 611-624.
25.
Thomas, R. L. (1997). Modern Econometrics: An Introduction. Harlow, UK: Addison-Wesley.
26.
Turner, L. W., and S. F. Witt (2001). “Factors Influencing the Demand for International Tourism: Tourism Demand Analysis Using Structural Equation Modelling, Revisited.” Tourism Economics, 7: 21-38.
27.
White, H. (1980). “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test of Heteroskedasticity.” Econometrica, 48: 817-838.
28.
Wilkens, M. R., and T. S. Breusch (1988). “Dynamic Specification, the Long-Run and the Estimation of Transformed Regression Models.” Economica Journal, 98 (conference): 189-205.
29.
Witt, S. F. (1980). “An Abstract Mode-Abstract(Destination) Node Model of Foreign Holiday Demand.” Applied Economics, 12: 163-180.
30.
Witt, S. F., and C. A. Witt (1992). Modeling and Forecasting Demand in Tourism. London: Academic Press.
31.
Witt, S. F., and C. A. Witt (1995). “Forecasting Tourism Demand: A Review of Empirical Research.” International Journal of Forecasting, 11: 447-475.
32.
Zellner, A. (1988). “Bayesian Analysis in Econometrics.” Journal of Econometrics, 37: 27-50.
