Tourism Demand Modelling and Forecasting

by Haiyan Song,; Haiyan Song

• ISBN13: 9780080436739
• ISBN10: 0080436730
• Format: Hardcover
• Copyright: 2000-06-30
• Publisher: ROUTLEDGE

Summary

The phenomenal growth of both the world-wide tourism industry and academic interest in tourism over the last thirty years has generated great interest in tourism demand modelling and forecasting from both sectors. However, the tendency for researchers and practitioners engaged in quantitative causal tourism modelling and forecasting to run many regression equations and try to choose the 'best' model based on various parametric and non-parametric criteria has been widely criticised as failing to provide credible results. The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications. The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data. The book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions.

Author Biography

Stephen F. Witt is Professor of Tourism Forecasting in the School of Management Studies at the University of Surrey, UK.

Table of Contents

Preface	vii
Introduction to Tourism Demand Analysis	1	(14)
Introduction	1	(1)
Determinants of Tourism Demand	2	(6)
Functional Form and Demand Elasticities	8	(5)
Summary	13	(2)
Traditional Methodology of Tourism Demand Modelling	15	(12)
Introduction	15	(1)
Traditional Methodology of Tourism Demand Modelling	16	(10)
Failure of the Traditional Approach to Tourism Demand Modelling	26	(1)
General-to-Specific Modelling	27	(26)
Introduction	27	(1)
General-to-Specific Modelling	28	(5)
Tests of Restrictions on Regression Parameters	33	(1)
Diagnostic Checking	34	(8)
Model Selection	42	(1)
Worked Example	43	(10)
Cointegration	53	(20)
Spurious Regression	53	(2)
The Concept of Cointegration	55	(2)
Test for Order of Integration	57	(11)
Test for Cointegration	68	(5)
Error Correction Model	73	(18)
Cointegration and Error Correction Mechanism	73	(3)
Estimating the ECM	76	(3)
Worked Examples	79	(12)
Vector Autoregression (VAR) and Cointegration	91	(32)
Introduction	91	(1)
Basics of VAR Analysis	92	(2)
Impulse Response Analysis	94	(3)
Forecasting with VAR and Error Variance Decomposition	97	(1)
Testing for Granger Causality and Exogeneity	98	(3)
An Example of VAR Modelling	101	(10)
VAR Modelling and Cointegration	111	(12)
Time Varying Parameter Modelling	123	(14)
Introduction	123	(1)
Are Tourism Demand Elasticities Constant Over Time?	124	(4)
The TVP Model and Kalman Filter	128	(3)
A Worked Example	131	(3)
Summary and Conclusions	134	(3)
Panel Data Analysis	137	(20)
Introduction	137	(1)
Model Specification and Estimation	138	(4)
An Empirical Study of a Tourism Demand Model Based on the Panel Data Approach	142	(10)
Summary and Conclusions	152	(5)
Evaluation of Forecasting Performance	157	(10)
Introduction	157	(2)
Measures of Forecasting Accuracy	159	(2)
Forecasting Evaluation of Different Models	161	(3)
Concluding Remarks	164	(3)
References	167	(6)
Author index	173	(2)
Subject index	175