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Modeling tourism: A fully identified VECM approach.

Carl Bonham1, Byron Gangnes1, Ting Zhou2

  • 1Department of Economics, University of Hawaii at Manoa, Honolulu, HI 96822, United States.

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|April 15, 2020
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This study applies a sequential reduction method to cointegration analysis for Hawaii tourism. It successfully identifies long-run relationships and shows strong forecasting performance, improving economic modeling.

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CointegrationHawaiiIdentificationTourism demand and supply analysisTourism forecastingVector error correction model

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Area of Science:

  • Economics
  • Econometrics
  • Tourism Studies

Background:

  • System-based cointegration methods are widely used for economic analysis and forecasting.
  • Identifying structural relationships in cointegrated systems can be challenging, especially in small samples.

Purpose of the Study:

  • To apply a theory-directed sequential reduction method for estimating a vector error correction model of Hawaii tourism.
  • To identify stable long-run equilibrium relationships considering both demand and supply factors.
  • To evaluate the forecasting accuracy of the developed model.

Main Methods:

  • Utilized a theory-directed sequential reduction method based on Hall, Henry, and Greenslade (2002).
  • Estimated a vector error correction model (VECM) incorporating demand and supply influences.
  • Employed Diebold-Mariano tests to assess forecast accuracy.

Main Results:

  • Successfully identified plausible long-run equilibrium relationships within the Hawaii tourism sector.
  • The vector error correction model demonstrated satisfactory forecasting performance.
  • The sequential reduction method proved effective for identifying structural relationships in small samples.

Conclusions:

  • The theory-directed sequential reduction method is a viable approach for identifying cointegrated systems in economic research.
  • The VECM provides a robust framework for modeling and forecasting Hawaii tourism.
  • Accurate identification of long-run relationships enhances the reliability of economic forecasts.