African Journal of
Business Management

  • Abbreviation: Afr. J. Bus. Manage.
  • Language: English
  • ISSN: 1993-8233
  • DOI: 10.5897/AJBM
  • Start Year: 2007
  • Published Articles: 4193

Full Length Research Paper

Model selection on tourism forecasting: A comparison between Bayesian model averaging and Lasso

Jiyuan Wang
  • Jiyuan Wang
  • School of Economics and Management, University of Chinese Academy of Sciences, China.
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Geng Peng*
  • Geng Peng*
  • School of Economics and Management, University of Chinese Academy of Sciences, China.
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  • Google Scholar
Shouyang Wang
  • Shouyang Wang
  • Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China.
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  • Google Scholar


  •  Received: 29 December 2016
  •  Accepted: 03 February 2017
  •  Published: 28 April 2017

Abstract

This study tries to tackle the tourism forecasting problem using online search queries. This recent-developed methodology is subject to several criticisms, one of which is how to choose satisfying search queries to be built in the forecasting model. This study compares two popular candidates, which are the Bayesian Model Averaging (BMA) approach and the Least Absolute Shrinkage and Selector Operator (Lasso) approach. Evidence shows that the two approaches produce similar forecasting performance but different query selection results.

Key words: Tourism forecasting, query selection, Bayesian model averaging, Lasso, Baidu query data.

Copyright © 2024 Author(s) retain the copyright of this article.

This article is published under the terms of the Creative Commons Attribution License 4.0

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