Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1772
Title: Confidence intervals for tourism demand elasticity
Authors: Song, Haiyan
Kim, Jae H.
Yang, Shu
Subjects: Tourism demand
Elasticity
Bias-corrected bootstrap
Issue Date: Apr-2010
Publisher: Pergamon
Source: Annals of tourism research, April 2010, v. 37, no. 2, p. 377-396.
Abstract: Long-run tourism demand elasticities are important policy indicators for tourism product providers. Past tourism demand studies have mainly focused on the point estimates of demand elasticities. Although such estimates have some policymaking value, their information content is limited, as their associated sampling variability is unknown. Moreover, point estimates and their standard errors may be subject to small sample deficiencies, such as estimation biases and non-normality, which renders statistical inference for elasticity problematic. This paper presents a new statistical method called the bias-corrected bootstrap, which has been proved to provide accurate and reliable confidence intervals for demand elasticities. The method is herein employed to analyze the demand for Hong Kong tourism.
Rights: Annals of Tourism Research © 2009 Elsevier Ltd. The journal web site is located at http://www.sciencedirect.com.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/1772
DOI: 10.1016/j.annals.2009.10.002
ISSN: 0160-7383
Appears in Collections:SHTM Journal/Magazine Articles

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