Economics of tourism investment in data scarce countries

•This paper develops a generalizable approach to building economy-wide models in data scarce environments.•Investment impacts on tourism demand are generated combining quasi-contingent valuation and ARIMA methods.•A first computable general equilibrium model and social accounting matrix is developed...

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Bibliographic Details
Published in:	Annals of tourism research 2016-09, Vol.60, p.115-138
Main Authors:	Banerjee, Onil, Cicowiez, Martin, Cotta, Jamie
Format:	Article
Language:	eng
Subjects:	Auto-regressive integrated moving average Computable general equilibrium Economy-wide model Ex-ante economic impact analysis Stated preference Tourism development
Online Access:	Get full text
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Summary:	•This paper develops a generalizable approach to building economy-wide models in data scarce environments.•Investment impacts on tourism demand are generated combining quasi-contingent valuation and ARIMA methods.•A first computable general equilibrium model and social accounting matrix is developed for Belize.•The model and methods developed are used to evaluate a US$15M investment in tourism development.•Results show the investment would stimulate GDP by 3% and reduce unemployment from 12% to 10% by 2040. Ex-ante economic impact analyses are required to demonstrate the development impact and viability of multilateral loans. These assessments are often performed under tight timelines, in data scarce environments and with limited opportunity for primary data collection. This paper develops a framework for assessing tourism interventions under these challenging conditions and evaluates a US$15 million tourism investment in Belize. This paper contributes to the literature by: (i) developing a generalizable approach to building economy-wide models in data scarce environments; (ii) generating realistic expectations of agent responses with quasi-contingent valuation and auto-regressive integrated moving average methods. Applying the first economy-wide model for Belize, results show that the investment would stimulate GDP by 3% and reduce unemployment from 12% to 10% by 2040.
ISSN:	0160-7383 1873-7722