| Abstract: |
Ex-ante economic impact analyses are required to demonstrate the development
impact and economic viability of loans and grants extended by multi-lateral
development banks. These assessments are performed under tight time
constraints and often in data poor environments. This paper develops a
framework for assessing development interventions in data poor environments
and applies it to the analysis of the Sustainable Tourism Program, a US$15
million loan from the Inter-American Development Bank to the Government of
Belize to foster tourism development in emerging destinations and enhance
participation of low income people in the tourism value chain. This paper
contributes to the literature in two critical ways: (i) the paper develops a
generalizable approach to building dynamic computable general equilibrium
models for development policy analysis in data poor environments; (ii)
realistic expectations of agent behavioral responses to development
interventions are required to calibrate model simulations. To estimate
business as usual tourism arrivals and expenditure, auto-regressive integrated
moving average methods were used. To estimate agent response to the
development intervention, a survey-based quasi-contingent valuation approach
was employed. These projections and information on investment structuring and
costs were used to calibrate the model shocks. Results of this analysis show
that the proposed investment will have positive impacts on Belize’s economy by
hastening economic growth. Gross domestic product increases 3% by 2040 and
unemployment falls from 12% to 10%. Cross validating with a break-even
scenario confirms that the Government of Belize would recover all investment
costs even if actual agent demand response were considerably less than
forecast. The model developed here may be applied to the ex-ante economic
analysis of other sectoral development interventions ranging from agricultural
policy to fiscal policy, from integration and trade, to health and education. |