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Abstract
A Meta-Analysis of potential Doha Development Agenda outcomes has identified characteristics of models, data and policy experiments that influence simulated welfare changes across a wide range of modelling frameworks. This analysis by Hess and von Cramon-Taubadel (2008) was based on 5800 observations from 110 studies. Meta-regressions produce plausible results and explain a significant proportion of the variation within the dependent variable. However, due to the complexity of the general and partial equilibrium models within the literature sample, explanatory variables in this analysis are mostly binary and do not allow for detailed assessments of the role of individual parameters across different models. Therefore, the partial equilibrium model “GSIM” and a single country CGE for Canada are employed in order to generate metadata out of synthetic scenarios. These scenarios are based on randomly specified combinations of base data, elasticities and tariff changes that a software routine has selected from previously specified, plausible ranges that were obtained from the literature sample of Doha assessments. The meta-regression based on these synthetic meta-data thus combines two different trade models into one econometric response surface meta-model. Further development of this approach may potentially enable simultaneous sensitivity assessments of scenarios from both models as well as predictions of model outcomes from alternative base data and parameter specifications.