Abstract
This study examined the bias introduced by regional aggregation (RA) when assessing the effect of climate change and trade liberalization through computational experiments. The analysis used global computable general equilibrium models with different pre-aggregation levels, based on the GTAP10 database. The bias was quantified by comparing the effects between large-scale and aggregated models. The results revealed that RA bias comprised over 35% of estimated effects related to climate change and global trade liberalization; it reversed the change direction in the simulation and deviated changes beyond the variation range observed in the sensitivity analysis; and it increased in developing countries where the proportions of imports were high. Much RA bias is artificially created by aggregating countries with different initial shocks, which then spreads to other countries through a pseudo-trade structure. Therefore, adopting a disaggregated global model is crucial to improve the accuracy of climate change assessments with diverse shocks worldwide.
Published Version
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