The impact of agricultural trade approaches on global economic modeling

•We develop a logit-based Armington trade modeling method and apply it to GCAM.•We study the impacts of global market integration assumptions on future projections.•Agroeconomics projections are sensitive to trade modeling methods and parameters.•China and Africa are the most sensitive regions to global market integration.•Ignoring product differentiation and economic geography affects LUC estimations. Researchers explore future economic and climate scenarios using global economic and integrated assessment models to understand long-term interactions between human development and global environmental changes. However, differences in trade modeling approaches are an important source of uncertainty in these types of assessments, particularly for regional projections. In this study, we modified the Global Change Analysis Model (GCAM) to include a novel logit-based Armington trade structure, to examine two approaches to modeling trade: (1) an approach that represents segmented regional markets (SRM), and (2) an approach that represents integrated world markets (IWM). Our results demonstrate that assuming IWM, i.e., homogeneous product modeling and neglecting economic geography, could lead to lower cropland use (i.e., by 115 million hectares globally) and terrestrial carbon fluxes (i.e., by 25%) by the end of the century under the default GCAM scenario, compared with the logit-based Armington SRM structure. The results are highly heterogeneous across regions, with more pronounced regional trade responses driven by global market integration. Our study highlights the critical role that assumptions about future trade paradigms play in global economic and integrated assessment modeling. The results imply that closer harmonization of trade modeling approaches and trade parameter values could increase the convergence of regional results among models in model intercomparison studies.