Climate change is affecting, and will affect, the economic geography of the world in significant ways, from warmer climates that can disrupt production patterns and the quality of life across regions, to sea level-rise and the resulting flooding of coastal cities. These effects are, evidently, highly heterogenous across space. Warming negatively affects locations that are already uncomfortably warm, while it can potentially benefit some of the coldest places; flooding only affects coastal areas. This large spatial heterogeneity in the impact of climate change implies that, in order to understand and predict its overall economic cost, we need to understand its local economic impact and the redistribution of resources that it will generate across regions.
Most integrated assessment models (IAMs) used in the climate literature focus on the dynamic implications of climate change, but abstract from spatial heterogeneity and its implications (e.g. Nordhaus 2017, IPCC 2013). When they do include regions, there are only a few of them and the interactions of economic agents across space are extremely limited. As such, these models do not incorporate the impact that changes in the distribution of economic activity will have on the fortunes of particular locations, or the implications that these changes will have on aggregate effects.
In a recent paper (Cruz and Rossi-Hansberg 2021), we propose an IAM that incorporates high spatial resolution as well as a rich set of interactions between regions (the core of our model is based on the dynamic-spatial model of Desmet et al. 2018). Agents that are impacted by warmer temperatures adapt by moving, trading, altered fertility decisions, and, in the case of firms, by investing in alternative locations that benefit from (or are less impacted by) higher temperatures. Of course, it is important to recognise and incorporate that these forms of adaptation are costly, and therefore that agents use them only when their benefits exceed their costs. Ultimately, in a world in which climate change has many regions that lose but also some that gain, these spatial adaptation costs are an essential part of the effective cost of this phenomenon. Costless adaptation results in no cost, or even net benefits, of climate change, and impossible adaptation implies costs that are unrealistically high. As is almost always the case, reality is somewhere in between. The role of geographically detailed IAMs is to determine these costs somewhat more precisely. Any serious evaluation of policy requires us to do so.