Jagoda Kaszowska, Juan Luis Santos, Federico Pablo-Martí
Prior to the financial crisis, little attention was paid to evaluating the spatial impact of public policies or to the proper inclusion of the financial sector in the models. Most of the central banks were using the computable general equilibrium models. After the emergence of the crisis, these models were widely criticized by policy-makers and academics. The recent developments in spatially disaggregated data could be a breaking-through point in the significance of alternative tools such as agent-based modelling. Making use of these models, we can learn in depth about the relations between actors, emphasizing the importance of heterogeneity, networks, location and learning. These models help us to understand the expected trend of macroeconomic variables as well as its impact on the other actors according to their characteristics. In this way, this kind of models seems to be more useful than the spatial econometric models for making forecasts. The heterodox (‘periphery’) models also resist the Lucas and Velupillai’s critiques. Moreover, financial institutions, markets and infrastructure can be satisfactory modelled, allowing for the analysis of prudential policies and financial regulation. The goal of this paper is to compare and discuss the mainstream (‘core’) and heterodox (‘periphery’) approaches to economic modelling in the context of public and prudential policy assessment. Taking into account the importance of the recent financial crisis, the possibility of using the agent-based approach in financial modelling is also discussed.
Keywords: agent-based models, computable general equilibrium models, spatial econometrics, economic forecasting, policy evaluation