Agent-Based and DSGE Macroeconomic Models: A Comparative Study

This project aims to compare and combine two major approaches to modelling: Dynamic Stochastic General Equilibrium (DSGE) and Agent-Based (AB) models. The former is arguably the best structured, most widely accepted, most sophisticated source of empirical information on the behaviour of national economies. The latter is arguably the most flexible tool for studying complex social systems with many dynamic and interacting components.

The two modelling approaches have different advantages and disadvantages. DSGE models may exaggerate individual rationality and foresight, and understate the importance of heterogeneity, that is, differences between agents focusing mostly on the way economic agents interact through aggregate prices. The AB models offer a more flexible approach to the role of other social interactions between individual agents in the economy by defining the characteristics and behaviour of individual heterogeneous agents with limited rationality, information and foresight. On the other hand, AB models may exaggerate errors in individual decision-making, since they usually model only simple strategies that are far from optimal choices and that evolve in time. The problem is that agents can depart from rationality in an infinite number of ways leading into what some economists refer to as a `wilderness'. The logical cohesion of rational expectations in DSGE models can be a benchmark for researchers interested in learning and bounded rationality.

This project will, we believe, be the first to compare the two modelling approaches systematically and draw conclusions on what each can learn from the other. Our general philosophy is to celebrate and exploit diversity in macroeconomic models. Our research strategy is to formulate AB model counterparts of DSGE models to reveal the relative strengths and limitations of the two modelling approaches. Our agentised DSGE (A-DSGE) models will provide important insights for strengthening the foundations of DSGE models while being better informed by economic theory than conventional AB models. Empirically, we will explore how AB models can benefit from the estimation approaches used in DSGE models, enabling us to perform a likelihood race between the traditional DSGE model and our agentised ones.

The project has three specific inter-related components of the research. First, we will take a conventional New Keynesian DSGE model as benchmark and build a DSGE model that more closely matches an AB model by relaxing the assumption of a representative agent with perfect information and cognitive abilities. This will involve multiple ways of modelling information limitations including the traditional approaches, as well as those associated with the `rational inattention' and `sticky information' literatures. We will investigate how the heterogeneity of agents can help to explain real world features and affect policy prescriptions.

Second, we will systematically compare our `best' DSGE model in terms of data fit with an AB macroeconomic model counterpart that has the same economic structure in terms of agents, markets and openness. We intend to draw upon existing methods of estimating DSGE models to estimate our ABM models, thus enabling us to perform a `likelihood race' (that maximizes the probability of observing selected macroeconomic data across the models on offer) between the traditional DSGE model and our agentized ones.

Finally, we will explore robust policies across these two contrasting modelling approaches. It is possible to design, for example, interest rate rules that are simple and robust across the rival models. Using this robust policy design methodology, our aim for macroeconomic policy recommendations is to avoid becoming `a prisoner of a single outlook' with respect to the modelling of expectations, departures from rationality in decision rules and aggregation.

With the financial crisis has come widespread criticism of the apparent failure of standard economic models to predict the current troubles and their inability to explain what happened --- ranging from questions by the Queen to doubts expressed by the Deputy Governor of the Bank of England (see, for instance, The Economist (2010) Agents of change: Conventional economic models failed to foresee the financial crisis. Could agent-based modelling do better? 22nd July). Many of these criticisms were unfair or uninformed, but they did highlight the need not to be complacent and to consider alternative forms of macro-economic modelling or enhance existing approaches to make them more useful for understanding a world in recession. The proposed research aims to to do this, comparing and synthesising Dynamic Stochastic General Equilibrium (DSGE) models and Agent-Based (AB) modelling.

Hence the beneficiaries of the research are potentially all those who use macro-economic models for forecasting or for analysing the likely consequences of policies. This includes a wide range of organisations outside academia. For example, in the UK, the Treasury and departments including BIS, DEFRA, DWP and DFID are all concerned with the macro-economic implications of their policy decisions. In the private sector, the banks and other financial institutions use macro-economic models to some extent and are likely to use them more when their confidence in them is greater. The UK's expertise in macro-economic modelling is internationally renowned and improvements to methods of modelling will reverberate around the world, affecting government and private institutions that use macro-economic models everywhere.

Improvements in the ability of macro-economic models to represent actual economic processes and outcomes have the potential to benefit society through (a) helping to stabilise the economic system (b) allowing more effective planning of policy measures to, for example, reduce unemployment and increase wealth creation (c) allowing policies to move away from 'one size fits all' prescriptions to those that are appropriately personalised and sensitive to individual circumstances, by increasing the ability of economists to model social heterogeneity.

Such impacts are likely to become visible some five to ten years after the completion of the research, as this is typically the time taken for academic social science innovations to penetrate the public and private sectors. One of the most efficient ways of moving new ideas out of academia is through training students and researchers. The proposed project will employ two post-doctoral researchers who will become highly experienced in building agent-based models of the macro-economy. Two of the co-investigators (Hamill and Gilbert) are writing a textbook on agent-based modelling in economics for senior undergraduates and postgraduates, and the text will incorporate some lessons learned from the project. Finally both research centres will conduct self-financing training courses in DSGE and ABM methodologies.