Seminar I

Friday 31 March 2017 h 16.30-19 –  Methodology in economics and validation
Aula 3 SSSUP

h 16.30

Taking a Model to the Data does Not Mean Testing it
by Prof. Moneta, SSSUP

In empirical macroeconomic analysis several approaches have emerged to confront theoretical models with data. This talk is going to discuss some of these approaches and argue that most of them fail a fair standard of theory testing. In this manner they hardly permit the researcher to empirically evaluate a model or to adjudicate among competing models. The talk will examine some roots of this problem and present possible routes for raising the reliability of policy-oriented macroeconomic models. One route goes in the direction of improving the statistical adequacy of models assumptions. Another, perhaps less taken, route goes in the direction of improving the quality and transparency of causal reasoning and inference.


SLIDES: “Taking a Model to the Data does Not Mean Testing it

h 17.15

Economic Models and Experiments
by Prof. Guala, University of Milan

The contemporary debate on the status and function of economic models has been recently formalized by Julian Reiss in terms of an “Explanation Paradox”: (1) Economic models are false; (2) Economic models explain; but (3) Only the truth explains.  In my talk I will discuss briefly the (alleged) paradox and argue that it must be solved by rejecting the first horn of the trilemma. I will justify this claim showing that economic models routinely and convincingly show us that they are true (in a way that I will explain) in the experimental laboratory. The problem is not the truth of models, but their domain of application.


SLIDES: “Economic Models and Experiments

h 18.15

Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead 
by Prof. Fagiolo, SSSUP

The Great Recession seems to be a natural experiment for economic analysis, in that it has shown the inadequacy of the predominant theoretical framework – the New Neoclassical Synthesis (NNS) – grounded on the DSGE model. In this talk, I briefly present a critical discussion of the theoretical, empirical and political-economy pitfalls of the DSGE-based approach to policy analysis. I suggest that a more fruitful research avenue should escape the strong theoretical requirements of NNS models (e.g., equilibrium, rationality, representative agent, etc.) and consider the economy as a complex evolving system, i.e. as an ecology populated by heterogenous agents, whose far-from-equilibrium interactions continuously change the structure of the system. This is indeed the methodological core of agent-based computational economics (ACE), which I shortly present here. I also discuss how ACE has been applied to policy analysis issues, providing a brief survey of macroeconomic policy applications (fiscal and monetary policy, bank regulation, labor market structural reforms and climate change interventions). Finally, I conclude by discussing the methodological status of ACE, as well as the problems it raises.