Reprinted with permission
By Ramon Marimon, Director of the Max Weber Postdoctoral Programme of the European University Institute (EUI), Chairman of the Barcelona Graduate School of Economics.
Continued from part one... Q1 hedge fund letters, conference, scoops etc Abrams and his team want to understand the fundamental economics of every opportunity because, "It is easy to tell what has been, and it is easy to tell what is today, but the biggest deal for the investor is to . . . SORRY! Read More
It seems, and often is, oxymoronic to speak of the scientific method in economic policy, even more so in these years of economic crisis and vocal discontent with the economics profession. Nevertheless, I think that “the scientific method in economic policy” is the best way to summarise the work of Thomas J. Sargent and Christopher A. Sims, in both object and method.
The interrelation between economic agents (families, firms, et al) and economic policy decisions is the central object of macroeconomics and the design of economic policies and institutions. In this interaction, agents’ expectations play a crucial role, which policymakers must take into account. For example, our expectations of whether we are or are not entering a recession in Europe affect our individual saving and investment decisions and collectively determine whether we do enter a recession. The understanding of this causality was at the root of what has been called the ‘rational expectations revolution’, to which Sargent and Sims have contributed from the beginning, together with other Nobel winners, like Robert Lucas, Edmund Phelps, Finn Kydland and Edward Prescott. In this sense, this year’s Nobel prize justifiably recognises that these two names were missing.
Part of the scientific method is to recognise not only the central problems and develop theoretical models providing analytical rigour to ideas and intuitions, but also to develop the methods and instruments that allow us to contrast these models with the data ? in this case, with the macroeconomic time series to analyse, for example, the effect of different fiscal and monetary policies. Sargent and Sims distinguished themselves by developing new econometric methods for the analysis of rational expectations dynamic models, which are nowadays an integral part of the toolkit of the empirical macroeconomists, whether in academia, in central banks, or elsewhere.
Not all scientific contributions need to be the basic research that ultimately seeks to solve problems affecting our society, but those contributions have special value. Behind the abstract models and econometric techniques developed by Sargent and Sims, there are two social scientists who have always followed this principle. It is not by accident that, beyond the ‘origins of the revolution,’ both have worked on models where agents form their expectations through learning, rationality is limited, or where policymakers are uncertain about what constitutes the proper model of the economy (and these features can help to better explain the data). It is not an accident that Sims’ pioneering paper introducing VARs was not titled “Introducing Vector Auto Regressions” but, rather, “Macroeconomics and Reality” (Econometrica 1980) nor that Sargent has worked on problems that affect us directly, such as European unemployment or what, with Neil Wallace, they called ‘unpleasant monetarist arithmetic’ (further developed by Sims in the ‘fiscal theory of the price level’). It was unpleasant because it made us aware of how monetary and fiscal policies – and now we need to add, the financial sector – are intrinsically integrated; for example, if we do not fix the solvency problems of the latter, the former will pay with a depreciation of the euro. These lessons, unfortunately, are too often forgotten by those who decide economic policy but harbor a disdain for economic theory.
For a list of references, as well as for a more detailed scientific account, see Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, “Empirical Macroeconomics”, 2011.