Winner of the New Statesman SPERI Prize in Political Economy 2016

Monday 8 October 2012

DSGE critics and future directions for macro

Microfounded macromodels, aka DSGE models, hold a dominant position in academic macro, and their influence in central banks is increasing. (The Bank of England’s core model is DSGE, but the approach has not yet quite achieved a similar dominance in the Fed or elsewhere.) At the risk of gross oversimplification, you can class the critics of this situation into two groups: the reformers and revolutionaries. The reformers (like myself) see DSGE analysis as always forming a central part of macro, but want greater diversity, with in particular more analysis using time series econometrics. The revolutionaries want to confine DSGE analysis to a much more minor role, if not the bin.

In a sense debate between these critics is a bit pointless. We are standing on the same train platform, agreed on the direction of travel, but at the moment the train shows no sign of moving. There is a danger that we spend too much time arguing about when the train should stop, and not thinking enough about how to get it going in the first place. Nevertheless I think it is worth having the debate, if only because of tactics. Those DSGE modellers who are sympathetic to reform can easily become defenders of the status quo in the face of more extreme attacks.

So let me give one argument for reform rather than revolution that I have only made implicitly before. When I studied macro and then began working as a macroeconomist, mainstream macro was divided into schools of thought. In an environment where both inflation and unemployment were high, you had monetarists saying that you just needed to control the money supply, some Keynesians arguing that we should focus on unemployment because it had nothing to do with inflation, and New Classicals saying unemployment was not even a problem. Each school had its models, and each claimed empirical backing. Econometric analysis was not strong enough to discriminate between schools. Different schools tended to talk across each other, and anyone trying to look for common ground or ultimate sources of disagreement had a hard time, and ended up writing lists. For a policymaker or student it must have seemed like a nightmare, and no wonder many chose which school to follow based on its ideological associations.

In my view microfoundations brought some order to this chaos (see this from here). Now for heterodox economists who think the microfoundation approach is fundamentally flawed, this is a problem: we are looking at alternatives through the wrong lens. But for those who think that, for at least some problems, basic micro reasoning is a good place to start, microfoundations provided a common language with which to discuss and appreciate different points of view. Note that this is not an argument for complete synthesis, but just a shared language.

As Diane Coyle noted about the conference we both recently attended, the UK’s social science funding agency (the ESRC) is considering what kind of research in macro is needed post crisis, and therefore what funding initiatives might be appropriate. Here I want to present a cautionary tale. Macro is dominated by US economists of course, but one area where the UK was strong was in the building and empirical evaluation of econometric macromodels. This reflected strength in time series economics (David Hendry, Hashem Pesaran, Andrew Harvey to name just three), but was embodied in the ESRC Macroeconomic Modelling Bureau, directed by Ken Wallis from 1983 to 1999. However with the intellectual tide moving ever more strongly in favour of calibrated DSGE models, macro papers by those involved with this area were not hitting the top journals. Partly as a result, the ESRC (which really means the academic and other macroeconomists advising the ESRC) decided to discontinue funding for the centre.[1]

I thought that was a huge mistake at the time, and that conviction has been reinforced by recent events.[2] What the Bureau did was bring modellers from policy institutions and academics together around the concrete endeavour of comparing the models used by those institutions. At the very least, modellers became aware of alternative perspectives, and models used by policymakers were subject to critique. This has now been lost.  The moral I draw from this mistake is that it is dangerous to sacrifice strengths to fashion. The UK retains strengths in time series macro: one of the strongest papers at the conference was presented by John Muelbauer, whose work on financial liberalisation and consumption I have discussed before. However the UK also has a number of economists producing strong work in the DSGE tradition, and this should also be encouraged. What the UK really lacks (and the key message from the report Diane cites) is academic macroeconomists, and the reason for that is for another post.  

[1] The Centre was co-funded by the Treasury and the Bank of England, and the absence of strong support from these institutions may also have been important in this decision. Both institutions were of course subject to the same intellectual tide, and may have had mixed feelings about being open to external critique.
[2] Unfortunately this was not the first time lack of support from the ESRC killed off a very innovative and productive macro research team. Many of the issues involved in optimal policy analysis in rational expectations models were first investigated by David Currie and Paul Levine in the 1980s, but funding support for this team was not renewed by the academics advising the ESRC. 


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  2. But for those who think that, for at least some problems, basic micro reasoning is a good place to start, microfoundations provided a common language with which to discuss and appreciate different points of view

    It's a common language, but as such, it's more like Scholastic Latin than Swahili - it lets a particular class of high-status professionals talk to each other about a particular set of problems in their own area of interest. For example, emphasis on microfoundations pretty much killed institutional economics and the whole tradition running from Veblen to Galbraith.

    At the moment, probably the biggest and most interesting question in macroeconomics is whether and on what terms Spain will enter an IMF/ESM program. That question is clearly tied up with the perceived long term political consequences of doing so for Rajoy and the Partido Popular. Obviously one could create a microfounded model whereby rational voters working with limited information decided to severely penalise governing parties who gave up sovereignty, and then combine it with a microfounded public-choice model, but it would be pretty clear that this was an ad hoc response; you wouldn't have it hanging around in the literature unless you had an independent reason to believe it might come in useful. So a literature based wholly on microfounded approaches is going to be doomed to always be fighting the last war. The real scandal of macroeconomics isn't anything to do with modelling - it's that so many macroeconomists didn't know what a CDO was until they read it in the Financial Times.

    My point is that it isn't just in empirical work that DSGE needs to be reformed and supplemented; there does need to be space for views that aren't based on a view of the economy under which everything can be reduced to choice theory. I would guess that this is sort of what you have in mind by saying that DSGE needs to be "a central part" rather than "the central part" of macroeconomics, but this is where a sociological approach to the profession itself is important. The microfoundations approach, as you say, is still dominant. They have a position at the top of the profession with a massive share of the top journal slots. They're not going to give that up or share it with other schools of thought willingly. So if you're a reformer in terms of ultimate aims, you need to be a revolutionary in terms of immediate tactics.

  3. What is your view on why the intellectual tide is moving ever more strongly in favour of calibrated DSGE models?

  4. 1. I would strongly supports any efforts in econometrics (statistics). At the end of the day, physics is a huge number of statistical links before any theory can be built. The Higgs boson is not a particle in the Standard Model- it needs the propability of 0.999999 and five standard deviations to be "found". Without an elaborated statistical model one can not declare the Higgs boson as found. A similar statistical approach is applicable to any theory.

    2. Both macro or microeconomics have to follow up all general prescriptions of metrology. When a researcher from hard sciences starts to dig into economic time series the first impression is that they all garbage. All macro time series I have ever touched (GDP, GDP defaltor, CPI, umeployment, labor force, productivity, population characteristics) have a big flag "not time compatibale". This kills any reasonable econometric approach by default. The first step has to be the preparation of a set of time compatible time series.

    3. In the history of physics, macrofeatures (e.g. gas laws or photo effect) were usually precursors of microfoundations. When some phenomenon has a consistent (in time and space) behaviour one may try to explain it using a (short or far-field) coordinated (collective) behaviour of constituent parts. At this stage, the link between micro and macro economics looks like "garbage in - garbage out".

  5. Ivan Kitov is correct: metrology is the key. Gary Gorton made a similar point:
    "Go back to macroeconomics. Macroeconomics as a paradigm in large part is determined by what is measured. If I told you that I had a 30-year panel data set of firms by sector and I had the deltas of the change in value with respect to certain systemic risks and idiosyncratic risks, people would calibrate models to measures of risk, right?

    The way models are built, and the way people think, is determined in large part by what we measure. It’s determined by Kuznets, basically. So it’s hard to even imagine how you’re going to build models if we don’t measure things that are more directly associated with what we would like to know."

    Gorton, 2011

  6. Somewhat vainly, I like to imagine that this post is directed at me ( among many others many of whom have made contributions which dwarf mine ). I am going to try to reply without being rude (there's a first time for everything).

    I will invent a hypothetical possible alternate Simon Wren-Lewis (hence ASWL) with whom I agree. Not claiming to read minds, I won't guess if this fantasy figure is in any way similar to Simon Wren-Lewis. ASWL thinks that the DSGE school dominates the field (hence the alernative is called heterodoxy) and so to suggest tossing DSGE models in the bin is to become irrelevant. The proper rhetorical strategy for reducing the dominance is to argue for reform not revolution, to argue for diversity and not to dismiss the vast bulk of research in recent decades as totally unsatisfactory etc.

    I note that the hypothetical ASWL would feel no need to address the relationship between recent research in Macro-economics and the data. Even in the hypothetical case that it were similar to that which would one expect for a fundamentally misguided research program, the power within the profession would make it unwise to consider that this might be possible.

    Someone with a higher opinion of economists than I or the purely hypothetical ASWL have might assume that the best approach to the common quest for knowledge is frank discussion in which data are considered when evaluating the promise of research programs. But since the academic debate has some effect on the very important policy debate, potentially influential people should not sacrifice their potential influence by expressing frank opinions.

    Again I am not even speculating about the relationship between ASWL and Simon Wren-Lewis.

  7. Why not use agent-based modelling (ABM)? They're a great alternative to DSGE models, without compromising microfoundations. The Economist had a good article about ABMs:


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