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Thursday, 30 August 2012

Arguments for ending the microfoundations hegemony


Should all macroeconomic models in good journals include their microfoundations? In terms of current practice the answer is almost certainly yes, but is that a good thing? In earlier posts I’ve tried to suggest why there might be a case for sometimes starting with an aggregate macro model, and discussing the microfoundations of particular relationships (or lack of) by reference to other papers. This is a pretty controversial suggestion, which will appear for many to be a move backwards not just in time but in terms of progress. As a result I started with what I thought would be one fairly uncontroversial (but not exactly essential) reason for doing this. However let me list here what I think are the more compelling reasons for this proposal.

1) Empirical evidence. There may be strong empirical evidence in favour of an aggregate relationship which has as yet no clear microfoundation. A microfoundation may emerge in time, but policy makers do not have time to wait for this to happen. (It may take decades, as in the microfoundations for price rigidity.) Academics may have useful things to say to policy makers about the implications of this, as yet not microfounded, aggregate relationship. A particularly clear case is where you model what you can see rather than what you can microfound. For further discussion see this post.

2) Complexity. In a recent post I discussed how complexity driven by uncertainty may make it impossible to analytically derive microfounded relationships, and the possible responses to this. Two of the responses I discussed stayed within microfoundations methodology, but both had unattractive features. A much more tractable alternative may be to work directly with aggregate relationships that appear to capture some of this complexity. (The inspiration for this post was Carroll’s paper that suggested Friedman’s PIH did just that.)

3) Heterogeneity. At first sight heterogeneity that matters should spur the analysis of heterogeneous agent models of the kind analysed here, which remain squarely within the microfoundations framework. Indeed it should. However in some cases this work could provide a rationalisation for aggregate models that appear robust to this heterogeneity, and which are more tractable. Alan Blinder famously found that there was no single front runner for causes of price rigidity. If this is because an individual firm is subject to all these influences at once, then this is an example of complexity. However if different types of firm have different dominant motives, then this is an example of heterogeneity. Yet a large number of microfoundations for price rigidity appear to result in an aggregate equation that looks like a Phillips curve. (For a recent example, see Gertler and Leahy here.) This might be one case where working with aggregate relationships that appear to come from a number of different microfoundations gives you greater generality, as I argued here.

4) Aggregate behaviour might not be reducible to the summation of individuals optimising. This argument has a long tradition, associated with Alan Kirman and others. I personally have not been that persuaded by these arguments because I’ve not seen clear examples where it matters for bread and butter macro, but that may be my short-sightedness.

5) Going beyond simple microeconomics. The microeconomics used to microfound macromodels is normally pretty simple. But what if the real world involves a much more substantial departure from these simple models? Attitudes to saving, for example, may be governed by social norms that are not always mimicked by our simple models, but which may be fairly invariant over some macro timescales, as Akerlof has suggested. This behaviour may be better captured by aggregate approximations (that can at least be matched to the data) than a simple microfoundation. We could include under this umbrella radical departures from simple microfoundations associated with heterodox economists. I do not think the current divide between mainstream and heterodox macro is healthy for either side.

If this all seems very reasonable to you, then you are probably not writing research papers in the macroeconomics mainstream. Someone who is could argue that once you lose the discipline of microfoundations, then anything goes. My response is that empirical evidence should, at least in principle, be able to provide an alternative discipline. In my earlier post I suggested that the current hegemony of microfoundations owed as much to a loss of faith in structural time series econometrics as it did to the theoretical shortcomings of non-microfounded analysis. However difficulties involved in doing time series econometrics should not mean that we give up on looking at how individual equations fit. In addition, there is no reason why we cannot compare the overall fit of aggregate models to microfounded alternatives.

While this post lists all the reasons why sometimes starting with aggregate models would be a good idea, I find it much more difficult to see how what I suggest might come about. Views among economists outside macro, and policy makers, about the DSGE approach can be pretty disparaging, yet it is unclear how this will have any influence on publications in top journals. The major concern amongst all but the most senior (in terms of status) academic macroeconomists is to get top publications, which means departing from the DSGE paradigm is much too risky. Leaders in the field have other outlets when they want to publish papers without microfoundations (e.g. Michael Woodford here).

Now if sticking with microfoundations meant that macroeconomics as a whole gradually lost relevance, then you could see why the current situation would become unsustainable. Some believe the recent crisis was just such an event. While I agree that insistence on microfoundations discouraged research that might have been helpful during and after the crisis, there is now plenty of DSGE analysis of various financial frictions (e.g. Gertler and Kiyotaki here) that will take the discipline forward. I think microfoundations macro deserves to be one of, if not the, major way macro is done. I just do not think it is the only route to macroeconomic wisdom, but the discipline at the moment acts as if it is.

13 comments:

  1. You are a fantastic example of a mainstream guy who's willing to admit and explore flaws in the discipline. Good post.

    Obviously microfoundations originate from the Lucas Critique. With this in mind, its worth exploring Lucas Critique Critiques:

    (1) Microeconomic agents are based on preference driven individuals. There is nothing holy about preferences (insofar as they exist as in economic models); they are as vulnerable to the Lucas Critique as anything else.

    (2) You touch on this - to an extent we could argue that microeconomics needs to be 'macrofounded;' people's behaviour must be understood in its political and social context.

    (3) The Lucas Critique is, in many ways, 'right' (even though it was stated better by both Keynes and Phillips). However, to argue that a policy change will necessarily impact the area under discussion, and even further that it will entirely neutralise it? This is absurd.

    As far as an 'alternative' methodology goes, how about just the scientific one? i don't understand the economist's obsession with deduction.

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    1. Excellent post (and excellent comment).
      It is all the more valuable to have someone like Pr Wren-Lewis who lists such arguments, as he offers more an analysis than sheer criticism, and he's himself a practitioner of micro-founded models.

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    2. Not sure about your argument for (3). The Lucas critique doesn't suggest that a policy change will necessarily alter an aggregate relationship, merely that it might. But treating an aggregate relationship as structural when it is not potentially has high costs.

      Perhaps the best example of this was the high inflation of the 1970s which was in part caused by central banks thinking that the aggregate Phillips Curves they had estimated using 1960s data were static and unchanging. Hence they kept monetary policy too loose in response to negative supply shocks, and the result was stagflation.

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    3. JM Pinder, we are broadly in agreement. However I have seen many economists dismiss unmicrofounded models outright, simply 'because Lucas Critique.' We need to explore how a policy change could affect the parameters of a model, rather than assume that a certain methodology will make us immune and anything outside that methodology is useless.

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  2. This kind of dichotomy appears very frequently. Two common examples in my field are generative vs discriminative models in statistics, model-based vs value-fuction-based algorithms in reinforcement learning. The question is, are you trying to explicitly model everything, or are you going to focus on modelling the quantities of interest?

    The latter approach is in some sense more robust, as it only models the observable variables. However, even in that case, there are implicit assumptions about the latent variables whose ramifications are unclear.
    In the end, the class of models to be used is largely determined by application and empirical performance. I see no reason why this should not be the case in economics.

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  3. I don't think 'hegemony' is right. It could easily be argued that there are no macro models that really are micro founded. The New Keynesian literature usually takes the short-cut of Calvo prices. This is the mainstream, but what is micro-founded about this?

    The profession therefore to some extent recognises the arguments you're making.

    Do you have specific ideas in mind about what currently is 'micro-founded' and what might preferably be used to replace these formulations?

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  4. Someone could argue that once you lose the discipline of the real world, then anything goes. I certainly would. Someone arguing that microfoundations should be mandatory should ask themselves the following question: is economics a branch of pure mathematics, or does have a different goal?

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  5. Since Newton's laws were devised, our conception of the physical microfoundations that underly them have changed several times. However because they were devised independently of microfoundations they are still as useful in everyday engineering as they ever were. Surely that demonstrates strongly that there is something to be said for empirical economic laws which are formulated independently of the fundamental economic substrate.

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  6. What's needed is true microfoundations, not the pretend ones they use to pretend to answer the Lucas critique. i.e. Agent-based models with millions (at least) of heterogeneous, cognitively biased, irrationally herding agents.

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  7. genauer says:
    As a physicist, (with an h-index > 10), I value the emphasis on microfoundations, but I also want to stress, that for the most of times, like "macro" thermodynamcis was developed and very useful, long before we understood the "micro" of it. Given the semi-science status of economics, I smile a lot at ideologically rigidity, which is clearly over hyping/ventilation, given this nascent state of the art.

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  8. 1. Let's stop talking about 'micro-foundations'. DSGE models are not micro-founded at all in the sense that they are founded upon the behaviour individual people and companies. It is just ASSUMED that, for instance, the entire sector households behaves like an individual. I've not yet encountered an article which not just assumes this, but gives proof (empirical).In fact, organizations like the ECB by now already use the phrase microfoundations for macro-statistics which ARE founded upon micro data.

    2. To the contrary, macro-models like the national accounts ARE founded upon the aggregation of( the results of) individual behaviour, do have an excellent and explicit modelling of the financial sector, are stock-flow consistent and do work with model-cosnstent variables. DSGE models show non of these characteristics and are (looking at it from the empirical side) rather incoherent, ad-hoc and inconsistent. Just compare two DSGE articles: it's not uncommon that these use entire different ways to define relations in the economy, while non of these models can be used to ESTIMATE the (macro-) economy.



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  9. Hi Simon, I had not seen this post till this morning...pity as I would quite like to have included in some of my own work on the subject. I include a link to this...
    https://www.linkedin.com/pulse/prediction-very-difficult-especially-future-maria-demertzis?trk=pulse_spock-articles
    many thanks
    Maria

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  10. Simon, you would have been pleased to hear about this...

    http://www.rba.gov.au/publications/bulletin/2018/mar/meet-martin-the-rbas-new-macroeconomic-model.html

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