James Morley discusses modern macroeconomics, and defends the use of large-scale econometric models that have been discarded by adherents to the DSGE framework (this is a bit wonkish, even more so in parts I left out):
The Emperor has no Clothes: The state of "modern" macro, by James Morley: [pdf]: Much has been made of the failure of modern macroeconomics to predict or understand the Great Recession of 2007–2009. In this Macro Focus, our resident time-series econometrician, James Morley*, explains what is currently meant by “modern” macroeconomics, what is behind its failure, and what can be done to rehabilitate its reputation.“Modern” Macroeconomics
In a recent essay, Narayana Kocherlakota, President of the Federal Reserve Bank of Minneapolis, acknowledged that modern macroeconomics failed during the recent financial crisis. However, his essay misses the point of why it failed.
Like many in academia, Kocherlakota associates modern macroeconomics with a particular school of thought that takes something called the “Lucas critique” as its guiding principle. The Lucas critique refers to an argument put forth by the Nobel Prize-winning macroeconomist Robert Lucas about how the changing expectations of economic agents will confound forecasting and policy analysis based on macroeconomic data. Its main implication is that an economic model with “deep structural parameters” related to preferences and technology for households and firms should provide more reliable forecasts, especially when predicting the effects of policy, than a model based more on the apparent historical correlations between macroeconomic variables. This is sometimes referred to as the “microfoundations” approach to macroeconomics because it presumes that a microeconomic structure — in particular, the metaphor of optimizing economic agents— is more robust to changes in the policy environment than macroeconomic correlations.
Rather than question the relevance of the Lucas critique, Kocherlakota explains the recent failure of modern macroeconomics as due to much narrower issues. In his view, the micro-founded models failed because they lack sufficient complexity, especially in terms of their treatment of financial markets. Also, he points out, rightly, that the models are driven by “patently unrealistic shocks”.
However, the rehabilitation of modern macroeconomics requires a different tack than suggested by Kocherlakota. In particular, macroeconomists need to do more than simply add complexity to their models. They should also remember that it is empirically testable whether models that put most of their weight on “deep structural parameters” produce more accurate predictions than models that put more weight on historical correlations. In doing so, it may be found that some macroeconomic relationships are useful even if they cannot be easily motivated as the literal outcome of a micro-founded model. This is not to deny the important role that economic theory plays... However, there is no reason for models to take theory quite so literally as is typically done in modern macroeconomics. Instead, the data should be taken more seriously.
History Repeats Itself
The idea of the Lucas critique arose out of the 1970s. It was a time when large-scale macroeconometric models that relied heavily on historical correlations — especially the traditional Phillips curve tradeoff between unemployment and inflation — failed to predict or even explain “stagflation” in the form of simultaneously high rates of unemployment and inflation. ...
Ironically, this historical episode should remind us somewhat of the present. Now it is “dynamic stochastic general equilibrium” (DSGE) models inspired by the Lucas critique that have failed to predict or even explain the Great Recession of 2007–2009. ...
So can the reputation of modern macroeconomics be rehabilitated...? As discussed below, the problems for DSGE models run deeper than a lack of complexity, while the large-scale macroeconometric models have improved considerably since the 1970s. ...
The Lucas Critique and Large-Scale Macroeconometric Models
Before discussing the details of large-scale macroeconometric models, it is perhaps useful to revisit Kocherlakota’s essay on modern macroeconomics. ... An immediately noticeable thing about ... Kocherlakota’s discussion of the Lucas critique is that he presents it as some sort of universal truth that estimated demand and supply relationships will be unstable and of limited use for policy analysis. This might be valid if a DSGE model were reality. But DSGE models are models, not reality. Thus, the relevance of the Lucas critique is testable and the tests have not been favorable. Meanwhile, according to a meta-critique of the Lucas critique by Christopher Sims, the lack of practical relevance should come as no surprise. ...
Thus, contrary to the precepts of “modern” macroeconomics, the Lucas critique in no way proves that DSGE models will predict the effects of policy better than large-scale macroeconometric models based more on historical correlations.
However, to avoid getting lost in a long, fruitless debate over the semantics of the Lucas critique, it is perhaps more constructive to simply review the features of modern macro models that Kocherlakota argues have been inspired by it. In his words, modern macro models have the five following properties:
- They specify budget constraints for households, technologies for firms, and resource constraints for the overall economy.
- They specify household preferences and firm objectives.
- They assume forward-looking behavior for firms and households.
- They include the shocks that firms and households face.
- They are models of the entire macroeconomy.
The thing that is notable about this list is that these features are far from the sole domain of DSGE models. They are also present in contemporary versions of the large-scale macroeconometric models of the U.S. economy such as those developed by Macroeconomic Advisers (WUMM/MAUS), the Federal Reserve Board (FRB/US), and the Bank of Canada (MUSE). In this sense, it might well be reasonable to acknowledge the impact of some interpretations of the Lucas critique on macroeconomics. However, it is quite a leap to go from this acknowledgment to discarding all but DSGE models, as Kocherlakota would seem to have us do.
So what about contemporary large-scale macroeconometric models? They have a number of advantages over DSGE models. ... [lists and discusses the advantages] ...
Can’t We All Just Get Along?
In some sense, the various approaches to macroeconomics are not really as different as they are sometimes made out to be. Although Finn Kydland and Edward Prescott, the Nobel Prize-winning gurus of the RBC camp, once wrote dismissively of a “system-of-equations” approach, the reality is that VARs, large-scale macroeconometric models, and DSGE models all imply systems of equations. Policy forecasts for these different approaches are all based on some assumptions from macroeconomic theory and some consideration of how economic agents perceive a given change in policy — i.e., was it anticipated or unanticipated and will it be permanent or transitory? The main differences across approaches are in terms of how estimation is carried out and how the theoretical assumptions are imposed. The VAR places the least (but not zero) weight on theory, while the DSGE models place the most, even to the extent of imposing strong restrictions on some parameters across equations. It is ultimately an empirical question as to whether the imposition of these cross-equation restrictions really helps with predicting the effects of policy and forecasting more generally. ...
Doing Better in the Future
It is a safe bet that future versions of DSGE models will incorporate more complicated financial sectors and allow for different types of fiscal policies. And guess what? The new-and-improved DSGE models will turn out to imply (ex post) that the Great Recession was actually due to serially-correlated financial intermediation shocks and suboptimal fiscal policy.
Alas, these conclusions will be driven much more by the DSGE framework than by the data. In general, the implications of DSGE models for policy are more assumed than estimated. ... At the very least, the analysis of DSGE models should be geared much more towards convincing a skeptic that results are being driven by endogenous economic mechanisms that are consistent with data, not by assumed exogenous processes...
In general, promoters of DSGE models need to convince non-believers that estimates are robust across policy regimes in the sense of producing better forecasts than other models in changing policy environments. ... The bottom line then is that DSGE models should be subject to the same (market-based) forms of evaluation that large-scale macroeconometric and other forecasting models have been subject to — i.e., they need to forecast well in real time.
Meanwhile, it should be acknowledged that,... in terms of really predicting the crisis, the award obviously goes to theories of endogenous financial crises inspired by the ideas of Hyman Minsky. Formal evaluation of these more narrative approaches is hard... But it would be foolish to dismiss such theories out of hand. In particular, a ludicrous notion sometimes expressed in the ivory towers of academia is that, for Minsky to be taken seriously, his ideas need to be put into a DSGE model. Instead, the converse is true. For DSGE models to be taken more seriously outside of academia, they need to explain and predict as well as Minsky. And serially-correlated preference and technology shocks aren’t going to do it!
To be critical of the Lucas critique is not to say it is completely irrelevant. An important goal of macroeconomic models is to have stable parameters given changes in the policy environment. But how we get there is not necessarily through a particular class of micro-founded models. More broadly, if macroeconomists want to regain the trust of the public at large, they need to resist the notion that “macroeconomics” is defined as a method, rather than as a subject matter. Specifically, macroeconomists need to be more pluralistic. They should draw from different types of analysis, be it time-series models, large-scale macroeconometric models, DSGE models, and more narrative approaches. Ultimately, we will know that the reputation of macroeconomics has been rehabilitated when “modern macroeconomics” is no longer used as a label for a particular school of thought, but instead refers to a body of knowledge of substantive and useful insights into how the macroeconomy actually works and what will happen to it in the future.