What should we do with econometrics?

by
Lars Pålsson Syll
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from Lars Syll

Econometrics … is an undoubtedly flawed paradigm. Even putting aside the myriad of technical issues with misspecification and how these can yield results that are completely wrong, after seeing econometric research in practice I have become skeptical of the results it produces.

Reading an applied econometrics paper could leave you with the impression that the economist (or any social science researcher) first formulated a theory, then built an empirical test based on the theory, then tested the theory. But in my experience what generally happens is more like the opposite: with some loose ideas in mind, the econometrician runs a lot of different regressions until they get something that looks plausible, then tries to fit it into a theory (existing or new) … Statistical theory itself tells us that if you do this for long enough, you will eventually find something plausible by pure chance!

This is bad news because as tempting as that final, pristine looking causal effect is, readers have no way of knowing how it was arrived at. There are several ways I’ve seen to guard against this:

(1) Use a multitude of empirical specifications to test the robustness of the causal links, and pick the one with the best predictive power …

(2) Have researchers submit their paper for peer review before they carry out the empirical work, detailing the theory they want to test, why it matters and how they’re going to do it …

(3) Insist that the paper be replicated. Firstly, by having the authors submit their data and code and seeing if referees can replicate it (think this is a low bar? Most empirical research in ‘top’ economics journals can’t even manage it). Secondly — in the truer sense of replication — wait until someone else, with another dataset or method, gets the same findings in at least a qualitative sense …

All three of these should, in my opinion, be a prerequisite for research that uses econometrics (and probably statistics more generally … Naturally, this would result in a lot more null findings and probably a lot less research. Perhaps it would also result in fewer attempts at papers which attempt to tell the entire story: that is, which go all the way from building a new model to finding (surprise!) that even the most rigorous empirical methods support it.

Unlearning Economics

Good advise, underlining the importance of never letting our admiration for technical virtuosity blind us to the fact that we have to have a cautious attitude towards probabilistic inferences in economic contexts.  

Science should help us disclose causal forces behind apparent ‘facts.’ We should look out for causal relations, but econometrics can never be more than a starting point in that endeavour since econometric (statistical) explanations are not explanations in terms of mechanisms, powers, capacities or causes. Firmly stuck in an empiricist tradition, econometrics is only concerned with the measurable aspects of reality. But there is always the possibility that there are other variables – of vital importance and although perhaps unobservable and non-additive, not necessarily epistemologically inaccessible – that were not considered for the model. Those who were can hence never be guaranteed to be more than potential causes, and not real causes. A rigorous application of econometric methods in economics really presupposes that the phenomena of our real-world economies are ruled by stable causal relations between variables. A perusal of the leading econom(etr)ic journals shows that most econometricians still concentrate on fixed parameter models and that parameter-values estimated in specific spatiotemporal contexts are presupposed to be exportable to totally different contexts. To warrant this assumption one, however, has to convincingly establish that the targeted acting causes are stable and invariant so that they maintain their parametric status after the bridging. The endemic lack of predictive success of the econometric project indicates that this hope of finding fixed parameters is a hope for which there really is no other ground than hope itself.

Real world social systems are seldom governed by stable causal mechanisms or capacities. The kinds of ‘laws’ and relations that econometrics has established, are laws and relations between entities in models that presuppose causal mechanisms being atomistic and additive. When causal mechanisms operate in real-world social target systems they only do it in ever-changing and unstable combinations where the whole is more than a mechanical sum of parts. If economic regularities obtain they do it (as a rule) only because we engineered them for that purpose. Outside man-made ‘nomological machines’ they are rare, or even non-existent. Unfortunately, that also makes most of the achievements of econometrics – as most of the contemporary endeavours of mainstream economics – rather useless.

Maintaining that economics is a science in the ‘true knowledge’ business, yours truly remains a skeptic of the pretences and aspirations of econometrics. So far, I cannot see that it has yielded much in terms of relevant, interesting economic knowledge. Over all the results have been bleak indeed.