Structural econometrics

In the ongoing discussion on the ’empirical revolution’ in economics, some econometricians criticise — rightfully — the view that quasi-experiments and RCTs are the (only) true solutions to finding causal parameters. But — the alternative they put forward, structural models, have their own monumental problems.

Structural econometrics — essentially going back to the Cowles programme — more or less takes for granted the possibility of a priori postulating relations that describe economic behaviours as invariant within a Walrasian general equilibrium system. In practice, that means the structural model is based on a straightjacket delivered by economic theory. Causal inferences in those models are — by assumption — made possible since the econometrician is supposed to know the true structure of the economy. And, of course, those exact assumptions are the crux of the matter. If the assumptions don’t hold, there is no reason whatsoever to have any faith in the conclusions drawn, since they do not follow from the statistical machinery used!

 By making many strong background assumptions, the deductivist [the conventional logic of structural econometrics] reading of the regression model allows one — in principle — to support a structural reading of the equations and to support many rich causal claims as a result. Here, however, the difficulty is that of finding good evidence for many of the assumptions on which the approach rests. It seems difficult to believe, even in cases where we have good background economic knowledge, that the background information will be sufficient​ to do the job that the deductivist asks of it. As a result, the deductivist approach may be difficult to sustain, at least in economics.

The difficulties in providing an evidence base for the deductive approach show just how difficult it is to warrant such strong causal claims. In short, as might be expected there is a trade-off between the strength of causal claims we would like to make from non-experimental data and the possibility of grounding these in evidence. If this conclusion is correct — and an appropriate elaboration was​ done to take into account the greater sophistication of actual structural econometric methods — then it suggests that if we want to do evidence-based structural econometrics, then we may need to be more modest in the causal knowledge we aim for. Or failing this, we should not act as if our causal claims — those that result from structural econometrics — are fully warranted by the evidence and we should acknowledge that they rest on contingent, conditional assumptions about the economy and the nature of causality.

Damien Fennell

Econometricians still concentrate on fixed parameter models and the structuralist belief/hope that parameter-values estimated in specific spatio-temporal contexts are 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.

Most of the assumptions that econometric modelling presupposes are not only unrealistic — they are plainly wrong.

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 both structural and non-structural econometric forecasting and ‘causal explanation’ rather useless.