Lucas's Critique as an appeal to authority

Interesting: The Lucas critique from Wikipedia.

Robert Lucas' work on macroeconomic policymaking, argues that it is naive to try to predict the effects of a change in economic policy entirely on the basis of relationships observed in historical data, especially highly aggregated historical data.

The basic idea pre-dates Lucas' contribution (related ideas are expressed as Campbell's Law and Goodhart's Law), but in a 1976 paper, Lucas drove to the point that this simple notion invalidated policy advice based on conclusions drawn from large-scale macroeconometric models. Because the parameters of those models were not structural, i.e. not policy-invariant, they would necessarily change whenever policy (the rules of the game) was changed. Policy conclusions based on those models would therefore potentially be misleading. This argument called into question the prevailing large-scale econometric models that lacked foundations in dynamic economic theory. Lucas summarized his critique:

"Given that the structure of an econometric model consists of optimal decision rules of economic agents, and that optimal decision rules vary systematically with changes in the structure of series relevant to the decision maker, it follows that any change in policy will systematically alter the structure of econometric models."

The Lucas critique is, in essence, a negative result. It tells economists, primarily, how not to do economic analysis. The Lucas critique suggests that if we want to predict the effect of a policy experiment, we should model the "deep parameters" (relating to preferences, technology, and resource constraints) that are assumed to govern individual behavior: so-called "microfoundations." If these models can account for observed empirical regularities, we can then predict what individuals will do, taking into account the change in policy, and then aggregate the individual decisions to calculate the macroeconomic effects of the policy change.

Somewhat similar to the Heisenberg Uncertainty Principle - You want to know two things accurately but have to choose between them.

Lucas' Critique also highlights a related issue. Or rather, there is a logical argument that describes this model of forecasting - the appeal to authority (example - Einstein said XYZ therefore it must be true). How often are forecasts essentially an appeal to historical authority. It's as if we were saying: I don't know why this happened in the past but it happened under these circumstances and I think it will happen again. That forecast may end up being accidentally true but it has no modelling integrity. If you don't understand root causes and causal relationships, your forecast is predicated on a lucky repetition of history.