Many central banks rely on dynamic stochastic general equilibrium models – known as DSGEs to cognoscenti. This column […] argues that the models’ mathematical basis fails when crises shift the underlying distributions of shocks. Specifically, the linchpin ‘law of iterated expectations’ fails, so economic analyses involving conditional expectations and inter-temporal derivations also fail. Like a fire station that automatically burns down whenever a big fire starts, DSGEs become unreliable when they are most needed.
In most aspects of their lives humans must plan forwards. They take decisions today that affect their future in complex interactions with the decisions of others. When taking such decisions, the available information is only ever a subset of the universe of past and present information, as no individual or group of individuals can be aware of all the relevant information. Hence, views or expectations about the future, relevant for their decisions, use a partial information set, formally expressed as a conditional expectation given the available information.
Moreover, all such views are predicated on there being no unanticipated future changes in the environment pertinent to the decision. This is formally captured in the concept of ‘stationarity’. Without stationarity, good outcomes based on conditional expectations could not be achieved consistently. Fortunately, there are periods of stability when insights into the way that past events unfolded can assist in planning for the future.
The world, however, is far from completely stationary. Unanticipated events occur, and they cannot be dealt with using standard data-transformation techniques such as differencing, or by taking linear combinations, or ratios. In particular, ‘extrinsic unpredictability’ – unpredicted shifts of the distributions of economic variables at unanticipated times – is common. As we shall illustrate, extrinsic unpredictability has dramatic consequences for the standard macroeconomic forecasting models used by governments around the world – models known as ‘dynamic stochastic general equilibrium’ models – or DSGE models.
Unfortunately, in most economies, the underlying distributions can shift unexpectedly. This vitiates any assumption of stationarity. The consequences for DSGEs are profound. As we explain below, the mathematical basis of a DSGE model fails when distributions shift (Hendry and Mizon 2014). This would be like a fire station automatically burning down at every outbreak of a fire. Economic agents are affected by, and notice such shifts. They consequently change their plans, and perhaps the way they form their expectations. When they do so, they violate the key assumptions on which DSGEs are built.
The key is the difference between intrinsic and extrinsic unpredictability. Intrinsic unpredictability is the standard economic randomness – a random draw from a known distribution. Extrinsic unpredictability is an ‘unknown unknown’ so that the conditional and unconditional probabilities of outcomes cannot be accurately calculated in advance.
Preberite več v David F. Hendry, Grayham E. Mizon, Why DSGEs crash during crises
in celotno, bolj tehnično razpravo v Hendry, D. F., and Mizon, G. E. (2014), “Unpredictability in economic analysis, econometric modelling and forecasting”, Journal of Econometrics, 182, 186–195.