Yes — there is something really wrong with macroeconomics

11 April, 2017 at 19:15 | Posted in Economics | 2 Comments

One way that macroeconomics stands out from other fields in economics is in how often it produces forecasts. The vast majority of empirical models in economics can be very successful at identifying causal relations or at fitting explaining behavior, but they are never used to provide unconditional forecasts, nor do people expect them to. Macroeconomists, instead, are asked to routinely produce forecasts to guide fiscal and monetary policy, and are perhaps too eager to comply …

sales-forecast-guessing-dart_0Forecasting is hard. Forecasting what people will do when their behavior is affected by many interrelated personal, local, and national variables is even harder. Forecasting when the forecasts cause changes in policy, which make people change their choices, which in turn make it required to revise the forecasts, is iteratively hard. Forecasting when economic agents themselves are forecasting your forecast to anticipate the policies that will be adopted involves strategic thinking and game theory that goes well beyond the standard statistical toolbox …

To conclude with the most important message, yes, economics models do a poor job forecasting macroeconomic variables. This deserves to be exposed, discussed, and even sometimes ridiculed. Critics like Haldane (2016) are surely right, and the alternatives that they propose for improvement are definitely worth exploring. If nothing else, this may help the media and the public to start reporting and reading forecasts as probabilistic statements where the confidence bands or fan charts are as or more important than the point forecasts. But, before jumping to the conclusion that this is a damning critique of the state of macroeconomics, this section asked for an evaluation of forecasting performance in relative terms. Relative to other conditional predictions on the effectiveness of policies, relative to other forecasts for large diverse populations also made many years out, and relative to their accuracy per dollar of funding. From these perspectives, I am less convinced that economics forecasting is all that far behind other scientific fields.

Ricardo Reis

Yes, indeed, forecasting sure is difficult. On that we all agree. But having said that, it’s pretty perplexing that a mainstream macroeconomist who has spent a large part of his career developing macro models, with all of the more or less standard assumptions on rational representative agents making only stochastic mistakes confronting intermittent ‘shocks’ in DSGE models with risk reduced uncertainty, admits that the models perform poorly when it comes to forecasting. Isn’t that kind of admitting that there is a monumental gap between model and reality? And isn’t that what critics — who Reis spend a lot of the article criticising — have pointed at for decades now?

Reis is not the only one trying to defend this rather unproductive forecasting activity so many modern macroeconomists spend their working days with. Not that long ago, Reis’ colleague Simon Wren-Lewis had a post up on forecasting activities, also defending an activity that admittedly has little value and most often come up with results no better than “intelligent guessing.”

So why do companies, governments, academic researchers, and central banks, continue with this more or less expensive, but obviously worthless, activity?

A couple of years ago yours truly was interviewed by a public radio journalist working on a series on Great Economic ThinkersWe were discussing the monumental failures of the predictions-and-forecasts-business. But — the journalist asked — if these cocksure economists with their “rigorous” and “precise” mathematical-statistical-econometric models are so wrong again and again — why do they persist wasting time on it?

In a discussion on uncertainty and the hopelessness of accurately modeling what will happen in the real world — in M. Szenberg’s Eminent Economists: Their Life Philosophies — Kenneth Arrow came up with what is probably the most plausible reason:

It is my view that most individuals underestimate the uncertainty of the world. This is almost as true of economists and other specialists as it is of the lay public. To me our knowledge of the way things work, in society or in nature, comes trailing clouds of vagueness … Experience during World War II as a weather forecaster added the news that the natural world as also unpredictable. cloudsAn incident illustrates both uncer-tainty and the unwilling-ness to entertain it. Some of my colleagues had the responsi-bility of preparing long-range weather forecasts, i.e., for the following month. The statisticians among us subjected these forecasts to verification and found they differed in no way from chance. The forecasters themselves were convinced and requested that the forecasts be discontinued. The reply read approximately like this: ‘The Commanding General is well aware that the forecasts are no good. However, he needs them for planning purposes.’

To this one might also add some concerns about ideology and apologetics. Although Reis is — as most other mainstream economists — only reluctantly prepared to discuss ideology, it’s undeniable that forecasting certainly is a non-negligible part of the labour market for (mainstream) economists, and so, of course, those in the business do not want to admit that they are occupied with worthless things (not to mention how hard it would be to sell the product with that kind of frank truthfulness …). Governments, the finance sector and (central) banks also want to give the impression to customers and voters that they, so to say, have the situation under control (telling people that next years X will be 3.048 % makes wonders in that respect). Why else would anyone want to pay them or vote for them? These are sure not glamorous aspects of economics as a science, but as a scientist it would be unforgivably dishonest to pretend that economics doesn’t also perform an ideological function in society.

And ultimately — who supplies these banks and companies with the basic models for the forecasting? People like Reis. I guess we have to allocate a part of the unforgivable dishonesty also to the academics that come up with blueprints for expensive and worthless activities.



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  1. If the IMF cannot forecast the Greek economy while prescribing public policy in detail, it might indicate to a simple mind that the IMF’s doctrine of economic cause-and-effect could do with some revision. Similarly, if central bank forecasts are highly inaccurate — or as is the case with typical DSGE forecasts so abstractly stylized as to have no recognizable correspondence with the actual economy — it might indicate that they either do not know what they are doing, or do not want us to know why they are doing what they are doing. (I would go with the latter if pressed.)
    It is a truism that predicting future choices of other people is always problematic, but is it so hard to predict the consequences of past choices and change one’s mind when the prediction fails?
    It seems to me that economists make a shell game out of this confusion over the differences between what can be predicted or forecast accurately and what is, in fact, forecast or predicted accurately. Was it really difficult in mid-2005 to predict that the U.S. house bubble would deflate with significant consequences for financial institutions and the stability of the financial system? Still, few enough economists were interested enough in the actual economy to notice. Was this because of technical difficulty with the forecasting art?
    Ultimately, this confusion reflects an ontological problem in the “science” of economics. A certain ideology wants people to believe that the economy is a natural phenomenon akin to the weather and talks as if they were approaching economic forecasting as if it were a problem akin to meteorological forecasting. Not that any of them apply the empirical sophistication and curiosity of actual meteorologists to the economy — no, they just want to create the same confusion in the public mind that attends frequently inaccurate weather forecasting, and the impression that the economy is a natural phenomenon that no one can control or predict. The reality of the economy is that the economy, in contrast to weather, is almost entirely an artifactual phenomenon, something humans do and create; though it may be complex, it is always something people are doing.
    And, people are doing it wrong — as in the case of the housing bubble — it might be useful to the general public if economists could refrain from playing the fool for some malevolent rich guys. Just a thought.

  2. One favourable factor is the vast amount of data that can be collected on the economy and the enormous processing power available. Just how did Gosplan manage! All we need are the intelligent formulas on which to base forecasting/prediction!

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