Last summer, around this time, the consensus forecast for 2008 U.S. real GDP growth was 2.8%. Almost every month since then, the forecast has tended to be marked down a little: the latest consensus forecast, released ten days ago, is that U.S. growth this year will be 1.5 %. So even though the U.S. economy went through highly dramatic events over this period, professional forecasters appear to have kept their cool and made incremental changes in their forecast every month.
At first blush, this behavior seems quite sensible. Do we really want forecasters to jerk their forecasts around in response to every piece of news, even if its full implications are not clear? Actually, yes. That is their job, isn’t it? To give us their best guess—based on their analysis, models and judgment—of how incoming news affects near-term growth prospects?
Think about it this way: what use is a weather forecaster who never calls for rain until both you and he can look out of the window and see that it is indeed raining? A weather forecaster is doing his job if he does call, every now and then, for rain ahead of time, even at the risk of being wrong and annoying his clients for making them carry an umbrella around or rescheduling outdoor tennis matches when they didn’t have to. A weather forecast that bounces around can be annoying but it may also be a sign of the forecaster taking his job seriously.
Revise Early and Often!
Likewise, smoothness in revising forecasts is not something to be applauded. It is in fact a sign of inefficiency, as Yale University economist William Nordhaus demonstrated in an academic article two decades ago. Efficient forecasts, Nordhaus showed, “appear jagged because they incorporate all news quickly. Inefficient forecasts appear smoother … for they let the news seep in slowly.”
This tendency to smooth forecasts excessively is particularly costly at present, when some economies around the globe appear poised at turning points and could experience outright recessions or marked slowdowns. Making predictions at turning points requires unusual alertness on the part of forecasters to incoming economic information and a willingness to raise alarms about possible recessions, even at the risk that some of these calls will turn out to be wrong. However, the evidence shows that forecasters are unwilling or unable to signal that the economy is heading for a recession until one is absolutely imminent; and even then they initially underestimate the extent of the decline.
In a paper with Jair Rodriguez that was just published in World Economics, I studied the behavior of growth forecasts in the run-up to the 26 recessions that have occurred in the G7 economies and the seven major emerging market economies (the EM7) between 1989 and 2007. Only two of these recessions were predicted a year in advance. Only 8 of the 26 recessions were predicted in February of the year in which they occurred and 16 were predicted by August. But even as the year drew to a close, 6 of 26 recessions remained undetected by forecasters.
Moreover, while forecasters increasingly start to recognize recessions in the year in which they occur, the magnitude of the recession is underpredicted in the vast majority of cases. Even as late as December of the year of the recession, the forecast was more optimistic than the outcome in 15 of the 26 cases.
The figure shows the evolution of forecasts in the run-up to recessions. The forecast in February of the year before the recession is for about 2.5% growth. This forecast is slowly lowered over the course of the year and by the start of the year of the recession the average forecast is for a small decline in real GDP. It is only as the year is drawing to a close that the average forecast catches up with the reality of the recession. The impression one is left with is that of forecasters chasing the data rather than a step ahead of it.
Nordhaus’s idea of inspecting forecast revisions can also be used to show that forecasters tend to live in silos in the sense that they are reluctant to absorb quickly information from other countries. In other words, while economies are coupled, forecasters tend to be somewhat decoupled: forecasters for one country’s growth take a long time to absorb relevant information from other countries.
Evidence for such decoupling can be presented by looking at the relationship between revisions for a country’s forecasts and the revisions for other countries. If forecasts incorporate all the available information efficiently, forecast revisions for a country’s forecasts should be uncorrelated not only with past values of that country’s forecast revisions but with past values of the forecast revisions for other countries.
The evidence shows that forecasters have not given foreign news the degree of attention it deserves and are slow in absorbing news from other countries. Among G7 economies, we find that forecasters, particularly those forecasting growth in the United Kingdom and Canada, are slow to recognize the extent of the dependence of growth in their economies on U.S. growth.
Of course, some caution in revising forecasts is desirable given that data on economic activity are often extensively revised and the structure of economies is always changing. But the rate of absorption of news is so slow that it limits the usefulness of forecasts. This can be particularly costly around turning points, such as at the present conjuncture.