Good morning. It’s always a pleasure and an honor to speak at the NABE annual meeting. The topic this year, of course, is “risks in the economic outlook.” Diane has done an excellent job of discussing your forecasts for 2000 and the risks associated with it. So I’m going to take a somewhat broader view. And I believe this is an especially good time to do this.
As you know, the last three years have been very good years for the economy. But they haven’t been such great years for a lot of forecasters. Frankly, for much of that time, many of our forecasts predicted that the combination of fast growth, low unemployment, and low inflation was about to end any minute.
And it’s easy to understand why. It was natural to assume that there was little change in the structure of the economy. So it also was natural to assume that economic performance would return to historical norms. Over the last three years or so, that left most forecasts centered on a real GDP growth rate of 2 percent or a little higher, which was thought to be the long-run trend. Specifically, the median one-year-ahead forecasts from the Blue Chip survey were 2.1% in January 1996, 2.1% in January 1997, and 2.2% January 1998. But, in fact, the actual rates were almost twice that! At the same time, with the economy growing rapidly and labor markets apparently tight, most forecasts overshot actual inflation in 1997 and 1998. For example, the Blue Chip survey showed CPI inflation of 2.9 and 2.3 percent in 1997 and 1998, respectively, versus actual figures of 1.9 and 1.5 percent.
In my remarks today, I want to focus on what these forecast errors could be telling us about the current economy. And I’ll also discuss what the errors mean for the conduct of monetary policy.
So, let me turn to the first issue–what could be going on in the economy that would be consistent with fast output growth, low unemployment, and low inflation? Well, I can point to several special factors that have helped keep inflation down during this period. For example, global financial crises weakened foreign demand. That led to a stronger dollar–and therefore lower import prices–as well as falling commodity prices worldwide and a drop in capacity utilization rates in U.S. manufacturing. In addition, energy prices were falling during 1997 and 1998, and so were the costs of health care, as the industry restructured itself. Finally, there’s a technical point: the CPI is down 1/2 percent or a bit more because of the improvements the Bureau of Labor Statistics has made in measuring prices.
But beyond these special factors, there’s a more fundamental issue–and that’s the nation’s productivity. Certainly, several developments in the last couple of years suggest that we may be in the midst of a supply shock related to more rapid, and more dispersed, technological change. And that would be consistent with the fast growth, low unemployment, and low inflation we’ve seen. One obvious indicator is that measured productivity growth has picked up–rising to just under 2-1/2 percent on average. This compares to an estimated trend rate of only around 1 to 1-1/2 percent for the 1980s and the first half of the 1990s. Another indicator is the faster growth we’ve seen in real labor compensation. This result is something we’d expect to go along with higher labor productivity. A third indicator is the strength of corporate profits. This also can help explain at least part of the extraordinary rise in stock market values.
And it’s easy to see why people would point to technological advances as the source of much of this increase in productivity growth rates. For one thing, we’ve seen very rapid increases in investment in computers and other information processing equipment–since 1995, it has ranged from just under twenty percent a year to over thirty percent a year, in real terms! For another, there are plenty of examples of the difference technology can make–not only in labor-saving devices, but also in changing the way people do business. For example, I saw firsthand how technology could increase the flexibility of production processes when I visited a lumber mill in Oregon. They demonstrated how they used lasers to define the geometry of a log, and they then cut it based on the latest price information for different cuts. If there’s a shortage of two-by-fours, then prices on them rise and the mill cuts more of them and fewer of other sizes.
Such improvements in production flexibility and real-time information flows illustrate how technology can make a difference for U.S. firms. They can help eliminate bottlenecks, streamline production, and fine-tune specifications so firms can better match–and even anticipate–customers’ needs. And this all could translate into faster productivity growth for the economy.
But even though there are indicators–and anecdotes galore–suggesting that a productivity shock has been driving the recent performance of the U.S. economy, there also are serious uncertainties–many of them revolving around the productivity data themselves.
For example, just consider recent productivity numbers. Frankly, they don’t stand out as all that robust when you compare them to recent decades. There are lots of instances–especially early in past business cycle expansions–when the productivity growth rate was much higher than it is now.
Another issue is where the productivity is showing up in today’s data. Part of it is in the computer industry itself, and thus does not reflect efficiencies that are spreading throughout the economy.
Of course, it’s well-known that the data suffer from some real problems and could be missing much productivity growth. For example, the data don’t measure productivity in the services sector very well, and in some cases not at all. To resolve some of these problems, the GDP accounts are undergoing some major revisions. The new data will be released in October, and they’ll reflect a number of changes, such as beginning to include the measurement of productivity in banking and calculating software as investment spending, rather than simply as a raw material to the production process. As a result, estimates of productivity growth will be higher–though we don’t know by how much. As welcome as these revisions are, however, they’re not a complete solution to the problem of measuring productivity.
My final points about the uncertainties surrounding productivity are yet more fundamental. One problem is: at this early stage, we can’t tell whether the surge in productivity growth is a cause of the fast output growth–or a consequence of it. And it may be a consequence because, historically, productivity growth has followed a pro-cyclical pattern. So, it’s possible that the recent strength in productivity won’t last very long–it might largely be due to the strong business cycle upswing we’ve been in. In that case, continued strong real GDP growth and tight labor markets eventually would create pressures for inflation to increase.
Furthermore, even if the productivity surge is a cause of the fast output growth, we don’t know how long it will last. I must admit, I found your responses to the survey question on this point pretty interesting. Most of you appear to believe that much of the recent increase in productivity reflects a higher trend rate–which, presumably, means it would be longer-lasting. The survey showed a median estimate of the trend to be 2.0 percent. But while the data admit the possibility of a sustained increase in productivity, I can’t say that I find them convincing by themselves. So, until we have enough data to see the rapid growth sustained for a long time, we won’t know for sure.
The uncertainty about recent productivity growth appears to be the major uncertainty in the outlook for the U.S. economy, and also for the conduct of monetary policy. For policy, this uncertainty complicates the question of whether FOMC actions should be strongly pre-emptive or more cautious.
Ideally, policy should be pre-emptive because of the long lags between policy actions and their effects on the economy. For example, if policymakers wait until inflation actually begins to pick up steam, they face a problem that was all too familiar in the 1970s and early 1980s. In order to quell inflation, interest rate increases have to be bigger, which means the output losses are bigger, and the employment losses are bigger.
But, if a central bank reacts early and correctly, it can alter inflation expectations and cut off the rise in inflation before it gets started. It looks like that’s what happened in the U.S. in 1994. At that time, we were dealing with forecasts of higher inflation that were based not only on increasingly tight labor markets but also on low short-term real interest rates. So the Fed responded by raising interest rates substantially. In that case, inflation didn’t take off, and the economy moved smoothly into the favorable conditions we’ve enjoyed in recent years.
But, suppose there are reasons to doubt the forecasts. Suppose, like now, we’re uncertain about the underlying model of the economy. In that case, pre-emptive policy can lead to the wrong action. When there’s a high degree of uncertainty about forecasts, it could be best for policy to be more cautious–in the extreme, to wait until inflation actually starts to rise before acting to tighten. With high uncertainty about the future, a somewhat delayed action could be preferable to running the risk of tightening when it’s not warranted.
The appropriate degree of caution depends on an analysis of the risks of the two approaches in any particular circumstance, and it will vary over time. In 1994, there were several key indicators of rising inflation in the future; in addition, there was no major source of uncertainty to make us doubt the normal relationships in the economy.
In the current situation, we face uncertainty about whether the good news on productivity growth is a cause or a consequence of our current performance–and if it’s a cause, how long it will last. Since most forecasts of output and inflation have been off the mark recently, it makes sense to place less weight on them than we normally have in the past. And the same is true of our interpretation of some of our usual indicators. For example, labor markets have been tight for several years. And the so-called output gap, which compares real GDP with an estimate of its long-run trend, also has suggested rising inflation for a few years. But the possibility of a productivity shock renders these indicators much less reliable. As a result, the Fed has taken a fairly cautious approach in reacting to such indications of a higher future inflation, especially since actual inflation has been so well-behaved.
But it’s important to make a distinction here. While the Fed has reacted cautiously to signs of building inflationary pressures, that doesn’t mean that the Fed has reacted cautiously to everything. For example, last fall, there was no doubt that the financial crises abroad were putting a strain on U.S. markets, and we lowered rates promptly. So far, this strategy seems to have worked well. Inflation has remained subdued, while the expansion has not only continued for eight years–it has even strengthened!
I’m certainly pleased with the Fed’s contribution to this outstanding economic performance. But I’m also well aware that monetary policy is only part of what’s made the U.S. economy the envy of the world, especially in recent years when we have experienced a technology boom. By moving toward price stability, the Fed has helped to provide a healthy, stable environment for people and businesses to manage their economic affairs. At the same time, sound fiscal and regulatory policies certainly can claim credit for some share of the nation’s economic and financial success.
These policies provide an environment in which the drivers of America’s productivity and prosperity–hard work, innovation, and entrepreneurship–can flourish.