have probably played some role in these efficiency gains. but i suspect that longer - term, structural changes, reflecting the boom in capital spending and the revolution in information technology, probably have been more important. let me turn to the evidence on this point. technology change and productivity growth bob solow - - the mit economist who won the nobel prize in economics for his work on the theory of economic growth - - once quipped that you can see computers everywhere except in the productivity statistics. a few years ago that situation began to change, and we now have strong evidence that the faster productivity growth our economy has experienced is in fact due partly to newer technologies. research by economists steve oliner and dan sichel of the federal reserve board staff sheds some light on the sources of this faster productivity growth. about 1 / 2 percentage point of the increase in productivity growth over the 1995 - 99 period can be attributed to so - called " capital deepening, " most of which reflected greater spending by businesses on computers, software, and communications equipment. the high ( and rising ) levels of business investment raised the amount of capital per worker and thereby boosted productivity. another 1 / 2 percentage point of the pickup in productivity growth reflected technological innovations in the actual production of computer hardware and semiconductors as well as better management - - perhaps assisted by these high - tech investments - - of the nation ’ s capital and labor resources. oliner and sichel estimate that the consolidated influences of high - tech investments account for about two - thirds of the acceleration in productivity since 1995. this research supports the view that fundamental changes are underway in our economy. what ’ s so special about this capital? while it is interesting to note that trend productivity has picked up and that high - tech investments are the source of the acceleration, by now these are not new observations. perhaps at this stage it is more useful to explore more deeply this positive " shock " to the ability of our economy to produce goods and services. what is so special about computers and other information technologies that they can have such an impact on our economy? let me highlight three special characteristics of high - tech equipment. first, computers and communications equipment depreciate at a very rapid pace. the current best estimate is that computers probably depreciate about 30 percent annually, although that estimate might be low, while other equipment probably depreciates at a rate of less than 15 percent annually. therefore, computers are retired, on average, after three years, and the

of real gdp. of late, equity markets have given up some of their gains. however, economists who have studied the topic generally think that an impact of a change in stock market generated wealth on consumption begins to build in the first year and may take two to three years to be fully felt. additionally, equity markets are a source of investment capital, and valuations in the stock market are one determinant of the cost of capital for businesses. external financing conditions, including equity valuations, are important because recent investments have increasingly been financed from external sources. external funds raised now account for about 20 percent of nominal capital expenditures - close to the highs of the past two decades. monetary policy and the " new " economy as i have said many times before, uncertainty about productivity trends poses a major challenge in the design and implementation of monetary policy. as you can imagine, it is very difficult to infer the true structure of the economy through the interpretation of the twists and turns of incoming economic data. how do we know, for example, if unexpected developments are just temporary movements away from stable longer - run relationships or are manifestations of changes in the underlying economic structure? in many cases, this judgment is difficult to make with much confidence even considerably after the fact. in the meantime, we must bear in mind that the statistical relationships we work with, embodied in our econometric models, are only loose approximations of the underlying reality. the considerable uncertainty regarding statistical constructs such as the " natural " rate of unemployment or the " sustainable " rate of growth of the economy suggests, in my judgment, the need to downplay forecasts of inflation based solely on those variables. some fog always obstructs our vision, but when the structure of the economy is changing, the fog is considerably denser than at other times. what should be done when such uncertainties seem particularly acute? when we suspect that our understanding of the macroeconomic environment has deteriorated, as evidenced by strings of surprises difficult to reconcile with our earlier beliefs, i think that the appropriate response is to rely less upon the future predicted by the increasingly unreliable old models and more upon inferences from the more recent past. that means we should weight incoming data more heavily than data from decades past in trying to make judgments about the new economy and, of course, act appropriately when the evidence becomes clear. it also is important to be aware of the potential for unanticipated developments to emerge that might have implications for policymaking