For those who follow the actions of the Fed, here's a recent speech by Fed Governor Edward Gramlich, "Productivity Growth Spurt in the United States," which gives some background on how the Fed determines whether to tighten or ease:
federalreserve.gov
. . .As time goes on, many of these debates should presumably resolve themselves. At some point, it should be clearer how large the productivity shocks were, how much was cyclical and how much secular, how much was concentrated in particular industries, how much could reasonably be attributed to the boom in high-tech capital spending, how important electronic commerce will be, and how sustainable the growth spurt will be.
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[discussion of global trends and comparisons]
. . .There are other indications that the information technology revolution could explain the relatively good U.S. productivity performance. A recent study by the Agamus Consulting (1999) firm places the United States first or second among these countries in both the climate for and the success of innovation. The United States scores well in the OECD's (2000) index of regulation. In the automobile industry, U.S. carmakers have relatively short time lags between innovation and the actual production of cars.
More broadly, countries that are leading in the information revolution might also be expected to be those showing the most significant MFP increases. As Oliner and Sichel find, the direct production of high-tech equipment can raise overall MFP growth if producers of these goods themselves are experiencing large efficiency gains. Moreover, the use of information technology may also boost MFP* growth on the demand side, as transactions costs are lowered or as businesses reorganize to take advantage of network effects arising from greater use of Internet-ready computers and electronic commerce.
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*The other is what is known as multifactor productivity change (MFP), that occurring independently of supplies of capital and labor. As every economics graduate student learns early, production functions can be differentiated to identify the two terms, with the capital-deepening term represented by the growth of capital per worker times capital's share of national income and MFP growth represented by the production function growth residual. Since it is a residual, MFP growth could also reflect a great many other influences, including measurement biases.
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Productivity gains may also have even more complicated influences. Both foreign and domestic investors may be tempted to invest in the new high productivity equipment. As stated above, this new investment may boost aggregate demand, hence increasing inflationary pressures. After a short interval, it will also boost the capital stock, generating further capital- deepening productivity change and a drop in inflationary pressures. . . .
How should a central bank respond to all of these factors? The balance between aggregate demand and supply is likely to be changing, cost pressures are likely to be changing, investment and the capital stock are likely to be changing, international exchange rates are likely to be changing, and real interest rates are likely to be changing. Many of these movements are likely to end or be reversed at some point. Analytically, one would clearly need a multi-equation model to work everything out.
Although policymakers will generally have neither sufficient time nor sufficiently precise multi-equation models to analyze all these influences fully, I do think there is a workable policy strategy. My general answer to the policy quandary involves adapting a form of inflation targeting, a monetary policy strategy that has been successful and growing in popularity around the world.
In forward-looking, flexible inflation targeting (FFIT), a central bank would try to steer the economy toward some target rate of core inflation. If inflation threatens to rise above the target, for whatever reason, the central bank would tighten policy to limit spending pressures that may lead to inflation. Though not as well publicized, most actual inflation-targeting regimes are also two-sided. This means that if recession threatens, actual inflation is likely to come in below the target level, inducing a central bank following FFIT to ease policy, limiting the recession and actually nudging inflation back up toward the specified inflation target. In this sense, a FFIT monetary strategy may be pragmatically indistinguishable from a monetary strategy that follows a Taylor rule or some other kind of automatic feedback rule.
The harder question is operational. In actual practice, how does a central bank following FFIT know when to tighten and when to ease policy? In the U.S. context, such a central bank might use several proximate guides:
The level of resource utilization and the balance between the growth of aggregate demand and aggregate supply seem clearly relevant to future inflation. The central bank should try to forecast these magnitudes. The central bank would have some estimate of the level and growth of aggregate supply, including any gains in productivity, and would compare this estimate with a forecast of the level and growth in aggregate demand, with the latter possibly generated by an econometric model. If the rise in the wealth-income ratio, investment demands, exchange rates, or real interest rates influence spending demands, they would be factored in here.
Direct inflationary cost pressures also matter, and these should also be factored in. Here is where unit labor costs, or specifically the relationship between productivity growth and wage increases, would come into play. Here is also where the influence of commodity prices, energy prices, and exchange rates enter, though some of these factors would be temporary shocks and not indicators of true inflationary pressures.
Because all forecasting is uncertain, it makes sense to get readings from other forecasters. At least in the United States, there are now a series of other forecasts that can be examined, from the Blue Chip indexes to longstanding surveys of the ways in which economists and average people are forecasting inflation.
A standard drawback of reported forecasts is that the forecasters are not forced to stand behind their projections. In such cases, buttressing recorded forecasts with information about actual market trades makes sense. The most direct of these data is the spread between nominal bonds of a standard maturity, say ten years, and real or inflation-indexed bonds. This spread is sometimes affected by liquidity considerations, but in normal times it can be a good measure of the ten-year inflation foreseen by bond traders, a group that should be fairly sensitive to inflation. . . .
Conclusion
The United States productivity growth spurt, realized to a much lesser extent around the world, can be attributed largely to a combination of an investment boom and a technological revolution. The investment boom generates productivity gains through capital-deepening, and the technological revolution seems to raise MFP growth. The two forces may also be complementary, in that the technological revolution could raise investment profitability while the investment boom could speed a restructuring of industry.
The changes in productivity unleash all kinds of long- and short-run forces. In the long- run the effects are surely positive, leading to greater growth in per capita living standards and a lessening of the long-run entitlement spending problem. In the short-run, aggregate supply will rise, aggregate demand could rise, unit labor costs should fall, at least temporarily, and there could be further influences on investment, the capital stock, exchange rates, and real interest rates. Sorting through all of these influences is a daunting task indeed. But there is a policy strategy that nicely adapts to this welter of conflicting influences. Forward-looking, flexible inflation targeting can forecast future pressures in either an inflationary or recessionary direction, and it is at least a feasible way for the central bank to respond to this multiple-variable complexity. |
