Learning and Shifts in Long-Run Growth

Shifts in the long-run rate of productivity growth--such as those those experienced by the U.S. economy in the 1970s and 1990s--are difficult in real time to distinguish from transitory fluctuations. In this paper, we explore how economists' projections of trend productivity growth gradually evolved during the 1970s and 1990s, and examine the consequences of such real-time learning on the dynamic responses to shifts in trend growth in the context of a dynamic stochastic general equilibrium model. We find that a simple updating rule based on an estimated Kalman filter model using real-time data describes the evolution of economists' long-run growth expectations extremely well. We then show that incorporating learning in this fashion has profound implications for the dynamic effects of shifts in trend productivity growth, whether they are concentrated in the investment-goods sector or affect the entire economy. If immediately recognized, increases in the trend growth rate cause long-term interest rates to rise and produce a sharp decline in employment and investment. In contrast, with learning, a productivity acceleration sets off a sustained boom in employment and investment, and long-term interest rates rise only gradually in a pattern consistent with the experience of the 1990sKalman filter, real-time data, signal extraction

The role of forecasts in monetary policy

Forecasts of future economic developments play an important role for the monetary policy decisions of central banks. For example, forecasts of goal variables can help central banks achieve their goals and make them more accountable to the public. There are two primary explanations for the benefits of forecasts. The first is that monetary policy affects goal variables such as inflation and output only with substantial lags. Policy actions should, therefore, be based on forecasts of goal variables at horizons consistent with policy lags and be taken when these forecasts are inconsistent with policy goals. Under such an approach, the quality of a central bank's forecasts and the effectiveness of its actions to bring forecasts into alignment with targets provide a basis for judging the performance of policymakers and for holding them accountable.> The second, and less intuitive, explanation is that by focusing on a forecast of only one variable -- inflation -- a central bank can potentially achieve multiple goals. This approach can be successful even if there are tradeoffs among the various goal variables. For example, the approach can combine a commitment to long-run price stability with concern for the effects of monetary policy on output.> Amato and Laubach argue that the lagged effects of monetary policy make the use of forecasts necessary. They also argue that delegating a single goal—such as inflation stabilization—to the central bank facilitates accountability, but at the risk of not achieving other goals. They then examine how the Eurosystem and the Bank of England, both of which have been assigned a single goal, address the existence of tradeoffs among goals. Finally, the authors provide evidence that a monetary policy aimed primarily at stabilizing inflation forecasts—as practiced by the Bank of England, for example—can, in fact, achieve multiple goals.Forecasting ; Monetary policy ; Banks and banking, Central

The value of interest rate smoothing : how the private sector helps the Federal Reserve

Most central banks conduct monetary policy by setting targets for overnight interest rates. During the 1990s, central banks have tended to move these interest rates in small steps without reversing direction quickly, a practice called interest rate smoothing. For example, the majority of Federal Reserve policy moves in the last decade and a half have come in a sequence of 25 basis point moves, in striking contrast to the early 1980s, when short-term interest rates fluctuated widely. In light of this historical contrast, it is natural to ask whether interest rate smoothing is a desirable way to conduct monetary policy.> Amato and Laubach argue that interest rate smoothing is beneficial because the private sector is forward-looking. The private sector bases its decisions on expectations of the future. Thus, a monetary policy move today will be more effective if it is expected to persist over time. By smoothing interest rates, the size of changes in interest rates required to reduce fluctuations in the economy can be smaller than would otherwise be necessary.Monetary policy ; Interest rates ; Monetary policy - United States

Long-run growth expectations and "global imbalances" : [January 5, 2011]

This paper examines to what extent the build-up of "global imbalances" since the mid-1990s can be explained in a purely real open-economy DSGE model in which agents’ perceptions of long-run growth are based on filtering observed changes in productivity. We show that long-run growth estimates based on filtering U.S. productivity data comove strongly with long-horizon survey expectations. By simulating the model in which agents filter data on U.S. productivity growth, we closely match the U.S. current account evolution. Moreover, with household preferences that control the wealth effect on labor supply, we can generate output movements in line with the data. JEL Classification: E13, E32, D83, O4

Long-run growth expectations and 'global imbalances'

This paper examines to what extent the build-up of 'global imbalances' since the mid-1990s can be explained in a purely real open-economy DSGE model in which agents' perceptions of long-run growth are based on filtering observed changes in productivity. We show that long-run growth estimates based on filtering U.S. productivity data comove strongly with long-horizon survey expectations. By simulating the model in which agents filter data on U.S. productivity growth, we closely match the U.S. current account evolution. Moreover, with household preferences that control the wealth effect on labor supply, we can generate output movements in line with the data. --open economy DSGE models,trend growth,Kalman filter,real-time data,news and business cycles,current account

Welfare-maximizing monetary policy under parameter uncertainty

This paper examines welfare-maximizing monetary policy in an estimated micro-founded general equilibrium model of the U.S. economy where the policymaker faces uncertainty about model parameters. Uncertainty about parameters describing preferences and technology implies not only uncertainty about the dynamics of the economy. It also implies uncertainty about the model's utility-based welfare criterion and about the economy's natural rate measures of interest and output. We analyze the characteristics and performance of alternative monetary policy rules given the estimated uncertainty regarding parameter estimates. We find that the natural rates of interest and output are imprecisely estimated. We then show that, relative to the case of known parameters, optimal policy under parameter uncertainty responds less to natural-rate terms and more to other variables, such as price and wage inflation and measures of tightness or slack that do not depend on natural rates.Monetary policy

The Expectations-Driven U.S. Current Account

Since 1991, survey expectations of long-run output growth for the U.S. relative to the rest of the world exhibit a pattern strikingly similar to that of the U.S. current account, and thus also to global imbalances. We show that this finding can to a large extent be rationalized in a two-region stochastic growth model simulated using expected trend growth filtered from observed productivity. In line with the intertemporal approach to the current account, a major part of the buildup of the U.S. current account deficit appears to be driven by the optimal response of households and firms to improved growth prospects