6,882 research outputs found
The announcement effect: evidence from open market desk data : commentary
Paper for a conference sponsored by the Federal Reserve Bank of New York entitled Financial Innovation and Monetary TransmissionOpen market operations ; Monetary policy ; Federal Open Market Committee ; Federal funds market (United States)
Real-time Taylor rules and the federal funds futures market
This article compares movements in the federal funds rate from 1987 through 1997 with predictions from the federal funds market and a Taylor rule using unemployment and core CPI data. Although a Taylor rule using revised data does about as well as the futures market predictions, the best real-time predictions would have produced forecast errors about 50 percent larger than the futures data.Federal funds market (United States) ; Federal funds market (United States) ; Monetary policy
Data revisions and the identification of monetary policy shocks
Monetary policy research using time series methods has been criticized for using more information than the Federal Reserve had available in setting policy. To quantify the role of this criticism, we propose a method to estimate a VAR with real-time data while accounting for the latent nature of many economic variables, such as output. Our estimated monetary policy shocks are closely correlated with a typically estimated measure. The impulse response functions are broadly similar across the methods. Our evidence suggests that the use of revised data in VAR analyses of monetary policy shocks may not be a serious limitation.Monetary policy
Soft landings on a bumpy runway
Our case study of the 1995 economic slowdown reveals that part of the widespread deterioration in economic indicators was predictable in light of 1994 monetary policy actions. But it was also partly unanticipated due to a modest adverse supply shock in the first quarter of 1995.Monetary policy - United States ; Monetary policy ; Recessions
Economic determinants of the nominal treasury yield curve
We study the effect of different types of macroeconomic impulses on the nominal yield curve. We employ two distinct approaches to identifying economic shocks in VARs. Our first approach uses a structural VAR due to GalĂ (1992). Our second strategy identifies fundamental impulses from alternative empirical measures of economic shocks proposed in the literature. We find that most of the long-run variability of interest rates of all maturities is driven by macroeconomic impulses. Shocks to preferences for current consumption consistently induce large, persistent, and statistically significant shifts in the level of the yield curve. In contrast, technology shocks induce weaker and less robust patterns of interest rate responses, since they move real rates and expected inflation in opposite directions. Monetary policy shocks are the only macroeconomic shocks with a consistent and significant impact on the slope of the yield curve. We find no evidence that fiscal policy shocks induce any significant interest rate responses.Macroeconomics ; Monetary policy ; Fiscal policy
Fundamental Economic Shocks and The Macroeconomy
Recently there has been renewed interest in assessing economic models in the context of specific, empirically identified economic shocks. Typically, these shocks are identified one-at-a-time, ignoring potential correlations across shocks, or are identified in the context of a structural vector autoregression (SVAR) using zero restrictions only loosely tied to economic theory. In this paper, we develop an alternative approach that utilizes measures of economic shocks explicitly derived from economic models to identify multiple orthogonal structural impulses. We use this approach to identify technology shocks, marginal-rate-of-substitution (labor supply) shocks, and monetary policy shocks in the context of a Factor Augmented VAR. We then examine the Bayesian posterior distribution for the responses of a large number of endogenous macroeconomic and financial variables to these three shocks.. The shocks account for the preponderance of output, productivity and price fluctuations. Technology shocks have a permanent impact on measures of economic activity, whereas the other shocks are more transitory. Labor inputs have little initial response to technology shocks, with the response building steadily over the 5 year period. Consumption’s sluggish response to the technology shock is inconsistent with a simple formulation of the permanent income hypothesis, but would be consistent with a model of habit formation. Monetary policy has a rather small response to technology shocks, but responds “leans against the wind” in response to the more cyclical labor supply shock. This more cyclical shock has the biggest impact on interest rates. Stock prices respond to all three shocks. A number of other empirical implications of our approach are discussed.
Labor Productivity During the Great Depression
In a recent paper, Bemanke and Parkinson (1991) studied interwar U.S. manufacturing data with the objective of assessing competing theories of the business cycle. An important finding was that short-run increasing returns to Labor (SRIRL), or procyclical labor productivity, was at least as strong during the Great Depression as in the postwar period. The authors conclude that this information casts further doubt on the real business cycle explanation of economic fluctuations. The purpose of this note is to point out that, within the data set analyzed by Bemanke and Parkinson (20% of the manufacturing sector), labor productivity during the Great Depression (1928:III to 1933:1) was procyclical in some industries and countercyclical in others. Furthermore, our measure of labor productivity for the entire manufacturing sector during this period was countercyclical. We conclude that the evidence is not favorable toward the hypothesis that large, negative aggregate demand shocks pushed the 1929-33 economy down a static, neoclassical production function. Another possibility is that firms which typically hoarded labor during recessions chose not to do so during the 1929-33 period.
Seasonal Solow residuals and Christmas: a case for labor hoarding and increasing returns
In aggregate unadjusted data, measured Solow residuals exhibit large seasonal variations. Total Factor Productivity grows rapidly in the fourth quarter at an annual rate of 16 percent and regresses sharply in the first quarter at an annual rate of ?24 percent. This paper considers two potential explanations for the measured seasonal variation in the Solow residual: labor hoarding and increasing returns to scale. Using a specification that allows for no exogenous seasonal variation in technology and a single seasonal demand shift in the fourth quarter, we ask the following question: How much of the total seasonal variation in the measured Solow residual can be explained by Christmas? The answer to this question is surprising. With increasing returns and time varying labor effort, Christmas is sufficient to explain the seasonal variation in the Solow residual, consumption, average productivity, and output in all four quarters. Our analysis of seasonally unadjusted data uncovers important roles for labor hoarding and increasing returns which are difficult to identify in adjusted data.Seasonal variations (Economics)
Can VAR's describe monetary policy?
Recent research has questioned the usefulness of Vector Autoregression (VAR) models as a description of monetary policy, especially in light of the low correlation between forecast errors from VARs and those derived from Fed funds futures rates. This paper presents three findings on VARs' ability to describe monetary policy. First, the correlation between forecasts errors is a misleading measure of how closely the VAR forecast mimics the futures market's. In particular, the low correlation is partly due to a week positive correlation between the VAR forecasts and the futures market errors. Second, Fed funds rate forecasts from common VAR specifications do tend to be noisy, but this can be remedied by estimating more parsimonious models on post-1982 data. Third, time aggregation problems caused by the structure of the Fed funds futures market can distort the timing and magnitude of shocks derived from futures rates, and complicate comparisons with VAR-based forecasts.Monetary policy ; Vector autoregression ; Federal funds rate
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