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Keywords:Forecasting 

Speech
Confessions of a data dependent

Remarks before the New York Association for Business Economics, New York, November 2, 2006 ; "Globalization brings new influences into the Fed's navigation calculations to determine the best flight path for the U.S. economy. To determine that course...we must develop a better understanding of the new forces exerting themselves on the aircraft we have been charged with flying. That aircraft no longer flies solely in domestic space, affected soley by domestic factors. Rather, it flies all over the world, requiring more sophisticated navigation instruments to monitor changing global and ...
Speeches and Essays , Paper 59

Working Paper
Forecasting structural change with a regional econometric input-output model

The sophistication of regional economic models has been demonstrated in several ways, most recently in the form of linking several modeling systems or in the expansion in the number of equations that can be manipulated successfully to produce impact analyses or forecasts. In this paper, an alternative perspective is employed. What do regional macro-level forecasts indicate about the process of structural change? A new methodology is illustrated that enables analysts to make forecasts of detailed structural change in the interindustry relations in an economy. Using a regional ...
Working Paper Series, Regional Economic Issues , Paper WP-96-2

Discussion Paper
The Great Moderation, Forecast Uncertainty, and the Great Recession

The Great Recession of 2007-09 was a dramatic macroeconomic event, marked by a severe contraction in economic activity and a significant fall in inflation. These developments surprised many economists, as documented in a recent post on this site. One factor cited for the failure to anticipate the magnitude of the Great Recession was a form of complacency affecting forecasters in the wake of the so-called Great Moderation. In this post, we attempt to quantify the role the Great Moderation played in making the Great Recession appear nearly impossible in the eyes of macroeconomists.
Liberty Street Economics , Paper 20120514

Working Paper
The Ohio economy: using time series characteristics in forecasting

The premise of this study is that the regional economist can better understand the Ohio economy by studying the properties of important Ohio time series that can be identified and quantified through simple regression methods.
Working Papers (Old Series) , Paper 8508

Working Paper
Evaluating FOMC forecasts

Federal Reserve policymakers began reporting their economic forecasts to Congress in 1979. These forecasts are important because they indicate what the Federal Open Market Committee (FOMC) members think will be the likely consequence of their policies. We evaluate the accuracy of the FOMC forecasts relative to private sector forecasts, the forecasts of the Research Staff at the Board of Governors, and a nave alternative forecast. The Fed reports both the range (high and low) of the individual policymaker's forecasts and a truncated central tendency. We find no reason to consider the truncated ...
Working Papers , Paper 2001-005

Journal Article
The benchmark U.S. Treasury market: recent performance and possible alternatives - commentary

Economic Policy Review , Issue Apr , Pages 149-153

Working Paper
Forecast combination and encompassing: reconciling two divergent literatures

Finance and Economics Discussion Series , Paper 80

Journal Article
Predicting the money stock: a comparison of alternative approaches

Economic Review , Issue Spr , Pages 38-54

Journal Article
Forecasting cyclical turning points: the record in the past three recessions

New England Economic Review , Issue Mar , Pages 31-40

Working Paper
Optimal prediction under asymmetric loss

Prediction problems involving asymmetric loss functions arise routinely in many fields, yet the theory of optimal prediction under asymmetric loss is not well developed. We study the optimal prediction problem under general loss structures and characterize the optimal predictor. We compute it numerically in less tractable cases. A key theme is that the conditionally optimal forecast is biased under asymmetric loss and that the conditionally optimal amount of bias is time-varying in general and depends on higher-order conditional moments. Thus, for example, volatility dynamics (e.g., GARCH ...
Working Papers , Paper 97-11

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