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Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset

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Author Info
Jon Faust
Jonathan H. Wright

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Abstract

Many recent papers have found that atheoretical forecasting methods using many predictors give better predictions for key macroeconomic variables than various small-model methods. The practical relevance of these results is open to question, however, because these papers generally use ex post revised data not available to forecasters and because no comparison is made to best actual practice. We provide some evidence on both of these points using a new large dataset of vintage data synchronized with the Fed's Greenbook forecast. This dataset consists of a large number of variables, as observed at the time of each Greenbook forecast since 1979. Thus, we can compare real-time large dataset predictions to both simple univariate methods and to the Greenbook forecast. For inflation we find that univariate methods are dominated by the best atheoretical large dataset methods and that these, in turn, are dominated by Greenbook. For GDP growth, in contrast, we find that once one takes account of Greenbook's advantage in evaluating the current state of the economy, neither large dataset methods nor the Greenbook process offers much advantage over a univariate autoregressive forecast.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13397.

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Date of creation: Sep 2007
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Handle: RePEc:nbr:nberwo:13397

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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Cited by:
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  1. Fabio Canova & Luca Gambetti, 2007. "Do expectations matter? The Great Moderation revisited," Economics Working Papers 1084, Department of Economics and Business, Universitat Pompeu Fabra, revised Jan 2009. [Downloadable!]
  2. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2009. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Finance and Economics Discussion Series 2009-10, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
    Other versions:
  3. Jan J. J. Groen & George Kapetanios, 2008. "Revisiting useful approaches to data-rich macroeconomic forecasting," Staff Reports 327, Federal Reserve Bank of New York. [Downloadable!]
    Other versions:
  4. Helge Berger & Emil Stavrev, 2008. "The Information Content of Money in Forecasting Euro Area Inflation," IMF Working Papers 08/166, International Monetary Fund. [Downloadable!]
  5. Mehrotra , Aaron & Sánchez-Fung, José R., 2008. "Forecasting Inflation in China," BOFIT Discussion Papers 2/2008, Bank of Finland, Institute for Economies in Transition. [Downloadable!]
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