nep-for New Economics Papers
on Forecasting
Issue of 2006‒05‒06
five papers chosen by
Rob J Hyndman
Monash University

  1. (Un)Predictability and macroeconomic stability By Antonello D’Agostino; Domenico Giannone; Paolo Surico
  2. New Eurocoin: Tracking Economic Growth in Real Time By Altissimo, Filippo; Cristadoro, Riccardo; Forni, Mario; Lippi, Marco; Veronese, Giovanni
  3. An Unobserved Components Model to forecast Austrian GDP By Gerhard Fenz; Martin Spitzer
  4. Estimating multi-country VAR models By Fabio Canova; Matteo Ciccarelli
  5. Real-time model uncertainty in the United States - the Fed from 1996-2003 By Robert J. Tetlow; Brian Ironside

  1. By: Antonello D’Agostino (Address for correspondence: Central Bank and Financial Services Authority of Ireland - Economic Analysis and Research Departmant, PO Box 559 - Dame Street, Dublin 2, Ireland.); Domenico Giannone (ECARES, Université Libre de Bruxelles - CP 114 - av. Jeanne, 44, B-1050, Brussels, Belgium.); Paolo Surico (Monetary Assessment and Strategy, Bank of England, Threadneedle street - EC2R 8AH - London, United Kingdom.)
    Abstract: This paper documents a new stylized fact of the greater macroeconomic stability of the U.S. economy over the last two decades. Using 131 monthly time series, three popular statistical methods and the forecasts of the Federal Reserve’s Greenbook and the Survey of Professional Forecasters, we show that the ability to predict several measures of inflation and real activity declined remarkably, relative to naive forecasts, since the mid-1980s. This break down in forecast ability appears to be an inherent feature of the most recent period and thus represents a new challenge for competing explanations of the ‘Great Moderation’.
    Keywords: Predictive accuracy, macroeconomic stability, forecasting models, sub-sample analysis, Fed Greenbook.
    JEL: E37 E47 C22 C53
    Date: 2006–04
  2. By: Altissimo, Filippo; Cristadoro, Riccardo; Forni, Mario; Lippi, Marco; Veronese, Giovanni
    Abstract: This paper presents ideas and methods underlying the construction of a timely coincident index that tracks euro-area GDP growth, but, unlike GDP growth, (i) is updated monthly and almost in real time; (ii) is free from seasonal and shorter-run dynamics. We take as target the medium- long-run component of the GDP growth, defined in the frequency domain as including only waves of period larger than one year. We estimate the target by projecting it on generalized principal components extracted from a large panel of monthly macroeconomic series. The main contribution of the paper is that current values of our principal components, derived from a dynamic factor model, act as proxies for future values of GDP growth. In this way we improve with respect to the end-of-sample poor estimation which is typical with band-pass filters. Moreover, as it is defined as an estimate of a target which is observable (although with delay), the performance of our index at the end of the sample can be measured.
    Keywords: band-pass filter; coincident index; generalized principal components; large dataset factor models
    JEL: C51 E32 O30
    Date: 2006–04
  3. By: Gerhard Fenz (Oesterreichische Nationalbank, Economic Analysis Division); Martin Spitzer (Oesterreichische Nationalbank, Economic Analysis Division)
    Abstract: This paper deals with forecasting quarterly Austrian GDP growth using monthly conjunctural indicators and state space models. The latter provide an efficient econometric framework to analyse jointly data with different frequencies. Based on a Kalman filter technique we estimate a monthly GDP growth series as an unobserved component using monthly conjunctural indicators as explanatory variables. From a large data set of more than 150 monthly indicators the following six explanatory variables were selected on the basis of their in-sample fit and out of sample forecast performance: the ifo-index, credit growth, vacancies, the real exchange rate, the number of employees and new car registrations. Subsequently, quarterly GDP figures are derived from the monthly unobserved component using a weighted aggregation scheme. Several tests for forecasting accuracy and forecasting encompassing indicate that the unobserved components model (UOC-model) is able to outperform simple ARIMA and Naïve models.
    Date: 2006–03–24
  4. By: Fabio Canova (Universitat Pompeu Fabra, Department of Economics and Business, Jaume I building, Ramon Trias Fargas, 25-27, 08005-Barcelona, Spain.); Matteo Ciccarelli (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.)
    Abstract: This paper describes a methodology to estimate the coefficients, to test specification hypotheses and to conduct policy exercises in multi-country VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of MCMC routine. The transmission of certain shocks across G7 countries is analyzed.
    Keywords: Multi country VAR, Markov Chain Monte Carlo methods, Flexible priors, Internationalv transmission.
    JEL: C3 C5 E5
    Date: 2006–04
  5. By: Robert J. Tetlow (Contact address: Federal Reserve Board, Division of Research and Statistics 20th and Constitution Avenue NW, Washington, D.C. 20551, United States.); Brian Ironside (Safeco Insurance Companies, Safeco Plaza, SPI Actuarial, T-14, Seattle, WA 98185-0001, United States.)
    Abstract: We study 30 vintages of FRB/US, the principal macro model used by the Federal Reserve Board staff for forecasting and policy analysis. To do this, we exploit archives of the model code, coefficients, baseline databases and stochastic shock sets stored after each FOMC meeting from the model’s inception in July 1996 until November 2003. The period of study was one of important changes in the U.S. economy with a productivity boom, a stock market boom and bust, a recession, the Asia crisis, the Russian debt default, and an abrupt change in fiscal policy. We document the surprisingly large and consequential changes in model properties that occurred during this period and compute optimal Taylor-type rules for each vintage. We compare these optimal rules against plausible alternatives. Model uncertainty is shown to be a substantial problem; the efficacy of purportedly optimal policy rules should not be taken on faith.
    Keywords: Monetary policy, uncertainty, real-time analysis.
    JEL: E37 E5 C5 C6
    Date: 2006–04

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