nep-for New Economics Papers
on Forecasting
Issue of 2010‒06‒26
five papers chosen by
Rob J Hyndman
Monash University

  1. The Diversity of Forecasts from Macroeconomic Models of the U.S. Economy By Volker Wieland; Maik Wolters
  2. Evaluating real-time VAR forecasts with an informative democratic prior By Jonathan H. Wright
  3. Volatility forecasting of carbon prices using factor models. By Chevallier, Julien
  4. Yield-Curve Based Probability Forecasts of U.S. Recessions: Stability and Dynamics By Heikki Kauppi
  5. Theorem of existence of ruptures in probability scale. Preliminary short version. By Harin, Alexander

  1. By: Volker Wieland (Goethe University Frankfurt, Center for Financial Studies, and CEPR); Maik Wolters (Goethe University Frankfurt)
    Abstract: This paper investigates the accuracy and heterogeneity of output growth and inflation forecasts during the current and the four preceding NBER-dated U.S. recessions. We generate forecasts from six different models of the U.S. economy and compare them to professional forecasts from the Federal Reserve’s Greenbook and the Survey of Professional Forecasters (SPF). The model parameters and model forecasts are derived from historical data vintages so as to ensure comparability to historical forecasts by professionals. The mean model forecast comes surprisingly close to the mean SPF and Greenbook forecasts in terms of accuracy even though the models only make use of a small number of data series. Model forecasts compare particularly well to professional forecasts at a horizon of three to four quarters and during recoveries. The extent of forecast heterogeneity is similar for model and professional forecasts but varies substantially over time. Thus, forecast heterogeneity constitutes a potentially important source of economic fluctuations. While the particular reasons for diversity in professional forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets and parameter estimates.
    Keywords: Forecasting, Business Cycles, Heterogeneous Beliefs, Forecast Distribution, Model Uncertainty, Bayesian Estimation
    JEL: C53 D84 E31 E32 E37
    Date: 2010–05–20
    URL: http://d.repec.org/n?u=RePEc:cfs:cfswop:wp201008&r=for
  2. By: Jonathan H. Wright
    Abstract: This paper proposes Bayesian forecasting in a vector autoregression using a democratic prior. This prior is chosen to match the predictions of survey respondents. In particular, the unconditional mean for each series in the vector autoregression is centered around long-horizon survey forecasts. Heavy shrinkage toward the democratic prior is found to give good real-time predictions of a range of macroeconomic variables, as these survey projections are good at quickly capturing endpoint-shifts.
    Keywords: Forecasting ; Real-time data
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:fip:fedpwp:10-19&r=for
  3. By: Chevallier, Julien
    Abstract: This article develops a forecasting exercise of the volatility of EUA spot, EUA futures, and CER futures carbon prices (modeled after an AR(1)-GARCH(1,1)) using two dynamic factors as exogenous regressors that were extracted from a Factor Augmented VAR model (Bernanke et al. (2005)). The dataset includes 115 macroeconomic, financial and commodities indicators with daily frequency from April 4, 2008 through January 25, 2010 totalling 463 observations that capture the strong uncertainties emerging on the carbon market. The main result shows that the best forecasting performance for the volatility of carbon prices is achieved for the model including the dynamic factors as exogenous regressors, which can be useful to inform hedging or speculative trading strategies by energy utilities, financial market players and risk managers.
    Keywords: Volatility Forecasting; Carbon price; Factor models;
    JEL: Q4 C3
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:ner:dauphi:urn:hdl:123456789/4349&r=for
  4. By: Heikki Kauppi (Department of Economics, University of Turku)
    Abstract: Various papers indicate that the yield-curve has superior predictive power for U.S. recessions. However, there is controversial evidence on the stability of the predictive relationship and it has remained unclear how the persistence of the underlying binary recession indicator should be taken into account. We show that a yield-curve based probit model treating the binary recession series as a nonhomogeneous first-order Markov chain sufficiently captures the persistence of the U.S. business cycles and produces recession probability forecasts that outperform those based on a conventional static model. We obtain evidence for instability in the predictive content of the yield-curve that centers on a structural change in the early 1980s. We conclude that the simple dynamic model with parameters estimated using data after the breakpoint is likely to provide useful probability forecasts of U.S. recessions in the future.
    Keywords: recession forecast, yield curve, dynamic probit models, parameter stability
    JEL: C22 C25 E32 E37
    Date: 2010–06
    URL: http://d.repec.org/n?u=RePEc:tkk:dpaper:dp57&r=for
  5. By: Harin, Alexander
    Abstract: The theorems of existence of the ruptures have been proved. The ruptures can exist near the borders of finite intervals and of the probability scale. The theorems can be used, e.g., in economics and forecasting.
    Keywords: probability; economics; forecasting; planning; modeling; modelling; simulation; utility; decisions; uncertainty;
    JEL: G11 D81 O2 H3 C1 E47
    Date: 2010–06–15
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:23319&r=for

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