Yeung Lewis Chan (Department of Economics, Harvard University, Cambridge, MA 02138, USA Kennedy School of Government and NBER, 79 John F. Kennedy Street, Harvard University, Cambridge, MA 02138, USA Woodrow Wilson School, Princeton University, Princeton, NJ 08544, USA) James H. Stock (Department of Economics, Harvard University, Cambridge, MA 02138, USA Kennedy School of Government and NBER, 79 John F. Kennedy Street, Harvard University, Cambridge, MA 02138, USA Woodrow Wilson School, Princeton University, Princeton, NJ 08544, USA) Mark W. Watson (Department of Economics, Harvard University, Cambridge, MA 02138, USA Kennedy School of Government and NBER, 79 John F. Kennedy Street, Harvard University, Cambridge, MA 02138, USA Woodrow Wilson School, Princeton University, Princeton, NJ 08544, USA)
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A panel of ex-ante forecasts of a single time series is modeled as a dynamic factor model, where the conditional expectation is the single unobserved factor. When applied to out-of-sample forecasting, this leads to combination forecasts that are based on methods other than OLS. These methods perform well in a Monte Carlo experiment. These methods are evaluated empirically in a panel of simulated real-time computer-generated univariate forecasts of U.S. macroeconomic time series.
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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 C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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