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Forecasting Using First-Available Versus Fully Revised Economic Time-Series Data

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Author Info
Norman Swanson (Pennsylvania State University)

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Abstract

First-reported monthly and quarterly time-series data on nine macroeconomic variables from 1960-1993 are given. Features of this so-called "unrevised" or "first-reported data" are discussed, and the data is compared with standard "fully revised" data using Granger causality tests. For the purposes of real-time forecasting, as well as comparing professional forecasts with traditional econometric forecasts, the use of unrevised (or, even better, "real-time") data has a number of advantages over the use of fully revised data.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 1 (1996)
Issue (Month): 1 ()
Pages: 47-64
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Handle: RePEc:bep:sndecm:1:1996:1:47-64

Note: oai:bepress:snde-1012
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250. [Downloadable!] (restricted)
  2. James D. Hamilton & Gabriel Perez-Quiros, 1995. "What do the Leading Indicators Lead?," University of California at San Diego, Economics Working Paper Series 95-22, Department of Economics, UC San Diego.
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  3. Boschen, John F. & Grossman, Herschel I., 1982. "Tests of equilibrium macroeconomics using contemporaneous monetary data," Journal of Monetary Economics, Elsevier, vol. 10(3), pages 309-333. [Downloadable!] (restricted)
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  4. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June. [Downloadable!] (restricted)
  5. Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA. [Downloadable!]
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  6. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-75, July.
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  7. Phillips, Peter C B, 1995. "Fully Modified Least Squares and Vector Autoregression," Econometrica, Econometric Society, vol. 63(5), pages 1023-78, September. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 2001. "Copycats and Common Swings: the Impact of the Use of Forecasts in Information Sets," Econometrics Working Papers Archive wp2001_01, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti". [Downloadable!]
    Other versions:
  2. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia. [Downloadable!]
  3. Peter Christoffersen & Eric Ghysels & Norman R. Swanson, . "Let's Get "Real" about Using Economic Data," EPRU Working Paper Series 01-15, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics. [Downloadable!]
    Other versions:
  4. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 1999. "The Impact of the Use of Forecasts in Information Sets," University of California at San Diego, Economics Working Paper Series 99-18, Department of Economics, UC San Diego. [Downloadable!]
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  5. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City. [Downloadable!]
    Other versions:
  6. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," International Finance Discussion Papers 684, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
    Other versions:
  7. Dean Croushore & Tom Stark, 2002. "Is macroeconomic research robust to alternative data sets?," Working Papers 02-3, Federal Reserve Bank of Philadelphia. [Downloadable!]
  8. John C. Robertson & Ellis W. Tallman, 1998. "Data vintages and measuring forecast model performance," Economic Review, Federal Reserve Bank of Atlanta, issue Q 4, pages 4-20. [Downloadable!]
  9. Knetsch, Thomas A. & Reimers, Hans-Eggert, 2006. "How to treat benchmark revisions? : The case of German production and orders statistics," Discussion Paper Series 1: Economic Studies 2006,38, Deutsche Bundesbank, Research Centre. [Downloadable!]
  10. Hui Feng, 2005. "Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?," Econometrics Working Papers 0515, Department of Economics, University of Victoria. [Downloadable!]
  11. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia. [Downloadable!]
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  12. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy. [Downloadable!]
  13. Carlo Altavilla & Matteo Ciccarelli, 2007. "Information combination and forecast (st)ability. Evidence from vintages of time-series data," Working Paper Series 846, European Central Bank. [Downloadable!]
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