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Using Large Data Sets to Forecast Sectoral Employment

Listed author(s):
  • Rangan Gupta

    ()

    (Department of Economics, University of Pretoria)

  • Alain Kabundi

    ()

    (Department of Economics and Econometrics, University of Johannesburg)

  • Stephen M. Miller

    ()

    (Department of Economics, University of Nevada, Las Vegas)

  • Josine Uwilingiye

    ()

    (Department of Economics and Econometrics, University of Johannesburg)

We implement several Bayesian and classical models to forecast employment for eight sectors of the US economy. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of 143 additional monthly series in some models. Several approaches exist for incorporating information from a large number of series. We consider two approaches – extracting common factors (principle components) in a factor-augmented vector autoregressive or vector error-correction, Bayesian factor-augmented vector autoregressive or vector error-correction models, or Bayesian shrinkage in a large-scale Bayesian vector autoregressive models. Using the period of January 1972 to December 1999 as the in-sample period and January 2000 to March 2009 as the out-of-sample horizon, we compare the forecast performance of the alternative models. Finally, we forecast out-of sample from April 2009 through March 2010, using the best forecasting model for each employment series. We find that factor augmented models, especially error-correction versions, generally prove the best in out-of-sample forecast performance, implying that in addition to macroeconomic variables, incorporating long-run relationships along with short-run dynamics play an important role in forecasting employment.

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File URL: http://web.unlv.edu/projects/RePEc/pdf/1106.pdf
File Function: First version, 2011
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Paper provided by University of Nevada, Las Vegas , Department of Economics in its series Working Papers with number 1106.

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Length: 42 pages
Date of creation: Mar 2011
Handle: RePEc:nlv:wpaper:1106
Contact details of provider: Phone: (702) 895-3776
Fax: (702) 895-1354
Web page: http://business.unlv.edu/econ/

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  1. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
  2. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc.
  3. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  4. Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics 572, Boston College Department of Economics.
  5. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2011. "Forecasting large datasets with Bayesian reduced rank multivariate models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 735-761, 08.
  6. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
  7. Rangan Gupta & Stephen M. Miller, 2009. "The Time-Series Properties on Housing Prices: A Case Study of the Southern California Market," Working papers 2009-10, University of Connecticut, Department of Economics, revised Dec 2009.
  8. Sonali Das & Rangan Gupta & Alain Kabundi, 2009. "Could we have predicted the recent downturn in the South African Housing Market?," Working Papers 149, Economic Research Southern Africa.
  9. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
  10. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
  11. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  12. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2008. "Forecasting Exchange Rates with a Large Bayesian VAR," Working Papers 634, Queen Mary University of London, School of Economics and Finance.
  13. David E. Rapach & Jack K. Strauss, 2008. "Forecasting US employment growth using forecast combining methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 75-93.
  14. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages -.
  15. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2009. "Forecasting with Factor-Augmented Error Correction Models," Discussion Papers 09-06, Department of Economics, University of Birmingham.
  16. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  17. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2010. "Forecasting with Factor-augmented Error Correction," Discussion Papers 09-06r, Department of Economics, University of Birmingham.
  18. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
  19. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
  20. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  21. David Rapach & Jack Strauss, 2010. "Bagging or Combining (or Both)? An Analysis Based on Forecasting U.S. Employment Growth," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 511-533.
  22. Anindya Banerjee & Massimiliano Marcellino, 2008. "Factor-augmented Error Correction Models," Economics Working Papers ECO2008/15, European University Institute.
  23. David E. Rapach & Jack K. Strauss, 2005. "Forecasting employment growth in Missouri with many potentially relevant predictors: an analysis of forecast combining methods," Regional Economic Development, Federal Reserve Bank of St. Louis, issue Nov, pages 97-112.
  24. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
  25. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  26. Rangan Gupta & Stephen M. Miller, 2009. ""Ripple Effects" and Forecasting Home Prices in Los Angeles, Las Vegas, and Phoenix," Working papers 2009-05, University of Connecticut, Department of Economics, revised Jun 2009.
  27. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
  28. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  29. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
  30. Taylor, Carol A., 1982. "Econometric modeling of urban and other substate areas : An analysis of alternative methodologies," Regional Science and Urban Economics, Elsevier, vol. 12(3), pages 425-448, August.
  31. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  32. Christoffel, Kai & Warne, Anders & Coenen, Günter, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
  33. Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.
  34. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  35. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
  36. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, Oxford University Press, vol. 120(1), pages 387-422.
  37. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
  38. LeSage, James P, 1990. "A Comparison of the Forecasting Ability of ECM and VAR Models," The Review of Economics and Statistics, MIT Press, vol. 72(4), pages 664-671, November.
  39. Glennon, Dennis & Lane, Julia & Johnson, Stanley, 1987. "Regional econometric models that reflect labor market relations," International Journal of Forecasting, Elsevier, vol. 3(2), pages 299-312.
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