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Improving Unemployment Rate Forecasts Using Survey Data

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Author Info
Österholm, Pär () (National Institute of Economic Research)

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Abstract

This paper investigates whether forecasts of the Swedish unemployment rate can be improved by using business and household survey data. We conduct an out-of-sample forecast exercise in which the performance of a Bayesian VAR model with only macroeconomic data is compared to that when the model also includes survey data. Results show that the forecasting performance at short horizons can be improved. The im-provement is largest when forward-looking data from the manufacturing industry is employed.

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Publisher Info
Paper provided by National Institute of Economic Research in its series Working Paper with number 112.

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Length: 27 pages
Date of creation: 01 Jun 2009
Date of revision:
Handle: RePEc:hhs:nierwp:0112

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Related research
Keywords: Bayesian VAR; Labour market;

Find related papers by JEL classification:
E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation
E24 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution
E27 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation

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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. Pär Österholm, 2008. "Can forecasting performance be improved by considering the steady state? An application to Swedish inflation and interest rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 41-51. [Downloadable!]
  2. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring. [Downloadable!] (restricted)
  3. John A. Cotsomitis & Andy C. C. Kwan, 2006. "Can Consumer Confidence Forecast Household Spending? Evidence from the European COmmission Business and Consumer Surveys," Southern Economic Journal, Southern Economic Association, vol. 72(3), pages 597-610, January.
  4. Malin Adolfson & Michael K. Andersson & Jesper Lindé & Mattias Villani & Anders Vredin, 2007. "Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 111-144, December. [Downloadable!]
    Other versions:
  5. Galina Hale & Òscar Jordà, 2007. "Do monetary aggregates help forecast inflation?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue Apr 13. [Downloadable!]
  6. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121. [Downloadable!] (restricted)
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  7. Amos Golan & Jeffrey M. Perloff, 2004. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 433-438, 01. [Downloadable!] (restricted)
    Other versions:
  8. Philip Rothman, 1998. "Forecasting Asymmetric Unemployment Rates," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 164-168, February. [Downloadable!] (restricted)
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  9. Berger, Helge & Österholm, Pär, 2009. "Does money still matter for U.S. output?," Economics Letters, Elsevier, vol. 102(3), pages 143-146, March. [Downloadable!] (restricted)
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  10. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-67, July. [Downloadable!] (restricted)
  11. Armstrong, J. Scott, 2007. "Significance tests harm progress in forecasting," International Journal of Forecasting, Elsevier, vol. 23(2), pages 321-327. [Downloadable!] (restricted)
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