IDEAS home Printed from https://ideas.repec.org/p/hhs/nierwp/0112.html
   My bibliography  Save this paper

Improving Unemployment Rate Forecasts Using Survey Data

Author

Listed:
  • Österholm, Pär

    (National Institute of Economic Research)

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.

Suggested Citation

  • Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
    • Handle: RePEc:hhs:nierwp:0112
    as

    Download full text from publisher

    File URL: http://www.konj.se/download/18.4ee9b512150ed5e093b906ed/1447246073307/Working-Paper-112-Improving-Unemployment-Rate-Forecasts-Using-Survey-Data.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chao, John & Corradi, Valentina & Swanson, Norman R., 2001. "Out-Of-Sample Tests For Granger Causality," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 598-620, September.
    2. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
    3. Armstrong, J. Scott, 2007. "Significance tests harm progress in forecasting," International Journal of Forecasting, Elsevier, vol. 23(2), pages 321-327.
    4. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    5. 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.
    6. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring.
    7. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    8. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
    9. 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.
    10. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    11. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
    12. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    13. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    14. Berger, Helge & Österholm, Pär, 2009. "Does money still matter for U.S. output?," Economics Letters, Elsevier, vol. 102(3), pages 143-146, March.
    15. 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, John Wiley & Sons, vol. 72(3), pages 597-610, January.
    16. 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, February.
    17. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
    18. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    19. 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.
    20. Andy C.C. Kwan & John A. Cotsomitis, 2006. "The Usefulness of Consumer Confidence in Forecasting Household Spending in Canada: A National and Regional Analysis," Economic Inquiry, Western Economic Association International, vol. 44(1), pages 185-197, January.
    21. Antonio Ribba, 2006. "The joint dynamics of inflation, unemployment and interest rate in the United States since 1980," Empirical Economics, Springer, vol. 31(2), pages 497-511, June.
    22. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    23. Magnus Gustavsson & Pär Österholm, 2010. "The presence of unemployment hysteresis in the OECD: what can we learn from out-of-sample forecasts?," Empirical Economics, Springer, vol. 38(3), pages 779-792, June.
    24. Jared Laxton & Igor Ermolaev & Charles Freedman & Mr. Ondrej Kamenik & Michel Juillard & Mr. Douglas Laxton & Ioan Carabenciov & Dmitry Korshunov, 2008. "A Small Quarterly Multi-Country Projection Model," IMF Working Papers 2008/279, International Monetary Fund.
    25. Hanson, Michael S., 2004. "The "price puzzle" reconsidered," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1385-1413, October.
    26. Franses, Philip Hans & Paap, Richard & Vroomen, Bjorn, 2004. "Forecasting unemployment using an autoregression with censored latent effects parameters," International Journal of Forecasting, Elsevier, vol. 20(2), pages 255-271.
    27. 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, John Wiley & Sons, vol. 72(3), pages 597-610, January.
    28. Yang, Shu-Chun Susan, 2007. "Tentative evidence of tax foresight," Economics Letters, Elsevier, vol. 96(1), pages 30-37, July.
    29. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
    30. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    31. Galina Hale & Òscar Jordà, 2007. "Do monetary aggregates help forecast inflation?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue apr13.
    32. Michel Juillard & Charles Freedman & Dmitry Korshunov & Mr. Douglas Laxton & Mr. Ondrej Kamenik & Ioan Carabenciov & Igor Ermolaev & Jared Laxton, 2008. "A Small Quarterly Multi-Country Projection Model with Financial-Real Linkages and Oil Prices," IMF Working Papers 2008/280, International Monetary Fund.
    33. Philip Rothman, 1998. "Forecasting Asymmetric Unemployment Rates," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 164-168, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Helge Berger & Pär Österholm, 2011. "Does Money Growth Granger Cause Inflation in the Euro Area? Evidence from Out‐of‐Sample Forecasts Using Bayesian VARs," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 45-60, March.
    2. Helge Berger & Pär Österholm, 2011. "Does Money matter for U.S. Inflation? Evidence from Bayesian VARs," CESifo Economic Studies, CESifo Group, vol. 57(3), pages 531-550, September.
    3. Pär Stockhammar & Pär Österholm, 2018. "Do inflation expectations granger cause inflation?," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(2), pages 403-431, August.
    4. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    5. Soyoung Kim, 2013. "Vector autoregressive models for macroeconomic policy analysis," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 23, pages 555-572, Edward Elgar Publishing.
    6. Dimitris Korobilis, 2013. "Var Forecasting Using Bayesian Variable Selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 204-230, March.
    7. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    8. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    9. Raoufina, Karine, 2016. "Forecasting Employment Growth in Sweden Using a Bayesian VAR Model," Working Papers 144, National Institute of Economic Research.
    10. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    11. Beechey, Meredith & Österholm, Pär, 2010. "Forecasting inflation in an inflation-targeting regime: A role for informative steady-state priors," International Journal of Forecasting, Elsevier, vol. 26(2), pages 248-264, April.
    12. Stefan Laséen & Andrea Pescatori, 2020. "Financial stability and interest‐rate policy: A quantitative assessment of costs and benefit," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(3), pages 1246-1273, August.
    13. Zsolt Darvas, 2013. "Monetary transmission in three central European economies: evidence from time-varying coefficient vector autoregressions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(2), pages 363-390, May.
    14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    15. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    16. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    17. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    18. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "The Transmission of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 74-107, July.
    19. Par Osterholm, 2010. "The effect on the Swedish real economy of the financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 20(4), pages 265-274.
    20. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.

    More about this item

    Keywords

    Bayesian VAR; Labour market;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:nierwp:0112. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Hegardt Grant (email available below). General contact details of provider: https://edirc.repec.org/data/kongvse.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.