IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v23y2007i1p15-28.html
   My bibliography  Save this article

Using forecasts of forecasters to forecast

Author

Listed:
  • Nolte, Ingmar
  • Pohlmeier, Winfried

Abstract

No abstract is available for this item.

Suggested Citation

  • Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.
    • Handle: RePEc:eee:intfor:v:23:y:2007:i:1:p:15-28
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(06)00055-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dasgupta, Susmita & Lahiri, Kajal, 1992. "A Comparative Study of Alternative Methods of Quantifying Qualitative Survey Responses Using NAPM Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 391-400, October.
    2. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    3. Smith, Jeremy & McAleer, Michael, 1995. "Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 165-185, April-Jun.
    4. James Mitchell & Richard J. Smith & Martin R. Weale, 2002. "Quantification of Qualitative Firm-Level Survey Data," Economic Journal, Royal Economic Society, vol. 112(478), pages 117-135, March.
    5. 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.
    6. Pesaran, M Hashem, 1985. "Formation of Inflation Expectations in British Manufacturing Industries," Economic Journal, Royal Economic Society, vol. 95(380), pages 948-975, December.
    7. Nerlove, Marc, 1983. "Expectations, Plans, and Realizations in Theory and Practice," Econometrica, Econometric Society, vol. 51(5), pages 1251-1279, September.
    8. Kaiser, Ulrich & Spitz, Alexandra, 2000. "Quantification of qualitative data using ordered probit models with an application to a business survey in the German service sector," ZEW Discussion Papers 00-58, ZEW - Leibniz Centre for European Economic Research.
    9. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    10. Lahiri, Kajal & Teigland, Christie, 1987. "On the normality of probability distributions of inflation and GNP forecasts," International Journal of Forecasting, Elsevier, vol. 3(2), pages 269-279.
    11. repec:bla:econom:v:55:y:1988:i:219:p:317-31 is not listed on IDEAS
    12. repec:bla:econom:v:42:y:1975:i:166:p:123-38 is not listed on IDEAS
    13. Batchelor, R. A., 1982. "Expectations, output and inflation : The European experience," European Economic Review, Elsevier, vol. 17(1), pages 1-25.
    14. Wren-Lewis, Simon, 1986. "An Econometric Model of U.K. Manufacturing Employment Using Survey Data on Expected Output," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(4), pages 297-316, October.
    15. Fishe, Raymond P. H. & Lahiri, Kajal, 1981. "On the estimation of inflationary expectations from qualitative responses," Journal of Econometrics, Elsevier, vol. 16(1), pages 89-102, May.
    16. Fishe, Raymond P H & Idson, Todd L, 1990. "Information-Induced Heteroscedasticity in Price Expectations Data," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 304-312, May.
    17. Begg,Iain & Henry,Brian, 1998. "Applied Economics and Public Policy," Cambridge Books, Cambridge University Press, number 9780521624145, September.
    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. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    3. repec:amu:wpaper:2013-04 is not listed on IDEAS
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    5. Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237.
    6. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    7. Frederik Kunze, 2020. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 313-333, March.
    8. Panagiotis Papaioannnou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Papers 1310.5306, arXiv.org.
    9. Sandra Schmidt & Dieter Nautz, 2012. "Central Bank Communication and the Perception of Monetary Policy by Financial Market Experts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(2‐3), pages 323-340, March.
    10. Kunze, Frederik, 2017. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," University of Göttingen Working Papers in Economics 326, University of Goettingen, Department of Economics.
    11. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    12. Mokinski, Frieder, 2016. "Using time-stamped survey responses to measure expectations at a daily frequency," International Journal of Forecasting, Elsevier, vol. 32(2), pages 271-282.
    13. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    14. Stolzenburg, Ulrich & Lux, Thomas, 2010. "Identification of a core-periphery structure among participants of a business climate survey," Kiel Working Papers 1659, Kiel Institute for the World Economy (IfW Kiel).
    15. Kjellberg, David, 2006. "Measuring Expectations," Working Paper Series 2006:9, Uppsala University, Department of Economics.
    16. Brückbauer, Frank & Schröder, Michael, 2021. "Data resource profile: The ZEW FMS dataset," ZEW Discussion Papers 21-100, ZEW - Leibniz Centre for European Economic Research.
    17. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    18. Breitung, Jörg & Schmeling, Maik, 2013. "Quantifying survey expectations: What’s wrong with the probability approach?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 142-154.
    19. Heilemann, Ullrich & Stekler, H. O., 2003. "Has the accuracy of German macroeconomic forecasts improved?," Technical Reports 2003,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    20. Henry Sabrowski, 2008. "Inflation Expectation Formation of German Consumers: Rational or Adaptive?," Working Paper Series in Economics 100, University of Lüneburg, Institute of Economics.
    21. Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.

    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. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    2. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    3. Olivier Biau & Hélène Erkel-Rousse & Nicolas Ferrari, 2006. "Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière," Économie et Statistique, Programme National Persée, vol. 395(1), pages 91-116.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    6. Breitung, Jörg & Schmeling, Maik, 2013. "Quantifying survey expectations: What’s wrong with the probability approach?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 142-154.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    8. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data: A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    9. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    10. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.
    11. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.
    12. Ray Barrell, 1999. "Employment Security and European Labour Demand: A Panel Study Across 16 Industries," National Institute of Economic and Social Research (NIESR) Discussion Papers 148, National Institute of Economic and Social Research.
    13. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    14. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    15. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    16. Jürgen Bierbaumer & Werner Hölzl, 2015. "Business Cycle Dynamics and Firm Heterogeneity. Evidence for Austria Using Survey Data," WIFO Working Papers 504, WIFO.
    17. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.
    18. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    19. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    20. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    More about this item

    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:eee:intfor:v:23:y:2007:i:1:p:15-28. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.