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Qualitative Survey Responses and Production over the Business Cycle

Author

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  • Lindström, Tomas

    (Monetary Policy Department, Central Bank of Sweden)

Abstract

An examination of Swedish manufacturing data on real output and qualitative business tendency survey (BTS) responses from 1968 through 1998 reveals that survey-based attitude data typically improve the fit of simple autoprojective models of manufacturing output growth. It also turns out that traditional autoregressive distributed lag (ADL) models based on business survey data can provide more accurate one-quarter-ahead forecasts of output growth than naive alternatives. Another finding is that when BTS variables concerning ex post (ex ante) output growth are included in the empirical specifications, then no other ex post (ex ante) business survey variables seems to include any additional information about output growth.

Suggested Citation

  • Lindström, Tomas, 2000. "Qualitative Survey Responses and Production over the Business Cycle," Working Paper Series 116, Sveriges Riksbank (Central Bank of Sweden).
  • Handle: RePEc:hhs:rbnkwp:0116
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    File URL: http://www.riksbank.com/upload/4671/wp_116.pdf
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    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. Bechtel, Gordon G., 1981. "Measuring subjective social indicators," Journal of Economic Psychology, Elsevier, vol. 1(3), pages 165-181, September.
    3. Benjamin M. Friedman, 1980. "Survey Evidence on The Rationality of Interest Rate Expectations," NBER Working Papers 0261, National Bureau of Economic Research, Inc.
    4. Jonung, Lars, 1986. "Uncertainty about inflationary perceptions and expectations," Journal of Economic Psychology, Elsevier, vol. 7(3), pages 315-325, September.
    5. Nerlove, Marc, 1983. "Expectations, Plans, and Realizations in Theory and Practice," Econometrica, Econometric Society, vol. 51(5), pages 1251-1279, September.
    6. Carlson, John A & Parkin, J Michael, 1975. "Inflation Expectations," Economica, London School of Economics and Political Science, vol. 42(166), pages 123-138, May.
    7. F. Modigliani & H. M. Weingartner, 1958. "Forecasting Uses of Anticipatory Data on Investment and Sales," The Quarterly Journal of Economics, Oxford University Press, vol. 72(1), pages 23-54.
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    Citations

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    Cited by:

    1. Hansson, Jesper & Jansson, Per & Löf, Mårten, 2003. "Business Survey Data: Do They Help in Forecasting the Macro Economy?," Working Papers 84, National Institute of Economic Research.
    2. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2004. "On The Predictive Content Of Production Surveys: A Pan-European Study," ERIM Report Series Research in Management ERS-2004-017-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    More about this item

    Keywords

    Business cycles; Economic indicators; Manufacturing; Survey data; Time-series models;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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