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The use of consumer and business surveys in forecasting

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  • Klein, Lawrence R.
  • Özmucur, Süleyman

Abstract

Surveys improve forecasting performance by adding explanatory power to a model which is based on only past values of manufacturing growth. The issue addressed in this paper is whether surveys of production expectations, when added to equations that contain lagged values of a headline index pertaining to the real economy, improve forecasting performance. If so, it may be better for researchers to use not just the headline index, but production expectations or the Economic Sentiment Indicator if they wish to better predict manufacturing growth.

Suggested Citation

  • Klein, Lawrence R. & Özmucur, Süleyman, 2010. "The use of consumer and business surveys in forecasting," Economic Modelling, Elsevier, vol. 27(6), pages 1453-1462, November.
    • Handle: RePEc:eee:ecmode:v:27:y:2010:i:6:p:1453-1462
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    References listed on IDEAS

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    1. 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.
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    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. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    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.
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    6. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    7. 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.
    8. Sergey V. Arzhenovskiy, 2024. "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February.
    9. Hall, Stephen George & Roudoi, Andrei & Albu, Lucian Liviu & Lupu, Radu & Calin, Adrian Cantemir, 2014. "Lawrence R. Klein and the Economic Forecasting – A Survey," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-14, March.
    10. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    11. Tsuchiya, Yoichi, 2013. "Do corporate executives have accurate predictions for the economy? A directional analysis," Economic Modelling, Elsevier, vol. 30(C), pages 167-174.
    12. Marcin Olkiewicz, 2022. "The Impact of Economic Indicators on the Evolution of Business Confidence during the COVID-19 Pandemic Period," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    13. Gabriel Caldas Montes & André Almeida, 2017. "Corruption and business confidence: a panel data analysis," Economics Bulletin, AccessEcon, vol. 37(4), pages 2692-2702.
    14. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
    15. André Filipe Guedes Almeida & Gabriel Caldas Montes, 2020. "Effects of crime and violence on business confidence: evidence from Rio de Janeiro," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(7), pages 1669-1688, May.
    16. Ahmed, Walid M.A., 2020. "Stock market reactions to domestic sentiment: Panel CS-ARDL evidence," Research in International Business and Finance, Elsevier, vol. 54(C).
    17. Helder Ferreira Mendonça & André Filipe Guedes Almeida, 2019. "Importance of credibility for business confidence: evidence from an emerging economy," Empirical Economics, Springer, vol. 57(6), pages 1979-1996, December.
    18. 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.
    19. Alžbeta Suhányiová & Ladislav Suhányi & Michaela Kočišová, 2023. "Business Confidence in the Sustainable Manufacturing Sector in the Context of Production, Production Prices, and Interest Rates," Sustainability, MDPI, vol. 16(1), pages 1-20, December.
    20. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    21. Dimitriou Dimitrios & Pappas Anastasios & Kazanas Thanassis & Kenourgios Dimitris, 2021. "Do confidence indicators lead Greek economic activity?," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 1-15.
    22. Luboš Marek & Stanislava Hronová & Richard Hindls, 2019. "Možnosti odhadů krátkodobých makroekonomických agregátů na základě výsledků konjunkturních průzkumů [Possibilities of Estimations of Short-term Macroeconomic Aggregates Based on Business Survey Res," Politická ekonomie, Prague University of Economics and Business, vol. 2019(4), pages 347-370.
    23. Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.

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