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The Use of Qualitative Business Tendency Surveys for Forecasting Business Investment in Germany

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  • Klaus Abberger

Abstract

Investment in equipment and machinery is a very important component of GDP. In this paper we examine whether data from business tendency surveys are useful for a timely assessment of current investment behavior. In addition we investigate whether the survey results are helpful for forecasting investment growth in the short run. The first question is addressed with the help of spectral analysis. To study the forecast ability we estimate linear autoregressive and additive autoregressive models. The forecasting performance is assessed through filtered residuals. The analyses show that the business survey is indeed a useful tool for assessing investment in equipment and machinery.

Suggested Citation

  • Klaus Abberger, 2005. "The Use of Qualitative Business Tendency Surveys for Forecasting Business Investment in Germany," ifo Working Paper Series No.13, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Handle: RePEc:ces:ifowps:_no.13
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    File URL: https://www.ifo.de/DocDL/IfoWorkingPaper-13.pdf
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    References listed on IDEAS

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    1. Daniel Pena & Ismael Sanchez, 2005. "Multifold Predictive Validation in ARMAX Time Series Models," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 135-146, March.
    2. Oliner, Stephen & Rudebusch, Glenn & Sichel, Daniel, 1995. "New and Old Models of Business Investment: A Comparison of Forecasting Performance," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(3), pages 806-826, August.
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    Cited by:

    1. Sascha O. Becker & Klaus Wohlrabe, 2008. "European Data Watch: Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(2), pages 307-319.
    2. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 27-42, June.
    3. 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.
    4. Rossi, José Luiz J. & Laban, Sílvio A. Neto & Claro, Danny Pimentel & Bolzani, Luciana Corrêa, 2009. "Índice de Confiança do Empresário de Pequenos e Médios Negócios no Brasil (IC-PMN): Desenvolvimento e Consolidação," Insper Working Papers wpe_191, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Claro, Danny P & Júnior, José L. R. & Laban Neto, Sílvio A. & Lucci, Cíntia R. & Bolzani, Luciana C. & Carvalho, Marina D. de, 2009. "Índice de Confiança do Empresário de Pequenos e Médios Negócios no Brasil (IC-PMN): Metodologia e Resultados Preliminares," Insper Working Papers wpe_158, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

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    More about this item

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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