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The Contribution Of Business Confidence Indicators In Short-Term Forecasting Of Economic Development

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  • Gagea Mariana

    (Alexandru Ioan Cuza University of Iasi, Faculty of Economics and Business Administration)

Abstract

In this paper we study the usefulness of using confidence indicators derived from business surveys in the assessment of the state of economy and in short-term forecasting. For this purpose, we consider the relationship between the industrial confidence indicator and industrial production index in Romania and other European Union member states. We apply graphic methods to analyze the dynamics of variables considered, cointegration and causality tests, as well as the synchronization analysis of cyclical patterns of the confidence indicator and the industrial production index. The cyclic component of data series is extracted with Hodrick-Prescott filter and the identification of turning points is made with Bry -Boschan procedure. The results indicate that the industrial confidence indicator provides important information on the status and evolution of economic activity, although significant differences were found between the countries analyzed. For Romania, the confidence indicator is not Granger-cause for the reference series and the cycles of the two series do not have a strong synchronization, which restrict the use of the confidence indicator in assessing and forecasting the country's economic activity.

Suggested Citation

  • Gagea Mariana, 2012. "The Contribution Of Business Confidence Indicators In Short-Term Forecasting Of Economic Development," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 617-623, July.
    • Handle: RePEc:ora:journl:v:1:y:2012:i:1:p:617-623
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    References listed on IDEAS

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    More about this item

    Keywords

    confidence indicators; industrial production index; Granger causality test; Hodrick-Prescott filter; Bry-Boschan procedure;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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