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The European Commission’s business and consumer surveys and Maltese macroeconomic trends

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  • Aaron G. Grech

Abstract

The European Commission’s business and consumer surveys are the most extensive regular surveys of Maltese firms and households. The Economic Sentiment Indicator (ESI) for Malta is closely correlated with real GDP growth, particularly when one focuses on the first vintage of national accounts data. This suggests that the opinions expressed by economic agents are partly driven by news prevailing at the time. The sectoral confidence indicators that underpin the ESI are quite highly correlated, with construction sentiment being the most synchronised with sentiment in other sectors. In general, sectoral expectations on future activity appear to be less strongly correlated to changes in national accounts sectoral value added than survey responses to planned employment changes are to observed changes in sectoral employment. Maltese household economic expectations appear to be mostly reflective of current conditions and could be useful to forecast variables that are issued with some time lag, like real GDP.

Suggested Citation

  • Aaron G. Grech, "undated". "The European Commission’s business and consumer surveys and Maltese macroeconomic trends," CBM Policy Papers PP/05/2019, Central Bank of Malta.
  • Handle: RePEc:mlt:ppaper:0519
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    File URL: https://www.centralbankmalta.org/file.aspx?f=82475
    File Function: First version, 2019
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Simonelli, Saverio, 2009. "Nowcasting Euro Area Economic Activity in Real Time: The Role of Confidence Indicators," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210, pages 90-97, October.
    2. Sarah Gelper & Christophe Croux, 2010. "On the Construction of the European Economic Sentiment Indicator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 47-62, February.
    3. de Bondt, Gabe & Forsells, Magnus, 2017. "The recent strength of survey-based indicators: what does it tell us about the depth and breadth of real GDP growth?," Economic Bulletin Boxes, European Central Bank, vol. 8.
    4. Guido Bulligan & Massimiliano Marcellino & Fabrizio Venditti, 2012. "Forecasting economic activity with higher frequency targeted predictors," Temi di discussione (Economic working papers) 847, Bank of Italy, Economic Research and International Relations Area.
    5. Ellul, Reuben, 2016. "A real-time measure of business conditions in Malta," MPRA Paper 75057, University Library of Munich, Germany.
    6. Annabelle Mourougane & Moreno Roma, 2003. "Can confidence indicators be useful to predict short term real GDP growth?," Applied Economics Letters, Taylor & Francis Journals, vol. 10(8), pages 519-522.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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