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The Role of Survey Data in the Construction of Short-term GDP Growth Forecasts

Author

Listed:
  • Christos Papamichael

    (Economics Research Centre, University of Cyprus)

  • Nicoletta Pashourtidou

    (Economics Research Centre, University of Cyprus)

Abstract

The aim of this paper is to investigate the role of Business and Consumer Survey data, published by the European Commission, in the construction of short-term gross domestic product (GDP) growth forecasts. A pseudo out-of-sample forecasting exercise is conducted in which the availability of data mimics real-time releases. A sequence of GDP growth estimates is computed starting 5½ months prior to the publication of GDP growth and ending about 10 days before the release of the actual figure. The focus of the analysis is on Cyprus and some of its key trading partners. Due to the openness of the Cypriot economy, timely information on the expected economic performance of Cyprus’s main trading partners is crucial to the assessment of domestic prospects and challenges. The analysis for Cyprus reveals that the use of survey data improves the accuracy of GDP growth estimates, but the forecasting gains are not always statistically significant. The improvements in forecast accuracy from the use of survey data are larger and more significant for the euro area, the European Union and Greece compared to those for Cyprus, while survey predictors are not found to enhance the precision of GDP growth estimates for the United Kingdom. Thus, survey information for the European Union and the euro area as a whole, as well as for Greece, can be used by practitioners to extract reliable signals for the short-term growth prospects of these economies and identify risks to the outlook for the Cypriot economy. The use of survey data for Cyprus resulted in large forecasting gains during the international financial crisis and its aftermath and predicted the depth of the recession in 2009 and 2013 fairly accurately. Moreover, information from the Business and Consumer Surveys correctly signalled the moderation of the recession in Cyprus in 2013–2014.

Suggested Citation

  • Christos Papamichael & Nicoletta Pashourtidou, 2016. "The Role of Survey Data in the Construction of Short-term GDP Growth Forecasts," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 10(2), pages 77-109, December.
    • Handle: RePEc:erc:cypepr:v:10:y:2016:i:2:p:77-109
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    2. Ali Al‐Eyd & Ray Barrell & E. Philip Davis, 2009. "Consumer Confidence Indices And Short‐Term Forecasting Of Consumption," Manchester School, University of Manchester, vol. 77(1), pages 96-111, January.
    3. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-44, February.
    6. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
    7. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    8. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring.
    9. Karim Barhoumi & Olivier Darné & Laurent Ferrara & Bertrand Pluyaud, 2012. "Monthly Gdp Forecasting Using Bridge Models: Application For The French Economy," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 53-70, December.
    10. repec:bla:buecrs:v:64:y:2012:i::p:s53-s70 is not listed on IDEAS
    11. Marie Diron, 2008. "Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 371-390.
    12. Batchelor, Roy & Dua, Pami, 1998. "Improving macro-economic forecasts: The role of consumer confidence," International Journal of Forecasting, Elsevier, vol. 14(1), pages 71-81, March.
    13. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    14. John A. Cotsomitis & Andy C. C. Kwan, 2006. "Can Consumer Confidence Forecast Household Spending? Evidence from the European COmmission Business and Consumer Surveys," Southern Economic Journal, John Wiley & Sons, vol. 72(3), pages 597-610, January.
    15. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
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