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What Type Of Social Capital Is Engaged By The French Dairy Stockbreeders? A Characterization Through Their Professional Identities

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  • Mihaela Simionescu

    (Institute for Economic Forecasting of the Romanian Academy, Romania)

Abstract

The GDP forecasting is a prior concern for each country, but also for an entire region composed by more countries with specific and different evolutions of GDP. The GDP predictions for the 27 European Union are based on two econometric techniques. It was proved, using accuracy indicators like U1 and U2 Theil’s coefficients and statistical tests (Morgan-Granger-Newbold test, Harvey-Leybourne-Newbold test and Diebold-Mariano test) that the aggregation of forecasts made for each country in the EU on horizon 2011-2013 provided better forecasts than the use of a single semi-logarithmic model for the entire region. However, the naïve forecasts gave more accurate results than the proposed models, this conclusion being in accordance with the recent results in literature regarding GDP forecasting. For 2013 the ex-ante evaluation of forecasts was made, considering that the actual value is the one registered in 2012. It is anticipated an underestimation of the GDP rate according to the aggregation technique if the benchmark is the indicator’s value in 2012.

Suggested Citation

  • Mihaela Simionescu, 2014. "What Type Of Social Capital Is Engaged By The French Dairy Stockbreeders? A Characterization Through Their Professional Identities," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 8(1), pages 87-102, JUNE.
  • Handle: RePEc:rrs:journl:v:8:y:2014:i:1:p:87-102
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    References listed on IDEAS

    as
    1. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
    2. Marcellino, Massimliano, 2004. "Forecasting EMU macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 20(2), pages 359-372.
    3. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    4. Zizi Goschin, 2007. "Spatial and sectoral analysis of productivity-wage dissimilarities in Romania," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 1(1), pages 33-44, December.
    5. 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.
    6. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    7. Grant Allan, 2012. "Evaluating the usefulness of forecasts of relative growth," Working Papers 1214, University of Strathclyde Business School, Department of Economics.
    8. Bruno Deschamps & Paolo Bianchi, 2012. "An evaluation of Chinese macroeconomic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 10(3), pages 229-246, December.
    9. Ruth, Karsten, 2008. "Macroeconomic forecasting in the EMU: Does disaggregate modeling improve forecast accuracy?," Journal of Policy Modeling, Elsevier, vol. 30(3), pages 417-429.
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    More about this item

    Keywords

    forecasts accuracy; naive forecasts; predictions; GDP rate; econometric model;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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