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Predictive Evaluation of Sectoral and Total Employment Based on Entrepreneurial Confidence Indicators

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  • Pablo Pincheira B.

Abstract

We evaluate the ability of the monthly index of entrepreneurial confidence (IMCE) to predict the twelvemonth variation of total and sectoral employment. By focusing solely on the predictive relationship between employment and IMCE indicators —excluding from the analysis the autoregressive terms of the respective employment variables—, we find strong evidence of predictive power at the aggregate level and in the construction, trade and manufacturing sectors. When we incorporate in the analysis an autoregressive structure for employment, the additional predictive capacity of the IMCE indicators becomes more elusive and difficult to detect. However, there is evidence that the IMCE-Total has better predictive power than that found in the univariate structure of aggregate employment. By sectors, although the results are less robust than for the aggregate, the construction sector stands out for its fairly strong evidence of predictability while the mining sector emerges as one with little evidence of predictive ability.

Suggested Citation

  • Pablo Pincheira B., 2014. "Predictive Evaluation of Sectoral and Total Employment Based on Entrepreneurial Confidence Indicators," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 17(1), pages 66-87, April.
  • Handle: RePEc:chb:bcchec:v:17:y:2014:i:1:p:66-87
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    References listed on IDEAS

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    1. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    2. 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.
    3. Pablo Matias Pincheira Brown, 2013. "Shrinkage‐Based Tests of Predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 307-332, July.
    4. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    5. Pablo Pincheira & Carlos A. Medel, 2012. "Forecasting Inflation with a Simple and Accurate Benchmark: a Cross-Country Analysis," Working Papers Central Bank of Chile 677, Central Bank of Chile.
    6. Pincheira, Pablo & García, Álvaro, 2012. "En busca de un buen marco de referencia predictivo para la inflación en Chile," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(313), pages 85-123, enero-mar.
    7. Ghysels, Eric & Osborn, Denise R. & Rodrigues, Paulo M.M., 2006. "Forecasting Seasonal Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 13, pages 659-711, Elsevier.
    8. Javier Contreras-Reyes & Byron Idrovo, 2011. "En busca de un modelo Benchmark univariado para predecir la tasa de desempleo," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, December.
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