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Multistep Predictions for Multivariate GARCH Models: Closed Form Solution and the Value for Portfolio Management

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  • Jaroslava HLOUSKOVA
  • Kurt SCHMIDHEINY
  • Martin WAGNER

Abstract

The missing wage rigidity in general equilibrium models of efficiency wages is an artifact of the external wage reference perspective conventionally adopted by the literature. Efficiency wage models based on an internal wage reference perspective are capable of generating strong wage rigidity. We propose a structural model of efficiency wages that is broadly consistent with the reported evidence on fairness in labor relations and rent-sharing. Our model provides a robust explanation for wage rigidity and procyclical effort. It also rationalizes reciprocal behavior by workers and the observation that firm productivity is a significant predictor of wage setting.

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Bibliographic Info

Paper provided by Université de Lausanne, Faculté des HEC, DEEP in its series Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) with number 04.10.

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Length: 25 pages
Date of creation: Jun 2004
Date of revision:
Handle: RePEc:lau:crdeep:04.10

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Postal: Université de Lausanne, Faculté des HEC, DEEP, Internef, CH-1015 Lausanne
Phone: ++41 21 692.33.64
Fax: ++41 21 692.33.05
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Web page: http://www.hec.unil.ch/deep/publications/cahiers/series
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Keywords: multivariate GARCH models; volatility forecasts; portfolio optimization; minimum variance portfolio;

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References

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  1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
  2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  3. Ravi Jagannathan & Tongshu Ma, 2002. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," NBER Working Papers 8922, National Bureau of Economic Research, Inc.
  4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  5. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," CORE Discussion Papers 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Baillie, Richard T. & Bollerslev, Tim, 1992. "Prediction in dynamic models with time-dependent conditional variances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 91-113.
  7. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  8. Baillie, Richard T., 1980. "Predictions from ARMAX models," Journal of Econometrics, Elsevier, vol. 12(3), pages 365-374, April.
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  11. Li, W K & Ling, Shiqing & McAleer, Michael, 2002. " Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-69, July.
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  16. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  17. Nilsson, Birger, 2002. "International Asset Pricing and the Benefits from World Market Diversification," Working Papers 2002:1, Lund University, Department of Economics.
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Citations

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Cited by:
  1. Francisco Rubio & Xavier Mestre & Daniel P. Palomar, 2011. "Performance analysis and optimal selection of large mean-variance portfolios under estimation risk," Papers 1110.3460, arXiv.org.
  2. Lahiri, Kajal & Liu, Fushang, 2005. "ARCH models for multi-period forecast uncertainty-a reality check using a panel of density forecasts," MPRA Paper 21693, University Library of Munich, Germany.
  3. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.

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