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Identification and Inference in Linear Stochastic Discount Factor Models

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  • Craig Burnside

Abstract

When linear asset pricing models are estimated using excess return data, a normalization of the model must be selected. Several normalizations are equivalent when the model is correctly specified, but the identification conditions differ across normalizations. In practice, some or all of these identification conditions fail statistically when conventional consumption-based models are estimated, and inference is not robust across normalizations. Using asymptotic theory and Monte Carlo simulations, I present evidence that the lack of robustness in qualitative inference across normalizations can be attributed to model misspecification and lack of identification. I propose the use of tests for failure of the rank conditions. Using a calibrated model, I show that these tests are effective in detecting non-identified models.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16634.

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Date of creation: Dec 2010
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Handle: RePEc:nbr:nberwo:16634

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References

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  1. Cragg, John G. & Donald, Stephen G., 1997. "Inferring the rank of a matrix," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 223-250.
  2. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-66.
  3. Jonathan Lewellen & Stefan Nagel & Jay Shanken, 2006. "A Skeptical Appraisal of Asset-Pricing Tests," NBER Working Papers 12360, National Bureau of Economic Research, Inc.
  4. Raymond Kan & Cesare Robotti & Jay Shanken, 2009. "Pricing model performance and the two-pass cross-sectional regression methodology," Working Paper 2009-11, Federal Reserve Bank of Atlanta.
  5. Shanken, Jay & Zhou, Guofu, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," Journal of Financial Economics, Elsevier, vol. 84(1), pages 40-86, April.
  6. Lewellen, Jonathan & Nagel, Stefan, 2003. "The Conditional CAPM Does Not Explain Asset-pricing Anomalies," Working papers 4427-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
  7. Raymond Kan & Cesare Robotti, 2007. "Model comparison using the Hansen-Jagannathan distance," Working Paper 2007-04, Federal Reserve Bank of Atlanta.
  8. Hanno Lustig & Adrien Verdelhan, 2007. "The Cross Section of Foreign Currency Risk Premia and Consumption Growth Risk," American Economic Review, American Economic Association, vol. 97(1), pages 89-117, March.
  9. Kan, Raymond & Robotti, Cesare, 2008. "Specification tests of asset pricing models using excess returns," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 816-838, December.
  10. A. Craig Burnside, 2007. "Empirical Asset Pricing and Statistical Power in the Presence of Weak Risk Factors," NBER Working Papers 13357, National Bureau of Economic Research, Inc.
  11. Wright, Jonathan H., 2003. "Detecting Lack Of Identification In Gmm," Econometric Theory, Cambridge University Press, vol. 19(02), pages 322-330, April.
  12. Motohiro Yogo, 2006. "A Consumption-Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, 04.
  13. Hall, Alastair R., 2004. "Generalized Method of Moments," OUP Catalogue, Oxford University Press, number 9780198775201.
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Cited by:
  1. Craig Burnside, 2011. "The Cross Section of Foreign Currency Risk Premia and Consumption Growth Risk: Comment," American Economic Review, American Economic Association, vol. 101(7), pages 3456-76, December.
  2. Kroencke, Tim A. & Schindler, Felix & Sebastian, Steffen & Theissen, Erik, 2013. "GDP mimicking portfolios and the cross-section of stock returns," ZEW Discussion Papers 13-026, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  3. Craig Burnside, 2011. "Carry Trades and Risk," NBER Working Papers 17278, National Bureau of Economic Research, Inc.

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