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Information in the Revision Process of Real-Time Datasets

  • Norman R. Swanson

    ()

    (Rutgers University)

  • Valentina Corradi

    ()

    (University of Warwick)

  • Andres Fernandez

    ()

    (Universidad de Los Andes)

Rationality of early release data is typically tested using linear regressions. Thus, failure to reject the null does not rule out the possibility of nonlinear dependence. This paper proposes two tests that have power against generic nonlinear alternatives. A Monte Carlo study shows that the suggested tests have good finite sample properties. Additionally, we carry out an empirical illustration using a real-time dataset for money, output, and prices. Overall, we find evidence against data rationality for output and prices, but not for money

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Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 201107.

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Length: 20 pages
Date of creation: 14 May 2011
Date of revision:
Publication status: Published in Journal of Business and Economic Statistics, 27, 455-467
Handle: RePEc:rut:rutres:201107
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  1. Kavajecz, Kenneth & Collins, Sean, 1995. "Rationality of Preliminary Money Stock Estimates," The Review of Economics and Statistics, MIT Press, vol. 77(1), pages 32-41, February.
  2. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
  3. Hansen, B.E., 1991. "Inference when a Nuisance Parameter is Not Identified Under the Null Hypothesis," RCER Working Papers 296, University of Rochester - Center for Economic Research (RCER).
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