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New Goodness-of-fit Diagnostics for Conditional Discrete Response Models

Listed author(s):
  • Igor Kheifets

    (New Economic School, Moscow)

  • Carlos Velasco

    (Dept. of Economics, Universidad Carlos III de Madrid)

This paper proposes new specification tests for conditional models with discrete responses. In particular, we can test the static and dynamic ordered choice model specifications, which is key to apply efficient maximum likelihood methods, to obtain consistent estimates of partial effects and to get appropriate predictions of the probability of future events. The traditional approach is based on probability integral transforms of a jittered discrete data which leads to continuous uniform iid series under the true conditional distribution. We investigate in this paper an alternative transformation based only on original discrete data. We show analytically and in simulations that our approach dominates the traditional approach in terms of power. We apply the new tests to models of the monetary policy conducted by the Federal Reserve.

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File URL: http://cowles.yale.edu/sites/default/files/files/pub/d19/d1924.pdf
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Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1924.

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Length: 33 pages
Date of creation: Nov 2013
Handle: RePEc:cwl:cwldpp:1924
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Yale University, Box 208281, New Haven, CT 06520-8281 USA

Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.yale.edu/

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Order Information: Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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