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Identification and Estimation in an Incoherent Model of Contagion

Listed author(s):
  • Massacci, D.
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    This paper deals with the issues of identification and estimation in the canonical model of contagion advanced in Pesaran and Pick (2007). The model is a two-equation nonlinear simultaneous equations system with endogenous dummy variables; it also represents an extension of univariate threshold autoregressive (TAR) models to a simultaneous equations framework. For a range of economic fundamentals, the model produces multiple (i.e. two) equilibria, and the choice of the equilibrium is modelled as being driven by a Bernoulli process; further, the presence of multiple equilibria leads to an incoherent econometric specification. The coherency issue is then reflected in the analytical expression for the likelihood function derived in the paper. It is proved that neither identification nor Full Information Maximum Likelihood (FIML) estimation of the model require knowledge of the Bernoulli process driving the solution choice in the multiple equilibria region. Monte Carlo experiments show that the FIML estimator performs better than the GIVE estimators proposed in Pesaran and Pick (2007). Finally, an empirical illustration based on stock market returns is provided.

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    File URL: http://www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe0744.pdf
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    Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0744.

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    Length: 24
    Date of creation: Aug 2007
    Handle: RePEc:cam:camdae:0744
    Contact details of provider: Web page: http://www.econ.cam.ac.uk/index.htm

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