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Choosing between Two Income Distribution Models with Contaminated Data

PublisherLondon School of Economics
Collection
  • DARP discussion papers; 18
Publication date1996
Abstract

Choosing between two income distribution models typically involves testing two non-tested hypotheses, that is hypotheses such that one cannot be obtained as a special or limiting case of the other. Cox (1961, 1962) proposed a classical testing procedure based on the comparison of the maximised likelihood functions for the two models. In this paper it is shown that such a procedure is not robust in that a single observation can reverse the decision. Its robustness properties as well as other properties are shown in simulated examples

Keywords
  • M-estimators
  • Model choice
  • Robust tests
  • Income distribution
  • Linear regression
Citation (ISO format)
VICTORIA-FESER, Maria-Pia. Choosing between Two Income Distribution Models with Contaminated Data. 1996
Identifiers
  • PID : unige:23112
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