Stochastic Dominance, Estimation and Inference for Censored Distributions with Nuisance Parameter

Kim P. Huynh (), Luke Ignaczak () and Marcel Voia
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Kim P. Huynh: Department of Economics, Indiana University
Luke Ignaczak: Department of Economics, Carleton University

No 10-02, Carleton Economic Papers from Carleton University, Department of Economics

Abstract: This note investigates the behavior of stochastic dominance tests of censored distributions which are dependent on nuisance parameters. In particular, we consider finite mixture distributions that are subject to exogenous censoring. To deal with this potential problem, critical values of the proposed tests statistics are calculated using a parametric bootstrap. The tests are then applied to compare differences between distributions of incomplete employment spells with different levels of censoring obtained from Canadian General Social Survey data. The size of the proposed test statistics is computed using fitted GSS data.

Keywords: Stochastic Dominance Tests; Parametric Bootstrap; Censored Distributions; Finite Mixtures (search for similar items in EconPapers)
JEL-codes: C12 C14 C16 C41 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2010-01-21
New Economics Papers: this item is included in nep-ecm
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Published: Carleton Economic Papers

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