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Testing multivariate economic restrictions using quantiles: the example of Slutsky negative semidefiniteness

Listed author(s):
  • Holger Dette

    (Institute for Fiscal Studies)

  • Stefan Hoderlein

    ()

    (Institute for Fiscal Studies and Boston College)

  • Natalie Neumeyer

    (Institute for Fiscal Studies)

This paper is concerned with testing rationality restrictions using quantile regression methods. Specifically, we consider negative semidefiniteness of the Slutsky matrix, arguably the core restriction implied by utility maximization. We consider a heterogeneous population characterized by a system of nonseparable structural equations with infinite dimensional unobservable. To analyze the economic restriction, we employ quantile regression methods because they allow us to utilize the entire distribution of the data. Difficulties arise because the restriction involves several equations, while the quantile is a univariate concept. We establish that we may test the economic restriction by considering quantiles of linear combinations of the dependent variable. For this hypothesis we develop a new empirical process based test that applies kernel quantile estimators, and derive its large sample behavior. We investigate the performance of the test in a simulation study. Finally, we apply all concepts to Canadian individual data, and show that rationality is an acceptable description of actual individual behavior.

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File URL: http://cemmap.ifs.org.uk/wps/cwp1411.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP14/11.

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Date of creation: 01 May 2011
Handle: RePEc:ifs:cemmap:14/11
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