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A Simple Nonparametric Test for Independence

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Author Info
Bruce Mizrach () (Rutgers University)

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Abstract

A stationary stochastic process is defined to be locally independent if it eventually becomes independent of pastrealizations. I develop a simple nonparametric test for this condition. Size and power comparisons favor this statistic over the one proposed by Brock, Dechert and Scheinkman (1987) in samples under 250 observations.

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Publisher Info
Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 199523.

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Date of creation: 15 Jan 1995
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Handle: RePEc:rut:rutres:199523

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Related research
Keywords: nonlinear dependence; U-statistics;

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

Cited by:
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  1. Maurice Peat & Max Stevenson, 1994. "Asymmetry in the Business Cycle: Evidence from the Australian Labour Markets," Working Paper Series 37, School of Finance and Economics, University of Technology, Sydney. [Downloadable!]
  2. Fernandes, Marcelo, 2001. "Nonparametric Entropy-Based Tests of Independence Between Stochastic Processes," Economics Working Papers (Ensaios Economicos da EPGE) 413, Graduate School of Economics, Getulio Vargas Foundation (Brazil). [Downloadable!]
Statistics
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This page was last updated on 2009-10-18.

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