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Why We Should Not Be Silent About Noise

Published online by Cambridge University Press:  14 March 2025

John D. Hey
John D. Hey*
Affiliation:
Universities of York and Bari; Department of Economics, University of York, Heslington, York YO10 5DD, UK
*
email: jdh1@york.ac.uk
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Abstract

There is an odd contradiction about much of the empirical (experimental) literature: The data is analysed using statistical tools which presuppose that there is some noise or randomness in the data, but the source and possible nature of the noise are rarely explicitly discussed. This paper argues that the noise should be brought out into the open, and its nature and implications openly discussed. Whether the statistical analysis involves testing or estimation, the analysis inevitably is built upon some assumed stochastic structure to the noise. Different assumptions justify different analyses, which means that the appropriate type of analysis depends crucially on the stochastic nature of the noise. This paper explores such issues and argues that ignoring the noise can be dangerous.

Keywords

noisestochastic assumptionstestingestimationinferences

JEL classification

C91: Laboratory, Individual Behavior D81: Criteria for Decision-Making under Risk and Uncertainty B41: Economic Methodology C50: General

Information

Type
Research Article
Information
Experimental Economics , Volume 8 , Issue 4: Exploring the Error in Experimental Economics , December 2005 , pp. 325 - 345
Copyright
Copyright © 2005 Economic Science Association

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