A Method to Estimate Mean Lying Rates and Their Full Distribution

Ellen Garbarino (), Robert Slonim and Marie Claire Villeval
Additional contact information
Ellen Garbarino: University of Sydney

No 11798, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Studying the likelihood that individuals cheat requires a valid statistical measure of dishonesty. We develop an easy empirical method to measure and compare lying behavior within and across studies to correct for sampling errors. This method estimates the full distribution of lying when agents privately observe the outcome of a random process (e.g., die roll) and can misreport what they observed. It provides a precise estimate of the mean and confidence interval (offering lower and upper bounds on the proportion of people lying) over the full distribution, allowing for a vast range of statistical inferences not generally available with existing methods.

Keywords: experimental economics; dishonesty; lying; econometric estimation; sampling errors (search for similar items in EconPapers)
JEL-codes: C81 C91 D03 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2018-09
New Economics Papers: this item is included in nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Published - revised version published in: Journal of the Economic Science Association, 2018, 4 (2), 136-150.

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Related works:
Journal Article: A method to estimate mean lying rates and their full distribution (2018)
Working Paper: A Method to Estimate Mean Lying Rates and Their Full Distribution (2018)
Working Paper: A Method to Estimate Mean Lying Rates and Their Full Distribution (2018)
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