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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 Business School
Marie Claire Villeval: Univ Lyon, CNRS, GATE (UMR5824)

Journal of the Economic Science Association, 2018, vol. 4, issue 2, 136-150

Abstract: 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 the existing methods.

Keywords: Dishonesty; Lying; Econometric estimation; Sampling errors; Experimental economics (search for similar items in EconPapers)
JEL-codes: C91 C81 D03 (search for similar items in EconPapers)
Date: 2018
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Working Paper: A Method to Estimate Mean Lying Rates and Their Full Distribution (2018) Downloads
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) Downloads
Working Paper: A Method to Estimate Mean Lying Rates and Their Full Distribution (2018) Downloads
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