Analysis of deterrents to corruption through testing of Beckerian prediction

Abstract

Objectives: To study individuals’ behaviour in terms of the effectiveness of various deterrents to corruption via analysis of expected payoffs at different levels of probability of detection and imposed fines. Introduction: There are two major variables involved in expected penalty paid by an individual – Probability of detection and Penalty if detected. For similarly expected payoffs, there can be two situations i.e. High chances of detection & low penalty and Low chances of detection & high penalty. The aim of the project is to determine the behaviour of an individual in the two different scenarios for a similarly expected payoff (penalty). We plan to create small vignettes and use Qualtrics survey to gauge real responses from individuals. The vignettes will represent the two scenarios as described above via real-life situations and the obtained data will be used to calculate and plot the expected payoffs at different levels. Scope: The analysis and the results can be used to explain the real-life situations like detection & reduction of traffic rules violation etc maintaining same expected penalty. The behavioural aspects in many more such situations can be attempted to explain using these results. Presentation as Case Report: The objective of the project is to build a case as part of final report. The case will talk about the entire process of working around behavioural analysis for different loss scenarios, how to prepare the survey, collect the data, analyse and implement the results. The case is built to facilitate the possibility of publishing this as a case in future. Going forward, we begin with the case as part of report. The end of the report is marked with the end of the case.