Audits and logistic regression, deciding what really matters in service processes: a case study of a government funding agency for research grants
AbstractGovernmental agencies, the back office of private firms and nongovernmental organizations experience bureaucratic processes that are often repetitive and out-of-date. These imperfections cause resource misuse and support activities that diminish to the value of the process. An important element of these bureaucratic processes is checking whether certain projects approved by the office have actually been successful in their proposed objectives. Banks and credit card companies must evaluate whether creditors have fulfilled their supposed financial worthiness, tax authorities need to classify sectors of the economy and types of tax payers for probable defaults, and research grants approved by government funding agencies should verify the use of public funds by grant recipients. In this study, logistic regression is used to estimate the probability of conformity of research grants to the financial obligations of the researcher analyzing the correlation between certain characteristics of the grant and the grant´s final status as approved or not. The logistic equation uncovers those characteristics that are most important in judging status, and supports the analysis of results as false positives and false negatives. A ROC curve is constructed which reveals not only an optimal cutoff separating conformity from nonconformity, but also discloses weak links in the chain of activities that could be easily corrected and consequently public resources preserved.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 41557.
Date of creation: Aug 2012
Date of revision:
Logistic regression; ROC curve; probability; audits; government; research grants;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- M42 - Business Administration and Business Economics; Marketing; Accounting - - Accounting - - - Auditing
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
This paper has been announced in the following NEP Reports:
- NEP-ACC-2012-10-06 (Accounting & Auditing)
- NEP-ALL-2012-10-06 (All new papers)
- NEP-PPM-2012-10-06 (Project, Program & Portfolio Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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