Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance
| dc.contributor.advisor | Bhorat, Haroon | |
| dc.contributor.author | Unite, Emma | |
| dc.date.accessioned | 2020-02-25T10:48:17Z | |
| dc.date.available | 2020-02-25T10:48:17Z | |
| dc.date.issued | 2019 | |
| dc.date.updated | 2020-02-25T08:03:58Z | |
| dc.description.abstract | Corruption is a phenomenon in which many South Africans are well versed. While it continues to headline the news, the true extent of corruption is difficult to determine. Perception based indices have been proven to be inaccurate and experience-based data is also likely to incorrectly estimate the level of corruption. Forensic economics have come forward to fill this gap. These methods, however, are not always feasible as they rely on special datasets which are often difficult to come by. Using the National Income Dynamics Survey (NIDS) Waves 3, 4 and 5, this paper measures the difference in income underreporting between the public and private sectors. This difference is argued to represent the relative level of petty corruption in the public sector. Estimation results show an increasing trend in petty corruption over the period 2012-2017 with the public sector underreporting their income by, on average, 31.71%. Petty corruption is highest in law enforcement and the general government sectors. Evidence shows spatial variation in petty corruption with rural areas having the highest levels of underreporting. Petty corruption is also found to vary across the income distribution as levels of underreporting increase with income. | |
| dc.identifier.apacitation | Unite, E. (2019). <i>Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance</i>. (). ,Faculty of Commerce ,School of Economics. Retrieved from http://hdl.handle.net/11427/31307 | en_ZA |
| dc.identifier.chicagocitation | Unite, Emma. <i>"Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance."</i> ., ,Faculty of Commerce ,School of Economics, 2019. http://hdl.handle.net/11427/31307 | en_ZA |
| dc.identifier.citation | Unite, E. 2019. Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Unite, Emma AB - Corruption is a phenomenon in which many South Africans are well versed. While it continues to headline the news, the true extent of corruption is difficult to determine. Perception based indices have been proven to be inaccurate and experience-based data is also likely to incorrectly estimate the level of corruption. Forensic economics have come forward to fill this gap. These methods, however, are not always feasible as they rely on special datasets which are often difficult to come by. Using the National Income Dynamics Survey (NIDS) Waves 3, 4 and 5, this paper measures the difference in income underreporting between the public and private sectors. This difference is argued to represent the relative level of petty corruption in the public sector. Estimation results show an increasing trend in petty corruption over the period 2012-2017 with the public sector underreporting their income by, on average, 31.71%. Petty corruption is highest in law enforcement and the general government sectors. Evidence shows spatial variation in petty corruption with rural areas having the highest levels of underreporting. Petty corruption is also found to vary across the income distribution as levels of underreporting increase with income. DA - 2019 DB - OpenUCT DP - University of Cape Town KW - Economics LK - https://open.uct.ac.za PY - 2019 T1 - Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance TI - Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance UR - http://hdl.handle.net/11427/31307 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/31307 | |
| dc.identifier.vancouvercitation | Unite E. Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance. []. ,Faculty of Commerce ,School of Economics, 2019 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/31307 | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | School of Economics | |
| dc.publisher.faculty | Faculty of Commerce | |
| dc.subject | Economics | |
| dc.title | Predicting Petty Corruption in the Public Sector through Household Survey Non-Compliance | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MCom |