Relationship between corruption and capital flight in Kenya: 1998-2018

The study established the relationship between corruption and capital flight in Kenya over the period 1998 to 2018. Quarterly time series data for calculation of capital flight and for GDP growth rate and exchange rates were collected from the Central Bank of Kenya and Kenya National Bureau of Stati...

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Bibliographic Details
Main Authors: Mercy Mwangi, Amos Njuguna, George Achoki
Format: Article
Language:English
Published: Ümit Hacıoğlu 2019-08-01
Series:International Journal of Research In Business and Social Science
Subjects:
Online Access:https://www.ssbfnet.com/ojs/index.php/ijrbs/article/view/318
Description
Summary:The study established the relationship between corruption and capital flight in Kenya over the period 1998 to 2018. Quarterly time series data for calculation of capital flight and for GDP growth rate and exchange rates were collected from the Central Bank of Kenya and Kenya National Bureau of Statistics. Corruption perception index data was collected from the Transparency International website. Two Autoregressive Distributed-lagged models were fitted. Regression coefficients for corruption were -0.114 and 0.066 in the short run and -0.501 in the long run and the p values were 0.523 and 0.691 and 0.558 respectively, indicating no significant relationship. Regression results showed a coefficient of 0.01 and 0.003 for the Gross Domestic Product growth rate in the short run, and 0.049 in the long run. The p values were 0.670, 0.855 and 0.578 respectively denoting no significant relationship. Regression results showed a coefficient of 0.002 and 0.003 for the exchange rate in the short run, 0.43 for the exchange rate in the long run. The p values were 0.891 and 0.584 and 0.095 respectively indicating that a one % increase in the exchange rate would lead to a 0.043 % increase in capital flight in the long run. Regression results of lagged capital flight on capital flight showed a coefficient of 0.904. The p-value was 0.000 meaning that a one % increase in lagged capital flight would lead to a 0.904 % increase in capital flight. The study recommended that the government devises policies that would prevent further capital flight and generate capital flight reversal.
ISSN:2147-4478