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dc.contributor.advisorShadrack M. Mwilariaen_US
dc.contributor.authorMungai, Peter Muchugu
dc.date.accessioned2024-02-05T09:42:21Z
dc.date.available2024-02-05T09:42:21Z
dc.date.issued2023-11
dc.identifier.urihttps://ir-library.ku.ac.ke/handle/123456789/27506
dc.descriptionA Project Submitted to the School of Economics, Business & Tourism in Partial Fulfilment of the Requirements for A Master's Degree in Economics (Policy And Management) of Kenyatta University, November 2023.en_US
dc.description.abstractEconomies across the globe have witnessed wide variations in incomes, inviting researchers and policy makers to explore various interventions to bridge the gap. Among the interventions floated is focusing more on productivity levels than the accumulation of inputs. Total Factor Productivity, defined as a measure of output growth not explained by factor inputs, has been fronted as the solution to the widespread variations. Kenya targets achieving an annual Total Factor Productivity growth rate of 2.5 from the current 0.352 to achieve vision 2030 and Sustainable Development Goals. One way to increase Total Factor Productivity is by creating an enabling and conducive environment where factor inputs operate. Institutions, specifically the Rule of Law, play a vital role in ensuring a thriving environment is created. This project, therefore, sought to establish how the Rule of Law affects Total Factor Productivity in Kenya from 1996 to 2021. The period of study was chosen based on the availability of data. A time series data set from secondary sources was used. The research objectives of this project were; (i) to determine the trend of Total Factor Productivity in Kenya and (ii) to determine both the short-run and the long-run effects of the Rule of Law on Total Factor Productivity in Kenya. The standard growth accounting approach was used to determine the trend of TFP. The significant departure from the existing computed Total Factor Productivity estimates was the inclusion of labor quality improvements due to educational attainment. The second objective was achieved using an Auto Regressive Distributed Lag Model with an error correction term. The model was adopted due to the presence of co-integration relationships as established by the ARDL bound test. The ARDL bound test for co-integration was employed since variables were found to be of mixed series. Total Factor Productivity computations were done using Excel, while regression analysis used Stata. The study found incorporating labor quality improvements when computing Total Factor Productivity growth estimates yielded a 0.1041 average growth. In comparison, exclusion yielded a -0.9209 average growth, therefore, indicating the essence of factoring in improvements in human capital in TFP estimations. Secondly, the study found a positive long-run relationship and a negative short-run relationship between the Rule of Law and Total Factor Productivity in Kenya. Consequently, the study recommended that future computations of TFP estimates should include improvements in labor quality due to education attainment. Secondly, the study recommended that the government should support institutions that promote the entrenchment and adherence of rule of law.en_US
dc.description.sponsorshipKenyatta Universityen_US
dc.language.isoenen_US
dc.publisherKenyatta Universityen_US
dc.subjectRule of Lawen_US
dc.subjectTotal Factor Productivityen_US
dc.subjectKenyaen_US
dc.titleThe Effect of Rule of Law on Total Factor Productivity in Kenyaen_US
dc.typeThesisen_US


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