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dc.contributor.authorGewa, Nancy A
dc.date.accessioned2014-10-30T12:52:30Z
dc.date.available2014-10-30T12:52:30Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/11071/2305
dc.descriptionA dissertation Submitted in Partial Fulfillment of the Requirements for the degree of Masters in Business Administrationen_US
dc.description.abstractQuality and size of infrastructure provision in Kenya has been singled out as key impediment to economic growth. In fact Kenya’s greatest infrastructure challenge lies in the power sector where power supply remains unreliable, generation and transmission are stretched too thin and growing demand has led to frequent power interruptions. Despite these challenges, none of the economic growth studies in Kenya has provided any quantitative systematic evidence to assess the long term consequent implications of underinvestment in electric power infrastructure. This study presents a time series analysis framework that can be used at infrastructure strategic planning level to estimate the effects of different levels of electric power investments on economic growth. A study tailored to the Kenyan context which is a developing economy will enrich the academic debates on the effects of infrastructure investments on economic growth in developing economies. First, univariate time series analysis was undertaken to explain the properties of the data. Multivariate time series analysis was based on vector autoregressive models using both stationary and non stationary data series purely to examine the relationship between spending in electric power infrastructure and the associated economic growth effects. Findings based on cointegration testing suggest no long run relationship between electric power infrastructure investments and economic growth . However the short run rate of electric power expenditure based on variance decomposition results explains about 2% and 19% of variation in the rate of economic growth for stationary and non-stationary data series respectively. Granger causality does not run from rate of investments in electric power to the rate of economic growth or vice versa for stationary data series . However for non stationary data series, granger causality runs from rate of economic growth to rate of investments in electric power .Impulse response functions also show moderate linkages between electric power investment and economic growth. Further the rate of convergence in the economy by growth rate to shock changes in the rate of electric power infrastructure spending is gradual and tends to persisten_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectElectric poweren_US
dc.subjectEconomyen_US
dc.subjectKenyaen_US
dc.titleTime series analysis of the effects of electric power network expansions on economic growth in Kenyaen_US
dc.typeThesisen_US


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