| dc.description.abstract | The first of the big four pillars in the Third Medium Term Plan (MTP) (2018-2022) of
Vision 2030 was manufacturing. Its adoption would not only facilitate higher economic
growth and quicker job creation but also lower high cost of living by helping to reduce
the high quality of life of all citizens by contributing at least 15 per cent of Kenya GDP
p.a. However, there was little data on the contribution of different macroeconomic
aggregates to the growth of the manufactured exports in the country hence; a knowledge
gap to the policymakers in making serious decisions to enhance the growth of
manufactured exports in Kenya. This study, thus, sought to determine the effect of four
macroeconomic variables (capital expenditure (KXM), domestic debt (DMD),
population size (POP) and standard of living (DGC)) on Kenya’s manufactured exports
to Uganda and Tanzania. The specific objectives of this study were to: determine the
effect of capital expenditure on Kenya’s manufactured exports to Uganda and Tanzania,
to analyze the effect of domestic debt on Kenya’s manufactured exports to Uganda and
Tanzania, to establish the effect of population size on Kenya’s manufactured exports to
the Uganda and Tanzania and examine the moderating effect of standard of living on
the macroeconomic aggregates on the Kenya’s manufactured exports to Uganda and
Tanzania. This study further sought to conduct four separate hypothesis tests to
establish if there is a statistically significant effect of KXM, DMD, POP, and DGC on
Kenya’s manufactured exports to Uganda and Tanzania. The study focused on the
period 2008-2017 because 2007 was the period when the EAC was formed and,
therefore, most of the data was available from the three founding states, while 2018 was
the beginning of the MTP III, which prioritized manufacturing. This study was
anchored on Linder’s hypothesis of trade and employed the gravity model. It adopted a
correlational study design and relied on secondary panel data from the World Bank,
Central Bank of Kenya, Kenya National Bureau of Statistics and Kenya Export
Promotion and Branding Agency, which was analyzed using Stata software.
Descriptive statistics were computed to observe the general trend of sample variables.
According to the equation, both random and fixed effect models were estimated. The
Hausman test was then used to determine the best model to select the random effect
model. Results of the random effect model for Kenya’s exports to Uganda and Tanzania
indicated that the effect of KXM was positive and significant (β3 = 0.588, p-value
0.000< 0.05), DMD had a negative and significant effect (β4 = -0.207, p-value
0.002<0.05), POP had a positive and significant effect (β5=0.208, p-value 0.002<0.05)
and lastly, DGC had a negative and significant effect (β7 = -0.267, p-value 0.000<0.05).
The addition of a moderating variable, DGC, in the model increased the value of the
overall R2 from 0.783 to 0.798, meaning that the intervention of DGC causes
independent variables to jointly explain variation in the dependent variable by an
additional 0.015 units. This study therefore recommended that the Government of
Kenya and other stakeholders invest more in education, healthcare, and R&D,
incentivize novel sectors like the information and communication technology sector
and deter corruption in development projects. Additionally, the government of Kenya
should comply with the PFM Act public finance principle of solely using debt on
development projects and sourcing for cheaper yet long-term foreign debt instead of
domestic debt. | en_US |
