6 CONCLUSION AND FURTHER RESEARCH
This paper examined the effect of electricity consumption, capital, labour, and education on industrial output
in Uganda. The study results found strong evidence
that electricity consumption, labour employed, and
industrial output are positively correlated. To examine
the study objectives, we incorporate several input variables into an augmented Cobb–Douglas production
function. The results indicate that education, electricity consumption, and labour have a long-term causality
on industrial output using the vector error correction
model (VECM). Specifically, we find evidence that
electricity is a necessary condition for an industrial
and economic survival. When we estimate the augmented Cobb–Douglas production function with all
variables (electricity consumption, educational, and
labour employed), there is evidence that well educated
workers are more productive. To investigate whether
labour employed differentials reflect increased output
differentials, we present a model which simultaneously
estimates the labour productivity function and production function for workers and the firms where they are
employed.
These results suggest that industries that consume
electricity have higher output than their counterparts,
likewise those that have well-educated workers with
productive labour employed produce more because
they contribute more to the firm’s output. The key positive results that emerged from the findings are the
important roles of electricity consumption, education,
and the nature of the labour employed in agro-based
industries. On average, the relative factor differentials,
i.e., electricity consumed, education, labour employed,
and industrial output differentials, between different
industries are equivalent.
These results suggest that current efforts to improve
the supply and affordability of the electricity are a
facilitating condition for industrial output. Moreover,
results suggest industrial-led electricity consumption
policies can enhance industrial growth. Likewise, the
results also suggest efforts to encourage agro-based
industries to employ more well-educated workers to
increase the industrial output. The need to understand how industrial electricity consumption can be
improved calls for further studies that can employ qualitative approaches to examine the cost of power and the
causes of power fluctuations in Uganda.
REFERENCES
Abokyi, E. A.-K.-A. 2018. Consumption of Electricity and
Industrial Growth in the Case of Ghana. Journal of
Energy.
Alley, I. E. 2016. Electricity supply, industrialization and
economic growth: evidence from Nigeria. International
Journal of Energy Sector Management, 10(4), 511–525.
Arranz-Piera, P. K. 2017. Electricity generation prospects
from clustered smallholder and irrigated rice farms in
Ghana. Energy, 121, 246–255.
Asumadu-Sarkodie, S. &. 2017. The causal effect of carbon dioxide emissions, electricity consumption, economic
growth, and industrialization in Sierra Leone. Energy
Sources, Part B: Economics, Planning, and Policy, 12(1),
32–39.
Asumadu-Sarkodie, S., & Owusu, P. A. 2017. Recent evidence of the relationship between carbon dioxide emissions, energy use, GDP, and population in Ghana: a linear
regression approach. Energy Sources, Part B: Economics,
Planning, and Policy, 12(6), 495-503.
Bartelsman, E., Dobbelaere, S., & Peters, B. 2015. Allocation
of human capital and innovation at the frontier: firm-level
evidence on Germany and the Netherland’s. Industrial and
Corporate Change, 24(5), 875–949.
Daubaraitë, U. &. 2015. Creative industries impact on
national economy in regard to sub-sectors. ProcediaSocial and Behavioral Sciences, 129–134.
Dogan, E. S. 2016. Exploring the relationship between
agricultural electricity consumption and output: New evidence from Turkish regional data. Energy Policy, 95,
370–37.
Ettah Bassey Essien, G. E.-A. 2017. Public Supply Of Electricity And Economic Growth In Nigeria. Nternational
Journal Of Social Sciences, 53.
Fermont, A. &. 2011. Estimating yield of food crops grown by
smallholder farmers. International Food Policy Research
Institute, Washington DC, 1–68.
Fox, J., & Smeets, V. 2011. Does input quality drive measured
differences in firm productivity? International Economic
Review, 52(4), 961–989.
Ghali, K. H. 1999. Financial Development and Economic
Growth:TheTunisian Experience. Review of Development
Economics., 3(3), 310–322.
Harlan, T. 2018. Rural utility to low-carbon industry: Small
hydropower and the industrialization of renewable energy
in China. Geoforum, 59–69.
Izadmehr, M. D. 2018. Determining influence of different
factors on production optimization by developing production scenarios. Journal of Petroleum Exploration and
Production Technology, 8(2), 505–520.
Jebli, M. B. 2017. The role of renewable energy and agriculture in reducing CO2 emissions: Evidence for North
Africa countries. Ecological Indicators, 74, 295–301.
Klein, R., Spady, R., & Weiss, A. 1991. Factors affecting the
output and quit propensities of production workers. The
Review of Economic Studies, 58(5), 929–953.
Kumar, R. D. (2016).Agro-processing industries in Haryana:
Status, problems and prospects. Economic Affairs, 61(4),
707.
Li, G., Fang, C., Wang, S., & Sun, S. 2016. The effect
of economic growth, urbanization, and industrialization on fine particulate matter (PM2. 5) concentrations
in China. Environmental science & technology, 50(21),
11452–11459.
Liedholm, C. E. 2013. Small enterprises and economic development: the dynamics of micro and small enterprises.
Routledge.
Lin, B. &. 2016. Why is electricity consumption inconsistent
with economic growth in China? Energy Policy, 88, 310–
316.
Lucas, R., 1988, On the mechanics of economic development,
Journal of Monetary Economics 22, 3–42.
Mawejje, J. &. 2016. Electricity consumption and sectoral
output in Uganda: an empirical investigation. Journal of
Economic Structures, 5(1), 21.
Mitana, J. M. V., Muwagga, A. M., Giacomazzi, M., Saint
Kizito, O., & Ariapa, M. 2019. Assessing educational outcomes in the 21st century in Uganda: a focus on soft skills.
Journal of Emerging Trends in Educational Research and
Policy Studies, 10(1), 62–70.
92
This paper examined the effect of electricity consumption, capital, labour, and education on industrial output
in Uganda. The study results found strong evidence
that electricity consumption, labour employed, and
industrial output are positively correlated. To examine
the study objectives, we incorporate several input variables into an augmented Cobb–Douglas production
function. The results indicate that education, electricity consumption, and labour have a long-term causality
on industrial output using the vector error correction
model (VECM). Specifically, we find evidence that
electricity is a necessary condition for an industrial
and economic survival. When we estimate the augmented Cobb–Douglas production function with all
variables (electricity consumption, educational, and
labour employed), there is evidence that well educated
workers are more productive. To investigate whether
labour employed differentials reflect increased output
differentials, we present a model which simultaneously
estimates the labour productivity function and production function for workers and the firms where they are
employed.
These results suggest that industries that consume
electricity have higher output than their counterparts,
likewise those that have well-educated workers with
productive labour employed produce more because
they contribute more to the firm’s output. The key positive results that emerged from the findings are the
important roles of electricity consumption, education,
and the nature of the labour employed in agro-based
industries. On average, the relative factor differentials,
i.e., electricity consumed, education, labour employed,
and industrial output differentials, between different
industries are equivalent.
These results suggest that current efforts to improve
the supply and affordability of the electricity are a
facilitating condition for industrial output. Moreover,
results suggest industrial-led electricity consumption
policies can enhance industrial growth. Likewise, the
results also suggest efforts to encourage agro-based
industries to employ more well-educated workers to
increase the industrial output. The need to understand how industrial electricity consumption can be
improved calls for further studies that can employ qualitative approaches to examine the cost of power and the
causes of power fluctuations in Uganda.
REFERENCES
Abokyi, E. A.-K.-A. 2018. Consumption of Electricity and
Industrial Growth in the Case of Ghana. Journal of
Energy.
Alley, I. E. 2016. Electricity supply, industrialization and
economic growth: evidence from Nigeria. International
Journal of Energy Sector Management, 10(4), 511–525.
Arranz-Piera, P. K. 2017. Electricity generation prospects
from clustered smallholder and irrigated rice farms in
Ghana. Energy, 121, 246–255.
Asumadu-Sarkodie, S. &. 2017. The causal effect of carbon dioxide emissions, electricity consumption, economic
growth, and industrialization in Sierra Leone. Energy
Sources, Part B: Economics, Planning, and Policy, 12(1),
32–39.
Asumadu-Sarkodie, S., & Owusu, P. A. 2017. Recent evidence of the relationship between carbon dioxide emissions, energy use, GDP, and population in Ghana: a linear
regression approach. Energy Sources, Part B: Economics,
Planning, and Policy, 12(6), 495-503.
Bartelsman, E., Dobbelaere, S., & Peters, B. 2015. Allocation
of human capital and innovation at the frontier: firm-level
evidence on Germany and the Netherland’s. Industrial and
Corporate Change, 24(5), 875–949.
Daubaraitë, U. &. 2015. Creative industries impact on
national economy in regard to sub-sectors. ProcediaSocial and Behavioral Sciences, 129–134.
Dogan, E. S. 2016. Exploring the relationship between
agricultural electricity consumption and output: New evidence from Turkish regional data. Energy Policy, 95,
370–37.
Ettah Bassey Essien, G. E.-A. 2017. Public Supply Of Electricity And Economic Growth In Nigeria. Nternational
Journal Of Social Sciences, 53.
Fermont, A. &. 2011. Estimating yield of food crops grown by
smallholder farmers. International Food Policy Research
Institute, Washington DC, 1–68.
Fox, J., & Smeets, V. 2011. Does input quality drive measured
differences in firm productivity? International Economic
Review, 52(4), 961–989.
Ghali, K. H. 1999. Financial Development and Economic
Growth:TheTunisian Experience. Review of Development
Economics., 3(3), 310–322.
Harlan, T. 2018. Rural utility to low-carbon industry: Small
hydropower and the industrialization of renewable energy
in China. Geoforum, 59–69.
Izadmehr, M. D. 2018. Determining influence of different
factors on production optimization by developing production scenarios. Journal of Petroleum Exploration and
Production Technology, 8(2), 505–520.
Jebli, M. B. 2017. The role of renewable energy and agriculture in reducing CO2 emissions: Evidence for North
Africa countries. Ecological Indicators, 74, 295–301.
Klein, R., Spady, R., & Weiss, A. 1991. Factors affecting the
output and quit propensities of production workers. The
Review of Economic Studies, 58(5), 929–953.
Kumar, R. D. (2016).Agro-processing industries in Haryana:
Status, problems and prospects. Economic Affairs, 61(4),
707.
Li, G., Fang, C., Wang, S., & Sun, S. 2016. The effect
of economic growth, urbanization, and industrialization on fine particulate matter (PM2. 5) concentrations
in China. Environmental science & technology, 50(21),
11452–11459.
Liedholm, C. E. 2013. Small enterprises and economic development: the dynamics of micro and small enterprises.
Routledge.
Lin, B. &. 2016. Why is electricity consumption inconsistent
with economic growth in China? Energy Policy, 88, 310–
316.
Lucas, R., 1988, On the mechanics of economic development,
Journal of Monetary Economics 22, 3–42.
Mawejje, J. &. 2016. Electricity consumption and sectoral
output in Uganda: an empirical investigation. Journal of
Economic Structures, 5(1), 21.
Mitana, J. M. V., Muwagga, A. M., Giacomazzi, M., Saint
Kizito, O., & Ariapa, M. 2019. Assessing educational outcomes in the 21st century in Uganda: a focus on soft skills.
Journal of Emerging Trends in Educational Research and
Policy Studies, 10(1), 62–70.
92