Managerial Economics
MSFI 611
Group Assignment
Review of the article “Power outages, economic cost, and firm
performance: Evidence from Ethiopia”
Article Reviewed:
Lamessa T. A. (2018). Power outages, economic cost, and firm performance: Evidence from
Ethiopia. Utilities Policy, Vol. 53, pp. 111-120. https://doi.org/10.1016/j.jup.2018.06.009
The article in title “Power outages, economic cost, and firm performance: Evidence from
Ethiopia.” by the author Lamessa T. Abdisa was done with an aim of examining how firms in
Ethiopia respond to power outages. Considering firms in the industrial sector in Ethiopia, the
article tried to investigate how they responded to power interruptions and attempted to estimate
the resulting economic cost using two rounds of a firm-level survey.
The author begun with indicating the country’s unrealized potential in electricity generation but
then claimed that “there have been marginal improvements in recent years but the country is still
characterized by being one of the least electrified in the World and has low per capita electricity
consumption” (p.111). He went on to argue that due to poor supply and power outages, businesses
are facing constraints of doing business. He indicated that, “in 2015, electricity was the second
largest constraint to doing business in Ethiopia” (p. 111). The author further argued that “poor
supply of electricity can increase industrial firm's costs, steering their technological choices away
from energy-intensive technology and increasing the overall cost of production” (p. 111). Hence,
he deduced that firms used different strategies to cope with such challenges of which the common
one is ‘investment in self-generation’.
Based on Fisher-Vanden et al. (2015) empirical analysis of Chinese industrial firms using a
translog cost function, the author developed a conceptual framework, where the probability of
blackouts was introduced as a determining factor for production along with other variables. Using
Shephard's Lemma (which states the is one cost minimizing point for a given good with convex
cost function), the author used partial derivations to derive at the hypothesis (i) power outage
decreases the productivity of a firm (ii) to avoid the damage caused by power outage firms engage
in self-generation (iii) Outsourcing: when a firm is substituting materials for electricity, it is forced
to shift from making to buying (iv) firms may also respond to electricity outages by improving
their overall energy-consumption efficiency.
The article reviewed empirical works to see how other researchers have treated the effect of power
outages on firm performance. The review indicated that most studies used firm-level survey data
to study the economic cost of power outages. The author also looked at related literature that
utilized the production cost function approach to estimate the cost of power outages. This indicates
that the author’s use of survey data as well as the production cost function approach are well
justified.
The review of the literature also points out that power outages affect business activities in several
ways. Although the author indicated that the impact is different across firms, the argument weather
‘small firms are affected the most because they are unable to finance the cost of backup energy’
or ‘larger firms face greater outage loss because of the use of more machine-dependent production
processes than do small firms’ is still ongoing. The article also presented that the nature of the
power interruptions characterized by several dimensions, including duration, frequency, the timing
of interruption, and advance notification may have different cost impact. In line with this, the most
commonly-adopted strategy by firms to cope with power outages was presented as self-generation
(p.113).
The data set used by the article was obtained from WBES from surveys in 2011 and 2015 where a
sample size of 644 and 848 were used in respective years. The authors also used a stratified random
sampling in which the size of the firm, sector and region were used for stratification (p.113). It can
be noticed that the WBES data has provided apple data and the author’s method of stratification
appear to be logical.
Page 2 of 4
The author further used the Shephard’s Lemma to derive the cost share equation for each factor
of production dependent of power outages and as well as first-order derivative to determine the
marginal cost. The result of his analysis showed that power outage leads to substitution among the
factors of production. In the authors word “ …a power outage results in increased use of capital,
materials, and non-electric energy sources while the use of labor and electricity decreases” (p.115).
To put it comparatively, the findings indicated that for every one standard deviation increase in a
power outage leads to an increase in the cost share of capital, material and non-electric energy
sources of 0.022, 0.032, and 0.040 standard deviations, respectively. The same one standard
deviation increment in a power outage leads to a decrease in the cost share of labor and electricity
of 0.011 and 0.003 standard deviations, respectively (p.115). This finding showed that a power
outage negatively affects a firm's productivity which is which is consistent with the first hypothesis
of the article.
Similarly the increase in cost share of alternative energy sources while there is a decline in cost
share of electricity suggested the second hypothesis that proposed self-generation of electricity as
a coping strategy to mitigate the cost of a power outage is valid. A closer look in into the sectors
showed that food, wholesale and construction sectors respond significantly to power outages.
The analysis as presented in the article however was not able to justify the third and fourth
hypothesis. Although there was initial evidence of increment in the cost share of materials due to
increased outage intensity which suggests the outsourcing hypothesis, the estimated coefficient of
electricity and non-electric energy sources should have be negative. Hence the author was not able
to support the third hypothesis. For the fourth hypothesis, the result obtained also does not support
the improved energy-efficiency hypothesis, because there is no observed decline in the cost share
of non-electric energy in the result obtained (p.116).
Overall, the article arrived at the conclusion that marginal cost of a power outage was significant
and firms were found to self-generate electricity to cope with the power outages. Based on this,
the author concluded that there is a market for investing in the power systems.
The article touched a very timely and relevant topic in today’s the country’s industrial sector. In
addition, the author’s presentation of concepts and arguments looks well presented. However, his
conceptualization of the research question’ depends too much on the work of Fisher-Vanden et al.
Page 3 of 4
(2015). Although Klacek, et al. (2007)1 argues that the main advantage of translog production
function is that, unlike the case of Cobb-Douglas production function, it does not assume rigid
premises such as: perfect or “smooth” substitution between production factors or perfect
competition on the production factors. However, the writer simply assumes that ‘translog cost
function’ is appropriate and fails to present either a strong justification or alternative approach. In
a similar fashion, the author also claimed that ‘self-generation’ is the most common copying
strategy without looking in to change of working time of day, changing production process,
changing location of enterprise or taking insurance policy mentioned by other authors2.
Although the use of concepts like Shephard’s Lemma and the use of first-order derivative of the
cost function with respect to power outages to determine marginal cost (change in cost of
production) made sense, the depth of the author’s mathematical treatment was challenging to
comprehend. However, we were able to understand the interpretation of the outcome using the
sign (plus or minus) of the coefficients and their magnitude. Further, the assumption that the
production function followed ‘translog cost function’ was not clear.
1
Klacek J., Vosvrda M., Schlosser S. (2007), “KLE Production Function and Total Factor Productivity”,
in Statistika, No. 4.
2
Abeberese, A. B. Ackah, C., Asuming, P. (2017). Productivity Losses and Firm Responses to Electricity Shortages:
Evidence from Ghana. International Growth Center. E-33305-GHA-1. Available at:
https://www.theigc.org/wp-content/uploads/2018/06/Abeberese-et-al-2017-Working-paper.pdf
Page 4 of 4