Energy crisis and productive inefficiency: micro-evidence from textile sector of Faisalabad.
Ali, Haider ; Nawaz, Muhammad
This study measures productive inefficiency in the textile sector
of Faisalabad due to recent energy crisis in Pakistan. Primary data is
collected randomly from 125 firms of the industry. Results explain that
these firms are facing huge production loss which varies from 23 to 65
percent in 8-hour shift and 21 to 60 percent in 10-hour shift. Spinning
and textile firms are facing severe electricity outage while dyeing,
chemical and processing firms have huge production losses due to gas
shortage. The study further explains that 64 percent of the firms are
willing to pay for uninterrupted energy supply and their willingness to
pay varies on average in the range of PAK Rs 5 to 9 per unit of
electricity.
JEL Classification: D22, Q4, R34
Keywords: Energy Crisis, Production Loss, Order Delays, Willingness
to Pay
1. INTRODUCTION
Energy, being an essential component of every production process,
plays a pivotal role in the growth process of a country. The production
process has undergone a massive transition from labour intensive to
energy intensive techniques [Stem and Cleveland (2004)]. Now, it is
widely recognised that industrialisation is an energy-intensive process;
hence, uninterrupted supply of energy is necessary to keep the
production process in ran. In addition, high per-capita energy
consumption is considered as an indicator of the level of economic
development. This positive correlation between energy consumption and
output growth (and development) led many countries, particularly
developing ones, to design policies for subsidised energy provision with
focus on supply-side in late eighties. At the same time, some European
countries (i.e. Germany, Denmark, Belgium, Sweden) formulated energy
policy focusing on demand-side (energy conservation), and achieved
smaller growth rates in energy consumption without any reduction in
economic growth [Pintz (1986)].
After recent episodes of oil price increase (started from 2006-07),
tight financial position and huge trade deficits forced many developing
countries (Pakistan, in particular) to pull out, at least moderately,
from the policy of subsidised energy supply [Alahdad (2012) and Malik
(2012)]. The energy demand in Pakistan has also been increasing steadily
in every sector of the economy and future energy need of Pakistan is
forecasted to be, at least, three times that of today within next two
decades. (1) The focus of energy policy in Pakistan has been the demand
side as it is believed that energy crisis in Pakistan is a management
and not a capacity issue. (2) Besides, demand-side policies are being
adapted to save not only capital but also foreign exchange of the
country.
These demand side energy policies e.g. energy conservation,
energy-prices mechanism etc. have proved to be a serious constraint in
the industrial growth of Pakistan [Siddiqui (2004); Aqeel and Butt
(2011) and Malik (2012)]. Importantly annual production loss due to
power shortages is about two percent of gross domestic product [Abbasi
(2011)]. Various studies [i.e., Bose, et al. (2005) and Wijayatunja and
Jayalath (2008)] have tried to estimate the output loss due to power
outages. In case of Pakistan, a few attempts have been made to quantify
the cost of unserved energy [Lahore Chamber of Commerce and Industry
(1986); Pasha, et al. (1989) and Siddiqui, et al. (2011)]. Siddiqui, et
al. (2011) also quantified the industrial production loss due to shift
hours whereas the other studies focused on power outages only.
Textile being the largest industrial sector of Pakistan generates
the country's highest export earnings of about 58 percent;
providing the bulk of employment (39 percent) to largely unskilled as
well as underutilised workforce, and contributes 8.5 percent to GDP. (3)
Textile production is comprised of cotton ginning, yam, fabric, home
textiles, towels, hosiery and knitwear, readymade garments and canvas.
These components are being produced both in the large and small scale
organised sector as well as in unorganised cottage/small and medium
units.
Textile industry is presently comprised of 521 textile units with
installed capacity of 10.0 million spindles and 114000 rotors making
Pakistan to have third largest spinning capacity in Asia with spinning
capacity in Pakistan being 5 percent of the total world capacity and 7.6
percent of the capacity in Asia. (4) Despite this vigorous and export
oriented textile industry, dismal performance of textile exports
(decreased from 65 percent of total exports in 2007 to 53 percent in
2012) (5) can be mainly attributed to the stifling power shortages. This
crisis has left investors fighting for their survival and, in some
cases, they are shutting down production units in Pakistan and/or moving
abroad (especially in Bangladesh). In other cases, some export-specific
production units are, now, unable to meet international orders and have
converted into local production units with capturing local market in
order to fulfil its average fixed cost. Besides, the power crisis caused
prolonged delays in delivery schedule both at intra and inter industry
level resulting in less competitiveness of the industry along with tough
competition from regional competitors i.e., China, India, Bangladesh
etc. These problems in textile industry are structural in nature and
cannot be resolved through financial support of the government [Alam
(2011)].
Textile production is not only energy but also time consuming
process where a conversion of cotton into single type of good e.g.
shirt, vest, or socks takes about two months with the involvement of
many supporting sub-sectors. It is important to note that every sector
of textile industry is not equally energy-intensive and has different
level of energy consumption and dependency but delay in accomplishing
output orders in any sub-sector involuntarily causes further delays in
making the finished product. These delays cause extraordinary production
losses (as both domestic and foreign customers turn back) and badly
affect capability of the textile industry. Furthermore, energy gap also
varies among different sectors of the industry due to disparate scale of
production and input mix. Large scale production sectors are using
alternative sources of energy like generators; thus, reducing their
energy gap and production loss at increased cost of final products.
Therefore, high energy intensive industries may not have higher energy
gap relative to less energy intensive industries that are unable to
purchase costly energy inputs due to capital constraints or bad market
conditions (as less orders reduce economies of scale).
These sector-level differences of energy gap and resulting
production loss have not been analysed earlier in case of any industry
in Pakistan. A recent study by Siddiqui, et al. (2011) calculated total
industrial output loss by taking into account all major industries
including textile and reported that output loss falls in the range of 12
percent to 37 percent due to power outages. This study does not take
into account the production delays by sub-sectors of textile industry at
all. This restrictive assumption of homogeneity of sub-sectors (at
least, with regard to energy consumption) may result in a bias towards
under-estimation of the impact of energy shortage on production cost for
the reason discussed above. Further, the study is based on a survey
conducted in the second quarter of 2008 while taking 2007 as the
reference year. It cannot, therefore, account for impact of recent
developments regarding energy crisis in the textile industry i.e.,
severity of power outages, capital flight, increased use of alternative
energy resources etc. Against this backdrop, the present study would
significantly contribute to our understanding about the impact of energy
crisis on textile sector.
Based on primary data from various sectors and sub-sectors of
textile industry, this study reveals which sub-sectors of textile
industry are more energy deficient relative to other ones. This work
also attempts to calculate the magnitude of production losses due to
different size of lags in accomplishing production orders. Most
importantly, it is the first attempt to estimate producers'
willingness to pay for uninterrupted energy supply. Therefore, the
contribution of this study is twofold in the sense that it not only
estimates production loss of textile sector due to unavailability of
energy but also it reports producers' willingness to pay for
uninterrupted energy supply at various sub-sectors level.
The remainder of the study is organised as follows. Section 2
details the data, variables and methodology. Section 3 contains a brief
discussion on the results while final section concludes the study.
2. DATA, VARAIBLES, AND METHODOLGY
The study primarily utilises the primary data from the textile
industry of district Faisalabad, Pakistan. According to the Faisalabad
Chamber of Commerce and Industry [FCCI (2013-14)], there are almost 1090
registered units of different sub-sectors of textile industry. According
to Economic Survey of Pakistan (2012-13), this industry is categorised
into ginning (GIN), spinning (SPN), weaving (WEA), fabric and knitting
(FAB) and cotton cloth sectors whereas cotton-cloth sector is further
subdivided into sizing (SIZ); dyeing, chemical and processing (DCP);
textile (TEX); hosiery (HOS); readymade garments (RMG) and printing and
embroidery (PEM). This study covers 125 firms (sub-sectors of textile
industry) randomly selected according to their percentage share in the
market as shown in Figure 1. Fiscal year 2008 is taken as the reference
year because at that time energy crisis was in initial stages.
In Pakistan, energy crisis has badly affected the production
process of major local and export oriented textile sectors of Pakistan.
In order to identity the production loss (PL) and its magnitude due to
energy crisis in every sector of the industry, Siddiqui, et al.
(2011) is followed. Firstly, the production and energy loss is
computed as a whole and sub-sector-wise. The production loss is product
of output per labour-hour (OPLHz) and total loss of labour hours (TLLHz)
in each sub-sector.
[PL.sub.i] = [(OPLHz).sub.i] x [(TLLHz).sub.i] ... ... ... ... ...
... (1)
where i explains number of firms. Output per labour-hour (OPLHz)
depends on annual output and annual working hours whereas the later is
product of shift-hours of firm, number of shifts, number of workers and
annual work-days. Total loss of labour-hour (TLLHz) requires the average
labour hour loss, number of workers and work-days. For computation of
energy loss and compensated energy-loss, energy loss per-day without
alternative source (ELWAS) is calculated as follows.
EL WAS = ERH x LSH ... ... ... ... ... ... (2)
where ERH and LSH are energy requirements per-hour and
load-shedding hours per-day, respectively. The major contribution of
this study is that it takes both electricity and gas as sources of
energy inputs measured in their respective units. Energy required
per-hour is obtained by dividing the energy unit consumed per-month
(EUCM) and working hour per-month (WHM).
ERH = EUCM/WHM ... ... ... ... ... ... (3)
Working hour per-month is attained by multiplying working hour
per-day and total work days of a firm. After computing the energy loss
per-month, the compensated energy loss is calculated which is the
difference between energy loss per-day without the use of
alternative-source (ELWAS) and energy loss per-day after using the
alternative source (ELAAS) such as stand-by generators.
CELM = EL WAS- ELAAS ... ... ... ... ... (4)
The energy loss per-month in the presence of alternative source
makes Equation (2) as:
ELAAS = ERHx(LSH-UASH) ... ... ... ... ... (5)
Here UASH is the usages of alternative source per-hour and the
computation of ERH requires a change in Equation (3) in the light of
Equation (5). The whole process gives the production loss, energy loss
and compensated energy loss for both the whole and subsector wise.
Production order delays are the delays which firms are facing due to the
interruption in energy provision. Total number of order delays in
particular year and number of order delay days per-order are used for
the analysis.
2.1. Producer's Willingness to Pay for Uninterrupted Energy
Supply
On-going energy crisis has reduced the production level and the
producers of textile sector are compelled to use alternative energy
source such as heavy stand-by generators and self-production of energy.
These producers are paying large amount for uninterrupted energy to
fulfil their production orders. So, this sub-section relates with the
producer willingness to pay for uninterrupted energy supply (alternative
energy source).
In order to analyse the producer willingness to pay for alternative
energy sources (input), the work(s) of McConnell and Bockstael (2005),
modified by Zapata and Carpio
(2012) are followed. The theoretical stance of producer willingness
to pay requires both consumer and producer side. On consumer and
producer side, utility maximisation framework subject to budget
constraint and both profit maximisation as well as cost minimisation
framework subject to production constraint are required. After having
the indirect utility function, indirect profit function and cost
function from the optimisation framework, the compensated and equivalent
variation need to be mentioned. Non-labour income [bar.h] is assumed to
be function of profit that can be obtained from the linkages between the
consumer and producer, [bar.h] = [bar.h] (pi][[p.sub.y],r,q}k), and
written as:
Z[[bar.h]([pi]([p.sub.y],r,q),k},L,[P.sub.z] = [Z.sub.0] ... ...
... ... ... (6)
where, L, P, and r are non-labour income, prices of goods used by
consumer and input prices, respectively. In compensated variation (CV)
and equivalent variation (EV) concept, change in the vector of input
quantity "q" from "[q.sub.0]" to
"[q.sub.1]" make the amount of money to hold the condition
described below:
Z [[bar.h][[pi]([p.sub.y],r,[q.sub.0]),k)L,[P.sub.z]] =
Z[[bar.h][[pi]([p.sub.y],r,[r.sub.1]),k}-CV,L, [P.sub.z] ... (7)
Z [[bar.h][[pi]([p.sub.y],r,[q.sub.0]),k)+ EV, L,[P.sub.z]] =
Z[[bar.h][[pi]([p.sub.y],r,[q.sub.1]),k),L, [P.sub.z] ... (8)
Equations (7) and (8) represent the economic values that producer
is willing to pay for better input quantity level. It is obvious that
positive CV and EV measures lead to the better welfare and negative CV
and EV generate the welfare loss. CV and EV can also be explained by the
producer willingness to pay (WTP) function d, defined as:
d = [bar.h]([pi]([p.sub.y],r,[q.sub.1]),k) -
[bar.h]([pi]([p.sub.y],r,[q.sub.0]),k) ... ... ... ...(9)
CV and EV functions are described above which depend on the initial
and final levels of non-labour income [McConnell (1990)]. The best
availability of any input quantity/level, "[q.sub.1]" may
increase the profit as d > 0. In addition, it also represents the
maximum amount of profit that producer is willing to accept (forgo) to
give up (obtain) the benefits of new input quantity level,
"[q.sub.1]"
It has been assumed that non-labour income is a linear function of
firm profit and other factors defined by "k". It can also be
assumed that change in input quantity "q", from
"[q.sub.0]" to "[q.sub.1]" is also the linear
function of the difference in profits, written as:
d = [pi]([p.sub.y],r, [q.sub.1]) - [pi]([p.sub.y], r, [q.sub.0])
... ... ... ... ...(10)
The above equation yields that the maximum amount of money a
producer is willing to pay for the improvements of input quantity level
which may reduce the difference between ex-post (after new input) and
ex-ante (before new input) firm's profit levels.
In our analysis, the old input level is described by the current
energy provision to all industrial sectors of Pakistan. Water and Power
Development Authority (WAPDA) and Sui Northern Gas Pipeline Limited
(SNGPL) have been the supplier of electricity and gas provision to all
textile industries of Faisalabad, respectively. The ongoing energy
crisis has badly affected their production level and they have to rely
on alternative energy source such as heavy standby generators, working
on oil, solar energy plants and other such expensive opportunities to
run their industries. So, "[q.sub.0] " is energy provision in
form of electricity and gas and "[q.sub.1]" are alternative
expensive energy sources.
It is also apparent that alternative energy sources are more
expensive as compared to traditional energy sources. That is why,
industrialists pay higher amount for that which reduces their profit as
well (if price remains same). So, "r" is energy price that is
categorised in two components "[r.sub.0]" and
"[r.sub.1]" where former is the price of traditional energy
provision and latter is the price of alternative energy sources.
The analysis requires the specific form of production function for
both cost minimisation and profit maximisation. From these forms, we can
drive all the equations written above and extend the analysis for
comparative statics of WTP variation function. It is also helpful for
the sign and implication of input price effect, output price effect and
input quality effect. The expected sign are as:
[partial derivative]d/[partial derivative][r.sub.0] < 0,
[partial derivative]d/[partial derivative][r.sub.1] < 0 ... ...
... ... ... ... ... (11)
For better input quantity level or alternative energy source, the
willingness to pay for producer would be higher and the variation
function for own and cross price is negative. (6)
3. RESULTS AND DISCUSSION
This section presents the results of production loss and number and
duration of production order delays due to energy crisis in different
sub-sectors of textile industry. In addition, willingness to pay (WTP)
responses for uninterrupted energy supply across the sub-sectors will be
discussed.
3.1. Production Analysis
Energy crisis forced all sectors of the industry to produce less
than their potential levels. However, due to different scale of
production and level of dependency on energy inputs, the gap between
actual and potential production level varies across the sectors. Figure
2 depicts theses production capacity gaps.
[FIGURE 2 OMITTED]
Spinning, weaving and fabric sectors have the highest use of
alternative resources (mainly electric generators) and are producing 50
percent, 68 percent and 50 percent of their potential level,
respectively. The maximum gap of potential and current output is
apparent for textile, dyeing, chemical and processing and printing and
embroidery firms. Lower production capacity in dyeing, chemical and
processing (DCP) sector is exerting negative effects on production in
textile (TEX), hosiery and readymade garments (HOS and RMG) and printing
and embroidery (PEM) as the latter sectors depend upon DCP. These
sectors are using gas-intensive alternative resources; hence, it can be
deduced that production loss is worse in gas dependant industries than
in electricity dependant. Load-shedding of gas has aggravated the cost
of these firms where many units have purchased boilers to keep their
production process in run. Rice-waste, corn-waste and coal are being
used as an input in these boilers whereas using coal as an input is
subject to both quantity and quality constraints. Pakistani coal is not
of good quality and there are trade restrictions on import of coal from
the neighbouring countries particularly India.
Spinning and weaving and sizing have no production loss from gas
shortage but the later one depends more on electricity as compared to
former ones. The unserved energy-loss is higher in electricity-intensive
industries than gas-intensive industries. Overall, textile, dyeing and
hosiery and readymade garments firms are more energy dependant as
compared to others and facing severe production crises in their
industries. The current situation has also adversely affected the labour
market where textile, hosiery and readymade garments and dyeing sectors
are the major affectees. The situation is less severe in those sectors
where a working shift consists of ten hours rather than eight hours.
It can be seen from Table 1 that labour-hour loss is the highest in
the textile sector followed by hosiery and garments sectors that depend
upon the former. In weaving sector, there is less labour-hour loss
because large scale of production and high demand of good have allowed
producers to use alternative resources at the time of electricity
load-shedding. Printing and embroidery sector is also using alternative
sources to continue working at time of load-shedding. Production loss is
highest in textile sector followed by dyeing, chemical and processing
sector under both shifting hours. Zero production loss under gas as an
input in weaving and spinning sectors is because these sectors primarily
depend upon electricity and use electricity generators in load shedding
hours. It is important to note that production loss reduces as working
hours of a shift increase from eight to ten. It basically indicates that
increased labour-hours are not proportionate to energy loss and firms
may increase their output level by increasing their working hours.
The production loss for both 8-hour and 10-hour shifts in textile
industry is shown below in Figure 3. It ranges between of 23 to 65
percent for 8 hour shift while 21 to 60 percent for 10-hour shift. This
production loss is greater than the loss (25.6 percent) calculated by
Lahore Chamber of Commerce and Industry (LCCI) for Punjab during 1984-85
crises and, also, above the range of 12 to 37 percent estimated by
Siddiqui, et al. (2011) in 2008 when the energy crisis was in initial
stages.
[FIGURE 3 OMITTED]
The 65 percent production loss of textile industry clearly
indicates that up to 10hour per day electricity load-shedding and 4 days
a week gas load-shedding has thrown textile sector into troubles
resulting in huge output losses, loss of competitiveness in
international market (next section will demonstrate this phenomenon) and
capital outflow of major textile industries to neighbouring countries.
3.1.1. Production Orders and Delays
Energy crisis had adversely affected production orders, both local
and foreign, by increasing cost of production and by causing delay in
completion of production orders. As explained earlier, these delays in
completion of orders depend on the size of the firm and production
delays in other sectors of the industry on which a sector depends for
intermediate product. Table 2 presents a brief picture of this scenario
in the textile industry of Faisalabad.
In 2008, textile firms have the highest local and export orders as
percentage of the total orders per-year while spinning sector has the
least local orders in 2008 which is just 4.3 percent of total orders
obtained by the whole textile sector. In 2013, international orders in
all sectors have decreased as compared to reference period; expect
fabric which showed growth in export orders from 6.8 to 17 percent. It
is obvious that textile and hosiery and garments sectors have been
unable to fulfil the international requirements and faced reduction in
their export demands as compared to 2008. Further, embroidery and
weaving and sizing firms have no export orders in both 2008 and 2013.
The emerging results show that energy crisis has reduced the production
orders in both international and national market which resulted in loss
of production.
It can be seen from Table 2 that energy crisis has slowed down the
production process in the textile industry where both local and foreign
production orders have reduced in almost all sectors of the industry.
Textile sector is an exception where local orders have increased in 2013
as compared to 2008. This result can be explained by looking at the
export orders of this sector which has experienced a sharp decline in
export orders. Unable to meet the international orders on time, the
textile sector has changed its preferences from foreign market to local
market so that it may fulfil its fixed cost and keep its existence in
the market. It can be termed as a positive externality of recent energy
crisis where local market is now enjoying more variety of textile
products after energy crisis than it has before this crisis.
Increase in export orders of fabric (FAB) and hosiery and readymade
garments (RAM) sectors are due to conversion of production plants on
alternative resources and increased demand in international market of
these Pakistani products. Increase in production order-delays shows that
the problem of interrupted energy supply has not been addressed in
correspondence with the magnitude of the crisis and the situation is
getting worse.
For even a deeper analysis how energy crisis is worsening the
production process, delay-days per production (local) order are
presented in Figure 4. It can be seen that order delay has increased in
all sectors of the textile industry except printing and embroidery
(PEM). Dyeing, chemical and processing sector is experiencing the
highest delay duration in completion of an order due to the energy
crisis.
[FIGURE 4 OMITTED]
Overall the average duration of a local production order delay in
the textile sector has increased from seven days to ten days that
clearly shows the worsening of the crisis and hence textile production.
On the other hand, export order delay cannot exceed more than three
working days as a norm of international business in majority of cases.
3.2. Energy Analysis
Industrial sector in general and textile sector in particular is
experiencing the worst energy crisis of Pakistan's history where
eight hours per day scheduled electricity load shedding with a minimum
of two hours per day unscheduled load shedding is prevalent. In
addition, textile sector is facing four days a week gas load shedding
that is resulting in huge production losses across the industry.
Adaptation of alternative resources by firm owners have lessened the
magnitude of the problem over the time but the tight financial position
and growing energy crisis are making it difficult to get rid of this
problem completely. Increased hours of a working shift are normally
practiced to minimise the unserved energy loss but the issue becomes
even more critical when the load shedding hours are pegged with
peak-time working hours of the firms. Many of the firms have dual input
requirement of both electricity and gas as these sectors have implanted
technology where they can use whatever input is available at the time.
In is notable that in presence of gas, electricity is not used for
running of production process as electricity unit is costly than a unit
of gas. This study analyses energy loss (both electricity and gas) faced
by each sector of the textile industry, first, with respect to shifting
hours of a firm and then peak-time load shedding hours.
(a) Shifting Hour Criteria
Figures 5 and 6 explain the total energy (electricity and gas,
respectively) requirement of different sectors of the industry; supply
of energy; how much these sectors have compensated for deficiency in
energy requirement and the existing deficiency level. Electricity
consumption is the highest in spinning and textile sectors that require
18.35 and 14.29 thousand units per-day, respectively. Gas consumption is
highest in textile and dyeing and chemical sectors where the need is of
88.63 and 21.25 thousand units per-day, respectively. On the ether hand,
embroidery sector has the lowest electricity consumption per-day and
fabric sector has the lowest gas consumption per-day.
[FIGURE 5 OMITTED]
Spinning, Textile and Fabric sectors are facing severe electricity
loss but the textile sector is the one that is bearing highest cost by
employing alternative sources to compensate for energy loss. Although
energy loss is the highest in spinning sector yet this sector is not
using alternative sources to minimise its loss. Being highly electricity
dependant sector, spinning needs a huge fixed cost to finance a complete
alternate for smooth functioning of production' process. Hosiery
and garments and embroidery sectors are almost fully compensating their
energy loss by using alternative sources. Electricity gap is minimum in
DCP and WEA sectors where only severity of crisis (increased load
shedding hours) has raised their electricity loss against their employed
alternatives. Besides, DCP sector is more gas dependant than electricity
dependant; hence, requires less expenditure on electricity resources.
Figure 6 shows the gas requirements and shortfalls in different
sectors of textile industry. Contrary to electricity, gas load-shedding
is not on daily basis rather it happens according to a certain schedule
of four days a week. Textile is facing the highest energy (gas) loss
followed by DCP and hosiery and garments. Textile sector requires 91.55
thousand units gas per-day, the highest demand in the industry and
fabric has the minimum gas requirement. As a result, the textile
industry is more energy intensive sector in terms of both electricity
and gas.
[FIGURE 6 OMITTED]
Many firms in textile sector are using boilers as an alternative
resource for gas load shedding whereas wood, rice waste, com waste and,
in some cases, coal has been used as input. Environmental perspective of
using these boilers is far worse but covering that cost is beyond the
scope of this paper. Hosiery and garments sectors are sufficiently
equipped with alternative resources to keep the production process in
run in case of no energy provision.
(b) Peak Time Load-Shedding Hour Criteria
Most of the firms confirm that they face severe shortage of
electricity during their peak time of business and production activity.
Each value of concerned group of firms has more electricity requirements
during peak times as compared to shift-hour defined above. Figures 7 and
8 explain the total energy (electricity and gas, respectively)
requirement and loss situation of different sectors of the industry.
Electricity requirement for spinning sector is almost 3.2 million
units per-month while government is providing only 1.8 million units. In
this way, this sector is facing electricity shortage of 1.4 million
units per-month and compensating 0.25 million units to its energy loss
through standby generators and other alternative sources, left over with
huge energy deficiency. The weaving and sizing firms are least
compensating their energy loss same is true for shifting hour criteria.
[FIGURE 7 OMITTED]
Figure 8 depicts the picture of gas using firms that have higher
gas values as compared to shift-hour and weight according to shift-hour
criteria. Fabric, spinning and weaving and sizing are free from the
issue of gas shortage. They have less demand as well they compensate
according to their requirements. But textile, dyeing, chemical and
processing and hosiery and readymade garments are facing the severe
shortage of gas in spite of the utilisation of alternative source in
order to fulfil their requirements. In peak hour load shedding
environment, we found that firms are facing the severe loss of energy
and producing the less output. Overall, spinning sector is facing the
high deficiency of electricity while textile and dyeing, chemical and
processing are facing the huge deficiency of gas and their alternative
sources cannot fulfil their requirements.
[FIGURE 8 OMITTED]
3.3. Willingness to Pay (WTP) for Uninterrupted Energy Supply
The shortage of energy in textile sectors has compelled producers
to show their willingness to pay for uninterrupted energy supply per
unit of energy. Table 3.3 presents the estimates of WTP for
uninterrupted energy supply.
Out of 125 sample of industrial firms, only 80 (64 percent of
total) were willing to pay for uninterrupted energy supply. The
remaining firms were skeptical about provision of uninterrupted supply
even at a higher cost of input. Less interest of firm owners in
uninterrupted energy supply is due to lack of trust on public policies
and/or their less ability to face further shocks after recently faced
shock of higher price of electricity. (7) On average more than fifty
five percent firms in each sector are willing to pay higher if they are
provided nonstop energy supply.
The maximum willingness to pay was 20 Rs in DCP. The minimum
willingness to pay is 2 Rs in the textile firms. Textile sector has lost
its foreign competitiveness due to recent energy crisis and further
increase in input prices would result in complete loss of the foreign
market. It has already been shown that hosiery and readymade garments
have employed alternative resources for compensating their energy loss;
hence, that sector is less willing to pay for uninterrupted energy
supply. Interestingly, in HOS and RAM sector, those firms that are
willing to pay higher for energy supply are offering high (above than
average) prices per unit of energy.
In spite of all this energy and production crisis in textile
industry, the average range of willingness to pay is high that shows
animal spirit of the entrepreneurs of textile sectors who can make
progress and bring this industry on top of the world if they were given
necessary raw material, in this case energy, to keep production process
in run. Sector wise willingness to pay is given below in Figure 9 where
all of the curves have negative relation with the number of firms under
each sector, clearly defining the shape like demand curve.
[FIGURE 9 OMITTED]
[FIGURE 10 OMITTED]
If the first and last ten firms are ignored for time being, the
curve shows that most of the firms fall between the ranges of five to
nine rupees per unit of energy. This curve is representing the overall
willingness to pay of various sectors with different capacity of
production and; hence, an approximate picture of the textile industry.
This positive price signals need for new supplies of energy resources
into the system.
4. CONCLUSIONS
Since 2007, major export oriented textile sector has been unable to
meet the demand of both national and international orders due to heavy
planned and unplanned energy outages in Pakistan. This outage has
appeared in number of findings; intense production loss, big industrial
units have been converted into smaller one, most of the industries have
shut-down and large amount of capital flight (industries), in particular
to competing neighbouring countries, heavy loss of competitiveness in
international market and loss of business confidence by investors.
This study covers 125 firms of textile industry of Faisalabad. The
results reveal that textile industry is facing 23 to 65 percent
production loss for 8-hour shift and 21 to 60 percent for 10-hour shift
due to interruption in energy supply. Flosiery and readymade garments
sector has highest shares in production loss while weaving and sizing
firms have minimum shares in production loss. Textile firms have the
highest labour hour loss per-day in both shift-hours, including in
hosiery and readymade garments and dyeing, chemical and processing
industries. The energy outage has not only had adverse impact on
production but also created major delays in production orders. The
highest percentage increase in local order delays (as compared to its
reference period, 2008) are seen in textile firms, hosiery and readymade
garments and dyeing, chemical and processing industries. In
international market, the percentage increase in order delays is
observed for fabric firms, higher than that of textile and hosiery and
readymade garments. Furthermore, dyeing, chemical and processing firms
have highest order delays problem in both local and international
markets. It is evident that delays in production orders clearly indicate
fewer orders in near future. Most of the firms in the industry have lost
their both local and international orders. Weaving and sizing firms have
severe reduction in their local orders while textile firms have
strengthened as compared to reference period, 2008.
The findings reveal that spinning firms are more electricity
consuming and electricity deficient in Pakistan while textile firms are
facing big loss in their production due to the gas outage. The entire
firms in textile industry have taken the stand-by generator as
alternative source in order to kill the heavy schedule and unscheduled
load-shedding and to reduce the major output loss. They are trying to
compensate (maximum) their energy loss according to their requirements
but still they are facing the huge energy as well as production loss.
This heavy energy loss has compelled them to express their willingness
to pay for uninterrupted energy supply. From the sample, only 64 percent
of the firms are willing to pay for uninterrupted energy supply. On
average, the whole sub-sectors are willingness to pay around 5 rupees
per-energy unit. The embroidery firms have highest willingness to pay
while hosiery and readymade garments have least willingness to pay.
These findings are helpful for the policy makers to make the best energy
policy in favour of textile sector that may reduce the production loss
and generate the huge employment in this sector.
Comments
This study is also part of the research projects being funded by
the Pakistan Institute of Development Economics to promote innovative
research ideas and novelty in techniques needed to explore burning issue
of energy crises in Pakistan. First of all, I would like to congratulate
authors for presenting well researched study on the effect of energy
crises at the firm level of the worst affected industrial area of
Punjab. Authors have made good contribution in the existing literature
by exploring well into problems of the textile sector at the micro level
in Pakistan while earlier study by Siddiqui, et al. (2011) (1) have
computed total losses for industrial sector from prevailing energy
crises. Authors have dealt with methodology very well by decomposing
losses into output, labor hours and order delays from energy
crises-defined in terms of electricity and gas load shedding at the firm
level. Furthermore, the study measures the producer's maximum
willingness to pay (WTP) to avoid losses from energy crises by using
Hicksian approach --Compensation variation and relate it with willing to
pay (WTP). The study found that about 79 percent firms of Faisalabad are
willing to pay from Rs1 to Rs 20 per unit for uninterrupted supply of
energy. However, I would like to make few suggestions to authors for
further improvement in the study.
First, this article uses Hicksian concept of WTP in explicitly
dynamic structure while Hicksian is static in nature. Theory suggests
that in dynamic setting compensation variation or equivalent variation
can have expected value but their relationship to the concept of willing
to pay (WTP) becomes more complicated. It is because in addition to
compensation variation or equivalent variation, the willing to pay (WTP)
depends on the timing of the function of these values as even if
compensation variation or equivalent variation are unchanging with the
acquisition of new information, willing to pay (WTP) will generally not
be and at any point in time willing to pay (WTP) will not be equivalent
to expected CV or EV--this could have been incorporated as limitation of
this study.
Second, authors have computed industrial losses for gas and
electricity separately at the firm level which is good to look into the
separate impact of the energy sources used. However, total losses from
electricity and gas may also be computed and included in the tables
representing losses to output, employment and order delays from
electricity and gas load shedding.
Third, authors may incorporate the route map in policy guidelines
for handling with energy crises in the short and medium terms especially
for micro level firms. It will not only bring to light the usefulness of
this kind of study hardly undertaken at micro level in Pakistan due to
endless efforts and patience involved but will also help in policy
targeting.
Lubna Naz
PhD Scholar, PIDE, Islamabad.
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(1) NTDC Report (2011).
(2) Framework of Economic Growth 2012, Planning Commission.
(3) Ministry of Textile Industry Report 2013.
(4) Pakistan Textile Journal (Various Issues).
(5) Pakistan Economic Survey, 2012-13.
(6)Depend on substitutions and complements input alternatives.
Here, only complement is more relevant.
(7) We conducted our survey in the end of September and October at
that time; the entire industry faced almost 50 percent increase in
energy units. This huge increment also discourages their willingness to
pay for uninterrupted energy supply.
(1) Siddiqui, R., H. H. Jalil, M. Nasir, W. S. Malik, M. Khalid
(2011) The Cost of Unserved Energy: Evidence from Selected Industrial
Cities of Pakistan. (PIDE Working Papers 75).
Haider Ali <
[email protected]> is Lecturer (Economics) at
the Pakistan Institute of Development Economics, Islamabad. Muhammad
Nawaz <
[email protected]> is Junior Researcher at the Pakistan
Institute of Development Economics, Islamabad.
Authors' Note: The authors are highly thankful to; Dr Rehana
Siddiqui for her support throughout this research study, Dr Sajid Amin
for helpful suggestions in preparing questionnaire and M. Sajid Rafique
and M. Bilal Maqbool in conducting the survey. We are also grateful to
Mian Imtiaz Ali from Almaraj Hosiery Industry for his time and effort in
arranging the meetings with different industrialists and to help our
enumerators during the survey. The financial assistance for this
research paper is provided by the Pakistan Institute of Development
Economics (PIDE), Islamabad.
Table 1
Production and Labour-Hour Losses (Thousands Units Per-Day)
Sectors of Textile Industry
SPN WEA FAB
Labour- 8-Hour Shift Electricity 0.12 0.06 0.11
Hour Gas 0.06 0.00 0.01
Loss
10-Hour Shift Electricity 0.12 0.06 0.11
Gas 0.06 0.00 0.01
Production 8-Hour Shift Electricity 0.01 1.19 2.81
Loss Gas 0.00 0.00 0.26
10-Hour Shift Electricity 0.01 0.96 2.25
Gas 0.00 0.00 0.21
Sectors of
Textile Industry
DCP TEX
Labour- 8-Hour Shift Electricity 0.24 0.99
Hour Gas 0.15 0.58
Loss
10-Hour Shift Electricity 0.24 0.99
Gas 0.15 0.58
Production 8-Hour Shift Electricity 13.89 28.58
Loss Gas 8.77 14.73
10-Hour Shift Electricity 11 11 22.95
Gas 7.02 11.83
Sectors of
Textile Industry
HOS&RMG PEM
Labour- 8-Hour Shift Electricity 0.93 0.06
Hour Gas 0.56 0.03
Loss
10-Hour Shift Electricity 0.93 0.06
Gas 0.56 0.03
Production 8-Hour Shift Electricity 2.33 2.74
Loss Gas 0.49 1.57
10-Hour Shift Electricity 1.87 2.19
Gas 0.39 1.25
Table 2
Production Orders and Delays (Percentage of Concerned Orders
Per-Year)
Sectors of Textile Industry
Years SPN WEA FAB DCP
Local Orders 2008 4.3 15.2 5.0 18.6
2013 3.1 0.2 3.5 16.5
Local Order Delays 2008 22.8 47.8 23.3 31.8
2013 26.5 50.7 34.8 42.1
Export Orders 2008 6.4 0.0 6.8 3.2
2013 3.7 0.0 17.3 1.9
Export Order Delays 2008 0.0 0.0 6.4 0.0
2013 0.0 0.0 9.5 3.6
Sectors of Textile Industry
Years TEX HOS&RMG PEM
Local Orders 2008 34.5 14.7 7.8
2013 39.2 13.3 7.1
Local Order Delays 2008 31.7 16.3 27.3
2013 53.8 30.1 27.3
Export Orders 2008 60.3 23.2 0.0
2013 45.5 32.6 0.0
Export Order Delays 2008 8.2 11.1 0.0
2013 10.3 12.8 0.0
Table 3.3
Willingness To Pay (WTP) for Uninterrupted Energy Supply
Sectors of Textile Industry
SPN WEA FAB DCP
(WTP) % of Firms 66.67 60.87 73.33 66.67
Maximum (Rs.) 8 11 9 20
Minimum (Rs.) 3 4 5 4
Average (Rs.) 5.50 6.79 6.82 9.22
Sectors of Textile Industry
TEX HOS & RMG PEM
(WTP) % of Firms 61.54 57.14 77.78
Maximum (Rs.) 13 10 10
Minimum (Rs.) 2 6 4
Average (Rs.) 6.25 8.71 7.29
Fig. 1. Market Share of Different Sectors of Textile Industry
in Faisalabad
Weaving 21%
Fabric 14%
Textile 34%
Sizing 1%
Daying and Chemical 7%
Hosiery 11%
Readymade Garments 6%
Printing and
Embroidery 4%
Spinning 2%
Ginning 0%
Source: The Faisalabad Chamber of Commerce and Industry
(FCCI, 2013-14).
Note: Table made from pie chart.
