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The Lahore Journal of Economics
16 : SE (September 2011): pp. 317-346
Financing Constraints: Determinants and Implications for
Firm Growth in Pakistan
Hamna Ahmed* and Naved Hamid**
Abstract
This study has a twofold objective: (i) to investigate the determinants of
firm growth, specifically the extent to which finance constrains enterprise
growth; and (ii) to explore the determinants of external financial access in
Pakistan. External financial access is defined as access to credit through
institutional sources such as private commercial banks, nonbank financial
institutions, and state-owned banks and agencies. The study uses data from the
second round of the Investment Climate Assessment Survey conducted by the
World Bank in FY 2007. The methodology entails using an instrumental variable
approach to estimate the impact of external financial access on firm growth while
employing a probit model to explore the determinants of external financial access.
The results suggest the following: First, finance is a binding constraint to firm
growth in Pakistan—a 10 percent increase in the working capital financed
through external sources is predicted to increase the average annual growth rate
by 5.6 percentage points. Second, financial depth is important for access—across
the country, access is better where there is greater penetration of financial
infrastructure. Third, a range of internal factors such as size, export status,
quality of human capital, and organizational form emerge as important
determinants of external financial access in Pakistan.
Keywords:FinancialAccess,Firms,FinancialDepth,Pakistan.
JELClassification:043,C36.
1. Introduction
This study has a twofold objective: (i) to investigate the
determinants of firm growth, specifically to study the extent to which
finance constrains enterprise growth; and (ii) to explore the determinants
of external financial access in Pakistan.
* Research and Teaching Fellow, Centre for Research in Economics and Business, Lahore School
of Economics.
** Director, Centre for Research in Economics and Business, Lahore School of Economics.
Hamna Ahmed and Naved Hamid
318
For the purpose of this study, external financial access is defined as
access to credit through institutional sources such as private commercial
banks, nonbank financial institutions, and state-owned banks and agencies.
Subsequently in this article, the terms “external credit,” “formal credit,”
and “credit through financial institutions” are used interchangeably.
The study uses data from the second round of the Investment
Climate Assessment (ICA) Survey conducted by the World Bank in the
fiscal year (FY) 2007. The dataset provides detailed information on firm-
specific characteristics as well as a wide range of investment climate
variables pertaining to infrastructure and services, courts, crime,
government-business relations, degree of competition, and factor
markets, i.e., land, labor, and finance.
The remainder of the article is organized as follows. Section 2
develops the backdrop and outlines the motivation behind the study.
Section 3 provides a brief review of the literature on finance and growth.
Section 4 describes the data used and offers some basic statistics for the
overall sample and for the determinants of firm growth and external
financial access for the sample of firms under study. Section 5 discusses
the methodology and empirical framework. Section 6 presents the results,
and Section 7 concludes the study.
2. Motivation
Finance is an important pillar of growth. This finding has been
corroborated both at the macro and micro-level. The argument that
financial development and economic growth are positively correlated
dates back to Schumpeter (1911), and has been confirmed by various
subsequent studies such as Goldsmith (1969), King and Levine (1993),
Levine and Zervos (1998), and Robinson (1952), among others. At the
micro-level, financing constraints are predicted to exert a negative
influence on firm growth (Ayyagari, Demirgüç-Kunt, & Maksimovic,
2008; Beck, Demirgüç-Kunt, & Maksimovic, 2005). For instance, Beck et al.
(2005) find in a cross-country sample that firms that report finance as a
major constraint bear a growth penalty of 3 percent compared to firms
that do not report finance as an obstacle.
The constraint to financial access and its impact on growth is
considered most severe for small and medium enterprises (Beck &
Demirgüç-Kunt, 2006; Beck et al., 2005). For a sample of firms in eastern
Europe, employment growth was found to be 9 percent higher while
Financing Constraints in Pakistan: Determinants and Implications 319
revenue growth was 36 percent higher in firms with access to credit from
financial institutions between 2002 to 2005 (World Bank, 2009, p. 91). For
Pakistan, a decomposition of total factor productivity reveals that, among
different investment climate variables, finance accounts for 17 percent of
both average and aggregate productivity.1
Financial markets in Pakistan are underdeveloped relative to other
developing countries. With credit to the private sector at 23.5 percent of
gross domestic product (GDP) in 2009, Pakistan ranks lowest not only
compared to other South Asian countries such as India (46.8 percent) and
Bangladesh (41.5 percent), but also in comparison with other developing
countries (World Bank, 2011) (Figure 1). A look at the sources of working
capital finance reveals that a similar trend prevails at the micro-level. The
average percentage of working capital financed through commercial
banks is extremely low (6.5 percent) compared to other South Asian
countries such as Bangladesh (32 percent), Sri Lanka (21 percent), and
India (16 percent) (Figure 2).
Moreover, within the sample under study, almost 83 percent of
working capital is financed through internal funds and retained earnings,
while a mere 7 percent is financed through external credit. That financial
1 “Average” refers to the sample average productivity, and “aggregate” refers to the weighted
average productivity, with weights equal to the share of a firm’s sales in the sample.
0.0
40.0
80.0
120.0
160.0
South Africa
Thailand
Chile
Brazil
Ban
g
ladesh
Philippines
Pakistan
0
10
20
30
40
50
Mala
y
sia
Bangladesh
Brazil
Sri Lanka
South Africa
Pakistan
Figure 1: Financial Depth:
Domestic Credit to Private
Sector (% of GDP)
Figure 2: Commercial Banks’
Share of Working Capital
Finance (%)
Source: World Bank, World
Development Indicators, 2011.
Source: World Bank, Various rounds of
Investment Climate Assessment Surveys.
Hamna Ahmed and Naved Hamid
320
deepening in Pakistan is low also comes across when comparing
perceptions of managers in Pakistan on the severity of finance as a
growth constraint vis-à-vis perceptions of managers in other developing
countries. Pakistan ranks third-highest with almost 40 percent of firms
reporting finance as a major or severe obstacle to growth whereas the
number for other developing countries is much lower (Figure 3).
Figure 3: Access to Finance as a Constraint to Firm Growth (%)
Source: World Bank, Various rounds of Investment Climate Assessment Surveys.
The period covered is interesting for studying the link between finance and
firm growth in Pakistan. We examine firm growth between 2003 and 2006, a
period marked by abundant credit availability and fairly low interest rates.
In other words, 2003–06 can be thought of as a best-case scenario for ease of
financial access, and the results on the growth penalty of limited financial
access for manufacturing firms can be considered to be at the lower end.
Today, the situation is very different. The economic environment is
plagued by uncertainty, rising nonperforming loans, and excessive public
sector borrowing, which has crowded out private sector credit. Moreover,
with a tight monetary policy to rein in inflation, the severity of the financing
constraint for private sector businesses has become magnified. In this
context, the study helps shed light on the likely microeconomic
consequences of the current macroeconomic policies.
3. Literature Review
The debate on the link between finance and economic growth dates
back to Schumpeter (1911), and has both a macro and micro-dimension.
0
10
20
30
40
50
60
70
Financing Constraints in Pakistan: Determinants and Implications 321
At the macro-level, financial sector development is predicted to
have a positive impact on growth and per capita income (Schumpeter,
1911). For a cross-country sample of 35 countries, Goldsmith (1969) finds
that financial development is consistent with periods of high economic
growth. King and Levine (1993) find that high levels of financial
development are associated with rapid economic growth, physical capital
accumulation, and improvements in economic efficiency for a cross-
country sample spanning over 80 countries. This hypothesis is also
confirmed by Levine and Zervos (1998) who argue that the development of
financial markets and intermediaries has an important bearing on growth.
While these studies emphasize the statistically significant impact
of financial development on growth, there are others that are skeptical of
the direction of causality between financial sector health and growth. For
instance, Robinson (1952) argues that financial development is a natural
consequence of economic acceleration rather than a predictor of growth.
Following suit, Lucas (1988) contends that the link between finance and
growth is overemphasized.
At the micro-level, the emphasis is on how the lack of finance can
hamper enterprise growth. The main intuition underlying the growth-
finance link at the micro-level is that greater financial development makes
it easier to raise external finance. This, in turn, eases finance constraints,
especially for small and medium firms because their ability to raise
internal capital is limited. Firms are thus able to invest in profitable
growth opportunities. In this manner, greater financial access serves as a
catalyst for growth.
Demirgüç-Kunt and Maksimovic (1998) find that market
imperfections—such as underdeveloped financial and legal systems—
limit a firm’s ability to raise long-term external finance. This, in turn,
inhibits the firm’s investment and growth potential.
Based on a sample of US manufacturing firms, Rajan and Zingales
(1998) find that industries that depend more on external finance are likely
to grow faster in countries that ex ante have better developed financial
markets. This is made possible for two reasons: (i) financial development
reduces the cost of raising external finance, and (ii) it creates a
disproportionately favorable environment for young firms that would
otherwise find it more difficult to raise capital.
Hamna Ahmed and Naved Hamid
322
Later work by Beck et al. (2005) also supports this claim. For a
cross-country sample of firms, they find that financial and legal
constraints, as well as corruption, have an adverse impact on firm
growth. This relationship, however, varies by firm size. The authors find
that the growth of small firms tends to be most severely constrained by
financing issues compared to larger firms. The impact of financial and
legal constraints on firm growth tends to be strongest for small firms.
Ayyagari et al. (2008) investigate the importance of financing
constraints relative to other business environment obstacles to firm
growth for a sample of 4,197 firms from 80 different developed and
developing countries. The authors find that finance, policy instability,
and crime are the only binding constraints to firm growth. All other
features of the business environment—corruption, taxes and regulations,
judicial efficiency, and anti-competitive practices, etc.—have either an
insignificant or indirect impact on growth, which works through the
binding constraints channel.
An important channel through which access to finance promotes
growth is that of fostering innovation. For a sample of 10,000 firms from
34 developing countries, Ayyagari, Demirgüç-Kunt, & Maksimovic (2007)
show that firms with greater access to external finance are also more
innovative and dynamic. Innovation is measured by the firm’s ability to
introduce new products and processes. Dynamism, on the other hand, is
defined by activities such as the “opening of a new plant, bringing in-
house previously out-sourced activities, and establishing foreign joint
ventures and new licensing agreements” (Ayyagari et al., 2007).
This article contributes to the micro-level literature on finance and
firm growth. Two main features of this study distinguish it from existing
studies on the topic. Recognizing simultaneity in external financial access
and firm growth, we employ an instrumental variable approach and
construct a unique exogenous measure of access that incorporates both
demand and supply-side influences on financial access. Further details on
this are discussed in Section 5. In addition, this is the first study to
explore simultaneously the determinants of firm growth and external
financial access for Pakistan. This will be useful in providing an in-depth
and holistic picture of the finance-firm growth nexus for manufacturing
firms in Pakistan.
Financing Constraints in Pakistan: Determinants and Implications 323
4. Data
The study uses data from the second round of the Pakistan ICA-II
Survey conducted by the World Bank in 2006/07. The ICA-II survey
provides detailed information on firm characteristics and various aspects of
the business environment in the country. The former includes information
on an establishment’s sales, employment, and productivity. Key dimensions
of the business environment include infrastructure and services, courts,
crime, government-business relations, degree of competition, and factor
markets (land, labor, and finance).
The sampling frame consists of a stratified random sample of
firms drawn from the Census of Manufacturing Industries (2005), the
only firm-level survey available in Pakistan and conducted by the Federal
Bureau of Statistics. The total sample was based on 1,350 firms of which
1,186 are manufacturing establishments while the rest are service firms.
The sample is representative at the national, provincial, and sectoral level.
The analysis in this paper is limited to manufacturing firms only.
The surveyed firms are located in 13 cities across the country with
a large share coming from big cities such as Karachi, Lahore, Faisalabad,
etc. (Figure 4).2 The firms belong to nine different industries of which a 50
percent come from the textiles, food, and garments industries (Figure 5).
Another one third has been grouped together in the “others” category,
and consists of firms that produce products such as sports goods, surgical
instruments, cutlery, furniture, jewelry, shoes, plastics, and
pharmaceutical goods, etc.
2 For the rest of the paper, firms in Hub have been pooled with those in Karachi. Hub has not been
treated as a separate location for two reasons: (i) in terms of access to finance, conditions are
similar to those faced by firms in Karachi because it lies on the outskirts of the city, with most
nonproduction staff being based in Karachi; (ii) only six firms out of a total sample of 1,186 have
been surveyed from this location.
324
Source: W
o
A
medium
i
or more.
A
rest are e
i
located i
n
all large
f
and med
i
Sialkot,
G
T
h
large fir
m
intra-ind
u
machine
r
O
n
exportin
g
included
0
5
10
15
20
25
Karachi
2
Figur
e
o
rld Bank, Inv
e
firm is cla
s
i
f it emplo
ys
A
bout 50 p
e
i
ther mediu
m
n
large cities
;
f
irms in the
s
i
um firms,
r
G
ujranwala,
a
h
e inter-ind
u
m
s belong t
o
u
str
y
size d
i
y
/equipme
n
n
e fifth of
g
firms incr
e
(Figure 7).
Karachi
Faisalabad
Sialkot
Peshawar
0
14 14
11 10 7
6
e
4: Distrib
u
by Locati
o
H
amna Ah
m
e
stment Clima
s
sified as s
m
s
20–100 wo
r
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rcent of th
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;
Karachi an
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ample as c
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espectivel
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a
nd Faisalab
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i
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t manufac
t
the surve
y
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ases to 30
p
Peshawar
Quetta
Wazirabad
Hub
6
44433
1
u
tion of Fir
m
o
n (%)
m
ed and Nave
d
te Assessment
m
all if it em
p
r
kers, and l
a
e
sample co
n
Figure 6). L
a
d
Lahore al
o
o
mpared to
A third of
a
d (Table A
1
d
istribution
u
stries: texti
l
n the other
h
t
uring firms
ed firms e
x
p
ercent wh
e
Hub
1
0.0
10.0
20.0
30.0
40.0
m
s Figur
d
Hamid
Surve
y
, 2007.
p
lo
y
s fewer
a
rge if it em
p
n
sists of sm
a
a
rge firms
a
o
ne account
f
18.6 and 35.
3
all small fi
r
1
in the Ann
e
shows that
l
es, food, a
n
h
and revea
l
are predom
x
port direc
t
e
n indirect
e
Textiles
Food
Garments
Machinery
hl
21.9
18.0
10.25.7
e 5: Distrib
u
by Indus
t
than 20 w
o
p
lo
y
s 100 w
o
a
ll firms wh
i
a
re predomi
n
f
or 63.5 per
c
3
percent of
r
ms are loca
t
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xure).
60 percent
n
d garment
s
l
s that leath
e
inantl
y
sma
t
l
y
. The sh
a
e
xporters ar
C
h
emica
l
s
Leather
Electronics
NMM
Others
3.8 3.1 1.4 1.1
34
.
u
tion of Fir
m
t
ry (%)
o
rkers,
o
rkers
i
le the
n
antl
y
c
ent of
small
t
ed in
of all
s
. The
e
r and
ll.
a
re of
e also
.
8
m
s
F
Source: W
o
A
ccess to
O
f
external
f
small fir
m
locations
Wazirab
a
and Gujr
a
metropol
i
penalt
y
; f
o
large fir
m
Gujranw
a
small fir
m
to access
f
Source: A
u
Figure 6
:
F
inancin
g
Co
n
o
rld Bank, Inv
e
Finance
f
the total s
a
f
inance. Lar
g
m
s (Figure 8
)
where ther
e
a
d—and in c
a
nwala (Tab
l
i
tan cities s
u
o
r instance,
m
s in Karac
h
a
la. This co
u
m
s when co
m
f
inance whe
n
Fig
u
u
thors’ calculat
i
:
Distributi
o
Size
n
straints in Pa
e
stment Clima
a
mple, onl
y
g
e firms are
)
. Small fir
m
e
are predo
m
ities where
f
l
es A1 and
A
u
ch as Kar
a
small firms
a
h
i, but onl
y
u
ld impl
y
ei
t
m
petition fr
o
n
firms are
p
u
re 8: Fina
n
i
ons; World Ba
o
n of Firms
b
kistan: Deter
m
te Assessment
14.7 perce
n
six times m
m
s have easi
e
m
inantl
y
sm
a
f
irms are p
a
A
2 in the A
n
a
chi, Lahore
,
a
re 18 times
four times
t
her that ba
n
o
m large fir
m
p
art of a net
w
n
cial Access
nk, Investmen
t
Direct
Export
ers
21.3%
No
n
Dir
e
Ind
i
b
y Figure
m
inants and I
m
Surve
y
, 2007.
n
t of the fir
m
ore likel
y
t
o
e
r access to
e
a
ll or medi
u
a
rt of a clust
e
n
nexure). Be
i
,
or Faisala
b
less likel
y
t
o
less likel
y
n
ks are mor
e
m
s is limited
,
w
ork.
by Size (%)
t
Climate Asse
s
IE
7.1%
n
-Exporter (NE)
e
ct Exporter (DE
)
i
rect Exporter (I
D
7: Distribu
t
Export
S
mp
lications
m
s have ac
c
o
have acces
s
e
xternal fina
n
u
m firms—s
u
e
r, such as
S
i
ng a small f
i
b
ad comes
w
o
have acces
s
to have acc
e
likel
y
to l
e
,
or that it is
s
sment Surve
y
,
Non-
Export
ers
70%
Both
1.6%
)
D
E)
t
ion of Fir
m
S
tatus
325
c
ess to
s
than
n
ce in
u
ch as
S
ialkot
i
rm in
w
ith a
s
than
ess in
e
nd to
easier
2007.
m
s by
Hamna Ahmed and Naved Hamid
326
The correlation between size and external financing is also evident
from intra-industry patterns of financial access (Table A3 in the
Annexure). For almost all industries, financial access increases
substantially from small to large firms.
Between exporters and nonexporters, direct exporters are more
likely to have access. On average, a direct exporter is three times more
likely to have access than a nonexporter (Table 1). This is also true for each
size category. The advantage of access, however, systematically falls from
small to large firms; a small direct exporter is eight times more likely to
have access than a small nonexporter while a large exporter is only 1.5
times more likely to have access than its nonexporting counterpart.
This could imply either that, ex ante, more productive firms self-
select themselves into becoming exporters, or that, ex post, exporting
firms are more productive (Wagner, 2007). Irrespective of which way the
causality runs, a firm’s export status seems to have a bearing on its ability
to access external finance for the sample of firms under study. It is worth
noting that being an indirect exporter does not significantly improve
access to finance. This is an indication of the lack of documentation in
domestic commerce and the failure of government policies aimed at
providing indirect exporters with the same incentives as direct exporters.
Table 1: Firms with External Financial Access by Exporting Status
Size Direct Exporters (%) Indirect Exporters (%) Nonexporters (%)
Small 24.0 5.6 3.4
Medium 21.1 10.5 12.1
Large 43.9 33.3 28.6
Total 33.3 14.3 9.3
Source: Authors’ calculations; World Bank, Investment Climate Assessment Survey, 2007.
Finally, there are a number of other differences between firms
with access and those without access (Table 2). Firms with access are
more advanced technologically; twice as many machines are computer-
controlled compared to the sample of firms without access. They are three
times more likely to innovate by introducing new products and processes
than their counterparts without access. Moreover, firms with access have
better-quality human capital. In general, the top management in firms
with access is more experienced and has attained a higher education level
than their counterparts without access. Also, these firms are mostly
organized as private limited or publicly listed companies as compared to
Financing Constraints in Pakistan: Determinants and Implications 327
firms without access, of whom 78 percent are sole proprietorships or
partnerships.
Table 2: Characteristics of Firms by Financial Access
Variable Firms with Access
Firms without
Access
N (%) N (%)
Human capital
Top manager < undergraduate
degree
23 13.2 537 53.1
Top manager = undergraduate
degree
79 45.4 311 30.7
Top manager = postgraduate degree 72 41.4 161 15.9
Organizational form
Sole proprietorship/partnership 74 42.5 786 77.7
Private limited 77 44.3 179 17.7
Publicly listed 23 13.2 38 3.8
Innovation
New product 51 29.3 131 12.9
New process 56 32.2 102 10.1
Source: Authors’ calculations; Investment Climate Assessment Survey, 2007.
Growth
On average, firms in the sample grew at 4.3 percent per annum from
2003 to 2006. The growth rate was much higher for firms with access (7
percent) compared to firms without access (3.9 percent) (Figure 9a).
Moreover, growth rates are different across cities and across industries
(Figures 9b and 9c).
Hamna Ahmed and Naved Hamid
328
Figure 9: Average Annual Growth Rate, 2003–06 (%)
Source: Authors’ calculations; World Bank, Investment Climate Assessment Survey, 2007.
In light of these descriptive statistics, we can draw three broad
conclusions regarding the determinants of firm growth and external
financial access: First, access is a clear divide and that finance is an important
aspect of growth. Second, firms with access are inherently different with
regard to their organizational form, quality of human capital, and degree of
innovation from firms without access. Third, size, export status, industry,
and location appear to be important dimensions of access. In what follows,
these claims will be tested more rigorously using quantitative techniques.
5. Methodology
5.1. Determinants of Firm Growth
The observations in the last section are based on a casual glance at
the data and warrant more rigorous quantitative treatment. To that end,
the regression model is specified as follows:
∑
∑
∑
(1.1)
(1.2)
where GRfil measures the average annual labor growth rate of firm f,
industry i, location l between fiscal year 2003 to 2006.
4.3
7.0
3.9
0.0
2.0
4.0
6.0
8.0 8.9
5.3
4.1
3.3
1.3
0.0
2.0
4.0
6.0
8.0
10.0
Garments
Food
Textiles
Others
Leather
9.0
4.5 4.1
3.2 2.9
0.9
0.0
2.0
4.0
6.0
8.0
10.0
Karachi
Lahore
Sialkot
Others
Faislabad
Gujranwala
(a) Overall and by
Financial Access
(b) By Industry
(c) By Location
Financing Constraints in Pakistan: Determinants and Implications 329
Afil; financial access to formal credit for each firm f in industry i and
location l. For the dataset under study, financial access to formal credit
could have potentially been measured in three ways: (i) as a percentage of
the working capital financed through institutional sources in the past year,
(ii) as a percentage of new investments financed through institutional
sources in the past year, and (iii) in terms of the firm manager’s perceptions
of the severity of the “access to finance” constraint (i.e., availability and
cost of formal credit, interest rates, fees, and collateral requirements) as an
obstacle to the firm’s current operations.
The data on item (iii) was noisy because responses were based on
perceptions rather than actual availability. For instance, while a firm may
be financially constrained, managers might not perceive access to finance
as a major obstacle to growth relative to other constraints that the firm
might face at a particular point in time. Similarly, formal credit may be
readily available to a firm, but managers might perceive access to finance
as a major obstacle due to a poor working relationship between the
establishment’s management and that of the financial institution. Using
item (ii) as a proxy for financial access was also problematic as only 237 out
of a total of 1,168 firms reported having undertaken any new investment
over the past year. Using this measure would have thus meant a huge loss
in sample size, which would have affected the quality of results. For
reasons of data availability, the percentage of working capital financed
through institutional sources was used as a proxy for access to formal
credit. Institutional sources included private commercial banks, nonbank
financial institutions, and state-owned banks or agencies.
Apart from reasons of data availability, the financing of working
capital through formal credit serves as a good proxy for financial access
(or the lack thereof) in Pakistan’s context. This is because the main source
of credit in Pakistan is the banking sector, which provides funding largely
in the form of working capital. In most cases, even investment (except for
green-field projects or major capacity expansion) is financed through
lines of credit and short-term loans, which are automatically rolled over
on maturity.
X is a vector of firm-specific characteristics. Broadly, these
characteristics pertain to four main categories: (i) the general topography of
the firm as given by its size and export status, (ii) the quality of its human
capital, (iii) its organizational form, and (iv) degree of innovation. I is a vector
of industry dummies while L is a vector of location dummies to account
for industry and region fixed effects (see Table A4 in the Annexure for
Hamna Ahmed and Naved Hamid
330
more details on which variables are included under each head and how
they have been constructed). γ,β,α and δ are unknown parameters to be
estimated from the regression model. Finally,
is a normally distributed
error term comprising three components as illustrated in Equation 1.2.
(fil) represents all unobserved firm-specific characteristics that might
affect a firm’s growth rate.
The key identification condition required to produce an unbiased
estimate of the impact of financial access on firm growth using an
ordinary least squares (OLS) estimation technique is given by:
Cov (A,
) = 0 (1.3)
This identification condition is, however, violated by the presence
of endogeneity bias in the variable of interest, i.e., financial access. Firms
with access may find it easier to expand and invest in profitable
opportunities, and this will in turn spur growth. However, a firm’s
growth rate may have an impact on the probability of it being able to
access finance, and financial institutions may be more willing to lend to
rapidly growing firms with a sound cash-flow position. This reverse
causality between financial access and growth leads to endogeneity bias
and hence violates the key identification condition outlined in Equation
1.3. Applying the OLS method with an endogenous variable of interest
will produce a biased and inconsistent estimate of the impact of financial
access on growth.
An Exogenous Measure of Financial Access
We use an instrumental variable approach to account for
endogeneity. The degree of financial access available to a firm is likely to
be a function of both demand and supply-side factors. For instance, Rajan
and Zingales (1998) use an interaction term in which the demand side is
captured by calculating each industry’s technological demand for
external finance while the supply side is measured by the level of
financial development in the country. To account for this, we construct an
instrumental variable such that it is an interaction term between demand
and supply-side variables.
On the demand side, it is argued that some firms may be more
dependent on external finance than others. This could be because of
differences in the scale of the project, in the product’s gestation period, or
in the requirement for continuing investment (Rajan & Zingales, 1998).
Financing Constraints in Pakistan: Determinants and Implications 331
One possibility is to use a firm-level measure of external financial
dependence. For instance, Hyytinen and Toivanen (2005) use profitability-
based measures: a firm is classified as dependent on external finance if its
return on assets was negative in the last FY or if the entrepreneur
responded in the survey that the firm’s current profitability was worse
than its average performance over the last three years. Poor profitability
would imply the availability of a low level of internal finance and hence a
greater dependence on external finance. The drawback of using a firm-level
measure, however, is that reverse causality would persist between growth
and financial dependence, thus biasing the results.
To account for this limitation, the study uses an aggregate measure
of external financial dependence at the industry level. To that end,
information on bank advances as a ratio of total value added is used as a
proxy for an industry’s dependence on external finance. To capture the
supply side, a distinction is made between “availability” of external financial
credit and banks’ “willingness” to provide that credit. The level of local
financial development—as measured by the number of bank branches in the
city in which the firm is located—is used as a proxy for ”availability.”
“Willingness” is measured by the percentage of firms that have access to
external finance in a particular firm’s size category (see Table A4 in the
Annexure for details of data sources for each of these indicators).
For this interaction term to be a valid instrument of firm-level
external financial access, the following conditions must hold:
Cov (I, A) ≠ 0 (1.4)
Cov (I,
GR
) = 0 (1.5)
where I represents the instrumental variable, A is access, and GR is the
growth rate, the dependent variable. A fairly high correlation between A
and I (27.9 percent) and fairly low correlation between GR and I (0.08
percent) support the use of this interaction term as an appropriate
instrument for firm-level external financial access.
If conditions 1.4 and 1.5 are satisfied, Equation 1.1 can be
estimated in two stages. The first stage entails specifying a reduced-form
equation forwhich is a function of I as well as all other exogenous
variables. This equation is given by:
()
01 2
n
f
il l fs i m m fil
AFDDZ
π
πα π
μ
=
=+ ∗ ∗ +∑ + (1.6)
Hamna Ahmed and Naved Hamid
332
wheretheterminparenthesisrepresentstheinstrumentalvariable;FDlis
financialdepthinlocationl;
α
fs
representspercentageoffirmswith
externalfinancialaccessinfirms’sizecategorys;whileDimeasures
industryiʹsdependenceonexternalfinance.Zisavectoroffirmspecific
characteristics,aswellasindustryandlocationdummies.Thesecond
stageinvolvesestimating(1.1)afterreplacing(A)withitsfittedvalues
obtainedfrom(1.6).
The second stage involves estimating Equation 1.1, having
replaced with its fitted values obtained from Equation 1.6.
5.2. Determinants of Financial Access
In the next step, we specify the following regression model to
explore the determinants of financial access:
()
123
12
411
1,,,,,
f
il l f i
Prob A
n
fil m i i l l fil
mil
FD C GR X I L FD C GR
XIL
ε
γβ β β
βαδε
===
==++++
+++
∑∑∑
where is a dummy variable equal to 1 if firm f in industry i and
location l has access to external finance and 0 otherwise. is a measure
of financial depth proxied by number of bank branches in city l. is the
business climate index based on perceptions of firm f’’s manager. is
the average annual growth rate between 2003 to 2006 of industry i. Refer
to Table 4, Appendix A for more details on how the variables have been
constructed. i is a vector of firm specific characteristics, I
i a vector of
industry dummies while Li is a vector of location dummies to control for
industry and region fixed effects.
6. Results
6.1. Determinants of Firm Growth
Our results reveal that a range of internal and external factors are
important determinants of firm growth in Pakistan (Table 3).
Financing Constraints in Pakistan: Determinants and Implications 333
Table 3: Determinants of Firm Growth in Pakistan
Variable Coefficient P Value
External access 0.56** 0.03
Type of firm
Small or medium enterprise -0.02 0.90
Export status -0.04 0.39
Organizational form
Private limited -0.03 0.42
Publicly listed -0.04 0.56
Innovation
New process 0.12* 0.01
New product 0.00 0.97
Human capital
Experience 0.00 0.15
Undergraduate degree 0.01 0.80
Postgraduate degree 0.00 0.97
More than 13 years’ education3 -0.02 0.86
Business environment
Business climate index 0.01 0.26
Location dummies
Sheikhupura -0.091** 0.02
Faisalabad -0.085*** 0.06
Gujranwala -0.141* 0.00
Wazirabad -0.116*** 0.08
Sukkur -0.081** 0.05
Industry dummies
Chemicals -0.101** 0.05
Constant 3.538* 0.00
N 1,142
*** Significant at 1%, ** significant at 5%, * significant at 10%.
^ Only the significant location and industry dummies have been reported.
Source: Authors’ calculations.
The impact of financial access on firm growth is positive and
statistically significant. The instrumental variable estimate of the impact of
financial access suggests that a 10 percent increase in working capital
3 The model was also run with the dummy variable equal to 1 if a typical production worker has
attained more than six years of education, with no change in results.
Hamna Ahmed and Naved Hamid
334
financed through external sources will increase a firm’s growth rate by 5.6
percentage points, ceteris paribus. Thus, it is evident that the lack of external
financial access imposes a substantial growth penalty on Pakistani firms.
This finding is in line with the literature, with estimates for the growth
penalty ranging from 3 to 9 percent in the studies referred to earlier.
Innovation also turns out to be positively related to growth. Firms
that had introduced a new process in the last three years had a 12 percent-
higher average annual growth rate. However, one must be wary of causal
interpretation given the issue of simultaneity. High-growth firms may have
more available resources to undertake research and development, and thus
more likely to innovate. This finding is also consistent with the literature
on innovation, productivity, and growth. Ranging from early studies by
Solow in which technical progress is treated as an exogenous factor—to
studies that fall within the ambit of new growth theory—where technical
progress or innovation is treated as endogenous — the consensus seems to
be that innovation has a significant effect on productivity at the level of the
firm, industry, and country.
Other firm-specific characteristics such as size, organizational
form, human capital, and export status are not directly related to growth,
but they do have an indirect effect that works through the finance
channel (see Section 6.2 for further discussion).
The lack of significance of export status for firm growth is a
finding that warrants some discussion. The literature predicts a positive
relation between exports and productivity either because more
productive firms self-select themselves into becoming exporters or
because of the learning-by-exporting hypothesis whereby knowledge
flows from international buyers and competitors and improves firms’
post-entry performance. In Pakistan’s case, at least for this particular
period, export status seems to have no effect on firm growth. This could
partly be because export firms are concentrated in products such as food,
garments, and textiles, which rank at the low end of the technology
ladder. The possibilities of learning-by-doing and positive spillovers are
limited, and most firms may not be accruing the growth benefits of their
presence in export markets.
Financing Constraints in Pakistan: Determinants and Implications 335
On the external side, a firm’s location is significant for its growth.
Compared to big cities, firms in smaller cities have lower growth rates.4
For instance, as Table 3 illustrates, the growth rate differential between
firms in Karachi and other smaller cities such as Sheikhupura,
Gujranwala, Wazirabad, and Sukkur ranges between 8.1 and 14.1 percent.
Business climate, however, is insignificant for firm growth. This
would have been surprising in the case of a cross-country study, but in this
study, it is possible that our location dummies capture the impact of the
business climate. To explore this further, we estimate the following equation:
12
1
whereisthebusinessclimateindex,basedonperceptionsoffirmf’’s
managerinindustryi,andlocationl.Theindexrangesbetween0and13,
withgreaterthenumberofdimensionsofbusinessenvironmentthatthe
managersperceivetobemajorobstaclesforfirm’soperations,higherthe
valueoftheindex.Llontheotherhandisavectoroflocationdummies,
whileistheerrorterm.TheomittedcategoryisKarachi.Resultsshow
thatitisnotthatbusinessclimatedoesnotmatterbut,assuspected,the
locationdummiesarepickingupdifferencesinbusinessclimateacross
cities.Thisisevidentfromthefactthat8outof12locationsemergeas
statisticallysignificant(Table4).Also,itisinterestingtonoteisthat
managersperceivebusinessenvironmentinLahoretobebetterthanthat
inKarachi,whileinallothercities,managersconsiderbusiness
environmenttobeworsethanKarachi.
4 For the results in Table 3, Karachi is used as the omitted category. The finding also holds true
when Lahore is made the omitted category. In this case, the growth rate differential between firms
in Lahore and other smaller cities ranged between 8 and 20 percent.
Hamna Ahmed and Naved Hamid
336
Table 4: Business Climate and Location
Dependent variable: Business climate
City Coefficient P Value
Lahore -1.07*** 0.00
Sheikhupura 3.97*** 0.00
Faisalabad 2.99*** 0.00
Gujranwala 1.20*** 0.00
Wazirabad 1.67*** 0.00
Rawalpindi/Islamabad 3.04*** 0.00
Hyderabad 1.58*** 0.00
Quetta 1.32*** 0.01
Sialkot 0.29 0.32
Sukkur -0.67 0.25
Peshawar 0.01 0.99
*** Significant at 1%.
Source: Authors’ calculations.
6.2. Determinants of External Financial Access
The study’s results reveal that a range of both internal and
external factors are important in determining external financial access in
Pakistan (Table 5).
On the external side, the level of financial depth in the city as well
as the firm’s location is significant, while industrial growth is insignificant
for access. A 1 percent increase in the number of bank branches in the
firm’s city of location increases its probability of access to external finance
by 4.9 percent, ceteris paribus. Compared to firms located in metropolitan
cities such as Karachi, Lahore as well as those located in export-led hubs
such as Sialkot, firms in all other cities have a lower probability of access.5
The results show that the access differential between firms in Karachi and
other smaller cities ranges between 4.9 and 13.1 percent.
An establishment’s growth rate, on the other hand, is insignificant for
access. To account for reverse causality, the model was also estimated using
industry-level growth rate averages, for which the finding continued to hold
5 For the results in Table 5, Karachi is used as the omitted category. The model was also run using
different omitted categories, i.e., Lahore and Sialkot. The result holds true in each case. With
Lahore (Sialkot) as the omitted category, the access differential ranged between 9 and 20 percent (8
to 15 percent).
Financing Constraints in Pakistan: Determinants and Implications 337
true. This is not surprising given the nature of bank lending in Pakistan
whereby banks prefer short-term securities (State Bank of Pakistan, 2010, p.
15). Thus, lending by financial institutions occurs more on the basis of
operating capital rather than because they are forward looking.
On the internal side, a range of firm-specific characteristics such as
degree of innovation, size, export status, organizational form, and quality
of human capital emerge as important determinants of external financial
access. Innovative firms are more likely to have access; firms that have
introduced a new process over the last three years have an 8 percent higher
probability of access. Small and medium firms are, respectively, 12.2 and
7.4 percent less likely to have access to external finance compared to large
firms, ceteris paribus. Exporters are approximately 8 percent more likely to
have access than their counterparts who do not export.
Compared to sole proprietors and partnerships, private limited
and publicly listed companies are 3.4 and 5.8 percent more likely to have
access, respectively. The quality of human capital, as measured by the top
manager’s level of education and years of experience, is significantly and
positively related to probability of access. The more experienced the top
manager of the firm, the higher the chances of access. Moreover firms in
which the top manager has a bachelors or a post graduate degree have a
greater likelihood of access compared to their counterparts in which the
top manager is not a graduate.
To conclude, our results on the determinants of access suggest
that, broadly, access to formal credit is a function of two main factors: (i)
the availability of infrastructure to provide credit, and (ii) lending
organizations’ risk perception of the borrower. As far as the former is
concerned, there is still limited financial outreach. Even where there is
greater financial penetration (in big cities such as Karachi, Lahore, etc.),
the financial sector is underdeveloped—evident from the fact that most
lending occurs based on operations and turnover and is short-term. Thus,
banks evaluate an establishment on the basis of its current financial
position as reflected by its accounts or turnover.
In this regard, firm-specific characteristics such as export status,
organizational form, and quality of human capital provide important
information to banks when deciding whether and how much to lend.
Limited companies, for instance, have audited accounts, making it easier
for banks to assess the former’s financial viability. Exporters may not
necessarily have audited accounts but with export receipts coming
Hamna Ahmed and Naved Hamid
338
through bank, financial institutions can make well-informed assessments
of firms’ size and operation. Finally, the quality of human capital is likely
to ease interaction and facilitate negotiations with the bank.
Table 5: Determinants of External Financial Access in Pakistan
Variable Marginal Effect P Value
External factors
Financial depth 0.049*** 0.00
Business climate index 0.00 0.20
Average industry growth 0.00 0.20
Internal factors
Small -0.122*** 0.00
Medium -0.074*** 0.00
Exporting status 0.079*** 0.00
Organizational form
Privately listed 0.034** 0.03
Public limited 0.058*** 0.00
Innovation
New product -0.04 0.19
New process 0.078** 0.05
Human capital
Top manager’s experience 0.002*** 0.01
Top manager’s undergraduate education 0.135*** 0.00
Top manager’s postgraduate education 0.196*** 0.00
Location dummies^
Sheikhupura -0.130*** 0.00
Faisalabad -0.117*** 0.00
Gujranwala -0.049* 0.10
Islamabad/Rawalpindi -0.107*** 0.00
Sukkur -0.114*** 0.01
Hyderabad -0.078* 0.07
Quetta -0.131*** 0.00
Industry dummies^
Chemicals 0.169*** 0.01
Leather and leather products 0.129* 0.07
N 1,102
*** Significant at 1%, ** significant at 5%, * significant at 10%.
^ Only the significant location and industry dummies have been reported.
Source: Authors’ calculations.
Financing Constraints in Pakistan: Determinants and Implications 339
7. Conclusions
The study’s most important conclusion is that finance is a binding
constraint to firm growth in Pakistan. Even during the heyday of external
finance, manufacturing firms faced an average annual growth penalty of
the order of 5.6 percentage points, ceteris paribus. Within the country,
access to formal credit is better in cities where there is greater penetration
of financial infrastructure. Furthermore, all other firm-specific
characteristics such as size, export status, organizational form, and
quality of human capital affect growth indirectly through the binding
constraint, i.e., access to finance. This is evident from the fact that these
variables are statistically significant in the determinants of access
regression but insignificant in the growth regressions. These findings
shed light on the pivotal role that finance can play in the development of
industry and emphasize the need to overcome existing weaknesses in the
sector by moving the country toward greater financial development.
Hamna Ahmed and Naved Hamid
340
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Annexure A
Table A1: Size Distribution of Firms by Location*
City Small Medium Large
Karachi 8.5 19.9 43.1
Lahore 10.1 15.4 20.4
Sheikhupura 5.5 2.2 1.2
Sialkot 10.2 11.5 5.8
Faisalabad 16.2 13.8 9.2
Gujranwala 15.3 10.4 3.1
Wazirabad 5.8 2.0 0.4
Islamabad 7.6 7.6 6.5
Sukkur 5.3 2.0 0.8
Hyderabad 4.9 3.1 2.3
Quetta 6.0 1.7 1.2
Peshawar 4.6 10.1 3.8
Hub 0.0 0.3 1.9
*As a percentage of total number of small, medium, and large firms.
Source: Investment Climate Assessment Survey, 2007.
Table A2: Firms with External Financial Access by Location and Size
(%)
City Small Medium Large Total
Karachi 2.1 11.3 37.5 21.9
Lahore 5.3 10.9 39.6 18.2
Sheikhupura 0.0* 0.0* 33.3 0.6
Sialkot 13.8 17.1 46.7 16.5
Faisalabad 0.0 10.2 25.0 9.6
Gujranwala 10.3 21.6 37.5 24.1
Wazirabad 12.1 14.3 0.0 6.9
Islamabad 0.0 7.4 23.5 13.3
Sukkur 3.3 14.3 0.0 4.7
Hyderabad 3.6 27.3 16.7 11.9
Quetta 0.0 16.7 0.0 2.4
Peshawar 11.5 19.4 50.0 38.5
Hub N/O^ 0.0* 80.0 66.7
^ No small firms located in Hub.
* There were no firms in this category with access to finance.
Source: Authors’ calculations; Investment Climate Assessment Survey, 2007.
Financing Constraints in Pakistan: Determinants and Implications 343
Table A3: Firms with External Financial Access by Industry and Size
(Percent)
Category Small Medium Large Total
Textiles 4.4 14.3 27.9 12.8
Food 2.0 8.6 42.1 16.3
Garments 2.9 10.8 21.5 10.9
Machinery and equipment 9.3 14.3 20.0 11.9
Chemicals 0.0 22.7 66.7 28.9
Leather and leather products 11.1 14.3 0.0 12.5
Electronics 0.0* 0.0* 0.0* 0.0*
Nonmetallic minerals 10.5 33.3 60.0 25.0
Other manufacturing 6.4 13.0 36.6 13.3
* There were no firms in this category with access to finance.
Source: Authors’ calculations; Investment Climate Assessment Survey, 2007.
Hamna Ahmed and Naved Hamid
344
Table A4: List and Description of Variables
Variable Description
Firm growth Average annual employment growth rate of the firm
between FY2003 and FY2006.
Endogenous measure
of external access
Percentage of working capital financed through
institutional sources, including private commercial
banks, state-owned banks and agencies, and nonbank
financial institutions.
Instrument for external
financial access
An interaction term between supply- and demand-side
variables.
Supply side
Availability of credit: Measured by number of bank
branches in the city in which firm is located (Banking
Statistics, 2007).
Willingness to provide credit: Measured by percentage of
firms with access to external credit in the firm’s
respective size category (Investment Climate
Assessment Survey, 2007).
Demand side
Industry’s dependence on external finance: Measured by
bank advances as a ratio of total value added by the
industry (Census of Manufacturing Industries, 2005;
Handbook of Statistics on Pakistan Economy, 2010).
Small Dummy = 1 if firm is small, 0 otherwise.
Medium Dummy = 1 if firm is medium, 0 otherwise.
Export status Dummy = 1 if firm is an exporting firm, 0 otherwise.
Organizational form
Private limited Dummy = 1 if firm is a private limited company, 0
otherwise.
Publicly listed Dummy = 1 if firm is a publicly listed company, 0
otherwise.
Innovation
New process Dummy = 1 if firm has introduced a new process
during the last three years, 0 otherwise.
New product Dummy = 1 if firm has introduced a new product
during the last three years, 0 otherwise.
Financing Constraints in Pakistan: Determinants and Implications 345
Human capital
Experience Number of years the top manager has been in the field.
Undergraduate degree Dummy = 1 if the top manager has a BA degree, 0
otherwise.
Postgraduate degree Dummy = 1 if the top manager has a postgraduate
(local or foreign) degree, 0 otherwise.
Education of a typical
production worker
Dummy = 1 if a typical production worker has more
than 13 years of education, 0 otherwise.
Business climate index A simple average of 13 different dimensions of the
business environment. Responses are based on
manager’s perception of how much of a constraint
each of these factors is in firm’s operations and growth.
The various dimensions include: access to land, power,
telecommunications, water supply, crime/theft,
transportation, tax administration, tax regulation,
licensing and permits, macroeconomic instability,
political instability, corruption, labor regulations.
Location dummies
Lahore Dummy = 1 if firm is located in Lahore, 0 otherwise.
Sheikhupura Dummy = 1 if firm is located in Sheikhupura, 0
otherwise.
Sialkot Dummy = 1 if firm is located in Sialkot, 0 otherwise.
Faisalabad Dummy = 1 if firm is located in Faisalabad, 0
otherwise.
Gujranwala Dummy = 1 if firm is located in Gujranwala, 0
otherwise.
Wazirabad Dummy = 1 if firm is located in Wazirabad, 0
otherwise.
Islamabad/
Rawalpindi
Dummy = 1 if firm is located in
Islamabad/Rawalpindi, 0 otherwise.
Sukkur Dummy = 1 if firm is located in Sukkur, 0 otherwise.
Hyderabad Dummy = 1 if firm is located in Hyderabad, 0
otherwise.
Quetta Dummy = 1 if firm is located in Quetta, 0 otherwise.
Peshawar Dummy = 1 if firm is located in Peshawar, 0 otherwise.
Hub Dummy = 1 if firm is located in Hub, 0 otherwise.
Industry dummies
Garments Dummy = 1 if firm falls in this industry, 0 otherwise.
Hamna Ahmed and Naved Hamid
346
Textiles Dummy = 1 if firm falls in this industry, 0 otherwise.
Machinery and
equipment
Dummy = 1 if firm falls in this industry, 0 otherwise.
Chemicals Dummy = 1 if firm falls in this industry, 0 otherwise.
Electronics Dummy = 1 if firm falls in this industry, 0 otherwise.
Nonmetallic minerals Dummy = 1 if firm falls in this industry, 0 otherwise.
Leather and leather
products
Dummy = 1 if firm falls in this industry, 0 otherwise.
