“An Investigation of Firm Heterogeneity in the Constraints to
Development and Growth in Pakistan”

Sajjad MOGHAL and Wade D. PFAU1

Details of the corresponding author:
Wade D. Pfau, Associate Professor
National Graduate Institute for Policy Studies
7-22-1 Roppongi, Minato-ku
Tokyo-to 106-8677
Email: wpfau@grips.ac.jp
Phone: 03-6439-6225
Fax: 03-6439-6010

1

Sajjad Moghal was Deputy General Manager of the Policy and Planning Division, Small & Medium Enterprise
Development Authority in Lahore, Pakistan (sajjad_moghal@hotmail.com) at the time this paper was written
and is now serving as Project Management Specialist at USAID Pakistan Mission. Wade D. Pfau is an
Associate Professor of Economics at the National Graduate Institute for Policy Studies (GRIPS) in Tokyo, Japan(wpfau@grips.ac.jp). We are grateful to the World Bank and the Pakistan SMEDA for providing access to theInvestment Climate Survey of Pakistan. We are also thankful for comments provided by participants of the Asia
Consultative Conference on Creating Better Business Environments for Enterprise Development. Nonetheless,the views expressed in this study of those of the authors, and they do not represent SMEDA, the World Bank,USAID or the National Graduate Institute for Policy Studies.

1

Abstract
This study considers the importance of firm characteristics in explaining the degree ofbusiness constraints facing Pakistani firms in the Investment Climate Survey. We quantify
how firms with differing characteristics experience particular problems. After controlling forother factors, the largest differences in responses to business constraints occurs among firmsthat vary by manufacturing industry, and among firms operating under different ownership
structures or selling in different markets. In some cases, firm size and firm location also play
an important role. The age of the firm generally does not lead to significant differences.
These results are important, because they will guide policymakers to develop more specificapproaches to fostering the investment climate, which better account for the heterogeneity offirms.

Keywords: Pakistan, Investment Climate, Business Constraints
JEL No.: O53, L6, M0

2

1. Introduction
What is the key to a country’s economic development? This question has produced
great controversy and a wide variety of answers. In recent years, the answers haveincreasingly emphasized the microeconomic institutions of a country: is there a strong legal
system to promote property rights, is corruption under control, can financial institutions playtheir role as intermediaries between savers and investors, and so forth? In this new analyticalframework, macroeconomic stability is not sufficient for development. It is along these linesthat the most multilateral development institutions now place an increasing focus on
improving the business or investment climate. A country cannot be expected to grow andflourish if potential entrepreneurs see no incentive to taking risks and expanding theirbusinesses. Risk taking must provide the potential for rewards, but rewards can be almost
nonexistent without the appropriate microeconomic institutions.
In order to analyze the investment climate, the World Bank commissioned surveys for
53 countries. In the case of Pakistan, an Investment Climate Assessment (ICA) survey wasadministered in 2002 in conjunction with the Small and Medium Enterprise Development
Authority (SMEDA), Pakistan. This survey of 956 firms is the most extensive for Pakistan
and will be the subject of our analysis. It is not the only survey of Pakistani businesses
though, as more limited surveys were used to understand business constraints in World Bank
(2001a), SMEDA (2002), and Bari et al. (2002), among others.
Of course, the businesses of Pakistan are not homogenous units. They vary along a
number of important dimensions, including their size, location, exporter status, type of
production, age, and type of ownership. However, while previous studies have madeattempts to understand business constraints in Pakistan, they have not included a systematiceffort to understand the heterogeneity of Pakistani firms relating to these various constraints.
Many discussions of policy reform tend to imply a one-policy-fits-all approach. Some of3

these studies make initial attempts along these lines by tabulating their results based on firm
size or geographical region. But this is not sufficient to understand the differences inconstraints and we are often left to wonder what characteristic of the firm (its size or its
location) is driving the difference in firm responses.
Our goal in this paper is to provide a more systematic analysis of how thecharacteristics of a firm affect its responses to questions about various business constraints, inorder to contribute to the discussion of reform efficacy in Pakistan. We accomplish this byusing an ordered probit analysis. The reported degree of constraint facing a business is thedependent variable to be explained by a number of underlying firm characteristics, including
firm size, province, exporter status, type of firm production, firm age, and the type of firmownership. This regression analysis makes it possible to know whether firm size, forexample, leads to significantly different responses about firm constraints after controlling forthe other firm characteristics. By knowing this, we can gain more insight when interpretingthe cross-tabulations of business constraints by different firm characteristics. This will allow
for a more detailed analysis of Pakistan’s business or investment climate, and perhaps evenuncover further areas for reforms in the Pakistan economy.
As shared above, for the purpose of this paper, the Investment Climate Survey 2002
dataset has been analyzed and our analysis proceeds as follows.2 In Section 2, we provide
background about previous studies of the Pakistan business climate, as well as motivate how
the trend toward microeconomic institutional focus developed. Section 3 follows with adescription of the Pakistan ICA and summary statistics for the sample firms. Section 4
explains the methodology of the ordered probit model approach. Section 5 provides the2

In 2006, the World Bank and SMEDA began work on the Investment Climate Assessment II for Pakistan.
This survey is expected to be released in 2008, but it has not yet been cleared for use by private researchers.
Subsequent research will consider this survey as well. It will be interesting to study the ICA II, because
questions about business constraints are asked several times to check for consistency in the answers, and firms
are also asked to rank the biggest three constraints and the three most needed reforms.

4results, and Section 6 follows with conclusions and policy recommendations. Briefly, ourfindings suggest that a firm’s characteristics plays an important role in determining its
responses to different business constraints in Pakistan. Firms that differ by export status, by
the type of sub-manufacturing industry, and by firm ownership status, provide significantly
different responses about the degree of business constraints. Exporters enjoy better
conditions, as do firms in the sports goods, leather goods, and electronics industries.
Meanwhile, private limited companies face additional burdens than other types of firmownership structures. In some cases, firm size and firm location also play an important role.
Medium size firms generally face more difficult conditions, as do firms in Sindh or Punjab.
Finally, firm age does not generally play much role in determining firm responses.

2. Background
During the 1980s and 1990s, the World Bank (WB) and the International Monetary
Fund (IMF) designed the Structural Adjustment Program (SAP) to assist economic
development by providing credit for debt-ridden countries. Under World Bank and IMF
conditionality, the SAP dominated economic policy planning in many developing countries.
A typical SAP facility required the recipient country to restructure its economy in order toreduce deficits and yield financial resources required to pay debts. The prescribed
macroeconomic framework included "structural" reforms to deregulate the economy,liberalize trade and investment, and privatize state enterprises. These were coupled withshort-term stabilization measures, including cutbacks in government expenditures, increased
interest rates, and currency devaluation. The widespread failure of SAP in most of the low
and middle income countries to yield sustainable moderate growth, as discussed in WorldBank (2001b), prompted a paradigm shift even within the World Bank toward a broader
economic development approach. Policy makers realized that alongside deregulation, trade5liberalization, and fiscal discipline, microeconomic incentives are equally important to firm
development and to stimulate private sector growth.
As such, the World Bank has increasingly focused on microeconomic incentives inrecent years. James Wolfensohn, then president of the World Bank, developed the New
Development Framework in 1999. His approach de-emphasized macroeconomic issues andmoved the focus to fighting corruption, to creating an effective justice system, and topromoting a supervised financial system. There is only so much that macroeconomic
stability can provide if a country’s institutions are not designed to effectively facilitate
investment and growth.
The World Bank’s World Development Report 2005 describes the World Bank’sefforts to understand the investment climate in low and middle income countries. The reportanalyzes survey data from 26,000 firms in 53 developing countries, in order to examine therelationship between the investment climate and growth. These surveys are conducted withlocal partners in each country, in order to include local input for policy reforms. The purposeof these investment climate surveys is to identify areas for policy reform that can reduce theburden on business and encourage them to invest and expand, with the idea that such growth
will lessen poverty for everyone. The World Bank seeks to define how certain economic
policy measures have the ability to unleash the growth potential of a country or otherwise
restrain it from growing.
The World Bank, in collaboration with the Small and Medium Enterprise
Development Authority (SMEDA) of Pakistan, produced an investment climate assessment
for Pakistan in 2003. The World Bank (2003) concluded that Pakistan needs to focus on
microeconomic reforms to reduce business costs by providing better services in the areas of“power, telecom, tax administration, access to finance, and law and order” (p. iv). The WorldBank’s assessment focused on comparing various summary statistics from the survey to the6situation in other comparable countries, mainly China, Bangladesh, and India. More detailed
work was recently published as Dollar, Hallward-Driemeier, and Mengistae (2005). Table 1
compares the percentage of firms ranking a constraint as major or severe for these four
countries. Generally, Bangladesh faces a more severe situation than Pakistan, but Pakistan’s
firms have more complaints than those in China or India. While such analysis is important,
as a comparison to international benchmarks is needed to be able to quantify the severity ofproblems in Pakistan, there are still plenty of insights beyond the scope of the World Bank’s
assessment remaining to be learned from the survey results.
Table 1: Investment Climate Indicators in Four Countries(Percentage of Firms Ranking Constraint as Major or Very Severe)
CONSTRAINT

Pakistan

Bangladesh

China

Tax administration
47.0%
50.7%
26.7%
Tax rates
46.8%
35.8%
36.8%
Financing
40.8%
45.7%
22.3%
Economic policy uncertainty
40.4%
45.4%
32.9%
Corruption
40.3%
57.9%
27.3%
Electricity
39.3%
73.2%
29.7%
Crime, theft and disorder
21.4%
39.4%
20.0%
Labor regulations
15.8%
10.8%
20.7%
Skills & educ. of avail. Workers
13.0%
19.8%
30.7%
Source: For Pakistan, own calculations from Pakistan ICA. For others, World Bank (2004b).

India
26.4%
27.9%
19.2%
20.9%
37.4%
28.9%
15.6%
16.7%
12.5%

While the World Bank’s assessment is able to use the most comprehensive survey
available for Pakistani businesses, there have also been other analyses of the businesssituation. Of these, Bari et al. (2002) is the most thorough, though they rely on a more limited
survey of 54 firms to base their conclusions. These authors develop the notion of a “binding
constraint” as a way to target the problems most affecting firm growth and investment, noting
the need to focus on microeconomic as well as macroeconomic problems. They also do theirbest to obtain a good representation of firm sizes in several manufacturing and retail sectors.
The binding constraints they observe include issues related to financing, infrastructure,7

government regulation, human resources, market regulations, and macroeconomic
uncertainty.
In a separate study, World Bank (2001a) uses a larger survey of 500 firms to identify
the severity of constraints based on firm perceptions. Their two-tiered approach first
identifies the top ten problems experienced by firms in their efforts to grow, and then further
investigates seven of these constraints. The analysis is limited to the presentation ofsummary statistics based on enterprise perception. Nevertheless, the unique feature was thelarger representation of smaller size firms in the survey from the all major economic sectors,
including industry, trade, and services.
Finally, a key early paper that helped begin the debate on SME policy in Pakistan is
SMEDA (2002). They survey 333 firms in order to develop a set of policies for micro, small
and medium enterprises. They give special attention to the necessary legislation andadministrative steps for compliance. The distinctive contribution of this study is to identify
important issues related to labor welfare and taxation laws. The study further helps to clarify
the complications faced by smaller firms in their attempts to comply with these laws. The
study maintains an overall focus on three broad issues, which included labor laws, businesscredit or enterprise financing, and taxation.

3. Data Description
We will provide a more detailed analysis of business constraints in Pakistan, using theInvestment Climate Survey of Pakistan 2002. The data consists of 956 firms interviewed inPakistan by the Small and Medium Enterprise Development Authority of the Government ofPakistan in collaboration with the World Bank between May and November 2002. The firms
were sampled randomly from a sample frame drawn from the directories of registeredbusinesses published by each of the four provincial government labor departments. The
published directories were updated in 2000 and disaggregated in terms of employment and8industrial sub-sectors. This allows the survey sample to be fairly representative of industrial
activity in Pakistan’s twelve largest cities for seven manufacturing industries chosen in termsof their contribution to GDP. The ICA is the largest dataset available, and care was taken to
make it representative of Pakistan’s business enterprise population as described in Pakistan’s
Economic Census of 2001. Because of its size and scope, the dataset is rich enough to allow
an extensive look at the heterogeneity of firms, and how this heterogeneity contributes to firm
responses about business constraints.

Table 2: Description of Survey Data
Number of Firms
Percent of Firms
Firm Size
Micro
126
13.2%
Small
560
58.6%
Medium
141
14.7%
Large
129
13.5%
Province
Sindh
239
25.0%
NWFP
76
7.9%
Punjab580
60.7%
Baluchistan
61
6.4%
Exporter Status
No Exports
777
81.3%
Exports179
18.7%
Type of Production
Textiles342
35.8%
Garments
136
14.2%
Leather and leather products
40
4.2%
Food processing
151
15.8%
Electronics & electrical equipment
101
10.6%
Chemicals138
14.4%
Sports goods
46
4.8%
Other
2
0.2%
Firm Age
0-5 Years
96
10.0%
6-10 Years
285
29.8%
11-15 Years
228
23.8%
16 + Years
347
36.3%
Firm Ownership
Publicly listed company
32
3.3%
Private held, limited company
486
50.8%
Partnership
167
17.5%
Sole Proprietorship
255
26.7%
Other
16
1.7%
Source: Own calculations from Pakistan Investment Climate Assessment.

9

Table 2 provides summary statistics for the firm characteristics in the survey sample.
Firm size includes four categories based on the number of workers employed at the firm.3
Micro firms employ 1 to 9 workers, while small firms employ 10 to 49 workers, medium
firms employ 50 to 99 workers, and large firms have 100 or more workers. Micro firms
account for 13.2 percent of the sample. Meanwhile, small firms represent 58.6 percent of thetotal, medium firms another 14.7 percent, and large firms account for 13.5 percent. With
regard to Pakistan’s four provinces, Punjab accounts for 60.7 percent of the firms in thesurvey, while 25 percent are in Sindh, 7.9 percent in NWFP, and 6.4 percent in Balochistan.4
Meanwhile, 18.7 percent of the firms in the survey export at least some of their product.
Furthermore, the firms surveyed are involved in a variety of manufacturing industries.
These industries include textiles (35.8 percent), food processing (15.8 percent), chemicals(14.4 percent), garments (14.2 percent), electronics and electrical equipment (10.6 percent),
sporting goods (4.8 percent), leather and leather products (4.2 percent), and two other firmsthat were not classified. With regard to firm age, 10 percent of firms are between 0 and 5
years old, while 29.8 percent of firms are 6 to 10 years old, 23.8 percent of firms are 11 to 15
years old, and 36.3 percent of firms are at least 16 years old. Finally, the formal ownership
structure of the firm is also important. In this regard, the more formal firms, publicly listed or
privately held limited companies, together make up 54.1 percent of the surveyed firms. Sole
proprietorships and partnerships provide 44.2 percent of the sample, and other categories
represent another 1.7 percent.

3

These firm size definitions are based on the continuing discussions for the proposed SME Policy of Pakistan.
For details, please see SME Issues Paper and SME policy task force reports as available on the website
www.smepolicy.net.pk
4
The results of the Economic Census of 2005 also suggest similar geographic patterns of industrial
establishments, though we find that Sindh and Baluchistan are overrepresented. Punjab is home to six of themost industrialized cities and 68.4 percent of Pakistan’s 583,000 industrial establishments. Sindh, the home of
Pakistan’s largest industrial city Karachi, includes 13.9 percent of industrial establishments, while there are 16
percent in NWFP, and 1.4 percent in Baluchistan.

10

4. Methodology
Our goal is to understand the constraints facing Pakastani business. The businessconstraints in Pakistan will be considered along several different lines. Important among
these are the size of the firm, the location of the firm, whether the firm is an exporter, the typeof goods produced by the firm, the age of the firm, and the type of firm ownership. We
attempt to understand these constraints through a system of self-reporting in the Investment
Climate Assessment (ICA) of Pakistan. The ICA asked firms to rank seventeen different
business obstacles on a scale with five categories ranging from “No Obstacle” to “VerySevere Obstacle.” Table 3 shows how the 956 firms responded to each constraint. The list of
constraints is provided in descending order for the sum of the “major obstacle” and “verysevere obstacle” categories. We consider the results of the survey questions asking how
severely constraining are various possible impediments to Pakistani business. This discussion
will allow for a characterization of the problems most affecting business in Pakistan.
Table 3: Firm Responses to Business Obstacles
Constraints
None
Minor
Moderate
Tax administration
24.40%
11.20%
17.40%Tax rates
25.40%
9.40%
18.40%
Financing Costs (int. rates)
26.30%
13.10%
17.40%
Economic policy uncertainty
29.50%
11.20%
18.90%
Corruption
28.60%
12.00%
19.10%
Electricity
21.30%
20.10%
19.30%
Access to Financing (collateral)
29.60%
12.50%
19.60%
Macro-economic instability
30.40%
13.60%
21.60%
Customs & trade regul.
43.80%
14.10%
17.70%
Anti-competitive practices
37.20%
19.60%
21.80%
Crime, theft and disorder44.80%
17.40%
16.40%
Access to Land46.40%
16.80%
15.70%
Labor regulations
43.80%
17.40%
23.00%
Business permits
52.60%
17.30%
15.40%
Skills & educ. of avail. workers
48.30%
19.90%
18.90%
Transportation
46.40%
23.60%
19.90%
Telecommunications
53.90%
25.60%
12.90%
Source: Own calculations from Pakistan Investment Climate Assessment
Note: Constraints in the shaded part of the Table are "binding," as defined in Section 4.

Major
17.30%
15.30%
13.60%
14.20%
15.10%
16.60%
15.90%
14.60%
12.70%
8.70%
10.20%
10.10%
10.20%
8.00%
7.60%
6.50%
4.20%

Very Severe
29.70%
31.50%
29.60%
26.20%
25.20%
22.70%
22.40%
19.90%
11.70%
12.80%
11.20%
11.10%
5.70%
6.70%
5.30%
3.70%
3.50%

We employ the concept of “binding constraint” to identify those constraints which
produce the largest complaints from firms. Following the approach of Bari et al. (2002), we

11

use two criteria for determining a binding constraint: the median firm response must identify
the constraint as at least a “moderate obstacle,” and at least 30 percent of firms must identify
the constraint as a “major obstacle” or a “very severe obstacle.” Both criteria identify the
first eight constraints listed in Table 3 as binding, from “Tax Administration” to“Macroeconomic Instability.” At the cutoff point there is a large drop, as while 34.4 percent
of firms identify macroeconomic instability as a severe or major constraint, only 24.3 percent
of firms provide the same answer for customs and trade regulations. Binding constraints areof more interest, because these constraints suggest the areas where reform could produce themost benefit. It may be less effective to devote policy resources to areas where firms do notcomplain as loudly. We see that tax issues, financing issues, policy uncertainty, corruption,
electricity, and macroeconomic instability produce the largest concerns for firms. Customs
and trade regulations, anti-competitive practices, crime, land, labor and business regulations,the skills of the labor force, transportation, and telecommunications are not constraining firms
to as large of degree. In comparison, SMEDA (2006) identifies the business environment,
access to finance, human resource development, and support for technology as four of themost important areas for SME policy.
To understand the nature of the binding constraints, as well as the other constraints,
we wish to determine what characteristics of a firm lead it to respond in a particular way. For
example, it will be enlightening to know if small firms complain much more strongly thanlarge firms about the access to financing. The overwhelming benefit of our approach is that
we can control for other firm characteristics to make these conclusions. We will know that itis because firms are small that they answer in some particular way, and not because, forexample, small firms tend to manufacture particular goods or be located in particular regions,and it is these other factors that are driving the firm’s response. Such knowledge can guide12policymakers to design more appropriate policies responding to the specific needs ofPakistani firms.
An ordered probit model provides a natural approach for determining the significanceof particular firm characteristics in answering about the degree of a constraint. Our dependent
variable, the measure of constraint severity, includes five ordered categories. Ordinary leastsquares is not appropriate because there is no reason to believe that the differences between
categories will be equal. We cannot observe the true severity of a constraint, which we callvariable y*. Each of the ranking categories refers to a range of actual severity. As theconstraint grows for a firm, the constraint will reach a threshold and move to the next higher
category. An ordered probit model provides a way to model this phenomenon. We seek toestimate:

0, if y*  1
*
1, if 1  y   2

y*     X   , and we observe y, where y  2, if  2  y *   3
*3, if  3  y   4
4, if  4  y*
(1)

In the above expression, y* is the unobserved true underlying severity of theconstraint, X is a matrix of explanatory variables, y is the observed constraint ranking, and thes are the unknown threshold values that cause firms to decide their answer for y. We
consider these constraints as a linear function of firm characteristics X, which include size,
location, export status, type of production, firm age, type of firm ownership. The ordered
probit approach uses maximum likelihood to determine the role of the explanatory variables.
The value of using this approach is that it allows us to examine whether a particular firm
characteristic results in different answers about the severity of a constraint, after controlling
for the effects of other explanatory variables.

13

5. Analysis of the Constraints on Business
The framework used in this paper explains the business constraints for firms inPakistan along six specific firm characteristics, in order to provide the basis for a deeper
policy discussion. We identify those characteristics of firms that produce statisticallysignificant differences in their answers about the severity of business constraints. The mainemphasis will be on binding constraints, though the discussion also includes limited analysis
of other constraints. Table 4 provides the results of the ordered probit regressions. Tables 5through 10 follow by showing the percentage of firms identifying a constraint as “Major” or“Very Severe,” disaggregated by a particular firm characteristic. These tables incorporate
information from the ordered probit regression to identify which constraints produce
statistically significant differences in the responses of firms disaggregated by the particular
category. These tables also identify the binding constraints as they apply to each of the firm
characteristics.
5.1 Firm Size
The relationship between firm size and business constraints has been studied in theliterature. Bari et al. (2002) indicates that SMEs have generally faced greater challenges thantheir larger counterparts in Pakistan’s recent history, on account of the heavily regulatedindustrialization policy. Large firms held advantages because they were in better positions to
obtain limited government licenses and investment incentives. Large firms also had greater
access to finance, because credit and interest rate controls left banks with little reason to loan
to the riskier small firms. Fixed costs in dealing with government regulators andadministrators also worked to put a greater burden on smaller firms.
After controlling for other firm characteristics, we find evidence that firm size mattersat the 5 percent level of significance for the degree of constraint facing firms with regard to
the binding constraints of tax issues, electricity, and access to financing (see Table 5).

14

Table 4: Ordered--Probit of Constraints on Firm Characteristics
Binding Constraints
Tax
Administr
ation

Tax rates

Non-Binding Constraints
Economic
Cost ofpolicyFinancing
uncertainty

Corruption

Electricity

Access to
Financing(e.g.
collateral)

Macroeconomic
instability

Customs
and traderegulations

Anticompetitive
practices

Crime,
theft anddisorderAccess to
Land

Labor
regulation

Business
licensingandoperatingpermits

Skills andeducationofavailable
workers

Transport
ation

Telecomm
unications

Firm Size (Omitted Condition is "Large Firm")
Overall p-value
Micro Firm

0.0262*-0.3593*0.0000**-0.6885**0.7003-0.0073

0.0596-0.1671

0.5249-0.1801

0.0159*-0.2606

0.0265*0.10010.2651-0.16410.0641-0.5220**0.1105-0.00990.0013**-0.4576**0.0076**
0.4649**0.0044**-0.5386**0.45760.04060.4582-0.18130.5511-0.06620.0281*-0.4794**

Small Firm

-0.0505-0.2306

0.1007-0.2241-0.0724-0.09630.3091*-0.1336-0.3207**-0.1132-0.4399**

0.4326**-0.2289

0.1661-0.08210.0009-0.2889*

Medium Firm

0.07790.12930.0699-0.3693**0.03240.18540.2472-0.2722*-0.0934-0.2969*-0.5084**0.3659*-0.04110.08260.0497-0.1498-0.1464

Province (Omitted Condtion is "Sindh")
Overall p-value
NWFP

0.2201
0.0487

0.0614-0.0337

0.0488*-0.4426**0.32550.25070.5349-0.0295

0.0009**0.12620.0000**-0.7807**0.7189-0.0359

0.0046**0.18210.25240.29330.0051**-0.20710.0000**-1.1439**0.0606-0.3575*

0.0044**-0.5160**

0.0031**-0.5957**

0.0847-0.1399

0.4223-0.0882

Punjab

0.0225-0.0557-0.0772

0.03860.0145-0.1789-0.0516-0.0846-0.2300*

0.0398-0.1398-0.6174**-0.0069-0.1662-0.0291-0.1249-0.1184

Baluchistan-0.2898-0.4333**-0.0365

0.1974-0.2112-0.5373**-0.2206-0.1544-0.3041-0.0287

0.3583*-0.3523*-0.2565

0.108

0.13

0.2355-0.25910.8351-0.02240.0070**-0.2945**0.5582-0.06110.0019**-0.3331**0.2594-0.1205

0.5369-0.06880.0148*-0.2694*

0.2475-0.1299

0.58440.06

0.0045**-0.3178**

0.0310*-0.2491*

0.76970.0316

0.0662-0.20500.2324-0.1349

Exporter Status (Omitted Condition is "Non-exporter")
Overall p-value
Exporter

0.0006**-0.3774**

0.0040**-0.3153**0.0000**-0.4774**

Type of Production (Omitted Condition is "Textiles")Overall p-value

0.0000**0.0000**0.0000**0.0000**0.0000**0.0051**0.0000**0.0000**0.0000**0.0000**0.0000**0.69970.0000**0.0009**0.0361*0.0125*0.0018**Garments
Leather-0.1331-1.4174**-0.1706-1.2257**-0.0739-0.8074**

0.0382-0.9682**-0.1629-0.8473**-0.1132-0.3121-0.1243-0.4312*-0.01-0.554**0.0468-0.7407**0.0763-0.5382*

0.0153-0.6656**-0.0566-0.0068-0.0847-0.6226**-0.1695-0.5173*

0.00430.17090.0196-0.2764-0.2289-0.6800**

Food Proc.

0.2715*0.16780.05970.037

0.20510.173

0.1119-0.0571

0.05210.2609*0.0785-0.0058

0.0786-0.1825-0.3657**-0.1675

0.0613

Electronics-0.2885*-0.6186**-0.2631*-0.3459**-0.1074-0.0337-0.1637-0.2516-0.19420.09550.08970.1353-0.3690**-0.1598

0.04970.0402

0.074

Chemicals-0.0743-0.0585-0.0352-0.0510.0175-0.064-0.0073-0.02170.11970.16840.04090.06660.17630.0056

0.0483-0.1549

0.0413

Sports Goods-2.0439**-1.4757**-1.4185**-1.3818**-1.7798**-0.6394**-1.1207**-1.108**-1.0756**-1.8205**-2.1028**-0.2388-1.4861**-1.1451**-0.1175-0.7372**-0.6702**

Firm Age (Omitted Condition is "0-5 Yr.")
Overall p-value
6-10 Yr.

0.0041**0.3014*0.47880.072

0.45490.12760.28750.22810.74890.11740.05880.10180.4084-0.0057

0.0030**0.4813**0.10800.15710.13900.144

0.26050.219

0.0751-0.22400.0636
0.05170.29220.23930.08210.00920.821-0.1018

0.39970.191911-15 Yr.

0.4611**0.18490.21580.13750.10590.01890.148

0.3036*0.3302*0.2778*0.05480.02050.26950.24140.1-0.1320.1445

Over 15 Yr.

0.4372**0.14890.16780.22090.142

0.2444

0.09610.3908**0.20530.26000.1008-0.04110.04530.1495-0.1449-0.10140.2322

Firm Ownership (Omitted Condition is "Sole Proprietorship")Overall p-value
Publicly Listed Co.
Private limited Co.

0.0012**-0.0170.2956**0.0238*-0.28470.2125*0.0000**0.3654*0.4876**

0.0266*-0.1790.12210.0007**-0.03940.1912*

0.7831-0.10850.04520.0000**0.139
0.4302**0.0063**0.17680.2292*0.0003**0.19180.3579**0.0001**0.05740.3391**0.0107*-0.00710.2018*0.0357*0.177
0.2521*0.0056**0.302
0.3472**0.0241*
0.5261*0.3102**0.0419*0.4970*0.2655**0.06420.5923**0.2479*0.10990.3392
0.0914

Partnership-0.0556

0.02610.2521*-0.118-0.2479*

0.06350.1727-0.0694-0.0316-0.1128-0.15890.0062

0.21800.155

0.2579*0.1486

0.2769*Other-0.1323-0.4054-0.37930.64460.0254-0.188-0.1401

0.5688*0.11210.47500.10430.2772

0.09510.40020.34010.468

0.2885

953

954

953

954

953

954

953

953

948

954

953

953

954

952

953

953

952

Observations

Note: * significant at 5%; ** significant at 1%

15

For nonbinding constraints, firm size matters for crime issues, access to land, labor
regulations, and telecommunications. Interestingly, some issues do not produce
answers that differ in a statistically significant way by firm size, including financing
costs, economic policy uncertainty, corruption, macroeconomic stability, customs andtrade regulations, anticompetitive practices, business licensing and operating permits,skills and education of the labor force, and transportation. But regarding tax issues
and electricity, medium firms express the strongest complaints, followed by large
firms, small firms, and micro firms, once we control for other factors. In fact, microfirms generally have fewer complaints, as their only binding constraints are financing
costs and economic policy uncertainty. Meanwhile, for access to finance, small firms
complain most, followed by medium, micro, and large firms.

Table 5 - Percentage of Firms Identifying Constraint as "Major" or "Very Severe"by Firm Size
Micro
Small
MediumLarge
34.9%
Tax administration
47.7%
53.2%
49.6%
29.4%
Tax rates
45.9%
59.6%
54.3%
Financing Costs (int. rates)
33.3%
45.5%
41.8%
44.2%
Economic policy uncertainty
41.3%
39.2%
38.3%
46.5%
Corruption
33.3%
39.4%
45.4%
45.0%
33.3%
Electricity
38.9%
48.2%
38.0%
33.3%
31.8%
Access to Financing (collateral)
40.7%
39.0%
Macro-economic instability
27.8%
33.3%
34.0%
45.7%
Customs & trade regulations
13.5%
22.4%
30.5%
36.4%
Anti-competitive practices
26.2%
21.5%
12.1%
26.4%
17.5%
19.7%
19.9%
Crime, theft and disorder
33.3%
16.7%
22.0%
23.4%
18.6%
Access to Land
7.9%
14.3%
22.7%
22.5%
Labor regulations
Business permits
11.1%
15.4%
16.3%
13.2%
Skills & educ. of avail. workers
9.5%
12.2%
20.6%
11.6%
Transportation
10.3%
10.6%
7.1%
10.9%
6.3%
6.8%
6.4%
14.0%
Telecommunications
Note: Own calculations from Pakistan ICA. The constraint name is in boldface if the ordered probit
analysis identifies statistically significant differences at the 5 percent level in the answers of firms
varying by the firm characteristic. The percentage is in boldface if the constraint is binding for the
sub-category, where binding constraints are identified as those with a median response indicating theconstraint is at least "Moderate", and at least 30 percent of firms identify the constraint as "Major" or"Very Severe."16

First consider the issues of tax administration and tax rates. Micro firms
complain about these issues much less than their larger counterparts. In fact, tax
issues are not a binding constraint for micro firms. Regarding tax administration, theresponses of small and medium firms are not statistically distinguishable from theresponses of large firms. With regard to tax rates, we find evidence that micro andsmall firms do complain to a lesser degree in a statistically significant way, than do
medium or large firms. We can observe some justification for this through further
exploration of the data along three parameters: the amount of entrepreneurial timespent in dealing with tax regulators, average fines paid during a year, and average
bribes paid to the regulators. We find evidence in the ICA that larger firms must
devote significantly more resources in absolute terms for dealing with taxation issues,
while small firms are most burdened as a percentage of sales. Micro firms can moreeasily escape the targets of the government tax authorities.
Access to financing is an important issue, as it is seventh in the list of binding
constraints, and here it is the case that large firms complain least and small firms
complain most. Access to financing is only a binding constraint for small andmedium firms. In a topic deserving much greater attention, we indeed find evidence
that firm size has a direct bearing on a firm’s ability to get financing from formal
channels; larger firms enjoy easier and greater access to formal financing than theirsmaller counterparts in the ICA. It is puzzling why micro firms do not voice loudcomplaints despite having the least access to formal financing though. For example,
more than half of large firms had at least one loan from a bank at the time of thesurvey, while this is true for only 2.3 percent of micro firms. There are several
possible explanations. Micro firms believe that they will not be entertained by thefinancial institutions, and hence they are discouraged to apply in the first place and17then effectively find other sources of financing. Also, micro firms assign low
probability to their survival in a highly uncertain economic policy environment andavoid taking any additional liabilities in the absence of effective bankruptcy
procedures.
There are four other constraints with statistically significant differing answers
regarding firm size that are not binding in nature. These are related to crime, accessto land, labor regulations, and telecommunications. The most likely targets of theftand crimes are the large enterprises. Limited financial resources have translated into
the larger complaints by the micro, small and medium enterprises about the access toland. Unlike the usual perception that labor regulations are a real source of trouble forthe smaller firms, see SMEDA (2002) and SMEDA (2004), our analysis suggests
otherwise, as the bigger a firm is, the more it tends to complain about labor
regulations.
Revisiting the discussion above, our analysis suggests that conditions for the
SME manufacturing sector in Pakistan can improve if reform efforts focus on: a)
improving both tax rates and tax administration to respond better to SMEs’ uniqueconditions, b) ensuring the supply of electricity from the national grid, and c)
deepening the formal financing to reach out to smaller firms. To make the businessenvironment even more conducive for micro and small manufacturers, giving accessto land should be considered. However, any intervention in other areas is likely
benefit larger enterprises more than the SMEs.
5.2 Firm Location
Table 6 provides evidence that, after controlling for other firm characteristics,
the province in which a firm is located affects its business constraints. Firms in Sindh
and NWFP tend to voice louder complaints than those in Punjab and Balochistan.

18

The subset of binding constraints in which firm location plays an important role inproducing different responses, with at least 5 percent significance, include the cost offinancing, electricity, and access to financing. With regard to the costs of financing
and access to financing, the complaints are loudest in Sindh, though the responses in
Punjab, Balochistan, and Sindh do not differ significantly from one another.
However, financing issues are an area in which complaints from NWFP aresignificantly lower, once we control for other firm characteristics. As for electricity,
the degree of complaints is significantly less in Balochistan than the other regions.
NWFP experiences the biggest problems with electricity, followed by Sindh andPunjab. We find justification for this in the survey, as the median percentage ofmerchandise value lost due to electricity problems follows the same ordering. In
NWFP, the median firm estimates that it loses 5 percent of its merchandise on accountof electricity problems. Because different regions have different experiences withelectricity, there are grounds for a deeper analysis of the arrangement of electricity
production and supply in the four regions.
Table 6 - Percentage of Firms Identifying Constraint as "Major" or "Very Severe"
by Region
Sindh
NWFP
Punjab
Balochistan
Tax administration
54.4%
56.6%
43.6%
39.3%
Tax rates
54.8%
59.2%
42.7%
39.3%
Financing Costs (int. rates)
50.6%
40.8%
40.3%
44.3%
Economic policy uncertainty
39.7%
56.6%
38.4%
41.0%
Corruption
41.4%
47.4%
39.4%
34.4%
13.1%
Electricity
43.5%
52.6%
38.8%
23.7%
Access to Financing (collateral)
46.4%
36.9%
37.7%
Macro-economic instability
39.3%
40.8%
31.5%
34.4%
28.5%
20.9%
21.3%
Customs & trade regulations
39.5%
Anti-competitive practices
13.4%
23.0%
14.8%
39.5%
23.8%
15.8%
18.7%
Crime, theft and disorder
42.6%
38.1%
3.9%
16.3%
21.3%
Access to Land
Labor regulations
16.7%
10.5%
16.6%
11.5%
19.7%
5.3%
13.0%
23.0%
Business permits
12.1%
9.2%
12.6%
24.6%
Skills & educ. of avail. workers
Transportation
10.0%
11.8%
9.0%
18.0%
Telecommunications
7.5%
6.6%
7.6%
9.8%
Note: The Note in Table 5 explains how to interpret this table.

19

The regional location of firms also produces statistical significance for somenon-binding constraints as well. For instance, customs and trade regulations are lessof a problem in Balochistan and Punjab than in NWFP and Sindh. Meanwhile, accessto land is a bigger problem in Sindh than in other regions. This constraint points topossible opportunities for substantially improving the investment climate by
establishing new industrial zones in Sindh. Complaints about access to land areparticularly low in NWFP once we control for other factors. As for the issues ofcrime, business permits, and worker skills, Balochistan experiences the biggest
problems, followed by Sindh, Punjab, and NWFP.
5.3 Access to export markets
Exporting firms overwhelmingly have fewer complaints than firms serving
only the domestic market, as shown in Table 7. At the 5 percent level of significance,
our analysis regarding market access has confirmed significantly lower complaints forexporters with five of the eight binding constraints. For the other constraints,
exporters complain less, but not significantly less. In general, exporters complain lesswith regard to tax issues, financing issues, and experiences with corruption. In fact,
the only constraint identified as binding by exporting firms in the survey is electricity.
As for nonbinding constraints, exporters complain significantly less about anticompetitive practices, labor regulations, and business permits.
For practical reasons, exporting firms can complain less because they enjoy
special incentive packages in areas such as taxation, financing, and other regulations.5
Briefly, exporting firms are not required to pay sales tax (VAT), and income tax isgoverned by a presumptive tax regime, which allows exporters to settle their income

5

For details on incentives, please visit www.tdap.gov.pk

20

tax liability by paying tax at a rate ranging between 0.75 percent and 1.25 percent ofsales. This arrangement takes away both of the top ranking constraints for exporters,
and it allows them to internalize the costs of taxation as a fixed operating cost.
Table 7 - Percentage of Firms Identifying Constraint
as "Major" or "Very Severe"by Market Access
Non- Exporters
Exporters
29.2%
Tax administration
51.2%
30.3%
Tax rates
50.6%
25.8%
Financing Costs (int. rates)
47.2%
Economic policy uncertainty
28.1%
43.2%
27.0%
Corruption
43.3%
Electricity
41.4%
30.9%
21.3%
Access to Financing (collateral)
42.1%
Macro-economic instability
23.0%
37.0%
Customs & trade regulations
25.5%
19.1%
23.1%
14.0%
Anti-competitive practices
Crime, theft and disorder
22.7%
15.2%
Access to Land
22.0%
16.9%
17.0%
10.7%
Labor regulations
16.1%
8.4%
Business permits
Skills & educ. of avail. workers
13.5%
10.7%
Transportation
11.0%
6.2%
Note: The Note in Table 5 explains how to interpret this table.

The arrangement for financing is also unique for exporters. The central bankof Pakistan allows exporters to have access to an export refinancing fund, available
through all commercial banking channels without a requirement of furnishing any
physical collateral. Additionally, the export refinancing rates are pegged to theaverage six-month Treasury bill rates plus a certain percentage for covering
operational costs. This arrangement has allowed exporters to enjoy increased access tofinancing at the lowest possible market interest rates. There are some limitations,however, because commercial banks can occasionally demand additional collateral forriskier clients. Corruption and uncertainty about regulations and policy is also reduced
because of lessened contact between exporters and regulators. In general, our analysis
confirms the effectiveness of said incentives resulting in relatively better scores fromexporters against those constraints.

21

5.4 Manufacturing sub-sector
Does the type of product a firm produces matter for its well-being in the
Pakistani business environment? Are some industries able to offer better investment
opportunities than others? The answer to these questions is yes, as shown in Table 8.
After controlling for other factors, the sub-manufacturing industry of the firm is an
important determinant of its constraints. In fact, overall responses are different at the
sub-manufacturing level for all of the constraints except for access to land. Amongtextiles, garments, leather goods, food processing, electronics, chemicals, and sports
goods, business conditions in Pakistan tend to most favor the sports goods industry,followed by leather manufacturers and electronics manufacturers. To be precise, thesports goods and leather goods industries do not experience any binding constraints.
Meanwhile, the food processing industry complains most loudly, though the responses
from textiles, garments, and chemicals are also relatively close.
Table 8 - Percentage of Firms Identifying Constraint as "Major" or "Very Severe"by Industry
TextilesGarments
Tax administration
51.2%
49.3%
Tax rates
53.5%
50.7%
Financing Costs (int. rates)
47.7%
41.9%
Economic policy uncertainty
43.9%
41.9%
Corruption
43.3%
35.3%
Electricity
42.4%
33.8%
Access to Financing (collateral)
42.7%
33.8%
Macro-economic instability
38.9%
38.2%
22.8%
30.9%
Customs & trade regulations
16.4%
18.4%
Anti-competitive practices
20.5%
18.4%
Crime, theft and disorder
Access to Land
26.3%
20.6%
14.9%
16.2%
Labor regulations
17.0%
14.0%
Business permits
15.2%
14.0%
Skills & education of avail. Workers
10.8%
10.3%
Transportation
7.3%
5.1%
Telecommunications
Note: The Note in Table 5 explains how to interpret this table.

Leather
7.5%
7.5%
10.0%
15.0%
10.0%
17.5%
17.5%
10.0%
7.5%
12.5%
7.5%
0.0%
5.0%
7.5%
12.5%
5.0%
2.5%

22

Food
Processing
62.9%
62.3%
54.3%
51.7%
52.3%
53.6%
47.0%
39.7%
30.5%
31.1%
25.2%
21.9%
21.2%
15.9%
7.3%
11.9%
8.6%

Electronics
38.6%
25.7%
37.6%
32.7%
39.6%
37.6%
36.6%
26.7%
19.8%
30.7%
24.8%
19.8%
8.9%
11.9%
12.9%
8.9%
11.9%

Chemicals
50.0%
51.4%
48.6%
42.8%
46.4%
37.7%
40.6%
37.7%
30.4%
28.3%
30.4%
18.1%
25.4%
16.7%
15.9%
11.6%
10.9%

Sports
goods
2.2%
2.2%
2.2%
4.3%
2.2%
15.2%
4.3%
0.0%
2.2%
2.2%
0.0%
10.9%
0.0%
2.2%
4.3%
0.0%
0.0%

Given these results, the industrial sectors can be classified in two groups basedon their relative perceptions about the business environment. The first group
comprises sports goods, leather goods, and electronics. While sports goods andleather goods are well ahead, the case of electronics is more split, since they are betteroff than the textiles, garments, chemicals and food processing industries, but only forthe first four binding constraints, from tax administration to economic policy
uncertainty. For the rest of the binding constraints, from corruption to macroeconomic
instability, their experience is no different.
The second group includes textiles, garments, chemicals, and food processing.
It is interesting that textile and garment manufacturers voice loud complaints.
SMEDA (2005) and the World Bank (2004a) predict declining returns for the textile
and garment industries in Pakistan, with regard to the abolition of textile quotas andincreased competition from other regional players, such as India, Bangladesh, andChina. Food processing firms voice the loudest complaints, though tax administrationis the only area which has any statistical significance for this sector, besides
anticompetitive practices in the list of nonbinding constraints. On the other hand, in
terms of the availability of skilled labor, food processing is the only industry whichenjoys better conditions.
The survey results identify issues which have direct bearing on the industrial
policy of Pakistan. The results imply potential opportunities for improving investment
conditions substantially for the textiles, garments, chemicals and food processing
industries by placing them at the core of possible future industrial policy. Given the
fresh investment by the textile and the garment sectors to the tune of USD 4 billion, it
is all the more important to understand reasons for the differences at the submanufacturing level for evolving a more conducive business environment.

23

5.6 Firm Age
It is interesting that firm age is not an important factor for determining how
firms view potential business constraints, once we control for other factors (see Table
9). The only two constraints with differential responses are tax administration andmacroeconomic instability. With regard to tax administration, the largest constraints
are felt by firms between 11 and 15 years old, while the young firms are least affectedagain. As for macroeconomic stability, the youngest firms are least affected;
macroeconomic stability is not a binding constraint for firms between 0 and 5 years
old. The biggest complaints come from firms between 6 and 10 years old.
Table 9 - Percentage of Firms Identifying Constraint as "Major" or "Very Severe"by Firm Age
0-5 Years 6-10 Years 11-15 Years
Over 15 YearsTax administration
42.7%
48.4%
50.9%
44.7%
Tax rates
43.8%
49.1%
46.0%
46.4%
Financing Costs (int. rates)
37.5%
46.3%
45.1%
40.9%
Economic policy uncertainty
39.6%
42.5%
39.4%
39.5%
Corruption
36.5%
40.0%
41.2%
40.9%
Electricity
38.5%
36.5%
36.3%
44.1%
Access to Financing (collateral)
33.3%
38.6%
40.7%
37.8%
26.0%
Macro-economic instability
38.9%
34.1%
33.1%
Customs & trade regulations
18.8%
22.8%
27.4%
25.1%
Anti-competitive practices
17.7%
18.2%
25.7%
22.2%
Crime, theft and disorder
15.6%
23.9%
22.6%
19.9%
Access to Land
19.8%
15.8%
23.5%
24.2%
Labor regulations
12.5%
14.0%
18.6%
16.4%
Business permits
10.4%
15.8%
15.0%
14.7%
Skills & educ. of avail. workers
13.5%
14.0%
17.3%
9.2%
Transportation
14.6%
8.8%
9.3%
10.4%
Telecommunications
8.3%
8.1%
7.1%
7.5%
Note: The Note in Table 5 explains how to interpret this table.

As for why young firms complain the least, the answer may be related tosurvey bias in the ICA sample. As an illustration of this bias, a sample of 279
manufacturing firms from Directories of Labour Year Book 2000, Karachi –Government of Sindh, were contacted one year after publication, and it was
discovered that some 85 businesses were either closed or not traceable. This suggests
a degree of severity in business conditions for new entrants that cannot be picked up

24

entirely in the sample due to the lag between obtaining sources for choosing thesample and actually interviewing the selected firms.
5.7 Ownership Structure
Previous analysis, such as SMEDA (2002), indicates that ownership structure
does matter for the development and the growth of a firm. Ideally, more formalized
structures should lead to better business services delivery from the business support
institutions and should result in better business conditions for firms. This is not the
only possibility, however, as Osama (2004) suggests that corporatization provides noadditional advantages for taxes, access to business support services, or financing.
Instead, a limited liability structure is more expensive on account of tax rates andfixed operational costs associated with additional paper work.
Table 10 - Percentage of Firms Identifying Constraint as "Major" or "Very Severe"by Firm Ownership
Publicly
Privately
held limited
held limited
liability
liability
Tax administration
40.6%
57.6%
Tax rates
40.6%
57.4%
Financing Costs (int. rates)
34.4%
52.9%
Economic policy uncertainty
34.4%
44.2%
34.4%
Corruption
48.4%
Electricity
40.6%
42.4%
21.9%
Access to Financing (collateral)
45.9%
Macro-economic instability
40.6%
40.1%
28.1%
Customs & trade regulations
31.9%
21.9%
25.3%
Anti-competitive practices
21.9%
27.2%
Crime, theft and disorder
Access to Land
18.8%
25.7%
21.9%
18.3%
Labor regulations
12.5%
16.3%
Business permits
12.5%
15.0%
Skills & educ. of avail. workers
15.6%
12.3%
Transportation
Telecommunications
15.6%
8.8%
Note: The Note in Table 5 explains how to interpret this table.

Partnership
29.9%
33.5%
34.1%
26.9%
24.0%
38.9%
31.7%
25.1%
15.0%
10.2%
14.4%
13.8%
15.0%
12.0%
11.4%
5.4%
6.0%

Sole
Proprietorship
39.1%
36.4%
33.2%
41.1%
36.8%
34.0%
30.8%
27.7%
15.0%
20.6%
14.6%
17.0%
11.1%
13.4%
9.9%
7.5%
5.5%

The survey shows that firm ownership structure is very important indetermining the degree of constraint reported by businesses. Table 10 shows that25

ownership is statistically significant for all binding constraints except for electricity.
Private limited companies report the largest complaints for all of the statisticallysignificant binding constraints. Private limited companies and sole proprietors are
only comparable for economic policy uncertainty and electricity. On the other hand,publicly listed companies have lesser complaints than the sole proprietary concerns
for most of the binding constraints. In cases where publicly listed companies claim ahigher degree of binding constraint, which include cost of financing, access to finance,and macroeconomic instability, the results are not statistically significant. Firmownership continues to play a statistically significant role in explaining the responses
to seven of the nine nonbinding constraints. Again, in these cases, the complaints ofprivate limited companies are the largest by a statistically significant degree. The
complaints of sole proprietorships, publicly listed companies, and partnerships follow,
but are generally not distinguishable from one another, except for the case ofworkforce skills, where sole proprietorships complain significantly less.
The survey data confirms the fact that privately held companies spend moredays dealing with regulators and pay more to government regulators in terms of finesand bribes. Being a corporate entity in Pakistan does not offer any incentives in termsof dealing with tax authorities, qualifying for better tax rates, negotiating lower
interest rates or better access to finance, dealing with corruption, or fighting
macroeconomic instability. Sole proprietary concerns can more easily escape from
regulatory oversight without losing any advantages in terms of access to businessservices or resources. This has important implications for developing the formal
economy of Pakistan, and not letting firms slip into the informal economy. The StateBank of Pakistan (2001) estimates that the informal economy was close to 32 percentof the total between 1996 and 2000. The magnitude of the informal economy makes26

it difficult for the government to adequately plan and provide effective businessservices. As we understand, it has its roots in ownership structure of the firms and any
effort to improve conditions for privately held firms will help to improve theinvestment climate.

6. Conclusions and Policy Recommendations
This study confirms that a one-size-fits-all policy is not appropriate for
improving the conditions of Pakistan’s manufacturing firms. A number of different
firm characteristics are found to play important roles in determining businessconstraints. First, while existing research, such as SMEDA (2002) and SMEDA(2004), discusses firm growth vis-à-vis firm size, it does not recognize a need for
different mechanical processes based on firm size. The analysis of responses in thisresearch sketches a different picture. While confirming heterogeneity with regard to
the aforementioned constraints, the results suggest that smaller firms are better off inquantitative terms. The efforts of the smaller firms and micro firms in particular are
devoted in escaping regulatory burden, using bribes and gifts to regulators as a tool.
Large firms tend to use similar tools for reducing their official tax liabilities andremain within the regulatory environment. This difference in approach to dealing withregulatory burden requires a different policy treatment for ironing out the variations offirm size in the regulatory environment. This would also require the development ofdifferent mechanical processes based on firm size. Access to finance comes out as the
top ranking constraint for the small firms, where the difference is both wide andsignificant. Using Non-Bank Financial Institutions (NBFI) as a channel for small
firms would greatly improve their condition (please see Table 11 for a summary ofpolicy recommendations).

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Table 11 – Policy Analysis of Firm Conditions vis-à-vis Constraints
Analysis/ Challenges/ Policy Focal Points
Reducing interface between tax regulators and firms will reduce compliance costs
for all but micro sized firms
Only a responsive tax regime for smaller size firms (micro and small) can improvebusiness conditions – analysis confirmed that smaller firms end up paying more(as a percentage of sales) o avoid interface with tax authorities
Access to finance is a binding constraint for small size firms – survey results show
Firm Sizethat Non-Bank Financial Institutions are more effective than the commercial
banks
Increasing access to land can significantly improve the business climate for SMEs
Labor regulations are not a constraint for SMEs, reducing interface of labor
regulators is desired more by large firms
Firms in Sindh & NWFP tend to voice the loudest complaints
Cost of financing, electricity, and access to financing and industrial land are the
key areas for improvement in Sindh
Regional
Location
In NWFP major complaints are about economic policy uncertainty, electricity
supply and taxation
The major concern in Balochistan is the prevailing law and order situation
Non-exporters generally feel deprived
The incentive regime for exporters is effective resulting in fewer complaints
Market Access
The difference in the conditions of non-exporting and exporting firms are stark(Local &In order to avoid another divide in the economy, the incentive structure must be
Foreign)counterbalanced through other business support mechanisms for non-exportingfirms
The business or investment conditions across industries are significantly different
Sports goods, leather goods and electronics industries enjoy relatively better
investment conditions. Indeed, the first two do not experience binding constraints
Returns are declining in textiles, garments and chemical industries – due to fierce
Subforeign competition
Manufacturing
Sector
The food processing industry produces the most complaints, particularly about tax
administration and anti-competitive practices
Industrial and investment policies must carefully look into the incentives fordifferent industries
Analysis does not confirm any particular advantage related to the age of the firm,
except that old firms are more exposed to taxation-related problems
Firm Age
It is reasonable to conclude that the existing business climate does not encourage
new start-ups.
Policy Area

Ownership
Structure

Cross Cutting
ThemesPrivately held limited liability companies face large compliance costs
There is no added advantage to be a corporate entity in terms of taxation, finance,or in accessing business services or resources
Sole proprietary firms do not show any disadvantage or advantage over publicly
held companies or partnerships but are definitely better off than privately held
limited liability companies
There are constraints that are significant for many types of firms, such as
electricity supply from public grid, macroeconomic stability, and law and order
A more reliable power supply from public grid has the largest potential to improve
growth conditions across the board
Stabilizing the shifting policy regime would further strengthen the confidence ofinvestors
An improved law and order situation would greatly enhance firms' ability to growand plan for long-term investments

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Additionally, certain regional locations in Pakistan are posing an extra burden
on firms due to the lack of necessary infrastructure such as electricity and industrial
land, which becomes binding constraints to their growth. Most of the significantly
differing responses, though, come from the list of non-binding constraints. An
appropriate response to remove these barriers would include that the government
yield modest resources in terms of setting up new industrial parks with adequate
infrastructural support.
Meanwhile, exporting firms face only a few binding constraints. The
difference in the condition of non-exporters and exporters are stark and significant,and incentives for exporters with respect to most of the regulations are creating
another divide among industrial enterprises. While the incentive regime for exporters
is effective and results in fewer complaints, it needs to be counterbalanced with abusiness support mechanism for non-exporters to smooth differences.
Furthermore, there are definitely some industries which enjoy relatively better
regulatory environments than others. Sports and leather goods industries complain
least. The specific conditions surrounding these industries could give clues for making
life better for others. The results in this respect also pose doubts about theeffectiveness of industrial policies for creating better conditions. It appears that they
are distorting the business environment whereby some industries like food processing
are becoming worse off without bettering conditions for others. Current industrial
policy should be pragmatically reviewed.
Among the surviving enterprises, older firms do not enjoy any extra advantage,
despite prevailing popular beliefs. On the contrary, older firms are penalized in termsof tax administration. This suggests that tax regulators go after obvious targets

29regardless of their compliance record. This underlying psychology of the regulator
explains firms’ general preference for tax evasion.
Finally, we establish that more formal structures of organizing businesses,
such as privately held limited liability companies, can also be punishing to firms. The
current regulatory environment in Pakistan is killing the incentives for formal
business structure and becoming a liability for business.
Conclusively, evidence is found that economic policy reforms in Pakistan
cannot treat firms as homogeneous units. A great amount of heterogeneity exists, andthis heterogeneity can drive many different responses to questions about the severityof business constraints. For instance, fashioning an effective business climate formicro firms will entail different policies than for small, medium, or large firms.
Additionally, we find that access to foreign markets, type of production, and type offirm ownership play substantial roles in determining business responses to constraints.
The age of the firm is less important, as is the province in which the firm is located.
Some issues are cross-cutting across firms, such as a desire for a more reliable
electricity supply, but generally the results suggest that policymakers must develop
proposals that account for the heterogeneity of firms, and that a one-size-fits-all
approach will not be effective and could even have unintended consequences.

30

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