Report No. 59916-BW

Promoting Entrepreneurship in Botswana:

Constraints to Micro Business

Development

March 2011

Financial and Private Sector Development

Africa Region and

The Botswana Institute of Development Policy Analysis (BIDPA)

Document of the World Bank

Table of Contents

Acronyms and Abbreviations ........................................................................................................ iv

Acknowledgement .......................................................................................................................... v

Executive Summary ......................................................................................................................... i

1. Introduction ............................................................................................................................. 1

1.1 Why should we care about microenterprises? ............................................................................... 1

1.2 The Pilot survey ............................................................................................................................ 2

1.3 Objectives of this report ................................................................................................................ 3

1.4 Organization of the report ............................................................................................................. 5

2 Profile of the microenterprise sector ....................................................................................... 5

2.1 What do microenterprises do? Where? And how do they do it? ................................................... 5

2.2 Who are the micro-entrepreneurs? .............................................................................................. 14

2.3 Capability groups of microenterprises ........................................................................................ 24

3 Constraints to micro-business development .......................................................................... 43

3.1 Informality, productivity and access to services ......................................................................... 43

3.2 Access to services and markets ................................................................................................... 49

3.3 Constraints to the growth of active microenterprises .................................................................. 66

4 Conclusion: lessons for the design of market assessments for services ................................ 68

References ..................................................................................................................................... 73

List of Figures

Figure 1: Registration and licensing status by tax registration status ........................................................ 10

Figure 2: Registration and licensing of the registered or licensed .............................................................. 11

Figure 3: Average net income per person engaged in tax registered enterprises ....................................... 12

Figure 4: Difference in probability tax registration by gender of business owner (%) .............................. 16

Figure 5: Difference in probability (%) of tax registration by education level of make business owners-

(high school grads– primary school complete) ........................................................................................... 16

Figure 6: Percent difference in probability of tax registration by business motive of male entrepreneurs-

(active enterprises – involuntary enterprises) ............................................................................................. 19

Figure 7: Average net income per person engaged in active enterprises (involuntary enterprises = 100) 21

Figure 8: Fixed investment as % of net income ......................................................................................... 22

Figure 9: Average annual employment growth rate since start up (%), all sectors ..................................... 23

Figure 10: Average annual employment growth rate since start up, services only .................................... 23

Figure 11: Annual net income of own-account workers by time in business (000 pula) ........................... 28

Figure 12: Annual net income per worker by time in business and registration status- ............................ 29

Figure 13: Percent of registered licensed enterprises-own account work only .......................................... 31

Figure 14: Percent of registered licensed enterprises – only those engaging 2-4 people ........................... 31

Figure 15: Percent distribution of active enterprises by line of business ................................................... 34

Figure 16: Percent distribution of involuntary enterprises by line of business .......................................... 34

Figure 17: Annual net income per worker by age group of owner (000 pula) – active enterprises ........... 38

Figure 18: Percent of registered or licensed enterprises by schooling of business owners........................ 39

Figure 19: Percent of enterprises of high-school-graduates by line of business ........................................ 41

Figure 20: Percent of enterprises of non-high school grads by line of business ........................................ 42

Figure 21: Respondents rating factors as major barriers registration by registration status (%) ............... 45

Figure 22: Respondents rating various factors as major barriers to business registration (%) .................. 45

Figure 23: Percent rating factors as major deterrent to business registration by registration status ........... 46

Figure 24: Business owners who saw indicated benefits from registration (%) ....................................... 47

Figure 25: Business owners rating factors as major growth obstacles (%) ................................................ 48

Figure 26: Percent rating factors as major constraints to growth by business motivation ......................... 50

Figure 27: Percent of active enterprises rating various factors as major growth constraints ..................... 51

Figure 28: Involuntary enterprises rating factors as major growth constraints (%) .................................. 52

Figure 29: Active enterprises rating factors as major growth obstacles (%) ............................................. 53

Figure 30: Enterprises using external finance for investment or working capital (%)................................ 54

Figure 31: Enterprises using supplier and informal finance for investment or working capital (%) .......... 55

Figure 32: Enterprises using external finance l by source ......................................................................... 56

Figure 33: Percent of enterprises with non-residential business premises .................................................. 57

Figure 34: Percent of enterprises connected to the public electrical grid .................................................. 58

Figure 35: Enterprises with non-residential business premises by owners’ age group (%) ....................... 60

Figure 36: Enterprises connected to the public electrical grid by owners’ age groups (%) ....................... 61

Figure 37: Enterprise owners who had graduated from high school (%) ................................................... 62

Figure 38: Vocationally trained business owners (%) .............................................................................. 63

Figure 39: Percent of enterprises keeping books ....................................................................................... 64

Figure 40: Percent of enterprises using services of a professional accountant .......................................... 65

List of Tables

Table 1: Botswana Pilot Survey Sample Distribution by Location .............................................................. 3

Table 2: Pilot Survey Sample Distribution by Sector and Type of Location ................................................ 6

Table 3: Distributions of sample enterprises in other manufacturing and other services ............................ 7

Table 4: Distribution of sample by scale and other business characteristics ............................................... 8

Table 5: Average number of persons engaged per enterprise and net incomes per person ......................... 9

Table 6: Percent of enterprises by registration status.................................................................................. 10

Table 7: Distribution of the sample by registration status .......................................................................... 13

Table 8: Distribution of sample by business owner's characteristics .......................................................... 15

Table 9: Distribution business owners by reason for being in business ..................................................... 18

Table 10: Distribution business owners by reason for being in business................................................... 20

Table 11: Distribution by business age and size groups and business motivation ..................................... 25

Table 12: Average Annual net incomes and annual turnover per enterprise .............................................. 27

Table 13: Annual net incomes per worker and fixed assets per worker ..................................................... 30

Table 14: Percent distribution of business owners by demographic characteristics ................................... 33

Table 15: Annual net incomes and turnover per establishment by owner’s age and schooling ................. 35

Table 16: Annual net incomes per worker and fixed assets per worker by owners' characteristics ........... 36

Table 17: Percent distribution of enterprises by business owners' characteristics ...................................... 37

Acronyms and Abbreviations

BDS Business Development Services

BIDPA Botswana Institute for Development Policy Analysis

CEDA Citizen Enterprise Development Agency

FAP Financial Assistance Policy

IFS Integrated Field Services

LEA Local Enterprise Authority

MTI Ministry of Trade and Industry

NDB National Development Bank

NSO National Strategy Office

SBPA Small Business Promotion Agency

SEEP Small Enterprise Education and Promotion

SMME Small, medium, and micro enterprise

UYF Umsobomvu Youth Fund (South Africa)

Vice President: Obiageli Katryn Ezekwesili

Country Director: Ruth Kagia

Sector Director: Marilou Jane D. Uy

Country Manager: Timothy R. Gilbo

Acting Sector Manager: Michael J. Fuchs

Task Team Leader: Taye Mengistae

Acknowledgement

This report was prepared by a team drawn from Financial and Private Sector Development,

Africa Region, the World Bank Group, and the Botswana Institute of Development Policy

Analysis (BIDPA). Taye Mengistae (AFTFE, World Bank) was the task team leader. Achieng

Okatch led BIDPA’s contribution. Andrei Mikhnev (CICRS), Zeinab Partow (AFTP1), Sandeep

Mahajan (AFTP1), Rita Ramalho (GIAEA), and Ravi Ruparel (AFTFE) all of the World Bank

Group, kindly served as peer reviewers.

Tim Gilbo (Country Manager), Tom Buckley (Senior Country Officer), Chunlin Zhang (Sector

Leader, AFTFE), and Michael Fuchs (Acting Sector Manager) provided overall guidance.

Dorothy Judkins (AFTFE) provided administrative and editorial assistance.

The team is also grateful for comments on an earlier draft received from representatives of

various departments of the Government of Botswana, including from the Ministry of Finance and

Development Planning, the National Strategy Office (NSO), and the Local Enterprise Authority

(LEA). The comments were made at a meeting held on November 30, 2010 at the World Bank

Groups Country Office in Gaborone. Among those in attendance were Keamogetse Molebatsi,

Ruth Seipone, and Nancy Mabole of the NSO; Keganele Malikongwa of the Ministry of Finance;

and Jerry Mooketsane, Bokete Mokgosi, and Thato Jensen of LEA.

Overall guidance was provided to the team at a very early stage of the design of the study from

Ms. Banny K. Molosiwa, Permanent Secretary (MTI), Mr. Boniface G. Mphetlhe, Deputy

Permanent Secretary (MTI), Ms. Peggy Serame of the Ministry of Finance, and Ms. Neo Mooko,

Director of Research and Information Management at LEA.

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Executive Summary

Botswana has had active programs of government support to small, medium and micro

enterprises (SMMEs) since the1970s, but none of these have reached microenterprises to a

significant degree. Part of the reason could be that there are not many financial products and

Business Development Services (BDS) that are appropriate or affordable enough for micro

businesses.

In June-July 2009 the World Bank and the Botswana Institute of Development Policy Analysis

(BIDBPA) carried out a pilot sample survey of 800 microenterprises in the Eastern Corridor of

Botswana. The survey was designed to identify major capability groups of micro businesses in

the country and institutional constraints under which they operate, as potential input for the

design of formal market assessments for financial services and BDS tailored to the needs of this

important but little understood part of the economy.

This is a report on the main findings of the survey intended to help inform ongoing efforts to

support enterprise development by key agencies such as the Local Enterprise Authority (LEA)

and the Citizen Enterprise Development Agency (CEDA) and the Ministry of Trade and

Industry. The report identifies capability groups in the sample based on measured productivity

and earnings, and sorts the more productive and growth oriented businesses that could potentially

be a source of effective demand for BDS from those that are not likely to evolve into viable

enterprises in the long term. It then assesses the constraints under which various capability

groups operate based on business owners’ evaluations of the main obstacles to the operation and

expansion of their enterprises.

Capability groups are defined in the report at various levels. At the most fundamental level we

distinguish between active enterprises and involuntary enterprises based on the business

motivation and outlook of their owners, arguing that the relative productivity and dynamism of

the two groups indicates that only active enterprises are ultimately viable businesses. The report

also further classifies active microenterprises into smaller sub groups of capability, based

alternatively on the time they have been in business and the age and level of education of their

business owners. Based on time in business, we distinguish between starting up active

enterprises and post start-ups. Important distinctions of potential significance to policy are also

made between youth owned active enterprises and enterprises run by older owners, on one hand,

and businesses of high school graduates and less educated owners, on the other.

What makes microenterprises different?

For the purpose of this report, a microenterprise is a business that engages fewer than five

workers full time. A small enterprise is defined as employing at least five but no more than thirty

workers, and a medium enterprise is defined as employing more than thirty but less than 100

workers. More than 30 percent of enterprises in the survey sample were retail traders. Another

third were in services such as catering, transport, personal care, car repairs, printing services, and

finance and real estate. One quarter were in food processing, other manufacturing and crafts,

mainly in tailoring and knitting, wood work and metal work.

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Unlike SMEs, a high proportion of microenterprises operate from no fixed location. Itinerant

businesses constituted nearly 30 percent of the sample: most, but not all, of them as street

vendors. But an even higher percentage (46 percent) also operated from non-residential business

premises or structures. Another 23 percent of businesses were home based.

Microenterprises in Botswana also appear to last longer on average than their counterparts in

many other developing economies: just under 23 percent of the sample were businesses that

started within the past two years, while nearly one in three had been in business for ten years or

longer at the time of the survey.

Productivity

Typically, microenterprises are not as well organized as SMEs. Their workforce also is normally

less skilled than that of SMEs and functions with smaller capital per worker. Thus, on average,

microenterprises are far less productive than SMEs. For the full sample, the average annual net

income (or value added) per worker was just under 30,000 pula, and the value of fixed assets per

worker was about 57,600 pula. Each of these numbers concealed enormous variation across and

within business lines. The median net income per worker was much lower at 10,000 pula, which

would have been under one-third of the country’s per capita GDP at the time of the survey. The

mean annual net income per worker ranged from just below 19,000 pula for food vendors to

38,000 for transport businesses.

Informality

Most microenterprises in Botswana also are informal in the sense that they are not registered

with the tax office and do not hold a business license. The narrowest and probably the most

common definition of an informal business is that it is an enterprise that is not registered for tax

purposes. On this definition, only 14 percent of enterprises in the pilot survey sample were

formal.

Regardless of which definition is used, formal microenterprises are far more productive than

informal microenterprises. This is partly because inherently more productive enterprises are

more likely to be registered. But registered or licensed businesses also have better access to

markets and services, which may helped raise their productivity. Indeed, many unregistered and

unlicensed micro-businesses recognize that informality bars them from markets and services and

from participating in potentially useful business support programs. However, they choose not to

register or get a license nonetheless because those benefits have less weight in their view than the

costs that come with registration or being licensed. The main cost items include potential tax

liabilities, licensing and registration fees, and anticipated compliance costs of labor laws and

other aspects of business regulation. Therefore, reducing such regulatory barriers to registration

and licensing could be a significant component of formalizing microenterprises to improve their

access to services.

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Towards markets in financial products and BDS for microenterprises

At the same time, informality is not necessarily the most important of factors preventing

microenterprises from accessing the financial products and business services currently available

to SMEs. Most micro businesses in Botswana would not be able to make use of existing products

and services regardless of their registration status. Many of them would not afford those products

and services in any case. Even more importantly, existing products and services do not seem

match the circumstances of even the most promising of micro businesses.

Addressing these issues could require public investment in the development of markets in new

financial products and new BDS tailored to the needs and capabilities of the sector. Improved

availability of affordable and appropriate services could indeed be the driver rather than

consequence of formalization, and might be a greater incentive for registration and licensing than

any regulatory reforms.

Active enterprises vs. involuntary enterprises

For public investments in the development of new financial products and BDS for

microenterprises to have a positive social payoff, the investments may need to target primarily

the more promising and potentially viable businesses within the sector. From this point of view,

a more relevant distinction than that between formal and informal micro-businesses is that

between micro-businesses of “active entrepreneurs” and those of “involuntary entrepreneurs.”

Active entrepreneurs are business owners who could successfully earn a living in the labor

market if they chose to, but are self-employed because they make more money with their own

business than if they were working for someone else. In contrast, involuntary entrepreneurs are

those who are self-employed by default because they were rationed out of the labor market. They

would have taken up paid work at the going rate if there had been enough jobs to go around.

Only one in five of those in the pilot survey sample were active enterprises. The rest were all

involuntary. These proportions are probably close enough to those of the national population of

microenterprises in Botswana. A key message of the report is that public investments in the

development of markets for new financial products and new business development services for

micro-businesses might need to focus, at least initially, on active microenterprises. The reason is

that such enterprises have the best chance of evolving into viable and growth-oriented businesses

and of providing effective demand for these products and services over the long term.

This is by no means a suggestion that governments, donors or development agencies should not

provide support to involuntary entrepreneurs at all. The message is, rather, that the policy

challenge that involuntary entrepreneurs pose is one of integrating the younger among them to

the formal labor market through training and skills development schemes, and not necessarily

one of providing them with business development services.

On average, active entrepreneurs are younger and more educated. Their businesses also are

younger on average, and are far more likely to be registered for taxes. Active enterprises tend to

concentrate in relatively high value-added business lines such as manufacturing and crafts,

transport, and non-retail services. Involuntary enterprises tend to concentrate more in food

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vending and micro-retail more generally. Most significantly, active enterprises are far more

productive and have far higher growth rates than otherwise comparable involuntary enterprises.

Active enterprises also are far more growth-oriented than involuntary enterprises. The typical

active enterprise invests a greater share of its net income and grows faster than the typical

involuntary enterprise. For example, in the survey sample, an active enterprise that started out as

own-account work 3 to 5 years prior to the survey is likely to have approximately tripled in scale

by the time of the survey. In contrast, an otherwise comparable involuntary enterprise starting

from the same base is likely to have expanded by approximately 83 percent over the same time

interval.

More promising active enterprises as potential markets for BDS

Youth owned enterprises

As potential participants in new markets for financial products and BDS, active microenterprises

constitute a very diverse group in terms capabilities and constraints. It may be advisable to focus

initial public investment in the new markets on the more promising businesses among the group.

These can be defined in terms of characteristics of businesses or of their owners. Thus, based on

analysis of relative productivity and growth record in the survey sample, youth owned active

enterprises in general and those of young high school graduates in particular constitute the most

promising group of enterprises. The second most promising group of active enterprises defined

by owner characteristics is that of business of older high school graduates.

Startups

Youth-owned active enterprises largely overlap start-up active enterprises, by which is meant

active enterprises that came into existence within the last five years. Start-up active enterprises

are as promising and productive as the active enterprises of young high school graduates. This is

not surprising since this particular group of entrepreneurs account for a high proportion of

startups. Although some start-up active enterprises are own-account businesses, the vast majority

are micro-employers, meaning they engage up to three people other than the owner. The second

most promising group of active enterprises is that of post-start-up active micro-employers.

Therefore, investments in the development of markets in financial services and BDS for

microenterprises initially should target youth-owned active enterprises. These constituted

approximately 13 percent of the pilot survey sample and overlap more or less exactly the

subpopulation of start-up active enterprises. The second most promising target of the programs

seems to be active enterprises of older high school graduates. These constituted approximately 9

percent of the sample and more or less coincide with the subsample of post-start-up active micro-

employers.

What next?

The information that the pilot survey has generated on the various capability and constraints

groups of microenterprises could be useful input to future efforts to make available new financial

products and new BDS to active microenterprises in Botswana. An essential component of such

efforts should be a formal assessment of the market for existing and potential products and

services among the two most promising groups of active enterprises identified in the report:

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active startups and active youth-owned enterprises, with a particular focus on micro-employers

and on businesses of young high school graduates.

The scope of a formal market assessment for a given financial product or BDS includes four

analytic tasks: (a) an evaluation of a target group’s awareness and willingness and ability to pay

for existing products; (b) an evaluation of the group’s willingness to pay for potential products;

(c) an assessment of the extent of segmentation of the wider markets for existing or potential

products in which the group may be supported to participate; and (d) an assessment of the

potential for crowding out private demand or supply by public interventions in markets.

The findings of this report would be useful input to the design of tasks (a) and (b). The tasks will

require much more data on each constraints group than has been generated by the pilot survey,

which would need to be collected through focus group discussions with micro enterprise owners

within each group, more open in-depth interviews with enterprise owners and BDS providers,

market observation, and focused market surveys.

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1. Introduction

1.1 Why should we care about microenterprises?

1. This report analyzes data from the pilot sample survey of 800 microenterprises that was

carried out in selected localities of the Eastern Corridor of Botswana in the summer of 2009. The

aim of the survey was to identify major capability and constraints groups of micro-businesses in

the country as groundwork for formal market assessments for financial services and Business

Development Services (BDS) tailored to the needs of this important, but relatively neglected,

part of the economy. The intended audience of the report therefore includes policy makers

concerned with the development of the SMME sector in Botswana and experts involved in the

design and monitoring and evaluation of support programs targeting micro businesses and SMEs.

2. Botswana is an upper middle income, high growth economy with a long record of sound

macroeconomic management and good governance. However, it has long been dominated by

diamond mining, which currently accounts for a third of the country’s GDP and 80 percent of its

export earnings. And yet mining employs less than 5 percent of the work force. As a result,

unemployment and the incidence of poverty have both been persistently high, and SMME

support programs have figured prominently in the government’s strategies for economic

diversification, poverty reduction and employment generation. However, there are also

indications that the success of government efforts to support SMMEs is being hampered by

limited capacity to design and implement appropriate intervention.

3. For the purpose of this report, a microenterprise is a business that engages fewer than five

workers full time. A small enterprise is defined as employing at least five but no more than thirty

workers, and a medium enterprise is defined as employing more than thirty but less than 100

workers. According to the 2006 Labor Force Survey (Government of Botswana 2008),

approximately 300,000 people worked in the nonfarm private sector in Botswana, of which 80

percent were engaged in small, micro-, and medium enterprises (SMMEs). Approximately 1 in 3

of the workforce engaged in the SMME sector ran microenterprises. About 46,000 of these were

own-account workers. The rest worked in some 20,000 micro-and small enterprises that provided

paid employment to workers other than their owners. These statistics indicate fairly large sectors

of microenterprises and SMEs for a country of Botswana’s size. However, many experts also

believe that Botswana’s SME sector should be much larger than it is, not least of all because

more than one-third of the country’s labor force is unemployed. The development of a more

vibrant SME sector also is a major component of the government’s strategy for economic

diversification and poverty reduction.

4. As a result, Botswana has had active programs of government support to SMME since

the 1970s. The earliest framework of these programs was the Financial Assistance Policy (FAP),

which was introduced in the early 1980s to provide direct government financial assistance to small-

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scale manufacturers. In the late 1980s, the Integrated Field Services (IFS) was launched as a program

of training for SMMEs in recordkeeping, costing, business planning, marketing, buying, and stock

control. In 1999 the government set up the Small Business Promotion Agency (SBPA) to coordinate

all SMME support programs. This action was followed in 2001 by the establishment of the Citizen

Enterprise Development Agency (CEDA) as the implementing agency of FAP, now refocused on

providing subsidized loans to indigenous enterprises. Currently, CEDA offers loans ranging from

P500 to P150 000 to micro-and small-scale projects at an interest rate of 5.0%, repayable in 5 years;

and loans of up to P2 million to medium-scale projects with a 7.5% interest rate repayable in 7 years.

CEDA’s micro-lending activities are intended to complement those of the National Development

Bank (NDB), which has provided a range of regular-term loans to SMMEs since 1999.

5. In 2004, the Ministry of Trade and Industry (MTI) established the Local Enterprise

Authority (LEA) to incorporate the functions of the IFS and the SBPA. LEA offers highly

specialized development and support services including facilitating business planning; providing

training, mentoring, and advisory services; identifying business opportunities for existing and

future SMMEs; promoting domestic and international linkages; facilitating access to markets;

facilitating exploitation of government and large firms' procurement opportunities by SMMEs;

facilitating access to finance; facilitating technology adoption and diffusion; and promoting

general entrepreneurship and SMME awareness.

6. Unfortunately, none of these or the earlier programs has significantly reached

microenterprises. Microenterprises are very much part of the intended beneficiaries of existing

programs. Nevertheless, not many financial products or BDS have been tailored to the needs of

microenterprises. To the contrary, a common feature of existing and past SMME support

programs is that they all have been based on a top-down, one-size-fits-all approach.

7. Moving away from this approach to one whereby products and services on offer are

differentiated enough to match the diversity of needs and demands of their intended beneficiaries

is a necessary next step. However, doing so requires reasonably detailed knowledge of the

diversity of businesses in the SMME sector in capability and constraints. The pilot survey was

intended to help bridge this knowledge gap with respect to micro-businesses.

1.2 The Pilot survey

8. The survey was designed and implemented by the Botswana Institute for Development

Policy Analysis (BIDPA) during June and July 2009. It involved administering a common

written questionnaire to the 800 sampled business owners through face-to-face interviews by

trained enumerators. The subjects of the questions were:

• Demographic characteristics of business owners ;

• Location, activities , staffing, organization, start-up history, and current registration and

legal status of their businesses;

• Owners’ assessment of what they thought were obstacles to the day-to-day operations and

growth of their businesses;

• Information on turnover, employment, revenue, staff remuneration, cost of purchases,

and sources of finance; and

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• Indicators of the business environment in such areas as interaction with government

agencies, property crime, and quality of public utilities services.

9. The sample was drawn from localities in Gaborone and surrounding areas (including

Tlokweng, Mogoditshane, Ramotswa, Gabane, and Mochudi), Francistown and surrounding

areas (including Tonota, Sebina, Tsamaya, and Matsiloje), and Selebi Phikwe and surrounding

areas (including Bobonong, Mmadinare, and Tsetsebjwe), Palapye, and Serowe. The distribution

of the sample among these locations is shown in table 1.

Table 1: Botswana Pilot Survey Sample Distribution by Location

District Count Percent Town

Count Percent

Southern 254 31.75 Gaborone 256 32

South East 59 7.38 Mogoditshane 46 5.75

Kweneng 61 7.63 Mochudi 55 6.88

Kgatleng 55 6.88 Ramotswa 32 4

Central 242 30.25 Serowe 61 7.63

North East 129 16.13 Palapye 38 4.75

Selibe Phikwe 89 11.13

Total 800 100 Francistown 118 14.75

Other 105 13.13

Total 800 100

1.3 Objectives of this report

10. The report analyzes the returns to the survey with the broad objective of identifying

capability groups of micro-businesses and the constraints under which they operate as potential

input to formal assessments of markets in financial products and BDS. Prior market assessments

are a critical link in the methodology of the market development paradigm for public support to

small and microenterprise development that the Donor Committee (2001) has recommended for

the design and delivery of BDS. The purpose of a market assessment is to determine, (a) whether

or not there is significant actual or potential (effective) demand for particular types or categories

of BDS by some populations of enterprises; (b) whether BDS providers in the region have

sufficient capacity to meet that demand; and (c) whether there is lack of (effective) demand or

supply, the reasons for it, the kind of interventions that would be needed to remedy the observed

deficiency in demand or supply, and whether these interventions should come from local

development agencies or other sources. The interventions could come from the supply side and

involve the design of new products or the introduction or marketing of existing products from

other parts of the country. They also could come from the demand side and involve financing or

subsidy schemes such as vouchers and matching grants designed to make existing products

accessible to the group in question (box 1).

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Box 1. Market Paradigm for Public Intervention in the Provision of Business Development Services

A key element of the market development paradigm of the Donor Committee (2001) for public

intervention in the provision of BDS is that the intervention would be justified only insofar as there is

evidence that a significant segment of targeted enterprises would not have access to these services in

the absence of the interventions, despite the fact that their access would be socially profitable. In other

words, interventions would be justified only on grounds of evident market failure in provision.

A second element of the same paradigm is that public intervention should not crowd out existing or

potential commercial providers of services. Doing so would undermine the sustainability of the market

over the long term and its reach to the wider population of enterprises.

A third element is that, in principle, interventions should eschew free or highly subsidized provision of

BDS by the public in favor of facilitating the evolution of a genuine market in the service over the long

term.

We are not aware of specific schemes for the provision of BDS that reflect these principles in Botswana,

although several examples exist in neighboring South Africa. Perhaps the best known is the Umsobomvu

Youth Fund (UYF) voucher scheme, which enables young participating entrepreneurs to obtain business

planning services or training from a registered private sector service provider in the areas of services that

they otherwise could not afford. At the same time, the beneficiaries of the scheme have a say in which

provider to use from a number of competing suppliers.

In a second South African example of BDS provision, government agencies play the role of facilitators

rather than direct providers. This program is the BDS provision cluster that Investec established under the

name, Business Place. This program is one-stop provision of a wide range of services––from access to

finance, business planning, legal services, IT services, computer training, marketing, to export-import

advice––from a variety of private sector providers. These providers share a common service infrastructure

but otherwise compete with rival suppliers for clients. The cluster operates in partnership with a number of

public partners including the City of Johannesburg and the City of Cape Town.

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11. Because the scope of the survey instrument did not extend to service providers, the report

cannot say anything of relevance to objective (b) of a market assessment. However, the survey

provides a useful starting point for some of the analysis needed for objectives (a) and (c) of such

an assessment in two ways. First, it identifies capability groups based on measured productivity

and earnings, and, on this basis, sorts the more productive and growth-oriented businesses that

are likely to have effective demand for BDS from those that are not likely to evolve into viable

enterprises in the long term. Second, it highlights the differences between capability groups in

terms of the constraints they face based on business owners evaluation of growth factors.

12. A key consideration in the identification of capability groups of microenterprises in the

context of Southern Africa is the role that business informality plays in determining access to

services and markets. We characterize a business as formal if it is registered for tax purposes or

operates on an official business license. Gelb and others (2009) show that, unlike in other parts

of Sub-Saharan Africa, informality in Southern Africa is strongly associated with lower

productivity and with poorer access to services. The other dimensions on which enterprise

capability varies are the scale of the business, its age, and the human capital of business owners.

All three of these variables are significant correlates of productivity, registration and licensing

status, and access to markets and services.

13. In the process of identifying capability groups, the report draws a profile of Botswana’s

microenterprise sector insofar as the survey sample can be thought of as representative of the

national population of micro-businesses. It also describes the roles that business owners’ human

capital plays in the choice of lines of business, in productivity, and in access to markets and

services.

1.4 Organization of the report

14. The rest of the report is organized as follows. Chapter 2 defines the main capability

groups of microenterprises in terms of scale of activities, length of time in business, and the

experience, education, and business motives of their owners. The capability of each group is

measured by the average productivity and growth record of its members. Chapter 3 then

discusses how the capability groups identified in the second chapter differ in access to markets

and services. Chapter 4 concludes the report by laying out the implications of the survey results

for the design of public interventions to promote the development of markets in new financial

products and BDS.

2 Profile of the microenterprise sector

2.1 What do microenterprises do? Where? And how do they do it?

15. Approximately one-third of enterprises in the survey sample were retail traders (tables 2

and 3). Another one-third worked in services such as catering, transport, personal care, car

6

repairs, printing services, and finance and real estate. One-quarter were employed in food

processing and other manufacturing and crafts, mainly in tailoring and knitting, wood work, and

metal work.

16. Unlike SMEs and larger businesses, a very large proportion of microenterprises operate

from no fixed location. Itinerant businesses constituted nearly 30 percent of the sample. Most,

but not all, of them were street vendors. However, a surprisingly high 46 percent of the sample

also operated from nonresidential premises or structures. Another 23 percent of businesses in the

sample were residence based. The latter is quite low in comparison with other developing

economies. It probably reflects the fact that zoning regulations are enforced more stringently in

Botswana than in many other developing economies.

Table 2: Pilot Survey Sample Distribution by Sector and Type of Location

Industry

Count Percent Type of location

Count Percent

Food and beverages 65 8.13

Non-residential

location 375 46.88

Textiles 37 4.63 Located in residence 187 23.38

Garments 51 6.38 No fixed location 238 29.75

Transport 17 2.13

IT 14 1.75 Total 800 100

Retail trade 273 34.13

other services 286 35.75

Other 57 7.13

Total 800 100

Scale and longevity

17. Very much in line with the results of the 2006 Labor Force Survey of the Government of

Botswana, and the 2007 Informal Sector Survey, half of the microenterprises covered by the pilot

survey were run by own-account workers. The other half provided employment to 1–3 people

other than the business owner as paid employees or as unpaid full-time family workers (table 4).

7

Table 3: Distributions of sample enterprises in other manufacturing and other services

Manufacturing Count Services (excluding retail trade) Count

Food and beverages 68 Barber Shop and hair saloon 49

Textiles 37 Car repairs 36

Garments 52 ITC 20

Basic metals 6 Transport 20

Fabricate metal products 7 Shoe repair service 20

Machinery and equipment 1

Printing / secretarial services/

Photography 17

Electronics 14 Health/education 12

Other manufacturing 18 Financial and real estate services 9

Total 203 Hotels and restaurants 5

Advertising 5

Wholesale trade 4

Laundry and dry cleaning 4

Car Wash and tire repair 3

Entertainment 3

driving schools 2

Total 209

18. The median microenterprise engages two people full time. This number is consistent with

any of the following plausible pairings: a husband and a wife, the household head or the spouse

with a child helper, or either of the two with a hired hand from outside of the household. Many

of the larger enterprises rely on 2–3 paid employees. Such enterprises are common in tailoring

and similar crafts, and typify such services providers as barber and car repair shops. On the other

hand, the modal enterprise in transport would be an own-account cab driver, and the modal retail

trader would be an own-account street vendor (table 5).

19. Microenterprises in Botswana appear to last longer than their counterparts in many other

developing economies (table 4). At the time of the survey, just under 23 percent of the sample

were businesses that had started within the past two years, whereas close to 30 percent had been

in business for 10 years or longer.

8

Table 4: Distribution of sample by scale and other business characteristics

Scale Count Percent

Own-account work 387 48.38

Engaging 2 to 4 people 339 42.38

Engaging 5 or more people 74 9.25

Total 800 100

Business age group Count Percent

2 years or less 183 22.88

2-5 years old 238 29.75

5-10 years old 130 16.25

Older than 10 years 249 31.13

Total 800 100

Registration status:

Registered with some

authority 397 49.3

Registered with tax

authorities 111 13.98

Holds a trading license 361 45.41

Book keeping practice :

Kept books 358 44.75

Have an accountant 53 6.63

Productivity

20. Less than 50 percent of enterprises in the sample kept books, and only approximately 7

percent employed professional accountants for this task (table 4). These low rates no doubt have

to do with the fact that the microenterprise workforce is smaller and typically less educated and

skilled than that of larger businesses. Combined with low fixed assets per worker, these factors

also make microenterprises less productive than larger businesses.

9

21. The average annual net income (or value added) per worker for the full sample was just

under 30,000 pula, and the value of fixed assets per worker was approximately 57,600 pula.

However, each of these numbers concealed enormous variation across and within business lines.

The median net income per worker was much lower at 10,000 pula, which would be under one-

third of the country’s per capita GDP at the time of the survey. The median value of fixed assets

per worker was 12,000 pula. Comparing subsamples across sectors, the mean annual net income

per worker ranged from just below 19,000 pula for food vendors to 38,000 for transport

businesses.

Table 5: Average number of persons engaged per enterprise and net incomes per person

Net income per Fixed assets

Number of worker per worker

Persons engaged ('000 pula) ('000 pula)

Mean Median Mean Median Mean Median

Food and beverages 2.1 2 18.7 5.3 57.5 9.5

Manufacturing/crafts 2.6 2 29 11.2 50.5 20.2

Transport 2.4 1 38 26.4 55.5 40

Retail trade 1.5 1 26.8 8.7 48.6 7.2

Other services 2.9 2 30.9 11.6 74.2 16.3

All sectors 2.2 2 27.9 9.8 57.6 12

Informality

22. Most microenterprises also are informal in the sense that they are not registered with the

tax office and do not hold a business license. The narrowest and probably the most common

definition of an informal business is that it is an enterprise that is not registered for tax purposes.

By this definition, only 14 percent of enterprises in the pilot survey sample were formal (table 4).

However, approximately 50 percent of the enterprises in the sample held a business license or

had registered with some government authority other than the tax office.

23. The tax registration rate varies enormously across the sample by line of business, ranging

from a low of 6 percent for food vendors to a high of 40 percent for transport services (table 6).

In contrast, there is not much variation in the rate of licensing, which ranges from 43 percent for

food vendors to 50 percent for other sectors. When we use the weaker definition of formality to

characterize enterprises that either are registered for tax or hold a business license, but not

necessarily both, just a little over 50 percent of businesses in the sample were informal.

10

Table 6: Percent of enterprises by registration status

Registration or licensing status

Registered Registered Holds a Registered Registered

Industry with non-tax for tax business for tax or

with some

authority

authority license licensed or licensed

Food and beverages 29.4 6.1 52.9 54.4 58.8

Manufacturing/crafts 73.0 23.9 48.9 58.0 80.7

Transport 55.0 40.0 50.0 55.6 72.2

Retail trade 40.8 8.4 43.3 45.4 62.4

Other services 59.1 17.8 44.4 48.1 66.1

All sectors 49.4 13.6 45.2 48.7 65.5

24. If we choose the stricter definition of formality (tax registration only), 77 percent of the

micro-businesses we would classify as formal would be holding a business license, and 93

percent of them would be registered with the Office of Company Registration (figure 1).

Figure 1: Registration and licensing status by tax registration status

76.6

92.897.3

40.1 42.5

59.6

0

20

40

60

80

100

120

% holding a trade

license

% registered with

the registrar

% registered or

holding a license

of the tax registered of those not registered for tax

11

Figure 2: Registration and licensing of the registered or licensed

25. On the other hand, by using the stricter definition, we would leave out of the category

some 40 percent of microenterprises that hold business licenses and some 43 percent that are

registered with the company registration office. The advantage of the second, weaker definition

is that it allows us to categorize as formal all license-holders and two-thirds of those registered

with the office of company registration (figure 2).

26. A disadvantage of the weaker definition is that it somewhat blurs the performance gap

between what we would classify as formal businesses and their informal counterparts compared

to what would emerge from the stricter definition of business formality. For example, the

average net income per worker for tax-registered enterprises in the sample was 57 percent larger

(figure 3). Approximately 10 percent of this gap arose from tax-registered enterprises having

more fixed assets per person engaged. Another 5 percent reflects the fact that tax-registered

enterprises normally operate from better locations or better business premises than do the

unregistered. Table 7 shows that the tax registration rate of enterprises operating from

nonresidential business premises is twice the average rate.

27. Some 20 percent of the productivity gap reflects the skills advantage of tax-registered

enterprises. For example, more of them keep books. In addition, well over half of the

productivity gap in favor of tax-registered businesses reflects other sources, possibly including

unobserved advantages in skills and know-how, and better or cheaper access to resources and

30

67.7

93.3100

0 0 0

32.5

0

20

40

60

80

100

120

% tax registered % registered wih

the registrar

% hodling a license % registered with

registrar or for tax

or holding a

license

of those which are tax registered or hold a license

of those which are neither tax registered nor hold a license

12

publicly provided goods and services. One observed source is economies of scale: tax-registered

enterprises are significantly larger (table 7).

Figure 3: Average net income per person engaged in tax registered enterprises

(net income per person for unregistered = 100)

136

148

151

157

125 130 135 140 145 150 155 160

Controlling for fixed assets, type of premises,

bookkeeping practice

Controlling for fixed assets per worker, type of

business location

Controlling for fixed assets per worker

No controls

13

Table 7: Distribution of the sample by registration status

Business registered for tax?

Yes No Total

(1) Number of persons engaged

1 person (own-account

work) 13 371 384

% 3.39 96.61 100

2-4 persons 64 271 335

% 19.1 80.9 100

5 or more persons 34 41 75

% 45.33 54.67 100

Total 111 683 794

% 13.98 86.02 100

(2) Number of years in business

2 years or less 18 165 183

% 9.84 90.16 100

2-5 years old 36 199 235

% 15.32 84.68 100

5-10 years old 23 107 130

% 17.69 82.31 100

Older than 10 years 34 212 246

% 13.82 86.18 100

(3) Type of location of transactions

Non-residential premises 90 279 369

% 24.39 75.61 100

Located in residence 12 175 187

% 6.42 93.58 100

No fixed location of

operation 9 229 238

% 3.78 96.22 100

14

2.2 Who are the micro-entrepreneurs?

Gender, experience, and schooling

28. Important as they are as covariates of its productivity, the scale of an enterprise and its

registration and licensing status ultimately result from, among other things, predetermined

attributes of the business owner. These attributes include schooling, duration and type of prior

economic experience, and other significant social characteristics such as gender and ethnicity.

29. Nearly 70 percent of microenterprises in Botswana are owned and run by women (table

8)––quite a high rate compared to other developing countries. Women-owned enterprises are less

likely to be registered for tax partly because the women in the sample tend to be less educated

than the men (figure 4), and the more educated among business owners are more likely to have

their businesses registered with the tax authorities. Average schooling levels of micro-business

owners in Botswana are quite high compared to those in the region and other developing

economies. Less than 10 percent of owners in the pilot survey sample had no formal schooling at

all, while at the other end of the educational attainment spectrum, a comparable proportion had

some tertiary education. Between these extremes were the business owners who had graduated

from high school, those who had started but had not completed primary schools, and those who

had some secondary schooling but had not graduated from high school. Business owners who

had at least completed high school constituted approximately one-third of the full sample. Those

with some schooling but who had not yet completed high school made up another 60 percent of

the sample.

15

Table 8: Distribution of sample by business owner's characteristics

Characteristics Count Percent

Gender:

Female 550 68.75

Education:

No schooling 57 7.13

Primary incomplete 64 8.01

Primary Completed 139 17.4

Junior Secondary Completed 278 34.79

Senior Secondary Completed 119 14.89

Vocationally trained 82 10.26

Some University Training 60 7.51

Total 799 100

Reason for setting up this business:

Absence of alternative employment 375 46.93

Pay in alternative too low 149 18.65

Enjoy running it 127 15.89

This is what I am best at 84 10.51

Other 64 8.01

Total 799 100

30. A business owner’s schooling is a reasonably strong predictor of the scale of her or his

business and its productivity, and the likelihood of the business being registered for tax or

holding a trade license. More educated business owners are significantly more likely to run

registered or licensed enterprises. For example, the business of a male owner randomly picked

from the sample would be 14 percent more likely to have been registered for tax if the owner had

at least completed high school than if the owner had completed only primary schooling (figure

5).

16

Figure 4: Difference in probability tax registration by gender of business owner (%)

Figure 5: Difference in probability (%) of tax registration by education level of make business

owners- (high school grads– primary school complete)

Active entrepreneurs vs. involuntary entrepreneurs

31. Part of the reason that more educated business owners are more likely to run tax-

registered or licensed enterprises is that a larger proportion of them are in business as a positive

career choice, not because they have no alternative ways of earning their livelihoods. Ultimately,

people are found in occupations as the outcome of rational choices that they make subject to the

constraints imposed on them by market parameters and their skills and wealth. At the same time,

not everyone makes choices from the same set of alternatives. Even when their underlying

-8.9

-5.8

-5.2 -5

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

With no controls Controlling for

schooling

Controlling for

schooling and age

Controlling for

schooling, age and

business motive

13.9 13.8

8.9

0

2

4

6

8

10

12

14

16

With no controls Controlling for owners' age Controlling for owners age and

business motive

17

preferences are similar to those of everyone else, some people’s choices are more restricted than

those of others. In other words, not everyone found in self-employment or running a micro-

business––or, indeed, any business––is there because s/he would not want to be anywhere else

given a wider choice set.

32. A widely held view is that a large proportion of those who are self-employed or running

micro-businesses in developing economies are people who have been rationed out of formal

labor markets and who would be found working for someone else if there were enough jobs to go

around at the going wage rate or even less. A term occasionally used to describe people who run

micro-businesses by default, or because they cannot earn their livelihood as employees in the

formal sector, is “necessity entrepreneurs”. At the other end of the spectrum are the “opportunity

entrepreneurs”, who comprise business owners whose opportunity set is large enough to enable

them to earn a living as formal sector employees at the going wage rate, yet have chosen an

entrepreneurial career as they would make more money or find more self-fulfillment this way.

Alternative designations for “necessity entrepreneurs” are “involuntary entrepreneurs” and

“survivalist entrepreneurs.” “Opportunity entrepreneurs” often are referred to as “active

entrepreneurs.”

33. One way of telling “active entrepreneurs” from “involuntary entrepreneurs” in business

surveys is asking enterprise owners why they decided to be in business rather than work for

someone else. In the Botswana survey, owners were asked to pick what best fit their actual

business motive from the list of five alternatives shown in table 8. The idea behind the question

was that people who had been pushed into self-employment due to lack of opportunities for paid

employment at “living wages” would not claim to enjoy their current occupation or accept that

their current earnings are what they would inherently be worth in the labor market. On the other

hand, those who were self employed by choice would. If this reasoning is correct, some 26

percent of the sample, or 211 business owners, would quality as active entrepreneurs. The

remainder would be “involuntary entrepreneurs, who reportedly were in business only because

they could not find any alternative employment at all, or they could not live on the wages offered

to them by potential employers.

34. Table 9 breaks down various demographic strata of business owners by what their

responses would be to the hypothetical question of whether they would rather work for someone

else at the going wage rates based on the reasons they gave to the actual survey question

described in table 8. In effect, the responses classify each stratum into active entrepreneurs and

involuntary entrepreneurs. Table 9 suggests that the proportion of active entrepreneurs is slightly

smaller among women and younger business owners. However, this particular comparison does

not take into account the role of differences in educational attainment by gender and between

business owner age groups. Indeed, by far the sharpest pattern in the table is that the likelihood

of a business owner being an active entrepreneur consistently rises with his or her educational

attainment. Thus, 45 percent of the subsample of those who had at least completed high school

would quality as active entrepreneurs, compared to 18 percent of those who had at most

completed primary school. This correlation between schooling and active entrepreneurship

accounts for approximately one-third of the correlation between schooling and business

formality as indicated by business registration for tax (figure 5).

18

Table 9: Distribution business owners by reason for being in business

Prefer to work for someone else?

Yes No Total

(1) Level of Education

At most primary complete 199 43 242

% 82.23 17.77 100

Junior secondary complete 198 65 263

% 75.29 24.71 100

At least secondary complete 128 103 231

% 55.41 44.59 100

(2) Age Group

24 yrs. or younger 311 103 414

% 75.12 24.88 100

25-29 yrs 92 49 141

% 65.25 34.75 100

30 yrs. or older 122 59 181

% 67.4 32.6 100

(3) Gender

Female 374 136 510

% 73.33 26.67 100

Male 151 75 226

% 66.81 33.19 100

Total 525 211 736

% 71.33 28.67 100

35. The direct correlation between business formality and active entrepreneurship is depicted

in figure 6. According to it, a randomly chosen male active entrepreneur is approximately 17

percent more likely to have his business registered for tax than a randomly selected male

involuntary entrepreneur. Conversely, more than half of the businesses in the sample that are

registered for tax are run by active entrepreneurs, whereas less than one-quarter of businesses

that are not registered for tax are owned by active entrepreneurs. Approximately half of this

correlation between tax registration and motives for entrepreneurship (figure 6) is explained by

active entrepreneurs being more likely to run larger businesses, which are more likely to be

registered for tax. For example, the proportion of active entrepreneurs among micro-businesses

engaging 2–4 people in the sample averages 38 percent, compared to 16 percent for own-account

workers (table 10).

19

Figure 6: Percent difference in probability of tax registration by business motive of male entrepreneurs-

(active enterprises – involuntary enterprises)

16.8

8.9

7.1 7

5.9

4.1

0

2

4

6

8

10

12

14

16

18

No controls Controlling for

scale

Controlling for

scale and mode

of location

Controlling for

scale, mode of

location and

years in business

Controlling for

scale, years in

business, type of

location and

line of business

Controlling for

scale, years in

business, type of

location , line of

business, labor

productivity

20

Table 10: Distribution business owners by reason for being in business

Prefer to work for others?

Yes No Total

(1) Scale

1 person (own-account

work) 300 59 359

% 83.57 16.43 100

Engaging 2 to 4 people 196 119 315

62.22 37.78 100

Engaging 5 or more people 29 33 62

46.77 53.23 100

(2) Age group

start up=<5 yrs 291 101 392

74.23 25.77 100

Young=5 to 10 yrs 81 35 116

69.83 30.17 100

Established>10 yrs 153 75 228

67.11 32.89 100

(3) Location of business activities

Non-residential business premise 207 134 341

60.7 39.3 100

Located in residence 134 33 167

80.24 19.76 100

No fixed location 184 44 228

80.7 19.3 100

(4) Line of business

Food and beverages 60 5 65

92.31 7.69 100

Manufacturing/crafts 46 38 84

54.76 45.24 100

Transport 11 9 20

55 45 100

Retail trade 268 71 339

79.06 20.94 100

Other services 135 86 221

61.09 38.91 100

(5) Registered for tax?

Yes 45 52 97

46.39 53.61 100

No 477 156 633

75.36 24.64 100

21

36. Active entrepreneurs are also more likely to operate from nonresidential premises, and

they are more likely to operate in sectors subject to greater regulation, such as transport services,

manufacturing and crafts, and nonretail services (table 10). Both factors would make a business

more visible to authorities, and thus probably more likely to register with them. These two

factors are simultaneously associated with higher rates of active entrepreneurship. For example,

the proportion of active entrepreneurs in manufacturing and crafts or transport was 45 percent,

compared to 21 percent of retail traders and 8 percent of food vendors. Likewise, 39 percent of

businesses operated from nonresidential premises are run by active entrepreneurs, compared to

less than 20 percent each of those operated from home and those operated from no fixed location

at all.

Relative productivity and Relative Dynamism of Active enterprises

37. When we control for scale, line of business, and type of location of activities, an active

enterprise is only approximately 6 percent more likely to be registered for tax than an

involuntary enterprise (figure 6). Allowing for the facts that active enterprises are more

productive on average and that the more productive businesses are more likely to register takes

away two more percentage points from the gap in the probability of tax registration between

active and involuntary enterprises.

38. Regardless of tax registration status, active enterprises are on average far more

productive than involuntary enterprises (figure 7). For example, the average net income per

worker for tax-registered active enterprises is 29 percent greater than the average net income per

worker of tax-registered involuntary enterprises. The productivity advantage of unregistered

active enterprises over unregistered involuntary enterprises is even higher at 46 percent.

Figure 7: Average net income per person engaged in active enterprises (involuntary enterprises = 100)

138

142

143

146

114

124

126

129

0 20 40 60 80 100 120 140 160

Controlling for scale ,fixed assests per worker , type

of location of activities, bookkeeping practices

Controlling for scale ,fixed assests per worker , type

of location of activities

Controlling for scale and for fixed assests per

worker

No controls

Tax registered or licensed enteprises only Unregisterd, unlicensed enteprises only

22

39. Approximately half of the productivity advantage of the tax-registered active enterprises

over tax-registered involuntary enterprises reflects the advantages that active enterprises have in

scale economies, better technology, fixed assets per worker, and skills. The other half could

reflect unobserved advantage in skills or better access to services (figure 7).

40. Active enterprises also are far more growth oriented than involuntary enterprises. For the

year leading up to the survey, fixed investment rates averaged well over 90 percent of the net

income of active enterprises, compared to approximately 30 percent for involuntary enterprises

(figure 8). Although investment rates varied enormously across sectors, the pattern in every line

of business was that the rates were several times higher for active enterprises than for

involuntary enterprises. As a result, the typical active enterprise grows faster than the typical

involuntary enterprise. For example, an active enterprise that started out as own-account work 3–

5 years prior to the survey would have grown by approximately 300 percent by the time of the

survey (figure 9). In contrast, an otherwise comparable involuntary enterprise starting from the

same base would have expanded by approximately 83 percent over the same interval. Similarly,

an active enterprise that started out with 2 workers 3–5 years prior to the survey would have

increased in scale by approximately 84 percent by the time of the survey while an otherwise

comparable default enterprise would have expanded by only 16 percent over the same period.

This pattern applies across all four sectors and is particularly well illustrated for the nonretail-

trade service sector by figure 10.

Figure 8: Fixed investment as % of net income

0 20 40 60 80 100 120 140 160 180 200

All sectors

Manufacturing/crafts

Other services

Retail trade

Transport

Active enterprises involuntary enterprises

23

Figure 9: Average annual employment growth rate since start up (%), all sectors

Figure 10: Average annual employment growth rate since start up, services only

306

84

4318

83

15 16 12

0

50

100

150

200

250

300

350

Started out as

own-account

work 3-5 years

ago (n=15 for

active, n=24 for

involuntary)

Started out

with 2 workers

3-5 years ago

(n=24 for active,

n=28 for

involuntary)

Started out as

own-account

work 2 years

ago or later

(n=21 for active,

n=97 for

involuntary)

Started out

with 2 workers

2 years ago or

later (n=28 for

active, n=112

for involuntary)

Active entererprises involuntary entreprises

433

7346

14

92

45

8 5

0

50

100

150

200

250

300

350

400

450

500

Non-retail

services, started

out with 2

workers 2 years

ago or later

(n=9 for active,

n=13 for

involuntary).

Non-retail

services, started

out with 2

workers 3-5

years ago (n=12

for active, n=9

for involuntary).

Retail trade,

started out with

one person 2

years ago or

later (n=12 for

active, n=71 for

involuntary).

Retail trade,

started out with

one person 3-5

years ago (n=18

for active, n=69

for involuntary)

Active enterprises involuntary enterprises

24

2.3 Capability groups of microenterprises

41. The distinctions between formal and informal enterprises, on one hand, and active and

involuntary enterprises on the other, relate to only two of the dimensions in which capability

groups of microenterprises can be defined as segments of the sector that may respond differently

to a given set of policy reforms, new financial products, or new markets in BDS. Of these two

dimensions, whether a business is formal or informal is an outcome variable. Ultimately, owners

choose to have their businesses registered for tax or otherwise depending on their determination

of which of the two courses of action would make them better off. In contrast, whether these

same owners are active or involuntary entrepreneurs is not subject to their choice any more than

as their gender, age, and ethnicity are. Rather, whether they are active or involuntary

entrepreneurs is a characterization of their prior labor market options as one of the exogenous

determinants of their choice to pursue a business career. We classify business owners as active

entrepreneurs to indicate that, given their skills, they would have successfully earned a living in

the labor market had they chosen to. Business owners that do not meet this criterion are

classified as involuntary entrepreneurs as the alternative to self-employment in their case would

be unemployment or employment at below subsistence wages.

42. In this section, we identify narrower and more homogenous capability and constraints

groups among active microenterprises, based, first, on the scale of each enterprise and how long

it has been in business and, secondly, the age and schooling of the business owner. Like

registration and licensing status, the scale and age of an enterprise are outcomes of the decisions

that the entrepreneur has made since setting up the business and are strong correlates of the

business owner’s decision on whether or not to operate formally. In contrast, the age and

schooling of the business owner are largely predetermined in relation to these decisions and in

relation to the decision to set up the business in the first place. A business owner’s age and

schooling also are key determinants of the labor market earnings potential of the entrepreneur.

They consequently are likely determinants of whether the business owner is an active

entrepreneur or an involuntary one.

Startups vs. post-startups

43. The most natural division of the survey sample by scale of activities is probably that

between own-account work (or single-person enterprises) and micro-employers, that is,

microenterprises that provide full-time employment to people other than the owner as paid

workers or as unpaid but full-time family workers. We can further classify each scale group of

enterprises by how long they have been in business into “startups” and “post startups.” The first

term refers to enterprises that have been in operation for no more than five years. “Post-startups”

are those who have been in business for longer than five years. The first half of the upper panel

of table 11 shows the distribution of the 211 active enterprises of the sample across the 4

categories of this 2-way classification. The second half of the upper panel is the corresponding

distribution of 525 of the involuntary enterprises in the sample.

25

Table 11: Distribution by business age and size groups and business motivation

44. A little over one-quarter of all active enterprises in the sample were businesses of own-

account workers. These are divided more or less equally between startups and post startups. This

section compares the two age groups of own-account active enterprises with each other and with

active micro-employers in productivity and other characteristics of the business and of the

owner. The section also will compare both age groups of active micro-employers with one

another, with own-account active enterprises, and with their respective matching groups of

involuntary enterprises. Approximately one-third of the 211 active microenterprises in table 11

are “startup” micro-employers. Another one-third of active enterprises are “post-startup” micro-

employers. There are 123 involuntary enterprises that match the first group in workforce size and

time in business. The matching age-size group of involuntary enterprises for post-startup active

micro-employers comprises 102 businesses.

Own-account enterprises

45. Of the 211 active enterprises in the sample, 29 were start-up own-account enterprises.

Another 30 were post-startup own-account enterprises. These two groups contrast sharply with

each other and with their respective matching groups of involuntary enterprises in productivity,

line of business, informality, and the owners’ human capital. In the second half of the upper

panel of table 11 are 168 businesses in the matching group of involuntary enterprises for the 29

start-up own-account active enterprises. The matching group for the 30 post-startup own-account

Number of enterprises by size groups

Own-account work Engaging 2-4 people Total

Active enterprises

Start ups 29 72 101

Post-start up 30 80 110

Total 59 152 211

Involuntary enterprises

Start ups 168 123 291

Post-start up 132 102 234

Total 300 225 525

Number of enterprises by business owners' level of schooling

Had not completed high school Had at least completed high school Total

Active enterprises

Youth owned 72 79 151

Non-youth owned 35 22 57

Total 107 101 208

Involuntary enterprises

Youth owned 298 105 403

Non-youth owned 99 23 122

Total 397 128 525

26

active enterprises is the 132 post-startup own-account involuntary enterprises (same section of

table 11).

46. Start-up own-account active enterprises are far more productive than start-up own-

account involuntary enterprises. The former also are more productive than post-startup own-

account active enterprises. The average net income of start-up own-account active enterprises is

approximately 59,700 pula a year and corresponds to an average annual turnover of 67,900 pula

(table 12 and figure 11). These sums are several times higher than the average annual net

incomes of start-up own-account involuntary enterprises. The sums also are higher than the

average annual net incomes and average annual turnover of 44,200 pula and 57,400 pula,

respectively, of post-startup own-account active enterprises. Finally, start-up own-account active

enterprises are more likely to register for tax than post-startup own-account active enterprises or

start-up own-account involuntary enterprises (figure 13).

27

Table 12: Average Annual net incomes and annual turnover per enterprise

Active enterprises only Involuntary enterprises only

Average Average Average Average Average Average

number of annual annual

number

of annual annual

persons turnover net income persons turnover net income

engaged ('000 pula) ('000 pula) engaged ('000 pula) ('000 pula)

I. Own account work only

Startups

Tax registered or licensed enterprise

only 1 73.4 69.1 1 30.6 21.8

Unregistered, unlicensed enterprises

only 1 57.6 42 1 19.2 14.7

All 1 67.9 59.7 1 23.6 17.5

Post-startups

Tax registered or licensed enterprise

only 1 81.6 64.2 1 45.9 30.6

Unregistered, unlicensed enterprises

only 1 38.4 28.4 1 29 22.3

All 1 57.4 44.2 1 37.2 26.3

2. Enterprises engaging 2-4 persons

Startups

Tax registered or licensed enterprise

only 2.6 160.9 104.9 2.5 78 50.8

Unregistered, unlicensed enterprises

only 2.8 109.5 93.8 2.6 44.3 32

All 2.7 140.8 100.5 2.6 56.8 39

Post-startups

Tax registered or licensed enterprise

only 2.7 207.1 142.5 2.8 91.5 67.6

Unregistered, unlicensed enterprises

only 2.5 67.4 56.5 2.9 44.5 25.6

All 2.8 148 100.6 2.9 77 60.9

28

Figure 11: Annual net income of own-account workers by time in business (000 pula)

47. Part of the productivity advantage of own-account active enterprises over own-account

involuntary enterprises and the higher propensity of the active enterprises to register for tax is

explained by the fact that active enterprises tend to concentrate more in higher productivity

industries and in sectors in which tax registration is more difficult to avoid. These include

manufacturing and crafts, transport services, and nonretail services. For example, more than 40

percent of start-up own-account active enterprises operated in such sectors, compared to

approximately 12 percent of start-up own-involuntary enterprises also were in the same sectors.

Some 45 percent of post-startup own-account active enterprises also were in these sectors,

compared to approximately 27 percent of post-start up own-account involuntary enterprises that

operate in the same sectors (figures 15 and 16).

48. Some of the productivity advantage of starting-up own-account active enterprises over

post-startup own-account active enterprises is that their owners are, on average, younger and

more educated. The owner of the typical start-up active own-account enterprise is significantly

younger than the owner of the typical post startup active own-account enterprise. This correlation

holds despite the fact that the owner-age composition of each group of active own-account

enterprises is very similar to that of the respective involuntary match groups. The average

schooling of owners of start-up active own-account enterprises also is significantly higher than

that of the owners of post-startup own-account enterprises. The amount of schooling also is

22.3

30.6

28.4

64.2

14.7

21.8

42

69.1

0 10 20 30 40 50 60 70 80

Unregistered, unlicensed enterprises only

Tax registered or licensed enterprise only

Unregistered, unlicensed enterprises only

Tax registered or licensed enterprise only

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

Startups Post-startups

29

higher than the average schooling level of the owners of its match group of involuntary

enterprises.

Micro-employers

49. There were 72 active micro-employers in the start-up age group and 80 active micro-

employers in the post-startup age group of active startups (table 11). Their involuntary-enterprise

match groups included 123 startup businesses and 102 post startups, respectively.

50. Both age groups of active micro-employers were far more productive than their

involuntary enterprise match groups. Average net incomes per person engaged were 35,900 pula

for start-up active micro-employers, and 43,100 pula for post-start up micro-employers, which,

while significantly lower than the average annual net incomes per person for start-up own-

account active enterprises, are comparable to the average annual net income per person for post-

start up own-account active enterprises, but higher than those of their respective involuntary

enterprise match groups by more than 50 percent (figures 11 and 12, table 12). Moreover, the

average active micro-employer of either age group generated twice the aggregate net income of

the average own-account active enterprise and nearly twice the aggregate net income of the

average involuntary micro-employer (table 13).

Figure 12: Annual net income per worker by time in business and registration status-

Enterprises engaging 2-4 persons

11.3

20.7

34.8

37.8

23.5

21.8

19.1

62.5

0 10 20 30 40 50 60 70

Unregistered, unlicensed enterprises only

Tax registered or licensed enterprise only

Unregistered, unlicensed enterprises only

Tax registered or licensed enterprise only

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

Post-startups Startups

30

Table 13: Annual net incomes per worker and fixed assets per worker

Annual

Fixed

assets

net income per worker

per worker ('000) pula

('000) pula

I. Active enterprises only

Startups

Tax registered or licensed enterprise

only 37.8 28.4

Unregistered, unlicensed enterprises

only 34.8 138.8

All 35.9 138.9

Post-startups

Tax registered or licensed enterprise

only 62.5 50.8

Unregistered, unlicensed enterprises

only 19.1 20

All 43.1 39.5

II. Involuntary enterprises only

Startups

Tax registered or licensed enterprise

only 20.7 58.1

Unregistered, unlicensed enterprises

only 11.3 16.9

All 14.8 32.2

Post-startups

Tax registered or licensed enterprise

only 21.8 54.7

Unregistered, unlicensed enterprises

only 23.5 28.5

All 22.8 39

51. Some of the productivity advantage of active micro-employers over involuntary micro-

employers probably has to do with factors that make active micro-employers more likely to

register than involuntary micro-employers. The average start-up active micro-employer is more

than likely to register for tax than an involuntary micro-employer of either age group (figure 14).

One such factor is that active enterprises are far more concentrated in more productive sectors

including manufacturing and crafts, and transport and other nonretail services. In these sectors,

the benefits that enterprises derive from registering for tax or holding a license might outweigh

the costs. Some 70 percent of active micro-employers were found in these sectors, compared to

35 percent of involuntary micro-employers (figures 15 and 16).

31

Figure 13: Percent of registered licensed enterprises-own account work only

Figure 14: Percent of registered licensed enterprises – only those engaging 2-4 people

0 10 20 30 40 50 60

% registered for tax

% holding a license

% registered with non-tax authority

% registered for tax

% holding a license

% registered with non-tax authority

Sta

rtu

ps

Po

st-s

tra

tup

s

Active enterprises Involuntary enterprises

13.6

11.8

31.6

49.2

78

28.8

61

69.5

0 10 20 30 40 50 60 70 80 90

% registered for tax

% holding a license

% registered with non-tax authority

% registered for tax

% holding a license

% registered with non-tax authority

Str

atu

ps

Po

st-s

tra

tup

s

Active enterprises Involuntary enterprises

32

52. A second factor behind the productivity advantage of active micro-employers over

involuntary micro-employers is that owners of active micro-employers are more educated on

average. Although the age distribution of the two groups of business owners is quite similar, 49

percent of active micro-employers are high school graduates, compared to 22 percent of

involuntary micro-employers.

Youth-owned businesses and enterprises of older owners

53. More than three-quarters of enterprises in the sample were youth owned, meaning that

they were run by people who were no more than 29 years old (table 14). We can further classify

the schooling of youth-owned and “non-youth-owned” businesses owners’ into those run by

people who had at least completed high school and those run by people who had not. The

distribution of the subsample of active entrepreneurs between the four categories of this two-way

classification is shown in the first half of the lower panel of table 11.

54. A particularly interesting entry in this panel is the 79 active youth entrepreneurs who had

graduated from high school. The entry corresponds to a group of enterprises that stands out in

productivity in relation to the 72 enterprises of less-educated active young entrepreneurs (shown

in same panel) as well as to the involuntary enterprises of the 105 high school graduates shown

in the table. This section compares and contrasts the three groups of enterprises in productivity

and other business characteristics.

Businesses of high school graduates

55. Approximately half of the active enterprises in the sample were run by people who have

had at least high school education. The vast majority of these-79, to be precise -were young

people. The respective involuntary match groups of youth-owned and non-youth-owned active

enterprises of high school graduates are 105 youth-owned involuntary enterprises and 23 non-

youth-owned involuntary enterprises respectively (table 11).

56. When we cross-classify the subsample of active enterprises by scale and by time in

business, start-up own-account active enterprises turn out to be the most productive of the

resulting four categories of micro-businesses, but the productivity gap between them and active

micro-employers of either age group is not that large. When we cross classify the same sub-

sample of active enterprises by the schooling and age groups of business owners, youth-owned

businesses of high school graduates are by far the most productive group, followed at some

distance, by businesses of older high-school graduates. On average, a business run by a young

high school graduate generated a net income per person of 57,700 pula a year, with an average

workforce of 2.9 and an annual turnover of 184,000 pula (tables 15–17). In comparison,

businesses run by older high school graduates generate an average net income per worker of

42,000 pula a year on an annual turnover of 171,900 pula and with a workforce of 3.2. Within

each group, average scale and average productivity both were higher for businesses that were

registered for tax or held business licenses than for those that were neither nor licensed (figure

17). Each of the two groups of businesses run by high school graduates also was, on average,

more productive and had far larger turnover than active enterprises of owners who had not

33

graduated from high school and involuntary enterprises of high school graduates of the same age

group (figure 17 and tables 17 and 18).

Table 14: Percent distribution of business owners by demographic characteristics

24 years 29 years Female High school

or younger or younger graduate

I. Active enterprises only

Startups

Own account

work 82.1 92.9 67.9 25

Engaging 2-4

people 67.8 84.7 61 71.2

Post-startups

Own account

work 28.6 50 75 14.3

Engaging 2-4

people 23.7 59.3 68 49.2

II. Involuntary enterprises only

Startups

Own account

work 86.1 93.4 82.5 19.9

Engaging 2-4

people 85.5 93.6 57.3 41.8

Post-startups

Own account

work 25.2 52.7 74 13

Engaging 2-4

people 26.7 59.3 70.9 22.1

34

Figure 15: Percent distribution of active enterprises by line of business

Figure 16: Percent distribution of involuntary enterprises by line of business

0

10

20

30

40

50

60

70

Fo

od

an

d b

eve

rag

es

Ma

nu

fact

uri

ng

/cra

fts

Tra

nsp

ort

Re

tail

tra

de

Oth

er

serv

ice

s

Fo

od

an

d b

eve

rag

es

Ma

nu

fact

uri

ng

/cra

fts

Tra

nsp

ort

Re

tail

tra

de

Oth

er

serv

ice

s

Startups Post-startups

Own-account work Engaging 2-4 people

0

10

20

30

40

50

60

70

80

Fo

od

an

d b

eve

rag

es

Ma

nu

fact

uri

ng

/cra

fts

Tra

nsp

ort

Re

tail

tra

de

Oth

er

serv

ice

s

Fo

od

an

d b

eve

rag

es

Ma

nu

fact

uri

ng

/cra

fts

Tra

nsp

ort

Re

tail

tra

de

Oth

er

serv

ice

s

Startups Post-startupsOwn account work Engaging 2-4 people

35

Table 15: Annual net incomes and turnover per establishment by owner’s age and schooling

Active enterprises only Involuntary enterprises only

Average Average Average Average Average Average

number of annual annual number of annual annual

persons turnover net income persons turnover net income

engaged ('000 pula) ('000 pula) engaged ('000 pula) ('000 pula)

I. Youth owned businesses

Owner has completed high school

Tax registered or licensed enterprises

only 3.2 251.1 175.7 2.8 187 86

Unregistered, unlicensed enterprises

only 2.7 86.1 72.7 2.5 75.4 59.2

All 2.9 184 133.8 2.7 133.8 73.2

Owner has less than high school education

Tax registered or licensed enterprises

only 2.7 102.5 80.1 1.5 59.9 45.9

Unregistered, unlicensed enterprises

only 2.3 66.8 54.3 1.6 25.3 29

All 2.5 84.9 67.4 1.5 38.6 29.3

2. Businesses of older owners

Owner has completed high school

Tax registered or licensed enterprises

only 3.3 250.7 184 2.4 157.2 132.4

Unregistered, unlicensed enterprises

only 3.1 47.9 26.9 1.6 26.5 19.8

All 3.2 171.9 122.9 2 96.2 79.9

Owner has less than high school education

Tax registered or licensed enterprises

only 2 52 32.3 1.9 46.2 28.7

Unregistered, unlicensed enterprises

only 1.9 53.8 44.2 2.5 46 28.6

All 1.9 53.1 39.4 2.2 46.1 28.6

36

Table 16: Annual net incomes per worker and fixed assets per worker by owners' characteristics

Active enterprises only

Involuntary enterprises

only

Annual Fixed assets Annual

Fixed

assets

net income per worker

net

income per worker

per worker ('000) pula

per

worker ('000) pula

('000) pula

('000)

pula

I. Youth owned businesses

Owner has completed high school

Tax registered or licensed enterprise only 75.3 75.5 25 58.7

Unregistered, unlicensed enterprises only 31.9 26.1 31.2 22.2

All 57.7 55.4 28 41.3

Owner has less than high school education

Tax registered or licensed enterprise only 44.2 28.3 26 26.4

Unregistered, unlicensed enterprises only 26 28 12.6 33.3

All 34.9 28.1 17.7 30.6

2. Businesses of older owners

Owner has completed high school

Tax registered or licensed enterprise only 64 307.3 43.1 57.9

Unregistered, unlicensed enterprises only 17.6 26.9 14.5 31.3

All 42 198.3 29.8 45.5

Owner has less than high school education

Tax registered or licensed enterprise only 15.3 22.1 23.3 132.4

Unregistered, unlicensed enterprises only 13.5 41.6 19.1 18.5

All 14.3 33.3 20.7 63.8

37

57. Part of the productivity advantage of active enterprises of high school graduates of either

age group reflects that these enterprises have more fixed assets per person engaged than the

match group of involuntary enterprises, and also compared to active enterprises of owners who

had not completed high school. The higher turnovers and larger fixed assets of active enterprises

of high school graduates, compared to involuntary enterprises of the same education level of

group owners, also translate to greater propensity of active enterprises to formalize. For example,

37 percent of active enterprises of young high school graduates were registered for tax compared

to 14 percent of involuntary enterprises of young high school graduates that had done the same

(figure 18). On the other hand, tax registration rates among active enterprises of high school

graduates do not vary by much by age groups of owners.

58. Again, some of the differences in productivity and registration status between active

enterprises of high school graduates and their involuntary enterprises match group, and the same

differences between the two owner-age groups of the active enterprises of high school graduates

are related to differences in choice of lines of business. Active enterprises of young high school

graduates tend to concentrate in relatively high productivity sectors, for which tax registration

rates tend to be higher in any case. In contrast, involuntary enterprises of either age group are

more concentrated in retail trade, in which productivity generally is lower and tax registration

rates also are comparatively low (figure 19).

Table 17: Percent distribution of enterprises by business owners' characteristics

startups Engaging 2-4 Female

(%) people (%)

owned

(%)

I. Active enterprises only

Youth owned businesses

Owner has completed high school 61.5 85.9 48.7

Owner has less than high school education 56.3 49.2 73.2

Business run by older owner

Owner has completed high school 29.2 88.9 75

Owner has less than high school education 14.7 54.8 73.5

II. Involuntary enterprises only

Youth owned businesses

Owner has completed high school 75.2 59.6 57.1

Owner has less than high school education 64.7 34.5 74.6

Business run by older owner

Owner has completed high school 21.7 42.9 60.9

Owner has less than high school education 14.1 35.1 78.8

38

Figure 17: Annual net income per worker by age group of owner (000 pula) – active enterprises

13.5

15.3

17.6

64

26

44.2

31.9

75.5

0 10 20 30 40 50 60 70 80

Unregistered, unlicensed

tax registered or licensed

Unregistered, unlicensed

tax registered or licensed

Ow

ne

r d

id n

ot

gra

du

ate

fro

m h

igh

sch

oo

lO

wn

er

gra

du

ate

d f

rom

hig

h s

cho

ol

Youth owned Run by older owners

39

Figure 18: Percent of registered or licensed enterprises by schooling of business owners

59. A related factor in the higher productivity of active enterprises of young high school

graduates compared to active enterprises of older high school graduates is that businesses of

younger people also are younger and larger on average. Some 62 percent of businesses run by

young high school graduates in the sample were in the start-up business age group, compared to

only 29 percent of active enterprises of older high school graduates in the same category (table

17). Moreover, approximately 86 percent of the active enterprises of young high school

graduates engaged 2–4 people––twice the proportion of involuntary enterprises of young high

school graduates who engaged that many people.

11.8

15.7

14.4

34.8

37.2

0 10 20 30 40 50 60 70 80 90 100

% registered for tax

% holding a license

% registered with non-tax authority

% registered for tax

% holding a license

% registered with non-tax authority

% registered for tax

% holding a license

% registered with non-tax authority

% registered for tax

% holding a license

% registered with non-tax authority

No

n-y

ou

th o

wn

ed

en

terp

rise

s

Yo

uth

ow

ne

d

en

terp

rise

s

No

n-y

ou

th o

wn

ed

en

terp

rise

s

Yo

uth

ow

ne

d

en

terp

rise

s

invo

lun

tary

en

terp

rise

sA

ctiv

e e

nte

rpri

ses

Run by high school graduates Run by owners who did not graduate from high school

40

Businesses of the less educated

60. A little over half of the active enterprises in the sample were run by people who had less

than a high school education. Nevertheless, again, the vast majority of these (72) were youth

owned. The respective involuntary match groups of youth-owned, and non-youth-owned active

enterprise owners who had less than high school education consisted of 298 youth-owned

involuntary enterprises and 99 non-youth-owned involuntary enterprises, respectively (table 11).

61. Active enterprises of youth who had not completed high school operated on a smaller

scale: a 65 percent smaller turnover and 49 percent smaller fixed assets per worker. Furthermore,

they were on average 40 percent less productive than active enterprises of young high school

graduates (tables 15 and 16 and figure 17). However, the non-graduate youth-owned active

enterprises were nearly 60 percent more productive than active enterprises of older owners who

had not completed high school (table 16 and figure 17).

62. The productivity advantage that active enterprises of non-graduate youth had over

businesses owned by older people with comparable schooling is reflected in the former’s higher

rates of registration and licensing relative to comparator groups (figure 18). Their productivity

advantage also was reflected in the fact that these youth were more concentrated in high

productivity sectors than their involuntary enterprise match group (figure 20) and that the active

enterprises owned by these youth tended to be younger than active enterprises of older owners

who had not completed high school (table 17).

41

Figure 19: Percent of enterprises of high-school-graduates by line of business

0 10 20 30 40 50 60 70

Food and beverages

Transport

Other services

Food and beverages

Transport

Other services

Manufacturing/crafts

Retail trade

Manufacturing/crafts

Retail trade

invo

lun

tary

en

terp

rise

s

Act

ive

en

terp

rise

s

invo

lun

tary

en

terp

rise

s

Act

ive

en

terp

rise

s

Ru

n b

y o

lde

r o

wn

ers

Yo

uth

ow

ne

d

42

Figure 20: Percent of enterprises of non-high school grads by line of business

0 10 20 30 40 50 60 70

Food and beverages

Manufacturing/crafts

Transport

Retail trade

Other services

Food and beverages

Manufacturing/crafts

Transport

Retail trade

Other services

Food and beverages

Manufacturing/crafts

Transport

Retail trade

Other services

Food and beverages

Manufacturing/crafts

Transport

Retail trade

Other services

invo

lun

tary

en

terp

rise

sA

ctiv

e e

nte

rpri

ses

invo

lun

tary

en

terp

rise

sA

ctiv

e e

nte

rpri

ses

Ru

n b

y o

lde

r o

wn

ers

Yo

uth

ow

ne

d

43

3 Constraints to micro-business development

63. Some of the productivity gap observed among various categories of microenterprises was

related to differences in the skills and effort of their owners. However, another part of was

associated with differences in access to key markets and services. This access may not be related

to business owners’ talent or effort. Some businesses have easier or cheaper access to external

finance than others for reasons that may have nothing to do with how well run they are or how

profitable their projects might be. Some may have better access to public utilities or cheaper

access to markets and suppliers for reasons unrelated to their productivity or their prior or

potential market performance.

64. In Botswana, as in many other developing economies, SMMEs do not have as good

access to credit, markets, business services more generally, or public utilities as do larger

companies. Within the SMME sector, microenterprises are at a particular disadvantage not least

because they are less capable than SMEs of taking advantage available business support schemes

for improving access to services.

65. There also is some consensus that business informality often is a significant barrier to

microenterprise access to markets and services. Part of the effort to support the integration of the

microenterprises in financial and BDS markets might therefore need to go into formalizing

micro-businesses.

66. The next section assesses how much micro business owners think of finance and other

services as constraints to the productivity and growth of their enterprises and the role that

business informality may have played in impeding access to markets and services by the various

capability groups identified in section 2.

3.1 Informality, productivity and access to services

Drivers of informality

67. Why do so many microenterprise owners choose to operate informally, that is, opt not to

register with the tax authority and choose even not to get a business license? A short answer

would be that those who operate informally are doing so only because they would be worse off

had they registered for tax or taken out a license. This answer is correct but probably trivial if we

do not know exactly how formality would affect net profits (or net income). Enterprises would

choose to operate formally only if the act of registering for tax or getting a license would make

their net profits higher than otherwise. Getting registered or obtaining a license would raise an

enterprise’s net profits only if either of them increased the enterprise’s revenue by more than it

would add to the cost of the enterprise’s activities. Then the enterprise owners who operate

44

informally would be only those who had decided that registration for tax or being licensed would

increase their costs of operation by more than these actions would increase their revenues.

68. This line of reasoning is, by and large, correct. However, it also assumes that all micro-

business owners know approximately what they need to do to register or license their enterprises,

or what net benefits they would get directly or indirectly from doing either. In fact, one of the

main reasons that survey respondents gave for not registering their businesses was ignorance. In

the survey, ignorance of how and where to get registered––and, in many cases, even whether

they were expected to register their businesses––was cited by approximately one-third of

nonregistered respondents as a major reason for not registering. Moreover, this response rate

applied to active as well as involuntary entrepreneurs.

69. However, many survey respondents also pointed to several items that would discourage

registration by adding to the cost of running their businesses. These items are listed in figures

21–23. The items seem to be given the same weight by formal and informal enterprises as a

deterrent of registration. In figure 21, the comparison is limited to enterprises that are

unregistered for tax or those not holding business licenses, and shows that there probably is no

one regulatory factor in Botswana that we could single out as the main driver of informality

among microenterprises. At the same time, the figure suggests that a number of regulatory

requirements may have combined to make the cost of formalization too high and beyond any

possible benefit that entrepreneurs might expect to gain from operating formally.

70. Taxes represent one of the more prominent of these cost items. Approximately 30 percent

of unlicensed enterprises and almost as high a percentage of those unregistered for tax cited the

desire to avoid taxes as a major reason for not having registered their businesses. Only a slightly

smaller fraction of each of these groups of respondents also reported that registration fees were

prohibitive. Some 26 percent–27 percent of business owners cited the desire to avoid complying

with labor laws as a major reason that they had avoided registering. Approximately 25 percent of

each group thought that businesses were discouraged from registering by the length of the time

needed to complete the registration. A slightly smaller percentage of each group cited the cost of

compliance combined with other aspects of business regulation as a major factor.

45

Figure 21: Respondents rating factors as major barriers registration by registration status (%)

Figure 22: Respondents rating various factors as major barriers to business registration (%)

71. In figure 22, we compare ratings of the factors listed in figure 21 as potential deterrents

of registration. However, this time we limit ourselves to businesses that are registered for tax or

23.5

24.6

26.2

27.1

29.4

24.2

25.4

26.7

29.8

30.4

0 5 10 15 20 25 30 35

Compliance costs of regulation

Time cost of registration

Labor laws

Registration fees

Taxes on the registered

unlicensed unregistered for tax

26.7

30.3

24.5

30.6

28.2

17.9

23.8

28

29.8

35.4

0 5 10 15 20 25 30 35 40

Compliance costs of regulation

Labor laws

Time cost of registration

Taxes on the registered

Registration fees

Active enterprises involuntary enterprises

46

hold a business license. This time we also distinguish between active and involuntary enterprises.

On the whole, the relative weight attached by both groups to individual factors is not very

different from what is shown in figure 21. There also registration fees and taxes are marginally

the most prominent of all the items. However, the concern with labor laws seems to be slightly

lower for this group. Moreover, the cost of complying with aspects of regulation other than those

relating to labor or taxes is of significantly less of a concern for active than for involuntary

enterprises.

72. Figure 23 describes ratings of deterrents of registration by registered and unregistered

enterprises separately. Here, too, the basic pattern is that the composition of the factors that seem

to matter and the relative weights respondents attach to each does not vary much from figures 21

and 22.

Figure 23: Percent rating factors as major deterrent to business registration by registration status

Private costs of informality: Does informality reduce access to services?

73. Survey respondents identified potential tax liabilities, licensing and registration fees, and

the compliance costs of labor laws as key items of the cost to formally operate a business.

However, respondents also readily recognized that enterprises that failed to register for tax or get

a license would forgo the advantages of potentially cheaper access to markets and services,

which would have enhanced their revenue. For example, more than 70 percent of respondents

whose businesses were neither registered for tax nor licensed thought that registration would

enable them to participate in government business support or incentive programs (figure 24). The

proportion of those who thought of registration as a requirement for participation in government

programs was even higher among owners of tax-registered or licensed enterprises. The vast

majority of respondents also thought that registered businesses would have cheaper access to

finance and improved access to business space and utilities. Many even thought that registration

would provide some protection from demands for bribes.

26.2

25.7

33.8

22.7

27.6

20.1

24.3

25.5

26.1

28.5

0 5 10 15 20 25 30 35 40

Compliance costs of regulation

Time cost of registration

Taxes on the registered

Labor laws

Registration fees

Unregistered respondents Registered respondents

47

Figure 24: Business owners who saw indicated benefits from registration (%)

74. The effects that respondents expected that formalization would have on their businesses’

access to markets and services (figure 24) are consistent with the differences between the ratings

that tax-registered enterprises gave to various potential growth constraints and the ratings given

by those unregistered for tax (figure 25). For example, the proportion of businesses that

considered lack of access to finance to be a major growth constraint was significantly smaller for

those that were tax-registered than for those that were not (60 percent vs. 80 percent,

respectively). Tax-registered businesses also were significantly less likely to rate access to

business space or access to public utilities as major constraints than enterprises that were

unregistered for tax.

0 10 20 30 40 50 60 70 80 90

Protects from demand for bribes from officials

Improves access to utilities

Improves access to land/better business

premises

Enables business with government and large

companies

Reduces the cost of finance

Provides access to government

programs/incentives

registered for tax or holding a license unlicensed and unregistered

48

Figure 25: Business owners rating factors as major growth obstacles (%)

Does informality cost society? Informality and productivity

75. That a large majority of microenterprises operate informally despite the very same

owners’ belief that being formal would have advantages in access to services can mean only that

the private costs of informality (figures 21 and 22) outweigh the advantages. The question then

arises whether society at large would lose as a result. In other words, would raising the

formalization rate of microenterprises in Botswana increase the aggregate productivity of the

sector?

76. This question is difficult to answer based on cross section survey data. The evidence that

the Botswana survey data provided on the issue was rather inconclusive. The data showed that

microenterprises that were registered for tax or held business licenses were significantly more

productive than those that were neither tax registered nor held a license. For example, controlling

for business location, business line, and relevant characteristics of the business owner

(experience, education, gender, and business motivation), the net income per person engaged in

the enterprise was 57 percent higher for a tax-registered micro-business.

77. However, there are likely to be unobserved attributes of enterprises or of business owners

that influence productivity, but at the same time make businesses more likely to register for tax.

Once we control for such unobserved attributes, there is no statistical significant difference in

productivity between microenterprises that are registered for tax and those that are not. Basically

the same pattern of results is observed when we compare productivity between formal and

informal microenterprises on alternate definitions of informality. This pattern suggests that we

cannot rule out, on the basis of survey data, the possibility that the correlation that we see in the

data between formalization and productivity stems solely from the fact that inherently more

productive microenterprises also are more likely to register for tax for some reason.

0 10 20 30 40 50 60 70 80 90

Lack of skills

Lack of power connection

Lack of access to land

Crime

Lack of access to finance

unregistered , unlicensed registered for tax or holding license

49

78. On the other hand, the survey data provide some evidence that improvement in access to

external finance increases the productivity of microenterprises. The same data show that

registration for tax increases access to finance. This is indirect evidence that formalization does

lead to productivity gains. When controlling for relevant observable business characteristics

(other than scale and input mix) and relevant attributes of the business owner (including age,

gender, and schooling), microenterprises that reported being constrained by lack of access to

finance had net incomes per worker that were approximately 36 percent less than the average. If

we limit the comparison to active enterprises only, the productivity shortfall of enterprises that

are reportedly constrained by lack of access to finance is much higher at approximately 55

percent.

79. Again, these productivity gaps could merely reflect that inherently more productive firms

tend to complain less about lack of finance, or rely less on external finance, or be more

successful in obtaining credit. However, the negative correlation between being constrained by

lack of access to finance and productivity persists even when we control for unobservables that

may influence productivity as well as access to finance. Indeed, the use of these controls

suggests that the true effect on microenterprises of improved access to finance could be much

larger than suggested by the 36 percent labor productivity gap that we observe in the data

between financially constrained enterprises and others.

3.2 Access to services and markets

80. Getting registered for tax and operating with a license would improve a business’ access

to markets and services. However, informality is not necessarily the most important factor

preventing microenterprises from accessing the financial products and business services that may

be available to SMEs. Most micro-businesses in Botswana probably would not be able to make

use of existing products and services regardless of their registration status. The reason is that a

combination of factors, including that many enterprises probably could not afford them, that the

products and services seem to be ill suited to the needs and circumstances of most, and that many

business owners seem to be ignorant of what is available on the market. Addressing these factors

to improve the access of microenterprises to services probably requires public investment in the

development of markets in new financial products and new BDS tailored to the needs and

capabilities of the sector.

81. The results of the pilot survey suggest that the social payoff in higher productivity from

such investment could be substantial. The data show, for instance, that improved access to

finance would raise the average productivity of microenterprises. The data also suggest that

improved allocation of business space, better provision of infrastructure, and the development of

markets for training services and other business development schemes probably would have a

similar effect and help make the microenterprise sector a more likely foundation for a larger and

more dynamic SME sector.

50

82. However, the microenterprise sector is not homogeneous as a potential market for new

financial products and new BDS. The survey data show that the sector is extremely diverse in

productivity and development potential. In fact, efforts at introducing new financial products and

new BDS tailored to the sector would probably benefit only the most active enterprises. These

enterprises comprise the most productive segment of the sector and therefore are the most likely

to be able afford the new services over the long term. Productivity levels, growth prospects, and

reported constraints to business development also seem to vary considerably across the different

sections of the population of active enterprises that we described in the previous section. It could

be important to take these differences into account in the design and introduction of new

products and services. In the previous section, we discussed potentially relevant capability

differences among groups of active enterprises as measured by productivity. In the rest of this

section, we will highlight the differences and similarities in reported constraints to business

development among those groups.

83. For active and involuntary enterprises alike, the most important reported constraints are

access to finance, access to business space and utilities, crime, and lack of skills (figure 26).

However, the key difference between the two groups of enterprises is that active enterprises that

are tax-registered or licensed are significantly less likely to report any of these constraints as

“major” than are unregistered and unlicensed active enterprises (figure 27). In contrast, there is

no significant difference among registered or licensed involuntary enterprises in ratings of

individual constraints. Overall, “complaint” rates against individual constraints also are

consistently lower for active enterprises, which particularly are less likely to report being held by

lack of access to finance or by lack of access to business space.

Figure 26: Percent rating factors as major constraints to growth by business motivation

0 10 20 30 40 50 60 70 80 90

Skills

Electricity

Access to land

Crime

Access to finance

Active entrepreneurs involuntary entrepreneurs

51

84. Yet another striking contrast (figures 27, 28 and 29) between active enterprises and

involuntary enterprises is that complaint rates do not vary much by business age groups (startup

vs. post- startups), by scale groups (own-account enterprises vs. micro-employers), or even by

age and education groups among involuntary enterprise business owners, whereas issues these

very much do matter among active enterprises.

85. Across both scale groups of active microenterprises, and for startups as well as for post-

startups, tax-registered or licensed businesses are less constrained by lack of access to finance or

by lack of access to land. Tax-registered businesses also are more likely to have better access to

electricity and suffer from less crime. However, there also is indication that the association

between business formality and access to services in Botswana may have weakened in recent

years. The association was that the advantage that tax-registered or licensed businesses had over

the unregistered and unlicensed was larger among startups (own-account enterprises as well as

micro-employers) than it was among post startups.

Figure 27: Percent of active enterprises rating various factors as major growth constraints

0 20 40 60 80 100 120

Skills

Crime

Finance

Skills

Land

Finance

Skills

Crime

Skills

Land

Po

st s

tart

up

sS

tart

up

sP

ost

sta

rtu

ps

Sta

rtu

ps

En

terp

rise

s e

ng

ag

ing

2-4

pe

op

leO

wn

acc

ou

nt

wo

rk

Tax-registered or licensed Unregistered and unlicensed

52

Figure 28: Involuntary enterprises rating factors as major growth constraints (%)

Access to finance

86. A sizable proportion of active enterprises use external sources to finance fixed

investments and working capital. In the survey sample, the proportion ranged between 40 percent

and 50 percent for startups, and from 50 percent to 60 percent among post-startups (figure 30).

However, the external finance was almost invariably obtained from informal sources and

suppliers (figure 31). Access also was significantly lower among active enterprises that were not

tax registered or licensed; only 20 percent to 30 percent of these had used external sources.

Among youth-owned enterprises, only 30 percent to 40 percent had used external sources (figure

32)

87. Therefore, it was surprising that lack of access to finance was the top constraint for

almost all categories of active enterprises that had not registered for tax or did not have a

business license. Active enterprises comprised both scale groups of active startups, post-startup

active micro-employers, businesses of young active entrepreneurs who had not graduated from

high school, and businesses of older active entrepreneurs who had graduated from high school

(figures 27 and 29). The only group of active enterprises for which access to finance came as the

0 10 20 30 40 50 60 70 80 90 100

Skills

Electricity

Finance

Skills

Electricity

Finance

Electricity

Crime

Electricity

Crime

Po

st s

tart

up

sS

tart

up

sP

ost

sta

rtu

ps

Sta

rtu

ps

En

terp

rise

s e

ng

ag

ing

2-4

pe

op

leO

wn

acc

ou

nt

wo

rk

Tax-registered or licensed Unregistered and unlicensed

53

second most important constraint was businesses of young high school graduates, for which

access to finance was a close second to business space and utilities (figure 29).

Figure 29: Active enterprises rating factors as major growth obstacles (%)

0 10 20 30 40 50 60 70 80 90 100

Sklls

Electricity

Land

Crime

Finance

Sklls

Crime

Land

Electricity

Finance

Sklls

Electricity

Land

Crime

Finance

Sklls

Crime

Electricity

Finance

Land

Ru

n b

y o

wn

ers

wh

o d

id

no

t g

rad

ua

te f

rom

hig

h

sch

oo

l

Ru

n b

y h

igh

sch

oo

l

gra

du

ate

s

Ru

n b

y o

wn

ers

wh

o d

id

no

t g

rad

ua

te f

rom

hig

h

sch

oo

l

Ru

n b

y h

igh

sch

oo

l

gra

du

ate

s

No

n-y

ou

th o

wn

ed

en

terp

rise

sY

ou

th o

wn

ed

en

terp

rise

s

54

88. Overall, access to finance was less of a problem for tax-registered or licensed businesses

for two reasons. First, a smaller percentage of them rate it as a major problem than do

unregistered and unlicensed active enterprises. Second, historical rates of access to external

sources happen to be higher for active enterprises that are registered for tax or are licensed. The

gap between the ratings of registered or licensed vs. unregistered and unlicensed was particularly

large among active startups. The gap was evident both in actual rate of access to external finance

and in ratings of lack of such access as a business constraint (figures 29, 30). Interestingly, it

appears that the gap has decreased substantially in recent years. An indication of the decrease

was that the rate was much lower for active startups in the sample than it was for active post-

startups (figure 30). The decrease suggests that business informality may have become less of a

barrier to access to informal external finance than it used to be.

Figure 30: Enterprises using external finance for investment or working capital (%)

0 10 20 30 40 50 60 70

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

Startups

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

55

Figure 31: Enterprises using supplier and informal finance for investment or working capital (%)

0 5 10 15 20 25 30 35 40 45 50

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

Startups

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

56

Figure 32: Enterprises using external finance l by source

Business space and access to utilities

89. On average, active enterprises are significantly more likely to operate from nonresidential

business premises connected to the public electricity grid. Among active enterprises in the survey

sample, those registered for tax or holding a license also were more likely to operate from a

nonresidential business premise and to be connected to the public power grid than those that

were not registered for tax or hold a license (figures 33 and 34). Nevertheless, again, the

difference between the two groups of active enterprises has narrowed in recent years, suggesting

that business informality also may have become less of a barrier to access to business space and

utilities than it used to be. Moreover, the proportion of active enterprises operating from

0 10 20 30 40 50 60

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high schoolN

on

-yo

uth

ow

ne

d

en

terp

rise

s

Yo

uth

ow

ne

d

en

tep

rise

s

No

n-y

ou

th o

wn

ed

en

terp

rise

s

Yo

uth

ow

ne

d

en

tep

rise

s

invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

pri

ses

on

ly

From all external sources From informal external sources only

57

nonresidential premises appears to have increased markedly. This growth was indicated by the

fact that the proportion in the sample was significantly higher for startups than it was for post-

startups––own-account enterprises and micro-employers included. For example, 80 percent of

start-up active micro-employers in the sample––including those registered for tax or holding a

license as well as the unregistered and unlicensed––operated from nonresidential business

premises. In contrast, half that many (40 percent) unregistered and unlicensed post-startup micro-

employers and 60 percent of registered or licensed post-startup micro-employers did so (figure

34).

Figure 33: Percent of enterprises with non-residential business premises

0 10 20 30 40 50 60 70 80 90

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

Startups

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

58

Figure 34: Percent of enterprises connected to the public electrical grid

90. The proportion of those operating from nonresidential premises connected to public

utilities also was relatively high––70 percent to 80 percent for active enterprises of high school

graduates in the sample (figure 35 and 36). In contrast, the same proportion was quite low–– less

than 40 percent––among own-account active enterprises (figures 33 and 34), and among active

0 10 20 30 40 50 60 70 80 90

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

Startups

En

ga

gin

g 2

-4 p

ers

on

sO

wn

-acc

ou

nt

wo

rkE

ng

ag

ing

2-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

59

enterprises of youth who had not completed high school (figures 35 and 36). Thus, lack of

business space and access to utilities figured prominently in business owners’ ratings of

constraints to growth. These two issues were the second most important constraints reported by

startup active enterprises and a major problem for more than half of post-startup active

enterprises in the sample (figure 27). In fact, these issues were the top problems for active

enterprises of young high school graduates. They were rated as major constraints by more than

70 percent of active entrepreneurs who had graduated from high school––both young and older

(figure 29). More than 60 percent of all active enterprises in the sample including startups, post-

startups, own-account enterprises, and micro–employers considered not being connected to the

public power grid as a major problem.

Skills constraint

91. Lack of skills was a major constraint for approximately 40 percent of active enterprises in

the sample (figures 27 and 29). The percentage of active enterprises for which it was a major

constraint was significantly higher among own-account startups (more than 60 percent) than it

was for start-up micro-employers. This differential is not surprising because the average level of

schooling of own-account startups was far lower than that of start-up micro-employers. Less than

30 percent of owners running own-account active startups had not completed high school,

whereas more than 70 percent of start-up micro–employers had (figure 37). Similarly,

approximately 25 percent of owners of start-up micro-employers were vocationally trained

whereas only 10 percent of start-up own-account entrepreneurs are similarly trained (figure 38).

92. The differences in levels of training between the two groups of active entrepreneurs were

reflected in the way that they ran their businesses. For example, a start-up micro-employer was

approximately 20 percent more likely to have kept proper books than the typical own-account

enterprise, and more likely also to have used the services of a professional accountant for the

purpose (figures 39 and 40).

60

Figure 35: Enterprises with non-residential business premises by owners’ age group (%)

0 10 20 30 40 50 60 70 80 90 100

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high schoolN

on

-yo

uth

ow

ne

d

en

terp

rise

s

Yo

uth

ow

ne

d

en

tep

rise

s

No

n-y

ou

th o

wn

ed

en

terp

rise

s

Yo

uth

ow

ne

d

en

tep

rise

s

invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

pri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

61

Figure 36: Enterprises connected to the public electrical grid by owners’ age groups (%)

0 10 20 30 40 50 60 70 80 90

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high school

Owner did not graduate from high school

Owner graduated from high schoolN

on

-yo

uth

ow

ne

d

en

terp

rise

sY

ou

th o

wn

ed

en

tep

rise

s

No

n-y

ou

th o

wn

ed

en

terp

rise

sY

ou

th o

wn

ed

en

tep

rise

s

invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

pri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

62

Figure 37: Enterprise owners who had graduated from high school (%)

0 10 20 30 40 50 60 70 80 90

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

Startups

En

ga

gin

g 2

-4 p

ers

on

sO

wn

-acc

ou

nt

wo

rkE

ng

ag

ing

2-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

63

Figure 38: Vocationally trained business owners (%)

93. On the other hand, the proportion of post-startup micro-employers who rated lack of

skills as a constraint to growth was significantly lower than that of start-up active micro-

employers (figure 29). This response was notable since the average schooling level of owners of

post-startup micro-employers was lower (figure 37), the proportion of the vocationally trained

also was significantly smaller for the same group (figure 38), and post-startup micro-employers

were less likely to keep books or use the services of professional accountants for the purpose

(figures 39 and 40).

0 5 10 15 20 25 30 35

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

StartupsE

ng

ag

ing

2-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t w

ork

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

64

Figure 39: Percent of enterprises keeping books

0 10 20 30 40 50 60 70 80

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

Startups

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t

wo

rk

En

ga

gin

g 2

-4

pe

rso

ns

Ow

n-a

cco

un

t

wo

rk

Invo

lun

tary

en

terp

rise

s A

ctiv

e e

nte

rpri

ses

on

ly

Tax registered or licensed Unregistered for tax and unlicensed

65

Figure 40: Percent of enterprises using services of a professional accountant

Business environment issues: Crime

94. Crime was a major business environment problem for more than 60 percent of active

enterprises across all age and size groups of microenterprises in the sample (figures 27 and 29).

It was particularly a problem for post-startup active enterprises and for active enterprises run by

older or less educated business owners. Crime was rated as a major business obstacle by an even

higher percentage of involuntary enterprises. It was the second most important constraint after

access to finance (more important than land) for all size-age categories of involuntary enterprises

(figure 28).

0 5 10 15 20 25

Post startups

Startups

Post startups

Startups

Post startups

Startups

Post startups

StartupsE

ng

ag

ing

2-4

pe

rso

ns

Ow

n-a

cco

un

t w

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En

ga

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g 2

-4

pe

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Invo

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ctiv

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on

ly

Tax registered or licensed Unregistered for tax and unlicensed

66

95. Crime is a business environment issue, and the provision of protection against criminals

by the state should not be rationed. Part of the solution to crime as a business environment

problem includes private provision of security and insurance. Provision of secure business

premises also could offer a significant part of that solution.

3.3 Constraints to the growth of active microenterprises

Constraints facing Start-up active enterprises

Own-account startups

96. Let us say hypothetically that we are targeting active own-account startups as the

beneficiaries of a business support program limited to the group’s most pressing needs. Such a

program would focus on access to business space and utilities for the tax registered or licensed of

the group, and on access to finance for the unregistered and unlicensed. These emphases would

be based on the assumption that the most pressing need of a group would be what affects the

largest percentage of its membership. Skills and crime are not major issues for the tax registered

or licensed, but both affect almost as many of the unregistered and unlicensed as does the lack of

access to business space and utilities.

97. The percentage of the unregistered and unlicensed of active own-account startups who

complained of lack of access to finance in the survey sample was second only to the percentage

of post-startup own-account enterprises that complained about the same issue. Active own

account startups should therefore be a priority beneficiary, for example, of a program that

introduced a microfinance product, just as they should be for, say, a lease program for business

space or market stalls. Active own-account startups should also be among the priority

beneficiaries of a business skills development program since it is the group for which the highest

percentage of members rate skills as a major constraint.

Start-up micro-employers

98. For start-up micro-employers also, lack of business space and access to utilities are of

greater concern than lack of access to finance for the tax registered or licensed; and the reverse

for the unregistered and unlicensed. Skills constitute a major constraint only for the tax

registered or licensed of the group.

99. Again, let us hypothesize that we chose start-up micro-employers as a priority target for a

business support scheme limited to the group’s most pressing need. The focus of the scheme

would be access to business space, not access to finance, for the tax registered or licensed; and

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the reverse for the unregistered and unlicensed. Crime would be the third most pressing problem

for this group as a whole.

100. The complaint rate against lack of business space was larger for the tax registered or

licensed of this group than for any other group of active enterprises in the survey sample. The

complaint rate against shortage of skills also was the highest for the tax registered and licensed

of this group than for any other. Consequently, the tax registered or licensed of this group should

be the priority target for an innovative lease program for business space or a voucher program for

training in business skills. To put it another way, let’s say, for example, that we had a business

support program focused entirely on easing the business space constraint for microenterprises,

and, for some reason, we had to limit participation to sections of the sector that are most in need.

In this scenario, the tax registered or licensed among start-up active micro-employers would be

the group most in need, not the tax registered or licensed among start-up active own-account

enterprises.

101. The unregistered and unlicensed of the start-up active micro-employers also would be a

priority group of programs targeted for improving access to finance since the percentage of them

that complain of lack of access was comparable to that of any group of active enterprises.

Constraints to Youth-owned active enterprises

Businesses of young high school graduates

102. This group’s top concern is access to business space and utilities, followed by access to

finance. Because it had the highest complaint rate against access to business space, this group

would be a priority target for programs focused on improving access to space. This group also

would be a priority target of interventions to improve access to finance. The rationale would be

not because it had the highest complaint against access to finance in the survey sample (in fact it

had the third highest rate), but because it was the most productive of all groups and hence would

be a likelier source of effective demand for new financial products.

Businesses of youth who had not completed high school

103. This group’s reported top concern is lack of access to finance. The group would be a

priority target for programs to improve access to finance for a second reason: its complaint rate

against lack of access to finance was almost as high as any other group in the survey sample

including non-youth-owned enterprises of older high school graduates. The non-graduate

business owners also are one of the groups most affected by crime.

Other groups of active enterprises as constraints groups

104. Access to finance is the most complained about issue for active post-startup micro–

employers and was rated by the group as far more important than access to business space and

utilities. Lack of skills also was reported as a major constraint. This group would be a priority

beneficiary of a program for improved access to finance.

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105. The top problem of active enterprises of older high school graduates also is access to

finance. Thus, this group also would be a priority beneficiary for access to finance programs as

well as programs to strengthen access to business space and utilities.

4 Conclusion: lessons for the design of market assessments for services

106. There are two kinds of micro-businesses in Botswana today. One group sometimes is

known as “opportunity entrepreneurs” or “active entrepreneurs.” This group comprises people

who would successfully earn a living in the labor market if they chose to, but are self employed

because they are better off in business than they would be working for someone else. In contrast,

those who are alternatively referred to as “necessity entrepreneurs,” “involuntary entrepreneurs,”

or “survivalists” are self employed by default. They were rationed out of the labor market even

though they would have taken paid work at the going rate if there had been enough jobs.

Active enterprises as potential markets for BDS

107. This report on the results of the Botswana Pilot Survey of Microenterprises has

highlighted the sharp contrast that exists between the two segments of the microenterprise sector

in productivity and development potential. The degree of contrast is not surprising given the

underlying difference between the two groups in business motivation. We think that the contrast

has far-reaching implications for the scope of programs of interventions for the development of

markets in financial products and BDS tailored to the needs of the sector. The contrast suggests

that, in principle, such programs should target only businesses of active entrepreneurs, not those

of involuntary entrepreneurs. The appropriate interventions for the latter should be those relating

to markets in training programs in labor market skills. Productivity and growth patterns in the

survey data suggest that only active enterprises have a realistic chance of evolving into viable

and growth-oriented businesses that will have sustainable effective demand for these financial

products and BDS over the long term.

108. Nevertheless, the subpopulation of active microenterprises is extremely heterogeneous in

enterprise capabilities and constraints. This diversity may need to be taken into account in the

design of public investment programs to develop markets for financial products and BDS

tailored to the needs of the sector. Indeed, it may be advisable to concentrate initial investments

in the participation of the more promising of segments of the subpopulation in the evolving

markets. The report has identified such segments via characteristics of both businesses and their

owners.

More promising active enterprises

109. An analysis of the relative productivity of many of these segments suggests that youth-

owned active enterprises in general, and those of young high school graduates in particular,

constitute the most promising group on which to focus initial efforts at developing markets for

financial products and BDS . The second most promising group of active enterprises identified

by owner characteristics is that of businesses of older high school graduates. Youth-owned active

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enterprises and active enterprises of older high school graduates constitute 13 percent and 9

percent, respectively, of the pilot survey sample.

110. Youth-owned active enterprises largely overlap what we have termed “start-up active

enterprises,” defined as active enterprises that came into existence within the last five years.

Start-up active enterprises are as promising and productive as active enterprises of young high

school graduates. This finding is not surprising since high school graduates account for a high

proportion of start-ups. Initial public investments in the development of markets for financial

products and BDS probably should also concentrate on inducing the participation of start-up

active enterprises. A minority of these are own-account enterprises, but 75 percent of them are

micro–employers (engage 2–4 people). The second most promising group of active enterprises

identified by business characteristics is that of post-startup active micro-employers. Start-up

active enterprises and post-startup active micro-employers constitute 13 percent and 10 percent,

respectively of the sample. Together, they overlap the combined subsamples of youth-owned

active enterprises.

111. Thus, the basic message of this report is that intervention programs for the development

of markets in financial services and BDS for microenterprises initially should target youth-

owned active enterprises. This group constitutes approximately 13 percent of the pilot survey

sample and overlaps almost exactly the subpopulation of start-up active enterprises. The second

most promising target of the programs should be active enterprises of older high school

graduates. This second group constitutes approximately 9 percent of the sample and more or less

coincides with the subsample of post-startup active micro-employers. Only to the degree that

programs have reached these first and second most promising groups are they likely to succeed

in extending markets and services to a third group of active microenterprises, namely, post-

startup own-account active enterprises. Essentially, they are active enterprises of older owners

who did not graduate from high school and constitute approximately 4 percent of the pilot survey

sample.

112. Thus, the maximum initial target that public investment in the development of markets in

financial products and BDS should aim to reach in Botswana is probably no more than 26

percent of the population of microenterprises. This estimate assumes that the proportion of active

enterprises of the pilot survey sample is a reliable proxy for the true proportion of active

enterprises in the national population.

Involuntary enterprises

113. If a given mix of financial products and BDS does not eventually find a ready market in

active microenterprises, it is extremely unlikely to find a market in the involuntary

microenterprises, which constitute as high as 75 percent of micro-businesses in the country. The

report shows that, controlling for observable human capital variables of owners, location, and

line of business, involuntary enterprises consistently underperform active entrepreneurs in both

productivity and growth by very large margins.

114. More than providing BDS, the policy challenge that the population of involuntary

entrepreneurs poses is probably integrating the younger among them in the formal labor market

through training and skills development schemes. In this context, it is very significant that this

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subgroup of business owners is overwhelmingly dominated by young people. Approximately 68

percent of the group are aged 29 years or less. The youth of this group means that, in principle,

the majority are trainable in new labor market skills.

115. This conclusion is reinforced by the fact that approximately 49 percent–51 percent of the

group have been in business for fewer than 5 years, and are own-account workers. These factors

may mean that they are not too locked into their current occupation to join or rejoin the formal

labor market. This leaves approximately one-third or less of the group who have been in their

current occupations for too long and probably are too old to be retrained for a labor market

career. These workers probably would benefit more from business support schemes than from

schemes for labor market training.

116. The question is really whether the businesses of this last group are dynamic and

productive enough to ultimately provide effective demand for micro-financial products and

micro-BDS. Unfortunately we do not have the data needed to answer this question. What we can

say at this point is that active enterprises in general, and certain segments of them in particular,

are far more likely to eventually provide the market for these products and services than any

involuntary enterprises. If public investments in developing these markets have to be prioritized

to enterprises in which the return to the efforts is most likely to be positive, then priority should

be given to investing in the participations of active enterprises in the markets over investing in

the participation of involuntary enterprises.

Youth-owned active enterprises as a constraints group

117. The survey shows that as potential markets for new financial products and BDS, youth-

owned active enterprises rate lack of access to financing, business space and utilities, and skills

as major constraints to business development. However, the weight they attach to each of these

constraints relative to the others depends on the business owners’ education. For example,

business space and access to public utilities is the top concern for active enterprises of high

school graduates and is followed by access to finance as the second most important issue of

concern for that group. Although it rates skills and security of property as important issues as

well, this group is far less concerned about either of these two issues than other active

enterprises.

118. In contrast, businesses of active young entrepreneurs who had not completed high school

form the group that is most affected by the skills constraints and by property crime.

Nevertheless, both of these come second and third behind access to finance as the top of the list

of concerns of this group.

Active startups as a constraints group

119. Looking at differences in needs from another perspective, namely, across the age groups

of businesses rather than the age groups of their owners, we see a high degree of interaction

between the tax registration and licensing status of active enterprises and the relative weights that

their owners attach to different constraints to business development. In particular, as the more

promising age group of active enterprises, active startups that are registered for tax or hold a

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license are more likely to be constrained by business space and access to public utilities than they

are by financing, although both constraints top their list of concerns.

120. In contrast, access to finance is more of a constraint than lack or shortage of business

space and utilities for active startups that are not registered for tax and do not carry a business

licenses. Active startups also are the group that is reportedly most constrained by lack of skills.

This is true both of own-account startups and start-up micro-employers, but with significant

difference in the relative weight given to this particular constraint by tax registration and

licensing status within each group. Among start-up micro-employers, those registered for tax or

holding licenses are far more likely to be affected by the skills constraint than the unregistered

and the unlicensed. Conversely, among own-account start ups, the skills constraint is felt more

strongly by the unregistered and the unlicensed.

Formalization and access to services

121. Priority needs vary by tax registration and licensing status because whether a business is

formal is an important determinant of its access to markets and services. In particular, formal

businesses are more likely to have better access to finance, more likely to operate from

nonresidential business premises connected to public utilities, and less exposed to property crime

(probably because of the better location of their activities and assets). Moreover, formal

microenterprises are far more productive than informal ones, in part because of their better

access to services. Thus, there is some evidence that improving microenterprises’ access to BDS

may need to encourage formalization by removing some of the impediments to registration that

survey respondents cited.

122. The most common reasons that respondents gave for not registering their businesses

included the desire to avoid four things: paying taxes, compliance with labor laws, prohibitive

registration fees, and the cost of compliance with other aspects of business regulation.

Respondents who cited any of these reasons recognized that the lack of official status and

recognition that not having registered or not holding a license entailed also would bar them from

access to key services and markets. The reason that they did not register regardless was that they

did not think that there were attractive enough services and products whose value would

outweigh the anticipated costs of becoming and staying registered or licensed.

Toward markets in financial products and BDS for active microenterprises

123. The information that the pilot survey has generated on the various capability and

constraints groups of microenterprises will be useful input to future efforts to make available

new financial products and new BDS to active microenterprises in Botswana. An essential

component of the efforts will be a formal assessment of the market for existing and potential

products and services among the two most promising groups of active enterprises identified in

this report. They are active startups and active youth-owned enterprises, with a particular focus

on micro-employers and businesses owned by young high school graduates.

124. The Donor Committee (2001) guidelines define the scope for formal market assessments

to include four analytic tasks: (a) evaluate a target group’s awareness and willingness and ability

to pay for existing products, (b) evaluate the group’s willingness to pay for potential products,

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(c) assess the extent of segmentation of the wider markets for existing or potential products that

the group may be supported to participate in, and (d) assess the potential for crowding out private

demand or supply by public interventions in markets. The main findings of this report will be

useful input to the design of tasks (a) and (b). The tasks will require much more data on each

constraints group than has been generated by the pilot survey. The additional data will have to be

collected through focus group discussions with microenterprise owners within each group, more

open in-depth interviews with enterprise owners and BDS providers, market observation, and

focused market surveys (SEEP Network 2005). These methods also would be useful in

generating much of the information needed for tasks (c) and (d) of a formal market assessment.

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References

Committee of Donor Agencies for Small Enterprise Development. 2001. “Business Development

Services for Small Enterprises: Guiding Principles for Donor Intervention.” World Bank.

Gelb, A., T.A. Mengistae, R. Ramachandran, and M. Shah. 2009. “To Formalize or Not to

Formalize? Comparisons of Microenterprise Data from Southern and East Africa.”

Center for Global Development Working Paper 175. July.

Government of Botswana. 2008. “Labor Force Survey Report 2005/2006.” Central Statistical

Office. Gaborone.

_____. 2009. “Informal Sector Survey Report.” Central Statistical Office. Gaborone.

SEEP Network. 2005. International Labour Organization. www.seepnetwork.org