Pakistan Rural Investment Climate Survey

Background and Sample Frame Design

By

Innovative Development Strategies (Pvt.) Ltd

Islamabad

(2006)

This paper is prepared under contract with DFID for the South Asia Region Rural Development

Department of the World Bank Washington DC

List of Contents 1 Introduction 1 2 Review of Literature 2 3 An Overview of Rural Non-farm Sector in Pakistan 5

3.1 Defining the Non-Farm Sector 5 4 4.1

Nature of Rural Non-Farm Sector in Pakistan Evidence from Labour Force Survey

9 9

4.1.1 Informal Sector in Rural Pakistan 12 4.2 Evidence from the Survey of Small and Household Manufacturing

Industries. 14

4.2.1 Employment Size and Industrial Establishments in Rural Pakistan 15 4.2.2 Size of Fixed Assets and Industrial Establishments in Rural Pakistan 16 5

Conclusion Investment Climate Assessments Pakistan Rural Investment Climate Survey: Sampling Strategy Sample Selection Procedure

17 17 20 20

References 22

Annex 1 25

1

1. Introduction:

Rural areas of Pakistan are characterized by higher incidence of poverty, lower levels of

literacy, poor health status, low access to basic services and amenities, and higher levels

underemployment as compared to the Urban areas. Nearly 68 percent of total population

lives in rural areas. Among them 39 percent do not have enough income to fulfill their

basic needs. Poverty in Pakistan is overwhelmingly a rural phenomenon. Although rural

development has generally been considered synonymous with agricultural growth, yet

one can observe obvious paradoxes in the Pakistani context whereby high agricultural

growth has been accompanied with rising poverty levels. It is obvious that high aggregate

growth is a necessary but not sufficient condition for poverty reduction. Sustainable

poverty reduction requires that benefits of growth must transfer to the poor either directly

through increased employment and incomes or indirectly through improved social

services. About 60 percent Pakistan’s rural poor are landless; most of these (45 percent of

the total rural poor) are non-agricultural households, with landless agricultural laborers

making up the remaining 15 percent of the rural poor. Unfavorable labour-land-ratio

limits the income-earnings opportunities in agriculture. Therefore, agricultural growth

and associated growth linkages can play an important part in raising real incomes of these

households. In addition, a rapid reduction in rural poverty also requires sustained growth

in the rural non-farm economy even apart from these agricultural growth linkages.

The non-farm sector in rural areas is an important source of secondary employment for

the small and landless farmers. Sen (1996) has shown the greater importance of non-farm

occupations for the landless and functionally landless group with land-size up to 0.5 acres

in Bangladesh. He notes that the households who managed to participate in non-farm

activities have low incidence of poverty than their counterparts in farm occupations. Non-

farm activities can generally be categorized into two broad groups of occupations: “high-

labour-productivity” that leads to high-income activity, and “low-labour-productivity”

activities that serve only as residual source of income [Lanjouw (1999)]. However,

because of their low human capital endowments and lack of physical and financial

capital, the latter activities are more common among the poor.

In many developing countries the rural non-farm sector predominantly comprises of

displaced agricultural workers with low levels of education and technical training. Most

of these countries suffer from high levels of adult and youth illiteracy due to poor

educational infrastructure. Expected mean years of schooling in many countries are less

than 10 years [WDI (2003)]. Primary completion rate and average years of schooling are

lowest in South Asia. In addition, these countries are far behind in skill development

through technical training. Natural and applied sciences constitute a very small portion of

the total tertiary enrollment. Similarly the number of R&D scientists and technicians per

1000 population is dismally low. Females are even more under represented in the

working professionals despite the fact that they account for almost half of the population.

These indicators demonstrate low levels of human capital stock in many developing

2

countries, especially in South Asia. This low level of human capital translates into low

productivity rural enterprise that requires little skill and minimal education.

The non-farm sector absorbs a large number of rural labour force in various activities

such as, industry, trade/business, craft, and services and thus plays an important role in

increasing employment and income. Rola-Rubzen and Hardaker (2003) pointed out the

widespread presence of all these activities in many Asian countries. Rural non-farm

activities cannot be viewed as a single set of activities since various non-farm activities

differ widely from each other both in terms of the returns they provide as well as the

entry requirements. For example, higher returns in wage as well as self-employment are

associated with higher levels of education and technical training. Adams (1993), for

example, divided the non-farm sector into different economic activities. Based on data

from Pakistan, he concluded that the poor mainly depended on unskilled labor and self-

employment as major income sources. Hence unskilled labor served as inequality

decreasing source of income whereas government employment exacerbates inequality.

The main purpose of this paper is to examine the nature of rural non-farm sector in

Pakistan. This paper is based on the review of existing literature and analysis of data.

This paper uses the data of household surveys and survey of small household

manufacturing units conducted in rural Pakistan.

This paper is divided into four sections. Section two presents the review of literature. An

overview of rural non-farm sector is presented in section three. Section four presents the

nature of rural non-farm sector by analyzing the data of Labour Force Survey and Small

and Household Manufacturing Industries. Section five presents conclusions.

2. Review of Literature:

The rural non-farm sector in Asia has undergone economic evolution spanning over many

years. It is a dynamic sector that has been flourishing in different economies of the region

at a varying pace. The evolution of the rural non-farm sector comprises of numerous

stages. The rudimentary stage of this evolution is marked by the dominance of the

agricultural sector in the rural economy where mostly households produce farm as well as

non-farm goods for their own consumption. With an increase in incomes however,

consumption patterns become more diverse. This process leads to an increase in

specialization and expansion of non-farm activities. The share of agriculture in GDP has

declined over time in many developing countries. In the presence of declining

agricultural productivity and shrinking employment opportunities for agricultural labor,

the rural non-farm sector presents a lucrative option for both the landless as well as small

farmers. The growth of this sector, however, largely depends on the growth of

agricultural sector. Various non-farm activities are related to agriculture, such as agro-

processing industries/establishment, activity related to farm machinery, or transportation

of farm products.

Several studies show the increasing dependence of rural people on non-farm activities in

developing countries. Many studies highlighted the importance of the rural non-farm

3

sector in alleviating poverty through its linkages with the agricultural sector. [Mellor

(1976); Vaidyanathan (1983); Hazell and Haggblade (1993); Adams and He (1995);

Bakht (1996); Sen (1996); Lanjouw (1999); Lanjouw and Lanjouw (1995); Lanjouw and

Shariff (2002); Davis (2003)]. Yusuf and Kumar (1996) explored the preconditions for

the emergence of rural industry as a leading sector in Bangladesh. This study highlighted

the importance of location,; the contribution of transport and communication

infrastructure to rural industrialization; the advantages of adopting an export orientation

and of seeking foreign direct investment; and the potential developmental role of local

governments for a developed rural economy.

Lanjouw and Shariff (2002) examined the correlates of employment in the non-farm

sector and impact of a growing non-farm sector on agricultural wage rates in rural India

using the data on 32,000 households in 1,765 villages in 1993-94. This study found that

non-farm incomes account for a significant proportion of household income in rural India

with considerable variation across quintiles and across major Indian states. Education,

wealth, caste, village level agricultural conditions, population densities and other regional

effects influence in determining the access to non-farm occupations. this study suggests

to focus the efforts on removing the barriers to the entry of the poor into the non-farm

sector. This involves improving the educational level in rural areas. Second, the policy

makers should note the strong evidence of an impact on agricultural wages of the

expansion in rural construction employment. This study concludes that the because of the

lack of assets among poor, direct contribution of the non-farm sector to poverty reduction

is possibly quite muted. Non-farm sector is considered as more productive sector than

agriculture because education and technical skills play an important role [Unni (1997);

Fafchamps and Quisumbing (1998) and Kurosaki and Khan (2003)].

In a very recent study conducted by Foster and Rosenzweig (2004) used survey data

covering the major states of India over the past thirty years. They examined the effects of

yield improvements associated with the green revolution on rural non-farm activities by

using a general equilibrium framework. In this study, incomes and enterprises

distinguished by whether they are in non-traded (locally financed) or traded sectors with

spatially mobile, non-local capital. Results of this study do not support the thesis that

increases in agricultural productivity are a major engine of growth in the non-farm sector.

This study identified other possible factors influencing the growth of rural non-farm

sector. For example, presence of establishments/factories in village, level of employment

in these establishments, effects of capital, proximity to town, etc. This study found that

growth in non-farm income in rural India over the last 30 years has remained substantial.

Expansion of rural industry is the major source of this growth. Factory growth is found

highest in the low-yield growth quintiles. This indicates that local generation of capital

plays an important role as an engine of growth for local non-farm activity. The results of

econometric estimation suggest that an increase in crop yields reduces the probability that

a factory employs individuals from the village and decreases the level of non-farm wage

income. This indicates that non-farm capital is mobile and seeks low-wage areas, so that

agricultural development and non-farm activities are substitutes rather than complements.

In this study agricultural development also appears to have only a negligible effect on

4

local non-farm business income. This study concludes that non-farm growth is not only a

source of overall expansion in rural incomes but also is pro-poor.

In Pakistan, agricultural sector is the largest employer in rural areas. However recent

studies show decreasing factor productivity trends in the crop sector and increased

resource degradation [see for example, Ali and Byerlee, (2002)]. Given the over

saturation of the farm sector, there has been a shift of focus towards the non-farm sector.

Adams and He (1995), for example, observe that non-farm sector was the most important

source of income in rural areas. Rural non-farm sector is dominated by informal activities

that absorb a large majority of unskilled, uneducated or less educated and poor

individuals. Because of its nature, non-farm income plays an important role in reducing

income inequality. Adams and He (1995) indicate that income from self-employment,

unskilled labor and government employment are three major sources of non-farm income.

Unskilled labor and self-employment were found to be inequality reducing and

government employment to be inequality-increasing source of non-farm income.

Variations across income groups are however noted. For example, poorest households

depend more on unskilled labour income, while self-employed income is the most

important source of income for the households in highest income group. This finding

shows direct linkages of human capital with non-farm employment. Government jobs

require a high endowment of human capital and therefore have a higher entry cost which

makes them less accessible to poor households. On the extended sample of rural

households, World Bank (2002) also observed a high dependency on non-farm sources of

income in rural Pakistan. About 44 percent of rural households were found dependent on

non-farm sources of income in 2001. Among them 40 percent belong to lowest income

group and 45 percent to the highest income group. Non-farm income forms a

considerable share of total income (73%) for landless households. This share was found

higher for households belonging to highest income groups. Wage income appeared as the

largest source of non-farm income. A large proportion of farm income comes from crop

profits, followed by wage income. This study finds that incomes groups are negatively

associated with farm wage income and have positive relationship with crop profits and

livestock income.

Arif, Nazli and Haq (2000) found that wages and salaries and self-employment income

are the major sources of non-farm income. In their sample, these categories constitute

more than 94 percent of all non-farm workers. They found a significant difference in the

nature of activities between self-employed and wage employees. For self employed,

wholesale and retail trade appeared as the most important economic activity, whereas,

wage employees were found concentrated in the construction sector. According to this

study, only construction and service activities account for two-thirds of rural non-farm

employment in this category. However, looking across poverty status, some interesting

results emerge. For example, a majority of poor wage employees is found in the in the

construction sector, followed by services sector. A reverse pattern has been found for the

non-poor wage employees. Among self-employed, wholesale and retail trade were found

to be the most important non-farm activity for both poor as well as non-poor in rural

Pakistan.

5

Malik (2004) reports that a majority of poor households derive their non-farm income

from construction sector. Construction and services sectors are the two largest employers

of rural non-farm labour force. However, construction sector absorbs unskilled and/or

low-skilled labour. Services sector, on the other hand, appeared as the most important

source of non-farm income for the better off households. In addition, wholesale and retail

trade and transport and communication also contribute significantly in the non-farm

income of households belonging to higher income groups.

3. An Overview of Rural Non-farm Sector in Pakistan

The share of agriculture in GDP has declined from 53 percent in 1949-50 to 24 percent in

2003-04. On the other hand, the shares of manufacturing, wholesale and retail trade and

services sector is increasing continuously [figure 1]. The share of agro-base industries in

all industries is 63 percent that supply 64 percent of total industrial production [Census of

Manufacturing Industries (1995-96)]. This indicates that agriculture is the deriving factor

behind the growth and promotion of non-agricultural sector and hence overall economic

growth. In addition, employment growth and average labour productivity growth in non-

agricultural sector remained higher than that in agricultural sector during 1969-70 to

2002-03. Despite a continuous decline in agricultural output, this sector still absorbs 48

percent of the labour force. Lower average labour prodivity is an indication of surplus

labour in this sector that can be absorbed by other rapidly growing sectors if and only if

opportunities are available. Now question arises what type of non-agricultural activities

prevail in rural areas of Pakistan.

Figure 1: Share of major sectors in GDP.

0

10

20

30

40

50

60

19

49

-50

19

52

-53

19

55

-56

19

58

-59

19

61

-62

19

64

-65

19

67

-68

19

70

-71

19

73

-74

19

76

-77

19

79

-80

19

82

-83

19

85

-86

19

88

-89

19

91

-92

19

94

-95

19

97

-98

20

00

-01

Agri Min&manuf constr Ret trade Services

Source: Pakistan Economic Survey (various issues)

3.1. Defining the Non-farm Sector

In order to examine the nature of rural non-farm sector, there is a need to understand how

a non-farm sector can be defined in rural settings. Some studies presented a broad

distinction between rural and urban areas, rural towns, and urban industrial cities and

6

towns. In these studies rural sector includes small and medium-sized towns whose

economic role and functions are closely and directly linked with agriculture and hence

the needs of the rural population [Anderson and Leisersons (1980); Bakht (1996)].

However, keeping in view the nature of available statistics, it is not easy to separate rural

towns from other rural or urban areas of the country. Therefore the analysis of a non-farm

sector, especially in Pakistan, is based on the narrower definition of rural, sector.

The population census uses an administrative criterion to define ‘urban’ and ‘rural’. The

definition of urban areas is not given in the 1961 census report. In 1972, urban areas were

redefined as “those areas which had municipal corporations, municipal committees, town

committees and cantonment boards”. However, other places were also treated as urban

areas. These included settlements having at least 5,000 persons in a continuous collection

of houses, where the community sense was well developed, and where the community

maintained public utilities such as roads, street lighting, water supply and sanitation.

These places are generally centres of trade and commerce, with a population mostly non-

agricultural and with a comparatively higher literacy rate. To further complicate the

picture, some villages have been designated urban areas for administrative reasons. The

1981 and 1998 censuses have followed the definition of the 1972 census. However, these

definitions are based on the Provincial Local Government Ordinance. All urban centres

are officially notified on this basis.

Municipal Corporation is constituted for a city which may comprising an urban

area having population of more than 500,000.

District Council means a Council constituted for a District. It extends over the

area of revenue District excluding its Urban Area, Cantonment Board and Federal

Area.

Municipal Committee is comprising an Urban Area having Population of 20,000

or more.

Town Committee is constituted for Urban Area having Population of more than

5,000 but less than 20 Thousands.

Union Council comprising a village or number of villages excluding its Urban

Areas and Cantonment areas.

According to the Pakistan Population Census (1998), there are 46,242 rural localities in

Pakistan. Among them, 65 percent have population less than 5,000. However, there are

3.4 percent rural localities with population more than 20,000. Similarly, among the total

515 urban localities, 5.8 percent have population less than 20,000.

In rural areas where population size is greater than 5,000, more than 60 percent of the

employed labour force involve in non-farm activities. The data of Agriculture Census

(2000) indicates 45 percent of the rural households are non-farm in Pakistan [see figure

2]. Among farm households, one-third are livestock holders.

7

Figure 2: Distribution of rural households by activity status and province

31.6

5.1

18.3

45.0

0

5

10

15

20

25

30

35

40

45

50

Households –

operate own land

Tenant households Livestock holders Non-agricultural

households

Source: Agriculture Census of Pakistan (2000)

It is interesting to note that a considerable proportion of livestock holders is involved in

non-farm activities. According to Agriculture Census (2000), 64 percent of the livestock

holders work in own household and 36 percent work for other households. Among those

who work in own household, 14 percent are involved in non-farm activities. This

proportion is 29 percent for those who work for other households. It is also important that

among agricultural households, 14 percent who work for own household and 12 percent

who work for other households are also involved in non-farm activities. This can further

be explained by looking at the distribution of households according to non-farm sources

of income. Data reported in table 1 reveals that non-agricultural labour is an important

source of income not only for non-agricultural households but also for the livestock

holders. Nearly 19 percent agricultural households also derive income from non-

agricultural labour and 12 percent from services. For non-agricultural households, income

from services and business are other important sources. It is very interesting to note that

only 9 percent households who are classifies as livestock holders derive their income

livestock. Agricultural and non-agricultural labour appeared as major sources of income

for these households.

Table 1: Sources of non-farm income: % distribution of reporting households Source of non-farm

income

Farm households Non-agriculture

households

Livestock holders

Service 11.9 22.7 8.0

Business 7.1 19.5 8.4

Livestock 3.0 0.3 9.4

Remittances 2.9 1.7 1.3

Agriculture labour 21.6 4.9 14.9

Non-agri. Labour 18.5 42.5 46.8

Rent 1.6 0.7 0.9

Poultry 0.2 0.2 0.4

Others 6.6 7.5 9.9

None 26.5 0.0 0.0

8

Source: Agriculture Census of Pakistan (2000)

At this point, it would be useful to examine the levels of poverty among households

(individuals) engaged in farm and non-farm activities in rural areas. This can be seen

through either dividing households (individual) according to landholdings and/or activity

status [Lanjouw (1999); Newman and Canagarajah (2000); Arif, Nazli and Haq (2000)].

Qureshi and Arif (1999) found a higher incidence of poverty among non-farm household

in all provinces of Pakistan based on the HIES data for 1993-94 and 1998-99. These

estimates were based on a classification of households by industrial status of the head of

the household. They found a concentration of non-farm poor in Punjab in both years.

However, Arif, Nazli and Haq (2000) based on a more detailed classification did not find

any significant differences between the levels of poverty for farm and non-farm workers1.

Arif and Ahmed (2001) examined the levels of poverty of farm and non-farm households

across agro-climatic zones for the years 1993-94 and 1998-992. They found a higher

incidence of poverty among non-farm household in all zones except in barani Punjab in

1993-94 and 1998-99. For barani Punjab a higher incidence of poverty among non-farm

households than for farm households has been reported in 1998-99 -- a pattern that is

reversed when compared to 1993-94. For 2001-02, Malik (2004) observed that poverty

among non-farm households remained higher in all zones. It is quite alarming to note a

higher and increasing incidence of poverty among non-farm households in barani Punjab.

This part of Pakistan is characterized by high integration between rural and urban areas,

strong linkages with the services sector, and long history of higher participation of

households of this region in non-farm activities in nearby towns, major urban centers or

overseas [see table 2].

Table 2: Farm and Non-farm poverty head count by agro climatic zones

1993-94 1998-99 2001-02

Agro climatic zones Farm Non-farm Farm Non-farm Farm Non-farm

Rice/Wheat Punjab 21.6 39.9 22.3 33.1 24.9 40.4

Mixed Punjab 16.9 25.8 30.5 34.6 40.9 48.3

Cotton/Wheat Punjab 19.9 31.4 35.2 44.7 42.1 55.6

Low Intensity Punjab 15.3 28.3 40.2 63.4 48.9 54.6

Barani Punjab 15.7 12.5 3.9 10.1 24.2 25.2

Cotton/Wheat Sindh 33.4 34.2 20.4 32.2 59.3 57.7

Rice/Other Sindh 25.7 27.1 19.5 14.6 60.8 53.0

NWFP 23.0 32.3 31.7 31.1 45.7 47.6

Balochistan 33.0 21.1 31.3 26.7 40.4 39.4

Source: Malik (2004)

The distribution of income across farm and non-farm activities exhibits some interesting

results. The data of Agricultural Census shows that average annual income of farm

households is 1.7 times higher than those of non-farm households. Using the data of

HIES 1998-99, Nazli (2003) found a higher average monthly income for self-employed

1 They distinguish farm and non-farm households on the basis of individual occupation instead of industrial

status of head of the household. 2 They use the definition of Qureshi and Arif (2000) to define farm and non-farm households.

9

than the paid employees both for farm as well as non-farm activities. However, no

significant difference has been found in the average incomes of own account workers in

non-farm sector and that of owner cultivator in farm sector. On the other hand, average

income of paid employees in the farm sector is found much lower than that of the non-

farm sector.

4. Nature of Rural Non-Farm Sector in Pakistan

Several prevailing approaches are found in the literature to define non-farm activities,

depending on which source of data is used for analysis. For example, Household

Integrated Economic Surveys (HIES) and Labour Force Surveys (LFS) collects

information on all employed persons about their primary and secondary occupation,

industry, and employment status. Using these data sets, in one most commonly used

approach, non-farm households are identified by the main occupation of the head of the

household. In another definition, using the same data sources, households can be

identified by industry. Livestock and agricultural services are generally considered as

agricultural activities and all other activities come under non-agricultural. Similarly,

Agriculture Census identifies agricultural households as those who are involved in farm

or livestock activities and all other households as non-agricultural households.

Household surveys provide information on the type of available agriculture and non-

agricultural activities in rural areas. These are generally divided into: agriculture/fishing;

mining and quarrying; manufacturing; electricity/gas and water; construction; trade/hotels

and restaurants; transport and storage; finance and real estate; community services; and

other activities not defined. The Federal Bureau of Statistics conducts Surveys of Small

and Household Manufacturing Industries (SHMI) in urban as well as rural areas of

Pakistan. These surveys collect data on investment in fixed assets, employment and

employment cost, value of material and fuel consumed, value of products and by-

products manufactured, and the value added generated on all un-registered household

units and small establishments irrespective of the size of employment and type of

activity. Some basic information on household and industrial surveys is presented in

annex table a.

In order to examine the existing structure of non-farm sector in Pakistan, this section

presents the analysis of data of household as well as industrial surveys.

4.1. Evidence from Labour Force Survey

According to data of Labour Force Surveys the share of agricultural employment

declined substantially from 60 percent in 1963-64 to 42 percent in 2001-02. The inter-

temporal comparison is reflective of shift away from the agriculture to non-agriculture

employment. Data indicates that manufacturing, retail trade and constructions are other

important sectors in terms of employment. Figure 3 shows that the share of employment

in manufacturing sector has declined and in retail trade has increased after 1990. Overall

employment structure represents a shift from commodity production to the services

sector. Arif and Irfan (1997) pointed out return migration from overseas, especially from

10

Middle East, is one of the major reason of changes in employment structure. A large

number of returned migrant opted for the business category.

Figure 3: Percentage distribution of employed persons in major sectors

0

10

20

30

40

50

60

70

1963-

64

1966-

67

1969-

70

1972-

73

1975-

76

1978-

79

1981-

82

1984-

85

1987-

88

1990-

91

1993-

94

1996-

97

1999-

00

2002-

03

Agriculture Min&Manuf. Const. Elec&gas Trade

Source: Pakistan Economic Survey (various issues)

As mentioned earlier, agriculture sector is the largest employer of rural labour force in

Pakistan3. In 1982-83, 68 percent of employed persons were engaged in this sector. This

proportion has declined to 59 percent in 2001-02. Nearly 41 percent labour force was

employed in non-agricultural activities, such as, manufacturing, construction, wholesale

and retail trade, transport and communication and social services sectors [see annex table

1]. This pattern has not changed over time except minor fluctuations, for example, the

share of employed persons in manufacturing sector has declined and in construction has

increased. This is reflected in the slow growth of manufacturing sector and high growth

of construction sector in recent years.

This data indicates that most of the rural non-farm employed persons work as either

unskilled labour or craft workers. Looking at the distribution of employed persons across

industrial establishment, it has been observed that in agriculture most of the individuals

(71%) are skilled workers. Manufacturing sector is dominated by craft persons and

wholesale and retail trade is mostly governed by the managers [see annex table b].

Employment status indicates that non-farm sector consists of own account workers4.

Labour Force Survey 2001-02 indicates that the majority of rural employed persons are

working as self-employed (42%), followed by wage employees (31%) and unpaid family

workers (26%). However, looking at non-farm sector only, it has been found that a larger

proportion of employed persons is working as paid employees (59%), followed by self

3 Federal Bureau of Statistics defines an employment person as the one who participates in income/profit

generating activities irrespective of his/her employment status. 4 Labour Force Survey defines own account worker is a person who operates his/her own enterprise or

engages independently in a profession or trade and hires no employee. However, he/she may get assistance

of unpaid family workers

11

employed (32%). Proportion of unpaid family workers is found only 8 percent. Labour

Force Survey describes four categories of paid employees as: regular wage employees,

casual wage employees, paid at piece rate and non-family apprentice. The proportion of

causal and piece rate employees was more than half of the total wage employees in 2001-

02. The distribution of employed persons across industrial establishment indicates that a

majority (59%) of the regular wage employees is concentrated in services sector and most

of the causal employees (53%) are in construction sector. Piece rate workers are found

either in construction (32%) or in textile manufacturing (27%). Nearly 50 percent of the

self-employed are in wholesale and retail trade. Majority of unpaid family workers is

concentrated in whole and retail trade (39%), followed by household and personal

services (17%) and textile manufacturing (13%) [see annex table c].

The Labour Force Survey asks question about the location of enterprise where an

individual works. Overall 73 percent employed persons are found working in the

establishments located in rural areas. However, a larger proportion of workers working in

finance and insurance, electricity and gas, manufacturing, transport and communication,

and social services reported they work in urban areas. However, surprisingly only 21

percent workers of construction sector reported to work in urban areas. While this sector

is highly dominated by the rural workers. This may be due to the definition of household

members in the household surveys. A household is defined to be constituted of all

persons who usually live together and share their meals. Since most of the construction

workers live in cities where they find work, therefore they are not counted as member of

the household in a village.

Table : Location of the enterprise as indicated by the employed persons in rural Pakistan

(2001-02)

Urban Rural Total

Mining 1.63 98.37 14,353

Food manufacturing 28.56 71.44 218,968

Textile manufacturing 25.52 74.48 950,801

Wood & paper manufacturing 21.49 78.51 188,959

Chemical, metal/nonmetal 18.44 81.56 433,356

Other manufacturing 44.13 55.87 80,273

Electricity & gas 46.21 53.79 122,487

Construction 21.19 78.81 1,351,940

Wholesale & retail trade 18.06 81.94 1,994,569

Transport & comm 36.39 63.61 1,047,583

Finance & insurance 64.79 35.21 64,785

Social services 26.60 73.40 1,526,410

Household/personal services 19.50 80.50 892,554

Total 24.39 75.61 8,887,038

Source: Labour Force Survey (2001-02)

4.1.1. Informal Sector in Rural Pakistan:

Labour absorption has declined in many sectors due to the increasing reliance on capital

intensive techniques. The formal sector generally demands educated and skilled

manpower. A large proportion of Pakistan’s population consisting of the uneducated and

12

the unskilled labour force therefore, tend to seek jobs in the informal sector. The informal

sector as defined by the structure of the organisation and the size of the establishment

includes family enterprise/industrial establishment with less than 10 workers and non-

industrial establishments with workers not more than 20.

Various independently conducted studies in the cities of Pakistan, categorize the informal

sector workforce as consisting of self-employed, regular workers, family helpers and

shagirds. This is also true for the rural informal sector. Using the latest data of Labour

Force survey, Ginnari (2004) presented a detailed analysis of Pakistan’s informal sector.

He found a substantial contribution of the informal sector to GDP, especially wholesale

and retail trade accounted for over half of the total value added of the industry. The

sectors transport & communications and in social, community & personal services also

contribute significantly in GDP.

According to the Labour Force Survey (2001-02), about two-third (64.6%) of the non-

farm employed labour force were engaged in informal sector activities. In rural area the

percentage of employed involved in informal sector (68.3%) was higher compared to

urban areas (61.1%). As expected formal sector activities were more concentrated in

urban areas (38.9%) compared to rural areas (31.7%). Using the same dataset, Ginnari

(2004) also observed that employment in informal sector in rural areas is considerable as

compared to the employment in informal enterprises located in the countryside.

According to the findings of this study, nearly half of the informal sector workers work

either in private dwellings or on the street.

This sector is composed of either self-employed or wage employees. The proportion of

unpaid family helpers is very low in the informal sector as compared to the agricultural

sector [Figure 4].

Figure 4: Percentage distribution of employed persons engaged in informal sector by

employment status in rural Pakistan (2001-02)

Employer

1%

Self employed

45%

Unpaid family

helper

10%

Employee

44%

Source: Labor force survey (1999-00) and (2001-02)

13

The proportion of female workers is only 8 percent in this sector. In this sector, a

majority of males was found involved in wholesale, trade and related work as managers

while females in manufacturing sector as craft and related workers. As has already been

argued, this is basically a result of low levels of skills and capital as well as cultural

inhibitions faced by female workers. The data reveals that most of the non-farm

establishments in rural Pakistan are informal except those belong to electricity and gas,

finance and insurance social services and mining [see table 3]. All other sectors including

manufacturing, construction, transport and communication, etc are predominantly

informal.

Table 3: Percentage distribution of formal and informal establishment by type of industry

in Rural Pakistan (2001-02)

Industrial establishments Formal Informal Total

Mining 89.70 10.30 29

Food manufacturing 25.40 74.60 185

Textile manufacturing 29.80 70.20 738

Wood & paper manufacturing 11.20 88.80 143

Chemical, metal/nonmetal 56.20 43.80 338

Other manufacturing 33.80 66.20 68

Electricity & gas 98.30 1.70 120

Construction 15.70 84.30 1,220

Wholesale & retail trade 2.10 97.90 1,814

Transport & comm. 21.70 78.30 980

Finance & insurance 46.40 53.60 56

Social services 83.10 16.90 1,486

Household/personal services 5.60 94.40 716

Total (%) 30.20 69.80

Total (#) 2,383 5,510 7,893

Source: Labour Force Survey (2001-02)

Informal sector is characterized by long working hours and low wage rate. The data of

Labour Force Survey 2001-02 shows that average working hours per week in the

informal sectors are 50; 52 for males and 37 for females. Among working females in this

sector, 40 percent work 25-39 hours and 21 percent work 42-48 hours per week. The data

of Labour Force Survey allows calculation of weekly income for males and females

separately. This variable reveals very obvious gender disparity in the monetary reward

for an equal length of work [see table 4]. There are significant differences not only within

sectors but also across genders. On average males get higher reward in both formal as

well as informal sectors than females. In the informal sector, this difference is highest for

the working group 15-24 hours and 40-48 hours. This however, essentially

underestimates the actual working hours of females since it does not include the time they

spend in conducting their daily household chores. Also, when remunerative work is done

within the boundary of the household, it ends up being treated as part of ‘female work’

like the regular household chores of cooking, washing etc. And not always does it carry

the respect or empowerment that entails working in the formal sector. The following

section attempts to take this statistical bias into account and estimates the monetary value

of what is generally considered as female housework.

14

Table 4: Weekly income by working hours, gender and formal/informal sector (2001-02) Groups of working

hours

Formal sector (Rs/hour/week) Informal sector (Rs/hour/week)

Males Females Males Females

15-24 hours 316 186 184 117

24-34 hours 697 534 233 159

35-39 hours 740 507 191 189

40-48 hours 718 582 366 241

49-55 hours 409 309 264 189

56 and above 420 463 291 251

Source: Computed from Labour Force Survey (2001-02)

Distribution of total rural income across establishments in formal and informal sectors

reveals some interesting results. For example, nearly 55 percent of the total rural income

in the formal sector is generated by the services sector alone. Whereas construction, and

transport and communication sectors generate most of the rural income in the informal

sector income. Similarly wholesale and retail trade exhibit longest working hours in the

informal sector and same is found true for the social services in the formal sector.

4.2. Evidence from the Survey of Small and Household Manufacturing Industries

According to Factory Act 1934 of Pakistan, all establishments employing more than 10

persons should register. The Census of Manufacturing Industries (CMI) collects data on

registered firms and the survey of Small and Household Manufacturing Industries

(SHMI) covers all un-registered household units and small establishments irrespective of

the size of employment and type of activity. According to the latest CMI and SHMI,

there are approximately 400,000 manufacturing units in the country. Among them only

1,000 are reported to employ more than 100 persons. Less than 10,000 units are

registered under the Factories Act of which barely 5,000 are functioning and traceable.

Thus by any definition approximately 99 percent of the manufacturing units are small and

household. Furthermore nearly 40% of the small and household manufacturing units

operate from owners dwelling and are therefore treated as household manufacturing units.

The reported number of average employees in each of the three types of manufacturing

units is also quite revealing. On average there are 2 persons per unit in household

manufacturing units, 2.6 persons per units in small establishments and 126 persons per

unit in large manufacturing establishments [for details see Gallup (2004)].

This section presents the results of SHMI conducted in rural Pakistan during 1983-84 and

1996-97. The data of these surveys indicate a decline in household units and an increase

in small establishments during 1983-84 to 1996-97 in rural Pakistan [see table 5].

However, looking across provinces, this table shows an increase in household units and a

decline in small establishments in Sindh and Balochistan whereas a reverse pattern

observed in Punjab and NWFP.

15

Table 5: Percentage distribution of household units and small establishments in rural

Pakistan by Provinces

Household units (%) Small establishments (%)

1983-84 1996-97 1983-84 1996-97

Punjab 61.66 51.61 38.34 48.39

Sindh 42.68 59.01 57.32 40.99

NWFP 39.45 23.47 60.55 76.53

Balochistan 14.29 92.65 85.71 7.35

Pakistan 56.70 49.64 43.30 50.36

Source: SHMI (1983-84 and 1996-97)

4.2.1. Employment Size and Industrial Establishments in Rural Pakistan

As indicated above that average employment size in household units is 2 persons per unit

and 2.6 persons per unit are reported for small establishments. Table 6 reveals that

persons per unit in small establishments remained unchanged during 1983-84 to 1996-97

whereas in household units a rise of 14 percent is observed. This table shows that

employment size of household units has increased in all provinces except in Balochistan

and in small establishments declined in Sindh and NWFP.

Table 6: Persons per unit by type of establishment and province in rural Pakistan

Household units Small establishments

1983-84 1996-97 1983-84 1996-97

Punjab 1.72 2.02 2.34 2.52

Sindh 2.05 2.51 2.38 2.24

NWFP 1.66 2.04 3.72 3.01

Balochistan 1.79 1.26 1.82 2.84

Pakistan 1.73 2.02 2.61 2.62

Source: SHMI (1983-84 and 1996-97)

It has also been found that nearly 70 percent of the employed persons are engaged in 10

industries. In 1983-84, about 18 percent of total employed persons are found engaged in

“woolen carpets”. This proportion is declined to 10 percent in 1996-97. “Wheat &

milling” and “tobacco stemming” were on the top in 1996-97 in terms of employment.

Highest number of persons per unit (16) is found in “brick &tiles” followed by “tobacco

stemming” (15.3).

The data shows that 73 percent of total units employ 40 percent of total employed

persons. These are the units with 2 or less persons per unit. More than three-fourth of

household units and two-third of small establishments reported to have 2 or less persons

per unit [see table 7]. The data of SHMI (1996-97) shows that the proportion of paid

employees is only 25 percent; 10 percent in household units and 39 percent in small

establishments. It is interesting to note that almost 99.5 percent of total paid employees of

household units are found only in Punjab. The proportion of paid employees in small

establishments is found higher in Punjab and NWFP (56% and 37% respectively). This

indicates that most of the industrial units are small in nature and mostly operated by self-

employed persons who are classified as “own account workers”.

16

Table 7: Percentage distribution of industrial units and persons employed by size of

employment in rural Pakistan (1996-97)

Employment

size

Household units Small establishments Total

Units (%)

Employed

persons (%) Units (%)

Employed

persons (%) Units (%)

Employed

persons (%)

1 person 36.69 18.17 37.64 11.06 37.17 13.68

2 persons 39.13 38.75 32.32 19.00 35.70 26.29

3 persons 15.54 23.08 10.01 8.83 12.76 14.09

4 persons 5.93 11.74 5.13 6.03 5.53 8.14

5 persons 1.53 3.79 2.39 3.51 1.96 3.62

6-7 persons 0.80 2.47 3.17 5.95 1.99 4.66

8-9 persons 0.27 1.19 2.11 5.32 1.20 3.79

10 persons

and above 0.11 0.82 7.22 40.30 3.69 25.73

Pakistan 100.00 100.00 100.00 100.00 100.00 100.00

Source: SHMI (1996-97)

4.2.2. Size of Fixed Assets and Industrial Establishments in Rural Pakistan

Size of fixed assets is an important indicator to know the nature of an industrial unit. The

data of SHMI (1996-97) reveals that the value of fixed assets of 24 percent household

units is zero and that of 63 percent is not more than Rs 3,000. On the other hand, 45

percent of the small establishments have fixed assets of the value of more than Rs.

50,000. Figure 5 shows that the household units with larger values of fixed assets are

very few. Reverse is found true small establishments.

Figure 5: Distribution of industrial establishment by size of fixed assets (1996-97)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

No ne up to Rs

1,000

1,001 to

3,000

3,001 to

5,000

5,001 to

10,000

10,001 to

25,000

25,001 to

50,000

50,000 to

100,000

100,001 to

500,000

hhold units small estab

Source: SHMI (1996-97)

Most prominent fixed asset in both household units and small establishments is plant and

machinery. However, for small establishments land and building are equally important

assets.

17

Now question arises what are the sources of finance of these fixed assets and working

capital. SHMI (1996-97) reports that the predominant source of finance in household

units is own resources (91%), followed by friends and relatives (8.7%). Only 0.1 percent

are financed through non-bank finance institutions. Almost same pattern is observed in

small establishments with the exception that 1 percent funds are financed by the

commercial banks.

5. Conclusions:

The analysis presented here indicates diverse prevailing non-farm activities in rural areas

of Pakistan. However, the poor tend to be concentrated in low productivity activities that

demand low levels of skill and little education. Most of them are found in the activities

that involve minimum investment since they lack the resources to invest in high

productivity self employment or wage work. Better off households in the non-farm sector

invest in high productivity self-employment activities that demand high physical capital

or engage in wage work that has high returns and requires high levels of human capital.

In all Pakistan, approximately 99 percent of the manufacturing units are small and

household. Furthermore nearly 40 percent of the small and household manufacturing

units operate from owners dwelling and therefore treated as household manufacturing

units. The share of employment in rural non-farm informal sector in total non-farm

employment is 68.3 percent. In this sector, 47 percent individuals are illiterate and 39

percent have education less than 10 years. A majority of employees is concentrated in the

social services sector and self-employed in wholesale and retail trade. 35 percent formal

sector workers and 20 percent informal workers report their location of work is a urban

locality.

Evidence indicates that the households with higher levels of human capital stock also

have had more stable income and consumption patterns as compared to those who have

lower levels of human capital stock. It has been found that the poor households have

lower levels of literacy, poor health status, limited access to basic services and amenities,

and higher levels of unemployment and underemployment. In order to cope with disaster

and resultant income shocks, income diversification is needed [see Malik(2004)]. A well

functioning and developed rural non-farm sector is the best solution for income

diversification. A favourable investment climate in rural areas assures economic growth

and sustainable poverty reduction. In order to examine the current state of investment in

rural areas, an investment climate survey is needed that can help in identifying the

constraints on investment and growth in this key sector.

Investment Climate Assessments

The World Bank and the Asian Development Bank are undertaking a series of Investment

Climate Assessments (ICAs) based on a representative survey of national enterprises in

many developing Asian countries. The findings of these surveys presented in this section.

18

Dollar, Hallward-Driemeier, and Mengistae (2003), examined the investment climate by

investigating the relationship between infrastructure and international integration in

Bangladesh, Brazil, China, Honduras, India, Nicaragua, Pakistan, and Peru, with the help

of firm-level surveys conducted in these countries. This paper finds that firms experience

bottlenecks and delays in hard infrastructure such as power and telecom as well as in soft

infrastructure such as customs administration. For example, in Karachi problems are

observed to move goods through customs and to get reliable power or telecom services.

Similar problems, though not as extreme, are found in the port cities of Calcutta and

Chittagong. International integration is found higher in the countries where investment

climate is good. In order to take the advantage of opportunities in the international

market, good infrastructure and a sound regulatory environment is needed. In this regard,

the role of government in providing a good regulatory framework for infrastructure,

access to the international market, and finance is highlighted.

The World Bank Group in collaboration with the Confederation of Indian Industries

prepared an investment climate assessment by conducting a survey of more than 1,000

large-scale firms in 2003. This survey finds that Indian firms are potentially competitive.

However, n practice this potential competitiveness is offset by investment climate

bottlenecks. This survey identified three major bottlenecks: First, excessive regulation of

entry and exit; second, the availability and quality of infrastructure services; and third,

regulatory burden, governance, and corruption. The investment climate in India is found

comparatively weak than other emerging market economies such as China or Thailand.

Differences across states in India appeared significant. For example, investment climate

indicators are found poorer in states such at Uttar Pradesh and West Bengal, compared to

better climate states such as Andhra Pradesh, Gujarat, Karnataka, Maharashtra, and Tamil

Nadu. This study observes that if each Indian state could attain the best practice in terms

of regulation and infrastructure, the economy should grow about 2 percentage points

faster. The gains would be particularly large in the poor climate states. This report

concludes that removing bottlenecks that prevent efficient infrastructure services and

private initiative would lead to faster growth and poverty reduction in India.

The World Bank and Bangladesh Enterprise Institute conducted an investment climate

assessment in Bangladesh based on the data on manufacturing industries in 2002. Six

industries were included in the survey: garments, textiles, food and food processing,

leather and leather products, electronics, and chemicals and pharmaceuticals. The survey

collected data from a total of 1,001 firms in Dhaka (and surrounding areas) and

Chittagong. This report points out several features of the investment climate in

Bangladesh that require urgent attention for the growth of economy, such as, physical

infrastructure, governance, and the financial system. This report finds that small- and

medium-size enterprises have suffered more from the deficiencies in these areas than

large companies. At the same time, companies able to export have performed better than

companies that do not export. Yet without meaningful reforms in infrastructure,

governance, and finance, entering the export market will be difficult for small- and

medium-size enterprises. In infrastructure, power is found on the top for immediate

concern. In addition, reforms in telecommunications, transport, and ports and customs are

also suggested for improving the investment climate. In order to deal with the problem of

19

governance, a greater flow of information, enforcement of clear rules and regulations for

public sector administration, promotion of participation of civil society, are the suggested

measures. To make easy access to finance, this report proposes an independent banking

sector with enhanced regulatory authority.

In Sri Lanka, the Investment Climate Survey was conducted in 2003-04, covered the

manufacturing sector in rural and urban areas. This rural survey covers 1,327 non-farm

enterprises and 555 households not participating in rural non-farm activities. Most of Sri

Lanka’s rural enterprises are based outside the home and are primarily engaged in

manufacturing or trading with a far smaller proportion involved in service related areas.

These enterprises are small with an average employment of 2.4 workers, including family

members. Despite differences in the urban and rural investment climates, the poor quality

of infrastructure, especially energy and transport, and finance is found to be the major

obstacles to both urban manufacturing and rural enterprises. More than half of rural

enterprises are found registered. Access to electricity is cited as a top constraint and

represents an entry barrier and a significant operational cost to both rural and urban firms.

Transport constitutes the single most important constraint to rural and urban firms to start

or operate a business and to the expansion of tourism. Almost one-third of urban firms

and two-thirds of rural businesses reported the cost of finance as a major constraint. Rural

enterprises avail themselves of external finance but access to formal finance is found

extremely limited. Collateral plays a vital role in the availability of financing. Rural

entrepreneurs are found constrained by limited access to regional markets. Poor

transportation and telecommunications also limits the access to information. It has also

been found that rural enterprises are not effectively integrated into the policy-making

process and that government could do more to improve mechanisms to ensure greater

voice for rural entrepreneurs. This study recommends that to improve the access to and

the quality of energy and transport’ to reduce the cost of finance and improving access; to

improve labor market flexibility in urban areas and to improve access to major markets in

rural areas; to improving policy certainty and macroeconomic stability in urban areas.

In Pakistan, Investment Climate Survey was conducted jointly by SMEDA and the World

Bank in 2002. This survey covered 965 formal sector firms in key manufacturing and

exporting industries selected from twelve locations in all four provinces across Pakistan.

80 percent of these were non-exporters and 97 percent were owned by domestic owners.

Sales of these firms are mostly domestic (85%). This proportion is comparatively higher

than neighbouring countries like Bangladesh and India where domestic sales are 61

percent and 43 percent respectively. In India the proportion of sales that are exported is

considerably higher (54%). Tax administration, tax rate, cost of financing, corruption,

and electricity are found to be the major constraints to operate a business. Retained

earnings are major source of finance not only for working capital but also for starting a

new investment. Nearly half of the surveyed firms disagree that interpretations of

regulations are consistent and predictable. Nearly 2 percent of the sale revenue is paid to

officials as bribe. Using the results of Invest Climate Surveys carried out in Bangladesh,

Bhutan, Pakistan and India, the WDR (2005) pointed out that corruption and unreliable

electricity supply are the two major constraints being faced by firms in these South Asian

countries. These results are based on the survey of 3,900 registered and 1,000 micro and

20

informal firms. According to this report, bribes are averaging almost three percent of total

sales in Bangladesh. Losses from electricity outages average over 10 percent of sales in

India and over 6.5 percent in Pakistan. In addition, insecure property rights are also

identified as another major concern. This report finds 40 percent lower productivity in the

firms that are located in poor investment climate States as compared to those located in

the States with good investment climate. If the climate for firms in Dhaka matched that of

Shanghai, Dhaka could reduce its productivity gap by 40 percent and wages could rise by

18 percent. For Calcutta, this effect is estimated even larger, i.e., 80 percent of the

productivity gap could be reduced and wages could rise by 38 percent.

Pakistan Rural Investment Climate Survey: Sampling Strategy

In order to investigate the constraints on investment and growth in the non-farm sector, a

rural investment climate survey in Pakistan is planned. Initially this survey is planned to

be conducted in the province of Punjab. A two stage stratified sampling approach is

adopted. The sample includes all villages and town committees in Punjab. Town

committees will be divided into town committee blocks.

Punjab is divided into four strata

1. Faisalabad Strata: Six IFPRI villages from Faisalabad and also town committee

blocks in Faisalabad

2. Attock Strata. Seven IFPRI villages from Attock and town committee blocks in

Attock

3. Cotton Strata: Villages and town committee blocks from R.Y.Khan, Bahawalpur,

Bhawalnagar, lodhran, Multan, Vehari, D.G.Khan, Khanewal and Sahiwal

districts.

4. Rest of Punjab Strata: This strata includes villages and town committee blocks

not included in strata 1-3. This sample will be selected from 23 districts.

In order to keep in view the proportional distribution of rural population in third and

fourth strata, it is proposed to select 16 villages and 26 town committees in these strata.

Sample Selection Procedure

Rural Part:

The rural selection procedure of stand-alone and household enterprises is almost the same

which was suggested in our earlier proposal. The villages from third and fourth strata will

picked up using Probability to Proportionate Size (PPS) method of selection. Population

of each village will be used as measure of size.

From each first and second strata six and seven villages respectively from IFPRI sample

will be selected with equal probability method of selection. For large size villages blocks

of 250 households will be formed and one of the blocks will be selected with equal

probability method and listing of households and stand-alone enterprises will be carried

out for ultimate sample selection.

21

Town Committees:

All Town Committees having population 100,000 and less within a stratum will

constitute a Sampling Frame and requisite number of sample of Town Committees will

be selected by PPS Method of selection. Reason for considering these town committees is

that all such urban localities are feeding areas to rural population and all investment in

these areas is directly linked to rural population.

For stand-alone enterprises the sampling frame in a sample Town Committee will be

developed with the assistance of Traders and Manufacturing Associations. From this

frame the required number of sample enterprises will be selected by adopting simple

random method of selection.

For household part a starting point in the sample Town Committee will be determined

and 250 households will be systematically listed for selection of ultimate sampling units.

22

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25

ANNEX 1

Annex table a: Basic information from different data sources

HIES LFS

Agri

Census SHMI CMI

Year 2001-02 2001-02 2000 1996-97 1995-96

Secondary sampling unit Households Households Households Industries Industries

Sample size 14,599 18,890 18141800 45,578 4474

Rural sample 9,161 10,992 18141800 23,330

Persons emp in rural non-farm as

% total emp persons 52.1 41.1 63

Rural nonfarm enterprises 10,240 7,893

Rural nonfarm income as % total

rural income 82.7 85.4

Annex table 1. Percentage distribution of employed persons of ten years age and above

by major sectors (rural areas) Pakistan

1982-83 1985-86 1986-87 1987-88 1997-98 1999-00 2001-02

Total 100 100 100 100 100 100 100

Agriculture, forestry,

hunting and fishing 67.69 70.94 65.24 67.49 65.13 65.85 59.01

Mining and quarrying 0.11 0.29 0.22 0.18 0.24 0.07 0.07

Manufacturing 9.38 8.52 9.05 8.34 5.77 6.46 8.68

Electricity, gas and water 0.96 0.23 0.39 0.39 0.39 0.45 0.57

Construction 4.12 4.36 5.86 6.08 5.79 5.56 6.23

Wholesale and retail,

trade 7.14 6 7.25 6.85 7.62 7.98 9.2

Transport, storage and

communication 3.09 3.07 3.55 3.45 3.53 3.86 4.81

Financing, Insurance, real

estate etc. 0.26 0.22 0.18 0.2 0.23 0.2 0.29

Community, social and

personal services 7.25 6.36 8.24 7.01 11.32 9.57 11.13

Source: Labour Force Survey (various issues)

26

Annex table b: Percentage distribution of employed persons by different professions

across industrial establishments in Rural pakistan (2001-02)

Managers

Professionals

Associ

ate

professionals Clerks

Sales

persons

Market

-oriente

d

Agriculturists

Subsist

ance

agriculturist

Craft

persons

Plant

operators

labourer Total

Agriculture 0.00 0.06 0.01 0.02 70.87 11.29 0.01 0.74 17.00 12,753,061

Mining 17.91 10.67 1.76 0.00 7.62 1.62 60.43 14,353

Food manufacturing 7.28 0.56 2.30 2.40 66.68 2.24 18.54 218,968

Textile

manufacturing 0.60 0.75 0.59 0.49 91.04 1.79 4.75 950,801 Wood & paper

manufacturing 1.69 0.85 0.00 90.31 2.38 4.77 188,959

Chemical, metal/nonmetal 1.27 1.49 1.48 1.15 62.52 4.32 27.77 433,356

Other

manufacturing 2.12 1.54 84.93 11.41 80,273

Electricity & gas 1.49 3.71 8.56 13.56 5.19 8.60 29.14 8.67 21.08 122,487

Construction 0.77 0.28 0.25 0.12 0.09 25.88 0.90 71.71 1,351,940

Wholesale &

retail trade 75.97 0.02 0.27 0.51 10.71 0.03 0.38 0.17 11.96 1,994,569 Transport &

comm 1.62 0.11 1.30 1.84 10.40 0.15 2.10 49.92 32.57 1,047,583 Finance &

insurance 20.17 9.51 45.25 13.68 4.19 1.99 3.70 1.51 64,785

Social services 2.05 16.39 42.98 7.32 13.11 0.41 0.83 1.59 15.33 1,526,410

Household/person

al services 0.33 0.30 0.85 0.09 27.54 0.40 50.08 0.88 19.55 892,554

Total 7.50 1.24 3.49 0.88 3.67 41.87 6.66 11.09 3.34 20.26 21,640,099

Source: Labour Force Survey (2001-02)

27

Annex table c: Percentage distribution of employed persons by industrial establishments across employment status in Rural Pakistan

(2001-02)

Industrial establishments

Regular

paid

employee

Casual

paid

employee

Paid at

piece rate

Paid non-

family

apprentice Employer

Own

account

worker

Unpaid

family

worker Others

Mining 0.31 0.07 0.35 0.00 1.67 0.02 0.00 0.00

Food manufacturing 2.36 2.55 1.59 0.00 8.21 2.75 2.69 0.00

Textile manufacturing 6.15 6.05 26.69 28.50 2.41 9.93 12.91 0.00

Wood & paper manufacturing 1.01 2.30 1.79 2.07 13.46 2.36 4.18 0.00

Chemical, metal/nonmetal 3.94 5.52 11.22 5.17 2.39 2.08 7.65 12.75

Other manufacturing 0.39 0.65 2.40 2.43 2.46 0.42 2.47 0.00

Electricity & gas 4.97 0.18 0.00 0.00 0.00 0.00 0.00 0.00

Construction 1.62 53.36 32.14 7.46 3.47 1.93 1.76 0.00

Wholesale & retail trade 6.09 5.68 3.13 0.43 34.40 50.00 38.58 0.00

Transport & comm 14.41 11.19 8.51 9.03 26.21 11.65 9.28 6.14

Finance & insurance 1.18 0.50 0.13 0.00 1.90 0.74 0.63 0.00

Social services 52.94 4.87 2.28 1.57 1.98 4.21 3.08 45.29

Household/personal services 4.62 7.10 9.77 43.35 1.45 13.91 16.76 35.81

Total 2,703,550 2,078,366 1,977,675 80,620 70,346 2,877,219 704,016 11,216

Source: Labour Force Survey (2001-02)