Measuring Informal Sector Economic Activitiesin Nepal

by Rudra Suwal and Bishnu Pant

Socio-economic Determinants of Income Generation in the Informal Sector of Nepal –

A Case of Chitwan Districtby Manoj Kumar Agarwal and Ram Chandra Dhakal

Discussion by Andrea BrandoliniBank of Italy, Department for Structural Economic Analysis

Special IARIW-SAIM Conference on “Measuring the Informal Economy in Developing Countries”, Kathmandu, Nepal, 23-26 September 2009

Session 7: The Informal Sector in Nepal

Two papers are complementary

• Rudra – Bishnu paper – focuses on the general problem of how to

measure informal economy and provides aggregate estimates for Nepal

• Manoj – Ram Chandra paper– presents microeconomic results from a survey

carried out in a Nepalese district

Measuring Informal Sector Economic Activities in Nepal - 1

Informal economy

• Benefits of informal employment may not be sufficient to achieve acceptable standard of living, due to lack of social protection, good working conditions and adequate wages

• Challenge to policy-makers – Improve working conditions, legal and social

protection– Increase productivity, training and skills– Develop appropriate regulatory framework

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Role of statistics

• Statistics on the informal sector are needed as an important tool for policy making and advocacy

• Operational definition of the informal sector is required

• Regular data collection system of CBS Nepal does not cover the informal sector. Two implications:– Distorted estimates of the economy structure– Imprecise understanding of social and economic

issues in policy making

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Informal sector definition: an unresolved issue - I

• For statistical purposes:

group of production units part of household sector, as household enterprises or unincorporated enterprises, defined irrespective of:

• work place • extent of fixed capital assets • duration of operation of enterprise• main or subsidiary activity of owner

• Operational definitions vary in different countries

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Informal sector definition: an unresolved issue - II

• In many Asian countries (India, Indonesia, Philippines – but also Nepal), un-organized segment of an economic activity is defined to comprise:

operating units whose activity is not regulated under any legal provisions and/or which do not maintain any regular accounts

• In most developing countries, many economic units escape the administrative, legal or statistical framework

• Problem: country-specific definition, depending on prevailing administrative, legal or statistical framework; informal sector expands or contracts with a change in the underlying yardstick over time

Measuring Informal Sector Economic Activities in Nepal - 5

Nepalese experience

• In Nepal, CBS has not yet conducted nation-wide survey of informal sector

• But CBS has attempted a number of statistical methods for estimating the contribution of informal sector in the overall economy of the country

• Questionnaires of regular household surveys modified so that relevant information could be compiled

• Examination of results indicate that this is practical approach for the collection of informal sector statistics in absence of any specific survey

• Nepal Labor Force Surveys (NLFS). – 1998 limited questions – 2008 additional questions on the informal sector

Measuring Informal Sector Economic Activities in Nepal - 6

Share in total employment: 96.2%

Measuring Informal Sector Economic Activities in Nepal - 7

Comparing NLFS 1998 and NLFS 2008 • Strict comparison not possible because of limited

coverage and contents of questionnaire• But employment in non-agricultural informal sector

seems to have increased by more than 29%

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Informal sector value added

• NLFS 2008 does not provide estimates of production

• Informal sector value added estimated using information from surveys of small scale manufacturing establishments, some 30 surveys for benchmarking national accounts estimates, conducted by CBS in 2006

• Impute value added to informal employed:

Value added per labor × IS employment = IS value added

41,357 11,332,000 468,654 Rs millions

Total GDP including IS value added: 910523 Rs mln

Contribution of Informal sector to GDP: 51.5%

Measuring Informal Sector Economic Activities in Nepal - 9

Conclusions

• Mixed household and enterprise surveys is the most appropriate method

• Need of specially designed surveys (including time use surveys)

• Contribution of informal sector to economy is significant Important to conduct regular surveys of informal sector– official GDP estimates underestimated – loss of tax revenue– incorrect target spending across regions or socially

deserving groups– employment related statistics highly questionable

Measuring Informal Sector Economic Activities in Nepal - 10

Comments

1. Authors’ favorite definition of informal economy

2. Size of informal employment

3. Imputation: using more disaggregated information?

Background information on Nepalese Economy

• Highly instable economic growth– Up to 2000/2001 rate remained below 5%, but

afterwards, much below 4% → critical interruption – Decline due to poor performance of non-farm

sectors, in the face of a progress in the farm sector

• High population growth – no sign yet of demographic transition

• Political conditions harmful for growth

• High absolute poverty, but some progress – 41.76% in 1995-96 to 30.85% in 2003-04

• Unemployment in 2003-04, 2.9% of population 15+– 15% among youth

Socio-economic Determinants of Income Generation - 1

The Chitwan District – the “Rapti Valley”

• One of the 75 districts of Nepal

• Population of 470,700 in 2001– high growth rate – urban population of 27.5%.

• 55.5% of land holdings is marginal

• 3.1% of active population in industrial sector– 71 manufacturing units employing 3,755 persons,

with total fixed capital of Rs 432 millions– More employment in cottage industries, which

show a high mortality rate

Socio-economic Determinants of Income Generation - 2

Socio-economic Determinants of Income Generation - 3

Informal sector in Chitwan

• Sample survey of non-farm informal sector in rural and urban locations– Mixed household and enterprise surveys suitable to

collect comprehensive data on informal sector

• Informal sector activities are unregistered

Socio-economic Determinants of Income Generation - 4

Urban (Bharatpur

Nagarpalika)

Urban (Ratnanagar Nagarpalika)

Rural Total

NumberMale 122 61 118 301Female 62 21 34 117Total 184 82 152 418% shareMale 29.2 14.6 28.2 72.0Female 14.8 5.0 8.1 28.0Total 44.0 19.6 36.4 100.0

Features of informal sector – I

• Women respondents have higher:– household size (in U1 and rural)– employment– household literacy rate (schooling years)– household property

• Respondents have higher literacy level than other household members

• 66.7% had no training; 78.1% for females

• Initial investment higher in urban areas

• Beneficiaries of loans from microfinance below 20% in urban areas, around 40% in rural areas

• Few received government help

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Pattern of employment in informal sector

S. No. Types of employmentPersons Male Female

N % N % N %

1.Self-employed (single person)

159 38.0 130 43.2 29 24.7

2.Family members employed

148 35.4 81 26.9 67 57.3

3.Family & unpaid others employed

6 1.4 6 2.0 0 0.0

4.Family, unpaid & wage earners employed

40 9.6 26 8.6 14 12.0

5.Self-employed & wage earners employed

36 8.6 33 11.0 3 2.6

6. Wage earning employed 29 6.9 25 8.3 4 3.4

Total418 100.0 301 100.0 117 100.0

Features of informal sector – II• Women more articulate in mobilizing household

support whereas men basically depend upon themselves or wage earners and unpaid workers

• Women generally do not prefer to employ wage earners when they themselves are involved

• Women are harder workers than their male counterparts– longer working hours in all seasons– more working days in all seasons

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Household earnings in informal sector

Mobility /Pattern of Employment

Av. HH Earning from IS (NRs)

Av. HH Earning from OS (NRs)

CorrelationCoefficient (r)

Household earnings by mobility

Mobile 73,207 14,416 -0.019

Semi-mobile 72,236 13,586 -0.096

Fixed 90,418 15,350 -0.050

Household earnings by types of employment

Self-employed 65,193 13,747 -0.018

Family member employed

83,892 16,176 -0.184**

Family & unpaid other employed

85,000 9,500 0.594

Family, unpaid & wage earner employed

139,030 14,800 -0.038

Self-employed & wage earner employed

121,111 20,722 -0.070

Wage earner employed 54,931 8,376 -0.349

Informal sector earnings and caste

Caste

Urban 1 Urban 2 Rural

n Mean n Mean n Mean

Brahman/ Chhetri

87 307.38 31 246.61 56 215.25

Vaisya 57 301.16 27 192.04 56 194.82

Dalit 14 249.17 12 167.64 28 179.10

Musalman (Muslim)

12 282.36 9 168.89 3 145.56

Others 14 252.86 3 186.11 9 291.48

Total 184 295.22 82 206.34 152 204.20

Determinants of earnings in informal sector

• Log-linearized Cobb-Douglas production function

ln Y = 0+ 1 ln HHP + 2 ln ISL + 3 ln LITL + v

with 1 + 2 + 3 = 1 [?]

Y daily earnings from informal sector HHP household propertiesISL number of workersLITL schooling years of respondent

• Estimated separately by area/sex and caste

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Earning function by castes

Caste

Estimated coefficients

R2

0

(Constant)

1

(Labor employed)

2

(investment per day)

3

(literacy level)

Brahman/Chhetri 3.387

(26.588)*

0.129

(2.648)*

0.069

(1.154)*

0.763

(15.177)* 0.656

Vaisya 2.991

(18.042)*

0.155

(2.521)**

0.118

(2.147)**

0.720

(11.915)*0.714

Dalit 2.769

(16.752)*

-0.027

(-0.359)

0.069

(0.850)

0.913

(10.821)*0.621

Musalman (Muslim) 2.784

( 8.006 )*

-0.003

(-0.024)

0.033

(0.226)

0.879

(5.874)*0.808

Others 3.374

( 9.563)*

0.376

(3.327)*

0.030

(0.300)

0.670

(5.701)*0.916

All

Male 9.075

(144.106)*

0.094

( 3.381)*

0.037

(1.438)

0.867

(30.432)*0.883

Female 8.674

(68.936)*

0.083

(1.905)

0.150

( 3.557)*

0.818

(17.496)*0.874

Income earnings in informal sector• Schooling most important determinant for income

generation in rural as well as urban areas• Number of workers significant determinant of income

only in women run urban informal sector• Household property have significant bearings on

income generation• It would have been due to poor background of women

entrepreneurs or else they failed to seek advantage from the household properties for different unexplained reasons.

Socio-economic Determinants of Income Generation - 8

Daily Investments & Earnings of Households from IS in Chitwan

Impact of informal sector earnings on household earnings

Household monthly income

level (NRs)

IS earnings excluded IS earnings included

N % N %

Poor (<10000) 394 94.3 54 12.9

Low (10000-20000) 22 5.3 172 41.1

Middle <(20000-30000) 1 0.2 104 24.9

High (>30000) 1 0.2 88 21.1

All income group418 100.0 418 100.0

Conclusions and policy implications - I• Firms in informal sector spread in urban and rural

areas, highly diversified, expand beyond family to employ wage earners and others

• No formal training• Women more efficient, generate better household

conditions, mobilize family participation• Literacy level most important determinant of income• Social structure (caste or community) influences

income generation– Higher earnings for upper castes (Brahman/Chhetri

and Vaisya) than lower caste (Dalit) and Muslims– Due to better endowments for the upper castes in

terms of household properties, literacy, etc.

Socio-economic Determinants of Income Generation - 9

Conclusions and policy implications - II• Informal sector helpful in income and employment

generation, crucial source of earnings for many• Low, if any, state support. • Public policy options:

– Quality training– Credit facilities– Social security– Education

• Women should be given greater prominence• Poor and lower caste or social status people need

extra state support

Socio-economic Determinants of Income Generation - 10

Comments

1. More information about the sample: selection process, representativeness, data collection

• How are owners of informal businesses selected?• What does it mean: “To cover the homeless

respondents in informal sector, it was tried to obtain the information at the working spot both in urban as well as rural areas”?

2. Compare households with in formal and informal sector

3. Multivariate analysis– Constant returns to scale?– Why not a single multivariate regression to assess

the weight of various factors?

Socio-economic Determinants of Income Generation - 11