Download Informal Sector

Measuring Informal Sector and
Informal Employment
National Workshop on Informal Employment and
Informal Sector Data Collection:
Strategy, Tools and Advocacy
Amman
13-15 April 2008
Presentation Plan
• A Brief Background
• Definitions of Informal Sector and Informal
Employment
• Main Uses of Informal Economy Data
• Methods of measuring Informal sector
• Strategies of Data Collection
• Advantages and Disadvantages
Informal Sector –
A Brief Background (1)
• ILO’s Report of a Comprehensive Employment Mission to
Kenya (1972) used the term “informal sector”.
• Since then the term has gained acceptance in international
official documents.
• Initially, labour statisticians considered “informal sector” as
composed of urban “working poor” migrated from rural areas
in search of work.
• Later, recognised as an important employment-, productionand income- generating sector
– present as much as in rural areas as in urban areas
Informal Sector –
A Brief Background (2)
• Though the term “informal sector” is of relatively
recent origin, the idea of such a segment of economy
has existed since long.
• Particularly for ensuring complete coverage of the
national accounts statistics, building an adequate
database especially for this segment has been a
matter of concern since the early 1950s.
Informal Sector –
A Brief Background (3)
• The official statisticians have referred to this
segment – or a closely comparable one – by various
names like “unregistered”, “unorganised” and
“unrecorded” segment of the economy.
• The coverage of the segment of the economy
referred to by these terms were indeed varied.
Informal Sector –
A Brief Background (4)
• The 15th ICLS (1993) adopted a resolution relating
to statistics of employment in the informal sector.
• This provided an international statistical standard
definition of informal sector.
• The SNA 1993 identified “informal sector” as one of
the segments of economy that are not covered or not
adequately covered in the national accounts.
Non-observed Economy (NOE)
In measuring the activities within 1993 SNA production
boundary exhaustively, the 5 problem areas that are
most likely to be non-observed are:
– Underground
– Illegal
– Informal sector
– Household production for self consumption
– Deficiencies of basic data collection programme.
[OECD manual (2002) on Non-Observed Economy (NOE)]
Informal sector – a part of NOE
• Clearly, the NOE problem areas are not mutually
exclusive.
• But, the informal sector is the most important
component in many countries, especially in
developing countries.
• Besides obtaining exhaustive estimate of GDP,
measuring contribution of informal sector serves
important purposes relating to economic policies.
Definition of Informal Sector
• The three main criteria of defining the informal
sector, as adopted by the 15th ICLS, refer to
–Absence of legal organisation (unincorporated enterprises)
–Type of accounts (no complete set of accounts)
–Product destination (at least some market output)
• Consistent with the 15th ICLS, the SNA 1993 (and its
update) defines informal sector as a subset of the
“household sector”.
Definition of Informal Employment(1)
• Primarily, for consistency with the framework of
SNA, “informal sector” was defined by enterprise
approach, i.e.
• in terms of characteristics of the enterprises;
• instead of labour approach, based on the
characteristics of the workers and their employment
conditions.
• The labour statisticians were even then aware that this
definition would not be able to capture all forms of
“informal employment” .
Definition of Informal Employment(2)
•
•
The concept of employment in informal sector does
not embrace the concept of informal employment,
i.e. persons employed in jobs under informal
arrangements.
As defined by Hussmanns (2001), informal
employment comprise employment in the informal
sector plus jobs of the following groups of workers:
(i) own-account workers who produce for own final use
only; and contributing family workers;
(ii) employees with informal jobs in formal sector
enterprises and employees in unincorporated private
enterprises engaged in non-market production.
Definition of Informal Sector –
further details (1)
• The two conditions:
(i) unincorporated enterprise and
(ii) absence of accounts
follow from that it is a subset of household sector.
• The criterion “production for market” excludes
– household enterprises with no market production
– own account construction,
– services of paid domestic workers.
Definition of Informal Sector –
further details (2)
• Exclusion of household enterprises with non-market
production, leads to a problem of uniform application.
• Some agricultural activities are carried out solely for
subsistence, while others for selling the produce in the
market.
• Thus it is additionally proposed that all agricultural
activities be excluded from the purview of informal
sector, though it may be quite significant in most of
the countries with large informal sector.
Definition of Informal Sector –
further details (3)
•
There are other criteria that are proposed for
definition of “informal sector” like
–
–
•
exclusion of enterprises above a specified size – in terms
of employment
exclusion of persons engaged in professional or
technical activities like doctors, lawyers and engineering
consultants.
The Delhi Group has been working on framing a
uniform definition of informal sector – ILO is
expected to give a final shape to it very soon.
Definition of Informal Employment
– further details (1)
• The 15th ICLS definition of informal sector is not a
dichotomous sub-sectoring of the economy.
• It suggests a trichotomy – formal, informal & neither.
• The last category includes household enterprises like
– those engaged solely in agricultural activities, or
– production of goods solely for own final use or
– production of services employing paid domestic workers.
• All employment in this category is treated as informal
employment in addition to those in informal sector.
Definition of Informal Employment
– further details (2)
• Further, there is informal employment in formal sector, whose
identification requires a clear definition of ‘informal jobs’.
• Informal employee jobs: employment contract not subject to
standard labour legislation, taxation, social protection or
entitlement of certain employment benefits.
[Hussmanns (2001)]
• Such jobs are mostly
– undeclared, casual or of short duration,
– either without employment contracts or with shortterm contracts.
Informal Economy Data
– Main Uses (1)
• Informal economy – comprises all informal
sector enterprises and informal employment.
• Data on informal economy are of interest to
mainly two groups of users:
– labour statisticians & economists for labour
welfare policy making and
– national accountants for attaining exhaustive
coverage of National Accounts Statistics.
Informal Economy Data
– Main Uses (2)
• The main requirements for labour welfare related
policy making are data on
– entitlements, benefits, conditions of work and social
protection of informal employment;
– structure of informal sector like their productive activities,
employment- and income-generation, conditions and
constraints of operation and links with the formal sector.
• The national accountants - mainly concerned about
attaining exhaustive coverage - need data on
production-related parameters of informal sector.
Methods of measuring
Informal Sector
• Two broad groups of methods:
– Macro-model methods
– National accounts methods to achieve exhaustiveness
• Both these groups of methods attempt to measure
NOE (also referred to as ‘shadow economy’, ‘hidden
economy’, ‘underground economy’), in general,
- of which informal sector is but a component – albeit
the major component.
Macro-model Methods
• Macro-model methods – as termed in the Handbook produce an estimate of the entire NOE by means of a
single model.
• The Handbook – “…not considered useful in
obtaining exhaustive estimates of GDP or NOE …”
• “… and tend to tend to produce spectacularly high
measures …”
• Three broad types:
– Monetary methods
– Global indicator method
– Latent variable methods
Monetary Methods
• These rely on the assumption: “unexplained” (by the
model) monetary developments owes to incomplete
coverage of official GDP estimate.
• Start with Fisher’s quantity theory equation
• Obtain an estimate of GDP
• Difference between the model-based estimate and
official estimate is considered a measure of NOE.
• Three variants:
–Transaction method
–Cash/deposit ratio method
–Cash demand method
Global Indicator Method
• This method uses a single variable like
electricity consumption as the indicator of
entire economic activity.
• The difference between the estimate of GDP
obtained under the model and the official GDP
is claimed to represent a measure of NOE.
Latent Variable Methods
• These are multiple regression models with a nonobserved dependent variable and a number of
observed explanatory variables.
• Variants are:
–LISREL (linear Independent Structural Relationships)
models of Joreskog and Sorbom (1993)
–Multiple Indicator Multiple Cause approach (MIMIC) Frey and Weck-Hanneman (1984)
–DYMIMIC (the dynamic multiple-indicators multiplecauses approach)
GDP compilation in production
approach – Indirect Methods
• Indirect methods of covering NOE in the GDP
estimate:
–Supply based approaches, including labour input method;
–Demand based approaches;
–Income based approaches;
–Commodity flow approaches.
• Labour Input Method (LIM) is the most important
procedure that has been in use since 1950s to measure
contribution of unorganised sector to GDP.
Labour Input Method (1)
The labour input method (LIM) of estimating value added /
output for the informal segment (for an economic activity or a
group of economic activities) consists of:
• obtaining an estimate of labour input from Population Census
and / or Labour Force Survey (LFS) using other sources for the
informal segment
• obtaining estimates of output or value added per unit of labour
input for the informal segment from Establishment Survey; and
• multiplying the estimate of labour input by the estimate of per
unit value added / output to arrive at an aggregate estimate of
value added / output.
Labour Input Method (2)
• This is one of the most effective methods of
measuring gross value added (GVA) of informal
sector – usually by economic activity. Since
– most often, the enterprise surveys fail to cover all
enterprises.
– again, costs actually incurred for hiring (casual) labourers
are often shown as services charges rather than
compensation of employees and
– hired labour not included in labour input.
• In such cases, this procedure can be give a more
exhaustive coverage, since LFS data give more
complete coverage of labour input.
Labour Input Method (3)
• Measuring the value of production of goods and
services by LIM, therefore, demand a fair degree of
precision in the estimates of
– labour input (number of workers adjusted for multiple
employment) based on data from households (LFS)
and
– Gross value added per worker (GVAPW) from
enterprises obtained from enterprise survey (ES),
separately for activity groups.
Data Needs
• The requirements of estimates on informal economy
can be summarised as follows:
• For Informal Employment:
–
–
–
–
parameters defining informal employment (LFS)
terms & conditions of employment (LFS)
structural information (ES)
productivity (ES)
• For Informal Sector:
– parameters defining informal sector enterprise (ES)
– production related parameters (ES), including labour input,
output, intermediate consumption and GVA.
Data Collection Strategies (1)
• For measurement of informal employment and
informal sector employment the LFS is the best
instrument.
• Requires inclusion of some additional questions
relating to definitions.
[ILO Compendium of Official Statistics on Employment in the
Informal Sector (2002)]
• Informal sector production can be measured thru
enterprises surveys covering the informal sector.
Data Collection Strategies (2)
The main options of colleting data on production of
informal sector are as follows:
1. List-frame based establishment survey
2. Area frame based establishment survey
3. Area frame based mixed household and enterprise
surveys and
4. Area frame based Integrated “1-2” surveys
Data Collection Strategies (3)
List-frame based establishment survey:
•
•
•
•
business register does not usually cover the
informal sector units
List-frame has to be developed from a general
economic/establishment census
But, census do not ensure full coverage.
Thus, list-frame based establishment surveys can
not ensure complete coverage of informal sector.
Data Collection Strategies (4)
Thus, area-frame based surveys are essential for
complete coverage of informal sector.
• But the conventional area-frame based
establishment survey suffer from the same
limitation as the Establishment Census.
• In these surveys, a list frame of establishments is
developed for each selected area unit by door to
door enumeration.
• This procedure is prone to omission of activities
carried out inside the owner's home
Data Collection Strategies (5)
•
The choice of method is, therefore, practically
restricted to the two area-frame surveys, viz.
–
–
•
•
•
Mixed household enterprise survey and
Integrated “1-2”survey
Both these methods use a multi-stage (usually twostage) sampling scheme
A sample of area units are selected as the first stage
unit (fsu) in both the methods.
The methods differ at the second-stage.
Mixed household enterprise survey (1)
• Variously described in literature.
• As per the (Draft) Manual on Surveys of Informal
Employment and Informal Sector, its sampling frame
at the second stage consists of the following:
all identifiable establishments outside the owners’
home located in the selected area unit;
ii. household-based enterprises located within home; and
iii. the units without any fixed premises of operation
i.
are listed by a structure-to-structure visit.
• The units of later two categories are listed against and
interviewed in the owners’ households.
Mixed household enterprise survey (2)
• Units excluded from the survey coverage are not listed, e.g.
– agricultural or formal sector establishments and
– units covered in a list frame based survey.
• Within-scope units without fixed premises of within owner’s
home are identified through additional questions put to
households during listing; and
• are listed against the household where the proprietor (or a
partner of a partnership concern) resides.
• This way, all establishments within the scope of the survey in
the fsu are included in the list.
Integrated “1-2” Survey
•
This approach consists of two phases:
–
–
•
•
•
First phase: a household survey (LFS) and
Second phase: an enterprise survey.
The first phase used also for constructing the
sampling frame for the enterprise survey.
From the sample households in the first phase, the
within-scope enterprises owned by the households
are identified.
In the 2nd phase, a sample of within-scope
enterprises that are owned by the households is
drawn for the enterprise survey.
Integrated “1-2” Survey
•
The within-scope enterprises selected for
survey may either be
–
–
–
•
Within the fsu without fixed premises, or
Within the fsu with fixed premises
Outside the fsu
In all these cases, the enterprise is surveyed.
[as indicated in the next slide]
Integrated “1-2” Survey
Households owning/
operating enterprises
Within the sample
area
Outside the sample area
and with fixed premises
Capture at premise
With fixed
premises
Capture at premise
Without fixed
premises
Capture at household
Advantages & Disadvantages
of the two methods
Mixed Hhd-entp. survey
“1-2” Survey
• May be conducted
independent of other surveys
using EC data
• Estimate of informal sector
employment varies from that
obtained from Hhd. Survey.
• Involves extra costs –
expectedly marginally more
- for enterprise listing.
• Provides data on informal
employment & informal
sector
• Estimates of informal sector
employment from 2 sources
likely to be consistent.
• Involves extra costs for
travel – for surveying
enterprises outside the fsu.
Main disadvantage of “1-2” Survey
•
•
•
In a stage sampling, efficiency of an estimate
depends on how well the inclusion probability of
the fsu’s (pa) are correlated to the fsu-level value of
the parameter, e.g. sum of GVAs of all withinscope enterprises of the fsu.
In a mixed household enterprise survey, this can be
attempted by using EC data.
In an “1-2” survey, the choice of size variable for
fsu selection is based on distribution of population
and not on that of within-scope enterprises.
Possible way out
•
For an integrated “1-2” survey, population census
data may be used as the sampling frame.
Area units (fsu’s) with relatively high concentration
of self-employed workers may be put in a separate
stratum and
•
–
–
–
•
a higher sampling fraction may be used for drawing a
sample of fsu’s from it,
by PPS
using number of self-employed workers as size variable.
This could be a possible method of capturing a
representative sample of informal sector
enterprises, in absence of Economic Census data.
Thank You