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Decide what you mean by “informal”
“Informal businesses” can refer to the informal sector: household-owned, unincorporated production units grouped under the applicable statistical standards. That is an enterprise-based concept. Informal employment is job-based: it can include informal jobs in informal-sector businesses, formal businesses, and households. Employment in the informal sector is only one part of informal employment.
Write down the quantity your estimate is intended to measure before choosing data or counting units:
- Informal-sector businesses: the number and characteristics of in-scope enterprises.
- Employment in those businesses: the jobs or people working in informal-sector enterprises.
- Informal employment across the economy: informal jobs in informal and formal enterprises and households.
- Both enterprise and job measures: report them separately, explaining how they relate rather than treating them as interchangeable.
Business registration alone is not a universal test of informality. Registration, incorporation, bookkeeping, employment arrangements, social protection, and legal coverage are distinct features. Record the variables used to classify a unit or job so readers can understand the definition and results can be re-tabulated if standards change.
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Set the boundary of the study as well: geographic area, reference period, treatment of agriculture and own-use household production, unpaid contributing family workers, people with multiple jobs, and businesses operating across local boundaries. There is no single convention for all of these choices; disclose the ones that affect your estimate.
Choose data that can actually reach the population
No single source is automatically complete. The International Labour Organization (ILO) describes household surveys, particularly labour-force surveys, enterprise surveys, establishment surveys or censuses, and mixed household-enterprise surveys as alternative sources or approaches. The right design depends on the local population frame, the desired measures, and available resources.
| Approach | What it can contribute | Key dependency or trade-off |
|---|---|---|
| Household or labour-force survey | Can identify workers and household-based business operators, and may capture informal jobs outside informal-sector enterprises. | Business accounts and detailed sales or cost data may be limited; results depend on household coverage and questions. |
| Enterprise or establishment survey | Can collect business-level employment, sales, costs, and other operating details. | It depends on a usable frame and may miss unregistered or otherwise unlisted units. |
| Mixed household-enterprise survey | Can identify operators through household questions and follow up to collect business details. | It connects people and enterprises but requires more complex fieldwork. |
Before fieldwork, inventory the sources available in the locality: business registers, licensing and tax records, household and labour-force surveys, economic censuses, establishment data, and community-based lists. These are candidates to assess, not a guarantee that any particular locality has them or that they are complete. For each source, record its coverage, update cycle, unit counted, geographic and industry detail, worker variables, and likely exclusions. Also assess access, confidentiality rules, and whether sources can legally and safely be linked.
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A register with broad coverage may make an enterprise survey efficient, but its omissions still matter. Where no dependable register exists, a household listing followed by interviews with identified business operators is one possible design. Compare options by unregistered-unit coverage, ability to connect operators with workers and enterprises, detail on sales and costs, sampling and field cost, frequency, timeliness, local detail, nonresponse risk, and compatibility with official statistical concepts.
Classify units and jobs consistently
Use internationally aligned concepts and question wording where possible, while documenting how the standards are applied locally. The ILO’s Survey Questions for Collecting Data on Work Relationships and Informality, published 9 December 2024, reflects the 20th International Conference of Labour Statisticians (ICLS) resolution on work relationships (ICSE-18) and the 21st ICLS resolution on statistics for the informal economy. Its questions classify work relationships and economic units, including informal, formal, household own-use production, and community-sector categories.
Keep the underlying answers as well as the final classification. That makes the result auditable and lets analysts see which attributes—such as registration, incorporation, records, or job characteristics—shaped the count. State the standard, operational definition, and any local adaptations used; do not imply that one indicator, such as absence from a business register, captures every aspect of informality.
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Estimate scale and economic contribution separately
Count businesses and work
At minimum, report the number of in-scope businesses and the people or jobs engaged in them. Break results down by relevant local geography and broad industry when the sample supports reliable estimates and disclosure will not identify respondents. If collected credibly, add worker characteristics, hours, and earnings.
Be precise about the unit behind each figure: persons are not the same as jobs, and a person with multiple jobs can appear more than once in a job count. Explain whether the estimate covers main jobs, secondary jobs, or both. Apply the same care to business units—for example, clarify how an operator with more than one activity is treated.
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Measure output or gross value added
A business count or employment total describes scale, but does not by itself show economic contribution. Choose an economic aggregate, such as output or GVA, and define it. Output is the value of goods and services produced under the chosen accounting concept. GVA is output less intermediate consumption—the goods and services used up in production. The ILO’s Women and Men in the Informal Economy: A Statistical Picture identifies the informal sector’s contribution to total GDP or GVA as a key indicator.
Use production, expenditure, or income information that is compatible with the accounting framework used for the locality, and explain any imputation. State whether amounts are gross or net of intermediate inputs and whether they are nominal or adjusted for price changes. Describe how owner-operated firms and mixed household-business accounts are treated. Do not add business sales to wages or household spending and call the sum a contribution: those values may overlap or measure different sides of the same activity.
Published figures illustrate why the place and year matter. The ILO’s 2014 publication reported that informal-sector activity excluding agriculture accounted for 46 per cent of non-agricultural GVA in India in 2008. That is a country-specific historical figure, not a benchmark for another locality or period. The same publication reported direct measures of informal employment inside and outside informal enterprises for 47 countries and territories; that describes the publication’s coverage, not current local prevalence.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Account for what data do not observe
Informal businesses are not the only activity at risk of being missed. Underground, illegal, and own-use production, as well as activities missed because of data deficiencies, are also part of the broader non-observed economy. The OECD/ILO handbook Measuring the Non-Observed Economy (2002) describes two complementary fronts: improve direct measurement through data collection, and improve indirect measurement during national-accounts compilation.
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Better survey coverage can identify units and workers directly. Indirect adjustments in national accounts can address activity absent from basic data, but a macroeconomic adjustment does not identify the particular businesses or workers responsible unless the method can genuinely do so. Explain which parts of the estimate come from direct observation and which from adjustments or imputation.
Describe uncertainty in terms suited to the design:
- For probability samples, report sampling uncertainty using an appropriate measure.
- For incomplete frames, explain likely undercoverage and, where defensible, show sensitivity ranges rather than implying exact completeness.
- Disclose nonresponse, imputation, seasonal activity, and hard-to-enumerate groups that could affect the figures.
- Distinguish uncertainty in estimated totals from uncertainty about which specific units generated unobserved activity.
Publish enough detail for others to interpret the estimate
Alongside results, state the target population, geographic boundary, reference period, definitions, source data, estimation steps, and known omissions. Explain how units were classified, how records from multiple sources were handled, and how output or GVA was calculated. If a number is an estimate rather than a direct count, identify the assumptions and adjustments behind it.
This reporting discipline follows the ILO’s statistical guidance on standards, methods, tabulation, dissemination, and use in national accounts. A useful technical reference for survey and statistical-program design is the ILO’s Measuring Informality: A Statistical Manual on the Informal Sector and Informal Employment, published 4 October 2013. The ILO’s 2011 statistical update on informal employment explains the distinction between enterprise-based and job-based measures.
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