## ppea2021002

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### Proposed statistical framework for the informal economy
- The informal economy “comprises production of informal sector units, production of goods for own final use, production of domestic workers, and production generated by informal employment in formal enterprises.”
- The framework is consistent with internationally agreed concepts and methodology for measuring GDP and is intended to facilitate preparation of estimates of the informal economy as a component of GDP.

### Policy relevance and major implications
- Measuring the informal economy informs policy on economic growth, aggregate production, potential tax revenue, and income distribution.
- Informal workers may be more vulnerable to negative shocks such as the COVID-19 pandemic, facing greater income losses without the benefit of social protection; lack of registration may hinder their access to government interventions.
- Digitalization has created new opportunities for informal employment and generated new data sources that statistical compilers may use to measure the informal economy.

### Conceptual fragmentation and need for a consistent taxonomy
- No internationally agreed statistical framework has been in place despite an ILO analytical definition; diverse criteria have produced inconsistent definitions and estimates.
- Terms used interchangeably (e.g., “shadow economy,” “underground economy,” “hidden economy”) complicate policy discussions and cross-country comparisons.
- A consistent framework would improve cross-country comparability and link measurement to policy purposes.

### Measurement findings and empirical evidence (selected)
- Model-based measures (e.g., MIMIC) suggest declines in informal output as a percentage of GDP across regions between 1990–2017, but levels remain high in Sub-Saharan Africa and Latin America, averaging around 34 percent between 2010–2017.
- Using MIMIC and Dynamic General Equilibrium models, Elgin and others (2019) estimate that between 1990–2016 the share of informal output:
  - fell by about 7 percentage points of GDP in emerging and developing economies (to 32 percent of GDP);
  - fell by about 4 percentage points (to 17 percent of GDP) in advanced economies.
- The share of informal economic activity may vary over the business cycle; unmeasured variation could exaggerate GDP volatility.
- Tax-base considerations: taxing the informal economy would broaden the tax base and increase government revenue, but measures for national accounts purposes differ from measures of revenue not reported to tax authorities.
- Empirical evidence on cyclicality is mixed: studies focusing on shares tend to find countercyclical behavior, while studies on levels tend to find procyclical results; results remain inconclusive partly due to measurement difficulty.

### Effects on productivity, firms, and labor
- Informal firms can generate inefficiencies by avoiding detection or facing heavy administrative burdens in the formal sector; resources may be diverted to mask activities, and firms may remain sub-optimally small.
- Lower costs from avoiding tax and regulatory compliance can allow low-productivity firms to stay in business, potentially reducing formal-sector incentives to innovate and adopt new technologies.
- Informal employment can provide support where formal job creation lags labor force growth; poverty rates are higher among informal workers, though not all informal workers are poor.
- Wage differentials:
  - Informal sector wages are on average below those in the formal sector.
  - Factors behind wage differentials include worker characteristics, non-wage benefits (flexibility, independence), and labor regulations or tax provisions creating wedges between similar workers.
  - A World Bank (2019) analysis of 18 studies finds formal wage premia tend to be higher where informality is more widespread; when controlling for unobserved worker characteristics, the formal wage premium largely disappears.
- Informal employment is more prevalent in rural areas.

### Key statistics on informal employment by grouping (2016)
- Table 1 excerpts (percent):
  - Informal Emp.: 61 18 67 90
  - Rural: 80 22 83 90
  - Urban: 44 17 51 79
  - Agriculture: 94 59 93 98
    - Rural: 95 64 95 98
    - Urban: 87 49 82 98
  - Industry: 57 16 67 73
    - Rural: 69 17 75 87
    - Urban: 49 15 61 65
  - Services: 47 18 55 74
    - Rural: 65 19 71 79
    - Urban: 39 17 47 70
- Source: Women and Men in the Informal Economy—A Statistical Brief (2019); ILO calculations based on national labor force data.

### Informality and women's employment
- The ILO estimates that in developing economies, more women than men are informally employed.
- The informal economy provides opportunities to increase the participation of women in the economy and provides a source of income.
- Women tend to be in employment relationships with lower earnings and a higher risk of poverty (WIEGO, 2012).

### Share of Informal Employment by Age and Sex, 2016 (Table 2)
- Total: World 61; Men 63; Women 58.
- Total by region:
  - Developed: Total 18; Men 19; Women 18.
  - Emerging: Total 67; Men 69; Women 64.
  - Developing: Total 90; Men 87; Women 92.
- Age 15–24: World 77; Men 79; Women 73.
  - Developed: 19; Men 19; Women 19.
  - Emerging: 83; Men 85; Women 79.
  - Developing: 97; Men 97; Women 97.
- Age 25–64: World 58; Men 60; Women 54.
  - Developed: 17; Men 17; Women 16.
  - Emerging: 66; Men 67; Women 62.
  - Developing: 90; Men 87; Women 93.
- Age 65 and over: World 77; Men 78; Women 75.
  - Developed: 38; Men 39; Women 37.
  - Emerging: 88; Men 88; Women 88.
  - Developing: 96; Men 95; Women 98.

### COVID-19 impacts on informality
- Informal workers are more vulnerable to negative shocks; government containment measures severely impacted sectors with high concentrations of informal workers, including:
  - domestic workers;
  - accommodation and food services;
  - manufacturing; and
  - retail.
- More than 500 million farmers producing for the urban market were affected (ILO, 2020).
- Informality is prevalent in activities requiring direct interaction with consumers; social distancing and work-from-home arrangements may limit the ability of many service workers to work.
- Some countries applied light or no systemic lockdowns to avoid severe impacts on informally employed workers.
- Challenges in delivering government interventions:
  - Informal workers often have no insurance and are often unregistered, making direct income support delivery difficult.
  - Government support based on income or employment status may not efficiently target informal workers not included in employment or tax databases.
  - Programs may need non-income eligibility proxies (demographic characteristics, place of residence, ownership of assets) (Prady 2020).
- Social assistance coverage statistics:
  - Social assistance programs cover 20 percent of the population in Africa and 40 percent in Latin America (Diez and others (2020)).
- In-kind transfers and school feeding programs play an important role, notably in Africa, but may be hard to provide under COVID-19 containment measures.
- Migrant and undocumented workers, and rural workers without adequate access to information and medical treatment, remain vulnerable (FAO, 2020).

### Digitalization and data opportunities/limitations
- Digitalization has increased opportunities for informal jobs (gig economy) and financial inclusion via mobile money.
- Mobile money and digital payment forms are increasing in developing countries with high informality (Financial Access Survey, IMF); mobile money may expand into credit, savings, and insurance (Jacolin, Massil, and Noah, 2019).
- Some countries encouraged mobile money during COVID-19 to minimize physical interaction (IMF, 2020).
- Limitations: technological infrastructure may be unavailable; informal units/workers may lack capital to invest in technology.
- Digital platforms can be useful data sources (income and location), but compilers need expense data to derive benchmark input-output indicators; surveys of households and targeted service-provider surveys may be necessary.
- Platform-perspective data can make distinguishing formal registered transactions from unregistered informal transactions difficult; example: National Bureau of Statistics of China established an Internet Economic Statistics System of quarterly and annual surveys on major e-commerce trading platforms.

### Definition, scope, and the ILO framework
- The 15th ICLS (1993) definition: informal sector comprises units engaged in production of goods or services with the primary objective of generating employment and incomes to the persons concerned.
- Key characteristics of informal sector units:
  - Low level of organization; production usually small scale; little or no separation between labor and capital.
  - Constitute part of household entity (unincorporated household enterprises).
  - Undertake market production.
- Table 3 criteria (15th ICLS) include legal organization, ownership, type of accounts, product destination, kind of economic activity, number of persons engaged, and non-registration of enterprise/employees.
- The ILO’s approach defines informal sector in terms of the production unit; persons are considered informally employed if employed in a unit in the informal sector.

### The informal sector, informal employment, and the production boundary
- The informal sector does not segment the economy into exhaustive formal and informal groups; exclusions from the informal sector are not necessarily part of the formal sector.
- Informal employment (17th ICLS) captures informal jobs both within and outside the informal sector, including in households; employees have informal jobs if not subject in law or practice to labor legislation, income taxation, social protection, or entitlement to certain employment benefits.
- One person can hold jobs both in the formal sector and in the informal sector.
- The proposed statistical definition consolidates:
  - Production of informal sector units (ILO);
  - Production of goods by households for own final use;
  - Production of services by paid domestic staff; and
  - Production generated by informal employment in formal enterprises.
- These elements fall within the production boundary of the 2008 SNA and are consistent with the concept of production used to define GDP.
- Housing services produced by owner-occupiers are excluded from the informal economy.

### Treatment of specific activities
- Household production of goods for own final use is within the production boundary (2008 SNA, para. 6.82); separating own-use production from market production is practically difficult.
- Services of paid domestic staff are treated as employees of an unincorporated enterprise owned by the household (2008 SNA, para. 6.116) and should be included where production generates income.
- Production generated by informal employment in formal enterprises requires allocation of enterprise activities based on the nature of employment to estimate informality proportionally.

### Continuum of formality and multidimensional assessments
- The relationship between formality and informality is a continuum; units may meet some but not all criteria.
- Mbaye and Tall (2019) find heterogeneity applying seven criteria of informality to firms in francophone Africa.
- Colombia (DANE) is developing a multidimensional index of business formality across four dimensions: (i) entry; (ii) inputs; (iii) output; (iv) taxation.

### Non-observed economy and overlaps
- The informal economy overlaps with the non-observed economy but is not synonymous with it; non-observed economy includes activities omitted due to illegality, concealment, household production, or data collection deficiencies.
- Underground activities (Handbook definition) are legal and economically productive but concealed to avoid taxes, legal standards, or administrative procedures; overlaps with informal sector activities can cause inconsistencies.

### Data collection and estimation techniques
- Two broad approaches:
  - Direct approaches based on surveys (household surveys, enterprise surveys, dedicated surveys, mixed surveys).
  - Indirect approaches (“indicator” approaches) based on related statistics and macroeconomic estimation techniques (monetary methods, global indicator methods, MIMIC, supply-based, demand-based, commodity flow methods).
- Supply-based methods rely on inputs used in production; labor input method is a supply-based application using labor inputs to “gross-up” enterprise estimates.
- Demand-based methods use data about uses (e.g., household final consumption expenditures); best when a product has one major use.
- Commodity-flow methods estimate total supply of goods and services, generally applied to goods-producing activities.
- Supply and use tables are useful for gap identification but are costly; recommended minimum frequency of five years given cost constraints.
- Labor force surveys often need modification to capture secondary or sporadic informal jobs and full-time equivalents.

### Country practices: India and Mexico examples
- India: “unorganized sector” used interchangeably with “informal sector”; benchmark GVA derived using labor input and value added per worker; own-account production, imputed owner-occupied dwellings, services of domestic servants, and activities of unrecorded enterprises are included. India Box Table shows Organized and Unorganized sector shares by activity and TOTAL GVA at basic prices (e.g., TOTAL GVA at basic prices: Organized 46.1; Unorganized 53.9; of which: Households 45.5 (2011/12); Organized 47.6; Unorganized 52.4; of which: Households 43.1 (2017/18)).
- Mexico (INEGI): defines informal economy as (i) the ILO informal sector; and (ii) other modalities of informality (value added by informal employees in formal enterprises, value added in agriculture including own-consumption, paid domestic work). INEGI uses multiple data sources including economic censuses, National Occupation and Employment Survey, National Household Income and Expenditure Survey, employment statistics from the Social Security Institute, and supply and use tables.

### Non-official estimates, big data, and cautions
- Non-official indirect approaches assume unmeasured activity is informal or underground; three groups include monetary methods, global indicator methods (e.g., electricity consumption, nighttime lights), and MIMIC models.
- The Handbook cautions that these models may produce high but unreliable measures; MIMIC faces criticism over specification and assumptions.
- Big data (e.g., satellite nighttime lights) has been used to support GDP compilation (e.g., Leon and Lima (2019) for Zimbabwe) but assumes differences between official and model estimates reflect informal and illegal activity.

### Commodity-flow methods, informal financial services, and statistical capacity
- Commodity-flow methods are suited to goods-producing activities and associated supply chains.
- Informal financial services (examples: Tanda; Iqub in Ethiopia) require surveys to estimate credit and savings mobilized through these arrangements.
- Weak statistical capacity and irregular funding for benchmark surveys remain key impediments; many developing countries attempt household income and expenditure surveys at five- to ten-year intervals but face irregularity.

### Recommendations — International organizations
- Promote a consistent methodological framework and clarify concepts and definitions relating to the informal economy across national accounts, external sector statistics, and labor statistics.
- Integrate conceptual and methodological guidance into the next version of international statistical standards.
- Identify country best practices in data collection and develop practical guidance accounting for technical and resource availability.
- Improve coordination among donor agencies to aim for adequate funding with regular frequency.
- Develop dedicated training and technical assistance focused on measuring the informal economy and improving annual and quarterly GDP estimates.
- Consider mechanisms to support national statistical agencies in collecting data from multinational corporations and digital platforms.

### Recommendations — National statistical agencies
- Develop estimates of the informal economy as core aggregates—alongside GDP, GNI—for dissemination at regular frequency; quarterly frequency is preferable though resource intensive.
- Amend labor statistics collection programs to capture employment status, economic activity of employment, and full-time equivalents to aid derivation of labor output estimates.
- Compile supply and use tables at regular frequency; minimum frequency recommended of five years given costs.
- Promote use of administrative data, in particular from tax authorities, to provide estimates of informality in the digital economy.

### IMF Committee on Balance of Payments Statistics: Task Force on Informal Economy (TFIE) — findings and recommendations
- TFIE (2017 mandate) inventoried country practices and identified a range of data collection techniques and compilation methods for covering informal economy in external sector statistics.
- Findings:
  - Compilation practices center on the current account (goods), personal transfers and workers’ remittances (secondary income), and services (travel, transport, prostitution, gambling, smuggling of migrants’ services).
  - Economies use combinations of direct and indirect sources; availability of separately identifiable data on IE activities remains limited.
  - Data sources, enterprise registration, and methodology are major challenges.
- Final TFIE recommendations:
  - Continue disseminating collection and compilation practices via the web platform.
  - Tailor collection and compilation to available data sources, statistical capacity, and cost/benefit assessments.
  - Strengthen coordination between external sector statistics and national accounts compilers; encourage exchanges with regulatory/policy agencies.
  - Address informal economy issues in the financial account and IIP; use mirror statistics (e.g., BIS International Banking Statistics) where necessary.
  - Identify regional trends and tailor estimation methods to major regional informal/illegal activities.
  - Where possible, establish legal and institutional frameworks, confidentiality, and coordination among agencies (example: EU statistical regulations for some illegal activities).
  - Reassess the concept of the informal economy for greater harmonization and cross-country comparability.
  - Use big data to complement traditional sources where relevant.
  - Strengthen technical assistance and training to help economies identify data gaps and compile relevant informal economy data.

*Source: EXECUTIVE SUMMARY and selected excerpts, ppea2021002 (November 24, 2020).*

### EXECUTIVE SUMMARY

### EXECUTIVE SUMMARY

### Proposed statistical framework for the informal economy
- The paper proposes a framework for measuring the informal economy that is consistent with internationally agreed concepts and methodology for measuring GDP.
- Under the proposed framework, the informal economy “comprises production of informal sector units, production of goods for own final use, production of domestic workers, and production generated by informal employment in formal enterprises.”
- The proposed framework is intended to facilitate preparation of estimates of the informal economy as a component of GDP.

### Policy relevance and major implications
- Measuring the informal economy informs policy on economic growth, aggregate production, potential tax revenue, and income distribution.
- Informal workers may be more vulnerable to negative shocks such as the COVID-19 pandemic, facing greater income losses without the benefit of social protection; lack of registration may hinder their access to government interventions.
- Digitalization has created new opportunities for informal employment and generated new data sources that statistical compilers may use to measure the informal economy.

### Conceptual fragmentation and need for a consistent taxonomy
- An internationally agreed statistical framework for measuring the informal economy has been lacking, despite an ILO analytical definition.
- Diverse criteria have been used in practice—economic activity missing from official statistics, production outside the regulated economy, or production of households—leading to inconsistent definitions and estimates.
- Terms such as “shadow economy,” “underground economy,” and “hidden economy” have been used interchangeably, complicating policy discussions and cross-country comparisons.
- A consistent framework would improve cross-country comparability and link measurement to policy purposes.

### Measurement findings and empirical evidence (selected)
- Model-based measures (e.g., MIMIC) suggest declines in informal output as a percentage of GDP across regions between 1990–2017, but levels remain high in Sub-Saharan Africa and Latin America, averaging around 34 percent between 2010–2017.
- Using MIMIC and Dynamic General Equilibrium models, Elgin and others (2019) estimate that between 1990–2016 the share of informal output:
  - fell by about 7 percentage points of GDP in emerging and developing economies (to 32 percent of GDP);
  - fell by about 4 percentage points (to 17 percent of GDP) in advanced economies.
- The share of informal economic activity may vary over the business cycle; unmeasured variation could exaggerate GDP volatility.
- Tax-base considerations: taxing the informal economy would broaden the tax base and increase government revenue, but measures for national accounts purposes differ from measures of revenue not reported to tax authorities.
- Empirical evidence on cyclicality of the informal economy is mixed: studies focusing on shares tend to find countercyclical behavior, while studies on levels tend to find procyclical results; results remain inconclusive partly due to measurement difficulty.

### Effects on productivity, firms, and labor
- Informal firms can generate inefficiencies by avoiding detection or facing heavy administrative burdens in the formal sector; resources may be diverted to mask activities, and firms may remain sub-optimally small.
- Lower costs from avoiding tax and regulatory compliance can allow low-productivity firms to stay in business, potentially reducing formal-sector incentives to innovate and adopt new technologies.
- Informal employment can provide support where formal job creation lags labor force growth; poverty rates are higher among informal workers, though not all informal workers are poor.
- Wage differentials:
  - Informal sector wages are on average below those in the formal sector.
  - Factors behind wage differentials include worker characteristics, non-wage benefits (flexibility, independence), and labor regulations or tax provisions creating wedges between similar workers.
  - A World Bank (2019) analysis of 18 studies finds formal wage premia tend to be higher where informality is more widespread; when controlling for unobserved worker characteristics, the formal wage premium largely disappears.
- Informal employment is more prevalent in rural areas.

### Key statistics on informal employment by grouping (2016)
- Table 1 excerpts (percent):
  - Informal Emp.: 61 18 67 90
  - Rural: 80 22 83 90
  - Urban: 44 17 51 79
  - Agriculture: 94 59 93 98
    - Rural: 95 64 95 98
    - Urban: 87 49 82 98
  - Industry: 57 16 67 73
    - Rural: 69 17 75 87
    - Urban: 49 15 61 65
  - Services: 47 18 55 74
    - Rural: 65 19 71 79
    - Urban: 39 17 47 70
- Source: Women and Men in the Informal Economy—A Statistical Brief (2019); ILO calculations based on national labor force data.

### Measurement challenges and data approaches (overview)
- Informal activity is often small-scale or hidden, operating below registration or tax thresholds or actively evading detection, complicating measurement.
- Official statistics are generally lacking; users resort to a wide range of unofficial estimates.
- The paper reviews: the need to align a statistical framework with macroeconomic statistics; options for data collection and estimation techniques (including official statistics, non-official estimates, and model-based approaches such as MIMIC); and the approach of the non-observed economy.

### Structure of the paper (contents summary)
- The paper includes: Glossary; Introduction; Policy Implications of Measuring Informality (A. Economic Growth, Productivity, and Labor; B. Impact of the COVID-19 Pandemic on Informality; C. Digitalization and Informality); Definition and Scope and the need for a taxonomy; A Proposed Framework for the Informal Economy; Data Collection and Estimation Techniques (overview, official statistics, non-official estimates); Conclusion and Recommendations.
- Boxes and case studies include: Illegal Actions and Illicit Financial Flows; Mexico: Estimating the Informal Economy; India: Estimating the Unorganized Sector.
- Figures and tables highlight regional and time-series patterns (Figures 1–3) and conceptual criteria and frameworks (Tables 1–4).

*Source: EXECUTIVE SUMMARY, ppea2021002 - EXECUTIVE SUMMARY (November 24, 2020).*

### 17.      Informality is an important source of employment for women who may not be able to

### 17.      Informality is an important source of employment for women who may not be able to access formal employment

### A. Informality and women's employment
- The ILO estimates that in developing economies, more women than men are informally employed.
- The informal economy provides opportunities to increase the participation of women in the economy and provides a source of income.
- Women tend to be in the type of employment relationships that have lower earnings and a higher risk of poverty (Women in Informal Employment: Globalizing and Organizing (WIEGO, 2012)).

### B. Share of Informal Employment by Age and Sex, 2016 (Table 2)
- Total: World 61; Men 63; Women 58.
- Total by region:
  - Developed: Total 18; Men 19; Women 18.
  - Emerging: Total 67; Men 69; Women 64.
  - Developing: Total 90; Men 87; Women 92.
- Age 15–24: World 77; Men 79; Women 73.
  - Developed: 19; Men 19; Women 19.
  - Emerging: 83; Men 85; Women 79.
  - Developing: 97; Men 97; Women 97.
- Age 25–64: World 58; Men 60; Women 54.
  - Developed: 17; Men 17; Women 16.
  - Emerging: 66; Men 67; Women 62.
  - Developing: 90; Men 87; Women 93.
- Age 65 and over: World 77; Men 78; Women 75.
  - Developed: 38; Men 39; Women 37.
  - Emerging: 88; Men 88; Women 88.
  - Developing: 96; Men 95; Women 98.
- Source note: Women and Men in the Informal Economy—A Statistical Brief (2019); ILO calculations based on national labor force data.

### C. Impact of the COVID-19 Pandemic on Informality
- Informal workers are more vulnerable to negative shocks such as the COVID-19 pandemic.
- Government measures to curtail COVID-19 (lockdowns and other measures) severely impacted sectors with high concentrations of informal workers, including:
  - domestic workers;
  - accommodation and food services;
  - manufacturing; and
  - retail.
- More than 500 million farmers producing for the urban market were affected (ILO, 2020).
- Informality is prevalent in activities requiring direct interaction with consumers or other producers; social distancing and work-from-home arrangements may limit the ability to work and generate income for many service workers.
- Some countries applied light or no systemic lockdowns to avoid severe impacts on informally employed workers.
- Agriculture in developing economies may be less affected where production is subsistence on small farms, but:
  - income from sale of excess production may be affected by movement curtailments and demand decline;
  - agricultural supply chains may be disrupted by lockdowns and restrictions in movement leading to dampened demand for fresh produce.
- Challenges in delivering government interventions to informal workers:
  - Informal workers often have no insurance against income loss and are often unregistered, making direct income support delivery difficult.
  - Government support based on income or employment status may not efficiently target informal workers not included in employment or tax databases.
  - Programs may need to apply non-income methods with eligibility determined by proxies of income including demographic characteristics, place of residence, or ownership of assets (Prady 2020).
- Social assistance coverage statistics cited:
  - Social assistance programs cover 20 percent of the population in Africa and 40 percent in Latin America (Diez and others (2020)).
- In-kind transfers and school feeding programs play an important role, notably in Africa, but may be hard to provide under COVID-19 containment measures.
- If government programs cannot reach informal workers, mitigation efforts may be hampered; informal workers may continue to work without adequate protection, increasing health risks.
- Migrant and undocumented workers, and rural workers without adequate access to information and medical treatment, remain vulnerable (FAO, 2020).

### D. Digitalization and Informality
- Digitalization has created more opportunities for individuals to engage in informal jobs (gig economy) as main jobs or to supplement income.
  - New services (e.g., ride-hailing) and expanded existing opportunities (service hosting platforms helping domestic workers, skilled workers, producers of artisanal products).
- Digitalization can increase financial inclusion:
  - Mobile money and other digital payment forms have been increasing in developing countries with high informality (Financial Access Survey, IMF).
  - Mobile money services may expand into credit, savings, and insurance for informal workers and encourage entrepreneurship (Jacolin, Massil, and Noah, 2019).
  - In response to COVID-19, some countries have encouraged mobile money as a substitute for cash to minimize physical interaction and provide more access points (IMF, 2020).
- Limitations to digitalization opportunities:
  - Technological infrastructure for broadband and computerization may be unavailable.
  - Informal units and workers may lack capital to invest in technology.
- Digital platforms can be a useful source of data on informality:
  - Platforms collect information on income and location of service providers (e.g., ride-hailing transaction values; accommodation hosting revenue).
  - Compilers need alternative sources to collect data on expenses related to these activities to derive benchmark input-output indicators—surveys of households and targeted surveys of service providers may be necessary.
  - Data collection may be complicated when providers are based in a limited number of economic territories; compilers may need ways to collect data from non-resident enterprises lacking legal support to collect such information.
- Services on digital platforms may be provided by both formal and informal units:
  - E-commerce trading platforms can host large registered enterprises and multiple unregistered small producers.
  - Digital platform data may need supplementation or reconciliation with other sources such as surveys of registered enterprises.
  - National practice example: National Bureau of Statistics of China established an Internet Economic Statistics System of quarterly and annual surveys on major e-commerce trading platforms; platform-perspective data can make distinguishing formal registered transactions from unregistered informal transactions difficult, requiring additional formal-unit data to estimate informal-unit activities.

### E. Definition and scope: conceptual fragmentation and need for taxonomy and consolidation
- Debate over the definition and scope of informality is longstanding; literature is broad with debate on what constitutes the informal economy and how to measure it.
- Variations in definitions include:
  - Smith (1987): informal activities eluding national accounts because counting mechanisms do not detect them.
  - Giles (1999): similar definition for the “hidden economy.”
  - Tanzi (1983): excludes illegal activities in estimating the “underground” economy.
  - Feige (1990, 2015): distinguishes four underground economies—illegal economy; unreported economy; unrecorded economy; informal economy (circumvention of labor market regulations).
- Policy and research motivations shape parameters for defining informality:
  - Tax-based definitions focus on cost and benefit of informality and reasons for not paying taxes (Heintz 2012; Kanbur and Keen 2015).
  - Definitions aimed at identifying units outside the regulated formal economy align with deriving exhaustive estimates of economic activity.
- Chen (2012) classification of informal economy debates into four schools: dualist, structuralist, legalist, voluntarist; but the informal economy is acknowledged as heterogeneous and complex.
- International statistical standards do not provide definitions of the formal and informal economy but recognize formal and informal procedures (banking and financial laws, property regulations, fiscal obligations, labor codes).
- The concept of informality has three key statistical components:
  - (i) informal employment: employment and jobs;
  - (ii) informal units;
  - (iii) informal activity: production of goods and services.
- Informal production can be identified based on unit characteristics (e.g., formal registration for tax) or activity characteristics (e.g., household production for own final use or domestic staff services). These components are intrinsically linked and should form the basis of an overarching framework for the informal economy.

### F. The ILO framework: the informal sector (15th ICLS)
- The statistical definition from the Resolution concerning statistics of employment in the informal sector (15th ICLS, 1993):
  - The informal sector comprises units engaged in the production of goods or services with the primary objective of generating employment and incomes to the persons concerned.
- Key characteristics of informal sector units:
  - Low level of organization: production usually on a small scale; little or no separation between labor and capital; labor relations based on casual employment, kinship or personal and social relations rather than contractual arrangements with formal guarantees.
  - Constitute part of household entity (not separate legal entities): units are household unincorporated enterprises that (i) cannot engage in transactions or enter into contracts with other units, nor incur liabilities, on their own behalf; and (ii) the assets used in production do not belong to the production units but to the owners of the production units.
  - Undertake market production: units engaged in production of goods or services with the primary objective of generating employment and incomes for the persons concerned.
- Table 3. Criteria for Defining Informal Sector Enterprises (15th ICLS) — criteria listed:
  1. Legal organization: enterprise not constituted as a legal entity separate from its owner(s). Identification of unincorporated enterprises.
  2. Ownership: enterprise owned and controlled by member(s) of household(s). Identification of household unincorporated enterprises.
  3. Type of accounts: no complete set of accounts, including balance sheets. Exclusion of quasi-corporations from household unincorporated enterprises.
  4. Product destination: at least some market output. Identification of household unincorporated enterprises with at least some market production; exclusion of household unincorporated enterprises producing goods exclusively for own final use by the household.
  5. Kind of economic activity. Exclusion of households employing paid domestic workers; possible exclusion of enterprises engaged in agricultural and related activities.
  6.1 Number of persons engaged/employees/employees employed on a continuous basis: fewer than ‘n’. Identification of informal sector enterprises as a subset of household unincorporated enterprises with at least some market production.
  6.2 Non-registration of the enterprise, and/or
  6.3 Non-registration of the employees of the enterprise.
- The ICLS guidelines define the informal sector in terms of the production unit (consistent with national accounts) rather than characteristics of persons. Persons are considered informally employed if employed in a unit in the informal sector; persons not employed in production units in the informal sector are not considered employed in the informal sector even if they may not have formal jobs.

*Source: ppea2021002 - 17. Informality is an important source of employment for women who may not be able to access formal employment*

### 32.      The definition of the informal sector does not segment the economy or employment

### 32.      The definition of the informal sector does not segment the economy or employment

### Overview
- The definition of the informal sector does not segment the economy or employment into two exhaustive formal and informal groups. Some activities and employment categories excluded from the informal sector are not necessarily in the formal sector (paragraph 32).
- The 2008 SNA distinguishes between: (i) market production; and (ii) non-market production (footnote 15).

### Informal employment and informal jobs
- Informal employment is defined according to the guidelines of the 17th ICLS and captures all informal jobs both within and outside the informal sector, including in households (paragraph 33; footnote 16).
- Employees have informal jobs if their employment relationship is, in law or in practice, not subject to national labor legislation, income taxation, social protection or entitlement to certain employment benefits such as advance notice of dismissal, severance pay, paid annual or sick leave (17th ICLS para. 3.5) (paragraph 33).
- The definition recognizes multiple jobholding: one person can have jobs both in the formal sector and in the informal sector (paragraph 33).
- The ILO recognizes the following broad groups of jobs (paragraph 34):
  - own-account workers;
  - employers;
  - unpaid family workers;
  - employees; and
  - members of producers’ cooperatives.

### Conceptual distinctions: informal employment vs. employment in the informal sector
- Employment in the informal sector is a subset of informal employment; it is a job-based concept that relies on the type of enterprise and captures the labor supply in the informal sector (paragraph 35).
- Table 4 conceptual framework notes that the ILO definitions allow for the existence and recording of formal employment in the informal sector (footnote 1), which the text highlights as counterintuitive (paragraph 35 and footnote).

### Analytical framework and scope of the informal economy
- There is a need for an analytical approach to measure economic activity by individuals without formal employment who engage in activity to generate income for household consumption or to acquire household assets; compilation efforts should aim at deriving comprehensive estimates of economic activity deliberately hidden from the authorities (paragraph 36).
- The ILO proposed a definition of the informal economy covering all economic activities by workers and economic units that are—in law and in practice—not covered or insufficiently covered by formal arrangements (ILO, 2002) and explicitly excludes illicit activities (paragraph 37).

### Inclusion of illicit activities and production boundary
- The 17th ICLS excludes illicit activities, but the broader concept of production in macroeconomic statistics treats some illegal actions as production when they satisfy transaction characteristics (paragraphs 39–41; Box 1).
- Only illegal activities that are undertaken in the informal sector or generated through informal employment should be included in the informal economy (paragraph 39).
- Examples:
  - Example A: Individual produces illegal drugs in the home for sale — production by a household for sale and therefore informal (paragraph 40).
  - Example B: Registered corporation commits tax evasion — illegal action but the registered corporation is not an informal entity (paragraph 41).

### Proposed statistical definition of the informal economy
- The paper advocates consolidating a statistical definition comprising (paragraph 42):
  - Production of informal sector units, as proposed by the ILO;
  - Production of goods by households for own final use;
  - Production of services by paid domestic staff; and
  - Production generated by informal employment in formal enterprises.
- These elements fall within the production boundary of the 2008 SNA and are consistent with the concept of production used to define GDP; the production of the informal economy is a component of aggregate production (GDP) (paragraph 43).
- The production of services for own consumption within the same household falls outside the production boundary of the SNA, except for housing services produced by owner-occupiers and services produced by employing paid domestic staff (2008 SNA para. 9.54) (paragraph 43).
- Housing services produced by owner-occupiers are excluded from the informal economy (paragraph 43).

### Treatment of specific activities
- Household production of goods for own final use:
  - All goods produced by households are within the production boundary; those not delivered to other units are consumed or stored (2008 SNA, para. 6.82) (paragraph 45).
  - Practically, it is difficult to separate household own-use production from market production; household own-use production is a source of consumption and often a substitute for income in developing economies (paragraph 45).
- Services of domestic staff:
  - Paid domestic staff are formally treated as employees of an unincorporated enterprise owned by the household (2008 SNA, para. 6.116) (paragraph 46).
  - An economic argument cannot be made for excluding services of domestic staff if the goal is to generate income (paragraph 46).
- Informal employment production in formal enterprises:
  - Estimating value requires allocation of enterprise activities based on the nature of employment to estimate informality based on the proportional contribution of informal employment (paragraph 47).

### Practical definitions and compilation implications
- A practical definition of the informal sector can be built on the enterprise approach; a practical definition of the broader informal economy can be based on the labor approach (paragraph 48).
- The informal economy includes enterprise units considered informal and units not considered informal that generate output using informal employment (paragraph 48).
- Applying the employment criterion requires granular estimation of production of enterprises outside the informal sector and would require enterprise-level data or industry estimates of cost structure of production (including wages) (paragraph 48).

### Extending the framework to cross-border flows
- The domestic production in the informal economy may relate to cross-border transactions (shuttle trade, smuggling, tourism services for non-residents, vacation rentals, small eating establishments) and remittances transmitted through informal channels (paragraph 49).
- Informal workers may transmit remittances through formal money transfer channels; income from the informal economy may generate imports of consumer goods and services such as tourism (paragraph 50).
- Omissions in international trade statistics can arise from cross-border transactions outside regular statistical inquiries; some omissions relate to informal units, others to large corporations and government units (paragraph 51).

### Country practice example: Mexico
- Mexico (INEGI) defines the informal economy as:
  - (i) the ILO informal sector; and
  - (ii) other modalities of informality (value added by informal employees in formal enterprises, value added in agriculture including own-consumption, paid domestic work) (Box 2).
- INEGI uses multiple data sources: economic censuses; National Occupation and Employment Survey; National Household Income and Expenditure Survey; employment statistics from the Social Security Institute; and supply and use tables (Box 2).

### Institutional work and measurement efforts
- A Task Force under the IMF Committee on Balance of Payments Statistics was established in 2017 with a two-year mandate to take stock of country practices in measuring informal transactions in external sector statistics and identified a range of data collection techniques and compilation methods (paragraph 52).

### Informality as a continuum
- The relationship between formality and informality ranges between fully regulated/monitored (formal) and unregulated/non-monitored (informal); units may meet some but not all criteria, implying a continuum rather than a strict dichotomy (paragraph 53).

*ppea2021002 - 32.      The definition of the informal sector does not segment the economy or employment*

### 54.      The continuum of formality in identifying informal units also can apply to the use of

### 54.      The continuum of formality in identifying informal units also can apply to the use of

### Continuum of formality and informal employment
- A unit can be formally identified (for example, incorporated) yet employ informal workers (e.g., a large trucking company providing social protections for drivers but employing porters informally; a construction company recruiting casual day laborers).
- If informality is regarded as a continuum, relying solely on institutional units such as the enterprise distorts estimates of the informal economy.
- Mbaye and Tall (2019) apply seven criteria of informality to firms in francophone Africa and find considerable heterogeneity based on firms’ positions along the continuum.

### Multidimensional index of business formality (Colombia)
- DANE is developing a multidimensional index of business formality that assesses informality across four sequential dimensions from market entry to maturity:
  - (i) entry (commercial registration; tax registration)
  - (ii) inputs (formal contracting; affiliation to health, pensions, occupational risks and social benefits)
  - (iii) output (compliance with health, technical and environmental regulations)
  - (iv) taxation (tax declaration; payment of taxes; formal accounting)
- The index uses a sequential process to assess informality based on these four dimensions.

### The Approach of the Non-observed Economy
- Regular macroeconomic statistics assume structured systems where enterprises are registered and observable; activities omitted due to illegality, concealment, household production, or data collection deficiencies form the non-observed economy.
- The informal economy overlaps with the non-observed economy but is not synonymous with it.
- The Handbook on Measuring the Non-Observed Economy (OECD 2002) provides a conceptual framework for activities excluded from basic data on production, income, and expenditure.

### Definitions: informal sector and underground activities
- Informal sector activities:
  - Production undertaken by unincorporated enterprises in the household sector.
  - Goods and services may be legal but may bypass regulations or taxes.
  - Characteristically small-scale with few or no employees.
  - Household assets associated with informal activities are not differentiated from other household assets.
  - The 15th ICLS definition is followed by the ILO, the 2008 SNA, and the Handbook.
  - The household units engaged in informal activities constitute the informal sector — a subset of the household sector.
  - This implies excluding activities of households producing goods exclusively for own final use and activities of paid domestic workers from the informal sector definition despite their inclusion in the SNA production boundary.
- Underground activities (Handbook definition):
  - Legal and economically productive but concealed to: (i) avoid taxes and social security contributions; (ii) avoid legal standards (minimum wage, maximum hours, safety/health); (iii) avoid administrative procedures.
  - May include undeclared transactions, overstated expenses, and non-reporting of employees or compensation.

### Boundary problems and overlaps
- There is considerable overlap between informal sector activities and underground activities, causing potential inconsistencies over time and across countries.
- Informal activities are exclusively undertaken by households, but households may also undertake underground activities (e.g., unregistered taxi, unlicensed electrician, illegal drug production).
- A significant proportion of underground activities are undertaken by business enterprises (e.g., unlicensed factories) that may employ staff and hold distinguishable nonfinancial assets; such enterprises may be omitted from regular data collection.

### Data collection and estimation techniques — overview
- Two broad approaches to estimate the informal economy:
  - (i) direct approaches based on surveys
  - (ii) indirect approaches (“indicator” approaches) based on related statistics and macroeconomic estimation techniques
- Detailed estimates can be compiled for a benchmark year; indicators can adjust levels for subsequent years until a new benchmark is developed. Regular updates of benchmarks are needed.

### Official statistics — data sources and limitations
- Main data collection methods:
  - Household surveys (household budget/income and expenditure surveys) — often inadequate in coverage, scope, timeliness; recommended frequencies five or ten years but often not met.
  - Enterprise surveys — based on business registers listing units with physical business addresses; difficult to list informal units lacking separate addresses; enterprise surveys often lack detailed labor market data to identify informal employment in formal enterprises.
- Dedicated surveys on informal enterprises are required to capture production (income and expenditure), economic activity, and employment.
- Mixed (1-2-3) surveys combine household and enterprise modules to identify household enterprises and measure enterprise transactions.
  - Example: Vietnam collaboration since 2007 between the General Statistics Office and the French Research Institute for Sustainable Development to design methodology to account for the informal economy; results suggest significant underestimation of GDP, though the survey system has not yet been institutionalized.
- Labor force surveys often need modification to capture informal employment (they typically request only primary employment and may miss secondary or sporadic informal jobs and jobs outside the reference period).

### Official statistics — estimation methods
- No single universal approach fits all countries; suitability depends on measurement objectives, national statistical system capacity, existing surveys, and resources.
- Main indirect approaches:
  - Supply-based methods: rely on inputs used in producing goods and services (primary raw materials, labor, fixed capital). Example: estimate small construction output from sales of construction materials plus estimated labor inputs, fixed capital stock, and profit margins.
  - Labor input method (a supply-based application): use labor input estimates from household labor force surveys/demographic sources as weighting factors to “gross-up” enterprise survey estimates; combine with enterprise survey estimates of output and value-added per unit of labor to estimate activity. Requires reliable labor input and per-unit ratios and can estimate total production or non-observed production.
  - Demand-based methods: determine production by using data about uses (e.g., household final consumption expenditures of personal services, building permits). Best applied when a product has one major use.
  - Commodity flow methods (mentioned as a broad class alongside supply- and demand-based).
- Supply and use tables:
  - Useful to identify gaps by reconciling supply (output + imports) with use (intermediate consumption + final consumption + capital formation + exports).
  - Compilation is costly and time-consuming; many developing countries produce them at five-year intervals or less frequently; there is usually a lag of over one year between reference period and data availability.

### Box 3 — India: Estimating the Unorganized Sector
- Terminology and coverage:
  - In India, “unorganized sector” and “informal sector” are used interchangeably in official statistics.
  - Unorganized sector covers units that may not maintain regular, comprehensive accounts and whose activities are not regulated under any Statutory Act: enterprises operated by own-account workers and unregistered enterprises.
  - Unincorporated enterprises that maintain accounts are considered quasi corporations and included in the organized (formal) sector.
- Estimation approach:
  - Benchmark gross value added (GVA) for an activity is derived using estimated labor input and the value added per worker (labor input method is based on number of jobs, not number of persons).
  - Subsequent years’ GVA estimated by extrapolation using indicators relevant to the activity.
  - Benchmark data sources: surveys of small operating units (value of output, intermediate inputs, changes to capital stock); unorganized agriculture uses land use, area under cultivation, and input estimates.
- Box Table: India − Organized and Unorganized Sector by Economic Activity (as a share of gross value added)
  - Agriculture, forestry and fishing: Organized 3.2; Unorganized 96.8; of which: Households 94.8 (2011/12)
  - Mining and quarrying: Organized 77.4; Unorganized 22.6; of which: Households 22.6 (2011/12)
  - Manufacturing: Organized 74.5; Unorganized 25.5; of which: Households 12.7 (2011/12)
  - Electricity, gas, water: Organized 95.7; Unorganized 4.3; of which: Households 3.2 (2011/12)
  - Construction: Organized 23.6; Unorganized 76.4; of which: Households 76.4 (2011/12)
  - Accommodation; food services; trade: Organized 13.4; Unorganized 86.6; of which: Households 56 (2011/12)
  - Transport, storage, communication: Organized 53; Unorganized 47; of which: Households 39.6 (2011/12)
  - Financial services: Organized 90.7; Unorganized 9.3; of which: Households 0 (2011/12)
  - Real estate, ownership of dwellings: Organized 36.9; Unorganized 63.1; of which: Households 57.2 (2011/12)
  - Public administration and defense: Organized 100; Unorganized 0; of which: Households 0 (2011/12)
  - Other services: Organized 58.8; Unorganized 41.2; of which: Households 22.6 (2011/12)
  - TOTAL GVA at basic prices: Organized 46.1; Unorganized 53.9; of which: Households 45.5 (2011/12)
  - Agriculture, forestry and fishing (2017/18): Organized 2.9; Unorganized 97.1; of which: Households 95.2
  - Mining and quarrying (2017/18): Organized 77.5; Unorganized 22.5; of which: Households 22.5
  - Manufacturing (2017/18): Organized 77.3; Unorganized 22.7; of which: Households 12
  - Electricity, gas, water (2017/18): Organized 94.7; Unorganized 5.3; of which: Households 5.3
  - Construction (2017/18): Organized 25.5; Unorganized 74.5; of which: Households 74.5
  - Accommodation; food services; trade (2017/18): Organized 13.4; Unorganized 86.6; of which: Households 55.8
  - Transport, storage, communication (2017/18): Organized 52.3; Unorganized 47.7; of which: Households 39.6
  - Financial services (2017/18): Organized 88.1; Unorganized 11.9; of which: Households 0
  - Real estate, ownership of dwellings (2017/18): Organized 47.2; Unorganized 52.8; of which: Households 46
  - Public administration and defense (2017/18): Organized 100; Unorganized 0; of which: Households 0
  - Other services (2017/18): Organized 52.1; Unorganized 47.9; of which: Households 24.3
  - TOTAL GVA at basic prices (2017/18): Organized 47.6; Unorganized 52.4; of which: Households 43.1
- India’s unorganized sector estimates include:
  - (i) own account production of goods;
  - (ii) imputed services of owner-occupied dwellings;
  - (iii) services of domestic servants; and
  - (iv) activities of unrecorded enterprises.

*MEASURING THE INFORMAL ECONOMY, INTERNATIONAL MONETARY FUND*

### 74.      Commodity-flow methods attempt to estimate economic activity by indirectly

### ppea2021002 - 74.      Commodity-flow methods attempt to estimate economic activity by indirectly

### Commodity-flow methods and scope
- Commodity-flow methods attempt to estimate economic activity by indirectly estimating the value of the total supply of goods and services.
- These methods are generally used for goods producing activities, or for activities associated with the supply of goods such as agriculture, distribution, and small-scale manufacturing.

### Informal financial services and survey needs
- Informal units may utilize informal financial services; surveys likely are needed to capture these services.
- Examples of informal financial services cited:
  - The Tanda (informal loan club).
  - Iqub in Ethiopia (rotating savings and credit type association).
- Surveys of these informal financial services would be useful to estimate credit and savings of informal units.
- Ascertaining the amount of credit and savings mobilized through these arrangements would be key to estimate the size of the informal economy in some countries.

### Statistical capacity and resource availability
- Weak statistical capacity—mainly due to the unavailability of sufficient resources for collecting source data—remains a key impediment to developing reliable estimates of the informal economy.
- Coverage of the informal economy requires source data collected through surveys and censuses.
- Many developing countries attempt to undertake household income and expenditure surveys at regular five to ten years, but in practice the frequency may be irregular and there may be significant gaps.
- Surveys may be designed for a range of purposes (e.g., to derive household expenditure patterns) and may therefore lack the income/revenue detail required to derive comprehensive estimates of the informal economy.
- Many countries rely on donor funding to undertake the benchmark data collection exercises used to estimate informal activity; funding may be irregular and provided to meet immediate needs, reflected in irregular frequency of benchmark estimates.

### Non-official estimates: methods and cautions
- Non-official estimates are based on indirect approaches that assume unmeasured activity—the difference between official GDP and non-official estimates—is informal or underground.
- Three broad groups of non-official methods:
  - Monetary methods (include the transactions method, the cash deposit/ratio, and the cash demand method).
  - Global indicator methods (such as the electricity consumption approach).
  - Multiple indicators multiple causes (MIMIC) models.
- The Handbook on Measuring the Non-Observed Economy (2002) cautions that these models may produce spectacularly high measures that attract attention but may not be exhaustive or reliable.
- MIMIC models have been widely used for cross-country estimates but face criticism over model specification, broad assumptions, and reliability of results (see Breusch 2005; Feige 2016).

### Big data and alternative data sources
- Big data is increasingly used to support GDP compilation, but new data sources have limited use for deriving separate estimates of the informal economy.
- One new data source is satellite means to identify nighttime lights.
  - Leon and Lima (2019) combine satellite data with traditional data sources (e.g., energy consumption, agricultural production, external trade) to estimate GDP levels and growth rates for Zimbabwe.
  - Like other macro-models, this approach assumes the difference between official estimates and model estimates is due to informal and illegal activity.

### Conclusion: imperatives and two groups of recommendations
- Compiling estimates of the informal economy is challenging, especially in developing economies with less advanced statistical capacity and stretched resources.
- Reliable estimates are imperative and should be considered part of core economic statistics compiled by statistical agencies.
- Recommendations are grouped into: (i) recommendations for the IMF and other international organizations that could provide support to national statistical agencies; and (ii) recommendations for national statistical agencies providing broad guidance on the compilation process.

International Organizations — key recommendations
- Promote a consistent methodological framework and clarify concepts and definitions relating to the informal economy; framework should be consistent across national accounts, external sector statistics, labor statistics and be acceptable to labor statisticians and macroeconomic statisticians.
- Integrate conceptual and methodological guidance into the next version of the international statistical standards.
- Identify country best practices in data collection and develop practical guidance taking account of technical and resource availability in countries with greatest need.
- Improve coordination among donor agencies that provide support for statistical activities and for measuring the informal economy to aim for adequate funding with regular frequency.
- Develop dedicated training and technical assistance focused on measuring the informal economy—along with improving annual and quarterly GDP estimates.
- Consider mechanisms to support national statistical agencies in collecting data from multinational corporations and digital platforms.

National Statistical Agencies — key recommendations
- Develop estimates of the informal economy as core aggregates—alongside GDP, GNI—for dissemination at regular frequency; quarterly frequency is preferable though resource intensive.
- Amend labor statistics collection programs to capture information on employment status, economic activity of employment, and full-time equivalents to aid derivation of labor output estimates.
- Compile supply and use tables at a regular frequency; considering cost implications, supply and use tables should be compiled with a minimum frequency of five years.
- Promote the use of administrative data, in particular from the tax authorities, to provide estimates of informality in the digital economy.

### Appendix I — IMF Committee on Balance of Payments Statistics: Task Force on Informal Economy (TFIE)
- At its 2017 meeting, the IMF’s Committee on Balance of Payments Statistics endorsed creation of a Task Force on the Informal Economy (TFIE) with a two-year mandate.
- Primary objective: take stock of country practices to identify data collection techniques and compilation methods relevant for covering the informal economy in external sector statistics.
- Findings on country practices:
  - Balance of payments compilation practices for informal economy activities center on the current account, especially on goods; followed by personal transfers and workers’ remittances in the secondary income account; and travel, transport, prostitution, gambling and smuggling of migrants’ services in the services account.
  - Economies use a combination of direct and indirect sources to estimate the size of IE activities; some have direct (data-specific) surveys or draw on micro studies or other surveys as inputs.
  - Indirect estimation methods are generally aligned to either national accounts compilation or to economic modelling.
  - Availability of separately identifiable data on informal economy activities remains limited.
  - Data sources, enterprise registration, and methodology are the major challenges reported by compilers.
- Phase I produced an inventory of experiences; Phase II launched a web platform disseminating metadata for 24 economies covering almost 57 compilation practices on the informal economy in the international accounts and/or national accounts.

Final TFIE recommendations to improve collection and compilation of informal economy data
- Continue dissemination of encouraged collection, compilation, and dissemination practices through the dedicated web platform to assist compilers.
- Tailor collection techniques and compilation methods to available data sources, statistical capacity, resources, and adequate assessment of costs/benefits for including specific informal economy activities; delineation of typologies (informal, underground, illegal) should be secondary to achieving as accurate totals as possible.
- Step up coordination between external sector statistics and national accounts compilers to move towards a more integrated approach; encourage exchange of experiences between national accounts and balance of payments compilers and between regulatory/policy agencies (such as Customs) and statistics-producing agencies to develop statistical models.
- Emphasize informal economy data issues specific to the financial account and the IIP and encourage national compilers to extend initiatives beyond the current account; where necessary use international databases in mirror statistics exercises—such as the BIS’ International Banking Statistics (particularly deposits)—to detect and address data gaps.
- Identify regional trends and corresponding regional approaches that take account of statistical capacity; estimation methods may be specific to the most important buckets of informal, underground and illegal activities in countries or regions (examples: drug trafficking or illegal mining in some Latin-American countries; arms trafficking and smuggling of migrants in some European countries; cross border informal trade and other illicit flows in some African countries).
- Where possible, establish adequate legal and institutional frameworks (including confidentiality), organizational structure, and coordination among compilation agencies to encourage collection and compilation of informal economy data; example: EU statistical regulations to compile some illegal economic activities.
- Reassess the concept of the informal economy with a view to greater harmonization to strengthen cross-country comparability.
- Use big data to complement traditional data sources for informal economy compilation where relevant (examples include drug trafficking and remittances).
- Strengthen technical assistance and training to assist economies in identifying data gaps and compiling data on relevant informal economy activities; this requires assessing areas where the informal economy is of statistical relevance.

*International Monetary Fund — Measuring the Informal Economy (selected excerpts from the source content provided)*

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_Source: https://www.imf.org/-/media/files/publications/pp/2021/english/ppea2021002.pdf_