OIT - Unpacking informality - A multidimensional policy decomposition

X Unpacking informality A multidimensional policy decomposition Authors / Juan Chacaltana, Mabelin Villarreal-Fuentes

April / 2026 ILO Working Paper 169© International Labour Organization 2026 Attribution 4.0 International (CC BY 4.0) This work is licensed under the Creative Commons Attribution 4.0 International. See: https:// creativecommons.org/licenses/by/4.0/. The user is allowed to reuse, share (copy and redistribute), adapt (remix, transform and build upon the original work) as detailed in the licence. The user must clearly credit the ILO as the source of the material and indicate if changes were made to the original content. Use of the emblem, name and logo of the ILO is not permitted in connection with translations, adaptations or other derivative works. Attribution – The user must indicate if changes were made and must cite the work as follows: Chacaltana, J., Villarreal-Fuentes, M. Unpacking informality: A multidimensional policy decomposition. ILO Working Paper 169. Geneva: International Labour Office, 2026.© ILO. Translations – In case of a translation of this work, the following disclaimer must be added along with the attribution: This is a translation of a copyrighted work of the International Labour Organization (ILO). This translation has not been prepared, reviewed or endorsed by the ILO and should not be considered an official ILO translation. The ILO disclaims all responsibility for its content and accuracy. Responsibility rests solely with the author(s) of the translation. Adaptations – In case of an adaptation of this work, the following disclaimer must be added along with the attribution: This is an adaptation of a copyrighted work of the International Labour Organization (ILO). This adaptation has not been prepared, reviewed or endorsed by the ILO and should

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Authorization for publication: Sangheon Lee, Director, Employment Policy Department, and, Rafael Diez de Medina, Director and Chief Statistician, Department of Statistics ILO Working Papers can be found at: www.ilo.org/research-and-publications/working-papers Suggested citation: Chacaltana, J., Villarreal-Fuentes, M. 2026. Unpacking informality: A multidimensional policy decomposition, ILO Working Paper 169 (Geneva, ILO). https://doi.org/10.54394/0003319301 ILO Working Paper 169

Abstract This paper proposes a policy-decomposable approach to analysing informality that preserves the standard binary indicator of informal employment. The additive decomposition highlights (i) the role of the composition effects by status in employment, and (ii) the role of the within status policy-relevant criteria, explaining both the level of informality and its changes over time. We illustrate the method using Colombia’s labour force survey for 2022–2024. Results show that informality is dominated by own-account work in unregistered/non-bookkeeping units, complemented by employees without pension contributions. A nested shift-share analysis indicates that the decline in informal employment over this period was driven mainly by reduced informality among own-account workers -reflecting a small composition effect away from own-account work and improved registration/bookkeeping within the group-, and secondarily by higher employee pension affiliation. The decomposition provides a practical monitoring tool for policy dialogue,

the decline in informal employment over this period was driven mainly by reduced informality among own-account workers -reflecting a small composition effect away from own-account work and improved registration/bookkeeping within the group-, and secondarily by higher employee pension affiliation. The decomposition provides a practical monitoring tool for policy dialogue, clarifying which policy levers are likely to matter most for further reductions in informality. About the authors Juan Chacaltana is a Senior Employment Specialist at the ILO in Geneva. He previously worked as Regional Economist with the ILO Regional Office for Latin America and the Caribbean and as Employment Specialist with the ILO Office for the Andean Countries. He also was the head of the ILO Formalization Programme for Latin America and the Caribbean as well as Head of the Interagency United Nations MDG Programme on Youth, Employment and Migration. He holds a PhD in Economics from the Catholic University of Peru and a Master of Science in Economics from Texas A&M University in the United States. Mabelin Villarreal-Fuentes is a Statistician at the ILO Department of Statistics in Geneva, with extensive experience in labour statistics and statistical standards. She previously worked in the Global Data Service of UNHCR, in the Statistical Methodology Unit at DANE, the National Statistical Office of Colombia, and with the Economics Department of the OECD. She holds a Bachelor’s degree in Statistics from the National University of Colombia and a Master’s degree in Quantitative Economics from the University of Paris 1 Panthéon-Sorbonne.02 ILO Working Paper 169 Abstract 01 About the authors 01 X Introduction 04 X 1 Related literature 05 X 2 Decomposing labour informality 07 X 3 An application: the case of Colombia 08 Data and definitions 08 Methodology 11 Unpacking policy drivers    11 Comparing 2022 and 2024. What drives the reduction?    13 X Conclusions 16 References 17 Acknowledgements 19 Table of contents03 ILO Working Paper 169 List of Tables

Methodology 11 Unpacking policy drivers    11 Comparing 2022 and 2024. What drives the reduction?    13 X Conclusions 16 References 17 Acknowledgements 19 Table of contents03 ILO Working Paper 169 List of Tables Table 1. Colombia. Overview of descriptive statistics. 2022-2024 10 Table 2. Colombia. Decomposition of informal employment by employment status. 12 Table 3. Colombia. Shift share analysis by employment status. 13 Table 4. Colombia. Decomposition of the within status effect into policy drivers. 1404 ILO Working Paper 169 X Introduction Nearly 60% of the total employed population worldwide is in informal employment (ILO, 2018; ILO, 2023). Although there is increasing availability of statistics and studies about this phenomenon, policy making is not advancing at the same pace. Part of the problem is related to the fact that, as informality is a multifaceted reality, the same terminology has often been used to mean different things, and historical variation in concepts and operational criteria complicated both measurement and policy design. In terms of measurement, traditionally informality has been analysed through a binary lens, formal versus informal, which often oversimplifies a spectrum of realities. This aggregation is useful for tracking the extent of informality over time and across countries, but on its own it says little about why jobs are informal, the diversity of conditions within the informal (and formal) economy, and which policy levers matter. This paper proposes a policy-decomposable procedure that keeps the ILO-consistent binary indicator of informal employment and unpacks it into additive components aligned with concrete policy variables usually included in the definition (for example, pension affiliation, paid leave, registration/bookkeeping, tax compliance etc). The ILO methodology is based on information on employment status and use specific criteria in each case, using variables that are related to specific policy dimensions. By recovering the original variables – or unpacking informality - we

policy variables usually included in the definition (for example, pension affiliation, paid leave, registration/bookkeeping, tax compliance etc). The ILO methodology is based on information on employment status and use specific criteria in each case, using variables that are related to specific policy dimensions. By recovering the original variables – or unpacking informality - we move from a single headcount rate into a small set of policy related drivers, which allows more targeted, monitorable policy dialogue We illustrate the approach using Colombia’s GEIH microdata for 2022–2024 and show that the modest decline in informality over this period was driven primarily by a reduction in own-account workers operating in unregistered/non-bookkeeping units, with a secondary contribution from improved employee pension affiliation.05 ILO Working Paper 169 X 1 Related literature

The original conceptualization of informality, notably developed through the International Labour Organization (ILO)’s World Employment Programme (WEP) in the early 1970s, treated informality as a broad, complex, and heterogeneous phenomenon. The seminal Kenya Report (1972) recognized the informal sector not as a residual category but as a dynamic, productive, and employment-generating component of the economy. Crucially, these early analyses viewed informality involving diverse characteristics: enterprise and labour registration, production methods, labour relations, and integration with formal markets. Despite these multidimensional insights, the empirical toolkit of the time was limited, and most analyses remained qualitative and descriptive, lacking the statistical machinery to measure such complexity systematically. By the 1990s, the need for international statistical standardization led to more formalized but simplified approaches to defining and measuring informality. The 15th ICLS (1993) defined the informal sector based on the characteristics of production units (i.e., enterprises), primarily household unincorporated enterprises, and also considered criteria such as legal organization/ownership, type of accounts, registration and, in many instances, size thresholds. The 17th ICLS (2003) recognized that the 15th ICLS definition did not fully capture the extent of informal employment

hold unincorporated enterprises, and also considered criteria such as legal organization/ownership, type of accounts, registration and, in many instances, size thresholds. The 17th ICLS (2003) recognized that the 15th ICLS definition did not fully capture the extent of informal employment and therefore complemented it with a broader job-based concept of informal employment that spans formal sector enterprises, informal sector enterprises and households. In this framework, employees are considered to have informal jobs when their employment relationship is, in law or in practice, not subject to national labour legislation, income taxation, social protection or entitlement to certain employment benefits (e.g., advance notice of dismissal, severance pay, paid annual or sick leave)1. More recently, the 21st ICLS (2023) adopted statistical standards on the informal economy, defining it around the underlying concept of informal productive activitiesthat is, productive activities of persons or economic units that, in law or in practice, are not covered by formal arrangements, including forms of work other than employment (e.g., unpaid traineeships, volunteer work, etc). Related to employment, this includes the informal market economy. Importantly, the resolution operationalizes this conceptual core by specifying precise criteria and their combinations to classify economic units, work relationships, and productive activities, and it also emphasizes “the degree of exposure to economic and personal risk due to a lack of effective coverage by formal arrangements”2. While these standards enabled cross-country comparisons and provided statistical clarity, they often encouraged a binary reporting logic: an enterprise or job was either formal or informal. Even when multiple indicators were collected, - such as access to social protection, business registration, paid annual leave or sick leave, etc - results were typically collapsed into a single 1 In addition to the employee-based criterion, informal employment also includes own-account workers and employers without employees in the informal sector, as well as contributing family workers in the informal sector or without social protection in case is relevant in the country. It also covers members of producers’ cooperatives that are themselves informal and own-account workers

1 In addition to the employee-based criterion, informal employment also includes own-account workers and employers without employees in the informal sector, as well as contributing family workers in the informal sector or without social protection in case is relevant in the country. It also covers members of producers’ cooperatives that are themselves informal and own-account workers producing goods exclusively for their household’s own final use (where such work is counted as employment). 2 For more information see ILO (2023) for the full text of the Resolution on statistics on the informal economy.06 ILO Working Paper 169 categorical outcome. At the same time, the 21st ICLS indicator framework (2023) explicitly promotes complementary indicators that retain the dichotomy but add nuance, for example by reporting the share of employees with a formal main job who have effective access to paid leave benefits, as well as the share of employees with an informal main job who nonetheless have access to some employment benefits. Now a days, there is increasing consensus that measuring informality through a formal/informal dichotomy fails to capture its multidimensional, heterogeneous, and policy related implications3. The ILO acknowledged this consensus in 2023, when the 21st ICLS (2023) Resolution, broadened the scope of informality statistics to reflect its multidimensional nature and calls for the production of indicators set out in the resolution and its supporting indicator framework, relevant to countries’ policy needs and data systems. These indicators describe degrees of vulnerability, access to protections, and the diversity of informal conditions among workers and economic units, across six dimensions (extent, composition, exposure, working conditions and productivity, contextual vulnerability, and other structural factors). In practice, there are some interesting emerging approaches. Hamaguchi et al. (2025) propose a Composite Informality Index (CII) based on Multiple Correspondence Analysis, incorporating firm-level traits such as tax registration, business licensing, and bookkeeping practices. Shahid et al. (2020) develop a five-point index to position firms along a continuum from fully informal

a Composite Informality Index (CII) based on Multiple Correspondence Analysis, incorporating firm-level traits such as tax registration, business licensing, and bookkeeping practices. Shahid et al. (2020) develop a five-point index to position firms along a continuum from fully informal to fully formal, while Thoto et al. (2021) adopt a multidimensional perspective to capture overlapping degrees of legality. At the household level, Egger et al. (2024) introduce a measure of the depth of informality, defined as the proportion of income or hours worked without social insurance, highlighting household-level income diversification as a key welfare strategy. At the institutional level, the Colombia’s statistical agency (DANE, 2023) developed the Multidimensional Index of Business Informality (IMIE) that applies dual cut-offs to identify firms with deprivations across dimensions such as entry, production, inputs, and taxation. By assigning weights to each dimension, the IMIE enables a granular understanding of where informality is most concentrated, improving the targeting of formalization policies. These emerging approaches aim to developing multidimensional policies or strategies to reduce informality and improve livelihoods. [Normal for body text] 3 There is a growing body of literature challenging the binary framing. Some argue that many economic units engage simultaneously with formal and informal institutions - registering with some authorities but not others (Gallien & van den Boogaard, 2021; Díaz et al., 2018). Other (Amaral and Quintin (2006) and Hamaguchi et al. (2025)) highlight that informality operates along a continuum, often involving partial compliance with formal rules. Others emphasise that formalization is often gradual, selective, and reversible. Firms may adopt some formal practices while remaining informal in others and may revert to informality if the costs outweigh the benefits (Díaz et al., 2018). The 21st ICLS Resolution also acknowledge that while the binary framing is essential there is a need to also move beyond it (ILO 2023).07 ILO Working Paper 169 X 2 Decomposing labour informality

benefits (Díaz et al., 2018). The 21st ICLS Resolution also acknowledge that while the binary framing is essential there is a need to also move beyond it (ILO 2023).07 ILO Working Paper 169 X 2 Decomposing labour informality

We propose an additive decomposition of the most common indicator of informality: the share of workers with informal jobs to total employment as defined in the ILO’s international guidelines. It is worth emphasizing that our goal is not to create a new measure or indicator of labour informality, but to decompose the most frequently used indicator into its additive components. The ILO (2023) defines formal employment as “any activity of persons to produce goods or provide services for pay or profit in relation to a formal job, where the activities are effectively covered by formal arrangements”. This definition can be implemented across different categories of workers as per the 20th ICLS (2018) classification of work relationships4 - namely independent workers, dependent contractors, employees, and contributing family workers - and by combining legal criteria with observable operational indicators that encompass a set of protections or obligations –relevant for each country - as signals of formality. In practice, the process of measurement can be understood in two steps. First, the sector is classified by the intention of production and the formal status of the economic unit: units with formal recognition (e.g., registration, bookkeeping) are in the formal sector, while the informal sector consists of market-producing economic units that lack such recognition. Second, informal employment is determined at the job level, with operational criteria varying by status in employment: for independent workers (employers, own-account workers), job formality follows the formal status of their unit (i.e., they hold a formal job if they operate in a formal economic unit, and an informal job if they own or operate an informal economic unit); for employees, additional job-level criteria are checked, typically employer contributions to statutory social insurance and, where needed, access to paid annual leave and paid sick leave, to determine whether the job is formal or informal.

and an informal job if they own or operate an informal economic unit); for employees, additional job-level criteria are checked, typically employer contributions to statutory social insurance and, where needed, access to paid annual leave and paid sick leave, to determine whether the job is formal or informal. Using this approach, an indicator of informal employment is then created by collapsing all these diverse indicators into a single binary variable. This allows the construction of a headcount index at the national level: the share of informal employment as a percentage of the total workforce. This indicator has become increasingly relevant to describe a country’s capacity to create not only jobs, but also quality jobs, in the sense that they comply certain conditions of work captured by these variables. However, useful as it is, this indicator does not by itself reveal which policies are needed to reduce informality, even though many indicators related to policy dimensions were used in its construction5. Therefore, the challenge is how to perform a multidimensional decomposition that retrieves the fundamental variables used to build the informality dichotomy, in a way that is consistent with current standards on informality measurement . 4 Although ICSE-18 is the latest international standard, some countries still operationalize status in employment using ICSE-93 categories. 5 Recent ILO (2023) recommendations on measuring informality encourage moving beyond the formal/informal dichotomy and recovering multidimensional information that is useful for policy purposes.08 ILO Working Paper 169 X 3 An application: the case of Colombia

In this section we implement the proposed decomposition using data from Colombia. According to DANE, in Colombia the share of informal employment fell from 59.7% in the period June to August 2021 to 57.9% in 2022 and 55.2% in 2025. Therefore, we can use this reduction to first decompose the aggregate informality rates into its policy components and then use that information to assess what drove the reduction of informality in this period. X Figure 1. Colombia: % of informal employment 2021-2025

decompose the aggregate informality rates into its policy components and then use that information to assess what drove the reduction of informality in this period. X Figure 1. Colombia: % of informal employment 2021-2025

Source: DANE (Departamento Administrativo Nacional de Estadística). Extracted 23 October 2025

Note: Data refer to the June-August quarter of each year and use population projections based on the 2018 Census. Information prior to 2021 is not comparable, and thus not included in this graph, because (i) population projections relied on the 2005 Census;

(ii) a different operational definition of informality was used; and (iii) earlier published figures covered either 13 or 21 main cities, not the national total. Data and definitions The construction of the indicator on informal employment in Colombia used in this document, follows the latest statistical standards introduced above and depends on the status in employment of the worker6. For all employees (EES), including those in the public sector, private sector and domestic work, the primary criterion is contributions to a pension fund (used as an operational measure of contributions to statutory social insurance)7. If the worker reports pension contributions made by the employer on their behalf, the job is formal; if the worker reports no 6 This follows detailed information on how to compute each variable provided in the document: “Variable derivation Guide for ILO Model LFS questionnaire for CAPI. Job-type start (2024 Edition)”, available at: https://webapps.ilo.org/ilostat-files/LFS/LFSq_Rel1_Variable_ Derivation_Guide.pdf 7 The 21st ICLS (para. 78) recommends using the employer’s contribution to a statutory social-insurance scheme, typically a pension fund, to operationally identify formal jobs for employees.09 ILO Working Paper 169 employer contribution to a pension fund, it is informal. When the pension contribution response is recorded as “other / not asked / don’t know / NA”, we apply additional characteristics: the job is considered formal only if the worker reports having access to both paid annual leave and paid

employer contribution to a pension fund, it is informal. When the pension contribution response is recorded as “other / not asked / don’t know / NA”, we apply additional characteristics: the job is considered formal only if the worker reports having access to both paid annual leave and paid sick leave; otherwise, it is informal. In sum, for employees, social-insurance coverage is decisive and, when unknown or unavailable, jointly observed paid-leave entitlements establish formality. For contributing family workers (CFW), the decisive criterion is effective coverage by formal arrangements, where such arrangements exist in the country. A CFW working in a production unit classified in the formal sector (i.e., units with formal registration with a governmentally established system of registration8 or keeping a complete set of accounts for tax purposes9), the primary evidence is contribution to a pension fund. If such contributions are reported, the job is formal: if not, informal. Paid annual-leave or sick-leave entitlements are not utilised for this status. However, in Colombia, pension contributions targeting CFWs are not yet in place and thus not reported. For CFW working in economic units classified as in the informal sector, the job is informal. For employers (EPY) the classification relies on the classification of the unit of production. If the unit is registered or keeps accounts for tax purposes, the job is formal; if neither is present, it is informal. Personal entitlements (pension or leave(s)) are not utilised for this status either. The classification for own-account workers (OAW) depends on the intended destination of production, in particular whether it is mainly for own-final use or mainly for the market. If the intended destination is reported mainly for own-final use, the unit of production is placed in the household sector (i.e., outside employment for pay or profit) and the work relationship is considered informal. If production is mainly for the market, formality is determined by the status of the unit of production: units reporting registration or bookkeeping for tax purposes are formal, and thus the own-account worker is in formal employment; own-account workers in units classified as in

informal. If production is mainly for the market, formality is determined by the status of the unit of production: units reporting registration or bookkeeping for tax purposes are formal, and thus the own-account worker is in formal employment; own-account workers in units classified as in the informal sector or in household production are in informal employment.10 Due to the status and the sequence in which they are applied, these rules are mutually exclusive and exhaustive, which facilitates the decomposition by original variables used in the definition in an additive way. For the calculations, we use the Gran Encuesta Integrada de Hogares (GEIH), the country’s labour force survey implemented by the National Administrative Department of Statistics (DANE), since

2006. The GEIH surveys roughly 240,000 households annually and provides nationally representative information on labour market structure, income, and employment quality. Its design is probabilistic, stratified, and based on multi-stage cluster sampling, ensuring statistical robustness and comparability over time. The survey’s modules on informality build on earlier “1-2-3 Survey” methodologies and were deliberately preserved in the transition to GEIH to maintain consistency with international standards and ILO recommendations.

Before presenting the decomposition, Table 1 provides an overview of descriptive statistics that highlight the high prevalence and heterogeneous nature of informality in Colombia. The data reveal that between 55 and 57 percent of employment is classified as informal, while between 48 and 50 percent11 of employment is in informal or household production units. 8 Hereafter referred to as registration. 9 Hereafter referred to as bookkeeping. 10 In Colombia, the survey instrument does not allow distinguishing whether production is mainly for own-final use or mainly for the market. Therefore, for own-account workers, the operationalization continues to follow the 13th ICLS approach; as a result, some own-account workers may still be observed houesholds. 11 Note that here we are using annual data. For that reason, these figures are not the same as in figure 1 (quarterly data).10 ILO Working Paper 169 Employees12 represent about 50% of total employment, and among them, nearly 70% report

own-account workers may still be observed houesholds. 11 Note that here we are using annual data. For that reason,