## 1. Informality

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---

### I. Introduction and framing
- Informality: economic activity that is neither taxed nor monitored by the government.
- Prevalent in emerging market and developing countries where burdensome regulations and taxes coexist with poor public services and weak enforcement.
- Viewed as resulting from inefficient public policies and failure of political institutions to protect and promote efficient and equitable markets.
- Survey emphasizes need for dynamic general equilibrium (DGE) and ultimately dynamic stochastic general equilibrium (DSGE) models to fully understand costs, benefits, and policy implications of informality.

### Definitions and scope
- Disagreement over definitions:
  - Firm-focused (ILO (1972)) versus worker-focused (ILO (2002)).
  - Country-specific labels (e.g., in India the informal sector = unorganized sector).
  - In advanced economies, often refers to the ‘hidden’ economy (tax evasion).
- Informality must be defined relative to both product and factor markets.
- Term is multifaceted; measurement problems stem from lack of unified definition.

### Costs and benefits of informality (evidence summary)
- Arguments that informality is harmful:
  - Leads to inferior working conditions, social vulnerabilities, low productivity, unfair competition, disrespect for the rule of law, erosion of institutional legitimacy and integrity, corruption, and low fiscal revenues.
  - Low fiscal revenues limit improvements to public services and enforcement, perpetuating informality.
  - Negative correlation with economic growth via compressed productivity and restricted access to public services (see chapter VI.B).
  - Hinders enforcement of environmental, workers’ welfare and consumer protection, limiting global market integration.
- Arguments that informality can be beneficial:
  - Informal credit markets associated with positive growth rates (see chapter VI.B).
  - With product, credit and/or labour market imperfections, informality can increase efficiency and positively affect the formal economy.
- Literature assesses both costs and benefits to reach balanced conclusions (see Batini et al. (2009) and related chapters).

### Measured size and prevalence
- Accurate recent data available for a number of emerging market and developing economies (reported in chapter II.B).
- Examples (Bolivia, India, Nigeria, Panama, Pakistan, Paraguay, Peru):
  - Informality estimated to characterize over three quarters of the labour force.
  - Informality accounts for little less than a half of total sales.
  - Implies a shadow economy as large as 60 to 70 percent of GDP.

### Research agenda and policy relevance
- Literature objectives:
  - Quantify extent of informality across countries.
  - Explain causes and nature of the informal sector using empirical regularities and economic models for policy analysis.
- Crucial research tasks:
  - Understand drivers of informal behavior and responses to combinations of public policies (fiscal, financial, social protection, labour market, enforcement).
  - Study informal labour and credit markets to comprehend monetary policy transmission mechanisms and effective monetary policy design.

### Structure of the survey (organization of subsequent chapters)
- Chapter II: empirical evidence on informality.
- Chapter III: early models of informal labour markets.
- Chapter IV: three margins of informality and standard search-matching model:
  - Intersectoral margin for workers (wage dualism).
  - Intersectoral margin for firms.
  - Intrafirm margin and occupational choice.
- Chapter V: informality in the credit sector.
- Chapter VI: move to a dynamic general equilibrium approach.
- Chapter VII: summary and open questions.

### Key empirical questions motivating the literature
- How do we measure the informal economy?
- How large is the informal economy in the world?
- What are the main drivers of informal behavior?

### A. How Do We Measure the Informal Economy?
- Two principal approaches:
  - Hidden income approach (examples: Schneider (2005), Chaudari et al. (2006)): measures unregistered activities contributing to official GNP; scope can include illegal activities and informal household economy or be restricted to typically taxable legal activities; motivations include tax evasion and avoidance of social security contributions and labour market regulations.
  - Informal employment approach: measures size via informal sector and informal workers in the formal sector (example: NCEUS definition for India: incorporated private enterprises owned by individuals/households with less than 10 workers; unorganized workers include workers in unorganized sector, households excluding regular workers with social security benefits, plus workers in formal sector without social security benefit).
- Estimation methods:
  - Direct methods: surveys, tax-auditing — drawbacks: incomplete information, biased samples, cross-sectional limitations.
  - Indirect methods (summary from Schneider (2005)):
    - Currency demand approach: assumes cash demand rises with hidden transactions (controlling for other causes).
    - DYMIMIC (dynamic-multiple indicators multiple-causes): treats hidden economy as unobserved variable influenced by causes (tax/regulation burden, tax morality, labour force participation changes), estimated via structural equations (maximum likelihood); produces time-series ordinal index converted to cardinal via scaling to other indirect methods (e.g., currency-demand). Criticism: weak theoretical link between causes/indicators and informality as sole unobserved variable.
  - Model-based calibration: Solomon (2008) uses an RBC model to choose causes/indicators for estimation.

### B. The Size of the Informal Economy
- Measurement heterogeneity limits international comparisons; indirect methods often used.
- Informality expressed in income terms or employment terms.
- Key empirical figures:
  - Chen (2007): informal employment is about one-half to three-quarters of non-agricultural employment in developing countries.
  - Schneider (2005): DYMIMIC + currency-demand for 110 countries; reports notable increases in informal sector in African and other developing countries, with upward trends in transitional and developed economies.
- Cross-study notes:
  - Inclusion of agriculture and additional Asian countries likely increases estimated informality.
  - Official statistics and unofficial measurements may conflict (e.g., Schneider (2005) vs. national surveys; see Perry et al. (2007), Box 1.3).

### C. Causes and Impact of Informality
- Evidence and theoretical predictions:
  - Loayza (1996): in Latin America during 1990s, countries with large tax burdens and weak enforcement show negative relationship between informal sector size and economic growth; very restrictive labour regulations and poor enforcement associated with largest informal sectors (examples: Bolivia, Panama, Peru); also finds a negative relationship between informal sector size and real GDP growth.
  - Alternative hypothesis: informality may increase efficiency under market imperfections, yielding positive growth impact (e.g., Nikopour et al. (2008) review for 21 OECD countries finds positive impact).
  - Rei and Battacharya (2008): using Schneider (2005) data for low and middle-income countries, find no general evidence that higher taxation and labour market regulation increase informality; results sensitive to inclusion of public and corporate governance indices; main finding: stronger governance favors formality.

### D. Main Stylized Facts (SF) — Informal Employment
- SF 1: Developing countries tend to have a higher degree of informality than OECD countries.
- SF 2: Many countries reveal an increasing trend of informality.
- SF 3: Informalization of the formal sector — increase in informal jobs (without job/social security) within the formal/organized sector (observed in India, Argentina, other Latin American countries).
- SF 4: Job finding rate of formal jobs is highly procyclical (volatility puzzle); job finding rate of informal jobs is more stable.
- SF 5: Job separation rate in informal jobs is more responsive to negative shocks even though separation rates for formal and informal jobs are both countercyclical.
- SF 6: During a recession, despite large increase in job separation rate for informal jobs, the share of formal jobs decreases.
- SF 7: Negative correlation between informal sector employment and education within countries and between informal employment and average education attainment across countries.
- SF 8: Positive correlation between unemployment and shadow employment (cross-country/regional evidence for Brazil and Italy).
- SF 9: Example (Martin (2000), Mexico, 1990s): unemployment rate in the 1990’s was low (3.7 percent) and composed mainly by well-educated.
- SF 10: In Egypt, 70 percent of workers obtain a formal job through formal methods.
- SF 11: Negative and convex relationship between informal employment and country’s standard of living.
- SF 12: Positive relationship between informal employment and tax rate.
- SF 13: Significant earnings gap within informal economy: employers at top segment, then regular salaried employees, then casual workers.
- SF 14: Men over-represented in top segment; women over-represented in bottom segment; intermediate segment gender shares vary across sectors/countries.
- Empirical interpretations:
  - Informal sector heterogeneous: self-employed and salaried workers co-exist; in many cases informal sector is voluntary for some (Maloney 1999, 2004), but segmentation and constrained choices occur, especially in recessions.
  - Bosch and Maloney (2006, 2007): hiring behavior of formal firms is primary driver of formal employment share; flows from informal to formal are highly procyclical; flows from formal to informal are procyclical but less volatile.
  - Wage premium for formal workers: evidence ambiguous and depends on job category (self-employed often better paid than salaried informal); in India informal regular workers paid considerably less than formal counterparts.

### Informal Credit Markets — Stylized Facts and Evidence
- Historical and aggregate patterns:
  - Informal credit strong in many developing countries (India, Pakistan, Indonesia, Brazil, many African countries) and some emerging markets (China).
  - Bell (1990): in India, over 80 percent of rural households’ debt was owed to informal credit agencies in 1951 (excluding relatives/friends at ~11 percent); by 1981 the share to informal agencies was 24 percent; share owed to formal credit institutions rose from 7 percent in 1951 to 61 percent in 1981; implied informal credit market share about 39 percent in that period. AIDIS (2003) indicates moneylenders share over 9 percent and non-institutional share over 36 percent for India.
- SF 15: Economies with less developed credit markets tend to have more segmented credit markets and greater informal credit markets.
- SF 16: Both formal and informal lenders in less developed credit markets have extensive market power.
- SF 17: Informal credit is more important the more concentrated formal credit markets are.
- SF 18: Distributional pattern — formal loans to rural households favor wealthy borrowers/large farms; majority of informal loans distributed to poor borrowers/small farms.
- SF 19: High proportion of borrowers obtain credit from both formal and informal markets simultaneously.
- SF 20: Informal moneylenders obtain formal credit to fund informal credit services.
- SF 21: Informal interest rates on average much higher than formal rates.
- SF 22: Interest rates charged by informal moneylenders may range from 0 to 200 percent per year in India, Pakistan, and Thailand.
- Additional observations:
  - Informal interest rates may exceed 75 percent per year (Besley (1994), Hoff and Stiglitz (1990)).
  - Informal credit markets coexist with formal markets via horizontal (competition/displacement) and vertical (informal lenders borrowing from formal banks) linkages.

### III–V. Modeling Approaches — Labour and Credit Markets
- Early models:
  - Harris-Todaro tradition: geographically segmented labour markets with wage duality; formal-sector wages can be higher-than-market-clearing wages (Todaro (1969), Harris and Todaro (1970)).
  - Efficiency wage and information-based models: duality via adverse selection/moral hazard.
  - Voluntary/cost-benefit models: agents weigh costs of formal registration versus benefits of informality (Lucas (1978), Rauch (1991)).
- Search-matching framework (Mortensen-Pissarides) extensions:
  - Intersectoral margins for workers and firms:
    - Boeri and Garibaldi (2005): deterministic search-matching with heterogeneous workers; informal employment associated with more turnover, discouraging high-skill workers; multiple equilibria possible depending on relative profitability of regular vs. irregular sectors.
    - Badaoui et al. (2006): Burdett-Mortensen framework where large firms pay higher wages and concentrate in formal sector; small firms choose informal sector; differential tax-inspection probabilities matter.
  - Intersectoral margin for workers:
    - Albrecht et al. (2008): workers with high productivity accept only formal offers; relative productivity crucial; endogenous job destruction.
    - Zenou (2008): homogeneous workers more productive in formal sector; informal sector competitive and frictionless in limit; informal sector provides frictionless outside option.
    - Satchi and Temple (2009): urban formal/informal and agricultural sectors; informal sector as marginal self-employment with low entry costs; endogenous capital in formal sector; does not distinguish unemployed from informal workers.
  - Intrafirm margin and occupational choice:
    - Bosch (2006, 2007): within-firm decision to employ informal labour explains coexistence of formal and informal contracts in same firm; ex-post match heterogeneity implies only high productivity matches yield formal contracts; stricter labour regulations can expand informality via intrafirm decisions and informal self-employment.

- Informal credit market models:
  - Three main strands: adverse selection, moral hazard, imperfect enforcement; search-externalities also used.
  - Horizontal linkages: formal banks can displace informal lenders (Bell (1990)); formal credit rationing can foster informal sector (Kochar (1997)).
  - Vertical linkages: informal lenders may access formal funds; subsidized formal credit can perversely raise informal interest rates via entry, enforcement externalities, and weakened reputation effects (Hoff and Stiglitz (1997), Floro and Ray (1997), Bose (1998), Madestam (2009)).
  - Madestam (2009): heterogeneous informal lenders (rich vs. poor) generate:
    - Investment effect: additional informal finance increases investment of bank-rationed borrowers by channeling bank funds to informal lending.
    - Disciplinary effect: informal finance can increase borrowers’ returns and incentives to repay, raising bank lending.
    - Rent-extraction effect: banks use informal intermediaries to avoid agency costs, possibly making borrowers worse off; stronger banking market power increases rent-extraction and prevalence of informal credit.
  - Search/trading frictions approach: Wasmer and Weil (2004) model credit and labour market frictions symmetrically; credit market frictions reduce entrepreneurs and lenders via a “credit gap” (excess return on business loans), amplifying shocks.

### VI. General Equilibrium Models of Informality
- CGE/AGE models: static, data-driven analyses including informality in product or factor markets (Sinha (2005), Sinha and Adam (2000), Gibson and Kelley (1994), Portes et al. (1989)).
- Dynamic GE models with wage flexibility:
  - Agenor and Montiel (1996); Marjit and Kar (2008): capital mobility across formal and informal sectors; wage rate crucial welfare measure.
  - Ihrig and Moe (2004): dynamic GE with formal sector (labour+capital) and informal sector (labour only); agents choose consumption/savings and time allocation; capital accumulation shifts labour to formal sector.
  - Conesa et al. (2002): first DSGE with an “underground” sector; features wage premium, labour indivisibilities, households choose probability of working in informal sector; prediction: wage premium differentials affect amplification of technological shocks.
- Endogenous growth models:
  - Loayza (1997): AK-type model with congestible public services; larger informal sector reduces capital productivity and growth, especially with high taxes and weak enforcement.
  - Sarte (1997): rent-seeking bureaucracy forces marginal firms into informality, lowering growth.
  - Dasgupta (2005): informal financial markets can raise growth by separating high/low risk firms and reducing cost of credit rationing; informal markets can complement growth under certain regimes.
- New Keynesian DSGE with informality:
  - Castillo and Montoro (2008): dual labour market with formal/informal contracts; informality arises from lower hiring costs; informal workers act as buffer stock allowing output expansion without wage pressure, linking informality to inflation dynamics and monetary transmission.
  - Batini et al. (2009): model “unobservable” labour market and wage norm; conclude benefits from reducing informality (tax smoothing, stabilization gains) outweigh costs of reduced wage flexibility.

### VII. Conclusions and Open Questions
- Evolution of literature:
  - Shift from firm-characteristic view to employment-relationship view of informality (Chen (2007)).
  - Extensive but often contrasting empirical and theoretical findings; measurement and definitional issues persist.
- Synthesis:
  - Two main theoretical strands: informality in credit markets vs. informality in labour markets; both address many stylized facts (employment SF3–SF8; credit SF15, SF18–SF22) but several stylized facts require further development (employment SF1, SF2, SF13, SF14; credit SF16, SF17).
- Policy and research questions highlighted:
  - How effective are government policies in economies with large, unobservable labour/credit markets?
  - What are links between informality and endogenous growth?
  - Can informality be beneficial in some respects?
  - What is the link between informality and gender inequality?
- Methodological recommendation:
  - Move beyond partial-equilibrium models to dynamic general equilibrium approaches that capture multi-dimensional informality (product, labour, credit markets) and explicit intertemporal household/producer choices.

*Source: _wp1042 - 1. Informality and related chapters excerpt from the supplied PDF.*

### 1. Informality .........................................................................................................

### 1. Informality

### I. Introduction and framing
- Informality is usually regarded as an economic activity that is neither taxed nor monitored by the government.
- It is common in emerging markets and developing countries where burdensome regulations and taxes coexist with poor public services and government’s weak enforcement capabilities.
- From this perspective, informality often results from inefficient public policies and reflects the failure of political institutions to protect and promote an efficient and equitable market economy.
- The survey emphasizes the need for dynamic general equilibrium (DGE) and ultimately dynamic stochastic general equilibrium (DSGE) models for a full understanding of the costs, benefits and policy implications of informality.

### Definitions and scope
- There is disagreement over the definition of informality:
  - Focus can be on the firm (ILO (1972)) or the worker (ILO (2002)).
  - In some countries (e.g., India) the informal sector is identified with the unorganized sector.
  - In advanced economies the term usually refers to the ‘hidden’ economy implying some kind of tax evasion.
  - Informality needs to be defined with respect to both product and factor markets.
- The term is changing and multifaceted; measurement problems arise from the lack of a unified definition.

### Costs and benefits of informality (evidence summary)
- Arguments that informality is harmful:
  - Leads to inferior working conditions, social vulnerabilities, low productivity, unfair competition, disrespect for the rule of law, erosion of the legitimacy and integrity of public institutions, corruption, and low fiscal revenues.
  - Low fiscal revenues prevent improving public services and strengthening enforcement institutions, perpetuating informality.
  - Informality has been found to be negatively correlated with economic growth by compressing productivity and restricting access of informal firms and workers to necessary public services (see chapter VI.B).
  - Inability to enforce environmental, workers’ welfare and consumers’ protection hinders integration of many developing countries into the global market.
- Arguments that informality can be beneficial:
  - Evidence reveals that informal credit markets are associated with positive growth rates (see chapter VI.B).
  - In the presence of imperfections in the product, credit and/or labour markets, informality can increase efficiency and have a positive impact on the formal economy.
- The literature assesses both costs and benefits to arrive at balanced conclusions (see Batini et al. (2009) and related chapters).

### Measured size and prevalence
- Recent accurate data on the size of the informal sector are available for a number of emerging market and developing economies (reported in chapter II.B of this survey).
- In some countries (Bolivia, India, Nigeria, Panama, Pakistan, Paraguay, Peru):
  - Informality has been estimated to characterize over three quarters of the labour force.
  - Informality accounts for little less than a half of total sales.
  - Implying a shadow economy as large as 60 to 70 percent of GDP.
  - (See Perry et al. (2007) for more details.)

### Research agenda and policy relevance
- Recognition of informal behavior’s impact has spurred literature that:
  - Quantifies the extent of informality in various countries.
  - Seeks to explain causes and nature of the informal sector via empirical regularities and economic models for policy analysis.
- Understanding drivers of informal behavior and how the informal sector reacts to combinations of public policies—including fiscal, financial, social protection, labour market and enforcement policies—is crucial to design measures to reduce informality.
- Knowledge of informal labour and credit markets is important to understand monetary policy transmission mechanisms and to conduct effective monetary policy.

### Structure of the survey (organization of subsequent chapters)
- Chapter II surveys the empirical evidence on informality.
- Chapter III describes early models of informal labour markets.
- Chapter IV introduces the three margins of informality and the standard search-matching model:
  - Intersectoral margin for workers and wage dualism concerns.
  - Intersectoral margin for firms.
  - Intrafirm margin and occupational choice.
- Chapter V discusses informality in the credit sector.
- Chapter VI describes the move to a dynamic general equilibrium approach to informality.
- Chapter VII concludes with a summary of a number of open questions.

### Key empirical questions motivating the literature
- How do we measure the informal economy?
- How large is the informal economy in the world?
- What are the main drivers of informal behavior?

*Source: _wp1042 - 1. Informality.........................................................................................................*

### 4. What impact does informality have on the formal economy? Below we summarize key

### _wp1042 - 4. What impact does informality have on the formal economy? Below we summarize key

### A. How Do We Measure the Informal Economy?
- Two principal measurement approaches:
  - Hidden income approach: measures unregistered economic activities contributing to officially calculated GNP (examples: Schneider (2005), Chaudari et al. (2006)). Scope can be broader (including illegal activities and informal household economy) or stricter (legal activities typically taxable). Motivations for nonreporting include tax evasion and avoidance of social security contributions and labour market regulations.
  - Informal employment approach: measures size via informal sector and informal workers in the formal sector (example: NCEUS definition for India: incorporated private enterprises owned by individuals/households with less than 10 workers; unorganized workers include workers in unorganized sector, households excluding regular workers with social security benefits, plus workers in formal sector without social security benefit).
- Estimation methods:
  - Direct methods: surveys, tax-auditing — drawbacks include incomplete information, biased samples, and cross-sectional (one point in time) limitations.
  - Indirect methods: multiple techniques summarized in Schneider (2005). Notable methods:
    - Currency demand approach: assumes cash demand rises with hidden transactions (controlling for other causes).
    - DYMIMIC (dynamic-multiple indicators multiple-causes): treats hidden economy as an unobserved variable influenced by causes (tax/regulation burden, tax morality, labour force participation changes) and estimated via structural equations (maximum likelihood). Produces time-series ordinal index converted to cardinal series by scaling to other indirect methods (e.g., currency-demand). Criticism: weak theoretical link between causes/indicators and informality as the sole unobserved variable.
  - Model-based calibration: Solomon (2008) uses an RBC model to choose causes/indicators for estimation.

### B. The Size of the Informal Economy
- Measurement heterogeneity limits international comparisons; indirect methods often used.
- Informality can be expressed in income terms or employment terms.
- Key empirical figures and results:
  - Chen (2007): informal employment is about one-half to three-quarters of non-agricultural employment in developing countries.
  - Schneider (2005): uses DYMIMIC + currency-demand for 110 countries; reports notable increases in informal sector in African and other developing countries, with upward trends in transitional and developed economies.
- Cross-study notes:
  - Inclusion of agriculture and additional Asian countries likely increases estimated informality.
  - Official statistics and unofficial measurements may conflict (e.g., Schneider (2005) vs. national surveys; see Perry et al. (2007), Box 1.3).

### C. Causes and Impact of Informality
- Theoretical predictions and empirical results:
  - Loayza (1996) (Latin America, 1990s): countries with large tax burdens and weak enforcement show negative relationship between informal sector size and economic growth; very restrictive labour regulations and poor enforcement associated with largest informal sectors (examples: Bolivia, Panama, Peru). Also finds a negative relationship between informal sector size and real GDP growth.
  - Alternative hypothesis: informality may increase efficiency under imperfections (labour market regulation, corruption), yielding a positive impact on growth (e.g., Nikopour et al. (2008) review for 21 OECD countries finds positive impact).
  - Rei and Battacharya (2008) (low and middle-income countries using Schneider (2005) data): no general evidence that higher taxation and labour market regulation increase informality; results sensitive to inclusion of public and corporate governance indices. Main finding: stronger governance favors formality.

### D. Main Stylized Facts (SF) — Informal Employment
- SF 1: Developing countries tend to have a higher degree of informality than OECD countries.
- SF 2: Many countries reveal an increasing trend of informality.
- SF 3: Informalization of the formal sector — increase in informal jobs (without job/social security) within the formal/organized sector (observed in India, Argentina, other Latin American countries).
- SF 4: Job finding rate of formal jobs is highly procyclical (volatility puzzle); job finding rate of informal jobs is more stable.
- SF 5: Job separation rate in informal jobs is more responsive to negative shocks even though separation rates for formal and informal jobs are both countercyclical.
- SF 6: During a recession, despite large increase in job separation rate for informal jobs, the share of formal jobs decreases.
- SF 7: Negative correlation between informal sector employment and education within countries and between informal employment and average education attainment across countries.
- SF 8: Positive correlation between unemployment and shadow employment (cross-country/regional evidence for Brazil and Italy).
- SF 9: Example (Martin (2000), Mexico, 1990s): unemployment rate in the 1990’s was low (3.7 percent) and composed mainly by well-educated.
- SF 10: In Egypt, 70 percent of workers obtain a formal job through formal methods.
- SF 11: Negative and convex relationship between informal employment and country’s standard of living.
- SF 12: Positive relationship between informal employment and tax rate.
- SF 13: Significant earnings gap within informal economy: employers at top segment, then regular salaried employees, then casual workers.
- SF 14: Men over-represented in top segment; women over-represented in bottom segment; intermediate segment gender shares vary across sectors/countries.
- Empirical interpretations:
  - Informal sector often heterogeneous: self-employed and salaried workers co-exist; in many cases informal sector is voluntary for some (Maloney 1999, 2004), but segmentation and constrained choices occur, especially in recessions.
  - Bosch and Maloney (2006, 2007): hiring behavior of formal firms is primary driver of formal employment share; flows from informal to formal are highly procyclical; flows from formal to informal are procyclical but less volatile.
  - Wage premium for formal workers: evidence ambiguous and depends on job category (self-employed often better paid than salaried informal); in India informal regular workers paid considerably less than formal counterparts.

### Informal Credit Markets — Stylized Facts and Evidence
- Historical and aggregate patterns:
  - Informal credit strong in many developing countries (India, Pakistan, Indonesia, Brazil, many African countries) and some emerging markets (China).
  - Bell (1990): in India, over 80 percent of rural households’ debt was owed to informal credit agencies in 1951 (excluding relatives/friends at ~11 percent); by 1981 the share to informal agencies was 24 percent; share owed to formal credit institutions rose from 7 percent in 1951 to 61 percent in 1981; implied informal credit market share about 39 percent in that period. AIDIS (2003) indicates moneylenders share over 9 percent and non-institutional share over 36 percent for India.
- SF 15: Economies with less developed credit markets tend to have more segmented credit markets and greater informal credit markets.
- SF 16: Both formal and informal lenders in less developed credit markets have extensive market power.
- SF 17: Informal credit is more important the more concentrated formal credit markets are.
- SF 18: Distributional pattern — formal loans to rural households favor wealthy borrowers/large farms; majority of informal loans distributed to poor borrowers/small farms.
- SF 19: High proportion of borrowers obtain credit from both formal and informal markets simultaneously.
- SF 20: Informal moneylenders obtain formal credit to fund informal credit services.
- SF 21: Informal interest rates on average much higher than formal rates.
- SF 22: Interest rates charged by informal moneylenders may range from 0 to 200 percent per year in India, Pakistan, and Thailand.
- Additional observations:
  - Informal interest rates may exceed 75 percent per year (Besley (1994), Hoff and Stiglitz (1990)).
  - Informal credit markets coexist with formal markets via horizontal (competition/ displacement) and vertical (informal lenders borrowing from formal banks) linkages.

### III–V. Modeling Approaches — Labour and Credit Markets
- Early models:
  - Harris-Todaro tradition: segmented geographically distinct markets with wage duality; formal-sector wages can be higher-than-market-clearing wages (Todaro (1969), Harris and Todaro (1970)).
  - Efficiency wage and information-based models introduce duality via adverse selection/moral hazard.
  - Voluntary/cost-benefit models: agents weigh costs of formal registration vs. benefits of informality (Lucas (1978), Rauch (1991)).
- Search-matching framework (Mortensen-Pissarides) extensions:
  - Intersectoral margins for workers and firms:
    - Boeri and Garibaldi (2005): deterministic search-matching with heterogeneous workers; informal employment associated with more turnover, discouraging high-skill workers; multiple equilibria possible depending on relative profitability of regular vs. irregular sectors.
    - Badaoui et al. (2006): Burdett-Mortensen framework where large firms pay higher wages and concentrate in formal sector; small firms choose informal sector; differential tax-inspection probabilities matter.
  - Intersectoral margin for workers:
    - Albrecht et al. (2008): workers with high productivity accept only formal offers; relative productivity crucial; endogenous job destruction.
    - Zenou (2008): homogeneous workers more productive in formal sector; informal sector competitive and frictionless in limit; informal sector provides frictionless outside option.
    - Satchi and Temple (2009): introduces urban formal/informal and agricultural sectors; informal sector as marginal self-employment with low entry costs; endogenous capital in formal sector; does not distinguish unemployed from informal workers.
  - Intrafirm margin and occupational choice:
    - Bosch (2006, 2007): within-firm decision to employ informal labour explains coexistence of formal and informal contracts in same firm; ex-post match heterogeneity implies only high productivity matches yield formal contracts; stricter labour regulations can expand informality via intrafirm decisions and informal self-employment.

- Informal credit market models:
  - Three main strands: adverse selection, moral hazard, imperfect enforcement; search-externalities in credit markets also used.
  - Horizontal linkages: formal banks can displace informal lenders (Bell (1990)); formal credit rationing can foster informal sector (Kochar (1997)).
  - Vertical linkages: informal lenders may access formal funds; subsidized formal credit can perversely raise informal interest rates via entry, enforcement externalities, and weakened reputation effects (Hoff and Stiglitz (1997), Floro and Ray (1997), Bose (1998), Madestam (2009)).
  - Madestam (2009): heterogeneous informal lenders (rich vs. poor) generate:
    - Investment effect: additional informal finance increases investment of bank-rationed borrowers by channeling bank funds to informal lending.
    - Disciplinary effect: informal finance can increase borrowers’ returns and incentives to repay, raising bank lending.
    - Rent-extraction effect: banks use informal intermediaries to avoid agency costs, possibly making borrowers worse off; stronger banking market power increases rent-extraction and prevalence of informal credit.
  - Search/trading frictions approach: Wasmer and Weil (2004) model credit and labour market frictions symmetrically; credit market frictions reduce entrepreneurs and lenders via a “credit gap” (excess return on business loans), amplifying shocks.

### VI. General Equilibrium Models of Informality
- CGE/AGE models: static, data-driven analyses including informality in product or factor markets (Sinha (2005), Sinha and Adam (2000), Gibson and Kelley (1994), Portes et al. (1989)).
- Dynamic GE models with wage flexibility:
  - Agenor and Montiel (1996); Marjit and Kar (2008): capital mobility across formal and informal sectors; wage rate as crucial welfare measure.
  - Ihrig and Moe (2004): dynamic GE with formal sector (labour+capital) and informal sector (labour only); agents choose consumption/savings and time allocation; capital accumulation shifts labour to formal sector.
  - Conesa et al. (2002): first DSGE with an “underground” sector; features wage premium, labour indivisibilities, households choose probability of working in informal sector; prediction: wage premium differentials affect amplification of technological shocks.
- Endogenous growth:
  - Loayza (1997): AK-type model with congestible public services; larger informal sector reduces capital productivity and growth, especially with high taxes and weak enforcement.
  - Sarte (1997): rent-seeking bureaucracy forces marginal firms into informality, lowering growth.
  - Dasgupta (2005): informal financial markets can raise growth by separating high/low risk firms and reducing cost of credit rationing; informal markets can complement growth under certain regimes.
- New Keynesian DSGE with informality:
  - Castillo and Montoro (2008): dual labour market with formal/informal contracts; informality arises from lower hiring costs; informal workers act as buffer stock of labour allowing output expansion without wage pressure, linking informality to inflation dynamics and monetary transmission.
  - Batini et al. (2009): model “unobservable” labour market and wage norm; conclude benefits from reducing informality (tax smoothing, stabilization gains) outweigh costs of reduced wage flexibility.

### VII. Conclusions and Open Questions
- Literature evolution:
  - Movement from firm-characteristic view to employment-relationship view of informality (Chen (2007)).
  - Empirical and theoretical findings extensive but often contrasting; measurement and definitional issues persist.
- Synthesis of modeling strands:
  - Two main theoretical strands: informality in credit markets vs. informality in labour markets; both address many stylized facts (employment SF3–SF8; credit SF15, SF18–SF22) but several stylized facts require further development (employment SF1, SF2, SF13, SF14; credit SF16, SF17).
- Policy and research questions highlighted:
  - How effective are government policies in economies with large, unobservable labour/credit markets?
  - What are links between informality and endogenous growth?
  - Can informality be beneficial in some respects?
  - What is the link between informality and gender inequality?
- Methodological recommendation:
  - Most existing models remain partial-equilibrium; deeper understanding requires dynamic general equilibrium approaches capturing multi-dimensional informality (product, labour, credit markets) and explicit intertemporal household/producer choices.

*Source: IMF working paper chapter content provided in the supplied PDF excerpt.*

### REFERENCES

### _wp1042 - REFERENCES

### Major research themes and focus areas
- Informal economy definitions, measurement, and views:
  - Contrasting "The Old View: ILO 1972" versus "The New View: ILO 2002" on the informal economy (from Table 2 in Chen (2007)).
  - Table 1 outlines perspectives on Informality: View (Dualism, Legalistic, Structuralist), Markets (Wage Labour, Evasion, Credit), Processes/Goods/Services (Productive Scale, Legal), and Linkages (Dualist, Legalistic).

- Labor markets, search-matching, and informality:
  - Extensive literature on search and matching models, unemployment, job flows, and informal labor markets (e.g., Blanchard and Gali (2007); Boeri and Garibaldi (2005); Bosch (2006, 2007); Wasmer and Weil (2004); Zenou (2008); Satchi and Temple (2009)).
  - Table 4 classifies Search Matching Models by Heterogeneity, Informality Choice, and Informal Workers Status:
    - Albrecht et al. 2005 — heterogeneous formal workers; endogenous worker’s choice; informal self-employed
    - Boeri-Garibaldi 2005 — heterogeneous skills; end. worker’s and firm’s choice; employed in LM* with frictions
    - Bosch 2006 — homogeneous but SJM**; intrafirm margin; employed in LM with frictions
    - Bosch 2007 — heterogeneous but SJM**; intrafirm margin+occup. choice; informal self-employed
    - Fugazza and Jacques 2003 — heterogeneous informal workers; endogenous firm and worker choice; employed in LM* with frictions
    - Satchi and Temple 2008 — homogeneous; endogenous worker’s choice; unemployed in LM* with frictions
    - Zenou 2008 — Homogeneous, different sector TFPs; endogenous worker’s choice; employed in competitive LM*

- Credit markets, financial access, and informal finance:
  - Works addressing formal vs informal finance, credit rationing, and moneylenders (e.g., Banerjee (2003); Banerjee and Duflo (2007); Beck, Kunt, and Maksimovic (2004); Hoff and Stiglitz (1990, 1997); Madestam (2009); Straub (2005); Bell (1990); Das-Gupta et al. (1989)).
  - Studies on bank competition, regulation, and financial development (Barth, Caprio Jr., and Levine (2004); Fry (1978); McKinnon (1973); Shaw (1973)).

- Interaction of informality with macroeconomic policy and growth:
  - Papers linking informality to growth, monetary policy, taxation, and stabilization (Cavalcanti and Villamil (2003); Batini, Levine, and Lotti (2009); Castillo and Montoro (2008); Loayza (1997); Perry et al. (2007); Schneider and Enste (2000)).

- Measurement and empirical estimates of the informal economy:
  - Cross-country estimates and shadow economy analyses (Schneider (2005); Dell’Anno (2003); Chaudari, Schneider, and Chattopadhyay (2006); Nikopour, Shah, and Schneider (2008)).
  - Table 3 reports Informal Economy as a Percentage of GDP — Unweighted Average* from Schneider (2005):
    - 24 African countries: 33.9 (1989-1991), 37.4 (1994/1995), 41.2 (1999-2000)
    - 25 Asian countries: 20.9 (1989-1991), 23.4 (1994/1995), 26.3 (1999-2000)
    - 17 countries Cent. and South America: 34.2 (1989-1991), 37.7 (1994/1995), 41.5 (1999-2000)
    - 23 Transitional countries: 31.5 (1989-1991), 34.6 (1994/1995), 37.9 (1999-2000)
    - 21 OECD countries: 13.2 (1989-1991), 15.7 (1994/1995), 16.7 (1999-2000)
    - Note: *Unweighted average from Schneider (2005).

### Methodological and modeling approaches
- Partial equilibrium, DGE, and DSGE classifications for informality research (Table 5):
  - Labor-focused studies appearing across modeling approaches:
    - Boeri and Garibaldi (2005) — Labor — Partial
    - Bosch (2006, 2007) — Labor — Partial
    - Frankel and Pissarides (2006) — Labor — Partial
    - Albrecht et al. (2008) — Labor — Partial
    - Zenou (2008) — Labor — Partial
    - Satchi and Temple (2009) — Labor — Partial
    - Fiess et al. (2006) — Labor — DGE
    - Conesa et al. (2002) — Labor — DGE
    - Fugazza and Jacques (2003) — Labor — DGE
    - Ihrig and Moe (2004) — Product — DGE
    - Castillo and Montoro (2008) — Labor — DSGE (NK)
    - Marjit and Kar (2008) — Labor — DSGE (NK)
    - Solomon (2008) — Labor — DSGE (NK)
    - Batini et al. (2009) — Labor — DSGE (NK)
    - Wasmer and Weil (2004) — Labor+Credit — RBC
    - de Paula and Scheinkman (2007) — Labor+Credit — RBC
    - Cavalcanti and Villamil (2003) — Labor+Credit — DGE
    - Bell (1990) — Credit — RBC
    - Arnott and Stiglitz (1991) — Credit — RBC
    - Banerjee et al. (1994) — Credit — RBC
    - Floro and Ray (1997) — Credit — RBC
    - Hoff and Stiglitz (1997) — Credit — RBC
    - Kochar (1997) — Credit — RBC
    - Bose (1998) — Credit — RBC
    - Dell’Ariccia and Garibaldi (2000) — Credit — RBC
    - Antunes and Cavalcanti (2007) — Credit — RBC
    - Madestam (2009) — Credit — RBC
    - Dasgupta (2005) — Credit — DGE
    - Loayza (1997) — Product — DGE
    - Sarte (1997) — Product — DGE

### Representative citations (themes only)
- The references compile foundational and contemporary contributions on:
  - Informal sector theory and measurement (De Soto (1989); Loayza (1997); Schneider (2005); Chen (2007))
  - Labor market frictions, search, matching, and informality (Harris and Todaro (1970); Blanchard and Gali (2007); Mortensen and Pissarides-related literature)
  - Credit market imperfections and informal finance (Hoff and Stiglitz (1990, 1997); Banerjee (2003); Straub (2005))
  - Macro-micro links between informality, policy, and growth (Rebelo (1991); Romer (1990); Cavalcanti and Villamil (2003))

*Source: _wp1042 - REFERENCES*

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