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### I. INTRODUCTION AND MOTIVATION
- Financial inclusion promises to boost growth and reduce poverty and inequality by mobilizing savings and providing households and firms with greater access to resources needed to finance consumption and investment and to insure against shocks.
- Financial inclusion can foster labor and firm formalization, helping boost government revenues and strengthen social safety nets.
- Benefits could be particularly pronounced in Latin America and the Caribbean (LAC) where:
  - growth is modest and volatile,
  - poverty and inequality remain high,
  - savings and investment are low,
  - informality is rampant.
- Recent progress:
  - Strengthened financial systems after a period of instability and crises.
  - Progress via expansion of bank networks, improvements in payments systems, diversification of savings and credit services for households and SMEs.
  - Policy measures: liberalizing financial flows, addressing financial sector vulnerabilities, enhancing regulation and supervision, improving physical and market infrastructure; low-fee bank accounts; using banking sector to channel government transfers; correspondent banking arrangements; support for mobile and e-banking.
- Study objectives and approach:
  - Document current status of financial inclusion in LAC, identify gaps, analyze impacts on growth, inequality, and financial stability of removing impediments.
  - Data: FINDEX (updated), World Bank Enterprise Survey, novel composite measures of household and firm inclusion.
  - Extensions: determinants including size of shadow economy, regulatory quality, bank income sources, availability of bank safety buffers; determinants for SMEs.
- Household-side and enterprise-side analyses:
  - Household: reliance on informal finance (example of Colombia).
  - Enterprise: theoretical framework to identify binding financial frictions and simulate implications for inequality, growth, productivity.
- Organization:
  - Section II introduces indices and examines progress with financial inclusion in Latin America.

### II. MEASURING FINANCIAL INCLUSION IN LATIN AMERICA
- Indices constructed (three multi-dimensional indices):
  - (i) usage of financial services by households (Findex);
  - (ii) usage of financial services by SMEs (Enterprise Survey);
  - (iii) access to financial institutions (Financial Access Survey).
- Construction details:
  - Indices capture access and effective usage by households and firms; presented separately due to varying cross-country coverage.
  - Equal weights used for exposition; principal component analysis and factor analysis gave similar results.
- Household inclusion index components:
  - account at a formal financial institution;
  - ATM as main withdrawal mode;
  - debit card;
  - loan from a financial institution in the past year;
  - saved at a financial institution in the past year;
  - credit card.
  - (Insurance omitted due to data constraints.)
- Enterprise index components:
  - % of SMEs with a checking or savings account;
  - % of SMEs with bank loans/line of credit;
  - % of SMEs using banks to finance investments;
  - working capital bank financing (%);
  - value of collateral needed for a loan (% of the loan amount);
  - % of SME firms not needing a loan;
  - % of SME firms identifying access/cost of finance as a major constraint.
- Access to financial institutions indicators:
  - number of ATMs per 1,000 sq km;
  - number of branches of ODCs per 1,000 sq km;
  - number of branches per 100,000 adults;
  - number of ATMs per 100,000 adults.

### III. KEY PATTERNS IN HOUSEHOLD AND FIRM INCLUSION
- Household inclusion findings:
  - LAC lags other emerging markets, particularly emerging Asia, despite improvements between 2011 and 2014.
  - In 2014, 47 percent of households in LAC had an account at a formal financial institution versus 60 percent in emerging Asia.
  - Over one-fifth of households report borrowing from friends, family or an informal lender in 2014, up from 16 percent in 2011.
  - Less than 15 percent of adults in LAC, on average, obtain credit from a bank.
  - Significant gender gap in account holdings, though it has shrunk in Mexico, Costa Rica, Venezuela, and Jamaica.
  - Access to physical financial infrastructure broadly at par with other emerging markets, with pockets of poor access in the Caribbean, some Central American countries, Paraguay, and Uruguay.
  - LAC has the highest number of banking correspondents per capita in the world; Brazil, Mexico, and Colombia have strong correspondent coverage (all municipalities covered in Brazil; correspondents cover 61 and 88 percent of municipalities in Mexico and Colombia, respectively).
  - Mobile banking use is growing in areas lacking physical infrastructure but is less important than in Sub-Saharan Africa.
- Firm inclusion findings:
  - LAC compares favorably: share of firms with a loan or line of credit is 46 percent (comparable to 48 percent in emerging Asia).
  - Collateral requirements are high; access/cost of finance is a major constraint for many SMEs.
  - Nontraditional financing (factoring, Bolsa de Productos reverse factoring) growing in some countries (Chile, Mexico).
  - Regulatory environment (Global Microscope) ranks Peru first in fostering environment for financial inclusion (2014); LAC performs well on regulation of branches and agents, prudential regulation, market conduct rules; lags on credit reporting systems, regulation of electronic payments, and regulation/supervision of deposit-taking activities.

### IV. FINANCIAL INCLUSION GAPS AND THEIR DETERMINANTS
- Method:
  - Exogenous fundamentals: income per capita (log_GDP_pcap), mean years of schooling, shadow economies index, rule of law (−2.5 to 2.5), prevalence of foreign ownership (1–7), fuel exports (% of merchandise exports).
  - Gaps computed as deviations of inclusion indices from values predicted by these fundamentals.
  - Determinants of gaps analyzed: regulatory quality (Global Microscope), bank income sources, safety buffers, bank competition, bank efficiency.
- Fundamental correlates (selected coefficients as reported):
  - log_GDP_pcap: 0.0918***, 0.104***, 0.111***, 0.142***, 0.131*** across specifications (higher income per capita associated with higher household and firm inclusion).
  - Mean years of schooling: 0.0173**, 0.0160***, 0.0162** (higher education positively associated with household inclusion).
  - Rule of Law: 0.0733***, 0.0657***, 0.0502** (stronger rule of law associated with household inclusion).
  - Prevalence of foreign ownership: negative coefficients, e.g., -0.107*** for firm inclusion.
  - Fuel exports (% of merchandise exports): negative coefficients, e.g., -0.00235**, -0.00200* (lower fuel dependence associated with higher firm inclusion and access).
- Gap-level findings:
  - LAC broadly in line with domestic fundamentals for household inclusion, but substantial cross-country variation.
  - Largest positive household inclusion gaps: Bolivia, Brazil, Jamaica.
  - Largest negative household inclusion gaps: Peru, Chile, Mexico.
  - Household inclusion gaps versus Asian benchmark largely negative for LAC, exceptions include Chile and Costa Rica.
  - Firm inclusion on average outpaced fundamentals in LAC; large positive firm gaps in Peru, El Salvador, Dominican Republic; negative in Costa Rica, Mexico, Panama.
- Econometric determinants of gaps (selected relations and coefficients):
  - Higher gaps associated with lower non-interest income / total income (%) (coefficients e.g., -0.00428**, -0.00515*).
  - Lower bank safety buffers associated with household inclusion gaps (distance to default coefficient -0.00261**).
  - Bank efficiency (overhead costs / total assets %) associated with firm inclusion (e.g., overhead costs coefficient 0.0183, 0.0320*).
  - Stronger regulatory environment (Microscope overall score) associated with higher firm inclusion gaps in some specifications (Microscope coefficient 0.00314*).

### V. HOUSEHOLD ANGLE: DETERMINANTS OF INFORMAL FINANCE — CASE OF COLOMBIA
- Context:
  - Account ownership in Colombia increased from 30 to 38 percent between 2011 and 2014; remains below LAC and upper middle income averages.
  - Consumer small/medium payments mostly in cash (90 percent); large-value payments predominantly digital (almost 70 percent in 2012).
- Survey evidence (Financial Capabilities Survey):
  - 30 percent of respondents have money left after basic needs and save (top uses: emergencies; primary necessities; future purchases).
  - 60 percent run out of money to meet basic needs at least occasionally; of these, about 56 percent obtain credit from family, friends, loan sharks, stores and co-workers; 27 percent obtain credit for purchases at retail stores; one-third borrow formally.
- Empirical determinants (Colombia results):
  - Likelihood of using informal credit:
    - Increases with age.
    - Decreases at higher income levels.
    - Significantly lower for people with tertiary education.
    - For every incremental point improvement in financial education score, likelihood of using informal finance decreases by 5 percent.
    - Formal workers less likely to use informal finance than informal workers; recipients of government transfers and pensions less likely to use informal finance.
  - Among those who run out of money for basic needs:
    - Greater distance to a formal financial institution and lower education increase probability of using informal credit (distance significant at 10 percent; coefficient small).
  - IEFIC (Bogotá-focused) regressions:
    - Probability of using informal finance decreases for higher income and education, and is lower for formal workers and pension recipients.
    - Counterintuitive finding: higher financial education score associated with a higher probability of using informal finance in the IEFIC sample (significant at 1 percent), suggesting informal finance can meet certain needs even for financially educated individuals.

### VI. ENTERPRISE ANGLE: MODELING FINANCING CONSTRAINTS, GROWTH, INEQUALITY, AND STABILITY
- Model framework:
  - Micro-founded general equilibrium model where agents choose between worker and entrepreneur; entrepreneurs pay a fixed participation cost to borrow; borrowing constrained by collateral and information asymmetries; banks incur monitoring costs.
  - Three grouped financial constraints:
    - Participation costs (documentation, red tape, need for informal guarantors).
    - Borrowing constraints (collateral requirements, enforceability).
    - Intermediation costs (monitoring/audit costs, limited competition).
- Calibration:
  - Calibrated to 12 LAC countries using firm-level 2005 World Bank Enterprise Survey and macro/financial variables for 2010 or latest available.
- Model experiments (steady-state comparative statics):
  - Simulations:
    - (i) set participation cost to 0;
    - (ii) relax collateral requirements to the world minimum;
    - (iii) reduce monitoring costs to 0 (increase intermediation efficiency).
  - Key simulated outcomes:
    - Largest GDP gains across sample generally from taking collateral to the world minimum.
    - Example: GDP impact from relaxing collateral is about 4 times higher in Honduras than in Paraguay due to higher measured collateral in Honduras.
    - Declining participation costs unambiguously lowers inequality (Gini) across all countries.
    - Relaxing collateral requirements can either lower or raise inequality depending on country specifics:
      - Declines inequality where many firms already have access and collateral constraints are high (e.g., Costa Rica, Peru).
      - Raises inequality where benefits accrue disproportionately to already-included talented entrepreneurs (e.g., Uruguay, Guatemala).
    - Reducing intermediation costs can disproportionately benefit a small set of leveraged firms and raise inequality in some countries (e.g., Paraguay, Nicaragua).
    - Trade-offs:
      - Policies that most boost growth (relaxing collateral) can raise inequality and NPLs; policies that reduce participation costs reduce inequality but yield smaller GDP gains.
      - Lowering collateral constraints raises NPLs in some cases (e.g., Peru and Guatemala), illustrating growth–stability trade-offs.
    - Interaction effects:
      - GDP impact of relaxing collateral constraints is amplified when intermediation costs are lower.
      - Reducing participation costs has larger gains where the fraction of entrepreneurs without access is larger; effects depend on existing access ratios.

### VII. CASE STUDIES: GUATEMALA, EL SALVADOR, PERU — COUNTRY-SPECIFIC IMPLICATIONS
- Guatemala:
  - Gini coefficient 52 in 2011; PPP GDP per capita about US$7,500.
  - Gross national savings about 12 percent of GDP; banking penetration 40 percent (2014).
  - High labor informality (>70 percent); savings clubs reach 12 percent (2014); 20 percent borrow from family and friends versus 12 percent from financial institutions.
  - SME indicators: 60 percent of companies have a checking/savings account (LAC average 92 percent); 45 percent have lines of credit (LAC average 46 percent). Collateral averages 117 percent of the loan; spreads about 8 percentage points.
  - Model comparative statics: prioritize loosening participation constraints to lower inequality; recommended actions include increasing social spending (education), national financial inclusion plan, financial literacy; improve credit bureau implementation; promote competition to reduce spreads.
- El Salvador:
  - Gini fell from 53 (2000) to 42 (2012); average growth under 2 percent for the last decade; homicide rate in 2014 was 68.6 per 100,000.
  - Gross national savings 9.5 percent; banking penetration 35 percent (2014); 7 percent used savings clubs (2014); 17 percent borrow from banks.
  - Firm inclusion strong: >90 percent of firms have a bank account; about half have a line of credit. Loan-deposit spreads under 5 percentage points; collateral about 120 percent. Credit bureau covers over 80 percent of adults. Microfinance sector significant but largely unregulated.
  - Model suggests lowering collateral and spreads would boost growth but worsen inequality and could affect financial stability; reforms should be paired with stronger regulation/supervision and crisis management framework (dollarized economy without lender of last resort).
- Peru:
  - Average growth 6.2 (2002–13); average inflation 2.8 percent; Gini declined from 54 to 45; extreme poverty fell from 23 percent (2002) to under 5 percent (2014).
  - Gross national savings 23 percent of GDP; banking penetration low at 29 percent of adults with a bank account; proportion saving/borrowing from financial institutions 12 percent and 11 percent, respectively.
  - Enterprise inclusion: 85 percent of SMEs have a banking account; 63 percent have a loan or line of credit. High fees, spreads (~18 percentage points), and collateral (about 229 percent of loan) pose obstacles. Banking concentration: 4 banks hold 80 percent of assets.
  - Legal framework for collateral cumbersome: law specifies acceptable guarantees; mobile property rarely accepted in practice; collateral sale requires third-party sale procedure.
  - Policy priorities: multi-pronged approach — expand mobile banking and e-money under “Modelo Peru”; financial literacy programs; modernize and simplify collateral framework (modern collateral registry); foster banking competition and review M&A regulations; strengthen consumer protection and supervisory frameworks.

### VIII. CONCLUSIONS — SUMMARY FINDINGS AND POLICY TAKEAWAYS
- Progress and contrasts:
  - LAC countries have strengthened regulatory environments and improved physical access to financial institutions.
  - Firm financial inclusion has performed well on average; household financial inclusion lags, notably in account holdings and savings at financial institutions.
- Fundamental drivers:
  - Household inclusion largely explained by income per capita, education, size of shadow economy, rule of law.
  - Firm inclusion influenced by prevalence of foreign-owned firms and reliance on fuel exports.
- Policy diagnostics and recommendations:
  - Investigate short-term negative gaps relative to fundamentals for policy distortions and market frictions (e.g., high bank fees, predatory practices).
  - Promising policies include reviewing bank income sources, capping/limiting fees, eliminating predatory practices (usury laws), fostering regulatory environment for inclusion, establishing/expanding credit bureaus, leveraging mobile networks and correspondent banking to reduce costs, and strengthening bank balance sheets.
  - Positive gaps relative to fundamentals warrant scrutiny for excesses (e.g., rapid credit scaling that could endanger stability).
- Longer-run priorities to close gaps versus emerging Asian frontier:
  - Improve education systems and financial literacy.
  - Strengthen rule of law.
  - Reduce size of shadow economy.
  - Diversify economies away from oil dependence.
  - Foster higher income levels through growth.
- Trade-offs and strategy:
  - No one-size-fits-all; country-specific constraints determine optimal policy mix.
  - Policies lowering collateral requirements yield the largest growth gains but may increase inequality and NPLs; policies reducing participation costs reduce inequality but may yield smaller GDP gains.
  - Recommend multi-pronged, tailored strategies and monitoring of unintended side effects (financial stability, excessive household debt).

### Appendix. DATA AND FINANCIAL INCLUSION INDICES
- Global Findex data cover the period for 2011 and 2014 only.
- The data point from enterprise survey is the latest observation available.
- Variables and sources (selection):
  - Account at a formal financial institution (% age 15+) — Global Findex
  - ATM is main mode of withdrawal (% with an account, age 15+) — Global Findex
  - Debit card (% age 15+) — Global Findex
  - Loan from a financial institution in the past year (% age 15+) — Global Findex
  - Saved at a financial institution in the past year (% age 15+) — Global Findex
  - % of SMEs Firms With a Checking or Savings Account — Enterprise Survey
  - % of SME Firms With Bank Loans/line of Credit — Enterprise Survey
  - Value of Collateral Needed for a Loan (% of the Loan Amount) — Enterprise Survey
  - Number of ATMs per 1,000 sq km — IMF, Financial Access Survey
  - Number of branches per 100,000 adults — IMF, Financial Access Survey
- Normalization formulas:
  - Variables normalized using:
    I_xit = (x_it - min(x_it)) / (max(x_it) - min(x_it))
  - For variables capturing lack of inclusion (e.g., value of collateral needed, percent of firms identifying access/cost as a major constraint), the reverse formula was used:
    I_xit = 1 - (x_it - min(x_it)) / (max(x_it) - min(x_it))
- Weighting and aggregation:
  - Methods considered: principal component analysis (levels and differences), factor analysis (levels and differences), equal weights within subcomponents.
  - Weights were generally similar; the paper presents an index with equal weights for simplicity.
- Index counts by region and component (counts as reported):
  - Household Inclusion Index — Region 2011: East Asia and Pacific 9; Europe and Central Asia 29; Latin America 20; Middle East and North Africa 9; South Asia 6; Sub-Sahara Africa 31; Total 104. Region 2014: same counts; Total 104.
  - Firm Inclusion Index — Most recent available: East Asia and Pacific 9; Europe and Central Asia 2; Latin America 31; Middle East and North Africa 5; South Asia 4; Sub-Sahara Africa 28; Total 79.
  - Access Index — Most recent available: East Asia and Pacific 24; Europe and Central Asia 46; Latin America 32; Middle East and North Africa 15; North America 2; South Asia 7; Sub-Sahara Africa 35; Total 161.

*Source: _wp15206 - References (excerpt).*

### References .............................................................................................................

### _wp15206 - References .............................................................................................................

### I. INTRODUCTION AND MOTIVATION
- Financial inclusion holds the promise of boosting growth and reducing poverty and inequality by mobilizing savings and providing households and firms with greater access to resources needed to finance consumption and investment and to insure against shocks.
- Financial inclusion can foster labor and firm formalization, helping boost government revenues and strengthen social safety nets.
- Benefits of financial inclusion could be particularly pronounced in Latin America and the Caribbean (LAC) where:
  - growth is modest and volatile,
  - poverty and inequality remain high,
  - savings and investment are low,
  - informality is rampant.

### Recent progress and remaining scope
- Following a period of instability and crises, financial systems in LAC have been strengthened (International Monetary Fund, forthcoming).
- Progress has been made through:
  - expansion of bank networks,
  - improvements in payments systems,
  - diversification of savings and credit services available for households and SMEs.
- Policy measures contributing to inclusion include:
  - creation of an enabling environment via liberalizing financial flows, addressing vulnerabilities in the financial sector, enhancing effectiveness of regulation and supervision, and improving physical and market infrastructure,
  - specific inclusion policies such as introduction of low-fee bank accounts, use of the banking sector to channel government transfers, correspondent bank arrangements, and support for mobile and e-banking.
- Notwithstanding progress, considerable scope for enhancing household and firm financial inclusion remains.

### Study objectives, data, and approach
- The study seeks to:
  - document the current status of financial inclusion in LAC,
  - identify remaining financial inclusion gaps,
  - analyze the impact on growth, inequality, and financial stability when identified impediments to inclusion are removed.
- Data sources and measures:
  - uses the recently updated FINDEX dataset,
  - uses Enterprise Survey data collected by the World Bank,
  - develops novel and composite measures of household and firm financial inclusion to place LAC in temporal and cross-country perspective.
- Analytical extensions relative to existing research:
  - explores additional determinants of financial inclusion such as the size of the shadow economy, quality of the regulatory environment, bank income sources, and availability of bank safety buffers,
  - analyzes determinants of financial inclusion for SMEs.

### Household-side and enterprise-side analyses
- Household-side:
  - explores factors behind reliance of households on informal finance based on the example of Colombia.
- Enterprise-side:
  - applies a novel theoretical framework for identifying the most binding financial sector frictions that impede financial inclusion in several LAC countries.
  - the framework examines implications of alleviating financial frictions on inequality, growth, and productivity.
- Drawing on model results, the paper discusses case studies to offer policy priorities for fostering greater financial inclusion.

### Organization (as described)
- Section II introduces indices for measuring household and financial inclusion and examines progress with financial inclusion in Latin America.

*Source: _wp15206 - References*

### Section III presents analysis to identify financial inclusion gaps across LAC and the

### _wp15206 - Section III presents analysis to identify financial inclusion gaps across LAC and the

### II. MEASURING FINANCIAL INCLUSION IN LATIN AMERICA
- Constructed three multi-dimensional indices:
  - (i) usage of financial services by households (Findex);
  - (ii) usage of financial services by SMEs (Enterprise Survey);
  - (iii) access to financial institutions (Financial Access Survey).
- Indices capture access and effective usage of financial services by households and firms; indices are presented separately rather than combined due to varying cross-country data coverage.
- Indices constructed using equal weights for exposition; alternative aggregation methods (principal component analysis, factor analysis) yield similar results.
- Household inclusion index covers: account at a formal financial institution; ATM as main withdrawal mode; debit card; loan from a financial institution in the past year; saved at a financial institution in the past year; credit card. (Insurance omitted due to data constraints.)
- Enterprise index covers: % of SMEs with a checking or savings account; % of SMEs with bank loans/line of credit; % of SMEs using banks to finance investments; working capital bank financing (%); value of collateral needed for a loan (% of the loan amount); % of SME firms not needing a loan; % of SME firms identifying access/cost of finance as a major constraint.
- Access to financial institutions indicators include: number of ATMs per 1,000 sq km; number of branches of ODCs per 1,000 sq km; number of branches per 100,000 adults; number of ATMs per 100,000 adults.

### II. KEY PATTERNS IN HOUSEHOLD AND FIRM INCLUSION
- Household inclusion:
  - LAC continues to lag other emerging markets, particularly emerging Asia, despite improvements between 2011 and 2014.
  - In 2014, 47 percent of households in LAC had an account at a formal financial institution versus 60 percent in emerging Asia.
  - Over one-fifth of households report borrowing from friends, family or an informal lender in 2014, up from 16 percent in 2011.
  - Less than 15 percent of adults in LAC, on average, obtain credit from a bank.
  - Significant gender gap in account holdings, though it has shrunk in Mexico, Costa Rica, Venezuela, and Jamaica.
  - Access to physical financial infrastructure in LAC broadly at par with other emerging markets, with pockets of poor access in the Caribbean, some Central American countries, Paraguay, and Uruguay.
  - LAC has the highest number of banking correspondents per capita in the world; Brazil, Mexico, and Colombia have strong correspondent coverage (all municipalities covered in Brazil; correspondents cover 61 and 88 percent of municipalities in Mexico and Colombia, respectively).
  - Mobile banking use is growing in areas lacking physical infrastructure but is less important than in Sub-Saharan Africa.
- Firm inclusion:
  - LAC compares favorably overall for firms; share of firms with a loan or a line of credit is 46 percent (comparable to 48 percent in emerging Asia).
  - Collateral requirements are high; access/cost of finance is a major constraint for many SMEs.
  - Nontraditional financing (factoring, Bolsa de Productos reverse factoring) is growing in some countries (Chile, Mexico).
  - Regulatory environment (Global Microscope) finds Peru first in fostering environment for financial inclusion (2014); LAC performs well on regulation of branches and agents, prudential regulation, market conduct rules; lags on credit reporting systems, regulation of electronic payments, and regulation/supervision of deposit-taking activities.

### III. FINANCIAL INCLUSION GAPS AND THEIR DETERMINANTS
- Method:
  - Identify exogenous fundamentals: income per capita (log_GDP_pcap), mean years of schooling, shadow economies index, rule of law (−2.5 to 2.5), prevalence of foreign ownership (1–7), fuel exports (% of merchandise exports).
  - Compute gaps as deviations of financial inclusion indices from values predicted by these fundamentals.
  - Analyze determinants of gaps such as regulatory quality (Global Microscope), bank income sources, safety buffers, bank competition, and bank efficiency.
- Fundamental correlates (Table 1 summary):
  - Higher income per capita associated with higher household and firm inclusion (coefficients reported: e.g., log_GDP_pcap 0.0918***, 0.104***, 0.111***, 0.142***, 0.131*** across specifications).
  - Higher education positively associated with household inclusion (Mean years of schooling coefficients: 0.0173**, 0.0160***, 0.0162**).
  - Stronger rule of law associated with household inclusion (Rule of Law coefficient 0.0733***, 0.0657***, 0.0502**).
  - Lower degree of informality (shadow economy) associated with higher household inclusion (negative coefficients though not always significant).
  - Lower prevalence of foreign-owned firms associated with higher firm inclusion and access to institutions (Prevalence of foreign ownership coefficients negative, e.g., -0.107*** for firm).
  - Lower fuel exports (% of merchandise exports) associated with higher firm inclusion and access to institutions (negative coefficients, e.g., -0.00235**, -0.00200*).
- Gaps findings:
  - LAC as region broadly in line with domestic fundamentals for household inclusion, but substantial cross-country variation.
  - Largest positive household inclusion gaps: Bolivia, Brazil, Jamaica.
  - Largest negative household inclusion gaps: Peru, Chile, Mexico.
  - Household inclusion gaps vs. Asian benchmark largely negative for LAC, with exceptions (Chile, Costa Rica).
  - Firm inclusion: on average outpaced fundamentals in LAC; large positive firm gaps in Peru, El Salvador, Dominican Republic; negative in Costa Rica, Mexico, Panama.
- Econometric determinants of gaps (Table 2 summary):
  - Higher financial inclusion gaps associated with:
    - Lower non-interest income / total income (%) (coefficients e.g., -0.00428**, -0.00515*).
    - Lower bank safety buffers associated with household inclusion gaps (distance to default coefficient -0.00261**).
    - Lower bank efficiency (overhead costs / total assets %) associated with firm inclusion (e.g., overhead costs coefficient 0.0183, 0.0320*).
    - Stronger regulatory environment (Microscope overall score) associated with higher firm inclusion gaps in some specifications (Microscope coefficient 0.00314*).

### IV. HOUSEHOLD ANGLE: DETERMINANTS OF INFORMAL FINANCE — CASE OF COLOMBIA
- Context:
  - Account ownership in Colombia increased from 30 to 38 percent between 2011 and 2014; remains below LAC and upper middle income averages.
  - Large share of population continues to use informal finance; consumer small/medium payments mostly in cash (90 percent); large-value payments predominantly digital (almost 70 percent in 2012).
- Survey evidence (Financial Capabilities Survey):
  - 30 percent of respondents have money left after basic needs and save (top uses: emergencies; primary necessities; future purchases).
  - 60 percent of respondents run out of money to meet basic needs at least occasionally; of these, about 56 percent obtain credit from family, friends, loan sharks, stores and co-workers; 27 percent obtain credit for purchases at retail stores; one-third borrow formally.
- Empirical determinants (Colombia):
  - Likelihood of using informal credit:
    - Increases with age.
    - Decreases at higher income levels.
    - Significantly lower for people with tertiary education.
    - For every incremental point improvement in financial education score, likelihood of using informal finance decreases by 5 percent.
    - Formal workers less likely to use informal finance than informal workers; recipients of government transfers and pensions less likely to use informal finance.
  - Among those who run out of money for basic needs:
    - Greater distance to a formal financial institution and lower education levels increase probability of using informal credit (distance significant at 10 percent; coefficient small).
  - IEFIC (Bogotá-focused) regressions:
    - Probability of using informal finance decreases for higher income and education, and is lower for formal workers and pension recipients.
    - Counterintuitive finding: higher financial education score is associated with a higher probability of using informal finance in the IEFIC sample (significant at 1 percent); suggests informal finance can meet certain needs even for financially educated individuals.

### V. ENTERPRISE ANGLE: MODELING FINANCING CONSTRAINTS, GROWTH, INEQUALITY, AND STABILITY
- Model framework (Dabla-Norris et al., 2015 application):
  - Micro-founded general equilibrium model where agents choose between worker and entrepreneur; entrepreneurs pay a fixed participation cost to borrow; borrowing constrained by collateral and information asymmetries; banks incur monitoring costs.
  - Three grouped financial constraints:
    - Participation costs (documentation, red tape, need for informal guarantors).
    - Borrowing constraints (collateral requirements, enforceability).
    - Intermediation costs (monitoring/audit costs, limited competition).
- Calibration:
  - Calibrated to 12 LAC countries using firm-level 2005 World Bank Enterprise Survey and macro/financial variables for 2010 or latest available.
- Model experiments (steady-state comparisons):
  - Simulations:
    - (i) set participation cost to 0;
    - (ii) relax collateral requirements to the world minimum;
    - (iii) reduce monitoring costs to 0 (increase intermediation efficiency).
  - Key simulated outcomes:
    - Largest GDP gains across sample generally from taking collateral to the world minimum.
    - Illustrative example: GDP impact from relaxing collateral is about 4 times higher in Honduras than in Paraguay due to higher measured collateral in Honduras.
    - Decline in participation costs unambiguously lowers inequality (Gini) across all countries.
    - Relaxing collateral requirements can either lower or raise inequality depending on country specifics:
      - Declines inequality where many firms already have access and collateral constraints are high (e.g., Costa Rica, Peru).
      - Raises inequality where benefits accrue disproportionately to already-included talented entrepreneurs (e.g., Uruguay, Guatemala).
    - Reducing intermediation costs can disproportionately benefit a small set of leveraged firms and raise inequality in some countries (e.g., Paraguay, Nicaragua).
    - Trade-offs:
      - Policies that most boost growth (relaxing collateral) can raise inequality and NPLs; policies that reduce participation costs can reduce inequality but yield smaller GDP gains.
      - Lowering collateral constraints raises NPLs in some cases (e.g., Peru and Guatemala), illustrating growth–stability trade-offs.
    - Interaction effects:
      - The GDP impact of relaxing collateral constraints is amplified when intermediation costs are lower.
      - Reducing participation costs has larger gains where the fraction of entrepreneurs without access is larger; effects depend on existing access ratios.

### VI. CASE STUDIES: GUATEMALA, EL SALVADOR, PERU — COUNTRY-SPECIFIC IMPLICATIONS
- Guatemala:
  - Gini coefficient 52 in 2011; PPP GDP per capita about US$7,500.
  - Gross national savings about 12 percent of GDP; banking penetration 40 percent (2014).
  - High labor informality (>70 percent); savings clubs reach 12 percent (2014); 20 percent borrow from family and friends versus 12 percent from financial institutions.
  - SME indicators: 60 percent of companies have a checking/savings account (LAC average 92 percent); 45 percent have lines of credit (LAC average 46 percent). Collateral averages 117 percent of the loan; spreads about 8 percentage points.
  - Model comparative statics: loosening participation constraints recommended first to lower inequality; relax participation by increasing social spending (education), national financial inclusion plan, financial literacy; improve credit bureau implementation; promote competition to reduce spreads.
- El Salvador:
  - Gini fell from 53 (2000) to 42 (2012); average growth under 2 percent for the last decade; homicide rate in 2014 was 68.6 per 100,000.
  - Gross national savings 9.5 percent; banking penetration 35 percent (2014); 7 percent used savings clubs (2014); 17 percent borrow from banks.
  - Firm inclusion strong: >90 percent of firms have a bank account; about half have a line of credit. Loan-deposit spreads under 5 percentage points; collateral about 120 percent. Credit bureau covers over 80 percent of adults. Microfinance sector significant but largely unregulated.
  - Model suggests lowering collateral and spreads would boost growth but worsen inequality and could affect financial stability; reforms should be paired with stronger regulation/supervision and crisis management framework (dollarized economy without lender of last resort).
- Peru:
  - Average growth 6.2 (2002–13); average inflation 2.8 percent; Gini declined from 54 to 45; extreme poverty fell from 23 percent (2002) to under 5 percent (2014).
  - Gross national savings 23 percent of GDP; banking penetration low at 29 percent of adults with a bank account; proportion saving/borrowing from financial institutions 12 percent and 11 percent, respectively.
  - Enterprise inclusion: 85 percent of SMEs have a banking account; 63 percent have a loan or line of credit. High fees, spreads (~18 percentage points), and collateral (about 229 percent of loan) pose obstacles. Banking concentration: 4 banks hold 80 percent of assets.
  - Legal framework for collateral cumbersome: law specifies acceptable guarantees; mobile property rarely accepted in practice; collateral sale requires third-party sale procedure.
  - Policy priorities: multi-pronged approach — expand mobile banking and e-money under “Modelo Peru”; financial literacy programs; modernize and simplify collateral framework (modern collateral registry); foster banking competition and review M&A regulations; strengthen consumer protection and supervisory frameworks.

### VII. CONCLUSIONS — SUMMARY FINDINGS AND POLICY TAKEAWAYS
- Progress and contrasts:
  - LAC countries have strengthened regulatory environments and improved physical access to financial institutions.
  - Firm financial inclusion has performed well on average; household financial inclusion lags, notably in account holdings and savings at financial institutions.
- Fundamental drivers:
  - Household inclusion largely explained by domestic fundamentals: income per capita, education, size of shadow economy, rule of law.
  - Firm inclusion influenced by prevalence of foreign-owned firms and reliance on fuel exports.
- Policy diagnostics:
  - Short-term negative gaps relative to domestic fundamentals should prompt analysis of policy distortions and market frictions (e.g., high bank fees, predatory practices).
  - Promising policies include reviewing bank income sources, capping/limiting fees, eliminating predatory practices (usury laws), fostering regulatory environment for inclusion, establishing/expanding credit bureaus, leveraging mobile networks and correspondent banking to reduce costs, and strengthening bank balance sheets.
  - Positive gaps relative to fundamentals warrant scrutiny for excesses (e.g., rapid credit scaling that could endanger stability).
- Longer-run priorities to close gaps versus emerging Asian frontier:
  - Improve education systems and financial literacy.
  - Strengthen rule of law.
  - Reduce size of shadow economy.
  - Diversify economies away from oil dependence.
  - Foster higher income levels through growth.
- Trade-offs and strategy:
  - No one-size-fits-all: country-specific constraints determine optimal policy mix.
  - Policies lowering collateral requirements yield the largest growth gains but may increase inequality and NPLs; policies reducing participation costs reduce inequality but may yield smaller GDP gains.
  - Multi-pronged, tailored strategies are recommended; monitor and address potential unintended side effects (financial stability, excessive household debt).

*Source: IMF staff calculations and analysis as presented in the provided content.*

### REFERENCES

### _wp15206 - REFERENCES

### References
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- Aiyagari, M., A. Demirguc-Kunt, and V. Maksimović, 2010, “Formal versus Informal Finance: Evidence from China,” Review of Financial Studies, Society for Financial Studies, Vol. 23 (8), pp. 3048–97.
- Amidžić, G., A. Massara, and A. Mialou, 2014, “Assessing Countries’ Financial Inclusion Standing—A New Composite Index,” IMF Working Paper WP/14/36 (Washington: International Monetary Fund).
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- Beck, T., A. Demirguc-Kunt, and V. Maksimovic, 2005, “Financial and Legal Constraints to Growth: Does Firm Size Matter?” Journal of Finance, No. 60 (1), pp. 137–77.
- Blaum, J., 2013, “Wealth Inequality and the Losses from Financial Frictions,” Mimeo.
- Camara, N., and D. Tuesta, 2014, “Measuring Financial Inclusion: A Multidimensional Index,” BBVA Working Paper (14/26), BBVA Research.
- Clarke, G. R. G., L. C. Xu, and H. Fu Zou, 2006, “Finance and Income Inequality: What Do the Data Tell Us?” Southern Economic Journal, No. 72 (3), pp. 578–596.
- Central Bank of Brazil, 2011, Relatorio de Inclusao Financeira, Report No. 2 (Brasilia, Brazil).
- Dabla-Norris, E., Y. Ji, R. Townsend, and F. Unsal, 2015, “Distinguishing Constraints on Financial Inclusion and Their Impact on GDP, TFP, and Inequality,” NBER Working Paper No. 20821 (Cambridge, MA: National Bureau of Economic Research).
- Demirguc-Kunt, A., L. Klapper, D. Singer, P. Van Oudheusden, 2014, “The Global Findex Database,” Policy Research Working Paper 7255 (Washington: The World Bank).
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- Economist Intelligence Unit, 2014. “Global Microscope 2014: The Enabling Environment for Financial Inclusion,” sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY.
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### Appendix. Data and Financial Inclusion Indices

H3: Data sources and processing
- Global Findex data cover the period for 2011 and 2014 only.
- The data point from enterprise survey is the latest observation available.
- Table 1 (in source) shows the main data sources.

H3: Variables and sources (as listed)
- Account at a formal financial institution (% age 15+) — Global Findex
- ATM is main mode of withdrawal (% with an account, age 15+) — Global Findex
- Debit card (% age 15+) — Global Findex
- Loan from a financial institution in the past year (% age 15+) — Global Findex
- Saved at a financial institution in the past year (% age 15+) — Global Findex
- % of SMEs Firms With a Checking or Savings Account — Enterprise Survey
- % of SME Firms With Bank Loans/line of Credit — Enterprise Survey
- % of SME Firms Using Banks to Finance Investments — Enterprise Survey
- Working Capital Bank Financing (%) — Enterprise Survey
- Value of Collateral Needed for a Loan (% of the Loan Amount) — Enterprise Survey
- % of SME Firms not needing a loan — Enterprise Survey
- % of SME Firms Identifying Access/cost of Finance as a Major Constraint — Enterprise Survey
- Number of ATMs per 1,000 sq km — IMF, Financial Access Survey
- Number of branches of ODCs per 1,000 sq km — IMF, Financial Access Survey
- Number of branches per 100,000 adults — IMF, Financial Access Survey
- Number of ATMs per 100,000 adults — IMF, Financial Access Survey

H3: Normalization formulas
- All variables were normalized using the following formula:
  ,
  min(    )
  max(    )   min(    )
  itit
  x it
  itit
  xx
  I
  xx
  
  
  
  Where ,x it I is the normalized variable x of country i on year t, min(    ) it x is the lowest value of variable it x over all it; and max(    ) it x is the highest value of it x.
- For variables that capture a lack of financial inclusion (such as Value of collateral needed for a loan and percent of firms identifying access or cost of finance as major constraint), the reverse formula was used:
  ,
  min(    )
  1
  max(    )   min(    )
  itit
  x it
  itit
  xx
  I
  xx
  
  
  

H3: Weighting and aggregation method
- Methods used to estimate weights: principal component analysis with the variables in levels and in differences, factor analysis with the variables in levels and in differences, and equal weights within a subcomponent of the index.
- For most methods the weights were not very different from equal weights and econometric results were robust to the method of aggregation.
- The paper presents an index with equal weights for simplicity of exposition.

H3: Index counts by region and component
- Household Inclusion Index
  - Region 2011
    - East Asia and Pacific 9
    - Europe and Central Asia 29
    - Latin America 20
    - Middle East and North Africa 9
    - South Asia 6
    - Sub-Sahara Africa 31
    - Total 104
  - Region 2014
    - East Asia and Pacific 9
    - Europe and Central Asia 29
    - Latin America 20
    - Middle East and North Africa 9
    - South Asia 6
    - Sub-Sahara Africa 31
    - Total
      - 104

- Firm Inclusion Index
  - Region M.R.A. 1/
    - East Asia and Pacific 9
    - Europe and Central Asia 2
    - Latin America 31
    - Middle East and North Africa 5
    - South Asia 4
    - Sub-Sahara Africa 28
    - Total 79

- Access Index
  - Region M.R.A. 1/
    - East Asia and Pacific 24
    - Europe and Central Asia 46
    - Latin America 32
    - Middle East and North Africa 15
    - North America 2
    - South Asia 7
    - Sub-Sahara Africa 35
    - Total 161

- Note: 1/ Most recent year available.

*Source: _wp15206 - REFERENCES (excerpt).*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp15206.pdf_