## 2. Mobile Money and Accounts in Financial Institutions

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### I. Introduction and purpose
- Financial inclusion analyzed as an aspect of financial development with benefits including: promotion of economic growth, enhanced productivity growth, capital accumulation, reduced income inequality, and poverty alleviation.
- Chapter purpose:
  - Overview trends and drivers of financial inclusion.
  - Synthesize research findings useful for policymakers.
  - Identify directions for future research.
- Paper structure (high level): working definition and data trends (Section II); theoretical and empirical impacts (Section III); households’ access/use and MSME financing (Sections IV–V); conclusions and research directions (Section VI).

### II. Working definition and measurement
- Operational definition for empirical work: the proportion of individuals and firms that use financial services (World Bank’s 2014 Global Financial Development Report).
- Measurable dimensions: access, degree of use, quality, and cost (use measures often reflect access, cost, and quality simultaneously).
- Key datasets and composite-index approaches:
  - Global Findex: survey of about 150,000 households across 140 countries; indicators include account holdings, credit and savings activities, and whether wages or government transfers are paid directly into accounts. First conducted in 2011 and conducted every three years since.
  - World Bank Enterprise Surveys (WBES): firm-level indicators such as use of bank credit and whether lack of finance is a major obstacle.
  - IMF’s Financial Access Survey (FAS): supply-side measures such as number of borrowers per 1,000 adults, branches and ATMs per population.
  - Composite indicators: Svirydzenka (2016), Blancher and others (2019), Loukoianova and Yang (2018), Sahay and others (2020).

### III. Measured trends, mobile money, and limits
- Account holding and borrowing trends:
  - Global Findex adult account holding increased from 51 percent in 2011 to 69 percent in 2017.
  - Remaining unbanked: an estimated 1.7 billion adults without an account.
  - Borrowing from formal financial institutions increased from 9 to 11 percent if credit card use is excluded.
  - Borrowing increased from 22 to 23 percent if credit card use is included.
- Mobile money adoption and regional patterns:
  - Mobile money accounts are a key component of inclusion gains, concentrated mostly in Sub-Saharan Africa and to a lesser degree in South Asia.
  - In Sub-Saharan Africa, over one-fifth of the adult population uses mobile money accounts; worldwide share is 4 percent.
  - Country examples:
    - Kenya: mobile money penetration 73 percent.
    - Singapore: 10 percent mobile money penetration and much higher account holding.
    - Namibia: mobile money penetration 43 percent together with above-average account holding.
    - Chad: little presence of either mobile money or account holding.
- Income and regional differences:
  - Account holding exceeds 90 percent in high income countries on average.
  - Account holding is 70 percent in the emerging and developing regions with the highest levels (East Asia and Pacific and South Asia).
  - Bank borrowing: 55 percent in high income countries versus 24 percent in Europe and central Asia.
  - Across all regions and income levels, borrowing is much less widespread than account holding; even in rich countries, an adult is over four times as likely to have an account than to borrow from a formal financial institution.
- Correlations:
  - Account holding and borrowing indicators from Global Findex have the highest correlation with income per capita, with a coefficient of over 0.70.
  - Supply-side FAS indicators are positively correlated with income.

### IV. COVID-19: challenges and opportunities for financial inclusion
- Challenges:
  - Severe setbacks to the real economy weakened borrowers’ ability to repay, threatening financial institutions’ survival.
  - Non-bank institutions such as microfinance lenders experienced collapses in repayment rates.
  - Fintech startups faced funding withdrawals from venture capital and investors.
- Opportunities:
  - Rapid deployment needs for government transfers accelerated shift from cash to bank accounts and digital payments.
  - Concerns about cash as a virus transmission medium induced shifts away from cash, aiding digital inclusion.
  - Expansion of mobile money in many developing countries facilitated easier risk sharing among families and faster push-out of government support (example cited: Togo).

### V. Structural conditions, innovation, and the Financial Possibilities Frontier (FPF)
- Structural benchmark (SB) and Financial Possibilities Frontier (FPF) concepts:
  - Structural conditions (income, population size and density, demographic factors, special circumstances, global cycle) determine per-person cost effectiveness and expected inclusion levels.
  - Innovation (including mobile money) can reduce delivery costs, shifting SB and potentially the FPF upward.
  - Benchmarking exercise: quantile regressions for 46 indicators of financial depth, inclusion, or performance; predicted median used as structural benchmark.
- Empirical examples:
  - Inclusion measures plotted against GDP per capita show positive relationship; including mobile money raises account-holding measures for some low-income countries.
  - Uganda and Zimbabwe: account holding markedly greater than predicted by income.
  - Kenya: over 80 percent account holding, approaching levels of countries with many times its income per capita.
  - India: percent of account holders increased from 35 to 80 percent between 2011 and 2017; structural benchmark for account holding: 40 percent. Firms’ use of bank credit: 21 percent in 2014 versus predicted 35 percent by structural conditions.
  - Colombia: account holding underperformed its structural benchmark in 2017 while credit to firms overperformed.
  - Lithuania: 83 percent of adults reported having a bank account in 2017; survey responses indicate voluntary nonparticipation reasons (8 percent access via family member, 3 percent no need, 1 percent religious reasons).
- Interpreting gaps:
  - Overperformance relative to SB: successful pro-inclusion policies.
  - Underperformance relative to SB: possible policy failures or structural impediments.
  - Exceeding the FPF: “excessive financial inclusion” that may be undesirable or unsustainable (example cited: U.S. subprime mortgage expansion).
  - Distinguish voluntary exclusion (choice) from involuntary exclusion (market frictions, information asymmetries, high transaction costs).

### VI. Channels, models, and tradeoffs — DNJTU framework and simulations
- Key frictions identified in DNJTU (Dabla-Norris, Ji, Townsend, Unsal):
  1. Credit access/entry cost friction: distance to bank, documentation, lack of knowledge, cultural constraints, lack of trust, discrimination.
  2. Weak contract enforceability: collateral constraints limiting leverage.
  3. Efficiency of financial intermediation: spread between loan rate and deposit rate.
- Model implications:
  - Introduction of credit increases GDP; effects on productivity and income distribution ambiguous.
  - Simulations (reducing friction ψ for Malaysia, the Philippines, Egypt): greater access increases activity; TFP may decline as small firms enter; income distribution improves; little effect on spreads or nonperforming loans in those calibrations.
  - In low-income countries with much lower initial inclusion, larger reductions are required to increase entrepreneurship; initial TFP may not fall but income distribution can worsen as wealthier entrepreneurs benefit first.
- Tradeoffs and risks:
  - Policies easing frictions can introduce leverage and raise nonperforming loan ratios.
  - Large credit expansions can boost GDP and productivity while increasing systemic risks in frameworks with bank failures.
  - Even when all income groups benefit, Gini coefficient may increase.
  - No “one size fits all”: choice between reducing single most-binding friction or balanced approach depends on country conditions.

### VII. Household financial inclusion: scale, patterns, barriers, and interventions
- Scale and composition:
  - 1.7 billion adults excluded from financial services worldwide.
  - Half of the 1.7 billion unbanked live in seven developing economies: Bangladesh, China, India, Indonesia, Mexico, Nigeria and Pakistan.
  - 56 percent of all unbanked are women.
  - Half of unbanked adults come from the poorest 40 percent of households.
- Access versus use:
  - Global Findex 2017: reported 69 percent banked worldwide; adjusted for inactive accounts this becomes 55 percent worldwide and 48 percent for developing countries.
  - Nearly 750 million people worldwide have accounts they have not used in a year (majority in India and China).
  - In India, three quarters of the 222 million accounts opened remain inactive (post government effort).
- Reasons for not having an account (Global Findex seven reasons, ranked): lack of money; a family member has an account; opening an account is costly; banks are too far away; respondent lacks proper documentation; little trust in financial institutions; religious reasons.
- Specific numeric impacts of government-payment-driven account openings:
  - Roughly 90 million adults opened their first bank account to collect public sector wages.
  - 140 million to receive government transfers.
  - 120 million to receive public sector pensions.
  - 200 million to collect private sector wages.
  - About 100 million unbanked adults still receive government payments in cash; 230 million adults still receive private sector wages in cash.
- Digital infrastructure and KYC:
  - Digital penetration rate (percentage of population that use the internet) is 51 percent in 2019 (Statista, 2019).
  - 18 percent of Global Findex respondents cite documentation requirements as a reason for not having an account; some countries simplified KYC (examples noted: Brazil basic accounts, India “Aadhar” biometric ID).
- Evidence on payments and mobile money benefits:
  - M-PESA evidence:
    - M-PESA users facing negative shocks are less prone to cutting consumption and receive more diverse and larger transfers.
    - M-PESA adoption in 2007 can explain 10 percent of per capita income growth between 2007 and 2013 (Beck et al. calibration).
    - Suri and Jack (2016): M-PESA helped lift 2 percent of Kenyans out of poverty by reducing transaction costs and enhancing consumption smoothing.
  - M-Shwari: expanded access to credit and improved household resilience to income shocks but had no measurable effects on investments and savings (Bharadwaj, Jack, and Suri, 2019).
  - Paytm (India): district-level adoption associated with greater resilience of economic activity and household consumption to adverse rainfall shocks; firm-level adoption associated with greater sales.

### VIII. MSME inclusion: constraints, heterogeneity, and policy instruments
- Scale and heterogeneity:
  - MSMEs comprise over 95 percent of firms worldwide.
  - In low and middle income countries more than 50 percent of workers are in companies with fewer than 100 employees.
  - Heterogeneity: distinction between micro, small, medium; between subsistence and transformational entrepreneurs (examples: De Mel, McKenzie, and Woodruff; Bruhn).
- Constraints limiting MSME finance:
  - High fixed transaction costs -> economies of scale favor larger loans.
  - Severe information asymmetries: lack of audited financials, limited collateral.
  - Three limitation types: voluntary exclusion, supply-side constraints, institutional deficiencies.
- Policy instruments and caveats:
  - Financial capability programs and targeted financial literacy RCTs can affect entrepreneurship/business expansion under certain conditions.
  - Institutional reforms: macro stability, collateral registries (including movable assets), legal reform, accounting and auditing standards, credit registries/bureaus.
  - Market interventions: partial credit guarantee (PCG) schemes can overcome opacity and lack of collateral but require careful pricing, funding, institutional structure, and cost-benefit analysis; evidence on PCGs is mixed.
  - Transaction-based techniques (leasing, factoring) can expand access but require supportive legal frameworks.
  - Promote competition and private-sector solutions where institutional prerequisites exist.

### IX. Financial education and capability evidence and design lessons
- Meta-analyses (Fernandes and others (2014); Miller and others (2014)) find limited effectiveness in changing financial behaviors (e.g., likelihood of saving or planning for retirement); these studies generally do not address cost considerations.
- Design features that increase effectiveness:
  - Target less literate groups (women, youth, elderly, poor, lower education).
  - Leverage social networks and peer effects.
  - Tailor interventions to participants’ needs and teachable moments.
  - Adapt delivery channels (courses, workshops, counseling, online, radio, television, entertainment formats).
  - Simplify content and teach rules of thumb rather than complex calculations.

### X. Key policy implications and recommendations
- Focus diagnosis and policy on involuntary exclusion driven by market frictions rather than mechanically targeting a numeric inclusion rate.
- Use benchmarking tools (e.g., Finstats) to assess over- or underperformance relative to structural conditions.
- Recognize that innovation (including mobile money) can shift structural benchmarks and the FPF by lowering delivery costs.
- Distinguish voluntary from involuntary exclusion when designing interventions.
- Prioritize cost-effective remedies for the most binding frictions (credit access/entry cost, collateral constraints, intermediation inefficiency).
- Be cautious about pushing inclusion costs or risks beyond sustainable or socially desirable levels (avoid creating excessive financial inclusion).
- For MSME finance: combine institutional reforms, market-friendly instruments, and targeted interventions; evaluate PCGs for additionality and fiscal contingent liabilities.
- Improve information and credit infrastructure where cost-effective (credit registries, bureaus, payment histories).
- Encourage proportionate AML/CFT and risk-based KYC to avoid excluding low-value users.
- Invest in digital infrastructure, enabling regulation for fintech and mobile money, and supportive agent networks and payment systems.
- Strengthen bank regulation and supervision to manage inclusion–stability tradeoffs, especially for credit inclusion.

### XI. Conclusions and research priorities
- Financial inclusion has expanded markedly but persistent regional, income, and gender gaps remain; use often lags access.
- DNJTU framework identifies three core frictions constraining credit (entry costs, collateral, intermediation inefficiency); reducing these frictions yields gains in simulations but also tradeoffs.
- Research needs:
  - More empirical work on additionality and full cost-benefit analysis of inclusion policies (PCGs highlighted).
  - Theoretical models that incorporate financial stability effects to understand mechanisms where greater credit access may lead to undesirable outcomes ("too much finance" in an inclusion context).
  - Further empirical investigation of credit accelerations and financial distress to inform inclusion–stability tradeoffs.

*Source: Excerpt from “2. Mobile Money and Accounts in Financial Institutions” in IMF working paper (wpiea2020157-print-pdf).*

### 2. Mobile Money and Accounts in Financial Institutions ........................................................44

### 2. Mobile Money and Accounts in Financial Institutions ........................................................44

### I. Introduction and purpose
- Financial inclusion is analyzed as an aspect of financial development associated with benefits such as promotion of economic growth, enhanced productivity growth, capital accumulation, reduced income inequality, and poverty alleviation.
- The chapter’s purpose: overview trends and drivers of financial inclusion, synthesize research findings useful for policymakers, and identify directions for future research.
- Paper structure (high level): working definition and data trends (Section II); theoretical and empirical impacts (Section III); households’ access/use and MSME financing (Sections IV–V); conclusions and research directions (Section VI).

### II. Working definition and measurement
- Operational definition used for empirical work: the proportion of individuals and firms that use financial services (World Bank’s 2014 Global Financial Development Report).
- Different dimensions that can be measured: access, degree of use, quality, and cost. Use measures often reflect access, cost, and quality simultaneously.
- Key datasets and composite-index approaches:
  - Global Findex: survey of about 150,000 households across 140 countries; indicators include account holdings, credit and savings activities, and whether wages or government transfers are paid directly into accounts. First conducted in 2011 and conducted every three years since.
  - World Bank Enterprise Surveys (WBES): firm-level indicators such as use of bank credit and whether lack of finance is a major obstacle.
  - IMF’s Financial Access Survey (FAS): supply-side measures such as number of borrowers per 1,000 adults, branches and ATMs per population.
  - Composite indicators constructed using principal components or other weighting: Svirydzenka (2016), Blancher and others (2019), Loukoianova and Yang (2018), Sahay and others (2020).

### III. Signs of improvement, measured trends, and limits
- Account holding trends:
  - Global Findex adult account holding increased from 51 percent in 2011 to 69 percent in 2017.
  - Remaining unbanked: an estimated 1.7 billion adults without an account.
- Borrowing trends:
  - Borrowing from formal financial institutions increased from 9 to 11 percent if credit card use is excluded.
  - Borrowing increased from 22 to 23 percent if credit card use is included.
- Mobile money adoption and regional patterns:
  - Mobile money accounts are a key component of inclusion gains, concentrated mostly in Sub-Saharan Africa and to a lesser degree in South Asia.
  - In Sub-Saharan Africa, over one-fifth of the adult population uses mobile money accounts; worldwide share is 4 percent.
  - Country examples: Kenya with mobile money penetration 73 percent; Singapore with 10 percent mobile money penetration and much higher account holding; Namibia with mobile money penetration 43 percent together with above-average account holding; Chad with little presence of either mobile money or account holding.
  - Many countries with widely varying levels of account holding have very little presence of mobile money.
- Income and regional differences:
  - Account holding exceeds 90 percent in high income countries on average.
  - Account holding is 70 percent in the emerging and developing regions with the highest levels (East Asia and Pacific and South Asia).
  - Bank borrowing: 55 percent in high income countries versus 24 percent in Europe and central Asia.
  - Across all regions and income levels, borrowing is much less widespread than account holding; even in rich countries, an adult is over four times as likely to have an account than to borrow from a formal financial institution.
- Correlation with income per capita:
  - Account holding and borrowing indicators from Global Findex have the highest correlation with income per capita, with a coefficient of over 0.70.
  - Supply-side indicators from FAS (number of borrowers per 1,000 adults, branches and ATMs per population) are positively correlated with income.
- Policy adoption on financial inclusion:
  - According to the World Bank’s 2014 Global Financial Development Report, about 50 countries had adopted explicit policies to boost financial inclusion.
  - Economist Intelligence Unit’s Global Microscope (55 emerging market economies analyzed): about two-thirds had explicit national financial inclusion strategies in 2014; by 2019, all but one of the analyzed countries had them.

### IV. COVID-19: challenges and opportunities for financial inclusion
- Challenges:
  - Severe setbacks to the real economy have weakened borrowers’ ability to repay, posing challenges for survival of many financial institutions.
  - Non-bank institutions such as microfinance lenders have experienced collapses in repayment rates, generating uncertainty about their viability and potentially leaving many SMEs without access to finance.
  - Fintech startups have been affected, with venture capital and investors forced to withdraw funding.
- Opportunities:
  - Need for rapid deployment of government transfers accelerated the transition away from cash into bank accounts and digital payments.
  - Cash transactions as potential virus transmission medium have induced individuals to accelerate shift away from cash, with potential benefits for financial inclusion.
  - Expansion of mobile money accounts in many developing countries facilitates easier risk sharing among families and friends and easier push-out of government support programs through mobile money networks (example cited: Togo).

### V. Structural conditions and the Financial Possibilities Frontier
- Concept: providing financial services to a wide population entails costs that may exhibit economies of scale; structural conditions determine per-person cost effectiveness and thus expected financial inclusion levels.
- Key structural determinants:
  - Income level: higher-income countries face lower per-person costs of providing services, leading to higher financial inclusion.
  - Population size and density, and demographic factors (young and old age dependency ratios) influence cost-effectiveness of providing services.
- Empirical evidence:
  - Positive association between income per capita and various measures of financial inclusion (account holding, borrowing, firm use of bank credit, supply-side measures).

*Source: Excerpt from “2. Mobile Money and Accounts in Financial Institutions” in IMF working paper (chapter section).

### Section II.F reviews evidence of how mobile money can enhance risk sharing.

### wpiea2020157-print-pdf - Section II.F reviews evidence of how mobile money can enhance risk sharing

### Mobile money, innovation, and structural benchmarking
- Innovation can reduce the costs of providing financial services, effectively shifting upward the structural benchmark (SB) line, and potentially the Financial Possibilities Frontier (FPF) as well.
- Rapid proliferation of mobile money in some countries is presented as evidence of such innovation-driven shifts.
- The benchmarking exercise described uses quantile regressions for each of 46 indicators of financial depth, inclusion, or performance on structural explanatory variables (economic development, population factors, demographic factors, “special circumstances”, and the global cycle) and uses the predicted median from these regressions as the structural benchmark.

### Empirical examples and key statistics
- Inclusion measures plotted against GDP per capita show a positive relationship; including mobile money raises account-holding measures for several low-income countries.
- Country-level examples after including mobile money:
  - Uganda and Zimbabwe exhibit levels of account holding markedly greater than the level predicted by their income.
  - Kenya, at over 80 percent, approaches the level of countries with many times its income per capita.
- India:
  - Percentage of account holders increased from 35 to 80 percent between 2011 and 2017.
  - Structural benchmark for account holding: 40 percent.
  - Firms’ use of bank credit: 21 percent in 2014 versus a predicted 35 percent by structural conditions.
- Colombia:
  - Account holding underperformed its structural benchmark in 2017 while credit to firms overperformed.
- Lithuania (illustrative of voluntary exclusion and survey responses):
  - 83 percent of adults reported having a bank account in 2017.
  - 8 percent stated they did not have a bank account because they had access through another family member.
  - 3 percent felt they had no need for financial services.
  - 1 percent cited religious reasons.
  - In the Enterprise Survey in 2013, about 33 percent reported having a bank loan or line of credit.
  - 54 percent of firms responded that they had not applied for bank credit because they had no need for it.
- The Finstats database and Dashboard created by Feyen, Kibuuka, and Sourrouille (2019) provide observed values and estimated structural benchmarks for the 46 indicators.

### Financial Possibilities Frontier (FPF) and excessive financial inclusion
- The FPF represents the optimal level of financial inclusion obtained when policies extend services broadly in an efficient and sustainable manner.
- A country can:
  - Underperform its structural benchmark (positive financial inclusion gap) due to policies that hinder inclusion.
  - Overperform its structural benchmark (negative gap) due to successful pro-inclusion policies.
  - Exceed the FPF, resulting in excessive financial inclusion that may be neither desirable nor sustainable (example cited: U.S. subprime mortgage expansion prior to the crisis).
- The graphical relationships are stylized; the relationship between structural conditions, financial inclusion, and the FPF need not be linear, and both lines will shift by indicator (e.g., account holding tends toward universality as structural conditions improve, whereas use of bank credit stays well below 100 percent).

### Interpreting “gaps” in financial inclusion: voluntary versus involuntary exclusion
- Presence of a gap between observed inclusion and structural benchmark does not automatically imply a policy failure or that more inclusion is always better.
- Voluntary exclusion:
  - Some individuals choose not to use financial services (survey evidence from Global Findex and country examples).
  - Policy responses could include encouraging financial education or providing services compatible with religious beliefs, but cost effectiveness of such policies is an open question.
- Involuntary exclusion:
  - May reflect rational market equilibria driven by information asymmetries and risk (Stiglitz and Weiss (1981) adverse selection framework).
  - Lenders may ration credit or set maximum interest rates as equilibrium responses, leaving some demand unsatisfied; including excessively risky borrowers would be detrimental overall.
  - High transaction costs can render service provision to some segments uneconomic, meaning some exclusion may reflect underlying cost structures rather than a pure policy shortfall.

### Policy implications highlighted
- Policymakers should:
  - Recognize that innovation (including mobile money) can shift structural benchmarks and the FPF by lowering delivery costs.
  - Use benchmarking tools (e.g., Finstats) to assess over- or underperformance relative to structural conditions.
  - Distinguish voluntary from involuntary exclusion when designing interventions.
  - Be cautious about pushing inclusion costs or risks beyond sustainable or socially desirable levels (avoid creating excessive financial inclusion).
  - Consider targeted policies (financial education, service design compatible with religious beliefs, competition-enhancing reforms) where appropriate, weighing cost effectiveness and risk considerations.

*Source: wpiea2020157-print-pdf - Section II.F reviews evidence of how mobile money can enhance risk sharing.*

### Section IV discusses financial education and capability in greater detail. Fernandes and others (2014) and Miller and ot

### wpiea2020157-print-pdf — Section IV excerpt

### Financial education and capability
- Fernandes and others (2014) and Miller and others (2014) conduct meta analyses of studies of financial education programs and find that there is limited effectiveness in changing financial behaviors of individuals, for example, the likelihood of saving or planning for retirement.
- Note that these studies generally do not address cost considerations.

### Access, costs, and innovation in financial inclusion
- Fixed costs of providing loans exclude:
  - potential borrowers with projects whose return is not high enough;
  - individuals with demand for very small loans because providing these loans has an important fixed cost component.
- Spatial or geographic characteristics of inclusion arise from cost-driven branch placement; remote areas may lack branches because fixed costs cannot be covered by low demand.
- Innovation can dramatically change the landscape by reducing fixed costs. Example: low-income countries recently boosting account holding through mobile money.
- Some financial services (basic transactions and payments) can approach universality without undue costs or risks.

### Structural benchmark–FPF framework and targets
- The structural benchmark–FPF framework can guide policymakers to assess a country’s financial inclusion and compare with peers.
- Evidence of underperformance relative to the structural benchmark suggests examining policies from overperforming peers.
- Example: Indian firms’ use of credit—"21 percent compared with the structural benchmark of 35 percent"—should prompt examination of peer-country policies.
- The exact optimal level of financial inclusion (the FPF) is not known in practice; "35 percent could serve as an initial target" but determining an appropriate long-term target is challenging.

### Policy focus: reduce market frictions rather than target inclusion
- Major takeaway: policy should focus on involuntary exclusion driven by market frictions and enact policies that reduce these frictions.
- Example friction: imperfect or incomplete information in credit markets — policy response: improve information on prospective borrowers (e.g., setting up a credit registry) when possible and cost-effective.
- Other common frictions: weak contract enforcement and property rights, lack of competition.
- De la Torre, Gozzi, and Schmukler (2017) criterion for meaningful lack of access: when an investment project that would be internally financed by the agent if she had the required resources does not get external funding due to credit market frictions (wedge between lender’s required return and borrower’s required return).

### Diagnostic frameworks for policy prioritization
- Claessens and Rojas-Suárez (2020) propose a "decision tree" approach for digital financial services that uses country-specific information and cross-country benchmarks to identify the most binding constraints and guide policy interventions.

### Why financial inclusion matters — theoretical and empirical context
- Finance performs critical functions: (i) produce information; (ii) allocate capital to productive uses; (iii) monitor investments and exert corporate control; (iv) mobilize and pool savings; (v) facilitate trading, diversification, and management of risk; and (vi) ease exchange of goods and services (Levine, 2005).
- Financial depth indicators commonly used: ratio of credit to the private sector to GDP; stock market capitalization or volume of transactions per year to GDP.
- Empirical evidence links greater financial depth to higher long-run economic growth, capital accumulation, and productivity (Levine, 2005; Popov, 2018).
- "Too much finance" hypothesis: the relationship between growth and financial depth tends to be hump-shaped; benefits weaken at very high levels of depth. Footnote examples:
  - Arcand, Berkes, and Panizza (2015): positive link not unlimited; private credit to GDP exceeding "100 percent" may reduce growth benefits.
  - Cecchetti and Kharroubi (2015): rapid banking-sector growth can negatively impact productivity.
  - Rousseau and Wachtel (2017): incidence of financial crises weakens the finance–growth relationship.

### Financial inclusion as an additional dimension of financial development
- Financial inclusion complements financial depth; two countries with identical depth can differ in allocation breadth (e.g., credit distributed broadly vs. concentrated among few large firms).
- Inclusion can improve carrying out of financial functions (allocating capital, producing information, exerting corporate control) beyond what depth measures capture.
- Example divergence: banks provide credit equal to about "sixty percent of GDP" in both Bosnia and Herzegovina and Israel, yet in 2017 an individual in Israel was more than three times as likely to borrow from a formal financial institution than in Bosnia and Herzegovina—suggesting deeper financial development in Israel not captured by depth alone.

### Macro-level empirical findings on inclusion, growth, inequality, and stability
- Data limitations: IMF FAS annual observations since "2004"; Findex has only three observations per country over "2011-2017"; WBES offers limited, non-synchronous observations.
- Sahay and others (2015) use several FAS indicators and Svirydzenka (2016) composite indicators interacting them with private sector credit–GDP ratio; results suggest financial inclusion has a measurable impact on "10-year growth" above financial depth.
  - Impact of depth on growth increases with financial inclusion (ATM coverage or firms not considering lack of finance a significant obstacle).
  - Findings consistent with "too much finance" hypothesis: growth impact weakens with increases in both inclusion and depth.
- Cihák and others (2020): panel regressions for "105 countries over the 2004-15 period" link payments services (approximated by ATM coverage) to lower inequality (GINI coefficient). Relationship stronger when growth is faster, financial system more stable, and financial depth is lower.
  - For credit inclusion (share of borrowers), the negative inclusion–inequality relationship is strong at low depth, weakens at higher depth, and eventually reverts (at high depth an expansion in credit can increase inequality).
- Loukoianova and Yang (2018): composite measures show beneficial effects of inclusion—reducing inequality and poverty and increasing growth.
- Stability literature:
  - Han and Melecky (2013): greater inclusion in bank deposits had a stabilizing effect during the 2008 crisis—countries with larger deposit access suffered smaller withdrawals.
  - Mehrotra and Yetman (2015): consumption volatility tends to be lower where a larger percentage of adults have accounts and save formally.
  - Cihak, Mare, and Melecky (2016): panel of "150 countries" finds a complex inclusion–stability relationship—tradeoffs exist (notably for credit expansions) but also synergies during non-crisis times; relationship affected by country characteristics (financial openness, tax rates, education, credit information depth).
  - Sahay and others (2015) and Cihák and others (2020): credit inclusion’s relationship with stability depends on the quality of bank regulation and supervision—if high, no tradeoff; if low, tradeoff emerges and credit inclusion can reduce financial stability.
  - Ahamed and Mallick (2019): international sample of "2,635 banks in 86 countries" finds financial inclusion contributes to a more stable banking system, especially when banks are mostly deposit-funded, have low marginal costs, and operate within a strong institutional environment.

### Channels and mechanisms — DNJTU framework and model simulations
- DNJTU (Dabla-Norris, Ji, Townsend, and Unsal, 2015 and 2019) develop a theoretical model with heterogeneous agents and multiple financial frictions to trace channels through which finance and inclusion affect outcomes.
- Stylized distinctions in the model:
  - "Savings regime" (no credit): four agent types—unconstrained workers, constrained workers, constrained entrepreneurs, unconstrained entrepreneurs.
  - "Credit regime": introduction of credit allows talented but asset-poor individuals to become entrepreneurs; increases entrepreneurship and allows scaling up toward optimal production.
- Key frictions inhibiting credit expansion:
  1. Credit access/entry cost friction: distance to bank, documentation, lack of knowledge, cultural constraints, lack of trust, discrimination. High costs make access to services like credit very costly for large population segments.
  2. Weak contract enforceability: leads banks to impose collateral constraints, limiting leverage and quantity of credit.
  3. Efficiency of financial intermediation (spread between loan rate and deposit rate): increases cost of credit and reduces profitability of debt-financed activity.
- Model implications:
  - Introduction of credit increases overall GDP; effects on productivity and income distribution are ambiguous (entry of small-scale, initially less productive firms can reduce aggregate TFP while increasing entrepreneurship).
  - Calibration and simulations (example: reductions in financial inclusion friction ψ for Malaysia, the Philippines, and Egypt) show greater access to credit increases economic activity; TFP may decline due to entrance of small firms; income distribution improves; little effect on interest spreads or nonperforming loans in those simulations.
  - For three low-income countries with substantially lower initial inclusion, larger reductions in the friction are required to noticeably increase entrepreneurship; initial TFP may not fall but income distribution can worsen as wealthier entrepreneurs benefit first.
- DNJTU lessons:
  - No "one size fits all" policy—different policies have different impacts depending on country-specific conditions.
  - Because frictions interact, the most binding friction may not be obvious from descriptive data alone; careful diagnostic and country-specific analysis is needed before selecting interventions.

*Source: wpiea2020157-print-pdf (Section IV excerpt).*

### 6.7 percent of firms having access to credit, it would seem that in Pakistan the entry cost

### wpiea2020157-print-pdf - 6.7 percent of firms having access to credit, it would seem that in Pakistan the entry cost

### Key findings on financial frictions and tradeoffs
- Simulations indicate that, despite low entry (credit access) in some cases (example cited: 6.7 percent of firms having access to credit), it is the collateral constraint whose reduction produces the greatest gains to the economy in the DNJTU framework.
- Policies that facilitate finance often introduce leverage and raise the possibility of borrower default; facilitating finance can be accompanied by an increase in the nonperforming loan ratio.
- A large enough expansion of credit can boost GDP and productivity while increasing risks to financial stability in a framework that incorporates bank failures.
- Even when all income groups benefit from policies to ease frictions, income distribution may become more unequal — the Gini coefficient increases.
- Country conditions matter for strategy design: whether to reduce the single most-binding friction or to pursue a balanced approach across frictions.

### Microfinance, poverty traps, and empirical heterogeneity
- Theoretical benchmark models with heterogeneous entrepreneurs (talent and initial wealth) show financial frictions can prevent talented but poor individuals from becoming entrepreneurs, creating mechanisms for poverty traps at individual and aggregate levels.
- Field evidence and randomized experiments:
  - A randomized intervention in Hyderabad, India: micro credit randomly assigned to 52 neighborhoods and later withdrawn, showed persistent increases in entrepreneurship, profits, business scale, turnover and employment in treated neighborhoods.
  - Heterogeneity among recipients: “gung ho entrepreneurs” (GE), “reluctant entrepreneurs” (RE), and consumption borrowers. The bulk of positive business impacts concentrated among GEs; REs and consumption borrowers saw no significant credit impact relative to constrained counterparts.
- Policy implication: benefits from micro credit are primarily on the intensive margin (helping existing businesses) rather than on the extensive margin (creating many successful new entrepreneurs). Policy should prioritize alleviating constraints on existing businesses rather than broadly promoting new entrepreneurship.

### Benefits from payments services and mobile money
- Shifting cash payments into bank accounts lowers transaction costs, speeds payments, and can improve transparency and reduce corruption (examples: South Africa smart card, Argentina Jefes Program).
- Payment histories built via accounts can improve credit access (example: adding utility payment data in the U.S. increased number of adults with calculable credit scores).
- M-PESA findings:
  - Two studies comparing M-PESA users vs non-users when facing negative shocks show M-PESA users are less prone to cutting consumption and receive more diverse and larger transfers from networks.
  - M-PESA adoption in 2007 can explain 10 percent of per capita income growth between 2007 and 2013 (Beck et al. calibration to Kenyan firm-level survey data).
  - Suri and Jack (2016) find M-PESA helped lift 2 percent of Kenyans out of poverty by reducing transaction costs and enhancing consumption smoothing.
- Paytm evidence (India): district-level adoption associated with greater resilience of economic activity and household consumption to adverse rainfall shocks; firm-level adoption associated with greater sales.
- COVID-19: mobile money adoption accelerated as individuals shifted away from cash to reduce contagion risk; lowering barriers to opening mobile money accounts aided adoption and facilitated faster, safer social protection delivery.
- Mobile-banking-to-credit extensions: M-Shwari expanded access to credit and improved household resilience to income shocks but had no measurable effects on investments and savings (Bharadwaj, Jack, and Suri, 2019).

### Household financial inclusion: scale, patterns, and barriers
- Magnitude and composition:
  - Some 1.7 billion adults excluded from financial services worldwide.
  - Half of the 1.7 billion unbanked live in seven developing economies: Bangladesh, China, India, Indonesia, Mexico, Nigeria and Pakistan.
  - Fifty-six percent of all unbanked are women.
  - Half of unbanked adults come from the poorest 40 percent of households.
- Access vs use:
  - Global Findex 2017: reported 69 percent banked worldwide; adjusted for inactive accounts this becomes 55 percent worldwide and 48 percent for developing countries.
  - Nearly 750 million people worldwide have accounts that they have not used in a year (majority in India and China).
  - In India, three quarters of the 222 million accounts opened remain inactive (post government effort).
- Reasons for not having an account (Global Findex seven reasons, ranked): lack of money; a family member has an account; opening an account is costly; banks are too far away; respondent lacks proper documentation; little trust in financial institutions; religious reasons.
- Specific numeric impacts of government-payment-driven account openings:
  - Roughly 90 million adults opened their first bank account to collect public sector wages.
  - 140 million to receive government transfers.
  - 120 million to receive public sector pensions.
  - 200 million to collect private sector wages.
  - About 100 million unbanked adults still receive government payments in cash; 230 million adults still receive private sector wages in cash.
- Digital penetration and infrastructure:
  - Digital penetration rate (percentage of population that use the internet) is 51 percent in 2019 (Statista, 2019).
- Documentation and KYC: 18 percent of Global Findex respondents cite documentation requirements as a reason for not having an account; some countries simplified KYC to expand inclusion (examples noted: Brazil basic accounts, India “Aadhar” biometric ID).

### Policies and instruments to enhance household financial inclusion
- Supply- and demand-side measures with evidence of effectiveness:
  - Require banks to offer free or basic accounts with low/no fees and low minimum balances (example: India’s “Basic Savings Bank Deposit Accounts”: no minimum balance, provided a debit card, allowed four free withdrawals per month).
  - Make government payments via bank accounts to expand access (evidence: large numbers of first-time account openings tied to government payments).
  - Improve physical access: branch expansion, agent banking/correspondent models (examples: Reserve Bank of India branch requirement; Brazil’s Banco Postal and agent networks; Brazil opened 10 million postal saving accounts between 2002 and 2011; Brazil’s agent network opened 6.5 million new accounts).
  - Credit reporting systems and credit bureaus improve screening, increase loan sizes, and can expand access to commercial bank loans under favorable conditions (examples: Guatemala microfinance lender; Rwanda microcredit program coupled with credit bureau).
  - Encourage a risk-based approach to AML/CFT so KYC requirements are proportionate and do not unduly exclude low-value account users.
  - Invest in digital infrastructure and conducive regulation for fintech and mobile money adoption (internet/mobile availability, governance quality, lower bank concentration, consumer-friendly environment).
- Caveats:
  - Many accounts opened remain inactive; account ownership does not imply use.
  - Mobile money successes (e.g., Kenya) depend on enabling regulation, agent networks, reliable electricity and mobile networks, and functioning payment systems.

### Financial education and capability: evidence and design lessons
- Distinction:
  - Financial literacy = understanding basic financial information and concepts.
  - Financial capability = knowledge, skills, attitudes, and behaviors enabling sound financial decisions.
- Survey evidence:
  - Lusardi and Mitchell survey (initial U.S. results): only 30 percent answered all three core questions correctly; less than half answered the risk diversification question correctly.
- Effectiveness of interventions:
  - Meta-analyses conclude interventions increase knowledge but have mixed results on behavior change; other studies find positive behavioral impacts depending on design.
- Design features that increase effectiveness:
  - Target less literate groups (women, youth, elderly, poor, lower education).
  - Leverage social networks and peer effects.
  - Tailor interventions to participants’ needs and teachable moments.
  - Adapt delivery channels (courses, workshops, counseling, online, radio, television, entertainment formats).
  - Simplify content and teach rules of thumb rather than complex calculations.

### Financial inclusion of MSMEs: scope, constraints, and policy options
- Scale and importance:
  - MSMEs comprise over 95 percent of firms worldwide.
  - In low and middle income countries more than 50 percent of workers are in companies with fewer than 100 employees.
- Heterogeneity among MSMEs:
  - Distinction between micro, small and medium firms implies different financing needs and appropriate providers (microfinance vs bank finance vs venture capital).
  - Distinction between subsistence and transformational entrepreneurs:
    - De Mel, McKenzie, and Woodruff (Sri Lanka): only 30 percent of microenterprise owners resemble large firm owners; 70 percent resemble wage workers.
    - Bruhn (Mexico): about 50 percent of micro-entrepreneurs similar to wage workers.
  - Policy implication: focus financial sector policies on transformational enterprises if objective is long-term aggregate growth and job creation; target vulnerable populations with non-credit policies.
- Constraints limiting MSME finance:
  - High fixed transaction costs for credit assessment, processing, monitoring -> economies of scale favor larger loans.
  - Severe information asymmetries: lack of audited financial statements, limited collateral.
  - Three types of limitations: voluntary exclusion (demand-side), supply-side constraints (regulatory distortions, lack of competition), and institutional deficiencies (absence of credit information sharing, ineffective collateral registration).
- Channels through which financial deepening affects firms/economy:
  - External finance associated with more start-ups, firm dynamism, innovation, higher survival rates, and lower informality.
  - Finance enables existing firms to exploit growth opportunities and achieve larger equilibrium size.
  - Finance allows firms to choose more efficient asset portfolios and organizational forms (incorporation).
- Policy instruments for MSME inclusion:
  - Financial capability programs and targeted financial literacy RCTs for entrepreneurs (tailored interventions can affect entrepreneurship/business expansion under certain conditions).
  - Relax regulatory constraints and entry barriers: simplify documentation, tax treatment (e.g., VAT on leasing), proportionate AML/CFT.
  - Institutional reforms: macroeconomic stability, collateral registries (including movable assets), legal sector reforms, accounting and auditing standards, credit registries and bureaus.
  - Market interventions: partial credit guarantee (PCG) schemes can overcome opacity and lack of collateral but require careful pricing, funding, institutional structure, and cost-benefit analysis focused on additionality. Evidence on PCGs mixed; some schemes show positive additional lending and sales/profit growth, others indicate beneficiaries often already had bank loans.
  - Promote competition and private-sector solutions with attention to country institutional context: competition and foreign ownership can ease constraints where institutional prerequisites (collateral, credit registries) exist.
  - Transaction-based techniques (leasing, factoring) can expand MSME access since they rely less on firm reputation and more on asset cash-flows or buyer creditworthiness; legal frameworks are important for these techniques.

### Conclusions and research/policy priorities
- Financial inclusion has expanded markedly but with persistent regional, income, and gender gaps; use often lags access.
- The DNJTU framework identifies three frictions constraining credit: credit access (entry cost), collateral requirements, and efficiency (intermediation inefficiency); reducing these frictions yields gains in simulations.
- Policy design should:
  - Diagnose the most binding frictions for the targeted form of inclusion and choose cost-effective remedies rather than mechanically targeting a numeric inclusion rate.
  - Consider tradeoffs: financial inclusion vs fiscal costs (e.g., contingent liabilities from PCGs) and financial inclusion vs financial stability (credit expansions under weak supervision can raise systemic risk).
- Research needs:
  - More empirical work on additionality and full cost-benefit analysis of inclusion policies (PCGs highlighted as needing better cost measurement).
  - Theoretical models that incorporate financial stability effects to understand mechanisms where greater credit access may lead to undesirable outcomes ("too much finance" in an inclusion context).
  - Further empirical investigation of credit accelerations and financial distress to inform inclusion-stability tradeoffs.

*Source: wpiea2020157-print-pdf - 6.7 percent of firms having access to credit, it would seem that in Pakistan the entry cost*

### References

### References (wpiea2020157-print-pdf)

### Major cited works and themes
- Extensive literature on financial inclusion, microfinance, fintech, remittances, financial development, and financial stability, including working papers, journal articles, IMF and World Bank staff notes, and policy research papers.
- Recurring authors and institutions:
  - Authors: Agarwal; Aggarwal/Aggarwal; Ahamed; Allen; Banerjee; Barajas; Beck; Demirguc-Kunt; Dabla-Norris; Sahay; Suri; Duflo; Lusardi; Buera; Townsend; and others.
  - Institutions: World Bank; International Monetary Fund (IMF); National Bureau of Economic Research (NBER); Journal outlets (Journal of Finance, American Economic Review, Journal of Development Economics, Review of Financial Studies, World Development, Journal of Financial Economics); GSMA; Center for Financial Inclusion.
- Topics emphasized across references:
  - Financial inclusion measurement and drivers (Global Findex Database, Financial Access Survey).
  - Mobile money and digital financial services (M-PESA, fintech).
  - Microfinance and credit access evaluations (randomized evaluations, credit constraints).
  - Links between finance, growth, inequality, and stability (Finance and Growth literature; “Too Much Finance”; financial depth metrics).
  - Financial literacy and financial education impacts.
  - Policy frameworks and structural conditions for increasing access (postal networks, collateral registries, credit information sharing, partial credit guarantee funds).
  - Regional and country studies (Asia-Pacific, Middle East and Central Asia, Sub-Saharan Africa, Pacific Island Countries).

### Selected reference entries (verbatim examples)
- Agarwal, S., S. Alok, P.  Ghosh, S. Ghosh, T. Piskorski, and A. Seru. 2017. Banking the unbanked: What Do 255 Million New Bank Accounts Reveal About Financial Access? Georgetown University Working Paper.
- Agarwal, T. K., C. Minoiu, A. F. Presbitero, and A. F. Silva. 2018. “Financial Inclusion Under the Microscope”, IMF Working Paper 18/208.
- Ben Naceur, S., R. Chami, and M. Trabelsi. 2020. “Do Remittances Enhance Financial Inclusion in LMICs and in Fragile States?” IMF Working Paper 20/66. International Monetary Fund: Washington, DC.
- Demirguc-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess, 2018, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution (Washington, DC: World Bank Group).
- Sahay, Ratna, Martin Cihak, Papa N’Diaye, Adolfo Barajas, Srobona Mitra, Annette Kyobe, Yen Mooi, and Reza Yousefi. 2015a. “Financial Inclusion: Can it Meet Multiple Macroeconomic Goals?”, Staff Discussion Note 15/17 (Washington, DC: International Monetary Fund).
- Suri, T. 2017, “Mobile Money,” Annual Review of Economics, 9, pp. 497-520.
- World Bank, 2014, Global Financial Development Report: Financial Inclusion (Washington, DC: World Bank Group).

### Figures (captions, sources, and notes)
- Figure 1: Household Financial Inclusion
  - Source: World Bank, Global Findex Database.
- Figure 2. Mobile Money and Accounts in Financial Institutions
  - Source: World Bank, Global Findex Database.
  - World Averages, Changes 2011-17 (Percentage of the adult population)
    - Years listed: 2011, 2014, 2017
  - Regional Differences, 2017 (Percentage of the adult population)
    - Account holding
    - Borrowing from a financial institution
    - Borrowing from a financial institution or used a credit card
    - Mobile money account
  - Mobile Money and Accounts in Financial Institutions (percentage of adults)
    - Countries shown include: Kenya, Singapore, Namibia, Chad
- Figure 3. Financial Inclusion and Real GDP Per Capita—Cross-Country Correlation
  - Sources: World Global Findex and Enterprise Surveys, IMF Financial Access Survey.
- Figure 4. Stylized Financial Possibility Frontier
  - Source: Adapted from Barajas, Beck, Dabla-Norris, and Yousefi (2013)
  - Financial Inclusion indicators listed (no numeric values in caption): Account at a formal financial institution; Adults with account at a formal financial institution, or mobile money; Adults borrowed any money in the past year; Firms with a bank loan or line of credit; Firms not identifying access to finance as a major constraint; Bank accounts per 1,000 adults; Bank branches per 100,000 adults; ATMs per 100,000 adults.
- Figure 5. Mobile Money and Financial Inclusion
  - Source: World Bank Global Financial Development Database and authors' calculations
  - Scatter plots correlate Account holding by individuals (Percentage of adults, 2017) with GDP per capita (Constant 2005 USD)
  - Countries listed in two panels include: Tanzania, Uganda, Luxembourg, Switzerland, Ireland, Norway, Namibia, Kenya, Zambia, Zimbabwe, U.S.
- Figure 6: Financial Inclusion Observed Levels Compared to Structural Benchmarks
  - A. India — Percent of Adults with an account at a Formal Institution (%) and Percent of Firms With Line of Credit, All Firms (%)
  - B. Colombia — Percent of Adults with an account at a Formal Institution (%) and Percent of Firms With Line of Credit, All Firms (%)
  - Sources: World Bank Finstats Database.
- Figure 7. Financial Inclusion and Financial Depth
  - Sources: World Bank Global Findex, Enterprise Surveys, IMF Financial Access Survey and authors' calculations.
  - Panels include:
    - Borrowing by individuals vs Credit to the Private Sector by Banks and Other Financial Institutions/GDP, 2017 (Percent). Countries shown include Israel, Bosnia & Herzegovina, Hungary, Morocco, Ireland, Kenya, El Salvador.
    - Borrowing by firms vs Credit to the Private Sector by Banks and Other Financial Institutions/GDP (Percent). Countries shown include Latvia, Slovenia, Cambodia, Peru, Bosnia & Herzegovina, Moldova.
    - Availability of ATMs (ATMs per 100,000 adults, 2017) vs Credit to the Private Sector by Banks and Other Financial Institutions/GDP, 2017 (Percent). Countries shown include The Bahamas, Kazakhstan, Cambodia, Austria, Libya, India.
- Figure 8. Estimated Impact of Increases in Financial Inclusion and Financial Depth on Economic Growth
  - Sources: Adapted from Sahay and others, 2015.
  - Note (verbatim): "The graph on the left shows that, for a country with a private credit-to-GDP ratio (“privy”) at the 25th percentile, an increase in the availability of ATMs from the 25th to the 75th percentile is associated with an increase in average economic growth of 3 percentage points. When the private credit-to-GDP ratio is at the 75th percentile, the effect of a similar increase in ATMs yields considerably less additional growth, about 2 percentage points. The graph on the right shows a similar relationship between the percentage of firms not identifying access to credit as a major obstacle and the private credit-to-GDP ratio."
- Figure 9. Finance and Occupational Choice in the DNJTU (2015) Model
  - Sources: Dabla-Norris, Ji, Townsend, and Unsal (2015).
  - Financial Inclusion Indicator = ATMs per 100,000 adults
  - Financial Inclusion Indicator = Percent of firms not Identifying access to finance as a major constraint
- Figure 10. Simulated Effect of Reducing the Financial Inclusion Friction (ψ)
  - Sources: Dabla-Norris, Ji, Townsend, and Unsal (2015).
- Figure 11. Risk Sharing through M-Pesa (Mobile Money) in Kenya
  - Source: Suri (2017).
- Figure 12. Reported Reasons for Not Having a Bank Account
  - Source: Global Findex Database.
- Figure 13. Nearly Half of All Unbanked Live in Just Seven Countries
  - Source: Global Findex Database.
  - Breakdown in caption (Adult without account by economy (percent), 2017):
    - Bangladesh
    - China 13%
    - India 11%
    - Pakistan 6%
    - Mexico 3%
    - Rest of the world 54%
- Figure 14. Financial Literacy Around the World
  - Source: S&P Global FinLit Survey.
  - Note (verbatim): "A person is defined as financially literate when he or she correctly answers at least three out of the four financial concepts described in https://gflec.org/sp-global-finlit-survey-methodology/"

*Source: wpiea2020157-print-pdf - References (wpiea2020157-print-pdf)*

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