## 1. Nigeria: Poverty Headcount, 2012/13

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---

### Introduction
- Poverty in Nigeria remains high despite non-oil- and consumption-led growth.
- Poverty rate: 35.2 percent in 2009/10; 33.1 percent in 2012/2013.
- South West region exhibited the lowest poverty rate (around 16 percent).
- North East region had a poverty rate over 50 percent.
- Vulnerability to poverty remains high; minimal shocks can push households below the poverty line.
- Greater financial inclusion could help buffer the impact of unexpected adverse shocks on household consumption and micro-household businesses.
- Government instruments: sector-specific development banks, microcredit institutions, and government credit enhancement schemes for MSMEs; informal risk management channels (social network, family and membership institutions) are also prevalent.

### Data and Empirical Approach
- Data source: Nigerian General Household Survey (GHS) panel survey.
  - GHS Panel: 5,000 households, visited twice in a year (post-planting visit in August-October and post-harvest visit in February-April).
  - Two survey rounds: 2010-11 and 2012-13.
  - GHS-Panel covers all 36 states plus the FCT (Abuja); representative at national and zonal (rural/urban) levels.
- Key variable definitions (as used in analysis):
  - Formal borrowing: borrowing from a bank within the past six months.
  - Informal borrowing: borrowing from an informal group (ROSCAs, money lender, friends, or family) in the past six months.
  - Semi-formal borrowing: borrowing from a cooperative, savings association, or microfinance institution in the past six months.
  - Formal saving: used a bank to save in the past six months.
  - Informal saving: used an informal group to save in the past six months.
  - Semi-formal saving: used a cooperative, savings association, or microfinance institution to save in the past six months.
  - Formal financial access: engaged in formal borrowing or formal saving, or reports having a bank account or indirect access via a family member/close friend.
  - Informal financial access: either informal borrowing or informal saving.
  - Semi-formal financial access: either semiformal borrowing or semi-formal saving.
  - Household consumption: annualized consumption of food and non-food goods, averaged across post-planting and post-harvest surveys to control for seasonality.
  - Household net worth: total value of reported household assets plus reported value of housing (excluding agricultural or entrepreneurial assets).
- Empirical strategy:
  - Reduced-form difference-in-difference panel specification with household fixed effects and location-time fixed effects.
  - Dependent variable: log monthly per capita consumption (annualized for reporting).
  - Main parameters: β (impact of negative shock on those who do not use given source of finance), γ (effect of finance on consumption conditional on not experiencing a shock), δ (impact of financial access on consumption smoothing; interaction Shock∙FinUse).
  - Controls: household size, years of education, age of household head, household net worth, household occupation, remittance receipt; interactions of shock with controls included.
  - Identification relies on shocks being exogenous (survey designed to pick up unexpected shocks).

### Key Findings — Summary
- Consumption smoothing and financial access:
  - Households with some financial access are better able to smooth consumption when hit with a negative income shock than those without.
  - Those with financial access who experience an unexpected negative income shock see consumption fall by 15 percentage points less than those without access.
  - Informal financial access is the main driver of the consumption-smoothing result.
  - Household savings, in particular via informal institutions, account for the consumption-smoothing benefit more than borrowing.
- Regional heterogeneity:
  - Improved financial access delivered uneven consumption-smoothing benefits across regions.
  - Access to semi-formal financial institutions was more effective in smoothing negative shocks in the South than in the North.
  - Informal borrowing was more effective than savings in absorbing shocks in the North East.
  - Financial access does not seem to affect consumption smoothing in the North East in some specifications.
- Mechanisms and interpretation:
  - Informal networks provide important, but incomplete and limited-scale, risk sharing—more effective for household-specific shocks than for community-wide shocks.
  - Prominence of savings over borrowing suggests borrowing constraints and the importance of accumulated buffer stocks.
  - Measurement issues: transfers among friends and family may be recorded as reciprocity rather than borrowing, potentially understating informal borrowing.

### Key empirical results (selected coefficients and statistics preserved exactly)
- Aggregate regression results (Table 5, Panel regression; dependent variable: Log Household Consumption (Annualized)):
  - Negative Shock coefficient (All, Column 1): -0.341 (standard error 0.165).
  - Financial Access coefficient (All, Column 1): 0.016 (standard error 0.037).
  - Neg. Shock * Fin. Access interaction (All, Column 1): 0.146 (standard error 0.053).
- Informal vs formal/semi-formal channels:
  - Neg. Shock * Informal interaction (example): 0.174 (standard error 0.056).
  - Informal borrowing interaction significance: coefficient smaller and significant at the 10 percent level (example reported in Column 7).
  - Savings channels: informal saving interaction strong in Columns 9 and 11 (households reporting saving via any means and specifically via informal institutions are much better able to smooth consumption).
- Selected regional empirical highlights (coefficients and significance preserved exactly where reported):
  - North West: Neg. Shock * Fin. Access: 0.304 (0.120)**; other variants: 0.294 (0.146)**; 0.286 (0.118)**.
  - North East: Financial Access: 0.138 (0.064)**; Neg. Shock * Fin. Access: -0.068 (0.094); other variants show negative interaction coefficients including -0.242 (0.119)** and -0.888 (0.259)*** in some specifications.
  - South East: Neg. Shock * Fin. Access: 0.210 (0.100)**; 0.230 (0.096)**; 0.229 (0.089)***.
  - South South: Neg. Shock * Fin. Access: 0.340 (0.205)* (example of semi-formal impact).
  - South West: Financial Access large negative coefficient in some specifications: -1.882 (0.561)***; -1.143 (0.152)*** reported in other columns.
- Sample and summary statistics (Wave 1, Table 3 — exact figures):
  - Household Consumption (1,000 Naira): All 343; Formal 516; Informal 366; Semi-formal 502; No Access 230.
  - Household Net Worth (million Naira): All 1.7; Formal 3.8; Informal 1.5; Semi-formal 2.6; No Access 0.9.
  - Household Size: All 5.5; Formal 5.5; Informal 5.8; Semi-formal 5.6; No Access 5.2.
  - Distance to Nearest Bank (hours): All 0.83; Formal 0.62; Informal 0.81; Semi-formal 0.66; No Access 0.94.
  - Negative Shock in Current or Previous Year (dummy): All 0.18; Formal 0.18; Informal 0.19; Semi-formal 0.14; No Access 0.18.
  - Number of Observations: All 4,961; Formal 1,626; Informal 2,386; Semi-formal 418; No Access 1,742.

### Financial inclusion: background and key indicators (selected exact figures)
- Account ownership and usage:
  - World Bank Findex survey (2011): about 30 percent of adult population had an account in the formal banking system.
  - EFInA Access to Financial Services in Nigeria 2014: 36 percent (2014).
  - Comparators: World average 50 percent; South Africa 54 percent; Kenya 42 percent; developing countries in SSA average 24 percent.
- Saving behavior:
  - About 65 percent of adult population saves in Nigeria.
  - Comparators: world average 36 percent; Kenya 40 percent; Ghana 37 percent; South Africa 31 percent.
  - Informal saving via ROSCAs: 45 percent.
  - GHS 2012-13 (22,000 households): 18 percent of respondents used informal means to save money within the past 6 months.
- Credit access:
  - Findex (2011): only 2 percent of adult population obtained loans from a financial institution in the past year (world average 9 percent; Kenya and South Africa 9 percent).
  - 2010 Enterprise Surveys: about 14 percent of enterprises had either line of credit or loans (2008).
  - Working capital financing: about 70 percent from internal funds/retained earnings; close to 30 percent from credit from suppliers.
- Microfinance and regulatory context:
  - Microfinance Policy, Regulatory and Supervisory Framework developed by the Central Bank in 2005.
  - Legacy community bank relicensing under NGN 20 million minimum capital requirements.
  - GHS shows MFBs have not played a major role in taking deposits or providing credit to survey respondents.
- National Financial Inclusion Strategy (Central Bank of Nigeria, 2012) targets:
  - Reduce exclusion rate from 46.3 percent of adult population in 2010 to 20 percent by 2020.
  - Access to credit to reach 40 percent of adult population.
  - Identified barriers: (i) income, (ii) physical access, (iii) financial literacy, (iv) affordability, and (v) eligibility.
  - Major elements: simplified risk-based tiered KYC; improved agent banking regulation; financial literacy framework; consumer protection framework; enhancing mobile-payment systems and cash-less policies; credit enhancement schemes for MSMEs.
- Financial architecture gaps (World Bank findings): lack of functioning personal identification system; costly verification/official documentation; limited credit bureau data quality and scope; difficulty enforcing contracts and collateral with long judicial delays. Suggested reforms include enforcing data submission to credit bureaus; establishing registries for movable collateral and laws regulating secured transactions.

### Policy-relevant observations and recommendations
- Strengthen financial inclusion across both formal and informal channels to improve households' ability to smooth consumption in response to shocks.
- Policy design should account for zone-specific effectiveness:
  - Semi-formal institutions appear more effective in the South.
  - Informal credit mechanisms can be particularly important in the North East.
- Formal/semi-formal finance:
  - Improved access to formal (banks) or semi-formal (cooperatives, savings associations, MFIs) institutions has not yet delivered consumption-smoothing benefits.
  - Policy focus: address lack of capacity and capital in these institutions; better understand and address the disconnect between access (ownership/indirect access) and usage.
- Informal networks and social safety nets:
  - Informal networks play a key role but provide incomplete insurance and are limited in scale.
  - Further research needed to identify when, where, and for which shocks informal networks help families in need.
  - Consider whether public sector safety nets can complement informal mechanisms without crowding them out.
- Regional targeting:
  - Financial inclusion efforts could benefit from regional focus to address region-specific needs and bottlenecks and to boost poverty alleviation efforts.

### Annex highlights — Global Findex (selected exact figures)
- Debit card (% age 15+): Nigeria 18.56; Low income 7.35; SSA (developing only) 15.46; World 30.40.
- Account at a formal financial institution (% age 15+): Nigeria 29.67; Low income 23.68; SSA (developing only) 24.03; World 50.49.
- Saved any money in the past year (% age 15+): Nigeria 64.39; Low income 29.94; SSA (developing only) 40.21; World 35.90.
- Saved using a savings club in the past year (% age 15+): Nigeria 44.48; Low income 8.27; SSA (developing only) 19.25; World 5.29.
- Loan in the past year (% age 15+): Nigeria 48.28; Low income 44.11; SSA (developing only) 46.76; World 33.80.
- Loan from a financial institution in the past year (% age 15+): Nigeria 2.06; Low income 11.39; SSA (developing only) 4.76; World 9.05.
- Loan from family or friends in the past year (% age 15+): Nigeria 44.08; Low income 30.30; SSA (developing only) 39.94; World 22.74.
- Mobile phone used to receive money (% age 15+): Nigeria 11.16; Low income 9.11; SSA (developing only) 14.56; World 3.04.
- Saved for emergencies in the past year (% age 15+): Nigeria 57.17; Low income 22.80; SSA (developing only) 31.32; World 27.22.

*Source: IMF staff summary of chapter "1. Nigeria: Poverty Headcount, 2012/13" from the provided PDF content.*

### 1. Nigeria: Poverty Headcount, 2012/13 __________________________________________4

### 1. Nigeria: Poverty Headcount, 2012/13 __________________________________________4

### Introduction
- Poverty in Nigeria remains high despite non-oil- and consumption-led growth.
- Estimates suggest the poverty rate declined slightly from 35.2 percent in 2009/10 to 33.1 percent in 2012/2013, but with significant variation across states.
- Vulnerability to poverty remains high, implying that a minimal shock could easily push those living a little above the poverty line back into poverty.
- Greater financial inclusion could help poverty alleviation efforts by buffering the impact of unexpected adverse shocks on household consumption and micro-household businesses.
- The government has sector-specific development banks, microcredit institutions, and several government credit enhancement schemes programs to empower micro-, small- and medium-sized enterprises (MSMEs). Informal risk management channels (social network, family and membership institutions) are also prevalent.

### Data and Empirical Approach
- Data source: Nigerian General Household Survey (GHS), a panel survey that collects detailed consumption measures and includes information on adverse shocks faced.
- Empirical strategy: panel difference-in-difference specification with household fixed effects to compare changes in the response of consumption to shocks for households with some access to finance (formal and informal) and those without, both nationally and by region (zones).
- The GHS collects detailed information on credit and savings from:
  - formal institutions (banks),
  - informal institutions (access to an informal group, money lender, friends, or family),
  - semi-formal institutions (cooperative, savings associations, or microfinance institutions), allowing distinction between their impacts on risk sharing.

### Key Findings
- National-level poverty and regional variation:
  - Poverty rate: 35.2 percent in 2009/10; 33.1 percent in 2012/2013.
  - South West region exhibited the lowest poverty rate (around 16 percent).
  - North East region had a poverty rate over 50 percent.
- Consumption smoothing and financial access:
  - Households with some financial access are better able to smooth consumption than those without.
  - Households with financial access who experience an unexpected negative income shock see consumption fall by 15 percentage points less than those without access.
  - This result is mainly driven by households with informal financial access.
  - It is household savings, in particular via informal institutions, rather than borrowing that accounts for this result.
- Regional heterogeneity in effectiveness:
  - Improved financial access in recent years has delivered uneven consumption smoothing benefits across regions.
  - Access to semi-formal financial institutions was more effective in smoothing negative shocks in the South than in the North.
  - Informal borrowing was more effective than savings in absorbing shocks in the North East.

### Policy-relevant observations
- Strengthening financial inclusion — both formal and informal channels — can play a role in poverty alleviation by improving households' ability to smooth consumption in response to shocks.
- The effectiveness of interventions may be zone-specific:
  - Semi-formal institutions appear more effective in the South.
  - Informal credit mechanisms can be particularly important in the North East.
- Policies should consider the prominent role of informal savings mechanisms in consumption smoothing when designing credit and savings programs for vulnerable households.

*Source: IMF staff summary of chapter "1. Nigeria: Poverty Headcount, 2012/13" from the provided PDF content.*

### Section V concludes.

### _wp15169 - Section V concludes.

### Financial inclusion: background and key indicators
- Account ownership and usage
  - World Bank Findex survey (2011): about 30 percent of adult population had an account in the formal banking system.
  - EFInA Access to Financial Services in Nigeria 2014: 36 percent (2014).
  - Comparators: World average 50 percent; South Africa 54 percent; Kenya 42 percent; developing countries in SSA average 24 percent.
- Saving behavior
  - About 65 percent of adult population saves in Nigeria.
  - Comparators: world average 36 percent; Kenya 40 percent; Ghana 37 percent; South Africa 31 percent.
  - Informal saving via ROSCAs especially high at 45 percent.
  - GHS 2012-13 (22,000 households): 18 percent of respondents used informal means to save money within the past 6 months.
- Credit access
  - Findex (2011): only 2 percent of adult population obtained loans from a financial institution in the past year (world average 9 percent; Kenya and South Africa 9 percent).
  - 2010 Enterprise Surveys: about 14 percent of enterprises had either line of credit or loans (2008).
  - Working capital financing: about 70 percent from internal funds/retained earnings; close to 30 percent from credit from suppliers.
- Microfinance and regulatory context
  - Microfinance Policy, Regulatory and Supervisory Framework developed by the Central Bank in 2005.
  - Legacy community bank relicensing under NGN 20 million minimum capital requirements.
  - GHS shows MFBs have not played a major role in taking deposits or providing credit to survey respondents.
- National Financial Inclusion Strategy (Central Bank of Nigeria, 2012)
  - Target: reduce exclusion rate from 46.3 percent of adult population in 2010 to 20 percent by 2020.
  - Target: access to credit to reach 40 percent of adult population.
  - Identified barriers: (i) income, (ii) physical access, (iii) financial literacy, (iv) affordability, and (v) eligibility.
  - Major elements: simplified risk-based tiered KYC; improved agent banking regulation; financial literacy framework; consumer protection framework; enhancing mobile-payment systems and cash-less policies; credit enhancement schemes for MSMEs.
- Financial architecture gaps (World Bank findings)
  - Constraints: lack of functioning personal identification system; costly verification/official documentation; limited credit bureau data quality and scope; difficulty enforcing contracts and collateral with long judicial delays.
  - Suggested reforms: enforce data submission to credit bureaus; establish registries for movable collateral and laws regulating secured transactions. Progress has been slow.

### Data, definitions, and empirical approach
- Data source
  - Nigeria GHS Panel data of 5,000 households, visited twice in a year (post-planting visit in August-October and post-harvest visit in February-April) every other year.
  - Two survey rounds: 2010-11 and 2012-13.
  - GHS-Panel covers all 36 states plus the FCT (Abuja); representative at national and zonal (rural/urban) levels.
- Key variable definitions (as used in analysis)
  - Formal borrowing: borrowing from a bank within the past six months.
  - Informal borrowing: borrowing from an informal group (ROSCAs, money lender, friends, or family) in the past six months.
  - Semi-formal borrowing: borrowing from a cooperative, savings association, or microfinance institution in the past six months.
  - Formal saving: used a bank to save in the past six months.
  - Informal saving: used an informal group to save in the past six months.
  - Semi-formal saving: used a cooperative, savings association, or microfinance institution to save in the past six months.
  - Formal financial access: engaged in formal borrowing or formal saving, or reports having a bank account or indirect access via a family member/close friend.
  - Informal financial access: either informal borrowing or informal saving.
  - Semi-formal financial access: either semiformal borrowing or semi-formal saving.
  - Household consumption: annualized consumption of food and non-food goods, averaged across post-planting and post-harvest surveys to control for seasonality.
  - Household net worth: total value of reported household assets plus reported value of housing (excluding agricultural or entrepreneurial assets).
- Sample and summary statistics
  - Many households use multiple channels; informal access is the most important source (about half the sample reported borrowing or saving from an informal source over the past six months).
  - About one-third of households report having access to the formal financial system (mostly due to bank account ownership, not usage).
  - Semiformal access is quite low.
  - Financial access varies by zone: South West ~50 percent access to banks; North West 12 percent access to banks.
  - Summary stats (Wave 1, Table 3)
    - Household Consumption (1,000 Naira): All 343; Formal 516; Informal 366; Semi-formal 502; No Access 230.
    - Household Net Worth (million Naira): All 1.7; Formal 3.8; Informal 1.5; Semi-formal 2.6; No Access 0.9.
    - Household Size: All 5.5; Formal 5.5; Informal 5.8; Semi-formal 5.6; No Access 5.2.
    - Distance to Nearest Bank (hours): All 0.83; Formal 0.62; Informal 0.81; Semi-formal 0.66; No Access 0.94.
    - Negative Shock in Current or Previous Year (dummy): All 0.18; Formal 0.18; Informal 0.19; Semi-formal 0.14; No Access 0.18.
    - Number of Observations: All 4,961; Formal 1,626; Informal 2,386; Semi-formal 418; No Access 1,742.
- Empirical model
  - Reduced-form difference-in-difference panel specification with household fixed effects and location-time fixed effects.
  - Dependent variable: log monthly per capita consumption (annualized for reporting).
  - Main parameters: β (impact of negative shock on those who do not use given source of finance), γ (effect of finance on consumption conditional on not experiencing a shock), δ (impact of financial access on consumption smoothing; interaction Shock∙FinUse).
  - Controls: household size, years of education, age of household head, household net worth, household occupation, remittance receipt; interactions of shock with controls included.
  - Identification relies on shocks being exogenous (survey designed to pick up unexpected shocks).

### Key empirical findings
- Aggregate consumption-smoothing effect
  - Those with some financial access are better able to smooth consumption when hit with a negative income shock than those without.
  - Differential impact: those with financial access who experience a negative income shock see consumption fall by 15 percentage points less than those without access experiencing a shock.
- Regression coefficients (selected from Table 5, Panel regression; dependent variable: Log Household Consumption (Annualized))
  - Negative Shock coefficient (All, Column 1): -0.341 (standard error 0.165) ** (statistical significance indicated in table).
  - Financial Access coefficient (All, Column 1): 0.016 (standard error 0.037).
  - Neg. Shock * Fin. Access interaction (All, Column 1): 0.146 (standard error 0.053) ***.
- Channels and mechanisms
  - Informal financial access drives the consumption-smoothing result:
    - Interaction coefficient for informal access is positive and significant (e.g., Neg. Shock * Informal: 0.174 in Column 3, standard error 0.056) ***.
    - Interaction coefficient for formal and semiformal access is negative and insignificant in some specifications (Columns 2 and 4).
  - Savings matter more than borrowing:
    - Households reporting saving via any means and specifically via informal institutions are much better able to smooth consumption (Columns 9 and 11).
    - Informal borrowing helps with consumption smoothing but coefficient is smaller and significant at the 10 percent level (Column 7).
  - Regional heterogeneity
    - Semi-formal financial access more important in North Central (Column 12), South South (Column 4), and South West (Column 8).
    - Borrowing mechanism more important in South East (Column 7).
    - Financial access does not seem to affect consumption smoothing in the North East.
  - Household characteristics interactions
    - Being an entrepreneur worsens ability to smooth consumption in the North East.
    - Being a farmer cushions consumption smoothing in the North West and South South.
    - In the South South, being a wage earner helps smoothing.
    - In the South East, higher education of household head improves smoothing.
- Interpretation and limits
  - Informal networks are an important risk-sharing mechanism in Nigeria, especially in the North, but their insurance is often incomplete and limited in scale.
  - Informal channels more effective for household-specific shocks than community-wide shocks.
  - The prominence of savings over borrowing suggests borrowing constraints and the importance of accumulating buffer stocks.
  - Measurement issues: transfers among friends and family may be viewed as reciprocity rather than borrowing, potentially understating informal borrowing.

### Policy implications and recommendations
- Formal/semi-formal finance
  - Improved access to formal (banks) or semi-formal (cooperatives, savings associations, MFIs) institutions has not yet delivered consumption-smoothing benefits.
  - Policy focus: address lack of capacity and capital in these institutions; better understand and address the disconnect between access (ownership/indirect access) and usage.
- Informal networks and social safety nets
  - Informal networks play a key role but provide incomplete insurance and are limited in scale.
  - Further research needed to identify when, where, and for which shocks informal networks help families in need.
  - Given general ineffectiveness of more formal social safety nets in Nigeria, consider whether public sector safety nets can complement informal mechanisms without crowding them out.
- Regional targeting
  - Financial inclusion efforts could benefit from regional focus to address region-specific needs and bottlenecks.
  - Examples:
    - Semi-formal access was more effective in smoothing negative shocks in the South than in the North.
    - Informal borrowing was more effective than savings in absorbing shocks in North East.
  - A regional approach could boost financial access and aid poverty alleviation efforts.

*Source: _wp15169 - Section V concludes.*

### ANNEX 1: GLOBAL FINDEX (WORLD BANK)

### ANNEX 1: GLOBAL FINDEX (WORLD BANK)

### Formal Accounts
- Debit card (% age 15+): Nigeria 18.56, Low income 7.35, SSA (developing only) 15.46, World 30.40

### Frequency of Access
- 0 deposits in a typical month (% with an account, age 15+): Nigeria 2.80, Low income 8.29, SSA (developing only) 6.27, World 12.82
- 0 deposits/withdrawals in typical month (% with an account, age 15+): Nigeria 2.59, Low income 5.37, SSA (developing only) 3.78, World 7.69
- 0 withdrawals in a typical month (% with an account, age 15+): Nigeria 8.91, Low income 21.10, SSA (developing only) 11.69, World 13.87
- 1-2 deposits in a typical month (% with an account, age 15+): Nigeria 72.95, Low income 64.73, SSA (developing only) 69.52, World 65.37
- 1-2 withdrawals in a typical month (% with an account, age 15+): Nigeria 63.57, Low income 59.25, SSA (developing only) 63.41, World 51.72
- 3+ deposits in a typical month (% with an account, age 15+): Nigeria 23.97, Low income 23.14, SSA (developing only) 21.91, World 16.02
- 3+ withdrawals in a typical month (% with an account, age 15+): Nigeria 27.52, Low income 16.03, SSA (developing only) 22.95, World 27.38

### Mode of Access
- ATM is main mode of deposit (% with an account, age 15+): Nigeria 0.94, Low income 4.37, SSA (developing only) 6.61, World 13.60
- ATM is main mode of withdrawal (% with an account, age 15+): Nigeria 40.82, Low income 22.89, SSA (developing only) 41.82, World 43.25
- Bank agent is main mode of deposit (% with an account, age 15+): Nigeria 1.31, Low income 9.10, SSA (developing only) 2.69, World 3.14
- Bank agent is main mode of withdrawal (% with an account, age 15+): Nigeria 1.02, Low income 5.36, SSA (developing only) 2.47, World 1.87
- Bank teller is main mode of deposit, female (% with an account, age 15+): Nigeria 96.56, Low income 79.95, SSA (developing only) 84.77, World 68.64
- Bank teller is main mode of withdrawal (% with an account, age 15+): Nigeria 58.06, Low income 63.01, SSA (developing only) 49.39, World 47.70
- Retail store is main mode of deposit (% with an account, age 15+): Nigeria 0.32, Low income 1.91, SSA (developing only) 2.74, World 1.13
- Retail store is main mode of withdrawal (% with an account, age 15+): Nigeria 0.10, Low income 1.42, SSA (developing only) 2.50, World 2.00

### Penetration
- Account at a formal financial institution (% age 15+): Nigeria 29.67, Low income 23.68, SSA (developing only) 24.03, World 50.49

### Use of Accounts
- Account used for business purposes (% age 15+): Nigeria 7.45, Low income 4.55, SSA (developing only) 5.29, World 7.92
- Account used to receive government payments (% age 15+): Nigeria 6.30, Low income 2.50, SSA (developing only) 5.67, World 12.88
- Account used to receive remittances (% age 15+): Nigeria 15.70, Low income 4.75, SSA (developing only) 9.10, World 7.23
- Account used to receive wages (% age 15+): Nigeria 11.84, Low income 5.86, SSA (developing only) 9.91, World 20.88
- Account used to send remittances (% age 15+): Nigeria 10.84, Low income 2.78, SSA (developing only) 6.31, World 7.05

### Payments
- Mobile phone used to pay bills (% age 15+): Nigeria 1.38, Low income 2.57, SSA (developing only) 3.00, World 1.99
- Mobile phone used to receive money (% age 15+): Nigeria 11.16, Low income 9.11, SSA (developing only) 14.56, World 3.04
- Mobile phone used to send money (% age 15+): Nigeria 9.92, Low income 7.10, SSA (developing only) 11.18, World 2.16
- Checks used to make payments (% age 15+): Nigeria 4.04, Low income 4.56, SSA (developing only) 3.27, World 9.37
- Electronic payments used to make payments (% age 15+): Nigeria 2.42, Low income 1.94, SSA (developing only) 3.98, World 14.48

### Savings
- Saved any money in the past year (% age 15+): Nigeria 64.39, Low income 29.94, SSA (developing only) 40.21, World 35.90
- Saved at a financial institution in the past year (% age 15+): Nigeria 23.59, Low income 11.48, SSA (developing only) 14.22, World 22.43
- Saved using a savings club in the past year (% age 15+): Nigeria 44.48, Low income 8.27, SSA (developing only) 19.25, World 5.29
- Saved for emergencies in the past year (% age 15+): Nigeria 57.17, Low income 22.80, SSA (developing only) 31.32, World 27.22
- Saved for future expenses in the past year (% age 15+): Nigeria 40.12, Low income 20.36, SSA (developing only) 26.02, World 24.04

### Credit
- Credit card (% age 15+): Nigeria 0.79, Low income 1.86, SSA (developing only) 2.92, World 14.79
- Loan in the past year (% age 15+): Nigeria 48.28, Low income 44.11, SSA (developing only) 46.76, World 33.80
- Outstanding loan for funerals or weddings (% age 15+): Nigeria 2.60, Low income 5.42, SSA (developing only) 4.55, World 2.78
- Outstanding loan for health or emergencies (% age 15+): Nigeria 8.39, Low income 16.06, SSA (developing only) 15.14, World 10.96
- Outstanding loan for home construction (% age 15+): Nigeria 1.70, Low income 6.30, SSA (developing only) 3.44, World 5.00
- Outstanding loan to pay school fees (% age 15+): Nigeria 4.70, Low income 6.99, SSA (developing only) 9.01, World 5.38
- Outstanding loan to purchase a home (% age 15+): Nigeria 0.61, Low income 2.40, SSA (developing only) 2.01, World 7.02
- Loan from a financial institution in the past year (% age 15+): Nigeria 2.06, Low income 11.39, SSA (developing only) 4.76, World 9.05
- Loan from a private lender in the past year (% age 15+): Nigeria 2.43, Low income 6.99, SSA (developing only) 5.41, World 3.44
- Loan from an employer in the past year (% age 15+): Nigeria 2.96, Low income 3.36, SSA (developing only) 4.09, World 3.06
- Loan from family or friends in the past year (% age 15+): Nigeria 44.08, Low income 30.30, SSA (developing only) 39.94, World 22.74
- Loan through store credit in the past year (% age 15+): Nigeria 10.44, Low income 8.43, SSA (developing only) 8.31, World 7.53

### Insurance
- Personally paid for health insurance (% age 15+): Nigeria 0.40, Low income 2.22, SSA (developing only) 3.21, World 17.05
- Purchased agriculture insurance (% working in agriculture, age 15+): Nigeria 2.29, Low income 5.11, SSA (developing only) 9.71, World 6.48

*ANNEX 1: GLOBAL FINDEX (WORLD BANK) — 2011 or Most Recent Value Available*

### ANNEX 2: EMPIRICAL RESULTS BY ZONE

### _wp15169 - ANNEX 2: EMPIRICAL RESULTS BY ZONE

### All Zones (Full Sample)
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors (coefficients with standard errors in parentheses and significance):
  - Negative Shock: -0.341 (0.165)**; columns show values range: -0.225 (0.161), -0.368 (0.164), -0.235 (0.159), -0.276 (0.165)*(0.161), -0.273 (0.164)*(0.160), -0.295 (0.162)*(0.161), -0.289 (0.163)*(0.159)
  - Financial Access: 0.016 (0.037); 0.071 (0.039)*; 0.020 (0.036); 0.125 (0.052)**; 0.021 (0.034); -0.080 (0.278); 0.032 (0.035); 0.138 (0.077)*; 0.053 (0.033); -1.103 (0.132)***; 0.038 (0.035); 0.095 (0.055)*
  - Neg. Shock * Fin. Access: 0.146 (0.053)***; -0.045 (0.070); 0.174 (0.056)***; -0.014 (0.113); 0.086 (0.054); 0.356 (0.331); 0.084 (0.051)*(0.214); 0.133 (0.055)**; 0.689 (0.194)***; 0.135 (0.057)**; 0.097 (0.093)
- Controls highlights:
  - Dummy for 2nd Wave: 0.189 (0.102)* ... 0.183 (0.104)*
  - Dummy for HoH is Enterpreneur: 0.142 (0.054)*** ... 0.139 (0.054)**
  - Neg. Shock * HOH Entrepreneur: -0.178 (0.064)*** ... -0.162 (0.064)**
  - Neg. Shock * HoH Age: 0.004 (0.002)* ... 0.003 (0.002)
- Constant: 12.053 (0.198)*** ... 12.090 (0.197)***
- R-squared: 0.350 0.340 0.350 0.350 0.350 0.340 0.350 0.340 0.350 0.340 0.350 0.350
- Number of Observations: 3,9183,9183,9183,9183,9183,9183,9183,9183,9183,9183,9183,9183,918
- Number with Access: 2,1101,4141,9743801,518151,4351661,57121,405314
- Time Fixed Effects: YYYYYYYYYYYY
- Household Fixed Effects: YYYYYYYYYYYY
- Time-Location Fixed Effects: YYYYYYYYYYYY

### North Central
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors:
  - Negative Shock: -0.109 (0.647); -0.245 (0.543); -0.396 (0.610); -0.396 (0.610); 0.118 (0.645); -0.008 (0.601); -0.026 (0.598); 0.026 (0.641); -0.029 (0.598); -0.010 (0.594); 0.025 (0.615); -0.188 (0.546)
  - Financial Access: 0.105 (0.111); -0.083 (0.105); 0.078 (0.129); 0.078 (0.129); 0.111 (0.100); -0.014 (0.427); 0.127 (0.104); 0.154 (0.166); 0.144 (0.085)*; 0.111 (0.093); 0.107 (0.114)
  - Neg. Shock * Fin. Access: 0.221 (0.238); -0.328 (0.267); 0.506 (0.323); 0.506 (0.323); -0.130 (0.254); 0 (0.288); 0.142 (0.827); -0.229 (0.243)**; 0.479 (0.247); 0.283 (0.288)**; 0.706 (0.?)
- Controls highlights:
  - HoH Education: 0.012 (0.007)* ... 0.009 (0.007)
  - Dummy for HoH is Enterpreneur: 0.412 (0.257) ... 0.429 (0.262)
  - Neg. Shock * HOH Entrepreneur: -0.515 (0.328) ... -0.671 (0.341)**
  - Neg. Shock * Household Size: 0.095 (0.081) ... 0.143 (0.080)*
- Constant: 11.561 (0.198)*** ... 11.174 (0.197)***
- R-squared: 0.330 0.330 0.340 0.340 0.330 0.320 0.330 0.320 0.340 0.320 0.330 0.340
- Number of Observations: 637 repeated
- Number with Access: 39725036279307228936292024870
- Time/Household/Time-Location Fixed Effects: YYYYYYYYYYYY

### North East
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors:
  - Negative Shock: 0.050 (0.297); -0.041 (0.291); 0.016 (0.297); -0.109 (0.284); 0.107 (0.301); -0.035 (0.286); 0.092 (0.302); -0.030 (0.277); -0.051 (0.294); -0.033 (0.285); -0.076 (0.292); -0.088 (0.293)
  - Financial Access: 0.138 (0.064)**; 0.118 (0.093); 0.109 (0.065)*; 0.360 (0.132)***; 0.160 (0.069)**; -0.207 (0.121)*; 0.148 (0.073)**; 0.668 (0.195)***; 0.055 (0.077); -0.021 (0.084); 0.243 (0.156)
  - Neg. Shock * Fin. Access: -0.068 (0.094); -0.242 (0.119)**; -0.005 (0.096); -0.357 (0.254); -0.098 (0.097); -0.081 (0.097); -0.888 (0.259)***; 0.018 (0.101); 0.124 (0.105); -0.281 (0.274)
- Controls highlights:
  - Dummy for 2nd Wave: -0.355 (0.167)** ... -0.300 (0.162)*
  - Dummy for HoH is Enterpreneur: 0.238 (0.086)*** ... 0.247 (0.091)***
  - Neg. Shock * HOH Entrepreneur: -0.337 (0.112)*** ... -0.329 (0.110)***
  - Neg. Shock * HoH Wage Earner: 0.152 (0.105) ... 0.166 (0.106)
- Constant: 12.372 (0.198)*** ... 12.530 (0.197)***
- R-squared: 0.450 0.450 0.450 0.470 0.460 0.440 0.450 0.480 0.450 0.440 0.450 0.450
- Number of Observations: 693 repeated
- Number with Access: 35818234938267126318240022629
- Fixed Effects: YYYYYYYYYYYY

### North West
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors:
  - Negative Shock: -0.665 (0.324)**; -0.309 (0.318); -0.643 (0.322)**; -0.441 (0.310); -0.473 (0.319); -0.421 (0.309); -0.483 (0.320); -0.411 (0.308); -0.501 (0.309); -0.421 (0.309); -0.498 (0.310); -0.441 (0.310)
  - Financial Access: -0.023 (0.076); 0.031 (0.089); -0.003 (0.073); -0.002 (0.186); 0.025 (0.074); 0.000 (0.074); 0.010 (0.228); 0.280 (0.079); 0.049 (0.080); 0.102 (0.254); -0.012 (0.?)
  - Neg. Shock * Fin. Access: 0.304 (0.120)**; 0.294 (0.146)**; 0.286 (0.118)**; -0.202 (0.257); 0.094 (0.117); 0.000 (0.119); 0.107 (0.136)**; 0.000 (0.143)*(0.284)
- Controls highlights:
  - Dummy for 2nd Wave: -0.535 (0.139)*** ... -0.865 (0.248)***
  - Dummy for HoH is Wage Earner: 0.123 (0.073)* ... 0.138 (0.073)*
  - Neg. Shock * HoH Wage Earner: -0.387 (0.125)*** ... -0.394 (0.130)***
  - Neg. Shock * HoH Farmer: 0.315 (0.146)** ... 0.402 (0.143)***
- Constant: 12.369 (0.198)*** ... 12.671 (0.197)***
- R-squared: 0.470 0.460 0.470 0.450 0.450 0.450 0.450 0.450 0.470 0.450 0.470 0.450
- Number of Observations: 860 repeated
- Number with Access: 35015134134298029214214020322
- Fixed Effects: YYYYYYYYYYYY

### South East
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors:
  - Negative Shock: -0.414 (0.483); -0.192 (0.496); -0.456 (0.489); -0.270 (0.493); -0.345 (0.485); -0.230 (0.491); -0.367 (0.486); -0.355 (0.487); -0.386 (0.487); -0.244 (0.485); -0.386 (0.490); -0.244 (0.485)
  - Financial Access: -0.018 (0.063); 0.063 (0.065); -0.015 (0.060); -0.015 (0.085); -0.069 (0.054); 0.557 (0.234)**; -0.069 (0.054); 0.013 (0.153); 0.080 (0.062); 0.000 (0.060); 0.070 (0.101); -0.001 (0.?)
  - Neg. Shock * Fin. Access: 0.210 (0.100)**; 0.113 (0.115); 0.230 (0.096)**; -0.069 (0.161); 0.231 (0.092)**; -0.148 (0.332); 0.229 (0.089)***; -0.354 (0.218); 0.025 (0.104); 0.000 (0.113); 0.045 (0.205); 0.043 (0.?)
- Controls highlights:
  - HoH Education: 0.012 (0.007)* ... 0.013 (0.008)*
  - Neg. Shock * HoH Edu.: 0.016 (0.007)** ... 0.014 (0.007)*
  - Neg. Shock * HOH Entrepreneur: -0.043 (0.109) ... -0.060 (0.109)
- Constant: 11.966 (0.198)*** ... 11.874 (0.197)***
- R-squared: 0.380 0.380 0.380 0.370 0.380 0.380 0.380 0.370 0.380 0.370 0.370 0.370
- Number of Observations: 745 repeated
- Number with Access: 42929240466305429524343030952
- Fixed Effects: YYYYYYYYYYYY

### South South
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors:
  - Negative Shock: -0.451 (0.521); -0.322 (0.541); -0.441 (0.524); -0.249 (0.490); -0.411 (0.537); -0.342 (0.524); -0.364 (0.532); -0.131 (0.504); -0.428 (0.513); -0.297 (0.515); -0.443 (0.505); -0.377 (0.494)
  - Financial Access: -0.045 (0.080); 0.118 (0.093); -0.015 (0.083); 0.115 (0.126); 0.007 (0.086); 0.323 (0.388); 0.052 (0.086); 0.099 (0.237); -0.039 (0.076); 0.000 (0.080); -0.066 (0.140); 0.216 (0.140)
  - Neg. Shock * Fin. Access: 0.149 (0.133); -0.183 (0.190); 0.156 (0.131); 0.340 (0.205)*; 0.139 (0.128); -0.443 (0.464); 0.073 (0.129); 0.443 (0.335); 0.207 (0.140); 0.201 (0.139); 0.268 (0.222)
- Controls highlights:
  - HoH Education: 0.013 (0.006)** ... 0.013 (0.006)**
  - Dummy for HoH is Wage Earner: -0.310 (0.138)** ... -0.318 (0.137)**
  - Neg. Shock * HoH Farmer: 0.418 (0.143)*** ... 0.404 (0.144)***
  - Neg. Shock * HoH Wage Earner: 0.285 (0.149)* ... 0.261 (0.146)
- Constant: 11.796 (0.198)*** ... 11.937 (0.197)***
- R-squared: 0.390 0.390 0.390 0.410 0.390 0.390 0.390 0.400 0.390 0.380 0.390 0.410
- Number of Observations: 607 repeated
- Number with Access: 35331532665220520132277024851
- Fixed Effects: YYYYYYYYYYYY

### South West
- Dependent Variable: Log Household Consumption (Annualized)
- Panel Regression; AccessBorrowSave
- Key regressors:
  - Negative Shock: 1.276 (1.000); -0.262 (0.749); 0.580 (0.898); 0.235 (0.703); -0.247 (0.941); 0.333 (0.683); 0.776 (0.904); 0.086 (0.733); 0.957 (0.893); 0.171 (0.774); 0.705 (0.696); 0.236 (0.701)
  - Financial Access: -0.377 (0.259); 0.168 (0.163); -0.057 (0.181); 0.057 (0.149); -0.185 (0.132); -1.882 (0.561)***; 0.033 (0.111); -0.347 (0.161)**; 0.019 (0.214); -1.143 (0.152)***; 0.041 (0.148); 0.071 (0.125)
  - Neg. Shock * Fin. Access: -0.145 (0.282); -0.090 (0.202); -0.072 (0.274); 0.135 (0.227); 0.073 (0.271); 0 (0.281); -0.251 (0.312)**; 0.626 (0.355); -0.407 (0.433); 0.710 (0.382); -0.400 (0.232); 0.126 (0.232)
- Controls highlights:
  - Dummy for 2nd Wave: -0.849 (0.391)** ... -0.404 (0.389)
  - Neg. Shock * HOH Entrepreneur: 0.578 (0.291)** ... 0.407 (0.311)
  - Neg. Shock * HoH Age: -0.036 (0.014)** ... -0.018 (0.010)*
  - Neg. Shock * HoH Edu.: 0.026 (0.014)* ... 0.014 (0.014)
- Constant: 14.121 (0.198)*** ... 13.451 (0.197)***
- R-squared: 0.570 0.560 0.550 0.550 0.560 0.600 0.550 0.570 0.560 0.580 0.560 0.550
- Number of Observations: 376 repeated
- Number with Access: 2232241929812139542205217190
- Fixed Effects: YYYYYYYYYYYY

*Sources: NBS (2012); NBS (2014); and authors’ estimates.*

### REFERENCES

### _wp15169 - REFERENCES

### Empirical studies on risk-sharing and insurance
- Alem, Mauro, and Robert M. Townsend, 2014, “An Evaluation of Financial Institutions: Impact on Consumption and Investment using Panel Data and the Theory of Risk-Bearing.” Journal of Econometrics, Vol. 183 (1), pp. 91-103.
- Chiappori, P., K. Samphantharak, S. Schulhofer-Wohl, and R. M. Townsend, 2014, “Heterogeneity and Risk Sharing in Village Economies,” Quantitative Economics, Vol. 5, pp 1–27.
- Gertler, P., and J. Gruber, 2002, “Insuring Consumption Against Illness,” American Economic Review, Vol. (1), pp. 51–70.
- Gertler, P., D. Levine, and E. Moretti, 2006, “Is Social Capital the Capital of the Poor? The Role of Family and Community in Helping Insure Living Standards Against Health Shocks,” CESifo Economic Studies, Vol. 52(3), pp. 455–499.
- Fafchamps, M., and F. Gubert, 2007, “The Formation of Risk-sharing Networks,” Journal of Development Economics, Vol. 83(2), pp. 326–350.
- Kinnan, C., and R. Townsend, 2012, “Kinship and Financial Networks, Formal Financial Access, and Risk Reduction,” American Economic Review, Vol. 102(3), pp. 289–93.
- Jack, W., and T. Suri, 2014, Risk Sharing and Transactions Costs: Evidence from Kenya’s Mobile Money Revolution, American Economic Review, Vol. 104(1), pp. 183–223.
- Suri, T., 2012, “Estimating the Extent of Risk Sharing Between Households,” MIT Sloan Working Paper.
- Townsend, R., 1994, “Risk and Insurance in Village India,” Econometrica, Vol. 62, pp. 539–591.
- Townsend, R., 1995, “Financial Systems in Northern Thai Villages,” Quarterly Journal of Economics, Vol. 110, pp. 1011–1046.
- Udry, C., 1994, “Risk and Insurance in a Rural Credit Market: An Empirical Investigation in Northern Nigeria,” The Review of Economic Studies, Vol. 61(3), pp. 495–526.

### Informal networks, shadow banking, and dynamic poverty
- Sripakdeevong, Parit, and Robert M. Townsend, 2012, “Informal Networks and Shadow Banking,” project document, MIT.
- Molini, Vasco, Gbemisola Oseni, and Paul Corral, 2014, “No condition is permanent: The dynamic story of poverty and the emerging middle class in Nigeria”.

### Financial inclusion and country reports
- Central Bank of Nigeria, 2012, Financial Inclusion Strategy.
- World Bank, 2014, Nigeria Economic Report.

*Source: _wp15169 - REFERENCES*

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