## 3. The Informal Economy in Sub-Saharan Africa

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---

### Methodology and Estimation Approach
- Parametric model: Multiple Indicator–Multiple Cause (MIMIC) Model fitted by maximum likelihood.
- MIMIC model sample: 140 countries during 1991–2014.
- Model refinements:
  - Use night lights as a measure of the size of the economy to address endogeneity.
  - Starting value for annual series set to 2000 and taken from Schneider (2007) using a currency demand model.
- Observable drivers (causes) included:
  - Tax burden.
  - Institutional development (rule of law and governance).
  - Official unemployment rate.
  - Trade openness.
- Indicators (effects) included:
  - Currency as a fraction of broad money (M0/M1).
  - Labor force participation.
  - Size of the economy proxied by night lights.

### Size, Heterogeneity, and Trends
- Country-level range in sub-Saharan Africa (average over 2010–14):
  - Lowest: Between 20–25 percent of GDP in Mauritius, South Africa, and Namibia.
  - Highest: Between 50–65 percent of GDP in Tanzania and Nigeria.
- Regional and comparative estimates (share of informality):
  - Sub-Saharan Africa unweighted average: almost 38 percent of GDP during 2010–14.
  - Latin America and the Caribbean: 40 percent of GDP.
  - South Asia: 34 percent of GDP.
  - Europe: 23 percent of GDP.
  - OECD members: 17 percent of GDP.
- By income/type within sub-Saharan Africa:
  - Low-income countries: 40 percent of GDP.
  - Middle-income countries: 35 percent of GDP.
  - Oil exporters: close to 50 percent of GDP.
- Time trend: the share of informality in sub-Saharan Africa has been very gradually declining.

### Drivers and Correlates of Informality
- Income:
  - Informality tends to fall with higher income levels (log of GDP per capita inversely related to informality).
- Trade openness:
  - Greater trade openness associated with lower informality (negative slope in regional analysis).
- Institutions and governance:
  - Rule of law and Worldwide Governance Indicators (voice and accountability; political stability and absence of violence; government effectiveness; regulatory quality; control of corruption) are inversely related to informality.
- Entrepreneurship context:
  - Sub-Saharan Africa records the highest rate of total early-stage entrepreneurial activity and nascent entrepreneurship among comparators.
  - About a third of new entrepreneurs in sub-Saharan Africa report necessity as their motivation.
  - Societal attitudes toward entrepreneurship are the most positive among regions surveyed.

### Robustness and Validation of Estimates
- Alternative approach: Predictive Mean Matching (PMM) treating informality as a missing data problem.
  - PMM groupings broadly align with MIMIC findings.
- Comparison with statistical agency estimates:
  - Rank correlation between MIMIC results and national accounts/statistical agency estimates for eight countries: 0.73.
  - Spearman's Rank Correlation: 0.857***.
- Limitations of statistical agency estimates: not all countries publish data; differing methodologies and sampling affect comparability.

### Interaction with Economic Performance and Role as Safety Net
- Informality as employment safety net:
  - ILO surveys report that 30 to 90 percent of employment in the nonagricultural sector occurs in the informal sector in some sub-Saharan African countries.
  - Household survey evidence: between 55 and 75 percent of nonagricultural employment in low-income and resource-rich sub-Saharan African countries occurs in household enterprises.
- Household enterprises improve opportunities relative to agriculture based on household survey consumption/per capita evidence.

### Consumption and Welfare Comparisons
- Consumption levels:
  - Workers in agriculture: on average 60 percent of agricultural workers have consumption levels below the 25th percentile of salaried workers.
  - Household enterprises: consumption below salaried employment at the 50th and 75th percentiles; at the 25th percentile household enterprise consumption is below salaried workers for all sample countries except Rwanda and Uganda (where consumption is similar).
- Sample countries for consumption comparison: Cameroon, Ghana, Mali, Rwanda, Uganda, and Zambia.

### Informality and Productivity
- Productivity of informal firms (real output per employee, PPP terms):
  - Informal firms average 25 percent that of small formal firms.
  - Informal firms average 19 percent that of medium-sized formal firms.
- Large cross-country variation; particularly wide gaps in Kenya, Namibia, Niger, Senegal, Swaziland, and Tanzania.
- Productivity measurement follows Hsieh and Klenow (2009) for 16 sub-Saharan African countries.

### Informality and Firm Size
- Informal firms typically microenterprises with less than five workers.
- Average informal firm size:
  - about 30 percent of the average size of small formal firms.
  - about 7 percent the size of medium-sized formal firms.
- Proportion of small firms:
  - 71 percent in sub-Saharan Africa.
  - 61 percent in economies outside sub-Saharan Africa.
- Subnational analysis across 156 subnational regions groups regions into low-informality (below-average) and high-informality (above-average).

### Informality as a Vicious Cycle
- Obstacles keeping firm size small and informality persistent:
  - Cost of financing and limited access to credit.
  - Small size, low productivity, poor conditions for entrepreneurship.

### Informality and Tax Policy
- Heterogeneity in tax nonpayment:
  - Some firms below legal thresholds; others deliberately evade taxes even if above thresholds.
- Policy suggestions:
  - Raising the VAT threshold may encourage firms just below the threshold to increase production without changing number of informal firms or tax collection.
  - Relatively high VAT thresholds recommended for developing countries, with license fees or turnover taxes for businesses below the VAT threshold.
  - Simplify tax laws and reduce taxes on microenterprises and small businesses.
  - Revenue administrations should develop integrated compliance management strategies:
    - reduce community tolerance for tax evasion;
    - provide targeted assistance to promote voluntary compliance;
    - encourage self-regulation (which may rest on simplification);
    - demonstrate a visible and credible detection and enforcement capability.
- Household enterprises pay little direct tax but contribute indirectly via VAT on inputs and other charges; improving their productivity can generate additional revenue without imposing direct taxes.

### Pathways to Expand the Formal Sector
- Two pathways:
  1. Increase the size of formal enterprises and the entrance of new formal firms.
  2. Transform informal enterprises into formal enterprises by improving the business environment.
- Key constraints: cost of financing and access to finance; inefficiencies in labor and product market regulations.

### Panel Regression Results (Arellano-Bond GMM, sample of 108 countries, 2006–2014)
- Key coefficient estimates (dependent variable: share of informality):
  - Lagged share of informality: 0.963*** (Regression 1), 0.820*** (2), 0.781*** (3), 0.800*** (4), 0.827*** (5).
  - Growth rate of GDP per capita (2011 U.S. dollars, PPP): –0.422*** (1), –0.290*** (2), –0.273*** (3), –0.260*** (4), –0.205*** (5).
  - Efficiency of financial market (CGI): –2.551** (1), –1.817*** (2), –1.718** (3), –1.633** (4), –1.159* (5).
  - Cost of doing business: 1.340** (1), 1.106* (2), 1.682* (3), 1.600* (4), 1.492* (5).
  - Flexibility of labor market (CGI): 0.590 (1), 0.460 (4) — not statistically significant.
  - Governance indicator (first PCA component of Voice and Accountability and Political Stability): 0.393 (5) — not statistically significant.
  - Advanced economy dummy and oil exporter dummy not significant when included with policy variables.
- Interpretations:
  - High persistence of informality (strong significance of lagged informality).
  - GDP per capita growth strongly associated with reductions in informality.
  - Financial market efficiency (proxy for access to finance) strongly associated with reductions in informality; result robust.
  - Product market efficiency lowers informality in some subcomponents (cost to export, cost of enforcing contracts); labor market flexibility not significant.
  - No robust statistical relationship between the size of the informal economy and governance indicators or the macroeconomic environment proxy used.

### Product-Market and Competitiveness Indicators (comparison of low- vs high-informality countries)
- Subcomponents with largest statistically significant differences (means shown):
  - Getting electricity: Procedures (number) — Low Informality: 4.4; High Informality: 6.7; t-test p-value: 0.01
  - Time to export: Documentary compliance (hours) — Low: 55; High: 1050; t-test p-value: 0.01
  - Irregular payments and bribes, 1–7 (best) — Low: 2.4; High: 3.1; t-test p-value: 0.02
  - Property rights, 1–7 (best) — Low: 4.6; High: 3.5; t-test p-value: 0.03
  - Reliability of infrastructure, 0–8 (best) — Low: 2.7; High: 0.4; t-test p-value: 0.03
  - Burden of customs procedures, 1–7 (best) — Low: 4.2; High: 3.3; t-test p-value: 0.03
  - Doing Business Indicators - Country Rank — Low: 107; High: 154; t-test p-value: 0.03
- Policy-relevant areas highlighted: protection of property rights, electricity provision, customs procedures burden, ease of exporting, reliability of infrastructure.

### Success in Expanding the Formal Economy: Mauritius and Rwanda (Box 3.1)
- Mauritius and Rwanda reduced informality during 2010–14 relative to 1996–2000.
- Mauritius: informality fell by a further four percentage points of GDP from an already low level, reaching OECD levels.
- Common policy actions:
  - Proactive SME-friendly business environment.
  - Removal of barriers to formalization.
  - Strengthening SME capacity and competitiveness.
- Rwanda reforms:
  - Reformed commercial law.
  - Improved regulations to ease access to credit.
  - Accelerated trade and property registration.
  - Outperforms OECD standards in procedures to start a formally registered business.
- Mauritius reforms and outcomes:
  - Successive governments supported SMEs via improved access to financing, free export market intelligence, and industrial parks.
  - Risk-sharing programs with banks enabled SMEs to obtain credit at the prime rate.
  - Firm registration computerized to allow same-day creation; one-stop shops for financing, information, permits, and licenses.
  - Tax reform and extensive computerization (including online tax payments); shift from ex-ante authorization to ex-post verification.
  - Between 2005 and 2010 employment in SMEs continued to grow despite shocks.
  - SMEs represent close to 40 percent of GDP and about 45 percent of total employment.

### Measurement Alternatives and MIMIC Innovations
- Alternative measurement approaches summarized:
  - Direct approaches: surveys, voluntary replies, tax auditing and compliance methods.
  - Indirect approaches: discrepancy methods (national expenditure vs income), labor force discrepancies, electricity approach, transaction approach, currency demand approach, MIMIC approach.
- MIMIC criticisms addressed:
  - Replace GDP per capita indicators with night lights to reduce endogeneity.
  - Calibration to percent of GDP uses Schneider (2007) currency demand calibration for year 2000.
- Alternative robustness check: Multiple Imputation using Predictive Mean Matching (PMM) with survey-based observations for 49 countries; produces multiply-imputed plausible estimates under "missing at random" assumption.
- Resulting outputs include rankings of informal economy sizes as percent of GDP (selected country groupings provided in annex tables).

### Policy Implications and Recommendations
- Recognize household enterprises as an important safety net; policies should foster their productivity rather than primarily focus on extracting direct tax revenue.
- Prioritize improvements that expand the formal sector via both pathways (grow formal firms; transform informal firms):
  - Improve access to finance, particularly for SMEs (including technological innovations such as mobile banking/Fintech).
  - Foster product market efficiency:
    - Reduce the cost to export.
    - Reduce the cost of enforcing contracts.
    - Improve access to electricity.
  - Create a business environment friendly to SMEs to deepen financial markets and encourage formalization.
- Revenue administration reforms:
  - Simplify tax systems; reduce taxes on microenterprises and small businesses.
  - Develop integrated compliance management strategies (community tolerance reduction, targeted assistance, self-regulation encouragement, visible enforcement).
- Policy challenge: create an environment where small firms—both formal and informal—can thrive and grow, enabling gradual expansion of the formal sector; support household enterprises concurrently since transition to formality is expected to be slow.

*Source: sreo0517-chap3 — "3. The Informal Economy in Sub-Saharan Africa," Regional Economic Outlook: Sub‑Saharan Africa (chapter content).*

### 3. The Informal Economy in Sub-Saharan Africa

### 3. The Informal Economy in Sub-Saharan Africa

### Methodology and Estimation Approach
- Uses a parametric model: the Multiple Indicator–Multiple Cause (MIMIC) Model.
- MIMIC model sample: 140 countries during 1991–2014.
- Model refinements address past endogeneity concerns by using night lights as a measure of the size of the economy and other adjustments; starting value for annual series set to 2000 and taken from Schneider (2007) using a currency demand model.
- Observable drivers used in the MIMIC Model:
  - Tax burden.
  - Institutional development (rule of law and governance).
  - Official unemployment rate.
  - Trade openness.
- Indicators (effects) used in the MIMIC Model:
  - Currency as a fraction of broad money (M0/M1).
  - Labor force participation.
  - Size of the economy proxied by night lights.
- The MIMIC methodology: structural equation model (causes) + measurement model (indicators), fitted by maximum likelihood.

### Size, Heterogeneity, and Trends
- Country-level range in sub-Saharan Africa (average over 2010–14):
  - Lowest: Between 20–25 percent of GDP in Mauritius, South Africa, and Namibia.
  - Highest: Between 50–65 percent of GDP in Tanzania and Nigeria.
- Regional and comparative estimates:
  - Sub-Saharan Africa unweighted average share of informality: almost 38 percent of GDP during 2010–14.
  - Latin America and the Caribbean: 40 percent of GDP.
  - South Asia: 34 percent of GDP.
  - Europe: 23 percent of GDP.
  - OECD members: 17 percent of GDP.
- By income/type within sub-Saharan Africa:
  - Low-income countries: informal economy averages 40 percent of GDP.
  - Middle-income countries: informal economy averages 35 percent of GDP.
  - Oil exporters: informal economy close to 50 percent of GDP.
- Time trend noted: the share of informality in sub-Saharan Africa has been very gradually declining, consistent with a global pattern.

### Drivers and Correlates of Informality
- Informality tends to fall with higher income levels (log of GDP per capita inversely related to informality).
- Trade openness: greater trade openness is associated with lower informality (negative slope in regional analysis).
- Institutions and governance:
  - Rule of law and other Worldwide Governance Indicators (voice and accountability; political stability and absence of violence; government effectiveness; regulatory quality; control of corruption) are inversely related to informality.
  - Scatter evidence shows stronger governance indicators associated with lower shares of informality.
- Entrepreneurship context:
  - Sub-Saharan Africa records the highest rate of total early-stage entrepreneurial activity and nascent entrepreneurship among comparators.
  - Primary reported motivation globally is improvement-driven opportunity, but about a third of new entrepreneurs in sub-Saharan Africa report necessity as their motivation (slightly higher than other regions).
  - Societal attitudes in sub-Saharan Africa are the most positive toward entrepreneurship, with the largest share of working-age population considering entrepreneurship a desirable career and associating high status with it.

### Robustness and Validation of Estimates
- Alternative, independent approach used for cross-check: Predictive Mean Matching (PMM) method to treat informality as a missing data problem and match countries with survey data to those without.
  - PMM groupings broadly align with MIMIC findings.
- Comparison with statistical agency estimates:
  - For eight sub-Saharan African countries that publish national estimates, rank correlation between MIMIC results and national accounts/statistical agency estimates: 0.73; Spearman's Rank Correlation: 0.857***.
  - Limitations of statistical agency estimates: not all countries publish data; differing methodologies and sampling affect comparability; some approaches may not capture recent changes.
- Annexes referenced for further methodological detail (Annex 3.1 and Annex 3.2).

### Interaction with Economic Performance and Role as Safety Net
- Informality as employment safety net:
  - ILO surveys report that 30 to 90 percent of employment in the nonagricultural sector occurs in the informal sector in some sub-Saharan African countries.
  - Household survey evidence: between 55 and 75 percent of nonagricultural employment in low-income and resource-rich sub-Saharan African countries occurs in household enterprises.
- Household enterprises help improve opportunities relative to agriculture (household survey consumption/per capita evidence cited).

### Policy Implications and Recommendations
- To expand the formal sector and facilitate the transition of resources from informal to formal:
  - Improve access to finance, particularly for small and medium-sized enterprises (SMEs).
  - Foster product market efficiency; specific components highlighted:
    - Reduce the cost to export.
    - Reduce the cost of enforcing contracts.
    - Improve access to electricity.
  - Create a business environment friendly to SMEs to deepen financial markets and encourage formalization.
- Policy challenge emphasized: create an environment where small firms—both formal and informal—can thrive and grow, enabling expansion of the formal sector over time.

*Source: IMF staff calculations and analysis from "3. The Informal Economy in Sub-Saharan Africa," Regional Economic Outlook: Sub‑Saharan Africa (chapter content).*

### 3. THE INFORMAL ECONOMY IN SUB-SAHARAN AFRICA

### 3. THE INFORMAL ECONOMY IN SUB-SAHARAN AFRICA

### Consumption and Welfare Comparisons
- Workers in the agricultural sector have per capita consumption levels considerably lower than households with salaried workers, with on average 60 percent of agricultural workers having consumption levels below the 25th percentile of salaried workers.
- Household enterprises have consumption levels below that of salaried employment at the 50th and 75th percentiles; at the 25th percentile household enterprise consumption is below salaried workers for all sample countries except Rwanda and Uganda, where consumption is similar to that of salaried workers.
- Sample countries for consumption comparison: Cameroon, Ghana, Mali, Rwanda, Uganda, and Zambia.

### Informality and Productivity
- Based on World Bank Enterprise Surveys, the productivity of informal firms (real output per employee) is:
  - 25 percent that of small formal firms (on average).
  - 19 percent that of medium-sized formal firms (on average).
- Large cross-country variation in the informal-formal productivity gap exists; the gap is particularly wide in Kenya, Namibia, Niger, Senegal, Swaziland, and Tanzania.
- Productivity measurement: real output per employee in purchasing power parity terms for 16 sub-Saharan African countries (approach follows Hsieh and Klenow (2009)).

### Informality and Size of Firms
- Informal firms are typically microenterprises with less than five workers.
- Average informal firm size is:
  - about 30 percent of the average size of small formal firms.
  - about 7 percent the size of medium-sized formal firms.
- The proportion of small firms is 71 percent in sub-Saharan Africa, compared with 61 percent in economies outside sub-Saharan Africa.
- Subnational analysis: size of informal firms computed across 156 subnational regions; regions grouped into low-informality (below-average) and high-informality (above-average).

### Informality as a Vicious Cycle
- Key obstacles keeping firm size small and informality persistent include the cost of financing and limited access to credit.
- Features sustaining the vicious cycle: small size, low productivity, limited access to finance, poor conditions for entrepreneurship.

### Informality and Tax Policy
- Reasons for not paying taxes vary across informal firms; lumping all informal firms together risks misleading policy conclusions.
- Some firms do not remit taxes because they are below legal thresholds; others may deliberately evade taxes even if above thresholds.
- Policy suggestions from the analysis:
  - Raising the VAT threshold may encourage firms that operate just below the threshold to increase production, potentially without changing the number of informal firms or tax collection.
  - Relatively high VAT thresholds are recommended for developing countries, with license fees or turnover taxes for businesses below the VAT threshold.
  - Focus tax policy on simplifying tax laws and reducing taxes on microenterprises and small businesses.
  - Revenue administrations should develop integrated compliance management strategies, including:
    - reducing community tolerance for tax evasion;
    - providing targeted assistance to promote voluntary compliance;
    - encouraging self-regulation (which may rest on simplification);
    - demonstrating a visible and credible detection and enforcement capability.
- Household enterprises pay little direct tax but contribute indirectly via VAT on inputs and other charges; helping them be more productive in the informal sector can still generate additional revenue without imposing direct taxes.

### Pathways to Expand the Formal Sector
- Two pathways:
  1. Increase the size of formal enterprises and the entrance of new formal firms.
  2. Transform informal enterprises into formal enterprises by improving the business environment.
- Key constraints identified: cost of financing and access to finance, inefficiencies in labor and product market regulations.

### Panel Regression Results (Arellano-Bond GMM, sample of 108 countries, 2006–2014)
- Table 3.3 key coefficient estimates (dependent variable: share of informality):
  - Lagged share of informality: 0.963*** (Regression 1), 0.820*** (2), 0.781*** (3), 0.800*** (4), 0.827*** (5).
  - Growth rate of GDP per capita (2011 U.S. dollars, PPP): –0.422*** (1), –0.290*** (2), –0.273*** (3), –0.260*** (4), –0.205*** (5).
  - Efficiency of financial market (CGI): –2.551** (1), –1.817*** (2), –1.718** (3), –1.633** (4), –1.159* (5).
  - Cost of doing business: 1.340** (1), 1.106* (2), 1.682* (3), 1.600* (4), 1.492* (5).
  - Flexibility of labor market (CGI): 0.590 (1), 0.460 (4) — not statistically significant.
  - Governance indicator (first PCA component of Voice and Accountability and Political Stability): 0.393 (5) — not statistically significant.
  - Advanced economy dummy and oil exporter dummy not significant when included with policy variables.
- Interpretations:
  - High persistence of informality (strong significance of lagged informality).
  - GDP per capita growth is strongly associated with reductions in informality.
  - Financial market efficiency (proxy for access to finance) is strongly associated with reductions in informality; result robust across specifications.
  - Product market efficiency lowers informality in some subcomponents (cost to export, cost of enforcing contracts); labor market flexibility not significant.
  - No robust statistical relationship between the size of the informal economy and governance indicators or the macroeconomic environment proxy used.

### Drilling Down: Product-Market and Competitiveness Indicators (Table 3.4)
- Subcomponents with largest statistically significant differences between low- and high-informality countries (comparison of means, t-test p-values shown):
  - Getting electricity: Procedures (number) — Low Informality (Bottom quintile): 4.4; High Informality (Top quintile): 6.7; Comparison of Means (t-test): 0.01
  - Time to export: Documentary compliance (hours) — Low: 55; High: 1050; Comparison of Means (t-test): 0.01
  - Irregular payments and bribes, 1–7 (best) — Low: 2.4; High: 3.1; Comparison of Means (t-test): 0.02
  - Property rights, 1–7 (best) — Low: 4.6; High: 3.5; Comparison of Means (t-test): 0.03
  - Reliability of infrastructure, 0–8 (best) — Low: 2.7; High: 0.4; Comparison of Means (t-test): 0.03
  - Burden of customs procedures, 1–7 (best) — Low: 4.2; High: 3.3; Comparison of Means (t-test): 0.03
  - Doing Business Indicators - Country Rank — Low: 107; High: 154; Comparison of Means (t-test): 0.03
- Policy-relevant areas highlighted: protection of property rights, electricity provision, customs procedures burden, ease of exporting, and reliability of infrastructure.

### Policy Implications and Recommendations
- Recognize household enterprises as an important safety net and persistent component of the economy; policy should focus on fostering their productivity rather than primarily increasing direct tax revenue from them.
- For larger firms that evade taxes partially or fully, revenue authorities should improve tax compliance through simplified tax systems and enforcement.
- Prioritize improving access to finance and enhancing product market efficiency to expand the formal sector by both transitioning informal firms and enabling formal sector expansion:
  - Improving access to finance is key; countries may develop technological innovations in the financial sector (for example, mobile banking or Fintech).
  - Product-market efficiency improvements should target cost to export and cost of enforcing contracts, and enhancing access to electricity.
- Many of the policies that support formal sector growth also raise productivity of household enterprises; since transition to formality is expected to be slow, policies should simultaneously support household enterprises.

*Source: REGIONAL ECONOMIC OUTLOOK: SUB-SAHARAN AFRICA — Chapter 3 (sreo0517-chap3).*

### 3. THE INFORMAL ECONOMY IN SUB-SAHARAN AFRICA

### 3. THE INFORMAL ECONOMY IN SUB-SAHARAN AFRICA

### Success in Expanding the Formal Economy: The Cases of Mauritius and Rwanda (Box 3.1)
- Mauritius and Rwanda reduced the size of informality during 2010–14 relative to 1996–2000.
- Mauritius: informality fell by a further four percentage points of GDP from an already low level, reaching OECD levels.
- Rwanda: reduced the size of its informal sector significantly over the same period.
- Common policy actions enabling formalization:
  - Proactive creation of a business environment for SMEs to flourish.
  - Removal of identified barriers to formalization.
  - Strengthening SME capacity and competitiveness.
- Rwanda specific reforms:
  - Reformed commercial law.
  - Improved regulations to ease access to credit.
  - Accelerated trade and property registration.
  - Outperforms OECD standards in procedures to start a formally registered business.
- Mauritius specific reforms and outcomes:
  - Since early 1980s reforms, successive governments supported SMEs via improved access to financing, free export market intelligence, and industrial parks.
  - Responses to shocks (loss of trade preferences in textiles and sugar; global financial crisis in 2007) included intensified SME support.
  - Labor market reforms focused on protecting workers instead of jobs and liberalized access to skilled and unskilled global labor.
  - Risk-sharing programs with banks enabled SMEs to obtain credit at the prime rate.
  - Firm registration computerized to allow same-day creation; one-stop shops for financing, information, permits, and licenses.
  - Tax reform and extensive computerization (including online tax payments) leveled the playing field; Minister of Finance relinquished discretionary powers; shift from ex-ante authorization to ex-post verification.
- Impact in Mauritius:
  - Between 2005 and 2010 employment in SMEs continued to grow despite shocks and contributed more job growth than larger firms.
  - SMEs represent close to 40 percent of GDP and about 45 percent of total employment.

### Measuring the Informal Economy: Alternative Methodologies (Annex 3.1)
- Methodological categories:
  - Direct approaches: surveys, voluntary replies, tax auditing and compliance methods.
    - Strength: detailed structure of informal economy.
    - Weaknesses: sensitive to questionnaire design and respondent cooperation; unlikely to capture all informal activities.
  - Indirect (indicator) approaches: macroeconomic indicators and model-based methods.
- Specific indirect approaches described:
  - Discrepancy between national expenditure and income statistics:
    - Uses difference between national income and national expenditure estimates as proxy.
    - Assumes expenditure components measured without error and independence from income factors.
  - Discrepancy between official and actual labor force:
    - Interprets decline in official labor force participation as increase in informal economy if total participation constant.
    - Weak indicator due to other explanations for participation rate changes.
  - Electricity approach (Kaufmann and Kaliberda 1996):
    - Uses difference between growth of electricity consumption and growth of official GDP as proxy.
    - Assumes electricity-overall GDP elasticity close to one.
    - Drawbacks: not all informal activities use electricity; elasticity varies across countries/time.
  - Transaction approach (Feige 1979):
    - Uses Fisher’s equation Money*Velocity = Prices*Transactions and assumption Prices*Transactions = k (official GDP + informal economy).
    - Needs benchmark ratio for a base year; assumes k constant; vulnerable to payment technology changes affecting velocity.
  - Currency demand approach (Cagan 1958; Tanzi 1980):
    - Links informal transactions to increased demand for currency (cash).
    - Models currency demand as function of income, payment practices, interest rates, tax burden, regulation, and tax system complexity.
    - Problems: may underestimate informal economy (not all transactions are cash); shifts between currency and deposit types; arbitrary equal velocity assumption; questionable assumption of no informal economy in base year.
  - Multiple Indicators–Multiple Cause (MIMIC) approach:
    - Considers multiple causes and multiple observable effects of the unobserved informal economy.
    - Produces relative estimated sizes over time; requires benchmarking/calibration to convert to percent of GDP.
    - Calibration used: Schneider (2007) procedure, taking values from year 2000 using the currency demand approach.
    - Final step yields dynamic panel of informal economy size as percent of GDP.

### The MIMIC Methodology and Innovations (Annex 3.2)
- MIMIC features:
  - Explicitly models multiple causes and multiple effects of the informal economy.
  - Based on unobserved-variable framework combining causes and indicators.
- Main criticisms of MIMIC:
  - Use of GDP per capita and growth of GDP per capita as both causes and indicators (endogeneity concern).
  - Reliance on another independent study for calibration from standardized values to percent of GDP.
  - Sensitivity of estimated coefficients to specification, country sample, and time span.
- Innovations and robustness checks applied:
  - Replace GDP per capita indicators with night lights approach (Henderson, Storeygard, and Weil 2012) to independently capture economic activity and address GDP endogeneity.
  - Use of an alternative independent methodology: Multiple Imputation using Predictive Mean Matching (Rubin 1987; Little 1988).
    - Uses survey-based observations of informal economy size for 49 countries and matches to countries with missing data through multiply-imputed datasets estimated by linear regression.
    - Produces a set of plausible estimates to incorporate uncertainty associated with missing data.
    - Procedure summary:
      - Estimate linear regression of informal economy size for all countries using covariates similar to MIMIC.
      - Draw randomly from posterior predictive distribution of coefficients to predict new values for all countries.
      - Match predicted values of non-missing countries to countries with missing data within groupings; use actual values as estimates.
      - Average matches across samplings to produce final estimates.
    - Assumption: missing data mechanism is "missing at random" (weaker than "missing completely at random"); caveats discussed concerning potential violations but practical survey availability for countries with large informal economies offers partial validation.
- Resulting outputs:
  - Rankings of informal economy sizes as percent of GDP from lowest to highest summarized in Table A3.2.1 (Selected Sub-Saharan African Countries: Informal Economy, Average 2000–12).

### Regional Associations: Governance, Doing Business, and Competitiveness (Annex 3.3)
- Comparative indicators and the share of the informal economy shown across regions.
- Regions included: OECD; Middle East and North Africa; Asia; Europe and Central Asia; Latin America and the Caribbean; Sub-Saharan Africa.
- Indicators referenced:
  - World Governance Indicators (index range –2.5 to 2.5).
  - Doing Business Distance to Frontier (range 0–100 in figure axis context).
  - Global Competitiveness Index (index range 1 to 7).
- Table Annex 3.2.1 — Selected Sub-Saharan African Countries: Informal Economy, Average 2000–12
  - Low-Size Countries (0-20 percent): Mauritius; South Africa; Botswana; Lesotho; Swaziland; Senegal*
  - Middle-Size Countries (20-40 percent): Cabo Verde; Namibia; Kenya; Zimbabwe; Eritrea; Gabon; The Gambia; Uganda; Sierra Leone*; Cameroon*; Malawi; Madagascar; Equatorial Guinea; Niger*; Mozambique; Burkina Faso; Chad; Burundi*
  - High-Size Countries (>40 percent): Congo, Republic of; Togo*; Guinea-Bissau; Nigeria*; Mali; Comoros; Congo, Democratic Republic of*; Zambia; Ghana; Guinea; Tanzania; Ethiopia; Mauritania; Central African Republic; Angola; Côte D'Ivoire; Liberia; Niger*; São Tomé and Príncipe; Sierra Leone*; others as listed.
  - Note: Table is based on survey estimates and Predictive Mean Matching Analysis; entries marked * are based on survey estimates.

### Country Classifications (Annex 3.4)
- Annex Table 3.4.1 presents country classifications across categories:
  - Oil exporters
  - Upper-middle income
  - Lower-middle income
  - Low-income
  - Fragile states
- Countries listed with their applicable classifications include (selection from table):
  - Angola: Oil exporters; Upper-middle income
  - Benin: Lower-middle income
  - Botswana: Upper-middle income
  - Burkina Faso: Low-income
  - Burundi: Low-income; Fragile states
  - Cameroon: Oil exporters
  - Cabo Verde: Upper-middle income
  - Central African Republic: Low-income; Fragile states
  - Chad: Oil exporters; Upper-middle income; Low-income
  - Comoros: Low-income; Fragile states
  - Democratic Republic of Congo: Oil exporters; Low-income
  - Republic of Congo: Oil exporters; Upper-middle income; Low-income
  - Côte d'Ivoire: Lower-middle income; Low-income
  - Equatorial Guinea: Oil exporters; Upper-middle income
  - Eritrea: Low-income; Fragile states
  - Ethiopia: Lower-middle income
  - Gabon: Oil exporters; Upper-middle income
  - The Gambia: Lower-middle income
  - Ghana: Oil exporters; Upper-middle income
  - Guinea: Low-income; Fragile states
  - Guinea-Bissau: Low-income; Fragile states
  - Kenya: Lower-middle income
  - Lesotho: Upper-middle income
  - Liberia: Low-income; Fragile states
  - Madagascar: Low-income; Fragile states
  - Malawi: Low-income; Fragile states
  - Mali: Low-income; Fragile states
  - Mauritius: Upper-middle income; Oil exporters
  - Mozambique: Low-income
  - Namibia: Upper-middle income; Oil exporters
  - Niger: Low-income
  - Nigeria: Oil exporters; Upper-middle income
  - Rwanda: Lower-middle income
  - São Tomé and Príncipe: Oil exporters; Upper-middle income
  - Senegal: Lower-middle income
  - Seychelles: Upper-middle income; Oil exporters
  - Sierra Leone: Low-income; Fragile states
  - South Africa: Oil exporters; Upper-middle income
  - Swaziland: Upper-middle income; Oil exporters
  - Tanzania: Lower-middle income
  - Togo: Low-income; Fragile states
  - Uganda: Lower-middle income
  - Zambia: Upper-middle income
  - Zimbabwe: Low-income; Fragile states
- (The table provides full cross-classification for all listed Sub-Saharan African countries.)

*Source: sreo0517-chap3 - 3. THE INFORMAL ECONOMY IN SUB-SAHARAN AFRICA*

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*Regional Economic Outlook: Sub‑Saharan Africa — Chapter 3 references*

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_Source: https://www.imf.org/-/media/files/publications/reo/afr/2017/may/pdf/sreo0517-chap3.pdf_