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---

### I. Introduction — context, questions, and conceptual trade-offs
- Informal sector contribution and employment:
  - The informal sector contributes between 25 and 65 percent of GDP (IMF 2017).
  - The informal sector accounts for 85.8 percent of total employment in Sub-Saharan Africa (International Labor Organization, 2018).
- Key research questions:
  - How does immigration in developing and emerging economies impact native employment, including sectoral composition (formal versus informal employment) and type of employment (self-employment versus wage employment) within each sector?
  - How does this impact differ when foreign workers have complementary versus substitute skills compared with those of native workers?
- Conceptual trade-offs:
  - Immigration can increase labor demand and productivity if immigrants bring complementary skills.
  - Immigration can reduce native wages and employment if immigrants are substitutes for native skills, potentially shifting natives into informal, low-productivity jobs.

### III. Theoretical framework — model setup and predicted short-term outcomes
- Model setup and assumptions:
  - Modified Rivera-Batiz (1981) two-sector segmented labor market model adapted for developing/emerging economies.
  - Both formal and informal sectors hire foreign workers; foreign and native workers may be substitutes or complements.
  - Wages are flexible and labor markets are closed; short-run focus with fixed non-labor inputs (capital does not respond to immigration).
  - Formal sector production: Xf = Ff(Nf + S), with Ff' > 0, Ff'' < 0.
  - Foreign labor offer curve: Ws = G(S, Z), with Gs > 0, Gz > 0 (Z = average income of origin country).
  - Profits: Π = PR·Ff(Nf + S) – Wf·Nf – S·G(S, Z).
  - First-order conditions: PR·Ff' = Wf and PR·Ff' = Ws.
- Predicted short-term outcomes:
  - If foreign and native skills are substitutes:
    - Immigration increases labor supply in the formal sector → lower wages (W0 to W1) → native employment falls in formal sector (N0 to N1) → natives move to informal sector or become necessity-driven self-employed.
  - If foreign and native skills are complements:
    - Immigration can raise labor demand and wages for certain native skill groups, expand formal-sector production, and create positive spillovers that increase informal-sector employment (especially wage employment).

### IV. Empirical framework — data, identification, and stylized facts
- Stylized facts motivating strategy:
  - SSA features: large informal economies; immigration shares small (1 to 4 percent of population) including intra-regional and inter-regional flows.
  - Inter-regional immigrants (from outside SSA) tend to be relatively more educated and have skills complementary to natives; intra-regional immigrants tend to match native education profiles and act as substitutes.
  - SSA workers demonstrate high entrepreneurship (Global Entrepreneurship Monitor, 2018).
- Country selection and data:
  - Census and household survey PUMS from IPUMS-International for Cameroon, Ghana, and South Africa (period centered on 2010; proxies used where 2010 not available).
- Stylized statistics:
  - Native employment rates: Cameroon 48 percent, Ghana 75 percent, South Africa 41 percent.
  - Informal sector employment shares: Cameroon and Ghana > 80 percent; South Africa ~12 percent (excluding private household activities).
  - In Cameroon and South Africa, native workers are more present in formal sector while foreign workers are more present in informal sector; Ghana shows a slight opposite pattern.
- Empirical specification and identification:
  - National (regional) Borjas (2003)–style approach applied to SSA region, defining skill groups by education (7 groups) and experience (8 groups).
  - Two immigrant definitions:
    1. Inter-regional immigrant = foreign-born outside the considered country and outside SSA.
    2. Intra-regional immigrant = foreign-born outside the considered country but within SSA.
  - Primary regression for native employment rate:
    - Y_cij = η·Z_cij + C_c + I_i + J_j + ε_cij
    - Z_cij = M_cij / N_cij (immigrant share of working-age population for skill cell (c,i,j)).
  - Sectoral and employment-type regressions analogous; employment-type regressions add access-to-capital proxy A_cij (share owning dwelling via mortgage or lending arrangement).
  - Identification uses past immigrant distribution (1990s or closest census decade) as instrument for contemporary immigrant shares to address selection; sample restricted to men (primary) with women used as sensitivity test.
- Data specifics:
  - Education categories: (i) no schooling, (ii) some primary completed, (iii) primary completed, (iv) lower secondary completed, (v) secondary general completed, (vi) some college/post-secondary technical, (vii) college graduates.
  - Experience defined as age minus entry age (entry ages: 17 for first four categories, 19 for secondary, 21 for post-secondary technical, 23 for college); sample: experience 1–40 years (age 18–63).

### V. Results — aggregate, sectoral allocation, employment type, heterogeneity
- Aggregate employment effects (Table 3):
  - Inter-regional immigration (complementary skills) increases native employment:
    - Male Employment coefficient: 2.626** (standard error 1.274).
    - Female Employment coefficient: 5.40*** (standard error 1.392).
  - Intra-regional immigration (substitute skills) reduces native employment:
    - Male Employment coefficient: -1.488*** (standard error 0.352).
    - Female Employment coefficient: -1.575*** (standard error 0.298).
  - Regressions: 168 observations (3 countries × 7 education × 8 experience = 168 cells); specifications include fixed effects and are weighted by cell sample size.
- Sectoral allocation (Tables 4 and 5):
  - Inter-regional immigration:
    - Positive but not statistically significant effect on native formal employment.
    - Positive effect on informal employment (Table 5): Male Employment 2.160* (1.219); Female coefficient large but not precisely estimated in specification I (16.743, s.e. 19.875).
  - Intra-regional immigration:
    - Negative effect on formal employment for males: -2.638*** (s.e. 0.306).
    - Positive effect on informal employment: Male Employment 1.122*** (s.e. 0.433); Female Employment 21.277*** (s.e. 7.039).
  - Elasticities reported:
    - A 10 percent increase in inter-regional immigration → 0.4 percent increase in informal employment.
    - A 10 percent increase in intra-regional immigration → 0.2 percent increase in informal employment.
- Employment type within sectors (Tables 6–9):
  - Formal sector:
    - Inter-regional immigration reduces formal self-employment (male: -4.003***, s.e. 0.931; female: -3.160***, s.e. 0.853).
    - Inter-regional immigration increases formal wage employment (male: 1.933***, s.e. 0.764; female: 4.003***, s.e. 0.871).
  - Informal sector:
    - Inter-regional immigration increases informal wage employment (male: 0.305***, s.e. 0.118; female: 0.346***, s.e. 0.094).
    - Intra-regional immigration increases informal self-employment (male coefficient 0.847* in specification II, s.e. 0.468).
  - Access to capital (proxy = dwelling ownership with mortgage/loan) increases self-employment in both formal and informal sectors (coefficients positive and statistically significant in multiple specifications).
  - Calculated elasticities:
    - A 10 percent increase in inter-regional immigration raises informal wage employment by 0.5 percentage points.
    - A 10 percent increase in intra-regional immigration raises informal self-employment by 1.9 percentage points.
- Heterogeneity by skill groups (Table 11):
  - Restricting to natives with at least high school degree:
    - Inter-regional immigration shows a negative impact on informal employment and both self- and wage-employment in informal sector (e.g., Informal Employment coefficient -2.338**, s.e. 0.911).
    - Results suggest basic patterns may be driven by high-school-dropout groups prevalent in SSA immigration flows.
- Interpretation:
  - Inter-regional immigration (skills complementary to natives) tends to stimulate formal-sector production and generate positive spillovers that increase informal-sector wage employment.
  - Intra-regional immigration (skills substitutable with natives) tends to displace natives from formal sector into necessity-driven informal self-employment.
  - Distinction between necessity-driven and transformational self-employment is important; access to finance alone may be insufficient to convert necessity entrepreneurship into transformational entrepreneurship.

### VI. Conclusion and policy recommendations
- Main conclusions:
  - Directional impact of immigration depends on substitutability vs complementarity of immigrant and native skills:
    - Immigration bringing higher-skilled (complementary) workers increases native employment.
    - Immigration bringing lower-skilled (substitute) workers reduces native employment.
  - Immigration affects sectoral allocation: both types can raise informal employment, but mechanisms differ:
    - Inter-regional immigration → informal wage employment expansion via formal-sector spillovers.
    - Intra-regional immigration → increased informal self-employment driven by displacement.
- Policy recommendations:
  - Enhance complementarity between immigrant and native workers by:
    - Investing more in education and training and ensuring quality of the education system.
    - Implementing better targeted Active Labor Market Policies (ALMPs), especially in regions with large inflows of immigrants whose skill profiles match natives’.
    - Reducing gender gaps to increase women’s education and labor force participation.
    - Strengthening the overall business environment and expanding access to capital to help firms grow.
  - Caveat:
    - Access to finance is necessary but not sufficient to promote transformational self-employment; reforms in product and labor market regulation and political environment are also important to trigger sustained inclusive growth and greater demand for formal labor.

### References — thematic composition and data citations
- Major thematic groups in the references:
  - Labor market impacts of immigration (Altonji & Card; Borjas; Card; Peri & Sparber; Lewis; etc.).
  - Informal sector, formality, and microenterprise (Amaral & Quintin; De Paula & Scheinkman; De Soto; Gelb et al.; Perry et al.; ILO 2018; Malta et al. IMF Working Paper No. 19/112; etc.).
  - Entrepreneurship, self-employment, and small firms (Ardagna & Lusardi; Banerjee & Duflo; Falco & Haywood; Schoar).
  - Wage flexibility, labor market structure, and dual labor market theory (Dickens & Lang; Kindgon & Knight; Rivera-Batiz; Winter-Ebmer & Zweimuller).
  - Empirical and regional studies related to Sub-Saharan Africa and migration (Gonzalez-Garcia et al.; IMF Regional Economic Outlook April 2017; Sparreboom et al. 2019; Ratha et al. Migration and Remittances Factbook 2016).
- Key reference formats and dataset citations present:
  - Working papers and IMF/World Bank reports cited with exact report numbers and years (examples include NBER Working Paper No. 3123; NBER Working Paper No. 9755; IMF Working Paper No. 19/112).
  - Census and survey data sources for stylized facts annex:
    - Source: Cameroon Census and Survey data 2005.
    - Source: Ghana Census and Survey data 2010.
    - Source: South Africa Census and Survey data 2011.

*Source: IMF working paper content (I. Introduction through VI. Conclusion and policy recommendations).*

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

### I. INTRODUCTION

### Context and research questions
- The informal sector contributes between 25 and 65 percent of GDP (IMF 2017) and accounts for 85.8 percent of total employment in Sub-Saharan Africa (International Labor Organization, 2018).
- Key questions:
  - How does immigration in developing and emerging economies impact native employment, including sectoral composition (formal versus informal employment) and type of employment (self-employment versus wage employment) within each sector?
  - How does this impact differ when foreign workers have complementary versus substitute skills compared with those of native workers?
- Relevance: implications for productivity and recovery as African economies respond to the economic impact of the COVID-19 pandemic and begin to reopen borders.

### Conceptual trade-offs highlighted
- Immigration can increase labor demand and productivity if immigrants bring complementary skills.
- Immigration can reduce native wages and employment if immigrants are substitutes for native skills, potentially shifting natives into informal, low-productivity jobs.

---

### III. THEORETICAL FRAMEWORK

### Model setup and key assumptions
- Modified Rivera-Batiz (1981) two-sector segmented labor market model with adjustments for developing/emerging economies:
  - Both formal and informal sectors hire foreign workers.
  - Foreign and native workers may be substitutes or complements.
  - Wages are flexible and labor markets are closed.
  - Short-run focus with fixed non-labor inputs (capital does not respond to immigration).
- Formal sector production: Xf = Ff(Nf + S), with Ff' > 0, Ff'' < 0.
- Foreign labor offer curve: Ws = G(S, Z), with Gs > 0, Gz > 0 (Z = average income of origin country).
- Profits: Π = PR·Ff(Nf + S) – Wf·Nf – S·G(S, Z).
- First-order conditions: PR·Ff' = Wf and PR·Ff' = Ws.

### Predicted short-term outcomes (substitute vs complementary skills)
- If foreign and native skills are substitutes:
  - Immigration increases labor supply in the formal sector → lower wages (W0 to W1) → native employment falls in formal sector (N0 to N1) → natives move to informal sector or become necessity-driven self-employed.
- If foreign and native skills are complements:
  - Immigration can raise labor demand and wages for certain native skill groups, expand formal-sector production, and create positive spillovers that increase informal-sector employment (especially wage employment).
- Table 1 (expected short-term employment impacts) summarizes signs by total employment, sector (formal/informal), and employment type (self-employed/wage-employed) under complementary vs substitute labor (preserved in structure).

---

### IV. EMPIRICAL FRAMEWORK

### Stylized facts motivating empirical strategy
- SSA features motivating study:
  - Large informal economies (e.g., informal sector dominance except South Africa).
  - Immigration shares are small (1 to 4 percent of population) but include both intra-regional and inter-regional flows.
  - Inter-regional immigrants (from outside SSA) tend to be relatively more educated and have skills complementary to natives; intra-regional immigrants tend to match native education profiles and act as substitutes.
  - SSA workers demonstrate high entrepreneurship (Global Entrepreneurship Monitor, 2018).
- Country selection and data source:
  - Census and household survey PUMS from IPUMS-International for Cameroon, Ghana, and South Africa (period centered on 2010; proxies used where 2010 not available).
- Stylized statistics:
  - Native employment rates: Cameroon 48 percent, Ghana 75 percent, South Africa 41 percent.
  - Informal sector employment shares: Cameroon and Ghana > 80 percent; South Africa ~12 percent (excluding private household activities).
  - In Cameroon and South Africa, native workers are more present in formal sector while foreign workers are more present in informal sector; Ghana shows a slight opposite pattern.

### Empirical specification and identification
- National (regional) Borjas (2003)–style approach applied to SSA region, defining skill groups by education (7 groups) and experience (8 groups).
- Two immigrant definitions:
  1. Inter-regional immigrant = foreign-born outside the considered country and outside SSA.
  2. Intra-regional immigrant = foreign-born outside the considered country but within SSA.
- Primary regression for native employment rate:
  - Y_cij = η·Z_cij + C_c + I_i + J_j + ε_cij
  - Z_cij = M_cij / N_cij (immigrant share of working-age population for skill cell (c,i,j)).
- Sectoral and employment-type regressions analogous; employment-type regressions add access-to-capital proxy A_cij (share owning dwelling via mortgage or lending arrangement).
- Identification uses past immigrant distribution (1990s or closest census decade) as instrument for contemporary immigrant shares to address selection; sample restricted to men (primary) with women used as sensitivity test.

### Data specifics
- Education categories: (i) no schooling, (ii) some primary completed, (iii) primary completed, (iv) lower secondary completed, (v) secondary general completed, (vi) some college/post-secondary technical, (vii) college graduates.
- Experience defined as age minus entry age (entry ages: 17 for first four categories, 19 for secondary, 21 for post-secondary technical, 23 for college); sample: experience 1–40 years (age 18–63).

---

### V. RESULTS

### Aggregate employment effects (Table 3)
- Inter-regional immigration (complementary skills) increases native employment:
  - Male Employment coefficient: 2.626** (standard error 1.274).
  - Female Employment coefficient: 5.40*** (standard error 1.392).
- Intra-regional immigration (substitute skills) reduces native employment:
  - Male Employment coefficient: -1.488*** (standard error 0.352).
  - Female Employment coefficient: -1.575*** (standard error 0.298).
- Regressions: 168 observations (3 countries × 7 education × 8 experience = 168 cells); specifications include fixed effects and are weighted by cell sample size.

### Sectoral allocation (Tables 4 and 5)
- Inter-regional immigration:
  - Positive but not statistically significant effect on native formal employment.
  - Positive effect on informal employment (Table 5): Male Employment 2.160* (1.219); Female coefficient large but not precisely estimated in specification I (16.743, s.e. 19.875).
- Intra-regional immigration:
  - Negative effect on formal employment for males: -2.638*** (s.e. 0.306).
  - Positive effect on informal employment: Male Employment 1.122*** (s.e. 0.433); Female Employment 21.277*** (s.e. 7.039).
- Elasticities reported:
  - A 10 percent increase in inter-regional immigration → 0.4 percent increase in informal employment.
  - A 10 percent increase in intra-regional immigration → 0.2 percent increase in informal employment.

### Employment type within sectors (Tables 6–9)
- Formal sector:
  - Inter-regional immigration reduces formal self-employment (male: -4.003***, s.e. 0.931; female: -3.160***, s.e. 0.853).
  - Inter-regional immigration increases formal wage employment (male: 1.933***, s.e. 0.764; female: 4.003***, s.e. 0.871).
- Informal sector:
  - Inter-regional immigration increases informal wage employment (male: 0.305***, s.e. 0.118; female: 0.346***, s.e. 0.094).
  - Intra-regional immigration increases informal self-employment (male coefficient 0.847* in specification II, s.e. 0.468).
- Access to capital (proxy = dwelling ownership with mortgage/loan) increases self-employment in both formal and informal sectors (coefficients positive and statistically significant in multiple specifications).
- Calculated elasticities:
  - A 10 percent increase in inter-regional immigration raises informal wage employment by 0.5 percentage points.
  - A 10 percent increase in intra-regional immigration raises informal self-employment by 1.9 percentage points.

### Heterogeneity by skill groups (Table 11)
- Restricting to natives with at least high school degree:
  - Inter-regional immigration shows a negative impact on informal employment and both self- and wage-employment in informal sector (e.g., Informal Employment coefficient -2.338**, s.e. 0.911).
  - Results suggest basic patterns may be driven by high-school-dropout groups prevalent in SSA immigration flows.

### Interpretation
- Inter-regional immigration (skills complementary to natives) tends to stimulate formal-sector production and generate positive spillovers that increase informal-sector wage employment.
- Intra-regional immigration (skills substitutable with natives) tends to displace natives from formal sector into necessity-driven informal self-employment.
- Distinction between necessity-driven and transformational self-employment is important; access to finance alone may be insufficient to convert necessity entrepreneurship into transformational entrepreneurship.

---

### VI. CONCLUSION AND POLICY RECOMMENDATIONS

### Main conclusions
- Directional impact of immigration depends on substitutability vs complementarity of immigrant and native skills:
  - Immigration bringing higher-skilled (complementary) workers increases native employment.
  - Immigration bringing lower-skilled (substitute) workers reduces native employment.
- Immigration affects sectoral allocation: both types can raise informal employment, but mechanisms differ:
  - Inter-regional immigration → informal wage employment expansion via formal-sector spillovers.
  - Intra-regional immigration → increased informal self-employment driven by displacement.

### Policy recommendations
- Enhance complementarity between immigrant and native workers by:
  - Investing more in education and training and ensuring quality of the education system.
  - Implementing better targeted Active Labor Market Policies (ALMPs), especially in regions with large inflows of immigrants whose skill profiles match natives’.
  - Reducing gender gaps to increase women’s education and labor force participation.
  - Strengthening the overall business environment and expanding access to capital to help firms grow.
- Caveat: access to finance is necessary but not sufficient to promote transformational self-employment; reforms in product and labor market regulation and political environment are also important to trigger sustained inclusive growth and greater demand for formal labor.

*Source: IMF working paper content (I. Introduction through VI. Conclusion and policy recommendations).*

### References

### References (wpiea2020149-print-pdf)

### Major thematic groups in the references
- Labor market impacts of immigration
  - Altonji, J., and Card, D., (1989). “The Effects of Immigration on the Labor Market Outcomes of Natives.” NBER Working Paper No. 3123.
  - Altonji, J., and Card., D., (1991), “The Effects of Immigration on the Labor Market Outcomes of Less-skilled Natives.” Chapter in Immigration, trade and the Labor Market, 1991, pp. 201-234 from National Bureau of Economic Research, Inc.
  - Borjas, G. J., (2003), “The Labor Demand Curve is Downward Sloping: Reexamining the Impact of Immigration on the Labor Market.” NBER Working Paper No. 9755.
  - Borjas., G., and Monras, J., 2017. “The Labour Market Consequences of Refugee Supply Shocks.” Economic Policy, CEPR; CES; MSH, 32(91) pp 361-413.
  - Card, D., (2001), “Immigrant Inflows, Native Outflows, and the Local Market Impacts of Higher Immigration.” Journal of Labor Economics, 19(1), pp. 22-64.
  - Card, D., (2007), “How Immigration Affects U.S. Cities.” Center for Research and Analysis of Migration Discussion Paper Series No 11/07.
  - Card, D., and Lewis, E., (2007). “The Diffusion of Mexican Immigrants During the 1990s: Explanations and Impacts.” In Mexican Immigration to the United States, edited by George Borjas, National Bureau of Economic Research Conference Report, Cambridge, MA.
  - Glitz, A., (2012), “The Labor Market Impact of Immigration: A Quasi-Experiment Exploiting Immigrant Location Rules in Germany.” Journal of Labor Economics, 30(1), pp.175-213.
  - Pischke J., and Velling J., (1997). “Employment Effects of Immigration to Germany: An Analysis Based on Local Labor Markets.” The Review of Economics and Statistics, 79(4), pp. 594-604.
  - Schoeni, R. F., (1997), “The Effects of Immigration on the Employment and Wages of Native Workers: Evidence from the 1970s and 1980s.” RAND Working Paper.
  - Tumen, S., (2016). “The Economic Impact of Syrian Refugees on Host Countries: Quasi-Experimental Evidence from Turkey.” American Economic Review: Papers & Proceedings, 106(5) pp. 456-460.
  - Del Carpio, X., Ozden, C., and Testaverde, M., (2015), “Local Labor Supply Responses to Immigration,” The Scandinavian Journal of Economics, 117(2), pp. 493-521.
  - Bryant J., and Rukumnuaykit P., (2012). “The Labour Market Impacts of Immigration to Developing Countries: Evidence from a Registration Campaign in Thailand.” The Journal of Development Studies, 49(6), pp. 785-800.
  - Bond, Me., And Gaston, N., (2011), “The Impact of Immigration on Australian-born Workers: An Assessment using the National Labour Market Apporach” Economic Papers, 30(3), pp. 400-413.
  - Peri, G., and Sparber, C., (2009), “Task Specialization, Immigraiton, and Wages” American Economic Journal: Applied Economics, 1(3), pp. 135-69.
  - Peri, G., and Sparber, C., (2009), “Task Specialization, Immigration, and Wages.” American Economic Review, 1(3), pp. 135-169.
  - Ottaviano, G., Peri, G., and Wright, G., (2013), “Immigration, Offshoring, and American Jobs.” American Economic Review, 103(5), pp. 1925-59.
  - Lewis, E., (2011), “Immigration, Skill Mix, and Capital Skill Complementarity.” Quarterly Journal of Economics, 126(2), pp. 1029-1069.
  - Lewis, E., (2013), “Immigration and Production Technology.” Annual Review of Economics 5, pp. 165-191.
  - Waldinger, R., (1997). Social Capital or Social Closure? Immigrant Networks in the Labor Market. Los Angeles: Lewis Center for Regional Policy Studies.
  - Drever, A. I., & Hoffmeister, O., (2008). “Immigrants and social networks in a job-scarce environment: The case of Germany”. International Migration Review, 42(2), pp. 425-448.
  - Elliott, J. R., (2001). Referral hiring and ethnically homogeneous jobs: How prevalent is the connection and for whom? Social Science Research, 30(3), 401-425.
  - Maani, S., and Tse M., (2017). “The Impact of Immigration on Earnings and Employment: Accounting for Effective Immigrant Work Experience”. Australian Journal of Labour Economics, 20(1), pp. 291-317.
  - Borjas et al. and related empirical work on local labor markets and native outcomes (Card, Pischke, Schoeni, etc.)
  - Peri and Sparber, and related task-specialization approaches.

- Informal sector, formality, and microenterprise
  - Amaral, P., and Quintin, E., (2006), “A Competitive Model of the Informal Sector.” Journal of Monetary Economics, 53 (7), pp 1541-1553.
  - De Paula, A., and Scheinkman, J. A., (2011), “The Informal Sector: An Equilibrium Model and Some Empirical Evidence form Brazil”. Review of Income and Wealth, 57, pp S8-S26.
  - De Soto, H., (1989) “The Other Path: The Invisible Revolution in the Third World.” New York: Harper and Row.
  - De Soto, H., (2000) “The Mystery of Capital: Why Capitalism Triumphs in the West and Fails Everywhere Else.” New York: Basic Books.
  - Gelb, A., Mengistae T., Ramachandran V., and Shah M.K., (2009). “To Formalize or Not to Formalize? Comparisons of Microenterprise Data from Southern and East Africa”. Center for Global Development Working Paper No 175.
  - Perry G.E., W. F. Maloney, O.S. Arias, P., Fajnzyblber, A., Mason, and J. Saavedra-Chanduvi (2007). Informality: Exit and Exclusion. Washignotn, DC: World Bank.
  - Rauch J., (1991), “Modelling the Informal Sector Formally.” Journal of Development Economics, 35 (1), pp 33-47.
  - Kanbur, R., (2009). “Conceptualizing Informality: Regulation and Enforcement”. Working Papers 2009/01. Ithaca: Cornell University.
  - La Porta, R., and Shleifer A., (2008) “The Unofficial Economy and Economic Development.” Brookings Papers on Economic Activity Fall: 275-352.
  - De Paula & Scheinkman and Amaral & Quintin on equilibrium models of informal sector.
  - International Labour Office, 2018. “Women and Men in the Informal Economy: a Statistical Picture”, ILO report, Geneva.
  - Malta, V., Kolovich, L., Martinez L., and Tavares M., (2019). “Informality and Gender Gaps Going Hand in Hand.” IMF Working Paper No. 19/112.
  - Benjamin N., and Mbaye A.A., (2012a). “The Informal Sector in Francophone Africa: Firm Size, Productivity and Institutions”. Washington DC: World Bank.

- Entrepreneurship, self-employment, and small firms
  - Ardagna, S., and Lusardi A., (2008).  “Explaining International Differences in Entrepreneurship: The Role of Individual Characteristics and Regulatory Constraints.” In International Differences in Entrepreneurship, ed. Josh Lerner and Antoinette Schoar. Chicago: University of Chicago Press.
  - Banerjee, A., and Duflo E., (2011) “Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty.”  New York, Perseus Books, Public Affairs.
  - Falco, P., and Haywood L., (2013), “Entrepreneurship versus Joblessness: Explaining the Rise in Self-Employment.” Journal of Development Economics, 118, pp. 245-265.
  - Schoar, A., (2010), “The Divide between Subsistence and Transformational Entrepreneurship.” Chapter in NBER book Innovation Policy and the Economy, volume 10 (2010), Josh Learner and Scott Stern, editors p, 57-81.
  - Ardagna & Lusardi, Banerjee & Duflo, Falco & Haywood, Schoar on entrepreneurial heterogeneity and constraints.

- Wage flexibility, labor market structure, and dual labor market theory
  - Dickens W., T., and Lang K., (1985), “A Test of Dual Labor Market Theory.” The American Economic Review, 75(4), pp. 792-805.
  - Kindgon, G., and Knight J., (2006). “How Flexible are Wages in Response to Unemployment in South Africa ?” Industrial and Labor Relations Review, 59(3), pp. 471-495.
  - Rivera-Batiz, F., (1981). “The Effects of Immigration in a Distorted Two-Sector Economy.” Economic Inquiry, 19, pp. 626-39.
  - Winter-Ebmer R., Zweimuller, J., (1996), “Immigration and the Earnings of Young Native Workers” Oxford Economic Papers, 48, pp. 473-491.
  - Dickens & Lang; Kindgon & Knight; Rivera-Batiz; Winter-Ebmer & Zweimuller on wage responses and sectoral distortions.

- Empirical and regional studies related to Sub-Saharan Africa and migration
  - Gonzalez-Garcia, J., Hitaj, E., Montfort, M., and Viseth, A., (2016), “Sub-Saharan African Migration, Patterns and Spillovers”, IMF Spillover Notes 9.
  - International Monetary Fund, April 2017. “Regional Economic Outlook: Sub-Saharan Africa, “Restarting the Growth Engine”.
  - Sparreboom, T., Mertens, J., Berger, S., (2019), “The Labour Market Impact of Immigration in Three Sub-Saharan African Economies” Journal of International Migration and Integration. https://doi.org/10.1007/s12134-019-00707-7
  - Ratha, D. K., Plaza, S., and Dervisevic, E., (2016), “Migration and Remittances Factbook 2016.” Washington, D.C.: World Bank Group.
  - Bryant & Rukumnuaykit (Thailand) and regional IMF/World Bank work on migration spillovers and remittances.

### Key reference formats and dataset citations present
- Working papers and IMF/World Bank reports cited with exact report numbers and years:
  - NBER Working Paper No. 3123 (Altonji & Card, 1989).
  - NBER Working Paper No. 9755 (Borjas, 2003).
  - IMF Working Paper No. 19/112 (Malta et al., 2019).
  - Center for Global Development Working Paper No 175 (Gelb et al., 2009).
  - IMF Country Report No. 20/33 (International Monetary Fund).
  - Migration and Remittances Factbook 2016 (World Bank Group).
- Census and survey data sources for stylized facts annex:
  - Source: Cameroon Census and Survey data 2005.
  - Source: Ghana Census and Survey data 2010.
  - Source: South Africa Census and Survey data 2011.

### Observations about coverage and emphasis in the bibliography
- Strong emphasis on empirical labor-market effects of immigration (local labor markets, task specialization, native employment and wages).
- Extensive coverage of informality and the informal sector (theory, equilibrium models, measurement, gender dimensions).
- Multiple entries on entrepreneurship, self-employment, and microenterprise formalization.
- Regional attention to Sub-Saharan Africa and developing-country contexts through IMF, World Bank, and academic studies.

*Source: wpiea2020149-print-pdf - References.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020149-print-pdf.pdf_