## 1. International Comparison on Informality

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### Introduction
- Vietnam’s labor market is characterized by a high degree of informality.
- Informal employment can act as a shock absorber, but pervasive informality can exacerbate vulnerability to economic shocks, as highlighted by the COVID-19 pandemic.
- Informal workers in Vietnam typically have no access to sick leave or unemployment benefits, precarious access to health benefits, and limited savings.

### Scope and methodology
- Documents labor informality in Vietnam using labor force surveys; examines transitions between formal and informal employment and the role of worker characteristics.
- Empirical analysis uses panel probit regressions for the period 2015-2018.
- Exploits regional variation (PCI, PAPI, provincial averages) and interaction terms to assess differential impacts across worker characteristics.

### Stylized facts and key statistics
- Overall labor informality level: 56.2 percent in 2018.
- Total number of workers working informally (2018): 19.3 million.
- Sectoral concentration of informal employment (shares of total informal workers):
  - wholesale and retail business 25 percent;
  - construction 18 percent;
  - food and beverage services 11 percent.
- Composition by firm registration: nearly a third of informal workers were employed by registered firms in 2018.
- Employment shares (2018): wage workers 44 percent; own-account workers 39 percent; family-contributing workers 15 percent; employers 2 percent; members of producers’ cooperatives 0.1 percent.
- Access to compulsory insurance: only 35 percent of non-farm workers overall have access.
- Informal-worker concept used (non-agricultural):
  - all employers working in non-regsitered firms,
  - own-account workers in the informal or non-farming household sectors,
  - all family-contributing workers,
  - members of producer’ cooperatives in the informal sector,
  - wage workers either not having a contract of more than three months or, if they have such a contract, not participating in social insurance.

### Returns to formality, wage gaps, and mobility
- Wage regressions and mobility findings:
  - Pooled OLS: formal workers paid 42 log points, or 53 percent, more than informal workers without controls.
  - Accounting for sectoral differences raises the raw premium to 67 percent.
  - Adding age, education and experience reduces the premium to 51 percent (41.1 log points).
  - Panel regressions with individual fixed effects: wage premium reduced to 8 log points; implied that a given worker would earn 8 percent more if he moved to formal from informal employment.
  - Internationally, Vietnam’s formal-informal wage gap similar to countries on the lower end (Mexico 5 percent, Brazil 4 percent).
  - Workplace effect: almost no difference (only 1 percent) in earnings of informal workers regardless of whether they work in informal vs. formal firms.
- Mobility flows (2017–2018 quarterly panel):
  - Around 4 percent of workers move from formal to informal jobs in a given quarter; a marginally higher proportion move in the opposite direction.
  - Around 2 percent move from informal self-employment into formal self-employment; similar reverse flow.
  - Around 2 percent move from informal to formal wage employment; reverse flow smaller.
- Appendix transition matrices (2018Q1–2018Q3) highlight high persistence within statuses:
  - Formal wage employment → Formal wage employment: 95.6–95.8 across quarters.
  - Informal wage employment → Informal wage employment: 88.5–89.7 across quarters.
  - Cross-quarter employment distribution example (2018Q1): Formal wage employment 35.5; Formal self-employment 11.0; Informal wage employment 26.7; Informal self-employment 26.8; Total 100.0.
- Wage dynamics for switchers:
  - Switchers from informal to formal have 13–16 percent higher informal wages than non-switchers before switching.
  - Moving to formal jobs increases salaries by roughly 10 percent compared to wages received while working informally.
  - Workers who move from formal to informal were doing worse in wages even before switching; after moving, wages decline further by a marginal rate of 4 percent.
- Caveats:
  - Panel follows workers for at most four quarters; wage gaps reflect short-term gains and may not capture long-term gains from formalization.
  - Panel wage-gap estimates use workers who switch sectors; gains for non-switchers may differ.
  - Longer-span evidence (Vietnam Household Living Standards Surveys 2002, 2004, 2006) suggests informal wage penalties of 15 percent (Nguyen et al. 2013).

### Labor market segmentation and heterogeneity
- Evidence consistent with a two-tier informal labor market:
  - Upper tier: informal, higher-skill workers whose employment decisions are driven by choice.
  - Lower tier: low-skilled workers potentially stuck in informal employment (exclusion).
- Determinants at individual level (baseline probit/logit marginal effects):
  - Higher likelihood of being informal associated with: less education; being young; being male; lacking work experience; living in rural areas; working for a nonregistered firm (especially non-FDI firms).
  - High school graduates: probability of working informally is 10 percent lower than those without high-school education.
  - More than 5 years of work experience reduces likelihood of being informal by roughly 20 percent compared to a person with less than one year of experience.
  - Working in a formal firm can reduce the likelihood of informal employment by as much as 60 percent.
- Skill mismatch and education:
  - Almost 80 percent of workers with only a primary education or lower tend to be in informal employment.
  - Tertiary-educated workers in informal employment: 13 percent; of these, 66 percent are young (ages 20–34).
  - In 2018, more than half of informal workers were not trained for their jobs; only 31 percent of informal workers reported doing jobs matching their learning/training (formal workers: 68 percent).

### Role of policy and institutional variables
- Data and policy indicators:
  - Vietnam Provincial Competitiveness Index (PCI) and sub-indices; PAPI control of corruption index used.
  - Provincial average earnings and unemployment rates included.
- Policy-augmented probit findings:
  - Average earnings coefficient negative: higher income associated with lower probability of being informal.
  - Weighted PCI index coefficient significantly negative: improving governance and transparency reduces informality.
  - Disaggregated PCI:
    - Entry barriers: coefficient -0.00319*** (reducing entry barriers lowers informality).
    - Property rights: coefficient -0.00520*** (securing property rights lowers informality).
    - Support policy: 0.00104 (not statistically significant in main specification).
  - PAPI (control of corruption) supports evidence that better control of corruption and secure property rights lower informality.
  - Robustness checks:
    - Dropping potentially endogenous individual characteristics: main signs unchanged except support policies.
    - Controlling for provincial unemployment rate: confirms findings; coefficient of support policies becomes significantly positive in this check.

### Heterogeneous impacts and interaction results
- Interaction model findings (who benefits from reforms):
  - Less educated workers:
    - Benefit disproportionately from reforms that strengthen property rights and from support policies (business support, labor training).
  - Young workers (15-25 years old):
    - Labor training support has a positive and significant impact in reducing informality.
  - Rural workers:
    - Reforms that reduce entry costs and strengthen property rights help firms in rural areas formalize and create formal employment opportunities.
    - Reforms improving labor training and business services benefit urban workers more.
  - Non-FDI sector:
    - Support policies (business services and labor training) disproportionately lower informality in the non-FDI sector.
- Selected interaction coefficients (Table 6 highlights, preserved exactly):
  - policy_variable main effects: Weighted PCI -0.0400***; Entry barriers -0.00326 (ns); Property rights -0.0174***; Support Policies -0.0156**.
  - underedu*policy_variable: -0.0177*** (Weighted PCI), 0.00695*** (Entry barriers), -0.00189*** (Property rights), -0.0146*** (Support Policies).
  - rural*policy_variable: 0.00381*** (Weighted PCI), -0.00921*** (Entry barriers), -0.00570*** (Property rights), 0.00903*** (Support Policies).

### Policy implications and recommendations
- Promote business formalization:
  - Reduce entry costs for start-ups.
  - Secure property rights (land access, law and order, control of corruption).
  - Business formalization linked to greater formal employment and higher wages.
- Strengthen human capital and labor market policies:
  - Invest in education, job training, and life-long learning.
  - Active labor market policies and targeted training for young and low-experience workers.
  - Ongoing workforce upgrading crucial for productivity and modern sector skills.
- Tailor reforms to worker groups:
  - Less educated, rural, and unregistered-firm workers: prioritize property-rights strengthening and entry-cost reduction.
  - Young and urban workers: prioritize labor training and skill-matching programs.
  - Non-FDI firms: improve access to business support services and labor training.
- Recognize limits of single-policy solutions:
  - Business formalization alone is not sufficient given the large share of informal employment inside formal firms.
  - Future research: examine the role of regulations, social security contributions and minimum wages on informality in Vietnam.

### Key regression and sample magnitudes
- Observations in key regressions:
  - Table 1 observations: 1,030,399; 1,030,384; 1,030,089; 1,030,074; 266,276; 266,276.
  - Table 2 observations vary by column: 106,491; 18,120; 102,463; 16,049.
  - Table 4 observations: 1,110,530; 1,110,530; 1,110,515.
  - Table 5 and Table 6 observations: 1,110,515 each.
- Selected Table 4 marginal effects (preserved exactly across columns):
  - underedu (<high school): 0.766***, 0.727***, 0.618***.
  - young (15-25 years old): 0.143***, 0.151***, 0.148***.
  - female: -0.180***, -0.176***, -0.113***.
  - registered firm: -3.813***, -3.787***, -3.691***.
- Table 5 policy coefficients (Column (1)–(4) examples, preserved exactly):
  - average earnings: -0.0617***, -0.0738***, -0.0840***, -0.0705***.
  - Weighted PCI: -0.00467***.
  - entry barriers: -0.00319***.
  - property rights: -0.00520***.
  - support policy: 0.00104 (not statistically significant in main specification).

*Source: wpiea2020273-print-pdf, https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020273-print-pdf.pdf*

### 1. International Comparison on Informality __________________________________________________  9

### 1. International Comparison on Informality

### Introduction
- Vietnam’s labor market is characterized by a high degree of informality.
- Informal employment can act as a shock absorber, but pervasive informality can exacerbate vulnerability to economic shocks, as highlighted by the COVID-19 pandemic.
- Informal workers in Vietnam typically have no access to sick leave or unemployment benefits, precarious access to health benefits, and limited savings.

### Scope and methodology
- The paper documents the nature of labor informality in Vietnam using labor force surveys, examines transitions from formal-informal employment status, and analyzes the role of worker characteristics.
- Empirical analysis uses panel probit regressions for the period 2015-2018.
- The paper also exploits regional variation within Vietnam to examine policy and institutional determinants of informality and uses interaction terms to assess differential impacts across worker characteristics.

### Stylized facts and key statistics
- Out of the 19 million workers working informally in 2018, nearly a third were employed by registered firms, mostly in retail, hospitality, transportation, textiles and garments.
- Controlling for both observable and unobserved characteristics, a given worker would earn 8 percent more if he moved to formal from informal employment.
- Estimated marginal effects:
  - The likelihood of a high school graduate working informally is 10 percent lower than for a worker without a high-school education.
  - Having more than 5 years of work experience can reduce the likelihood of being in informal employment by roughly 20 percent compared to a person with less than one year of work experience.
  - Working for a formal firm can reduce the likelihood of informal employment by as much as 60 percent.

### Labor market segmentation and mobility
- Evidence is consistent with a two-tier informal labor market:
  - An upper tier of informal workers comprised of high-skill workers whose employment decisions are driven by choice.
  - A lower tier of low-skilled workers potentially stuck in informal employment (exclusion).
- There is a statistically significant but modest formal wage premium, partially mitigated by high mobility between informal and formal employment status.

### Determinants of informality (individual-level)
- Higher likelihood of being informally employed is associated with:
  - Less education
  - Being young
  - Being male
  - Lacking work experience
  - Living in rural areas
  - Working for a nonregistered firm (especially non-FDI firms)
- Among determinants, the most important for obtaining formal employment are education, work experience, and working in a registered (formal) firm.

### Policy drivers and differential impacts
- Policy-relevant findings:
  - Education, training, and business formalization are important for individuals to find formal jobs.
  - Reforms encouraging business registration (for example, by reducing entry costs for start-ups and securing property rights) can play a key role in encouraging labor formality.
- Structural reforms can have differential impacts across workers:
  - Workers with low levels of education benefit disproportionately from reforms that strengthen property rights (access to land, law and orders, corruption control) that encourage greater firm formalization.
  - Better labor training and efforts to reduce skill mismatches have a positive and significant impact on tackling informal employment among the young, and for workers in urban as compared to rural areas.

### Contribution to literature
- The paper contributes to literature on market segmentation, wage gaps, and mobility between formal and informal employment, and tests the “two-tier” hypothesis for Vietnam.
- Complements existing Vietnam literature by focusing on worker-level informality determinants and implications, and by empirically examining the role of investment climate and economic governance using regional variation.

*Source: wpiea2020273-print-pdf, https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020273-print-pdf.pdf*

### Section 5 concludes.

### Section 5 concludes.

### Definitions and Data Used
- Informality discussed as firm informality (firms operating outside legal/regulatory frameworks) and labor informality (working conditions: lack of long-term contracts and access to social insurance).
- ILO (2018) definition used: workers informally employed if they either do not have a contract of more than three months or, if they have such a contract, do not participate in social insurance.
- Scope: non-agricultural informal employment only.
- Data source: Vietnam Labor Force Survey (LFS).
- Economic sectors defined by economic ownership: the formal sector (registered firms), the informal sector, and the non-farming household sector.
- Employment status categories in LFS: (i) employer, (ii) own-account or self-employed worker, (iii) family-contributing worker, (iv) member of producers’ cooperatives, (v) wage or salaried worker.
- Employment shares (2018): wage workers 44 percent; own-account workers 39 percent; family-contributing workers 15 percent; employers 2 percent; members of producers’ cooperatives 0.1 percent.
- Informal-worker concept in this paper includes:
  - all employers working in non-regsitered firms,
  - own-account workers working in the informal or non-farming household sectors,
  - all family-contributing workers,
  - members of producer’ cooperatives working in the informal sector,
  - wage workers either not having a contract of more than three months or, if they have such a contract, not participating in social insurance.

### Trends and Stylized Facts on Informality in Vietnam
- Overall labor informality level: 56.2 percent in 2018.
- Sectoral concentration of informal employment (shares of total informal workers): wholesale and retail business 25 percent; construction 18 percent; food and beverage services 11 percent.
- Total number of workers working informally (2018): 19.3 million.
- Composition of informal employment by firm registration: nearly a third of informal workers were employed by registered firms in 2018.
  - Within informal employment in formal firms: wholesale and retail business 23 percent; food and beverage services 8.9 percent; transportation, textiles and garments noted as affected sectors.

### Social Insurance Coverage
- Two types of insurance: compulsory (covers sickness, labor accidents, pensions, death, and unemployment) and voluntary (covers pensions and death).
- Access to compulsory insurance: only 35 percent of non-farm workers overall have access.
- Non-participation in social insurance among informal workers is universal.
- Low compulsory-insurance coverage partly due to non-requirement of employers and own-account workers to participate and potential non-compliance by firms to reduce labor costs.

### Education, Skill Mismatch, and Worker Characteristics
- Informal-employment prevalence by education:
  - Almost 80 percent of workers with only a primary education or lower tend to be in informal employment.
  - Tertiary-educated workers in informal employment: 13 percent.
  - Of tertiary-educated informal workers, 66 percent are young (ages 20–34).
- Skill mismatch:
  - In 2018, more than half of informal workers were not trained for their jobs.
  - Only 31 percent of informal workers reported doing jobs matching their learning and/or training.
  - For formal workers, 68 percent reported working in areas that fit their background and experience.
- Interpretation: informal salaried work acts as a point of entry for many educated young; share of tertiary-educated in informal employment declines sharply with age.

### Wage Distribution, Regressions, and Mobility
- Wage distribution (2015-2018): higher wage distribution for formal workers than informal workers; gap persists after controlling for age, education, year and industry fixed effects.
- LFS income definition: net income from primary job, including wages and overtime remuneration, bonus, and other welfare payment.
- Regression setup:
  - Two dummy variables: “formal” dummy and “informal at formal firms” dummy, compared to informal workers in the informal sector.
  - Pooled regressions (2015-2018) and panel regressions using quarterly panel data for 2017–2018 with individual fixed effects.
- OLS / pooled regression results:
  - Columns (1) and (2): formal workers are paid 42 log points, or 53 percent, more than informal workers when observables are not controlled for.
  - Formal workers are paid 67 percent more once sectoral differences are accounted for.
  - After adding age, education and years of experience, the wage premium of formality falls from 67 percent to 51 percent (41.1 log points).
  - Age, education and years of experience account for roughly 25 percent of the overall formal-informal wage gap.
- Panel regression results with individual fixed effects:
  - Wage premium reduced to 8 log points.
  - Implied that 86 percent of the wage premium can be explained by worker’s fixed characteristics: a given worker would earn 8 percent more if he moved to formal from informal employment.
- International comparison: Vietnam’s formal-informal wage gap similar to countries on lower end of gap (Mexico and Brazil reported 5 percent and 4 percent wage premium for formal workers, respectively).
- Workplace effect: almost no difference (only 1 percent) in earnings of informal workers regardless of their workplace (informal vs. formal firms).
- Labor-market mobility and segmentation:
  - Market-segmentation concept: uni-directional flow from formal to informal should dominate if barriers hinder movement to formal sector.
  - Using 2017–2018 quarterly flows among workers observed for at least two continuous quarters:
    - Around 4 percent of workers move from formal to informal jobs in a given quarter; a marginally higher proportion move in the opposite direction.
    - Around 2 percent of workers shift from informal self-employment into formal self-employment; same proportion move in the opposite direction.
    - Around 2 percent of workers move from informal to formal wage employment; the reverse flow accounts for a smaller proportion.
  - Appendix-related findings: most informal wage workers (95 percent) do not change their jobs within a quarter; formal self-employed workers have a 23 percent quarterly job-change rate.
- Caveats noted:
  - Panel wage-gap estimates use workers who switch sectors; gains for non-switchers may differ.
  - Panel follows a worker for at most four quarters; wage gaps reflect short-term gains and may not capture long-term gains from formalization.
  - Longer-span panel evidence (Vietnam Household Living Standards Surveys 2002, 2004, 2006) suggests informal wage penalties of 15 percent (Nguyen et al. 2013).

*wpiea2020273-print-pdf - Section 5 concludes.*

### 1.5 percent. Interestingly, the fluidity between informal and formal jobs mostly happens within a

### wpiea2020273-print-pdf - 1.5 percent. Interestingly, the fluidity between informal and formal jobs mostly happens within a

### Worker Mobility and Wage Dynamics
- Fluidity between informal and formal jobs mostly happens within a given employment status: workers do not move from self-employment to wage work (or the other way around) when they move from formal to informal employment (or vice versa).  
- Bidirectional movement between formal and informal employment provides a cushion against shocks but informal workers are likely worse off in terms of income and social protection.  
- Evidence on wage differentials and movements (Table 2):
  - Switchers from informal to formal have 13–16 percent higher informal wages than non-switchers before switching (Columns (1) and (2)).  
  - Moving to formal jobs increases their salaries by roughly 10 percent compared to wages received while working informally (Columns (3) and (4)).  
  - Workers who were formally employed but moved to informal employment were doing worse in terms of wages compared to those who remained formal (Columns (5) and (6)), even before joining informal employment.  
  - After moving from formal to informal, wages decline further by a marginal rate of 4 percent (Columns (7) and (8)).  
- Interpretation: Two-tier informal sector:
  - Lower-tier: low-skilled workers for whom entering formal employment may not be possible (market segmentation).
  - Upper-tier: skilled workers who can obtain formal jobs but choose informality based on a cost-benefit decision.

### Data and Methodology
- Data sources:
  - Vietnam Labor Force Survey (LFS), pooled for the 2015-2018 period.
  - Vietnam Provincial Competitiveness Index (PCI): firm-level survey covering about 13,000 enterprises across 63 provinces; weighted overall PCI plus ten sub-indices covering entry costs; land access and tenure; transparency and access to information; time costs of regulatory compliance; informal charges; competition environment and policy bias; proactivity of provincial leadership; business support services; labor policy and law and order. All indices normalized so higher values denote improvement.
  - Vietnam Provincial Governance and Public Administration Performance Index (PAPI): citizen survey covering 6 dimensions; use index of control of corruption as proxy for law enforcement.
  - Monthly average earnings and unemployment rate at provincial level from CEIC Data database.
- Empirical approach:
  - Dependent variable: dummy for informal employment.
  - Primary estimator: probit regressions.
  - Baseline model (1) includes individual and workplace characteristics: (i) highest education level, (ii) demographic characteristics (sex, marital status, age group), (iii) years of work experience, (iv) workplace characteristics (legality of workplace, existence of labor union, FDI vs. non-FDI), (v) location (rural/urban); fixed effects for regions, economic sectors, and years.
  - Extended model (2) adds provincial-level economic and policy variables Y (average earnings, PCI indices, PAPI).
  - Interaction model (3) includes X_selected * Y to test who benefits most from policy changes.

### Drivers of Informality: Individual and Workplace Characteristics
- Baseline model findings (Table 4 and discussion):
  - Higher likelihood of being informal for: less educated, young, male, single, rural workers.
  - Education and work experience are the most important individual drivers.
    - High school graduates: probability of working informally is 10 percent lower than those without high-school education.
    - More than 5 years of work experience reduces likelihood of being informal by roughly 20 percent compared to a person with less than one year of experience.
  - Workplace characteristics:
    - Working in a formal firm, especially with FDI or a labor union, strongly reduces informality.
    - Working in formal firms can reduce the likelihood of informality by as much as 60 percent.

### Role of Policy Variables and Robustness
- Results from policy-augmented model (Table 5):
  - Average earnings coefficient is negative: higher income associated with lower probability of being informal.
  - Weighted PCI index coefficient is significantly negative: improving governance and transparency reduces informality.
  - Disaggregated PCI groups:
    - Reducing entry barriers and securing property rights reduce likelihood of informality (both statistically significant).
    - Support policy (business support) not statistically significant in general, but results vary in robustness checks.
  - Robustness checks:
    - Dropping potentially endogenous individual characteristics: results robust; signs unchanged except support policies.
    - Controlling for provincial unemployment rate: confirms findings; coefficient of support policies becomes significantly positive in this check.
  - PAPI (control of corruption) supports evidence: better control of corruption and secure property rights lower likelihood of informality (Column 11).

### Heterogeneous Impacts: Who Benefits from Structural Reforms?
- Interaction model results (Table 6) — groups and policy responsiveness:
  - Less educated workers:
    - Benefit disproportionately from reforms that strengthen property rights (access to land, law and order, corruption control) and from support policies (business support, labor training).
  - Young workers (15-25 years old):
    - Labor training support has positive and significant impact in reducing informality among the young.
  - Rural workers:
    - Reforms that reduce entry costs and strengthen property rights help firms in rural areas formalize, creating formal employment opportunities.
    - Reforms improving labor training and business services benefit urban workers more.
  - Non-FDI sector:
    - Support policies (better access to business services and labor training) disproportionately lower informality in the non-FDI sector.

### Policy Implications and Recommendations
- Promote business formalization:
  - Reduce entry costs for start-ups.
  - Secure property rights (land access, law and order, control of corruption).
  - Business formalization linked to greater formal employment and higher wages.
- Strengthen human capital and labor market policies:
  - Invest in education, job training, and life-long learning.
  - Active labor market policies and targeted training for young and low-experience workers.
  - Ongoing workforce upgrading crucial for productivity and modern sector skills.
- Tailor reforms to worker groups:
  - Less educated, rural, and unregistered-firm workers: prioritize property-rights strengthening and entry-cost reduction.
  - Young and urban workers: prioritize labor training and skill-matching programs.
  - Non-FDI firms: improve access to business support services and labor training.
- Recognize limits of single-policy solutions:
  - Business formalization alone is not sufficient given the large share of informal employment inside formal firms.
  - Future research: examine the role of regulations, social security contributions and minimum wages on informality in Vietnam.

### Key Statistics and Table Highlights
- Wage and mobility statistics:
  - Switchers' informal wage advantage pre-formalization: 13–16 percent.
  - Wage increase upon formalization: roughly 10 percent.
  - Wage decline upon informalization from formal: marginal 4 percent.
- Labor market magnitudes and regression outputs:
  - Observations in key regressions:
    - Table 1 observations: 1,030,399; 1,030,384; 1,030,089; 1,030,074; 266,276; 266,276.
    - Table 2 observations vary by column: 106,491; 18,120; 102,463; 16,049.
    - Table 4 observations: 1,110,530; 1,110,530; 1,110,515.
    - Table 5 and Table 6 observations: 1,110,515 each.
  - Table 4 marginal effects (logit/probit coefficients reported):
    - underedu (<high school): 0.766***, 0.727***, 0.618*** across columns.
    - young (15-25 years old): 0.143***, 0.151***, 0.148***.
    - female: -0.180***, -0.176***, -0.113***.
    - registered firm: -3.813***, -3.787***, -3.691***.
  - Table 5 policy coefficients (Column (1)–(4)):
    - average earnings: -0.0617***, -0.0738***, -0.0840***, -0.0705***.
    - Weighted PCI: -0.00467***.
    - entry barriers: -0.00319***.
    - property rights: -0.00520***.
    - support policy: 0.00104 (not statistically significant in main specification).
  - Table 6 interaction highlights:
    - policy_variable main effects: Weighted PCI -0.0400***; Entry barriers -0.00326 (ns); Property rights -0.0174***; Support Policies -0.0156**.
    - underedu*policy_variable: -0.0177*** (Weighted PCI), 0.00695*** (Entry barriers), -0.00189*** (Property rights), -0.0146*** (Support Policies).
    - rural*policy_variable: 0.00381*** (Weighted PCI), -0.00921*** (Entry barriers), -0.00570*** (Property rights), 0.00903*** (Support Policies).

*Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020273-print-pdf.pdf*

### Appendix Table 1: Worker Mobility between Formal and Informal Employment

### Appendix Table 1: Worker Mobility between Formal and Informal Employment

### Note on sample and methodology
- The table only account for workers who are both working in non-farm employment for two continous quarters.  
- Source: authors’ calculations.

### 2018Q1: Transition matrix (row = origin; column = destination)
- Formal wage employment → Formal wage employment: 95.8
- Formal wage employment → Formal self-employment: 0.2
- Formal wage employment → Informal wage employment: 3.7
- Formal wage employment → Informal self-employment: 0.2
- Formal wage employment row total: 100.0

- Formal self-employment → Formal wage employment: 0.6
- Formal self-employment → Formal self-employment: 79.9
- Formal self-employment → Informal wage employment: 1.9
- Formal self-employment → Informal self-employment: 17.5
- Formal self-employment row total: 100.0

- Informal wage employment → Formal wage employment: 6.3
- Informal wage employment → Formal self-employment: 0.7
- Informal wage employment → Informal wage employment: 89.7
- Informal wage employment → Informal self-employment: 3.3
- Informal wage employment row total: 100.0

- Informal self-employment → Formal wage employment: 0.3
- Informal self-employment → Formal self-employment: 7.9
- Informal self-employment → Informal wage employment: 4.2
- Informal self-employment → Informal self-employment: 87.6
- Informal self-employment row total: 100.0

- Cross-quarter employment distribution (column totals): Formal wage employment: 35.5; Formal self-employment: 11.0; Informal wage employment: 26.7; Informal self-employment: 26.8; Total: 100.0

### 2018Q2: Transition matrix (row = origin; column = destination)
- Formal wage employment → Formal wage employment: 95.7
- Formal wage employment → Formal self-employment: 0.2
- Formal wage employment → Informal wage employment: 3.8
- Formal wage employment → Informal self-employment: 0.3
- Formal wage employment row total: 100.0

- Formal self-employment → Formal wage employment: 0.8
- Formal self-employment → Formal self-employment: 80.9
- Formal self-employment → Informal wage employment: 2.0
- Formal self-employment → Informal self-employment: 16.3
- Formal self-employment row total: 100.0

- Informal wage employment → Formal wage employment: 6.9
- Informal wage employment → Formal self-employment: 0.8
- Informal wage employment → Informal wage employment: 89.0
- Informal wage employment → Informal self-employment: 3.3
- Informal wage employment row total: 100.0

- Informal self-employment → Formal wage employment: 0.4
- Informal self-employment → Formal self-employment: 7.0
- Informal self-employment → Informal wage employment: 3.4
- Informal self-employment → Informal self-employment: 89.1
- Informal self-employment row total: 100.0

- Cross-quarter employment distribution (column totals): Formal wage employment: 35.1; Formal self-employment: 11.2; Informal wage employment: 26.3; Informal self-employment: 27.4; Total: 100.0

### 2018Q3: Transition matrix (row = origin; column = destination)
- Formal wage employment → Formal wage employment: 95.6
- Formal wage employment → Formal self-employment: 0.3
- Formal wage employment → Informal wage employment: 3.9
- Formal wage employment → Informal self-employment: 0.3
- Formal wage employment row total: 100.0

- Formal self-employment → Formal wage employment: 1.1
- Formal self-employment → Formal self-employment: 76.7
- Formal self-employment → Informal wage employment: 2.5
- Formal self-employment → Informal self-employment: 19.6
- Formal self-employment row total: 100.0

- Informal wage employment → Formal wage employment: 7.2
- Informal wage employment → Formal self-employment: 0.9
- Informal wage employment → Informal wage employment: 88.5
- Informal wage employment → Informal self-employment: 3.4
- Informal wage employment row total: 100.0

- Informal self-employment → Formal wage employment: 0.6
- Informal self-employment → Formal self-employment: 7.1
- Informal self-employment → Informal wage employment: 3.9
- Informal self-employment → Informal self-employment: 88.4
- Informal self-employment row total: 100.0

- Cross-quarter employment distribution (column totals): Formal wage employment: 35.6; Formal self-employment: 10.7; Informal wage employment: 26.5; Informal self-employment: 27.2; Total: 100.0

*Source: authors’ calculations.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020273-print-pdf.pdf_