Abstract
Informal employment accounts for about two-thirds of employment in Sri Lanka, and has been adversely affected by the COVID-19 pandemic. Revenues, employment, and salary expenditures of micro, small, and medium enterprises declined substantially during the lockdown, and the decline was more severe in micro informal enterprises. The authorities’ COVID-19 relief helped mitigate the adverse impact, but it remained small compared to household income and expenditure, calling for revenue mobilization to provide fiscal space to support the poor and vulnerable groups.
The Informal Sector and the Impact of the Covid-19 Pandemic in Sri Lanka1
Informal employment accounts for about two-thirds of employment in Sri Lanka, and has been adversely affected by the COVID-19 pandemic. Revenues, employment, and salary expenditures of micro, small, and medium enterprises declined substantially during the lockdown, and the decline was more severe in micro informal enterprises. The authorities’ COVID-19 relief helped mitigate the adverse impact, but it remained small compared to household income and expenditure, calling for revenue mobilization to provide fiscal space to support the poor and vulnerable groups.
1. This study presents the characteristics of the informal sector in Sri Lanka and the impact of the COVID-19 pandemic. The informal sector has played an important role in Sri Lanka, contributing to economic growth, absorbing employment, and providing income and a safety net for millions of people. Informal economic activities are typically small-scale, unregistered, and not covered by regulations, including on occupational safety, health, and social protection. The sector has low productivity, low rates of savings and investment, and limited capital accumulation, making it vulnerable to economic shocks. Moreover, the COVID-19 economic shutdown has affected both formal and informal sectors at the same time, preventing adjustment and resource allocation from the formal to the informal sector. The first section of this paper describes the concept, stylized facts, and determinants of informality; the second section provides the COVID-19 impact on the informal sector; and the third section discusses the authorities’ COVID-19 relief measures.
A. The Concept of Informality and Stylized Facts in Sri Lanka
Definition and Measurement
2. The informal sector is defined as a group of production units in the economy that are not captured by formal arrangement in terms of regulations and institutions. While the informal sector refers to production units, informal economy refers to activities by economic agents that are not captured by formal arrangements, and informal employment refers to jobs under informal arrangements. Economic activities in the informal sector are mostly legal but are not captured by official statistics for various reasons, such as the absence of tax payments and social security contributions and the exclusion from regulation such as company or employment laws. Measuring informal economic activities is challenging since they are undetected and previous studies have utilized direct and indirect methods. The direct approach is mostly based on surveys and samples, relying on voluntary replies or tax auditing, and other compliance methods. The indirect approach uses indirect information, such as the number of informal jobs or informal enterprises as a proxy for the informal economy. Recent literature uses Multiple Indicator Multiple Cause (MIMIC) models that treat the informal economy as an unobserved component to be estimated based on observable causes and effects (Medina and Schneider, 2019).
3. This study uses informal employment indicators developed by the International Labor Office (ILO) and applied to national labor force and household survey data collected by Department of Census and Statistics (DCS). Based on ILO classification and DCS data, informal employment is measured as the number of informal jobs carried out in formal enterprises, informal enterprises, or households. These include employees holding informal jobs, employers, and own-account workers employed in their own informal sector enterprises or households; members of producers’ cooperatives; and contributing family workers in formal or informal sector enterprises (ILO, 2013). The formal or informal enterprises are classified based on criteria such as the number of employees, whether the enterprise is registered, and whether the employees are informal or registered.
The Informal Sector in Sri Lanka
4. Based on the concept of informality above, informal employment contributed to two thirds of total employment in Sri Lanka (Table 1, Figure 1). In 2019, about 5.5 million (67 percent) of total 8.2 million employed in Sri Lanka were considered informal.2 These workers are neither subject to national labor legislations and income tax nor entitled to social protection and employment benefits. They are not registered with the Inland Revenue Department (IRD) and Employment Provident Fund (EPF), do not have formal financial accounts, do not have EPF accounts, or do not have 10 or more employees. An important feature of informal employment in Sri Lanka is that a significant share of workers (0.8 million, 9 percent of total employment or 22 percent of formal sector employment) has informal contractual relationships while working in formal enterprises. They work in the formal sector but without contribution to social security programs.
Sri Lanka: Formal and Informal Employment by Sector – 2019
(Number of Employment in thousands, unless otherwise indicated)
Sri Lanka: Formal and Informal Employment by Sector – 2019
(Number of Employment in thousands, unless otherwise indicated)
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Sri Lanka: Formal and Informal Employment by Sector – 2019
(Number of Employment in thousands, unless otherwise indicated)
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5. Formal employment contributed to the remaining one third of total employment, with a 40:60 percent split between the public and private sectors. In 2019, total formal employment was about 2.7 million, comprising public sector employment (excluding the armed forces) of about 1.2 million and private sector employment of 1.5 million (including employers and self-employment). The low share of formal employment in the economy indicates that a large segment of workers is excluded from social security programs and other benefits from formal employment contracts. It also implies a smaller tax base, posing a challenge in mobilizing revenues and financing public goods.
Sri Lanka: Population and Employment Status
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Labor Force Survey 2019, Department of Census and Statistics6. Informal employment in Sri Lanka is concentrated in the primary and trade sectors and has remained persistent for the past two decades (Figures 2 and 3). Sectors with the highest share of informal employment include agriculture, forestry, and fisheries sectors, followed by craft and related trade sectors such as construction, mining, textiles, and elementary occupations such as street vendors, domestic workers, and daily wage earners. Informal employment has stayed around 70 percent during 2000-17, broadly comparable to the world average in emerging and developing economies, but lower than the South Asian average of 79 percent (Figure 3). Contributing factors would include: (1) the smaller agriculture sector in Sri Lanka compared to South Asian peers such as Nepal, India, and Bangladesh, and (2) the relatively higher level of education in Sri Lanka which generally correlates with lower informality.
Sri Lanka: Informal Employment by Occupation
(Percent of Total Employment in Occupation)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Labor Force Survey 2019, Department of Census and Statistics.Informal Employment in South Asia, 2000-17
(Percent of Total Employment)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: ILOSTAT.1/ Emerging market and developing economies.7. Our empirical analysis of the determinants of informality in South Asia identifies several factors that could explain the level of informality in Sri Lanka (Annex 1). The empirical results show that income inequality and tax burden tend to increase informal employment, while education, government effectiveness, labor freedom, and business freedom tend to lower it. The negative impact of education on informality and the relatively higher level of education in Sri Lanka could explain the lower levels of employment informality in Sri Lanka compared to its South Asian peers. On the other hand, stringent labor laws and lack of enforcement have contributed to persistent informality in Sri Lanka. For example, employment termination in Sri Lanka involves high severance pay cost to the employer which are difficult to enforce, reducing job creation in the formal sector (World Bank, 2020). Moreover, mandatory social security contributions by private sector employers to EPF and ETF make formal employment costly. Similar to other South Asian countries, poor business environment, land tenancy issues, complex business registration processes, and poor access to finance are often cited in the literature as barriers to formalization in Sri Lanka (de Mel et al, 2012).
8. Our empirical results above help identify policies to facilitate transition of informal workers and firms to the formal sector in Sri Lanka. The transition to the formal sector would improve productivity, increase potential growth, raise tax revenues, and provide labor protection, but a gradual and balanced approach is crucial as the informal sector represents the only source of income and critical safety net for millions of people (IMF, 2021). Based on our empirical findings above and Sri Lanka’s current business environment, the relevant policies include: 1) Investing in human capital including equal access to education; 2) Reforming labor laws to promote formal employment and reduce labor-related transaction costs; 3) Improving the business, trade, and investment regimes to promote trade and business freedom; 4) Increasing access to finance; and 5) Strengthening the quality of public service and governance to facilitate formal economic activities.
B. The Impact of COVID-19 on the Informal Sector
9. Sri Lanka experienced three COVID-19 waves from March 2020 to December 2021 (Figure 4). During the first wave (March–September 2020), the authorities implemented strict containment measures that helped contain the infection, including airport closure, island-wide lockdowns, contact-tracing, mandatory quarantine, and isolation of high-risk areas (including a 4,000-personnel Navy camp). However, a cluster that emerged from a garment factory in the Gampaha district led to a second wave in October 2020, resulting in a lockdown of high-risk areas, inter-provincial travel bans, limitation of public and private functions, and restriction of inbound flights, while agricultural and export sectors were permitted to resume activities. Cases started to decline significantly in January 2021 amid the commencement of vaccinations, before the third outbreak following the national new year holidays in April 2021. Cases peaked in May 2021 and led to a lockdown through June 2021. Cases started to rise again in August, largely due to the spread of the more transmissible Delta variant and led to a lockdown during August–October 2021. Cases then declined alongside a strong vaccination drive with over 63 percent of the population fully vaccinated, and a further 18 percent of the population having received the booster (third dose) by December 2021.
Sri Lanka: Daily Covid-19 Cases and Fatalities
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Our World in Data.10. The COVID-19 impact is expected to be more severe in the informal sector, partly due to its reliance on physical operations and lack of savings or access to finance. Frequent lockdowns and travel restrictions reduced activities that require workers to be physically present, particularly construction, tourism, transport, education, hotels, and restaurants, hurting informal workers in those sectors. Many informal workers also miss the opportunity of a flourishing online business, such as food delivery, due to their limited infrastructure and capacity. In addition, low-wage informal workers tend to have little savings or less access to finance, thus less cushion to absorb losses or smooth out consumption.
11. Informal workers also receive less protection from labor regulations due to gaps in labor legislation and weak law enforcement in the informal sector. Although Sri Lankan labor laws seek to protect all workers, some components of the law exclude informal workers. For example, provisions of the Termination of Employment of Workmen Act (TEWA) and the Payment of Gratuity Act generally apply to enterprises with 15 or more workers. Thus, workers engaged in smaller, informal establishments lack protection and compensation against sudden dismissals by an employer, like in the case of COVID-19. Informal workers also have limited protection since the unemployment and retirement benefits in Sri Lanka rely on payment by the employer at the end of the contract. Workers in informal establishments are also vulnerable due to limited enforcement of labor laws due to their lack of visibility.
12. Preliminary data suggest that the COVID-19 pandemic would reverse recent progress in poverty reduction and widen inequalities. The World Bank (2021) estimates that the job losses due to COVID-19 are expected to have increased the $3.2/day poverty rate in Sri Lanka from 9.2 percent in 2019 to 11.7 percent in 2020. This would reverse progress since 2016 and push 500,000 people into poverty, particularly those from urban areas and sectors affected by the pandemic. Estimates based on the $1.90/day (extreme) poverty line suggest that the poor in Sri Lanka have also fallen into deeper poverty in the wake of the pandemic. Earnings losses have been disproportionately spread across the income distribution, with richer households experiencing minor earnings losses compared to the bottom 40 percent (World Bank, 2021), likely exacerbating income inequalities.
13. We use primary survey data collected by the DCS to assess the impact of COVID-19 in Sri Lanka. A representative sample of 17,469 enterprises was used to capture the 1.36 million enterprises belonging to the micro, small, and medium enterprises (MSME) sector based on the 2013 Economic Census Listing Database classification (Table 2). Within the MSME, we use the size of enterprises as a criterion for informality and assume enterprises, with 1-4 persons employed, as micro enterprises, while the rest of the SMSE enterprises in the survey as small and medium enterprises (SMEs). The micro enterprises are considered to be more informal in nature than the SMEs. The first phase of the DCS survey covers the period January–May 2020 and collects data on firm revenue, employment, and expenditure on salaries before and after the onset of the pandemic in March 2020.
Sri Lanka: Responses to the Survey by the Department of Census and Statistics (DCS), 2020
Sri Lanka: Responses to the Survey by the Department of Census and Statistics (DCS), 2020
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Sri Lanka: Responses to the Survey by the Department of Census and Statistics (DCS), 2020
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14. Revenue data indicate a substantial negative impact of COVID-19 on the MSME sector, with a more severe impact on the micro enterprises (Figures 5 and 6). The average revenue in the MSME sector during March–May 2020 fell by 57 percent from the same period last year, and the decline was much steeper for the micro enterprises (61 percent) compared to the SMEs (48 percent). The steepest decline took place during the height of the first COVID wave in April 2020, before recovering slightly in May as soon as travel restrictions were relaxed, indicating the resilience of the sector. These results are broadly consistent with the preliminary survey conducted by the Ministry of Labor in May 2020 that found that smaller firms were more likely to close operations and lay off workers, while larger firms demonstrated a higher level of resilience to the pandemic by continuing to operate, albeit at lower capacity (Wimalaweera, 2020).
Sri Lanka: Average Revenue of Micro Enterprises
(In thousands of rupees)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Department of Census and Statistics.Sri Lanka: Average Revenue of Small & Medium Enterprises
(In thousands of rupees)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Department of Census and Statistics.15. The sectoral comparison reveals that the education, accommodation, food, administrative services, construction, transport, and manufacturing sectors were among the hardest hit (Figures 7 and 8). Furthermore, the disproportionate impact of the pandemic on the micro enterprises compared to the SMEs during the first wave in March–May 2020 was more apparent in the manufacturing, transport, and administration sectors. In contrast, the SMEs were hit harder than the micro enterprises in the ICT and financial and insurance service sectors. The results are generally consistent with the fact that the tourism sector, where three quarters of the labor force is estimated to be informal (ILO, 2020), was the earliest affected sectors and will likely take the longest to recover, with possible spillovers to the hospitality and food and beverage industries. Lockdowns and travel restrictions clearly hampered transport, mining, construction, and entertainment, while supply chain disruptions affected the manufacturing sectors such as textile and garment.
Sri Lanka: Average Revenue of Micro Enterprises by Sector, March-May 2019-20
(In thousands of rupees/percent (RHS))
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Department of Census and Statistics.Sri Lanka: Average Revenue of Small & Medium Enterprises, by Sector, March-May 2019-20
(In thousands of Rupees/ percent(RHS))
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Department of Census and Statistics.16. Employment in the MSME sector declined substantially during the COVID-19 lockdown. COVID (Figure 9). The DCS survey data show that employment in the MSME sector fell by 64 percent during the first wave in March–May 2020. Nonetheless, the data also indicate the resilience of the informal sector, reflected by some employment recovery as soon as the lockdown restrictions were relaxed in May 2021. This is consistent with the Ministry of Labor 2020 survey showing that 64 percent of workers were not at work by May 2020 but only 9 percent of workers had lost their jobs or expected to be laid off. The UNICEF-UNDP survey conducted in May– December 2020 also found that 16 percent of households lost their incomes due to job losses, while 57 percent faced a decline in income due to fewer hours of work, travel restrictions, or illness (UNICEF & UNDP, 2020).
Sri Lanka: Average number of persons employed per establishment, January - May 2020
(Number of persons)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Department of Census and Statistics.17. The decline in salary expenditures mimics the employment trend with a sharper decline in micro enterprises (Figure 10). These outcomes are consistent with the UNICEF-UNDP survey showing that the COVID-19 impact has been particularly hard on daily and weekly wage earners with informal contracts as more than 95 percent have lost their incomes or have experienced pay-cuts. The World Bank (2021) also indicated that low-waged informal workers were more vulnerable during the pandemic as job and earning losses concentrated in the lower-middle of the income distribution, according to preliminary data. Workers on the higher end of the distribution are likely to have formal contracts, access to paid leave, better protection by labor laws, and better connectivity infrastructure that enable them to work remotely. Meanwhile, low-waged informal workers face greater risk of losing jobs and have limited savings, access to finance, or severance pay, thus widening existing labor market inequalities.
Sri Lanka: Average Expenditure on Salaries, January - May 2020
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Department of Census and Statistics.C. The Impact of COVID-19 Relief Measures on the Informal Sector
18. The authorities implemented various COVID-19 relief measures in 2020 to mitigate the adverse impact on low-income households and small businesses. In addition to the regular welfare and subsidy programs, the authorities allocated Rs. 117.5 billion3 (0.8 percent of GDP) in 2020 to finance the COVID-19 support package (Table 3). A large component of this, about Rs. 79 billion (0.5 percent of GDP), was in the form of cash transfers to poor and vulnerable households. The remaining funds were used to facilitate quarantine processes, improve health infrastructure, support state-owned enterprises (SOEs), and provide emergency funding for agriculture, IT, education, and transport sectors. In a cross-country comparison, however, the COVID-19 related spending is low compared to South Asian peers (Figure 11). A further Rs. 192 billion (1.2 percent of GDP) was allocated in 2021, of which Rs. 18.5 billion (0.1 percent of GDP) was for cash transfers to selected families in April 2021 and the remaining funds for vaccination, quarantine, medical supplies and infrastructure, and other COVID-19 measures.
Government Expenditure on Covid-19 in South Asia1/
(In percent of 2020 GDP)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Data base of Fiseal Policy Response, to Covid-19.IMF Fiscal Affairs Department (July, 2021).1/ Insufficient data for Bhutan and NepalSri Lanka: Allocations for COVID-19 Support Measures by the Government, 2020
19. Existing Social Safety Net (SSN) programs and networks were used to provide COVID-19 relief, substantially increasing SSN spending to 0.9 percent of GDP in 2020 from 0.4 percent on average during 2015-19 (Figure 12). The SSN programs include poverty targeted cash transfers such as Samurdhi and illness allowances; social pensions such as the elderly or disability allowances; and emergency cash or in-kind transfers during natural disasters. The Samurdhi program remains the largest SSN program, benefitting nearly 1.8 million households (33 percent of total households) in the form of monthly cash grants and several savings and credit schemes targeted at informal entrepreneurs and own-account workers. The authorities provided cash transfers of Rs. 5,000/month during the first (April–May 2020) and second (October 2020) waves of the pandemic to existing and waitlisted or newly identified beneficiaries of the existing SSN programs, in addition to livelihood support and in-kind transfers to poor and vulnerable households excluded by the above programs. In addition to these COVID-19 relief spending in the budget, the authorities introduced other policies to support individuals and small businesses, including the informal sector.4
Sri Lanka: Spending on Social Safety Net Programs, 2010-20
(In percent of GDP)
Citation: IMF Staff Country Reports 2022, 341; 10.5089/9798400222771.002.A002
Source: Ministry of Finance.20. Early evidence suggests that these COVID-19 relief measures helped mitigate the impact of the pandemic on poor and vulnerable households. While it is too early to estimate the precise impact, the COVID-19 relief reached around 6.1 million people (Table 3) in 3.6 million households or 66 percent of total households since more-than-one recipient in each household may receive the benefit (UNICEF, 2020a). World Bank estimates suggest that these measures have the potential to buffer the impact on poor households by reducing the share of population living under the $3.2 poverty line by 1.4 percent from the estimated baseline under COVID-19 of 11.7 percent in 2020.
21. Data on sectoral distribution revealed that a larger proportion of workers in the primary sectors benefitted from the COVID-19 support. UNICEF (2020b) used household income and expenditure survey (HIES) data to estimate the share of workers receiving COVID-19 support by occupation (Table 4, Column 3). The study finds relatively good coverage among elementary occupations and skilled agricultural, forestry, and fisheries sectors which tend to have a higher share of informal workers. In contrast, professionals, clerical workers, technicians, and armed forces, that are largely formal occupations, are less likely to have received support.
Sri Lanka: Distribution of COVID-19 Support by Occupation
(In percent)
22. Despite this positive outcome, the size and duration of these relief measures remain small compared to household income and expenditure. The cash allowance of Rs. 5,000 accounts for only 12.8 percent of monthly expenditure of an average household (UNICEF, 2020b). It is also well below the average earnings of workers in the hardest hit sectors, where median monthly wages were around Rs. 32,000 for salaried workers and Rs. 20,000 for daily wage earners (ILO, 2020). Moreover, Rs. 5,000 only accounts for around 3.9 percent of the average monthly revenue (pre-pandemic) of micro enterprises, providing limited protection to self-employed and own-account workers. Furthermore, poorer households tend to be larger in size and therefore received lower transfers per person. The support level was not sustained during subsequent waves of the pandemic. In the meantime, many households faced depressed incomes for a prolonged period, beyond the implementation period of the relief measures. Many lower-income households had to resort to alternative financing options such as borrowing from relatives and selling or pawning their belongings.
23. There are also gaps in coverage that exclude a large number individuals who need support. Although the relief measures reached 97 percent of the first (poorest) decile, it excluded 30 percent of middle-income earners who are close to the poverty line and are at risk of losing their incomes (ILO, 2020). Moreover, only 33 percent of households in urban areas and a small number of workers in the manufacturing sector were eligible for relief, meaning that many daily wage earners and those severely hit by the pandemic were likely excluded.
24. The preliminary findings above call for policy priorities as follows. In the near term, mobilizing revenue to provide adequate fiscal space to support the poor and vulnerable groups remain the top priority. This could be complemented by broadening the coverage of SSN programs to include the informal sector and improve targeting, allowing for support to be intensified during a crisis. Over the medium-term, the policies should focus on facilitating a gradual transition from the informal to formal sector to increase productivity, employment protection, and government revenues. These include investing in human capital, improving business and investment climate, simplifying registrations and regulations for new businesses, simplifying tax payments, reforming labor market and laws, and improving access to finance.
References
DCS. (2019). Sri Lanka Labor Force Survey - Annual Report 2019. Department of Census and Statistics.
De Mel, S., McKenzie, D., & Woodruff, C. (2012). The Demand for and Consequences of Formalization among Informal Firms in Sri Lanka. Cambridge, MA: National Bureau of Economic Research Working Paper 18019.
IMF. (2021). The Global Informal Workforce: Priorities for Inclusive Growth. Washington, DC: International Monetary Fund.
ILO. (2013). Measurement of the Informal Sector. Geneva: International Labor Office.
ILO. (2020). Social Protection and the COVID-19 crisis: Responses to support workers and their families in Sri Lanka. International Labour Organization; ILO Country Office for Sri Lanka and the Maldives, ILO Regional Office for Asia and the Pacific.
Medina, L., & Schneider, F. (2019). Shedding Light on the Shadow Economy: A Global Database and the Interaction with the Official One. Munich, Germany: CESifo Working Papers.
Ministry of Finance. (2021). Annual Report 2020. Colombo: Ministry of Finance, Sri Lanka.
Perry, G., Maloney, W., Arias, O., Fajnzylber, P., Mason, A., & Saavedra-Chanduvi, J. (2007). Informality: Exit and Exclusion. Washington DC: World Bank.
UNICEF. (2020a). Tackling the COVID-19 economic crisis in Sri Lanka: Providing universal, lifecycle social protection transfers to protect lives and bolster economic recovery. UNICEF Sri Lanka Working Paper. UNICEF.
UNICEF. (2020b). Sri Lanka’s Initial Social Protection Response to COVID-19: An analysis of who benefits and who does not. UNICEF Sri Lanka Policy Brief April 2020/01. UNICEF.
UNICEF & UNDP. (2020). COVID-19 Crisis: Household Impact, Sri Lanka Telephone Survey Round 4. UNICEF, UNDP.
Wimalaweera, A. (2020). COVID-19 and Beyond: The Impact on the labor market of Sri Lanka. Department of Labor, Sri Lanka.
World Bank. (2020). Informality, Job Quality, and Welfare in Sri Lanka. Washington, DC: The World Bank.
World Bank. (2021). The Long Shadow of Informality: Challenges and Policies. Washington, DC: The World Bank.
Annex I. Determinants of Informality in South Asia: Empirical Analysis
1. This annex presents the determinants of informality in South Asia by estimating empirical model that specifies informal employment as a function of explanatory variables (Table AI.1). The model is fitted on cross-country time series data using panel regression. Seemingly Unrelated Regression approach is also used to obtain parameter estimates for South Asia and other countries separately, and test whether the parameter estimates are statistically different between the two regions. The model is estimated based on 2000-17 data from 13 countries in South Asia (Bangladesh, India, Maldives, Nepal, Pakistan, and Sri Lanka) and other Asian countries (Cambodia, Indonesia, Lao PDR, Mongolia, Myanmar, Thailand, and Vietnam). The dependent variable is informal employment in the informal sector, and the choice of independent variables is motivated by the existing literature and data availability.
The baseline model specification is as follows:
Informal employmentit + α + β1 GDP per capitait + β2 Educationit +
β3 Gini indexit + β4 Government effectivenessit + β5 Tax burdenit +
β6 Labor freedomit + β7 Business freedom + β8 Trade freedomit + uit;
2. The results indicate that income inequality, tax burden, and labor freedom tend to increase informal employment in Asian countries in general, while education, government effectiveness, business freedom, and trade freedom tend to lower it (Table AI.2, Column 2-3). The positive coefficient on tax burden, reflected in both tax policies and administration, leads to larger informal employment in the region as firms and workers attempt to avoid high costs. The impact of labor freedom is also positive, suggesting that higher labor market flexibility can increase informal employment. Conversely, the impact of education (used as a proxy for national income) on informal employment is generally negative, indicating that a higher level of education and income would reduce informality. Similarly, the negative effects of government effectiveness, business freedom, and trade freedom suggest that better quality of public goods and services as well as stronger governance facilitate formal economic activity, while a conducive business environment and trade liberalization incentivize formalization.
Determinants of Informality: Description of Variables
Determinants of Informality: Description of Variables
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Determinants of Informality: Description of Variables
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3. More in-depth analysis shows that the effects of education, government effectiveness, and labor freedom differ between South Asia and other Asian countries (Table AI.2, Column 4-6). The negative impact of education on informality is more prevalent in South Asia. On governance, the result for South Asia supports the argument that better public governance lowers informal employment. In contrast, the impact in the other Asian countries support the notion that workers choose to remain informal if they could reap the benefits of better public goods and services regardless of their employment status (Perry et al., 2007). The negative impact of labor freedom on informal employment in South Asia shows that greater labor freedom reduces market segmentation and encourages labor movement from the informal to formal sectors. This suggests that promoting labor flexibility is important to facilitate labor transition to the formal sector.
Determinants of Informal Employment: Regression Results 1/
(Dependent variable: informal employment rate)
Determinants of Informal Employment: Regression Results 1/
(Dependent variable: informal employment rate)
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Determinants of Informal Employment: Regression Results 1/
(Dependent variable: informal employment rate)
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Prepared by Tubagus Feridhanusetyawan and Manavee Abeyawickrama, with contributions by Amitha Sundararaj.
Labor Force Survey 2019 is based on a nationwide two-stage stratified sample of 25,750 housing units. The survey covers persons living in housing units only and excludes the institutional population such as the armed forces.
This excludes COVID-19 spending by other ministries (e.g., the Ministry of Defense) and support for farmers and other institutions that were not reported as COVID-19 spending in the 2020 Annual Report of the Ministry of Finance.
Additional COVID-19 measures to support individuals and small businesses included debt moratoria, concessional working capital loans, and tax concessions for MSMEs, lending targets for priority sectors, a grace period for utility bill payments, and moratoria on lease payments.
