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Investigating Informal Employment and its Implications for Closing the Coverage Gap

5 th International Research Conference on Social Security March 5-7, 2007 Session 2.1 Addressing the Coverage Gap in Informal Employment. Investigating Informal Employment and its Implications for Closing the Coverage Gap in Trinidad and Tobago. TOPICS.

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Investigating Informal Employment and its Implications for Closing the Coverage Gap

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  1. 5th International Research Conference on Social SecurityMarch 5-7, 2007Session 2.1 Addressing the Coverage Gap in Informal Employment Investigating Informal Employment and its Implications for Closing the Coverage Gap in Trinidad and Tobago

  2. TOPICS • Conceptualizing and estimating informal employment • Key findings • Gender structures characterizing self-employment in Trinidad and Tobago • Characteristics of self-employment by industry and occupation • Implications for closing the coverage gap

  3. CONCEPTUALIZING INFORMAL EMPLOYMENT • Informal employment IE is understood in contrast to formal employment FE • FE = standard employment relation SER = paid employees in standard jobs SJ • SER 1st order distinction: paid employees PE implies self-employed workers SEW = IE • SER 2nd order distinction: PE in SJ (national norms) implies PE in nonSJ = non-standard employees NSM = IE • Conclusion: IE = SEW + NSM

  4. ESTIMATING INFORMAL EMPLOYMENT BY SUCCESSIVE APPROXIMATIONSUSINGHOUSEHOLD DATA FIELDS • Maximum IE, MIE = NIP – ACE, where NIP is non-institutional population (> 15 years old, so excludes child labour) and ACE is active employees (on whose behalf employers make contributions to national insurance) • Broad IE, BIE = TLF - ACE, where TLF is total labour force • Broad self-employment, BSE = SEWLF, where SEWLF is self-employed workers in the labour force • Broad non-standard employees, BNSM = TLF - (BSE + ACE) = BIE-BSE • Narrow IE, NIE = PWJ – ACE, where PWJ is persons with jobs • Narrow self-employment, NSE= SEWJ, where SEWJ is SEW with jobs • Narrow non-standard employees, NNSM = PWJ - (NSE + ACE) • Data on the above (except ACE) is generated through continuous probabilistic sampling surveys of households as undertaken by the Central Statistical Office. ACE is administrative data generated by NIBTT.

  5. ESTIMATING INFORMAL EMPLOYMENT BY USING DATA FIELDS FROM BUSINESS ESTABLISHMENT SURVEYS • Informal Establishment Employment, IEE = • Sole trader employment, STE ; plus • Micro-enterprises employers, MER; plus • Paid employees of micro-enterprises, PME • Summarizing: IEE = STE + MER + PME • Data on the above is generated by the CSO’s Business Survey Establishment Register (BSER)

  6. WHAT MAKES OUR ESTIMATION METHODOLOGY DIFFERENT • Our concern here is not the “informal economy” nor “informal sector” perse, so we sought an alternative to the “residual” and other approaches to estimating IE (see ILO Decent Work and the Informal Economy and Women and Men in the Informal Economy: a Statistical Picture, 2002.) • Our informal employment estimation methodology involves projecting key proportions from business data fields (serving as partial surrogates for household categories) into household data fields.

  7. KEY PROPORTIONS FROM 2005 BUSINESS ESTABLISHMENT SURVEY STE/IEE = 21.1% MER/IEE = 22.6% PME/IEE = 56.3% PME/MER = 2.487 PME/(MER+STE) = 1.288 IEE/TEW = 24.2% , where TEW is total engaged workers (per BSER) PME/TPE = 15.3%, where TPE is total paid employees (per BSER) PME/TEW = 13.6%

  8. PROJECTIONS FROM BUSINESS ESTABLISHMENT FIELDS INTO HOUSEHOLD FIELDS • It seems reasonable to use IEE/TEW as a proxy for IEE/PWJ and use it to generate a projection of IE from Household PWJ data. • Likewise it seems appropriate to use PME/TEW as surrogate for NSM/PWJ, and • PME/TPE for NSM/EMPE and generate projections of NSM from household data on persons with jobs and on paid employees. • Projections of NSM can also be generated out of the SEW sub-segment MPR from PME/MER and out of SEW from PME / (MER+STE).

  9. KEY FINDINGS ON THE EXTENT OF INFORMAL EMPLOYMENT IN TRINIDAD AND TOBAGO Population 1,294,494 NIP 979,000 TLF 623,600 PWJ 573,900 ACE 460,827 OAW 84,800 EMR 25,300 NSM (projected) 48,120 IE (projected) 148,326 • Active employees ACE & non-standard paid employees NSM sum to 508,947; the addition of SEW sums to 619,047 and is consistent with the 623,600 figure for the labour force. • The 508,947 paid employees constitute 81.6% of the labour force, with the formal segment (ACE) 73.9% and the non-standard segment 7.7%.

  10. KEY FINDINGS ON THE EXTENT OF IE (continued) • NSM account for 9.5% of paid employees or 10.4% of the number of formal employees; approximately one out of every ten paid employees is in IE, and there is one paid employee in IE for every ten in formal employment. • Some 23.8% of the labour force and 25.9% of PWJ are engaged in IE, while 7.7% of the labour force and 8.4% of PWJ are more specifically among the non-standard paid employee segment of the informally employed. • Roughly 32% of IE are paid employees rather than SEW. • For every one paid employee engaged in informal employment, there are 2.3 SEW.

  11. SEW GENDER STRUCTURES • Among women with jobs, 14% (32,700)are self-employed workers SEW. Among men with jobs, 23% are SEW. • While women account for 40% of persons with jobs, they account for only 30% of SEW, implying a higher dependence on/access to formal paid employment (especially public sector) than is the case for men. • Less than one (0.9) out of every three SEW was a woman. For every female SEW, there are 2.37 male SEW. Among SEW, women account for 32% of OAW but only 23% of MPR. Among OAW, 31% are women, and for every female OAW, there are 2.27 male OAW.

  12. GENDER STRUCTURES (continued) • Self-employment is relatively more prominent among men than women. This is due mostly to the share of male MPR (employers) among men with jobs being more than double the share of female MPR among employed women. • Among MPR, 25% are women, and for every female MPR, there are 2.94 male MPR. In contrast, the share of male OAW among men with jobs is 47% greater than the percentage among women. • Among female SEW, 79.4% % are OAW and 19.6 % are MPR, while among male SEW, 75.6% are OAW and 24.4% % MPR. • While employed women number 68% the number of males with jobs, female OAW number 46% the number of male OAW, SEW women number 42% the number of male SEW, and female MPR number only 30% the number of male MPR.

  13. SEW GENDER and WORK SITE • Less than 3% of female SEW work from a mobile place of business, while over 19% of males do. • While 67% of female OAW work at their residence, only 45% of males do. • Male OAW are almost as likely to have a mobile as fixed business address, while female OAW are ten times more likely to have a fixed rather than mobile address.

  14. GENDER and WORK SITE (continued) • Regardless of gender, a majority of MPR work at a fixed business address. Among men with jobs carrying out work from their residence, more than 1 in 5 is an MPR, while this is true for only 1 in 10 women with jobs who work at their residence. • Among men with jobs working from a mobile business site, 77% are SEW, while among women with jobs working from a mobile site, 62% are SEW.

  15. SEW INDUSTRY STRUCTURE • The two industries community-social-personal services and wholesale-retail trade & restaurants/hotels account for 51% of SEW. Another 40% are found in transportation-communications-storage, construction, and agriculture-forestry-fisheries-sugar. • Among SEW, construction accounts for twice the share of MPR as compared to the share of OAW. The comparison is reversed in trans-communications-storage, which figures far less important for MPR than for OAW. • Self-employed women are much more concentrated in a small number of industries as compared to men, with fully 85% of female SEW found in the two industries wholesale-retail trade & restaurants/hotels and community-social-personal services. Self-employment among men is more dispersed, with five industries each accounting for at least 15% of male SEW.

  16. INDUSTRY STRUCTURE (continued) • Among women, the sub-segments OAW and MPR mirror the same structure by industry. Among men, the sub-categories show noteworthy differences in structure, with transportation-communications-storage and community-social-personal services most important for OAW but construction and wholesale-retail trade & restaurants/hotels most important for MPR. • Self-employment accounts for 38% of the jobs in transportation-communications-storage, 27% of jobs in wholesale-retail trade & restaurants/hotels, and 16%of jobs in community-social-personal services. SEW outnumber formal paid employees in agriculture/forestry/fisheries/sugar.

  17. SEW OCCUPATIONAL STRUCTURE • More than 50% of SEW are found among the two occupational categories of craft-related, and legislative-senior officials-manager. Among OAW, the largest occupation is craft-related for men, but legislative-senior officials-manager for women. Among both male and female MPR, the category legislative-senior officials-manager is overwhelmingly dominant. • Among female SEW, the largest three occupations are service workers, clerks, and elementary workers. Among male SEW, the largest three occupations are craft-related, legislative-seniorofficials-manager, and manufacturing operators-assemblers.

  18. OCCUPATIONAL STRUCTURE(CONTINUED) • Almost 85% of persons with jobs in agriculture-forestry-fishing are SEW, with OAW the dominant sub-segment. • SEW likewise account for the majority (65%) of persons with jobs in legislative-senior officials-manager, but MPR are more prevalent than OAW. • Roughly three out of every ten persons with jobs in both craft-related and manufacturing operators-assemblers are SEW, with OAW dominating.

  19. IMPLICATIONS FOR CLOSING THE COVERAGE GAP • Some 70% of the informally employed are SEW. • For all practical purposes, closing the coverage gap for self-employed persons also means closing the coverage gap for informally-employed persons. • The Social Insurance Act No.35 (1971) expressly includes self-employed workers in the definition of “employees”. Amendment of the provisions regulating contributions and benefits under the act so as to explicitly include the self-employed will go a long way to narrowing the coverage gap with respect to the informally employed. • Field work is necessary to profile the NSW segment.

  20. IMPLICATIONS(CONTINUED) • Anecdotal evidence on the incomes of informally employed suggests that the majority have low earnings. This suggests the policy priority of ensuring minimum basic income security, independently of the amounts of contributions paid by IE person to NIS. • Usual seasonal or cyclical fluctuations in the levels of economic activity and associated irregularity of incomes affect IE persons’ capacity to pay contributions regularly. This suggests the policy priority of providing for appropriately scheduled and otherwise flexible contribution arrangements.

  21. IMPLICATIONS(CONTINUED) • Compulsory coverage would seem desirable in order to secure a participation rate high enough to ensure a sound contribution base towards payment of benefits. Interestingly, the compulsory approach received support among some sections of the informally employed. • Enforcement of compliance is more difficult than for paid employees in bigger and formal establishments. • Problems in securing adequate levels of compliance should be anticipated, both because of the motivation of the informally employed and because of the higher administrative costs associated with monitoring and enforcing compliance.

  22. IMPLICATIONS(CONTINUED) • Closing the coverage gap through a phased sequencing with respect to both NI products (benefit coverage) and segments of the informally employed to be covered is desirable in light of the administrative challenges surrounding compliance and likely disproportionately higher monitoring and enforcement costs. • A mix of tax incentives and subsidy could be granted in respect of contributions paid. • There should be a collaborative approach with other government agencies along with intense marketing of the programme prior to its implementation.

  23. Research and Development Department NATIONAL INSURANCE BOARD OF TRINIDAD AND TOBAGO 2A Cipriani Blvd, Port of Spain Trinidad and Tobago research@nibtt.co.tt 868-625-2177 fax: 627-1787

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