55thth International Research Conference on Social Security International Research Conference on Social SecurityMarch 5-7, 2007March 5-7, 2007

Session 2.1 Addressing the Coverage Gap in Informal Session 2.1 Addressing the Coverage Gap in Informal EmploymentEmployment

Investigating Informal Investigating Informal Employment and its Employment and its

Implications for Closing Implications for Closing the Coverage Gap the Coverage Gap

in Trinidad and Tobagoin Trinidad and Tobago

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TOPICSTOPICS

• Conceptualizing and estimating Conceptualizing and estimating informal employmentinformal employment

• Key findingsKey findings• Gender structures characterizing self-Gender structures characterizing self-

employment in Trinidad and Tobagoemployment in Trinidad and Tobago• Characteristics of self-employment by Characteristics of self-employment by

industry and occupationindustry and occupation• Implications for closing the coverage Implications for closing the coverage

gapgap

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CONCEPTUALIZING INFORMAL EMPLOYMENTCONCEPTUALIZING INFORMAL EMPLOYMENT

• Informal employment IE is understood in contrast Informal employment IE is understood in contrast to to

formal employment FEformal employment FE• FE = standard employment relation SER FE = standard employment relation SER = paid employees in standard jobs SJ= paid employees in standard jobs SJ• SER 1st order distinction: paid employees PESER 1st order distinction: paid employees PE implies self-employed workers SEW = IEimplies self-employed workers SEW = IE

• SER 2nd order distinction: PE in SJ (national norms) SER 2nd order distinction: PE in SJ (national norms) implies PE in nonSJ = non-standard employees NSM = IEimplies PE in nonSJ = non-standard employees NSM = IE • Conclusion: Conclusion: IE = SEW + NSMIE = SEW + NSM

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ESTIMATING INFORMAL EMPLOYMENT BY ESTIMATING INFORMAL EMPLOYMENT BY

SUCCESSIVE APPROXIMATIONSSUCCESSIVE APPROXIMATIONS USINGUSING HOUSEHOLD HOUSEHOLD DATA FIELDSDATA FIELDS

Maximum IE, MIE = NIP – ACE, where NIP is Maximum IE, MIE = NIP – ACE, where NIP is non-institutional populationnon-institutional population (> 15 years old, so excludes child labour) and ACE is (> 15 years old, so excludes child labour) and ACE is active employeesactive employees (on whose behalf employers make contributions to national insurance) (on whose behalf employers make contributions to national insurance)

Broad IE, BIE = TLF - ACE, where TLF is Broad IE, BIE = TLF - ACE, where TLF is total labour forcetotal labour force Broad self-employment, BSE = SEWLF, where SEWLF is Broad self-employment, BSE = SEWLF, where SEWLF is self-employed self-employed

workers in the labour force workers in the labour force Broad non-standard employees, BNSM = TLF - (BSE + ACE) = BIE-BSE Broad non-standard employees, BNSM = TLF - (BSE + ACE) = BIE-BSE Narrow IE, NIE = PWJ – ACE, where PWJ is Narrow IE, NIE = PWJ – ACE, where PWJ is persons with jobspersons with jobs Narrow self-employment, NSE= SEWJ, where SEWJ is Narrow self-employment, NSE= SEWJ, where SEWJ is SEW with jobsSEW with jobs Narrow non-standard employees, NNSM = PWJ - (NSE + ACE)Narrow non-standard employees, NNSM = PWJ - (NSE + ACE)

Data on the above (except ACE) is generated through continuous Data on the above (except ACE) is generated through continuous probabilistic sampling surveys of households as undertaken by the probabilistic sampling surveys of households as undertaken by the Central Statistical Office. ACE is administrative data generated by NIBTT.Central Statistical Office. ACE is administrative data generated by NIBTT.

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ESTIMATING INFORMAL EMPLOYMENT BY USING ESTIMATING INFORMAL EMPLOYMENT BY USING DATA FIELDS FROM BUSINESS ESTABLISHMENT DATA FIELDS FROM BUSINESS ESTABLISHMENT SURVEYSSURVEYS

Informal Establishment Employment, IEE = Informal Establishment Employment, IEE = Sole trader employment, STE ; plusSole trader employment, STE ; plus Micro-enterprises employers, MER; plus Micro-enterprises employers, MER; plus Paid employees of micro-enterprises, PMEPaid employees of micro-enterprises, PME Summarizing: IEE = STE + MER + PMESummarizing: IEE = STE + MER + PME

Data on the above is generated by the CSO’s Data on the above is generated by the CSO’s Business Business Survey Establishment Register (BSER)Survey Establishment Register (BSER)

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WHAT MAKES OUR ESTIMATION WHAT MAKES OUR ESTIMATION METHODOLOGY DIFFERENTMETHODOLOGY DIFFERENT Our concern here is not the “informal economy” nor Our concern here is not the “informal economy” nor

“informal sector” “informal sector” perper sese, so we sought an alternative , so we sought an alternative to the “residual” and other approaches to estimating to the “residual” and other approaches to estimating IE (see ILO IE (see ILO Decent Work and the Informal EconomyDecent Work and the Informal Economy and and Women and Men in the Informal Economy: a Women and Men in the Informal Economy: a Statistical PictureStatistical Picture, 2002.) , 2002.)

Our informal employment estimation methodology Our informal employment estimation methodology involves projecting key proportions from business involves projecting key proportions from business data fields (serving as partial surrogates for data fields (serving as partial surrogates for household categories) into household data fields.household categories) into household data fields.

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KEY PROPORTIONS FROM 2005 KEY PROPORTIONS FROM 2005 BUSINESS ESTABLISHMENT SURVEYBUSINESS ESTABLISHMENT SURVEY

STE/IEE = 21.1% STE/IEE = 21.1% MER/IEE = 22.6% MER/IEE = 22.6% PME/IEE = 56.3% PME/IEE = 56.3% PME/MER = 2.487 PME/MER = 2.487 PME/(MER+STE) = 1.288PME/(MER+STE) = 1.288IEE/TEW = 24.2% , where TEW is total IEE/TEW = 24.2% , where TEW is total

engaged workers (engaged workers (per BSERper BSER))PME/TPE = 15.3%, where TPE is total paid PME/TPE = 15.3%, where TPE is total paid

employees (employees (per BSERper BSER))PME/TEW = 13.6%PME/TEW = 13.6%

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PROJECTIONS FROM BUSINESS PROJECTIONS FROM BUSINESS ESTABLISHMENT FIELDS INTO HOUSEHOLD ESTABLISHMENT FIELDS INTO HOUSEHOLD FIELDSFIELDS

It seems reasonable to use IEE/TEW as a It seems reasonable to use IEE/TEW as a proxy for IEE/PWJ and use it to generate a proxy for IEE/PWJ and use it to generate a projection of IE from Household PWJ data. projection of IE from Household PWJ data.

Likewise it seems appropriate to use Likewise it seems appropriate to use PME/TEW as surrogate for NSM/PWJ, and PME/TEW as surrogate for NSM/PWJ, and

PME/TPE for NSM/EMPE and generate PME/TPE for NSM/EMPE and generate projections of NSM from household data on projections of NSM from household data on persons with jobs and on paid employees. persons with jobs and on paid employees.

Projections of NSM can also be generated Projections of NSM can also be generated out of the SEW sub-segment MPR from out of the SEW sub-segment MPR from PME/MER and out of SEW from PME / PME/MER and out of SEW from PME / (MER+STE).(MER+STE).

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KEY FINDINGS ON THE EXTENT OF INFORMAL KEY FINDINGS ON THE EXTENT OF INFORMAL EMPLOYMENT IN TRINIDAD AND TOBAGOEMPLOYMENT IN TRINIDAD AND TOBAGO

Population 1,294,494 NIP 979,000 TLF Population 1,294,494 NIP 979,000 TLF 623,600 623,600

PWJ 573,900 ACE 460,827 OAW 84,800 EMR 25,300PWJ 573,900 ACE 460,827 OAW 84,800 EMR 25,300 NSM NSM (projected)(projected) 48,120 IE 48,120 IE (projected)(projected) 148,326 148,326

Active employees ACE & non-standard paid Active employees ACE & non-standard paid employees NSM sum to 508,947; the addition of employees NSM sum to 508,947; the addition of SEW sums to 619,047 and is consistent with the SEW sums to 619,047 and is consistent with the 623,600 figure for the labour force. 623,600 figure for the labour force.

The 508,947 paid employees constitute 81.6% of The 508,947 paid employees constitute 81.6% of the labour force, with the formal segment (ACE) the labour force, with the formal segment (ACE) 73.9% and the non-standard segment 7.7%. 73.9% and the non-standard segment 7.7%.

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KEY FINDINGS ON THE EXTENT OF IE KEY FINDINGS ON THE EXTENT OF IE (continued)(continued)

NSM account for 9.5% of paid employees or 10.4% of NSM account for 9.5% of paid employees or 10.4% of the number of formal employees; approximately one the number of formal employees; approximately one out of every ten paid employees is in IE, and there is out of every ten paid employees is in IE, and there is one paid employee in IE for every ten in formal one paid employee in IE for every ten in formal employment.employment.

Some 23.8% of the labour force and 25.9% of PWJ are 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% engaged in IE, while 7.7% of the labour force and 8.4% of PWJ are more specifically among the non-standard of PWJ are more specifically among the non-standard paid employee segment of the informally employed. paid employee segment of the informally employed.

Roughly 32% of IE are paid employees rather than Roughly 32% of IE are paid employees rather than SEW.SEW.

For every one paid employee engaged in informal For every one paid employee engaged in informal employment, there are 2.3 SEW.employment, there are 2.3 SEW.

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SEW GENDER STRUCTURESSEW GENDER STRUCTURES

Among women with jobs, 14% (32,700)are self-Among women with jobs, 14% (32,700)are self-employed workers SEW. Among men with jobs, employed workers SEW. Among men with jobs, 23% are SEW. 23% are SEW.

While women account for 40% of persons with While women account for 40% of persons with jobs, they account for only 30% of SEW, implying a jobs, they account for only 30% of SEW, implying a higher dependence on/access to formal paid higher dependence on/access to formal paid employment (especially public sector) than is the employment (especially public sector) than is the case for men.case for men.

Less than one (0.9) out of every three SEW was a Less than one (0.9) out of every three SEW was a woman. For every female SEW, there are 2.37 woman. For every female SEW, there are 2.37 male SEW. Among SEW, women account for 32% male SEW. Among SEW, women account for 32% of OAW but only 23% of MPR. Among OAW, 31% of OAW but only 23% of MPR. Among OAW, 31% are women, and for every female OAW, there are are women, and for every female OAW, there are 2.27 male OAW.2.27 male OAW.

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GENDER STRUCTURES GENDER STRUCTURES (continued)(continued)

Self-employment is relatively more prominent among men Self-employment is relatively more prominent among men than women. This is due mostly to the share of male MPR than women. This is due mostly to the share of male MPR (employers) among men with jobs being more than double (employers) among men with jobs being more than double the share of female MPR among employed women. the share of female MPR among employed women.

Among MPR, 25% are women, and for every female MPR, Among MPR, 25% are women, and for every female MPR, there are 2.94 male MPR. In contrast, the share of male there are 2.94 male MPR. In contrast, the share of male OAW among men with jobs is 47% greater than the OAW among men with jobs is 47% greater than the percentage among women. percentage among women.

Among female SEW, 79.4% % are OAW and 19.6 % are 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 among male SEW, 75.6% are OAW and 24.4% % MPR. MPR.

While employed women number 68% the number of males While employed women number 68% the number of males with jobs, female OAW number 46% the number of male with jobs, female OAW number 46% the number of male OAW, SEW women number 42% the number of male SEW, OAW, SEW women number 42% the number of male SEW, and female MPR number only 30% the number of male and female MPR number only 30% the number of male MPR.MPR.

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SEW GENDER and WORK SITESEW GENDER and WORK SITE

Less than 3% of female SEW work from a Less than 3% of female SEW work from a mobile place of business, while over 19% mobile place of business, while over 19% of males do.of males do.

While 67% of female OAW work at their While 67% of female OAW work at their residence, only 45% of males do. residence, only 45% of males do.

Male OAW are almost as likely to have a Male OAW are almost as likely to have a mobile as fixed business address, while mobile as fixed business address, while female OAW are ten times more likely to female OAW are ten times more likely to have a fixed rather than mobile address.have a fixed rather than mobile address.

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GENDER and WORK SITE GENDER and WORK SITE (continued)(continued)

Regardless of gender, a majority of MPR Regardless of gender, a majority of MPR work at a fixed business address. Among work at a fixed business address. Among men with jobs carrying out work from their men with jobs carrying out work from their residence, more than 1 in 5 is an MPR, residence, more than 1 in 5 is an MPR, while this is true for only 1 in 10 women while this is true for only 1 in 10 women with jobs who work at their residence. with jobs who work at their residence.

Among men with jobs working from a Among men with jobs working from a mobile business site, 77% are SEW, while mobile business site, 77% are SEW, while among women with jobs working from a among women with jobs working from a mobile site, 62% are SEW.mobile site, 62% are SEW.

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SEW INDUSTRY STRUCTURESEW INDUSTRY STRUCTURE

The two industries The two industries community-social-personal servicescommunity-social-personal services and and wholesale-retail trade & restaurants/hotelswholesale-retail trade & restaurants/hotels account for 51% account for 51% of SEW. Another 40% are found in of SEW. Another 40% are found in transportation-transportation-communications-storagecommunications-storage, , constructionconstruction, and , and agriculture-agriculture-forestry-fisheries-sugar.forestry-fisheries-sugar.

Among SEW, construction accounts for twice the share of Among SEW, construction accounts for twice the share of MPR as compared to the share of OAW. The comparison is MPR as compared to the share of OAW. The comparison is reversed in reversed in trans-communications-storage, trans-communications-storage, which figures far which figures far less important for MPR than for OAW.less important for MPR than for OAW.

Self-employed women are much more concentrated in a Self-employed women are much more concentrated in a small number of industries as compared to men, with fully small number of industries as compared to men, with fully 85% of female SEW found in the two industries 85% of female SEW found in the two industries wholesale-wholesale-retail trade & restaurants/hotels retail trade & restaurants/hotels andand community-social- community-social-personal services. personal services. Self-employment among men is more Self-employment among men is more dispersed, with five industries each accounting for at least dispersed, with five industries each accounting for at least 15% of male SEW.15% of male SEW.

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INDUSTRY STRUCTURE INDUSTRY STRUCTURE (continued)(continued)

Among women, the sub-segments OAW and MPR Among women, the sub-segments OAW and MPR mirror the same structure by industry. Among men, mirror the same structure by industry. Among men, the sub-categories show noteworthy differences in the sub-categories show noteworthy differences in structure, with structure, with transportation-communications-storagetransportation-communications-storage and and community-social-personal servicescommunity-social-personal services most most important for OAW but important for OAW but constructionconstruction and and wholesale-wholesale-retail trade & restaurants/hotels retail trade & restaurants/hotels most important for most important for MPR.MPR.

Self-employment accounts for 38% of the jobs in Self-employment accounts for 38% of the jobs in transportation-communications-storagetransportation-communications-storage, 27% of jobs in , 27% of jobs in wholesale-retail trade & restaurants/hotels, wholesale-retail trade & restaurants/hotels, and 16%and 16% of of jobs in jobs in community-social-personal services. community-social-personal services. SEW SEW outnumber formal paid employees in outnumber formal paid employees in aagriculture/forestry/fisheries/sugar.griculture/forestry/fisheries/sugar.

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SEW OCCUPATIONAL SEW OCCUPATIONAL

STRUCTURESTRUCTURE More than 50% of SEW are found among the two More than 50% of SEW are found among the two

occupational categories of occupational categories of craft-relatedcraft-related, and , and legislative-senior officials-manager. legislative-senior officials-manager. Among OAW, Among OAW, the largest occupation is the largest occupation is craft-related craft-related for men, but for men, but legislative-senior officials-managerlegislative-senior officials-manager for women. for women. Among both male and female MPR, the category Among both male and female MPR, the category legislative-senior officials-managerlegislative-senior officials-manager is is overwhelmingly dominant.overwhelmingly dominant.

Among female SEW, the largest three occupations Among female SEW, the largest three occupations are are service workersservice workers, , clerksclerks, and , and elementary workers. elementary workers. Among male SEW, the largest three occupations are Among male SEW, the largest three occupations are craft-relatedcraft-related, , legislative-seniorlegislative-senior officials-managerofficials-manager, , and and manufacturing operators-assemblers.manufacturing operators-assemblers.

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OCCUPATIONAL STRUCTUREOCCUPATIONAL STRUCTURE (CONTINUED)(CONTINUED)

Almost 85% of persons with jobs in Almost 85% of persons with jobs in agriculture-forestry-fishingagriculture-forestry-fishing are SEW, with are SEW, with OAW the dominant sub-segment.OAW the dominant sub-segment.

SEW likewise account for the majority SEW likewise account for the majority (65%) of persons with jobs in (65%) of persons with jobs in legislative-legislative-senior officials-manager, senior officials-manager, but MPR are but MPR are more prevalent than OAW.more prevalent than OAW.

Roughly three out of every ten persons Roughly three out of every ten persons with jobs in both with jobs in both craft-relatedcraft-related and and manufacturing operators-assemblersmanufacturing operators-assemblers are are SEW, with OAW dominating.SEW, with OAW dominating.

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IMPLICATIONS FOR CLOSING THE IMPLICATIONS FOR CLOSING THE

COVERAGE GAPCOVERAGE GAP Some 70% of the informally employed are SEW. Some 70% of the informally employed are SEW. For all practical purposes, closing the coverage gap For all practical purposes, closing the coverage gap

for self-employed persons also means closing the for self-employed persons also means closing the coverage gap for informally-employed persons. coverage gap for informally-employed persons.

The The Social Insurance Act No.35 (1971)Social Insurance Act No.35 (1971) expressly expressly includes self-employed workers in the definition of includes self-employed workers in the definition of “employees”. Amendment of the provisions “employees”. Amendment of the provisions regulating contributions and benefits under the act regulating contributions and benefits under the act so as to explicitly include the self-employed will go so as to explicitly include the self-employed will go a long way to narrowing the coverage gap with a long way to narrowing the coverage gap with respect to the informally employed.respect to the informally employed.

Field work is necessary to profile the NSW segment.Field work is necessary to profile the NSW segment.

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IMPLICATIONSIMPLICATIONS (CONTINUED)(CONTINUED)

Anecdotal evidence on the incomes of informally Anecdotal evidence on the incomes of informally employed suggests that the majority have low employed suggests that the majority have low earnings. This suggests the policy priority of earnings. This suggests the policy priority of ensuring minimum basic income security, ensuring minimum basic income security, independently of the amounts of contributions independently of the amounts of contributions paid by IE person to NIS. paid by IE person to NIS.

Usual seasonal or cyclical fluctuations in the levels Usual seasonal or cyclical fluctuations in the levels of economic activity and associated irregularity of of economic activity and associated irregularity of incomes affect IE persons’ capacity to pay incomes affect IE persons’ capacity to pay contributions regularly. This suggests the policy contributions regularly. This suggests the policy priority of providing for appropriately scheduled priority of providing for appropriately scheduled and otherwise flexible contribution arrangements.and otherwise flexible contribution arrangements.

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IMPLICATIONSIMPLICATIONS (CONTINUED)(CONTINUED)

Compulsory coverage would seem desirable in order Compulsory coverage would seem desirable in order to secure a participation rate high enough to ensure to secure a participation rate high enough to ensure a sound contribution base towards payment of a sound contribution base towards payment of benefits. Interestingly, the compulsory approach benefits. Interestingly, the compulsory approach received support among some sections of the received support among some sections of the informally employed.informally employed.

Enforcement of compliance is more difficult than for Enforcement of compliance is more difficult than for paid employees in bigger and formal establishments. paid employees in bigger and formal establishments.

Problems in securing adequate levels of compliance Problems in securing adequate levels of compliance should be anticipated, both because of the should be anticipated, both because of the motivation of the informally employed and because motivation of the informally employed and because of the higher administrative costs associated with of the higher administrative costs associated with monitoring and enforcing compliance.monitoring and enforcing compliance.

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IMPLICATIONSIMPLICATIONS (CONTINUED)(CONTINUED)

Closing the coverage gap through a phased Closing the coverage gap through a phased sequencing with respect to both NI products sequencing with respect to both NI products (benefit coverage) and segments of the informally (benefit coverage) and segments of the informally employed to be covered is desirable in light of the employed to be covered is desirable in light of the administrative challenges surrounding compliance administrative challenges surrounding compliance and likely disproportionately higher monitoring and and likely disproportionately higher monitoring and enforcement costs. enforcement costs.

A mix of tax incentives and subsidy could be A mix of tax incentives and subsidy could be granted in respect of contributions paid.granted in respect of contributions paid.

There should be a collaborative approach with other There should be a collaborative approach with other government agencies along with intense marketing government agencies along with intense marketing of the programme prior to its implementation.of the programme prior to its implementation.

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Research and Development DepartmentResearch and Development Department NATIONAL INSURANCE BOARD OF TRINIDAD AND NATIONAL INSURANCE BOARD OF TRINIDAD AND

TOBAGO TOBAGO

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Trinidad and TobagoTrinidad and Tobago research@nibtt.co.ttresearch@nibtt.co.tt

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