Benefit Reforms for Inclusive Societies in the United States

Income Security During Joblessness

Report

9 May 2023

1. De facto benefit receipt of standard and non-standard workers

Abstract

This chapter sets out by comparing the size and structure of income support for working-age individuals and their families in the United States to other OECD countries. It then assesses the accessibility of social benefits for jobless individuals with past “standard” employment (continuous wage and salaried work) and “non-standard” work (self-employed, part-time, and unstable work) in the international perspective, before zooming in on the benefit coverage of US workers with similar work histories, but different racial and ethnic backgrounds.

Main findings of the report

This report examines support gaps for jobseekers in the United States in a “non-pandemic” labour market before the onset of COVID‑19. It also considers the effects of COVID-related extensions to unemployment insurance, and their suitability for strengthening income security for jobseekers beyond the pandemic.

The first chapter compares the total support package available to out-of-work individuals in the United States to other OECD countries. It looks at the de facto benefit receipt of “standard” full-time wage and salaried- workers, “non-standard” workers (part-time workers, those on temporary contracts, and self-employed including own-account workers), as well as of workers from different racial and ethnic groups as well as men and women. Main findings include:

Spending on working-age benefits in the United States is comparatively low (2% of total household income, compared to 8% and more in the United Kingdom, France, and Belgium) and more tightly means-tested – more than half of all working age benefits are received by the poorest 20% of the population.
Longer-term jobless individuals (six months +) are unlikely to receive any transfers, even when they have a history of standard employment and a clear need for support. Only about 40% of them receive any support, similar to Korea or Greece, and much lower than Belgium and France (about 95%), or the United Kingdom, Spain, Germany or Hungary (about 80%).
Because of the comparatively short duration of Unemployment Insurance payments, the accessibility and levels of income support are similar (and similarly low) for standard and non-standard workers (e.g. those with past part-time or self-employment). Support is, however, significantly less accessible for non-standard workers during the early stages of a jobless spell (under six months). They are about 20% less likely to receive any benefits than otherwise similar jobseekers with a history of full-time wage or salaried work.
For a given employment history, there are no significant social protection gaps across racial and ethnic groups, or between men and women. However, labour market patterns do vary systematically across racial and ethnic groups, and drive observed differences benefit coverage, as documented in the second chapter of the report.

The second chapter focuses on unemployment benefits specifically. Prior to the onset of the COVID‑19 pandemic, unemployment-benefit coverage in the United States was lower than in most other OECD countries: 12% of all US jobseekers received unemployment benefits, compared to about 30% in the United Kingdom, Spain or Australia, and around 60% and over in Austria and Germany. The chapter examines the statutory reach and generosity of unemployment compensation for US workers and jobseekers, with a particular focus on disadvantaged labour market groups, such as racial and ethnic minorities, women, and non-standard workers. Main findings include:

UI benefits are initially comparatively accessible across all US states. For jobseekers with low to average earnings, six months of continuous wage or salaried employment is sufficient to qualify. Most OECD countries require one year or more.
Cross-state differences in statutory UI coverage are not principally a result of different statutory entitlement rules, but mostly due to differences in workforce composition across states, reflecting diverging patterns of employment form, earnings levels, and employment stability.
But cross-state differences in support generosity are significant: effective benefit amounts range from below 30% of the state‑wide average wage in Washington D.C., Arizona and Louisiana to 70% in North Dakota. Southern states, where larger shares of the population are African American, offer comparatively modest benefit ceilings. Benefit replacement rates for full-time average‑wage workers are significantly below the OECD average.
Benefit durations are short in the international comparison: they vary across states but mostly do not exceed 26 weeks. On average across 33 OECD countries, the maximum benefit duration is 17 months.
For working individuals, UI would be accessible in the event of job loss: almost all current full-time and most part-time workers would be entitled to UI if they lost their job. Self-employed earnings do not give rise to UI entitlements in their own right, but those becoming jobless after self-employment can receive UI if they also had wage and salaried income in the past, and 13% of self-employed workers would qualify for UI on this basis.
Among jobseekers, long-term unemployment is the primary reason for non-entitlement to UI. Prior to the pandemic, 63% of jobseekers have been out of work more than 26 weeks (the maximum UI duration in most states). Other reasons for non-coverage include voluntary job quits (about 15% of all jobseekers), past self-employment (2%), or insufficient work/earnings history from past employment (3%).
Long-term unemployment is more prevalent among African American jobseekers than among other jobseeker groups, and this is the main reason for the significant differences in UI coverage among ethnic and racial groups. Only 8% of African American jobseekers are entitled to UI, compared to 16‑17% of non-Latino whites and Latinos.

Chapter 2 of the report also examines how the pandemic-related extensions to UI, which were phased out in late 2021, would affect statutory entitlements if kept in place – and whether such extensions would succeed at diminishing support gaps for jobseekers in a non-pandemic labour market.

Pandemic Unemployment Assistance (PUA) significantly increased receipt durations to a flat 79 weeks in all states, extended benefits to self-employed workers, and reduced minimum contribution requirements to one week’s work at the minimum wage. Given patterns of unemployment in a non-pandemic labour market (2016), these extensions would double UI coverage.
About two‑thirds of this increase is driven by longer maximum receipt durations. Jobseekers with a short work history or low earnings, and those who were self-employed before becoming jobless also benefit. Yet, nearly half of all jobseekers have been out of work for 80 weeks or longer and would therefore remain without benefits even with PUA-type UI extensions in place.
Coverage gains from a PUA-type extension are bigger for Asian and African American jobseekers, compared to Latinos and non-Latino whites. Asian jobseekers have the highest incidence of past self-employment among all racial and ethnic groups, while long-term unemployment is particularly prevalent among African Americans.
Prior to any UI extensions, roughly half of all jobseekers live in relative poverty. Among African Americans, the share is two out of three, compared to one out of three among Asian and non-Latino white jobseekers. PUA-type extensions would mechanically lower poverty by 5%. The reduction would be largest for African American jobseekers (-7%), but a large majority of them would remain in poverty even with PUA-type extensions in place.
Building on the analysis and current reform efforts and experiences in other OECD countries, this report presents four reform options: (i) an extension of UI to the evolving and potentially growing group of self-employed workers, (ii) a softening of the requirement of involuntary unemployment as a pre‑condition of UI receipt, (iii) the harmonisation of benefit amounts and maximum durations across states, with a view to increasing them in the most restrictive states, and (iv) the introduction of an unemployment assistance benefit for job-ready jobseekers without a recent history of employment.
Given robust in-work tax credits in the United States, there appears to be space for increasing out-of-work supports without undue weakening of work incentives. Participation tax-rates for jobseekers taking up low-wage employment currently range from 10% to 30% in California, Michigan and Texas, compared to 45% on average across OECD countries.

1.1. Introduction

Social protection plays a key stabilising role for individuals and societies alike. The recent prominence of social protection in governments’ reform agendas can be seen in the context of unprecedented shocks during the COVID‑19 pandemic, heightened uncertainties about the paths of labour-market recoveries and the cost of living, as well as structural transformations driven by digitalisation and other “mega trends”, such as globalisation and climate change. While crises and uncertainties underscore the vital role of social protection, they also highlight the individual and social costs of protection that is ineffective or inaccessible. A future world of work, with less stable career patterns and an emergence of new forms of employment, presents one set of distinct challenges that may erode the prevention, protection or promotion capacities of present-day social protection systems (OECD, 2019[1]; European Commission, 2022[2]; Acemoglu and Restrepo, 2020[3]).

The COVID‑19 pandemic has further accentuated structural challenges facing social protection policies (OECD, 2020[4]). Paid sick-leave schemes and unemployment insurance benefits have supported many who have lost their incomes early on during the health crisis. The United States, like many OECD countries quickly expanded benefits and eased access to short-time work schemes. Yet, many emergency measures mostly aided dependent employees. Even in countries with well-developed (or recently reinforced) social protection systems, many workers without standard employment contracts, or with short or unstable work histories, struggled to make ends meet when confronted with a job or earnings loss. Moreover, despite additional support for COVID-related job losses, those who were already out of work before the crisis often faced periods of extended hardship.

To examine the gaps in income support for different groups of workers, this chapter assesses the amount of support that individuals receive when experiencing out-of-work spells, either due to unemployment or to labour-market inactivity. It looks at differences in de facto benefit receipt between wage and salaried- and “non-standard” workers (part-time workers, those on temporary contracts, and self-employed including own-account workers), workers with different racial and ethnic backgrounds, as well as men and women. It compares results for the United States to other OECD countries using a methodology proposed in Immervoll et al. (2022[5]). The approach is based on information on actual (empirical or “de facto”) benefit receipt. It therefore captures the interplay of (i) statutory entitlement rules, (ii) the implementation of these rules across different groups and (iii) the take‑up of benefits, which may also vary across groups.

The approach consists of estimating statistical models of benefit receipt while controlling for the most important determinants of social benefit entitlements. The resulting models are then used to “predict” the income support that people receive in specific circumstances (“vignettes”), such as jobless workers with a history of wage and salaried or self-employment.1

This chapter relies on available longitudinal household surveys for 17 OECD countries containing rich information on individual incomes and employment patterns. Administrative records of the universe of workers and sufficiently detailed information on employment history and benefit receipt would have distinct advantages over survey data but are currently not available for most countries.2

In spite of the limitations inherent in available survey data, results are indicative of the approximate patterns of social protection gaps for standard and non-standard workers prior to the COVID‑19 crisis. Results therefore point to structural social protection features and challenges that existed already prior to the COVID‑19 crisis. The analysis presented here is intended as an illustration using readily available survey data, and as a template for possible future applications with statistically more powerful data sources that may become available for some countries.

This chapter is structured as follows. Section 1.2 provides an overview of the architecture of working-age income support in the United States compared to other OECD countries, to inform the interpretation of the estimates of social protection gaps. To the same end, Section 1.3 provides an overview of statutory access gaps for non-standard workers across the OECD. Section 1.4 provides a short description of the econometric model and the data used for the United States and presents internationally comparable results on social protection gaps between standard and non-standard workers. Section 1.5 presents more granular results on the United States using a model tailored to enable analysing social protection gaps for a larger group of out-of-work individuals, as well as social protection gaps between racial and ethnic groups, as well as between men and women.

1.2. Income support in the United States in a comparative perspective

Income‑support strategies and policy setups differ significantly across countries. Workers in many OECD countries acquire entitlements to earnings-replacement benefits such as unemployment insurance, accident insurance, disability, and parental-leave benefits through contributions. Some groups, e.g. families with children, receive support regardless of income or past employment (universal benefits). In addition, households with limited resources may have access to minimum-income benefits (MIB). This reflects different policy institutions and traditions, but also different strategies for balancing the various objectives of social protection such as risk sharing, income smoothing over time, inequality reduction and poverty alleviation.

Differences in the mix of entitlement criteria across countries are important drivers of social protection gaps between standard and non-standard workers. In 2019, only 11 of 36 OECD countries with available information offered self-employed workers the same unemployment protection as dependent employees, and two of them (Australia and New Zealand) exclusively relied on means-tested income support for jobseekers (OECD, 2022[6]). Several factors make the provision of contribution-based benefits for self-employed workers in particular more complex than for wage and salaried workers (see section 1.3). In contrast, means-tested benefits may be more accessible to non-standard than to standard workers, because they often have lower, and more fluctuating incomes (OECD, 2020[4]). Understanding how the income support architecture in the United States compares to other countries is therefore key for understanding how it compares in terms of social protection gaps between standard and non-standard workers.

1.2.1. Countries employ a range of benefit entitlement criteria

Some countries rely very strongly on means-tested benefits for working-age support (e.g. Australia or the United Kingdom, where means-tested or universal child benefits make up the bulk of spending on working-age benefits, see Figure 1.1). Others mainly rely on insurance‑based transfers to cushion earnings-losses, with a limited role for means-tested transfers for those who do not have the required contribution history (e.g. Belgium, Italy, Korea or Spain). A third group uses “layered” systems that combine insurance‑based out-of-work benefits with universal support for families with children and means-tested benefits as a lower-level safety net (e.g. Austria, France, Germany, the Slovak Republic and to a lesser extent, Hungary). Especially in Austria, Germany and Hungary, universal child benefits account for a significant share of the incomes of working-age households.

This mix of benefits can differ at similar levels of spending. In both France and the United Kingdom, public benefits make up around 8% of the incomes of working-age households (before benefits), but with very different underlying targeting mechanisms (Figure 1.1). The support package in the United Kingdom consists almost entirely of universal and means-tested support, while contributory benefits account for one‑third of the support package in France. Similar differences can be seen across Germany and Italy, or Hungary and Spain. In Belgium, where public benefits account for over 10% of the incomes of working-age households, over 80% of payments depend on previous earnings.

Figure 1.1. The importance of contributory benefits varies considerably across countries

Share of working-age benefits in total household incomes, by entitlement criterion, at or before 2018

In the United States, benefit spending makes up only 2% of the total income of working-age households. Less than one‑third of these benefits are contribution based (mainly veterans’ benefits and, to a lesser extent, unemployment compensation).

1.2.2. Tightly targeted benefits dominate in the United States, with Unemployment Compensation playing a minor role

Looking at the total benefit package for working-age households in the United States, Unemployment Compensation is a relatively minor programme in terms of spending, accounting for only nine percent of overall social spending on working-age households. This is consistent with low coverage and receipt durations of UI (see Chapter 2). With the exception of Veteran’s benefits, which account for 12% of spending for working-age households, all other social spending is means-tested.

The bulk of spending is made up of means-tested programs targeting poor households. The nutritional assistance programmes Supplemental Nutrition Assistance Program (SNAP) and Special Supplemental Assistance Program for Women, Infants and Children (WIC) account for 30% of overall spending,3 and the disability benefit Supplemental Security Income (SSI) for disabled, low-income adults for 25%, followed by the employment-related Earned Income Tax Credit (EITC, 20%). Other social assistance programmes (state‑level General Assistance, GA, and Temporary Assistance for Needy Families, TANF) make up 4% of spending.

Consistent with the importance of means-tested benefits, more than half of all working-age social spending in the United States is targeted to poorest 20% of households (Figure 1.2). Unemployment Compensation makes up a negligible share of total benefits among the poorest households (3% of benefit spending in the first income quintile). Last resort benefits (SNAP, WIC, GA, and TANF) make up the bulk of benefit spending on the poorest households, implying that many do not have the contribution history to qualify for unemployment compensation. Disability benefits account for 30% of benefit expenditure in the first quintile, indicating that many in the poorest quintile are in fact unable to work because of ill-health. The receipt rate of disability benefits in the working-age population in the United States is, however, not exceptionally high in the international comparison (at 6%, the same as the average across OECD countries, (OECD, 2022[7])).

Unemployment Compensation payments increase with household income (Figure 1.2). This is consistent with the short maximum receipt duration (around five months) – UI recipients are more likely to have labour income during the year. The benefit is also not means-tested and can therefore be received by those living with other income earners.

Figure 1.2. Nutritional assistance and disability benefits dominate working-age income support

Shares of expenditure on working-age benefits across the income distribution, in percent, by programme, 2016

1.2.3. For able‑bodied adults, statutory entitlements are less generous than in other countries

Coverage and receipt durations for unemployment benefits in the United States are low in comparison to other countries (see Chapter 2). In line with low overall spending on working-age benefits (see section 1.2.1), the United States also provides less generous non-contributory benefits for those who are not or no longer entitled to UI, through unemployment assistance, family benefits, minimum income benefits or through a combination of different measures. Figure 1.3 shows entitlements for a one‑adult household, and a couple with two children, in the 13th month of unemployment, to abstract from short unemployment spells, and to show the effects of MIBs that often compensate once unemployment benefit entitlements run out. As many benefits in the United States vary at the state‑level, Figure 1.3 shows results for three states with different labour markets and benefit rules: California, Texas and Michigan. It draws on the OECD TaxBEN model, that assesses statutory entitlements in specific policy-relevant, but hypothetical, household circumstances. For an in-depth analysis of work incentives and benefit levels in the United States in a comparative perspective, see the companion paper to this report, (Pearsall, Pacifico and Magalini, forthcoming[8]).

Across the OECD on average, long-term unemployed adults living alone receive benefits amounting to about a third of median household income, significantly below the relative poverty threshold (incomes below 50% of the median household income, following the standard OECD definition). Net incomes are above the poverty threshold in countries where maximum receipt durations of UI benefits exceed one year, including Switzerland, the Netherlands and Portugal, but benefits are close to the relative poverty threshold also in Luxembourg and Japan, where means-tested social assistance takes the place of unemployment benefits after one year of unemployment. In the United States, SNAP is the only benefit that can be received by a long-term jobseeker without children, leading to very low benefit levels in all three states with available data (Figure 1.3, Panel A). Families with children receive family benefits in many OECD countries, which increase household incomes for workless couples with two children, particularly in Australia, Poland and Canada. In the United States, the only family benefit for jobless families is TANF, that has very low coverage rates in practice (see Box 1.1). However, even for households receiving TANF, total benefit packages in the United States are significantly below the OECD average (Figure 1.3, Panel B).

Figure 1.3. Income support for jobseekers falls short of a relative poverty line in many countries

Box 1.1. Temporary Assistance for Needy Families

TANF, the main benefit for workless families with children in the United States, replaced its precursor, Aid to Families with Dependent Children (AFDC) with the welfare reform act of 1996. In contrast to AFDC, TANF is not an entitlement programme, but is financed by nominally fixed grants to states. The welfare reform act also introduced a maximum receipt duration of 60 months during any recipient’s lifetime (although states can choose longer, or more often shorter maximum receipt durations) as well as stringent work requirements underpinned by sanctions (Aizer, Hoynes and Lleras-Muney, 2022[9]; Ziliak, 2016[10]). For instance, 40 states required single parents to work a minimum of 30 hours per week in 2019 – while education and training are generally allowed as part of the activity requirements, some paid work is required in most states and circumstances (The Urban Institute, 2021[11]). The programme is also tightly asset tested, e.g. in July 2019, allowable assets in Texas were USD 1 000, USD 2 250 in California, and USD 3 000 in Michigan.1 Following the introduction of these stringent eligibility requirements, receipt numbers and spending fell, starting in 1996 and even through the great recession (Hoynes and Schanzenbach, 2018[12]). Research indicates that African American families in particular were negatively affected by these changes, as they are more likely to live in states with less generous and more restrictive TANF regulations and are more likely to be sanctioned (Shrivastava and Thompson, 2022[13]).

TANF is now a minor programme, serving around 1.5 million children (Aizer, Hoynes and Lleras-Muney, 2022[9]). In Texas, only four out of 100 families with children living in poverty receive TANF, and in Michigan it is around 10 in 100. California provides the highest benefit level and more generous income testing provisions, resulting in around 70% of households with children in poverty receiving support (Shrivastava and Thompson, 2022[13]).

1. California and Michigan have since increased allowable asset limits to USD 10 000 and USD 15 000 respectively. The assets which are assessed and/or excluded vary between states. See the online annex to this report’s companion paper (Pearsall, Pacifico and Magalini, forthcoming[8]) for more detail on eligibility requirements for TANF in the selected states.

1.3. Statutory access to Social Protection for non-standard workers

Statutory access to income support varies by employment type and by programme/branch. Temporary and part-time workers are in principle covered in the same way as permanent full-time employees in most countries and for most risks, as long as they meet minimum contribution periods and earnings thresholds.

By contrast, statutory access for self-employed workers is very frequently restricted. Indeed, contributory social protection systems that were mostly set up with a steady employer-employee relationship in mind do not easily accommodate the self-employed (OECD, 2018[14]):

1. Double contribution issue: Who should be liable for employer contributions in the absence of an employer? Requiring the self-employed to pay the equivalent of both employer and employee contributions brings formal burdens in line with dependent employees. But effective burdens may be higher for the self-employed, especially those with lower earnings, because minimum wages typically do not apply to them and because they may lack the bargaining power to shift any contribution-related costs onto their clients by charging higher prices.

2. Fluctuating earnings (and margins for avoiding contribution liabilities): The self-employed are often paid at irregular intervals, either because of time lags between work and payment, or because demand for their services is erratic (ISSA, 2012[15]). This complicates the calculation of contributions (as well as the assessment of entitlements). In particular, self-employed workers may be able to avoid or lower contributions by optimising their contribution base, e.g. through timing their work or earnings.

3. Moral hazard: Demand or price fluctuations affecting self-employed workers are difficult to distinguish from voluntary idleness and this complicates the provision of unemployment insurance. There is no employer to confirm a layoff and efforts to re‑establish a business operation are more difficult to monitor than the search for dependent employment. In addition, earnings levels of the self-employed react with more volatility to market developments, e.g. because there are no minimum wages and downward wage rigidity does not apply to them. If entitled to unemployment benefits, those with poor earnings prospects may therefore have relatively strong financial incentives to wind down their business in order to claim benefits.

Box 1.2 describes statutory entitlements to unemployment and other working-age benefits for non-standard workers to aid the interpretation of the empirical support gaps presented in section 1.4.

Box 1.2. Statutory entitlements to social protection for non-standard workers

Unemployment benefits have been the least accessible branch of income support for non-standard workers. In 2020, 13 of the 36 countries shown in Figure 1.4 did no not offer any kind of unemployment protection for self-employed workers. Access is also restricted for some forms of dependent non-standard work, e.g. casual workers in the United States, or para-subordinate workers in Italy (SSA and ISSA, 2017[16]; Raitano, 2018[17]). OECD (2019[1]) provides equivalent graphical overviews for other social protection branches.

Figure 1.4. Access to unemployment benefits for self-employed workers was limited before the pandemic

Statutory access to unemployment benefits for self-employed workers compared to dependent employees (“employees”) in 2020 by incidence of self-employment (2019)

The rules for accessing incapacity benefits – covering cash sickness benefits, work accidents and disability – vary across countries and type of non-standard work. Statutory access for non-standard dependent employees was mostly similar to standard employees in all three types of incapacity benefits. Exceptions include Australia, where casual workers are not entitled to cash sickness benefits (which are an employer-provided benefit), the United States, where casual workers do not have access to accidents-at-work insurance, and Italy, where some para-subordinate workers are not covered by short-term sickness insurance. Access for self-employed workers, however, is typically more difficult. Statutory access was weakest for benefits following work accidents: only ten of 38 OECD countries offered self-employed workers the same protection as dependent employees. Many self-employed workers indeed have considerable control over their working environment and, as in the case of unemployment benefits, insurance against work accidents can therefore be prone to moral hazard. But the exclusion of self-employed workers does create important social protection gaps for those with genuinely risky activities, including for workers who are wrongly classified as independent, or who are in the “grey zone” between self-employment and dependent employment (e.g. workers who have very few or even only a single client). Self-employed workers have more ready access to (long-term) disability benefits: 29 countries offered them the same access as dependent employees (OECD, 2022[18]).

When contingencies are independent of a specific job or past career, protection for non-standard workers tends to be more readily available. For instance, social assistance or minimum income schemes are typically financed through general tax revenue, and legal entitlement rules are based on need, regardless of past employment type, duration or stability. Because non-standard workers are often over-represented at the low end of the income distribution – part-time workers because of low-earnings, temporary and unstable workers because of periods of joblessness, and self-employed workers because of earnings-fluctuations and because their earnings are more dispersed in general – they may in fact be more likely to receive means-tested benefits (see (OECD, 2018[14])).

Family benefits, such as child allowances, are typically universal or means-tested, and statutory access to maternity benefits also tends to be similar for workers in standard and non-standard forms of dependent employment. An exception is Italy, where “workers on vouchers” and foreign seasonal workers do not have access to contributory family benefits (Jessoula M, Pavolini E and Strati F, 2017[19]). For the self-employed, maternity benefits are often part of contributory schemes that have separate provisions for independent workers. In all countries with compulsory maternity coverage for standard employees, self-employed workers can either opt into the main scheme voluntarily, or they have access to a separate benefit that is, however, less generous than for dependent employees (lower benefit amounts and/or shorter duration).

Source: (OECD, 2022[6]), OECD Employment Outlook 2022, https://doi.org/10.1787/1bb305a6-en (OECD, 2022[18]), Disability, Work and Inclusion: Mainstreaming in All Policies and Practices, https://doi.org/10.1787/1eaa5e9c-en, (Immervoll et al., 2022[5]), “De‑facto gaps in social protection for standard and non-standard workers: An approach for monitoring the accessibility and levels of income support”, https://doi.org/10.1787/48e282e7-en.

1.4. Effective support gaps between standard and non-standard workers in the United States and other OECD countries

This section presents new results on empirically observed income support gaps between standard and non-standard workers in the United States. De facto support gaps are the result of a statistical model of benefit entitlements for jobless individuals that controls for the most important determinants of social benefits. Results are intended as shorthand summaries of benefit accessibility and generosity in a comparative perspective. They also allow quantifying the accessibility and generosity of support packages across different population groups, including standard and non-standard workers.

The approach is detailed in a companion paper to this report, (Immervoll et al., 2022[5]), that presents de facto support gaps for 16 OECD countries. This section therefore only provides the main intuition for the model, focussing on the new results for the United States.

1.4.1. Statistical approach

The social protection gaps approach aims to estimate receipt probabilities and benefit levels for a specific set of circumstances, and seeks to control for the key characteristics that determine benefit receipt. As benefit access and amounts often depend on past events, the method relies on longitudinal household data that include information on current and past employment, earnings and other relevant individual and family characteristics. The drawback of using easily accessible survey data is comparatively small sample sizes, which can make the analysis of subgroups – such as the out-of-work population with a history of non-standard work – problematic. Data from administrative sources would be more appropriate for this type of analysis, but is currently not readily available for comparative work of the type proposed here.

The main variable of interest is the value of the total benefit package, rather than any individual category of social transfer, reflecting the fact that countries provide support through different channels and programmes. The policy scope comprises the most important social transfers to working-age individuals and their families: unemployment and disability benefits, (employer as well as publicly provided) sick pay,4 family (including maternity) benefits, any benefits tied to education (such as public student aid), in-work and minimum income benefits (means-tested transfers aimed at reducing poverty, most importantly social assistance and housing benefits).5 For the United States, the analysis furthermore includes Supplemental Nutrition Assistance Program (SNAP) and Special Supplemental Nutrition Program for Women, Infants and Children (WIC).6 For details on the benefits included for the United States, see Annex 1.A.

The variable of interest also encompasses support provided through the tax system that is akin to cash benefits (such as refundable child or in-work tax credits) when these are reported in the data.7 For the United States, EITC amounts are imputed for individuals who report EITC receipt in the data; however EITC coverage is underestimated because of survey underreporting, as well as inconsistencies between reported EITC receipt and previous year’s earnings, see Annex 1.B for details. Receipt of the Child Tax Credit is unfortunately not reported in the US data, and the analysis therefore does not account for CTC receipt. Estimated benefit receipt incidence and amounts will therefore underestimate the true extent of income support for households with children in the United States (see Annex 1.B).

Benefit receipt is measured over an entire year and therefore accounts for both generosity in a given month, any benefit reductions for longer out-of-work spells, and the effective duration of entitlements (including any waiting periods or other possible gaps between benefit entitlement and pay-out). For benefits that are observed/reported at the household rather than the individual level (family benefits, minimum income benefits), amounts are divided equally across all adult household members on a per-capita basis.

The empirical assessment of income support for different labour market groups proceeds in two steps. A first step estimates the relationship between individual benefit receipt and a number of key structural drivers of support. The model specification includes the following independent variables, along with relevant interactions and higher-order terms: Main employment status and pre‑transfer household income during the reference period (year 0), main employment status and earnings during the two years preceding the reference period (years ‑1 and ‑2), household composition in year 0, including the presence of dependent children (plus children under the age of six to capture maternity/paternity benefits), as well as health status, housing tenure and housing costs, sex and age (all year 0). See Figure 1.5 and Figure 1.6.

Figure 1.5. Total benefit package at the individual level: Determinants included in the model

Separate models are estimated for benefit receipt (yes/no) and benefit levels (benefit amounts), see (Immervoll et al., 2022[5]) for details. A second step uses the estimated relationships for inference on the benefit gaps between standard and non-standard workers in specific concrete circumstances (“vignettes”) that are defined in a consistent way across countries. The use of a vignette‑based analysis facilitates the communication of complex statistical results in a comparative setting, and the identification of possible policy mechanisms driving entitlement gaps.

Benefit “gaps” for non-standard workers are calculated relative to a baseline standard worker, who is likely to require out-of-work support. This baseline standard worker is an individual who was out of work (either unemployed or labour-market “inactive”) for at least six months during the reference year, lives in a low-income household in the reference period (bottom 20% of the national distribution), and has neither significant health problems, nor young children under the age of six.8 In the two years prior to the reference period, the baseline standard worker was a dependent full-time employee with earnings at or above the 40th percentile of the national distribution.9 The comparator vignette is an otherwise similar individual, with a history of “non-standard” work, detailed in the notes to Figure 1.6, as well as the figures showing model results.

It is important to note that the analysis looks at a subset of out-of-work individuals who are both persistently out of work (for at least six months in year 0) and may not be actively seeking work, which is a requirement for receiving unemployment benefits in all countries barring special circumstances.10 It also focuses on individuals who are in clear need of support (in the bottom 20% of the income distribution before benefits), and therefore likely to satisfy means-tests.

Figure 1.6. Comparison of the benefit package: “standard” vs “non-standard” worker

1.4.2. Data

Model estimates for the United States11 are based on the first three waves of the 2014 Panel of the Survey of Income and Programme Participation (SIPP), covering labour market histories and incomes in the years 2013, 2014 and 2015.12 While more recent waves of SIPP data are available, a redesign of the survey means that it is difficult to obtain three consecutive waves of data.

While in principle it is possible to link the three waves of the 2018 SIPP survey (corresponding to the years 2018, 2019, and 2020), low response rates in 2019 and 2020 led the Census Bureau to issue a warning for researchers to use the data with caution. In 2019, a lapse in survey funding disrupted the data collection process, while the 2020 survey relies exclusively on telephone‑based interviews due to the COVID‑19 pandemic, making it difficult for survey administrators to follow up on non-responders. In addition to data collection issues, the COVID‑19 emergency measures implemented in 2020 represent an extraordinary situation that was not the focus of the original cross-country analysis. This means that the data from the 2014 SIPP survey remains the most appropriate for use in the analysis.

The sub-sample of interest comprises all working-age individuals aged 18‑64 who are potentially in need of working-age support: individuals who (i) have not worked for pay or profit during the majority (six months or more) of the observation/reference period (year 0: 201613 for the United States, 2018 for all European countries and Korea, 2019 for Australia), (ii) are not already retired,14 and (iii) were not in education or military service in year ‑1 (and thus had the opportunity to accumulate entitlements to any insurance‑based benefits). This is typically a small share of the working age population, with effective sample sizes for the 1st stage coverage model ranging from fewer than 2000 observations in Austria, Korea and the Baltic countries, to more than 6 000 observations in Australia, Greece, Italy, Spain. For the United States, the estimation sample comprises 3 430 unique individuals, representing a population of about 28 Million, see Annex Table 1.C.1.

The descriptive statistics in Annex Table 1.C.1 show that women are strongly over-represented in the out-of-work estimation sample, accounting for two‑thirds of out-of-work individuals. This tendency is slightly more pronounced in the United States compared to the cross-country average. Furthermore, compared to other OECD countries, out-of-work individuals in the United States are less likely to be in the bottom 20% of the income distribution, and more likely to be in the top 20%. Only 14% of the sample population are unemployed, with the remainder being inactive, compared to 34% in the cross-country average (not shown). The share of unemployed individuals in the sample is only significantly lower in Korea (4%). A high share of economically inactive women living in households in the middle and upper end of the income distribution is in line with the male‑breadwinner model.

In line with the categorisation of the (partial) simulations of unemployment benefits in Chapter 2, part-time workers are wage and salaried workers working below 35 hours per week. Self-employed workers include workers in the residual category of “other work arrangement” according to guidance from the Census Bureau that these workers are mostly independent contractors or consultants. Workers who are wage and salaried workers as well as self-employed are categorised as self-employed if their earnings from self-employment in a given month are higher than their wage or salaried income (and vice‑versa). For individuals with missing earnings the simulations use the number of hours worked as either a wage or salaried worker or as self-employed to determine the primary status (see also Box 2.1 in Chapter 2).

Raw receipt rates of social benefits are significantly lower than in other countries – 49% in the United States compared to 68% across countries on average. Previous standard workers – who worked mostly full-time as wage‑ and salaried employees during the two years before the income reference period – were less likely to receive benefits than the overall out-of-work sample, consistent with the prevalence of means-tested benefits in the United States (see section 1.2).

1.4.3. Results

The presentation of results starts out by discussing receipt patterns for the standard worker “baseline vignette”: an able‑bodied individual who has been out-of-work for six months or more, and who has a record of stable full-time wage or salaried employment, and whose income before benefits put them into the bottom 20% of the income distribution. The results therefore show benefit entitlements for individuals who are both in clear need of support as well as “deserving” in having made prior contributions. The support available for standard workers is indicative of cross-country differences in income support architectures, and useful for building intuition for the resulting drivers of support patterns.

Even for jobless individuals with a history of standard employment, and a clear need for income support, the likelihood of receiving support varies markedly across countries

In Belgium and France, the “baseline” standard worker’s chance of receiving support is 95% or more, compared to less than 60% in Greece and Italy, and below 50% in Korea and the United States (“baseline: past standard work” in Panel A, Figure 1.7). In most other countries, the share is about 70%‑80%.

The countries with the lowest estimated receipt probabilities, the United States, Korea and Greece, also have the lowest levels of spending on working-age transfers in the analysed countries (under 4%, see Figure 1.1). Working-age transfer spending is somewhat higher in Italy where the benefit receipt probability was also under 60%, but benefits are largely insurance based and thus less targeted to low-income groups (for instance, in Italy in 2018, 43% of all working age benefits went to the top income quintile according to the OECD Income Distribution Database). In contrast, in the countries with the highest receipt probabilities, Belgium and France, government transfers represent over 10% of the incomes of working-age households. In Belgium, unemployment benefit receipt durations are in principle not limited (see section 1.3), while France and Germany combine insurance‑based unemployment benefits with means-tested unemployment and social assistance programmes.

For the United States, the fact that the vignette is defined to have no significant health problems may also contribute to the low receipt probability, given the importance of (means-tested) disability benefits for low-income households (see Figure 1.2).

Yet, the low benefit receipt probability for a long-term out-of-work individual with a recent history of employment is likely connected to the overall low coverage rates for unemployment benefits in the United States (see Chapter 2). Unlike in many other OECD countries, standard workers who are “voluntarily” unemployed, are not entitled to unemployment benefits. Statutory benefit receipt durations are also comparatively short (up to 26 weeks, depending on the state of residence, see Chapter 2). Last-resort benefits, in the case of the United States mainly SNAP, General Assistance and TANF, are therefore the only benefit that many jobless workers may claim. These benefits can be associated with social stigma, and may have strict means- and asset tests, leading to low take‑up (see Box 1.1 and (Hyee et al., 2022[20])).

Estimated benefit amounts depend on the duration of out-of-work spells and the type of benefits received

The predicted average sizes of overall benefit packages also vary enormously across countries. They range from under 20% of the national median household income in Korea, the United States and Greece, to around 30% or less in parts of Central and Eastern Europe (Lithuania, Estonia, Latvia, and Hungary), Germany and Australia, 35 to 40% in Poland and the United Kingdom, and 40 to 50% in Spain, Portugal, Italy, and France. At 60% of median income, estimated benefit levels are highest in Belgium (Panel B of Figure 1.7).

In terms of country rankings, these benefit levels are broadly in line with “theoretical” benefit entitlements, as calculated with policy simulation models (e.g. http://oe.cd/TaxBEN). For a number of reasons, however, actual values as estimated here differ from – and are generally lower than – theoretical levels implied by headline indicators for “typical workers”, such as replacement rates at the beginning of an unemployment spell:

1. De facto estimates are based on actually observed spells of joblessness. Unlike “typical worker” replacement rates, the resulting entitlements reflect the characteristics of those experiencing job loss, such as past earnings histories. Since those with lower earnings or shorter career histories tend to be over-represented among job losers, the resulting entitlements to any earnings-related insurance benefits can be noticeably lower than those of an “average” worker.

2. Results refer to support received over an entire calendar year. They therefore capture differences in benefit amounts in a given month, in benefit duration limits, and in the average duration of out-of-work spells. The latter varies across countries, even among the selected sample with jobless spells of six months or longer. For instance, the average spell duration for previous standard workers who have been jobless for six months or longer in the United States is almost two months shorter than in Italy (see Annex Table 1.C.1 for the United States and Table B‑1 in the online Annex15 of (Immervoll et al., 2022[5]) for other OECD countries with available information).

Estimates of de facto benefit levels refer to recent job losers receiving any type of cash support. This can include people who do not receive out-of-work benefits, but transfers of a lower value, such as housing benefits or nutritional support in the case of the United States or “universal” benefits (e.g. jobless people with children may receive universal child benefits in Austria and Germany). In the case of the United States, unemployment compensation plays a minor role for the selected vignette (who is in the bottom income quintile), as the majority of payments are received by households further up the income distribution (Figure 1.2).

With that in mind, the (comparatively small) group of out-of-work Italians with past standard employment who do qualify for benefits receive significantly more generous support on average (over 40% of median household income) than, for example, an equivalent individual in Australia, where (flat-rate and means-tested) benefits amount to about 20% of median household income. In both cases (and in most other countries), those relying on benefit income alone would typically have income below commonly used relative poverty cut-offs, but poverty gaps would be significantly bigger for benefit recipients in Australia.

Across countries, there is no obvious general link between accessibility and generosity. As noted, benefit access in Italy is comparatively difficult, but benefit levels for recipients are higher than in the majority of other countries. Hungary, Germany and the Baltic countries follow the opposite pattern, with implied coverage above 80%, but with comparatively low benefit levels around 30% of median household incomes. Accessibility and generosity scores are both high in Belgium.

In the United States, Korea and Greece, accessibility and generosity scores are both low. In the United States and Korea, low annual support levels are partly driven by short durations of (unemployment) benefits as noted above. In addition, effective minimum-income entitlements also tend to be lower than in many other countries (http://oe.cd/TaxBEN).

Accessible support for non-standard workers is achievable with different targeting mechanisms

In the United States, as well as four other countries (Austria, Germany, Hungary and the United Kingdom) both coverage and generosity gaps between standard and non-standard workers are statistically insignificant. In Australia and Belgium, access gaps are statistically insignificant, and receipt probabilities are at around 70% or above for both the standard and non-standard vignettes. While results for France and Spain point to statistically significant gaps, with somewhat lower point estimates for the implied coverage for non-standard workers, receipt probabilities for both types of worker are also above 70%. As these eight countries follow very different social protection strategies, these results suggest that accessible support for non-standard workers is achievable with different targeting mechanisms.

Out-of-work support in the United States, Australia and the United Kingdom is largely means-tested (and therefore unrelated to previous employment and earnings, see section 1.2); in the case of the United States, support is almost entirely means-tested for low-income households (Figure 1.2). By contrast, Hungary and Belgium offer earnings-related unemployment protection to both standard and non-standard workers.

A finding of small or insignificant gaps in the protection afforded to standard and non-standard workers in such a diverse set of countries is notable. For instance, it raises questions about recent prominent calls for a strong reliance on means-tested safety-net benefits, or for a universal basic income, that are sometimes motivated by concerns that insurance‑based systems cannot provide effective protection for non-standard workers (World Bank, 2018[21]; Gentilini et al., 2019[22]; Browne and Immervoll, 2017[23]).

Figure 1.7. Out-of-work support in the United States is equally patchy for standard and non-standard workers

Overall support package for working-age individuals, at or before 2018/19

In Hungary, non-standard workers, including the self-employed, are entitled to unemployment benefits (Albert, Gáspár and Gal, 2017[24]). In Belgium, non-standard workers can qualify for unemployment insurance support though benefit amounts are much more generous than in Hungary, and benefits for self-employed workers in Belgium account also for household needs (De Wispelaere and Pacolet, 2017[25]). In both countries, means-tested support provides further layers of protection for those not entitled to insurance benefits. Austria and Germany also combine a first-tier unemployment insurance system with a second layer of means-tested support. In France, a key explanation for the insignificant coverage gaps is the very short qualification period for unemployment benefits, paired with the possibility to retain unused benefit entitlements for future out-of-work periods, and to cumulate benefit rights across successive out-of-work spells for the (large and growing number) of workers with short-duration employment contracts.16 Like Austria, Belgium and Germany, France also provides multi-layered income support that benefits workers across different types of non-standard employment (as well as others who may not qualify for first-tier insurance benefits).

Implied access gaps are largest in Korea, Portugal and Italy, where standard workers were between 50% (Italy, Portugal) and 100% (Korea) more likely than non-standard workers to receive income support following a job loss (Figure 1.7, “past non-standard work”). Gaps are also large in Latvia, Lithuania and Estonia.

The example of Portugal, in particular, illustrates the need to consider effective access in addition to statutory entitlements: Portugal has one of the biggest access gaps of all considered countries, mostly driven by the low coverage of self-employed workers (see Annex 1.D). This is despite unemployment benefits being open to owners of businesses and independent contractors with only one client (Perista and Baptista, 2017[26]). But not all self-employed workers have access (e.g. unincorporated self-employed workers, or those working for more than one client), and the required contribution period for self-employed workers is twice as long as for employees. Self-employed workers also have legal access to cash sickness benefits, but the maximum entitlement period is one‑third of the duration for employees. These factors result in limited effective access to cash support for self-employed workers in Portugal, even though they do have better statutory protection than in other countries.

Statutory entitlement rules vary significantly across different types of non-standard work (section 1.3). Self-employed workers for example may not be covered at all for certain types of risks, while part-time workers and those with interrupted/unstable work histories may suffer reduced effective access, because they fail to meet the required earnings or contribution histories. Results on the gaps between standard workers and a heterogeneous group of all non-standard workers may therefore mask significant differences between different types of non-standard employment. Understanding these differences is necessary for designing tailored policy strategies for tackling unintended gaps.

1.4.4. De facto support gaps can vary across different types of non-standard workers

The analysis for granular employment types is only possible for a sub-group of countries where sample sizes allow such disaggregation (see Annex Table 1.C.1 for the United States and Table B‑1 in the online Annex17 of (Immervoll et al., 2022[5]) for other OECD countries with available information). For the United States, sample sizes are sufficient to estimate gaps for all granular employment types.

Results highlight that self-employed workers (including independent contractors) are typically least likely to receive support, while gaps are less common, and tend to be smaller, for part-time and unstable workers (see Annex 1.D). Accessibility gaps for those with past self-employment are sizeable in three of the six countries considered: In Portugal, Spain and Italy, implied coverage gaps (the difference of estimated receipt probabilities between previous standard and self-employed workers) are around 50 percent. In Italy and Spain, self-employed workers do not have access to unemployment benefits, and in Portugal, access is incomplete. Self-employed workers thus have to rely on lower-tier income support such as social assistance and housing benefits, which typically feature strict eligibility requirements including income and asset tests, and are subject to significant non-take‑up, lowering their effective reach. For instance, receipt of means-tested support is particularly low in a number of southern European countries. Minimum-income benefits also tend to be less generous than social insurance transfers.

In Poland, self-employed workers can receive unemployment benefits, but only after a 90‑day waiting period (compared to seven days for dependent employees). The benefit is not linked to previous earnings, which explains the small and insignificant gap between self-employed and standard workers in access, and the comparatively small gap in generosity.

Access gaps for part-time workers are less common, in line with the statutory entitlement results, affecting only three out of 11 countries (see Annex Figure 1.D.2, Panel A). Benefit levels for part-time workers were significantly lower than for (full-time) standard workers in six of the 11 countries considered, in line with the strong previous earnings link that shapes entitlements in many unemployment benefit programmes (Annex Figure 1.D.2, Panel B). Gaps in levels were largest in Southern European countries where insurance‑related benefits dominate. In Australia, somewhat higher benefit payments to those with previous part-time work likely reflect the importance of means-testing in combination with lower household incomes of households with (past) part-time work.

In Italy and Poland, those with interrupted work histories are less likely to receive out-of-work support than standard employees (Annex Figure 1.D.3, Panel A). In some countries, workers can qualify for unemployment insurance support after comparatively short periods in work, e.g. three months in France. In Austria, qualification periods are shorter for workers with repeated unemployment spells (such as seasonal workers). And in some countries, jobseekers are able to keep unused unemployment benefit entitlements for future claims if they found work prior to benefit expiration, among them Australia, Austria, France, Spain and the United Kingdom. This is, however not the case in Latvia and Poland. In France, a recent reform in 2021 has reduced entitlements of workers with short contracts and repeated unemployment spells by taking out-of-work spells into account when assessing the earnings base for benefit entitlements.

For the United States, effective protection gaps are insignificant for all granular employment types. This is connected to the specific mix of benefits in the United States and the choice of vignette – a low-income individual who has been persistently out of work (at least six months over the reference year) and is therefore in clear need of support:

Means-tested benefits make up the bulk of payments to working-age households in the United States, in particular at the bottom end of the income distribution (see section 1.2).There are typically no access gaps to means-tested benefits for non-standard workers; in fact, means-tested benefits may be more accessible and generous for non-standard workers (see Box 1.2).
The only benefit that depends on past employment – unemployment compensation – has a maximum receipt duration of 26 weeks depending on the state (see Chapter 2).
Because of data limitations, it is not possible to perform the above analysis for jobless individuals with shorter out-of-work durations for European countries.18 Looking at shorter unemployment durations is, however, possible with the SIPP. Section 1.5 presents an adaption of the econometric model that allows also looking at shorter episodes of joblessness.

1.5. Granular results on social protection gaps for the United States

Because benefit receipt is reported in the SIPP on a monthly basis, it is possible to adjust the model described in section 1.4 to include shorter out-of-work spells (below six months). Since the maximum duration of unemployment compensation is 26 weeks (depending on the state, see section 2.3), this approach is more suitable to detecting differences in unemployment compensation receipt. Including shorter out-of-work spells also increases the size of the sample of out-of-work individuals, which enables a more granular look at de facto access gaps for racial and ethnic groups as well as women and men.

As for the econometric model described in section 1.4 and in more detail in (Immervoll et al., 2022[5]), the sample consists of working-age, non-retired individuals with a complete employment history over the years 2014 – 2016.19 To guarantee that the model captures all relevant work and earnings history that determines eligibility to unemployment compensation, the model contains two groups of jobless individuals:

Individuals who have been out-of-work for the entire duration of the panel – 2014‑16, either unemployed or labour-market inactive. These individuals are persistently out-of-work.
Individuals who have worked for the first 12 months of the panel and became jobless – either unemployed or labour-market inactive – at some point between month 13 and month 36 of the panel. The 12‑month observation period is chosen to coincide with the assessment period for unemployment compensation (the period that is used to calculate unemployment compensation amounts, see section 2.3). The model categorises these workers as full-time, part-time, or self-employed if, out of the 12 months directly preceding the out-of-work spell, they were full-time or part-time wage and salaried workers, or self-employed, for at least nine months. Workers who combined full-time/part-time/self-employed work and were in neither status for more than eight months are classified as hybrid workers.

The left-hand-side variable of interest is the monthly average of the total package of working-age benefits as in the model described in section 1.4, calculated over the entire spell.20 The regression models determining benefit receipt (yes/no) and benefit amounts are equally similar to the comparative model, but only control for earnings over the 12 months preceding the start of the out-of-work spell, in-line with the short assessment period for unemployment compensation in the United States compared to other countries (see section 2.3). Deciles of current household incomes are similarly calculated on a monthly basis over the entire spell, see Annex Table 1.D.1 for descriptive statistics, and the table notes for details on the calculation of explanatory variables of the econometric model.

1.5.1. Including shorter unemployment spells reveals social protection gaps between standard and non-standard workers

In line with the comparatively short duration of UI benefits in the United States, differences between standard and non-standard workers appear in the US-specific model that includes individuals with shorter (one to six months) spells of joblessness. Previous part-time, self-employed or hybrid workers are about 10 percentage points, or around 20%, less likely to receive any benefits during an out-of-work spell than previous full-time, wage or salaried workers Figure 1.8.21 The gap for self-employed workers is not significant, likely because point estimates are less precise because of the lower number of self-employed workers in the sample, see Annex Table 1.D.1. Estimated generosity gaps are significant for part-time workers, in line with lower earnings, and therefore lower entitlements to UI.22

Figure 1.8. Social protection gaps become apparent when looking at shorter out-of-work spells

Overall support package for working-age individuals, 2016

1.5.2. For a given employment history, there are no significant social protection gaps across racial and ethnic groups

Larger sample sizes in the US-specific model also enable an analysis of social protection gaps for non-Latino whites,23 African Americans (including Latino African Americans) and Latinos. Sample sizes are insufficient to analyse social protection gaps for Asian Americans and other racial or ethnic minority groups (including mixed-race individuals).

For a given employment history (at least 12 months of standard or non-standard work immediately preceding the start of the out-of-work spell with earnings at or above the 40th percentile of the earnings distribution), there are no statistically significant differences in the de facto probability of receiving any benefits between non-Latino white and African American or Latino previous standard and non-standard workers (Figure 1.9, Panel A and B, left hand side). African American previous standard workers have significantly lower estimated benefit entitlements than white standard workers (10% compared to 15% of median household income, Figure 1.9, Panel A, right hand side) whereas Latino previous non-standard workers have significantly lower entitlements than white previous non-standard workers (6% compared to 11% of median household income, Figure 1.9, Panel B, right hand side). This is most likely due to lower previous earnings of African American and Latino previous standard and non-standard Latino workers (see descriptive statistics in Annex Table 1.D.1).

These results however only indicate that, for workers with similar employment histories, benefit receipt patterns are comparable among racial and ethnic groups. They do not inform about differences in employment patterns between groups: for instance, Latino jobseekers are more likely than non-Latino whites to have worked part-time before becoming unemployed, and African American jobseekers are more likely to have been self-employed (see Figure 2.11). Thus, as previously non-standard workers, they are less likely to be covered by benefits in the first place (Figure 1.8 and Figure 1.9). African Americans are also over-represented in the group of long-term unemployed workers, who do not have access to more generous unemployment compensation (see Chapter 2).

Holding previous work status constant may therefore mask larger labour market inequalities, with knock-on effects on benefit access and poverty. Chapter 2 looks in more detail at racial and ethnic differences in previous employment patterns for current jobseekers. There are no significant gender differences in benefit receipt patterns (not shown).

Figure 1.9. When controlling for labour market history, there are no sizeable racial coverage gaps

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Annex 1.A. Benefit receipt in the SIPP

The analysis is restricted to the working age population, and considers the following government transfers:

Unemployment Compensation benefits,
Sickness benefits,
Disability benefits (Supplemental Security Income SSI and veterans’ benefits),
Earned Income Tax Credit (EITC), partially imputed for the analysis (see below),
Supplemental Nutrition Assistance Program (SNAP),
State‑level General Assistance (GA) benefits,
Temporary Assistance to needy Families (TANF), and
Special Supplemental Nutrition Program for Women, Infants and Children (WIC).

With the exception of the EITC (see Annex 1.B), all benefit receipt information is taken directly from (self-reported) benefit receipt information in the SIPP (see Annex 1.C).

SNAP, GA, TANF and WIC are household-level benefits. In the SIPP, they can be received by an individual person, subset of the household or the entire household. As such, it is possible for multiple programme units (and received benefit amounts) to exist within one household (U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau, 2019[27]).

The SPgaps approach assumes that the entire household benefits from these payments. Household level benefits are therefore summed up over the entire household and assigned to the adult members of the household in equal shares. This leads to higher benefit receipt rates compared to the United States Census Bureau Statistics (see Annex Table 1.A.1). Differences are especially large for TANF and WIC, family benefits that are likely to be received by those living in larger households. In contrast, receipt rates for individual benefits such as Unemployment Compensation or disability benefits are virtually identical to Census Bureau calculation based on the entire SIPP. It is reassuring that the sample exclusions necessary for the analysis do not lead to a distortion of overall benefit receipt rates.

Benefit classification	Coverage in the OECD sample (%)	Coverage in in the SIPP according to the Census Bureau (%)
Unemployment Compensation	2.0	2.0
SSI Disability benefits	4.0	3.7
VA disability pension*	0.3	0.4
VA service‑related disability pension*	1.1	1.4
EITC	7.7	N/A
SNAP	16.8	11
State‑level General Assistance	0.9	0.3
TANF	1.2	0.3
WIC	6.2	1.2
Any social protection payments	27.9	N/A

*SIPP official statistics refer to the total US population aged 18‑64 except for VA disability and service‑related disability pensions, which refer to all persons aged 15+, and unemployment compensation, which refers to persons aged 15‑59.

Note: Individual components do not sum to total as some individuals receive benefits from multiple sources. To ensure comparability with other countries, coverage for household-level benefits (SNAP, GA, TANF, WIC) is defined on the household rather than the family level, resulting in higher coverage rates.

The OECD sample refers to the working age population in 2016 (aged 18‑64) who were not in military service or students, equalling to a (weighted) sample of 180 503 443 individuals.

Source: OECD calculations based on 2014 SIPP Panel data (reference year is 2016), the United States Census Bureau: Survey of Income and Program Participation (SIPP): detailed programme receipt tables (2016), https://www.census.gov/data/tables/2016/demo/public-assistance/sipp-receipts.html, (last accessed 25March2022).

Annex 1.B. Earned income and child tax credits

A particularity of the income support architecture in the United States is its comparatively heavy reliance on tax credits as a tool for working age income support. As the Social protection gaps analysis aims to compare the effective reach of income support across countries, including tax credits in the total package of income support as far as possible was a priority.

As a tax credit, the EITC amounts are not directly reported in the SIPP. However, the SIPP does include a question on whether an individual received an Earned Income Tax Credit (EITC) on their tax form. Because de facto receipt of the EITC is recorded in the SIPP, and amounts are deterministic, the Secretariat decided to impute EITC amounts based on self-reported recipients’ previous year’s income and the number of dependent children in a given household. As the income reference year for this analysis covers receipt during the calendar year 2016, the EITC amounts were imputed using policy rules as of the 1January 2015.

While the imputation was straightforward, there were some discrepancies between self-reported incidence of EITC receipt and entitlement based on past income and household composition. About a third of all individuals who reported receiving the EITC had imputed amounts of zero because their previous year’s earnings were either too low or too high to be entitled to the tax credit. Self-reported EITC receipt was also lower than according to tax records (Annex Table 1.B.1).

The volume of EITC payments was somewhat lower in the imputation than in administrative statistics, with the average imputed value 13% lower than according to IRS tax returns data (Annex Table 1.B.1). Underreporting of the EITC is therefore likely to contribute to the overall low receipt rate of income support in the United States as compared to other countries.

	Number of Recipients (in millions)	Average annual amount for recipients, in USD
SIPP self-reported recipients, full sample	21.2	n.a
OECD imputation, SIPP full sample	13.7	2 111
OECD imputation, working-age sample*	9.5	2 332
OECD imputation, out-of-work estimation sample **	1.7	1 747
Internal Revenue Service, Tax Returns Statistics	27.4	2 434

*The OECD sample refers to the working age population in 2016 (aged 18‑64) who were not in military service or students.

** The out-of-work estimation sample is the subset of the working-age sample, comprising individuals who were out-of-work for at least six months in 2016.

Source: OECD calculations based on the SIPP (2016), Internal Revenue Service, Statistics for Tax Returns with the Earned Income Tax Credit (EITC), https://www.irs.gov/credits-deductions/individuals/earned-income-tax-credit/earned-income-tax-credit-statistics (last accessed 25March2022).

Similarly, the Child Tax Credit (CTC) is an important programme for working parents: in 2017, 28.2 million recipients received USD 998 on average.24 CTC receipt is not recorded in in the SIPP either, but unlike the EITC, the SIPP does not contain information on whether the CTC was claimed. While it would have been possible to impute the CTC from statutory entitlement rules, this would be against the purpose of the social protection gaps approach, as the goal is to measure and compare de facto benefit receipt, taking into account differences in actual programme implementation as well as non-take‑up. The analysis therefore does not account for CTC receipt, and estimated benefit receipt incidence and amounts will therefore underestimate the true extent of income support for households with children in the United States.

Annex 1.C. Descriptive statistics

		Working-age population**, 2015		Out of work = 6 months in 2015
					By previous work status, years 2014 and 2013
				Estimation sample ***	Mostly out of work	Mostly standard work (SW)	Mostly non-standard work (NSW)
		All	With complete calendar info				Total	Self-	Part-time	Unstable
		All	With complete calendar info				Total	employed	Part-time	Unstable
Number of observations		23 131	13 223	3 430	2 531	354	545	72	177	296
Number of observations		27 450	23 441	3 371	2 632	271	467	71	102	293
Population (weighted, in thousands)		190 017 866	113 349 006	27 827 973	19 794 433	3 155 967	4 877 574	596 098	1 646 020	2 635 456
Population (weighted, in thousands)		786 172	654 378	100	75	10	15	2	4	10
Number of individuals (% of out-of-work estimation sample)		-	-	100	71	11	18	2	6	9
		-	-	100	75	10	15	2	4	10
Women (%)		51	51	69	73	53	62	57	71	57
Women (%)		50	50.9	64.3	65.3	56.9	62.5	53.6	70.0	61.6
Strong health limitations (%)		9	11	20	23	11	15	10	10	19
Strong health limitations (%)		5	5	14	17	7	8	8	7	9
Adults receiving benefits (%) ^†	Total	18	22	49	50	42	46	38	48	47
	Total	48	48.5	68.3	68.1	72.1	67.6	50.4	69.5	70.2
	average amount (% of median income)	11	11	9	10	7	7	9	7	7
	average amount (% of median income)	17	17.8	24.3	24.0	26.0	23.3	16.5	20.2	25.1
	Without children	16	18	44	49	35	31	26	28	34
	Without children	28	29	59	60	61	55	34	60	58
	average amount (% of median income)	11	11	11	12	8	6	6	5	7
	average amount (% of median income)	25	25	28	29	28	25	23	22	27
	With children	19	25	52	50	53	58	49	63	57
	With children	69	69	79	79	83	80	70	79	81
	average amount (% of median income)	10	11	7	7	7	7	11	7	7
	average amount (% of median income)	14	15	21	20	25	22	13	19	24
	With children under the age of 6	20	26	62	61	54	73	79	67	75
	With children under the age of 6	80	81	86	85	89	85	78	90	85
	average amount (% of median income)	11	11	7	7	7	7	8	8	7
	average amount (% of median income)	18	18	22	20	26	23	14	20	24
Household composition	Adult living alone	13	15	10	10	9	8	10	9	7
	Adult living alone	12	12	12	13	11	11	12	10	11
	Couple without children	25	27	22	21	26	22	25	19	24
	Couple without children	22	22	22	23	20	19	23	19	20
	Three adults or more without children	16	15	19	19	22	18	16	19	18
	Three adults or more without children	18	18	20	20	18	19	20	20	18
	Couple with children	27	27	25	26	20	25	26	25	26
	Couple with children	32	33	29	27	34	33	32	32	34
	Three adults or more with children	15	13	20	20	19	22	21	24	21
	Three adults or more with children	13	12	14	14	14	14	12	14	13
	Lone parent	5	4	4	3	3	4	2	4	5
	Lone parent	3	3	4	4	3	4	2	4	4
Annual earnings during 2014 (%) ††	No earnings	22	22	70	92	0	23	30	2	35
	No earnings	20	19	68	84	4	28	17	4	39
	Quintiles 1‑2	26	25	22	7	52	63	51	91	49
	Quintiles 1‑2	30	31	22	12	56	52	62	87	37
	Quintiles 3‑5	52	53	9	1	48	13	19	7	16
	Quintiles 3‑5	48	49	12	5	40	25	25	13	28
Annual earnings during 2013 (%) ††	No earnings	27	22	68	91	6	15	43	10	11
	No earnings	23	21	65	83	9	13	27	14	10
	Quintiles 1‑2	25	26	23	8	51	66	43	78	64
	Quintiles 1‑2	29	30	23	12	50	62	48	73	61
	Quintiles 3‑5	47	52	9	1	43	19	14	12	25
	Quintiles 3‑5	48	49	12	5	40	25	25	13	28
Disposable household income before social transfers in 2015 ^†††	Quintile 1	16	8	41	42	37	38	39	35	39
	Quintile 1	19	18	47	51	34	41	42	38	43
	Quintile 2	13	13	20	21	20	18	12	18	19
	Quintile 2	17	17	22	22	24	22	18	23	22
	Quintile 3	23	24	15	15	12	16	15	15	16
	Quintile 3	20	20	14	13	18	16	14	18	15
	Quintile 4	23	26	12	11	14	16	23	17	14
	Quintile 4	22	22	10	8	14	11	10	9	11
	Quintile 5	25	30	13	12	17	13	11	14	13
	Quintile 5	23	24	7	6	11	10	16	12	8
Number of months spent out-of-work	reference year (t)	3.0	2.8	11.2	11.6	9.4	10.4	9.7	9.9	10.9
	reference year (t)	3.0	2.8	11.3	11.6	9.9	10.7	10.5	10.3	10.9
	t‑1	2.9	2.8	9.3	11.7	0.8	4.9	0.3	1.0	8.3
	t‑1	3.0	2.8	9.8	11.7	0.8	6.1	0.3	0.8	9.1
	t‑2	3.1	2.9	8.8	11.6	1.4	2.4	2.5	3.2	1.8
	t‑2	3.3	3.1	9.2	11.6	2.1	2.2	2.3	3.5	1.7
Number of months worked in 2015	Standard work	6.4	7.5	0.4	0.1	1.6	0.5	0.2	0.5	0.5
	Standard work	6.4	6.8	0.5	0.2	1.8	0.6	0.4	0.4	0.7
	Self-employment	0.7	0.9	0.1	0.0	0.1	0.3	1.9	0.1	0.1
	Self-employment	1.2	1.3	0.0	0.0	0.0	0.2	1.0	0.0	0.1
	Part-time work	1.5	1.6	0.4	0.2	0.9	0.8	0.2	1.4	0.6
	Part-time work	1.1	1.2	0.2	0.1	0.3	0.5	0.1	1.2	0.2
Household composition	With children aged < 6	4	3	24	24	23	26	18	25	28
Household composition	With children aged < 6	3.5	3.1	21.1	18.9	27.5	26.2	21.0	20.7	28.8

* Unweighted average values for the following countries: Australia, Austria, Belgium, Estonia, France, Germany, Greece Hungary, Italy, Korea, Latvia, Lithuania, Portugal, Poland, Spain, the United Kingdom, the United States.

** Working-age population refers to age 18‑64 not in early retirement, and who were not in education or compulsory military service in the year before the reference period.

*** Estimation sample: Working-age individuals who have been out of work for six months or more during the reference year (t), and who were not in education or military service in year t‑1 (i.e. they could in principle acquire rights to any contributory benefits). The following observations were excluded: Those with incomplete labour-market calendar and earnings information, those without positive longitudinal sample weights, and those with reported transfers in the top percentile (to reduce the effects of outliers).

† Average amounts refer to benefit recipients.

†† Earnings quintiles based on pooled samples in years t‑1 and t‑2, excluding those with incomplete information (see notes on Estimation sample).

††† Disposable household income before social transfers is calculated over the entire population, including retirees.

Note: 18% of working age adults in the United States working age population sample have received benefits at some point in the income reference year, compared to 48% across countries with relevant information on average. For recipients, on average, the amount was 11% of median national household income in the United States, compared to 17% across countries on average. Among households with children in the United States, the benefit receipt rate was 16%, compared to 69% across countries on average.

“Children” are under the age of 18 or aged 18 to 24 who are economically inactive and live with their parents (EUROSTAT definition of dependent children). Breakdowns with the number of observations lower than 50 are not shown.

Source: EU Statistics of Income and Living Conditions for EU countries and the United Kingdom (EU-SILC, with observations pooled across the 2018, 2017 and 2016 waves to increase sample size), the German Socio‑economic Panel GSOEP (wave 2018), the Household, Income and Labour Dynamics Australia survey (HILDA, wave 2019) and the Korean Labour and Income panel study (KLIPS, wave 2019), and the US Survey of Income and Program Participation (SIPP 2014 wave).

Annex 1.D. Social Protection Gaps: granular results

Annex Figure 1.D.1. Self-employed workers receive little out-of-work support in some countries

Difference in the overall support package: Standard vs self-employed workers, at or before 2018/2019

Annex Figure 1.D.2. Part-time dependent employment: Comparatively good accessibility of out-of-work support, but lower entitlements than full-time employees

Difference in the overall support package: Standard vs part-time workers, at or before 2018/2019

Annex Figure 1.D.3. Unstable dependent employment: Comparatively good out-of-work income protection in most countries

Difference in the overall support package: Standard vs unstable workers, at or before 2018/2019

		Non-Latino white	African American	Latino	Asian/Other
Number of observations		1874	517	665	280

Previous work status*	Full-time	26%	27%	22%	21%
	Part-time	9%	8%	8%	9%
	Self-employed	4%	3%	5%	3%
	Hybrid	4%	4%	3%	4%
	Out-of-work	56%	59%	63%	64%

Duration of out-of-work spell	One to six months	25%	23%	17%	18%
	Seven to 12 months	11%	14%	14%	11%
	More than 12 months	64%	64%	69%	70%

Previous earnings quintile**	Zero earnings	56%	59%	63%	64%
	First quintile	11%	15%	14%	8%
	Second quintile	12%	14%	13%	13%
	Third quintile	8%	6%	6%	5%
	Fourth quintile	6%	5%	2%	5%
	Fifth quintile	6%	2%	1%	5%

Current income quintile***	First quintile	39%	67%	48%	43
	Second quintile	20%	20%	28%	22
	Third quintile	16%	8%	16%	10
	Fourth quintile	12%	4%	6%	15
	Fifth quintile	13%	2%	3%	11

* Full-time/part-time/self-employed worker: worked at least 12 months before the start of the out-of-work spell, at least nine months of which as a full-time/part-time wage or salaried or self-employed worker.

Hybrid worker: worked for at least 12 months before the start of the spell, transitioning between full-time and/or part-time and/or self-employment, but fewer than six months in either status.

Out-of-work: was out-of-work for the entire panel duration (2013 – 2015).

** Average monthly earnings over the previous 12 months, in the monthly earnings distribution over all workers with non-zero earnings.

*** Average monthly income before benefits over the entire spell, in the monthly income distribution over all households in the year of the start of the spell.

Note: The sample includes individuals who were either out-of-work for the entire panel duration (three years) or worked for at least the first 12 months of the panel duration and subsequently experienced a spell of joblessness of one month or longer.

Source: OECD calculations based on the SIPP (2014 panel).

Notes

← 1. Self-employed workers are all non-wage or salaried workers including independent contractors, see section 1.4.2 for details on the data used.

← 2. National and international open-data and digital government initiatives seek to facilitate the preparation and accessibility of such data sources for research purposes, including in the social policy domain (OECD, 2021[28]; OECD, 2018[29]; European Commission, 2022[30]). Yet, no comparative cross-country database of individual-level administrative data is currently available.

← 3. The Supplemental Nutrition Assistance Program SNAP makes up the bulk of spending on nutritional assistance; the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) for pregnant, breastfeeding, or post-partum mothers and children under the age of five is much smaller.

← 4. Information on sickness benefits is not available for Germany, while data for other European countries as well as Australia include employer provided sick pay whenever available. Receipt information on employer-paid sickness benefits is not available in the KLIPS.

← 5. The unemployment benefit variable includes severance payments for all countries except the United States; they are quantitatively important in Korea and in some Southern and Eastern European countries. The SIPP does not contain any information on severance payments.

← 6. The Social Protection Gaps analysis generally excludes in-kind benefits (such as free school-meals or subsidised housing) because cross-country comparisons between benefits in-kind are difficult to impossible. However, it considers SNAP and WIC to be close enough to cash to include it in the analysis.

← 7. Note that the package of working-age benefits in the United Kingdom and Korea includes refundable, income‑related child and in-work tax credits, whereas related programmes are not recorded as social transfers in some other countries. Receipt of means-tested tax credits in Korea may be somewhat under-reported (both the Earned Income Tax Credit, and also the Childcare Tax Credit, though the latter is not relevant for adults living alone).

← 8. The statistical model controls for age (including a higher order term), gender, education, household composition such as household size, presence of a partner and dependent children (under the age of 18) and young children (under the age of 6), as well as housing tenure and rent paid. The “vignette” only specifies the presence of children under the age of six, previous work status and earnings, income, health status, and that the worker worked for 12 months in the year before the reference period. This reflects the trade‑off between the sample size and good comparisons across countries.

← 9. In year ‑1, the baseline standard worker worked for the entire 12 months (this is to ensure recent contribution periods for contributory unemployment benefits), with at least six of them in full-time dependent employment, or five months in full-time dependent employment and three months in part-time dependent employment. In year ‑2, the baseline standard worker was in full-time dependent employment for at least six months, and out of work during at most two months.

← 10. E.g. in Austria, pregnant women are sometimes not required to actively seek work.

← 11. For details on the data sources for the other countries, see (Immervoll et al., 2022[5]).

← 12. The activity calendar and income in the SIPP always refers to activities and income in the year prior to the interview. Thus, the SIPP 2014 interviewed households in the years 2014 – 2017, and therefore holds labour market and income history for 2013‑16. The first three waves therefore indeed cover the period 2013 – 2015, with interviews one year later. This report however follows the convention of using the interview, not the income reference year used by other publications to facilitate comparisons.

← 13. Income and labour-market information pertain to 2015, but interviews were conducted in 2016, see endnote 12.

← 14. Individuals are defined as retired if they receive an old-age pension during the reference year. This can lead to imprecisions in countries where pensions are provided as a lump sum and therefore a pension income stream cannot be observed. In the country sample for the present study, this is only the case for Australia. Any means-tested old-age pension payments, veteran’s pensions etc. can however be identified in the Australian data source (HILDA).

← 15. https://www.oecd.org/els/soc/SEM271_Online Annexe Table B.xlsx

← 16. Responding to a steep increase in the number of “micro contracts” in France over the past 10 years, a 2021 reform reduced benefit generosity for those alternating repeatedly between short-duration employment and unemployment.

← 17. https://www.oecd.org/els/soc/SEM271_Online Annexe Table B.xlsx

← 18. The EU-SILC records benefit receipt amounts only at the annual basis, it is therefore not possible to link benefit receipt to short periods of joblessness.

← 19. Restricting the sample to individuals with complete observations for the entire three‑year panel duration does not lead to a change in the distribution of individuals over the categories race and income. Put differently, restricting the sample in this way does not lead to a disproportionate “loss” of disadvantaged labour market groups (as captured by the dimensions race and income).

← 20. A different specification looking exclusively at unemployment compensation receipt yields very similar results.

← 21. Alternative model specifications for vignettes with household disposable incomes in the middle of the distribution (between the 41st and the 70th percentile), as well as specifying that the vignette be unemployed at the beginning of the spell and not labour-market inactive, yield very similar gaps. Of course, the overall coverage rate is lower for the higher-income vignette (20% for previous standard workers, compared to around 50% for the low-income vignette).

← 22. Note that the vignette fixes previous earnings at or above the 40th percentile of the earnings distribution – part-time workers are expected to have lower earnings within this range.

← 23. There are two variables that identify race and ethnicity in the SIPP: race, that groups individuals into the categories “White alone”, “Black alone”, “Asian alone” and “Residual”, with the residual containing those considering themselves to be mixed race as well as other racial or ethnic minorities; and origin, that identifies “Spanish, Hispanic or Latino” individuals. In the 2016 SIPP, only 5.5% of African Americans and 3.1% of Asian Americans are also of Spanish/Hispanic or Latino origin. They are grouped with African Americans and Asian Americans, respectively.

← 24. Tax foundation (2020): “The Child Tax Credit: Primer”, published online under https://files.taxfoundation.org/20200413132740/Child-Tax-Credit-A-Primer.pdf

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