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  • 1
    ISBN: 9781464805394 , 9781464805424
    Language: English
    Pages: Online-Ressource (1 online resource (290 p.))
    Edition: Online-Ausg.
    Series Statement: World Bank E-Library Archive
    Parallel Title: Druckausg. Sundaram, Ramya Portraits of labor market exclusion
    DDC: 338.10923489
    Keywords: 2008-2011 ; Arbeitslosigkeit ; Soziale Ausgrenzung ; Bulgarien ; Estland ; Griechenland ; Ungarn ; Litauen ; Rumänien ; Cluster Analysis ; Eu-Silc ; Labor Market ; Labor Market Barriers ; Latent Class Analysis ; New Member States ; Social Assistance ; Social Exclusion
    Abstract: "Portraits of Labor Market Exclusion presents ""profiles"" or ""portraits"" of individuals who have limited labor-market attachment. It is widely accepted that those with limited attachment to the labor market are a highly heterogeneous group (including, for instance, recent job losers, long-term unemployed, school leavers with no labor-market experience, those close to retirement age, or people with caring responsibilities), and that understanding their circumstances and potential barriers is an essential prerequisite for designing and implementing a tailored and effective mix of policy support and incentives. The report takes a comprehensive view, focusing on both the labor market attachment of a country's out-of-work population and the social assistance package and poverty profile of the same segment of the population. In essence, the report looks at individuals through the lenses of both poverty/welfare status and labor market indicators, and, in doing so, the portraits helps move the dialogue from a purely labor market-centric view to a broader dialogue that includes social policy as a whole. This is an important shift; for instance, social protection programs, such as family benefits and maternity benefits, and broader social policy issues such as retirement ages, often have a great impact on who remains inactive. Specifically, the report presents portraits of the out-of-work population of six countries (Bulgaria, Estonia, Greece, Hungary, Lithuania and Romania) in terms of distance from the labor market, human capital, and labor supply conditions, as well as demographic conditions. The analysis relies on the European Union Statistics of Income and Living Conditions (EU-SILC) surveys for the years 2007 to 2011. Latent class analysis methodology allows multidimensional profiling of the out-of-work population, and identifies classes or groups of out-of-work individuals that are as homogeneous as possible within each class according to a set of observable characteristics, and as distant as possible between classes. Consequently, this analysis provide a much richer glimpse of the very different barriers to labor market integration that these various groups experience, considerably augmenting the limited amount of information contained in traditional descriptive statistics."
    Note: Description based on print version record
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 2
    Language: English
    Pages: 1 Online-Ressource (25 pages)
    Parallel Title: Erscheint auch als Print Version: Paul, Boban Varghese COVID-19, Poverty, and Social Safety Net Response in Zambia
    Abstract: What has the impact of the COVID-19 pandemic been on poverty in Zambia, and how can social protection programs mitigate these effects? This paper estimates the pre-pandemic poverty level in Zambia and then simulates the distributional impact of COVID-19 in the country. The paper also estimates the impact of a social cash transfer program that led the COVID response, on poverty levels. In the absence of recent nationally representative household survey data, this is done by updating the consumption distribution in the 2015 Living Conditions Monitoring Survey using annual real per capita gross domestic product growth rates for specific sectors. The study shows that the national poverty headcount rate increased from 54.4 percent in 2015 to 55.8 percent in 2019, and this change was driven entirely by rural areas. By contrast, the economic impact of COVID-19 has disproportionately impacted urban areas and exacerbated the already high poverty levels, with the poverty headcount increasing to 57.6 percent in 2020. Expanding and enhancing cash transfers have been a key policy lever that many countries have used to mitigate the negative economic consequences of the pandemic. Simulations in Zambia suggest that a fully operational social cash transfer program with the current and proposed enhanced transfer amounts has the potential to reduce poverty significantly-by four and six percentage points, respectively. Beyond this specific analysis, the paper makes a case for the innovative use of existing data to inform adaptive or shock responsive social protection, even in largely data poor environments
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