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  • 1
    UID:
    b3kat_BV048539905
    Format: 1 Online-Ressource (42 Seiten)
    Series Statement: OECD Social, Employment and Migration Working Papers no.271
    Content: Social protection systems play a key stabilising role for individuals and societies, especially in the recent context of heightened uncertainties. This paper proposes a new empirical approach for quantifying the accessibility and value of income transfers following an earnings loss. The approach allows to estimate and monitor gaps in the accessibility and value of social transfers between so-called "standard" and "non-standard" workers. It first presents a methodology for assessing support levels for jobless individuals in specific circumstances that allows for comparisons across countries and over time. It then illustrates the approach using longitudinal survey data in 16 OECD countries
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    b3kat_BV047928595
    Format: 1 Online-Ressource (40 Seiten)
    Series Statement: OECD Social, Employment and Migration Working Papers
    Content: Social protection systems use a range of entitlement criteria. First-tier support typically requires contributions or past employment in many countries, while safety net benefits are granted on the basis of need. In a context of volatile and uncertain labour markets, careful and continuous monitoring of the effectiveness of income support is a key input into an evidence-based policy process. This paper proposes a novel empirical method for monitoring the accessibility and levels of safety net benefits. It focusses on minimum-income benefits (MIB) and other non-contributory transfers and relies on data on the amounts of cash support that individuals in need receive in practice. Results show that accessibility and benefit levels differ enormously across countries - for instance, in 2015/16, more than four out of five low-income workless one-person households received MIB in Australia, France and the United Kingdom, compared to only one in five in Greece, Italy and Korea, three countries that have since sought to strengthen aspects of safety-net provisions
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    b3kat_BV047927959
    Format: 1 Online-Ressource (60 Seiten) , 21 x 28cm
    Series Statement: OECD Social, Employment and Migration Working Papers
    Content: Recent years have seen impressive advances in artificial intelligence (AI) and this has stoked renewed concern about the impact of technological progress on the labour market, including on worker displacement. This paper looks at the possible links between AI and employment in a cross-country context. It adapts the AI occupational impact measure developed by Felten, Raj and Seamans (2018[1]; 2019[2]) - an indicator measuring the degree to which occupations rely on abilities in which AI has made the most progress - and extends it to 23 OECD countries. The indicator, which allows for variations in AI exposure across occupations, as well as within occupations and across countries, is then matched to Labour Force Surveys, to analyse the relationship with employment. Over the period 2012-2019, employment grew in nearly all occupations analysed. Overall, there appears to be no clear relationship between AI exposure and employment growth. However, in occupations where computer use is high, greater exposure to AI is linked to higher employment growth. The paper also finds suggestive evidence of a negative relationship between AI exposure and growth in average hours worked among occupations where computer use is low. While further research is needed to identify the exact mechanisms driving these results, one possible explanation is that partial automation by AI increases productivity directly as well as by shifting the task composition of occupations towards higher value-added tasks. This increase in labour productivity and output counteracts the direct displacement effect of automation through AI for workers with good digital skills, who may find it easier to use AI effectively and shift to non-automatable, higher-value added tasks within their occupations. The opposite could be true for workers with poor digital skills, who may not be able to interact efficiently with AI and thus reap all potential benefits of the technology
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    gbv_1786135280
    Format: 1 Online-Ressource (60 p.) , 21 x 28cm.
    Series Statement: OECD Social, Employment and Migration Working Papers no.265
    Content: Recent years have seen impressive advances in artificial intelligence (AI) and this has stoked renewed concern about the impact of technological progress on the labour market, including on worker displacement. This paper looks at the possible links between AI and employment in a cross-country context. It adapts the AI occupational impact measure developed by Felten, Raj and Seamans (2018[1]; 2019[2]) – an indicator measuring the degree to which occupations rely on abilities in which AI has made the most progress – and extends it to 23 OECD countries. The indicator, which allows for variations in AI exposure across occupations, as well as within occupations and across countries, is then matched to Labour Force Surveys, to analyse the relationship with employment. Over the period 2012-2019, employment grew in nearly all occupations analysed. Overall, there appears to be no clear relationship between AI exposure and employment growth. However, in occupations where computer use is high, greater exposure to AI is linked to higher employment growth. The paper also finds suggestive evidence of a negative relationship between AI exposure and growth in average hours worked among occupations where computer use is low. While further research is needed to identify the exact mechanisms driving these results, one possible explanation is that partial automation by AI increases productivity directly as well as by shifting the task composition of occupations towards higher value-added tasks. This increase in labour productivity and output counteracts the direct displacement effect of automation through AI for workers with good digital skills, who may find it easier to use AI effectively and shift to non-automatable, higher-value added tasks within their occupations. The opposite could be true for workers with poor digital skills, who may not be able to interact efficiently with AI and thus reap all potential benefits of the technology.
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    UID:
    gbv_1770750592
    Format: 1 Online-Ressource (40 p.)
    Series Statement: OECD Social, Employment and Migration Working Papers no.252
    Content: Social protection systems use a range of entitlement criteria. First-tier support typically requires contributions or past employment in many countries, while safety net benefits are granted on the basis of need. In a context of volatile and uncertain labour markets, careful and continuous monitoring of the effectiveness of income support is a key input into an evidence-based policy process. This paper proposes a novel empirical method for monitoring the accessibility and levels of safety net benefits. It focusses on minimum-income benefits (MIB) and other non-contributory transfers and relies on data on the amounts of cash support that individuals in need receive in practice. Results show that accessibility and benefit levels differ enormously across countries – for instance, in 2015/16, more than four out of five low-income workless one-person households received MIB in Australia, France and the United Kingdom, compared to only one in five in Greece, Italy and Korea, three countries that have since sought to strengthen aspects of safety-net provisions.
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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