Documents Hyee, Raphaela 4 results

"This Working Paper looks at some of the shorter and longer-term impacts of the COVID-19 pandemic on labour markets across OECD countries. It examines how job retention schemes, unemployment benefits, sickness and disability-related benefits and their prompt expansion have succeeded in protecting people's jobs and incomes; and how successful countries were in preventing structural increases in labour market inactivity, as indicated by the development of disability benefit receipt. The paper demonstrates and confirms the overall significant success in the labour market response to the COVID-19 pandemic across OECD countries. This contributes to explaining why the COVID-19 pandemic has disappeared from the labour market discussion much faster than initially expected, despite an unprecedented shock to labour markets and a sharp decline in working hours at the outset of the crisis. Preventing sustained long-term unemployment and long-term sickness absence has secured jobs and incomes and prevented inactivity ."

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"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."

"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."

"Social protection systems play a key stabilising role for individuals and societies, especially in the recent context of heightened uncertainties. Income stabilisation and related social policy objectives hinge on the extent to which social protection is accessible for those requiring support. This paper proposes a new empirical approach for quantifying the accessibility and value of income transfers following an earnings loss. 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. The illustration focusses on differences in entitlements between people who were in "standard" and "non-standard" employment prior to joblessness. Results show that, prior to the COVID pandemic, income support gaps between standard and non-standard workers were often sizeable. For instance, in Korea, job losers with prior standard employment were nearly twice as likely to receive income support as otherwise similar individuals with a history of non-standard work. Gaps were also large in Italy and Portugal. By contrast, gaps were statistically insignificant in Australia, Austria, Belgium, Germany, Hungary and the United Kingdom. As these latter countries follow very different social protection strategies, results suggest that limiting support gaps for non-standard workers is achievable with different policy designs and targeting mechanisms."