Reports

COVID-19 is likely to leave long-lasting effects on local labour markets. It is accelerating a pre-existing trend towards automation, as firms look even more to new technologies to pandemic proof their operations. While automation offers the opportunity to boost productivity, it can also lead to job polarisation as vulnerable workers who lose their jobs may not have the skills needed in a changing labour market. This OECD report examines the potential impacts of automation on people and places across Australia. It also sheds light on policies and programmes that can help regions and cities to prepare for the future of work.

The longer run consequences of the pandemic will partly hinge on its impact on high productivity firms, and the ongoing process of labour reallocation from low to high productivity firms. While Schumpeter (1939) proposed that recessions can accelerate this process, the nature of the COVID-19 shock coupled with a policy response that prioritised preservation (over reallocation) raises questions about whether job reallocation remained productivity-enhancing. Using novel, near-real-time data for Australia, New Zealand and the United Kingdom, this paper shows that while labour turnover fell in response to the pandemic, job reallocation remained connected to firm productivity – that is, high productivity firms were more likely to expand and low productivity firms were more likely to contract. The pandemic coincided with a temporary strengthening of the reallocation-productivity link in Australia – but a weakening in New Zealand – which appears related to the design of job retention schemes. Finally, firms that intensively used Apps to manage their business were more resilient, even after controlling for productivity. Thus, while policy partly suppressed creative destruction, the nature of the shock – i.e. one where being online and able to operate remotely were key – favoured high productivity and tech-savvy firms, resulting in a reallocation of labour to such firms. The use of timely, novel data to investigate the allocative effects of the pandemic marks a significant advance, given that the seminal paper on productivity-enhancing reallocation during the Great Recession arrived some six years after Lehman Brothers collapsed.

The consequences of the pandemic for potential output will partly hinge on its impact on high productivity firms, and more generally the ongoing process of productivity-enhancing reallocation – the rate at which scarce resources are reallocated from less productive to more productive firms. While Schumpeter (1939) originally proposed that recessions can accelerate this process, the more ‘random’ nature of the COVID-19 shock coupled with a policy response that prioritised preservation (over reallocation) raises questions about whether job reallocation remained productivity-enhancing over the course of the pandemic. Despite these headwinds, our analysis based on novel high-frequency employment data for Australia shows that job reallocation (and firm exit) remained solidly connected to firm productivity over 2020. The greater resilience of high productivity firms is significant, given that an indiscriminate shakeout of such firms – and the associated destruction of firm-specific intangible capital – would have imparted significant scarring effects. As it turns out, the temporary nature of Australia’s job retention scheme (JobKeeper) made an important (and surprising) positive contribution to this process, with material consequences for aggregate productivity. But the scheme appears to have become more distortive over time, justifying its timely withdraw – on productivity grounds at least.

Increasing productivity at farm level is a key policy objective across most countries and fundamental to the overall performance of agricultural and food systems. This paper applies dynamic statistical methods to farm level data in order to identify the determinants of farm performance over time, in terms of productivity and measures of local sustainability. The analysis sheds light on the effects of policies on productivity, and the links between productivity and sustainability outcomes. It draws on key findings from seven case studies: crop farms in Australia, France, Italy and the United Kingdom (England and Wales); and dairy farms in the Czech Republic, Denmark and Norway, with different sample periods, from the most recent three decades to the last five years. A key finding is that policy changes increasing the degree of decoupling of payments have a positive impact on productivity. Furthermore, with the right incentives, productivity growth can be more locally sustainable insofar as farms can produce more output with less inputs that harm the environment. The detailed background work on the seven samples of crops and dairy farms in the above countries is available in OECD Food, Agriculture and Fisheries Paper N°165.

This paper provides detailed farm level data evidence on the dynamics of farm performance from case studies covering crop farms in Australia, France, Italy and the United Kingdom (England and Wales), and dairy farms in the Czech Republic, Denmark and Norway, with different recent sample periods of five to thirty years. An increase in productivity over time is common to all countries and most crop farm classes, but productivity dynamics vary significantly. In Australia, strong productivity growth among the most productive crop farms has led to an increase in the gap between the highest and lowest performing farms; whereas in France, Italy and the United Kingdom, productivity growth was weak among the most productive crop farms and the lowest performing farms closed the productivity gap. Productivity also increased among dairy farms, with an increasing gap between the most and the least productive farm classes in the three sample countries. The impact of policy changes on performance dynamics is analysed for decoupled payments in France and England, and dairy payments in the Czech Republic. The main findings across countries and policy implications are discussed in OECD Food, Agriculture and Fisheries Paper N°164.

Children’s learning, development and well-being are directly influenced by their daily interactions with other children, adults, their families and the environment. This interactive process is known as 'process quality', and leads to a key question – which policies set the best conditions for children to experience high-quality interactions in early childhood education and care (ECEC) settings? This report discusses five main policy levers and their effect on process quality, focusing particularly on curriculum and pedagogy, and workforce development. It presents indicators covering 26 countries and jurisdictions, 56 different curriculum frameworks, and more than 120 different types of ECEC settings.

Sound and timely data and statistics are essential for designing better policies for better lives. When the right data are available and used by policy makers, they play a crucial role in managing crises, as revealed during the COVID-19 pandemic. They are also indispensable for transparent and accountable delivery of policies and services and to guide business and investment decisions in line with the Sustainable Development Goals (SDGs). The first 2021 edition of the OECD’s Data for Development Profiles is a unique source of information and insights on how members of the Development Co-operation Committee (DAC) allocate official development assistance (ODA) to statistical capacity development and strengthening data ecosystems in low and middle income countries. By providing a comprehensive overview of members’ data and statistical policy priorities, strategies, funding, delivery modalities and partnerships, the profiles serve as a baseline for co-ordinating international support and highlight ways forward for greater impact and effectiveness.