2. Challenges and opportunities in a changing world of work

COVID-19 has led to a labour market shock, putting unprecedented pressure on people, places, and firms. While people were forced to stay home under lockdowns, economic activity has been interrupted, leading to declining GDP and rising unemployment. Unemployment rose in many OECD countries as the pandemic spread throughout the world. Some countries have been harder hit than others.

Ireland’s gross domestic product is projected to shrink by 2.1% in 2020, well below 7.8% for overall Europe (European Commission, 2020[1]). Public health measures to contain the spread of COVID-19 resulted in the largest monthly increase in unemployment ever recorded in March 202. By April 2020, more than 1 million people were in receipt of support interventions to the labour market, including those in receipt of the COVID-19 Pandemic Unemployment Payment1 and the Employment Wage Subsidy Scheme.2

The COVID-19 pandemic is already having a severe impact on job creation in Ireland. In response to the crisis, the Irish Government facilitated access to Jobseekers Benefit or Jobseekers Allowance for those whose jobs have been affected by the pandemic. As of March 2020, the number of people on the Live Register increased to 205 000 people, increasing 12.3% compared to February 2020 (Figure 2.1). By July 2020, the number had peaked at 244 000 people, or 18% above the numbers compared to July 2019.

In addition, the Irish Government introduced various income support schemes in response to the shock in the labour market. These schemes were initially set up as short-term emergency supports, which were extended as the crisis continued. The existence of multiple schemes and the overlap in the number of people who were registered on either the Live Register or the COVID-19 income support schemes made it very hard to measure the number of people in the labour market.

The overall headline unemployment numbers, which are based on the Live Register, do not reveal the full extent of the labour market shock of COVID-19. As a solution, the Central Statistics Office of Ireland (CSO) started releasing a COVID-19 adjusted unemployment measure, including the Pandemic Unemployment Payment claimants as unemployed. This new measure provides an additional lens to the overall unemployment situation. For instance, while the standard measure of unemployment was 7.2% in December 2020, the COVID-19 Adjusted Measure of Unemployment could indicate a rate as high as 20.4% for the same month (Figure 2.2).

As the crisis intensified, Irish firms have significantly reduced their hiring efforts. Recent evidence based on data from Indeed.com, the largest online job site in the world, shows that the labour markets experienced a significant contraction when the pandemic first hit. Compared to the average number of vacancies posted online throughout 2018-19, the Irish economy has seen a drop in available vacant jobs of more than 56% by June 2020 (Figure 2.3, Panel A). After peaking in the summer of 2020, Ireland narrowed most of the gap to 16% as of December 2020.

The headline figures mask the unequal impacts of the crisis on different types of jobs. During this period, job ads for positions in the medical, information, social services and nursing grew (Kennedy, 2020[2]). On the other hand, jobs in sectors heavily affected by lockdowns and social distancing measures, such as hospitality, tourism, beauty and wellness or face-to-face consumer services, experienced significant declines.

The Irish economy experienced one of the largest drops in overall vacancies in the first half of 2020 and yet one of the faster recoveries relative to comparable countries in the second half of the year (Figure 2.3, Panel B). By June 2020, while all countries saw lower vacancy numbers, Ireland experienced a markedly steeper decline than other countries, performing only better than the United Kingdom. Despite the large drop in the first half of 2020, Ireland caught up with these countries in the second half of the year and narrowed the gap.

Past economic shocks have affected economies and societies profoundly but also asymmetrically across geographies. Despite the shock’s symmetric origin and its global extent, the impact of COVID-19 across regions has been heterogeneous. In the global financial crisis of 2008, employment declined in almost all OECD regions, although the scale of these losses and the time it took employment levels (number of jobs) to rebound varied considerably across regions. The hardest-hit places lost 20% or more of their jobs at their respective lowest points, and in many regions, it took five years or more for employment to recover to the pre-crisis levels. Still, in 2018 nearly half of the OECD regions had unemployment rates higher than in 2008. While the COVID-19 shock is of a different scale and nature than any other shock in recent history, local resilience patterns to the last crisis suggest that the hardest-hit places will struggle to recover quickly.

Faced with the COVID-19, the resilience or vulnerability of countries and regions will depend on a wide range of factors related to health but also the economy. For instance, specialisation in sectors vulnerable to an economic shock, the share of jobs amenable to teleworking, and trade exposure may all impact local vulnerabilities. The impact and the intensity of the shock will also depend on the number of factors such as the pace and scale of roll-backs of short-time work or other schemes to promote job retention; the rigidity of employment protection legislation; employer expectations about how long COVID-19 will impact their activities; and the degree to which firms go out of business, reduce or re-organise activities permanently.

Widespread social distancing measures to contain the spread of COVID-19 have required nationwide lockdowns and international travels bans, interrupting both local and international economic activities. While some people and sectors are able to continue their activities from home, lockdowns practically force many to stop working. In this context, not all sectors are equally able to transition to remote working and therefore mitigate the economic disruptions due to the lockdown. Consequently, some economies and regions where sectors most heavily affected by these crises represent an important share, naturally are affected more than others.

Targeted containment measures in regions and cities continue to be the reality until the virus is contained or herd immunity is reached. This will undoubtedly have important impacts on local employment beyond what can be deduced based on local economic structure, but where and when cannot be predicted at this stage. Consequently, some regions are likely to suffer more than others from containment measures, facing a steeper economic recession and larger shares of jobs at risk. According to the OECD estimates, sectors most at risk include manufacturing of transport equipment; construction; wholesale and retail trade; air transport, accommodation and food services; real estate services; professional service activities; and arts, entertainment and recreation (see Figure 2.6 for region- and sector-specific estimates and Box 2.2 for further information on the methods to estimate the share of jobs potentially at risk).

Accommodation and food industries are the other lead drivers of the jobs losses in Irish regions. Tourism and services – including large retailers, coffee shops and restaurants, among other hospitality business – rely on face-to-face contact and have thus been devastated by the lockdown. Similarly, culture and creative industries will likely take a deep and prolonged hit and be the driver of the other main driver of the risk across all regions. The recovery for these sectors is likely to be slow as international tourism is anticipated to decrease by 60-80% in 2020 and is not expected to rebound quickly (OECD, 2020[6]).

COVID-19 could lead to deepening divides within labour markets at the national and local level. In many countries, the low skilled, low-wage workers, part-time workers, female workers, migrants and young people have been the most vulnerable to COVID-19-related job losses (Adams-Prassl et al., 2020[7]; Alstadsaeter et al., 2020[8]; Beland, Brodeur and Wright, 2020[9]; Belot et al., 2020[10]). The initial negative impact on employment was larger for women, minorities, the less educated, and the young, even after accounting for the industries and occupations they worked in (Lee, Park and Shin, 2021[11]).

Young people have again been hit hard relative to the rest of the population, similar to the global financial crisis (OECD, 2016[12]). This year’s graduates, sometimes referred to as the “Class of Corona”, are leaving schools and universities with often very poor chances of finding employment or work experience in the short term. Meanwhile, their older peers are already experiencing the second heavy economic crisis in their still-young careers.

Workers who lose their jobs during the COVID-19 crisis are also likely to suffer its consequences in the medium and long term. Workers who lose their jobs during an economic crisis are likely to suffer from the “scarring effects”, which refers to the negative long-term effect that unemployment has on future labour market possibilities in itself. Evidence from earlier recessions shows that workers who lose employment during a recession experience suffer from negative labour market experiences in the future (e.g. shorter contracts, lower hourly wages and so on), compared to an otherwise identical individual who has not been unemployed (Davis and Von Wachter, 2011[13]) Job losses during the COVID-19 crisis could also lead to weaker labour force participation in the long term. Workers who lose their jobs during a crisis such as the current one will face long-term unemployment and are also more likely to leave the labour market and become inactive (Yagan, 2019[14]).

The COVID-19 crisis presents several risks but also a few opportunities for persons with disabilities in Ireland. In the short term, the crisis could further exacerbate the barriers they face to fully participating in the labour market. In contrast, the shift to remote work provides a new avenue to promote overall participation in the medium term.

Prior to the pandemic, persons with disabilities had significant gaps in employment and unemployment. Ireland faces a large gap when comparing employment outcomes of persons with disabilities to the EU-OECD average (Figure 2.7). For instance, one out of every two working-age disabled people were employed in 2017 across the EU-OECD, whereas it was one of three in Ireland. The gap is also reflected in the unemployment rate. As of 2017, while 51% of the disabled working-age population participating in the labour market in 2017 across EU-OECD, this rate is only 30.1% in Ireland. Thus, there is significant untapped potential if more disabled people were active in the labour market.

Persons with disabilities face a labour force participation gap across all regions in Ireland. Nevertheless, this gap varies significantly within the country, indicating that certain local factors influence the participation rate. Figure 2.9 plots the differences for each county or city. Each bar corresponds to a locality and indicates the gap in labour force participation between persons with disabilities and the overall population living in the same area, relative to the overall gap in Ireland (i.e. national average = 0).3 For example, in Dún Laoghaire-Rathdown, the labour force participation gap is 6.9 percentage points smaller than the gap in Ireland, suggesting that some local factors facilitate the participation of persons with disabilities in the local labour force. At the other extreme, in Roscommon, the gap is 6.2 percentage points larger than the national average, indicating an even larger labour force participation gap than at the country level.

Human capital is a crucial element in understanding the labour force participation differences within societies. Individuals with higher years of formal education have a higher probability of participating in the labour market, earning higher wages, and working longer years. Similarly, evidence from various countries show better labour market outcomes for higher educated persons with disabilities (Baldwin and Johnson, 1994[16]; Kidd, Sloane and Ferko, 2000[17]; Charles, 2003[18]; Meyer and Mok, 2019[19]). The relationship between education levels and labour force participation rates of persons with disabilities do not indicate causality. For instance, persons with disabilities may drop out of formal education as they do not expect to participate in the labour market or have low labour market attachment. Alternatively, persons with lower levels of education are more likely to work in occupations with a higher risk of work-related disability than those with higher education levels (Cater and Smith, 1999[20]).

Persons with disabilities are much more often low educated than persons without disabilities. Four out of ten (or 41.8%) working-age individuals with disabilities are low-educated – a twice as high share compared to persons without disabilities (17.5%) (Figure 2.11). In contrast, the share of individuals with medium-levels of education among persons with disabilities is around 20.6%, which is lower than 28.2% observed for persons without disabilities. The real difference, however, is driven by the share of high-educated individuals. Among persons with disabilities, roughly one in three is highly educated, while for persons without disabilities it is one in two.

High-educated persons with disabilities participate much more often in the labour market than low-educated persons with disabilities. High-educated persons with disabilities represent half of the workers with disabilities in the labour market, although they only constitute 36.3% of persons with disabilities who are of working-age. In contrast, low-educated persons with disabilities represent 27% of those who are active in the labour market, far below their share in the working-age population (41.8%).

While low-educated individuals participate less often than high-educated in the labour market across the entire working-age population, the labour force participation gap between education groups is much larger among persons with disabilities. This suggests that low-educated persons with disabilities face particular labour market barriers.

More detailed information from the 2016 Census confirms that persons with disabilities more often are low-educated and make their way less often high up on the education ladder. In Figure 2.12 each bubble corresponds to the share of persons with disabilities within the population by education level in 2016, where bubbles reflect the size of the education group. Given that persons with disabilities corresponded to 15.5% of the population aged 15 and above, any bubble that falls to the right side of the vertical line indicates a higher share of the persons with disabilities within the group. Persons with disabilities are overrepresented among those with no formal education, primary and lower secondary education. For instance, they constitute 56% of those with no formal education or 36% of those with primary schooling as their highest level of education. In contrast, they are underrepresented in higher educational degrees, especially in bachelor’s degree and above.

High-school drop-out rates are an important driver of the low levels of education among persons with disabilities. Compared to the overall population, persons with disabilities have a higher likelihood to drop out of school, especially before the age of 17 (Figure 2.13). Two in five of those who drop out of school before the age of 14 have disabilities. About one in four of those who drop out of school at the age of 15 have disabilities. These elevated rates suggest that persons with disabilities face important education barriers.

In the past 20 years, significant progress has been made to improve the overall education levels in Ireland. Between 2004 and 2018, the share of low-educated decreased from 65.4% to 38.3% (or 27 percentage points) among persons with disabilities, and from 37.8% to 18% (or 20 percentage points) for persons without disabilities (Figure 2.14). Despite the progress, the share of persons with disabilities with low levels of education in Ireland remains high compared to other European OECD countries, in particular when compared to their peers without disability (Figure 2.15). Across OECD countries, 31% of persons with disabilities have low levels of education, while the share is 38% in Ireland. Moreover, Ireland has the largest disability education gap across OECD countries. Irish persons with disabilities have a 20 percentage point higher chance of having a low education.

Workers with disabilities may be more concentrated in specific industries or occupations that may be better suited for their skills and capacities. If such patterns exist, the growth or decline of industries or occupations with a high share of persons with disabilities can explain their labour market participation shifts. Understanding such patterns would also allow policy makers to target policies to support their employment in certain industries or occupations.

The labour force participation gap of persons with disabilities in Ireland does not differ much across occupations or industries. Workers with disabilities are employed across all sectors and constitute, on average, 6.5% of workers in each industry. Similarly, they are employed in all types of occupations without any clear patterns. On average, workers with disabilities constitute 7.2% of all occupations. Their distribution does not indicate any concentration in occupations requiring specific task contents employing certain skills or capabilities. Thus, there is significant untapped potential if more disabled people were active in the labour market.

Most Irish workers work as employees and full-time. In 2018, about 84% of workers were employees, with the rest working as self-employed. Among all workers, 75% worked full-time, when part-time work is defined as work of less than 30 hours per week in the main job.

Persons with disabilities in Ireland less often work full-time, both as employees or self-employed. While 76% of employees without disability work full-time (either as employed or self-employed), the share is only 66% for those with disabilities (Figure 2.16, Panel A). In contrast, 26% of workers with disabilities are employed part-time, which is larger than 21% observed for persons without disabilities. Similarly, the share of part-time self-employed is 8% which is twice the observed share for persons without disabilities. In terms of full-time self-employment, however, there are no differences between both groups.

Part-time employment can be voluntary or involuntary. As discussed in Chapter 3, part-time work can accommodate persons who prefer to work fewer hours or who face constraints, including for persons with disabilities. It can also facilitate a better work-life balance. On the other hand, part-time employment may be involuntary if workers cannot work more hours in their present job or find a full-time job.

Part-time work is more prevalent among persons with disabilities, partially due to involuntary part-time employment. While it could be expected that persons with disabilities may be inclined to work part-time to accommodate their needs, this is not the main driver in Ireland’s case. Among workers without disabilities, only 2% report working part-time although they want to work more, while it is 25% among persons with disabilities (Figure 2.17). The large gap between the two groups is an indication of an underlying issue preventing persons with disabilities from contributing to the labour market at their full potential. Experience from OECD countries indicates that involuntary part-time work increases during economic downturns (OECD, 2019[21]). Thus, it is not unreasonable to expect that the current economic crisis due to COVID-19 can increase involuntary part-time exacerbating conditions for persons with disabilities.

Persons with disabilities have about as often a temporary contract than the rest of the labour market. In Ireland, 94% of workers with disabilities hold a permanent contract, while this rate is 91% for persons without disabilities (Figure 2.16, Panel B). Temporary contracts generally provide lower job security levels and social protection compared to workers with permanent contracts. Workers on temporary contracts are generally disproportionally affected by economic downturns. Early evidence from OECD countries indicates that workers on temporary contracts were among the first to lose their jobs throughout the COVID-19 pandemic (OECD, 2020[22]).

Persons with disabilities are more often at risk of poverty; in particular so in Ireland. Households with at least one adult with disabilities faced high risks of poverty, as shown by data from before the COVID-19 pandemic. On average across the 26 OECD European countries, one in five households (22%) with at least one adult with disabilities risked poverty (Figure 2.18, Panel A). Instead, in Ireland one in three households with an adult with disabilities (32.3%) is at risk of poverty.

Persons with disabilities in Ireland and other European countries are more likely to face poverty compared to persons without disabilities. Figure 2.18 (Panel B) shows that in all countries, households with an adult with disabilities have a higher probability of facing poverty compared to other households (i.e. relative probability is above 1). In European OECD countries, households with persons with disabilities are 70% (i.e. 1.7 times) more likely to face poverty compared to the rest of the households, on average. However, the gap is the highest in Ireland, where households with disabilities are 2.7 times more likely to face poverty than persons without disabilities. It is important to note that the high levels of poverty that persons with disabilities face in Ireland are not driven by the overall high poverty rates in the country. On the contrary, the poverty rate for persons without disabilities in Ireland is one of the lowest in OECD European countries.

Even prior to COVID-19, structural megatrends related to digitalisation, automation, globalisation and ageing have been transforming labour markets across the OECD countries, reshaping the number and types of jobs as well as the skills in demand. The COVID-19 pandemic seems to accelerate these trends. This acceleration will make the transitional period even more difficult for some people and places.

While these transitions are almost universal, they are not uniform across places. Some of these changes, such as population ageing, will affect almost all communities, although they will be more pronounced in some places than others. These transitions will continue to create and destroy jobs, but not necessarily in the same places or require the same skills. National aggregates can overlook these difficult transitions for communities and the people who live there, as the people who lose jobs may not be in the right location or have the right skills for the new jobs created.

Automation has been reshaping the jobs and skill needs across the OECD countries for the past decades. Technological changes, such as industrial robots, artificial intelligence, and ongoing digitalisation, are causing a significant overhaul of labour markets and jobs’ geography. The introduction of technologies is replacing certain jobs entirely, changing the task content of many others and creating new jobs, thereby shifting the labour market’s occupational composition and the type of demanded skills.

Almost half of the jobs across the OECD are expected to change as a result of automation. About 46% of jobs across the OECD are either at risk of being destroyed (high risk) or face significant change and require new skills for workers to remain in that job (Nedelkoska and Quintini, 2018[23]). Manufacturing and agriculture have the highest share of jobs at risk on average. Comparatively, only a few service sectors – e.g. postal and courier services, land transport and food services – face relatively high risks. In contrast, the lowest relative risks sectors are predominantly service sectors, including many knowledge-intensive services.

Automation might exacerbate existing socio-economic inequalities by disproportionally affecting lower and middle-educated workers (Acemoglu and Autor, 2011[24]). Generally, the risk of automation decreases as the skill level of jobs increases. The occupations at the highest risk tend to be those that do not require specific skills or training – food preparation assistants, assemblers, labourers, cleaners and helpers – followed by occupations that require at least some training and include interacting with machines (machine operators, drivers and mobile plant operators, skilled agricultural workers etc.) (Nedelkoska and Quintini, 2018[23]).

Automation causes structural change affecting the types of skills that are needed in the labour market. In the past decade, some countries have seen their economies transform more rapidly than others, implying a greater need to re-train workers. It is possible to capture the changes in the labour demand through the Lilien index, which measures the extent to which employment in different sectors of the economy grows or shrinks at different speeds. The higher the Lilien index score, the more profound the economic structure transformation between 2005 and 2015. Figure 2.19 shows that Ireland is one of the countries that have experienced the biggest changes over the past decade, highlighting the relevance of the skill changes in the labour market driven by technological change.

The COVID-19 crisis is likely to accelerate digitalisation and automation, putting additional pressures on places with relatively high shares of jobs at risk. Due to social distancing and lockdown measures, firms and employees have embraced remote working and the digital tool. With the increasing use of digital services and new technologies, skill requirements for jobs also undergo significant change. Furthermore, a large body of evidence suggests that firms are more likely to invest in automation following economic downturns (Muro, Maxim and Whiton, 2020[26]).

A smaller proportion of the Irish labour market is vulnerable to automation than the rest of the OECD. In Ireland, 42% of jobs are highly automatable (i.e. probability of automation of over 70%) or have a significant risk of being strongly affected by automation, compared to 46% across the OECD Figure 2.20. More precisely, 26% of the overall labour force faces a significant risk of automation and thus the risk of suppression which is well below the overall OECD average of 32. Furthermore, 14% of jobs face a high risk of automation right at the OECD average.

The current risk of job automation presents an uneven picture across Irish regions. Differences in regions’ industrial structures determine the occupational composition that drives the differences in automation risk across regions. For example, sectors such as agriculture, construction, food and beverage services, manufacturing, or transport have a higher probability of losing jobs to automation. In the Northern and Western region and Southern region, more than 43% of jobs are likely to be automated or significantly transformed, which will change their skills requirements. In comparison, the Eastern and Midland region is relatively well shielded to the pending effects of automation and where 39% of jobs face the risk of automation. Employees in Eastern and Midland regions face lower automation risks because many work in industries that involve fewer routine tasks such as ICT, entertainment, financial and business services.

While automation will affect fewer jobs in Ireland than in most OECD countries, some groups will be affected more than others. Automation is likely to generate inequalities between population groups within Ireland, as different groups tend to occupy jobs at higher or lower risk of automation. Almost half of men (47%) face at least a significant risk of automation, making them the most vulnerable groups in terms of job losses (Figure 2.21) while it is the case of 46% of women. Women may be at less risk as this group tends to occupy less routine service jobs, in which fewer tasks may be replaced by technology.

Persons with disabilities face a significantly higher risk of automation. Across all demographic groups, persons with disabilities are affected more than their demographic counterparts. For instance, in the group aged between 25 and 50, while 52% of persons with disabilities face a risk of automation, compared to 44% for persons without disabilities. The difference is prevalent for both men and women.

Even before the onset of the COVID-19 pandemic, OECD economies experienced dramatic shifts in their labour markets. Labour markets across the OECD have become increasingly polarised over the last decades. The decline in manufacturing employment has played an important role in job polarisation as countries and regions deindustrialised or shifted to less labour-intensive production, but polarisation pervades all sectors. Computers have replaced secretaries in offices, while advanced machinery and robots have replaced middle-skill factory workers (Willis, 2013[27]). As a consequence, the share of employment in middle-skill jobs such as clerical and production jobs has declined. In contrast, high-skilled jobs such as managers, professional and technicians, or low-skilled jobs such as elementary occupations, service workers or market sales workers have increased (OECD, 2017[28]).

Job polarisation is increasing inequalities within OECD countries. At least in European OECD countries, polarisation is predominantly linked to changing labour market opportunities for new labour market entrants, including declining opportunities for those without a tertiary degree than previous cohorts. Furthermore, in the past century, middle-skill jobs were considered sufficient to achieve a middle-class lifestyle and offered socio-economic mobility for future generations. As the share of middle-skill occupations declined, most of the affected workers were pushed towards low-skill jobs (Utar, 2018[29]). Consequently, middle-skill workers are now more likely to be in lower-income classes than middle-income classes (OECD, 2019[30]).

Past waves of technological change have contributed to job polarisation across almost all OECD regions, particularly in urban areas. A polarised labour market may make local economies less resilient to shocks such as COVID-19 and is linked with declining labour market opportunities for non-tertiary educated workers.

Following general OECD patterns, in Ireland, all regions saw the share of middle-skill jobs decrease between 2000 and 2018 (Figure 2.22). The share of middle-skill jobs decreased by more than 8 percentage points in Southern and Eastern, representing a net decrease of almost 30 000 middle-skill jobs. In Southern and Eastern, decreasing shares of middle-skill jobs were predominantly offset by increasing shares of high-skill jobs, while in Border, Midland and Western, the share low-skill jobs grew relatively more.

COVID-19 has brought about a large increase in remote working as a result of strict containment measures such as social distancing and stay-at-home policies. Many firms have responded by making the necessary technological, cultural and organisational shift to allow their workers to operate from home. Early evidence suggests that workers that can work remotely are significantly less likely to have their labour market outcomes affected, while workers working in proximity to co-workers are more affected (Beland, Brodeur and Wright, 2020[9]).

Not all workers are in occupations amenable to working remotely. There are significant differences in remote working potential between occupations due to their daily task content differences. For example, occupations requiring workers to be outdoors (e.g. food delivery person) or to use heavy equipment (e.g. a vehicle) are considered to have a low potential of remote working. In contrast, occupations requiring only a laptop and an internet connection (e.g. an accountant, finance specialist, etc.) will have a high potential to work remotely. There is a strong positive correlation between skill level of the occupation and the remote working potential. Occupations with the highest potential are managers, lawyers and IT workers, while farmers, construction workers and artisans have the lowest teleworking potential. On average, young people, the low-skilled and low-wage workers are more likely to hold jobs requiring a physical presence.

The share of jobs amenable to remote working varies greatly both between and within OECD countries. The share depends on the local economy’s structure and the types of jobs that are locally available (see Box 2.7 for a detailed explanation). Large cities and capitals were generally more ready to seize the opportunities of digitalisation and embrace remote working. On the other hand, many rural areas still suffer a gap of access to high-speed broadband, of lower share of jobs amenable to remote working, and lower workforce education.

Ireland has higher remote work possibilities than the OECD average. In Ireland, 37% of jobs can be done remotely, above the OECD average of 34% (Özgüzel, Veneri and Ahrend, 2020[36]). However, there are significant differences across regions. The share of jobs amenable to remote working varies roughly 10 percentage points across regions, from 31% in Northern and Western to almost 41% in Eastern and Midland (Figure 2.23). Potential remote working is also higher in more densely populated areas. On average, 43% of workers in cities can work from home, while this share is only 33% in rural areas. While similar city-rural gaps are not unique to Ireland, the gap is one of the highest among the European countries.

Remote working potential and education levels are positively correlated. Workers with higher education levels are more likely to work in knowledge-intensive occupations and do not require physical presence, which allows them to work remotely. Figure 2.24 illustrates the relationship between the share of workers within each group and the share of workers who can work remotely, separately for persons with disabilities and without. For both groups, the share of workers who can work remotely increases with education. For example, while 7% of low-skilled workers with disabilities can work remotely, this share increases to 34% for high-skilled workers.

Remote working will be part of the future of work, although predicting its share in the future remains speculative. Remote working has many advantages for workers and firms, which indicates that there are reasons to believe that it will be part of the future. Before the pandemic, remote working was the most requested but refused accommodation for persons with disabilities (Foster and Hirst, 2020[38]). As businesses integrate remote working into their work culture, it will make remote working part of the work culture providing more remote working opportunity for workers with disabilities. Moreover, working from home reduce obstacles associated with commuting, especially those concerning public transportation. Finally, it could provide the flexibility to adjust their work hours depending on their needs.

Remote working should be used to increase inclusiveness and should not be exploited to avoid taking necessary steps. Remote working should be used to ensure the best possible working conditions for each individual. It can be a tool to customise work, allowing employers to better focus on the strengths and abilities of people with disabilities rather than on their support needs. However, it should not be adopted as a strategy to cut costs or as an excuse to avoid implementing workplace adjustments, leading to a reduction in long-term physical and environmental planning for persons with disabilities. For remote work to be really inclusive and non-discriminatory, the default position should be for it to be available and voluntary to the extent possible. Where job tasks allow, people should be free to decide whether and how much they want to telework, as some may want to do less instead of more. Working remotely or from the office should be an option, a facilitator and not a condition for access to work or retention. If people with disabilities are forced to work from home, rather than being offered the choice, it will entail the risk of isolation, loneliness and social exclusion.

The possibility to remote work will not benefit everyone equally, especially those who are low-skilled. Workers with low formal education have less chance to work remotely due to the task content of their jobs. Given the large share of low skilled among persons with disabilities, many would not be able to seize the opportunity, at least in the short term. While training programs should be offered to upskill and prepare workers with disabilities to maximise the opportunities presented with remote work, other policies should be developed in parallel to provide support to those who cannot remote work.

References

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Notes

← 1. COVID-19 Pandemic Unemployment Payment (PUP) is an income support scheme introduced by the Irish Government. This emergency payment corresponded to short-term support with the expected duration of 12 weeks after which people may return to work or may be considered for Jobseekers Benefit or Jobseekers Assistance. The the PUP became a longer term payment – started in April 2020 and only closed to new entrants in July 2021. Payment for those currently on the payment will reduce from September but some payments will continue until at least February 2022. https://www.citizensinformation.ie/en/social_welfare/social_welfare_payments/unemployed_people/COVID-19_pandemic_unemployment_payment.html

← 2. Employment Wage Subsidy Scheme (EWSS) is a subsidy received by firms impacted by COVID-19, to allow them to continue to pay their employees during the COVID-19 crisis. It aimed to keep employees registered with their employers so that they could get back to work quickly after the pandemic. It was preceded by COVID-19 Temporary Wage Subsidy Scheme which ended on 31 August 2020, and Revenue Employer COVID-19 Refund Scheme which lasted until 24 March 2020.

← 3. Persons with disabilities have higher employment rate in tight labour markets (Ross and Bateman, 2018[39]). Using the relative employment gap within the locality ensures that the spatial differences are not driven by labour market tightness.

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