2. The effects of automation in the Basque Country, Spain

Automation and digitalisation are likely to accelerate as the Comunidad Autónoma del País Vasco in Spain (onwards: Basque Country) recovers from the COVID-19 crisis. These trends will impact some sectors, places and groups more than others, raising the prospect of greater labour market inequalities (OECD, 2020[1]). To analyse these trends, this chapter is structured in three sections: section 1.1 provides an overview of the initial effects of the COVID-19 lockdown measures on the labour market in the Basque Country; section 1.2 presents OECD estimates of automation on jobs in the region; while section 1.3 looks at recent trends in job quality.

In 2020, the COVID-19 pandemic prompted governments to put in place lockdown measures to slow the spread of the virus, saving lives and reducing strain on health systems. The measures halted economic activity across the globe, precipitating a recession across OECD countries. In 2020, the European Union’s (EU) and Spain’s real GDP are set to contract by over 8.3% and 10.9% respectively due to the COVID-19 crisis (European Commission, 2020[2]). This unprecedented situation comes at a time when the Basque Country was still recovering from the 2008 and 2010 economic shocks.

Lessons from the past can help inform how the COVID-19 labour shock could impact the Basque region over both the short- and long-term. In 2007, unemployment in the Basque Country reached 7.4%, compared to 8.2% in Spain and 5.8% in the OECD (Figure 2.1). The two waves of the 2008 economic crisis, however, pushed unemployment to a high of 16.7% and 26.3% in the Basque Country and Spain respectively in 2013. During this time, the OECD average was already recovering, reaching 7.9% in 2013. In 2019, the Basque unemployment rate was 2.6% higher than its 2008 level, sitting at 9.3%, showing the local labour market had not yet fully recovered. In 2019, this rate situated the region below the Spanish average of over 14.1%, but above the OECD average of 5.4%.

Between January and June 2020, unemployment rose from 11.0% to 13.5% in the Basque Country, showing the initial effects of lockdown measures and other disruptions (Figure 2.1). Although the lengthy employment shock that followed the 2008 crisis may indicate a prolonged recovery after the pandemic, other factors will also determine the duration and severity of the labour market crisis. For example, the “double-dip” nature of the 2008 crisis in Spain, with its second wave of consequences in 2010, suggests the effects of the COVID-19 crisis may be shorter or longer depending on a second shock. Increases in unemployment may also be set to continue through 2020 and 2021, particularly depending on how redundancy restrictions and other measures are loosened.

The Spanish government put in place a host of measure to help contain the economic consequences of the lockdown measures. In particular, the government implemented a EUR 138.2 billion fiscal package, including EUR 4.3 billion for health measures and EUR 19.2 billion to support employment, notably though Expedientes de regulación temporal de empleo (ERTEs), or Short Time Work (STW) schemes that allow workers to obtain unemployment benefits (OECD, 2020[3]). At the regional level, the Basque government has put in place a COVID-19 programme entailing EUR 841 million, including EUR 500 million to support self-employed workers and SMEs (Gobierno Vasco, 2020[4]). Outside of this main package, the Basque government is also supporting the teleworking capacity of Basque SMEs during the pandemic. The region put in place a EUR 2 360 000 fund to co-finance the acquisition of teleworking equipment for Basque companies and the EUR 390 000 INPLANTALARIAK programme to consult SMEs and self-employed workers on teleworking measures (Gobierno Vasco, 2020[4]).

Facing a shutdown of all non-essential economic activity in March 2020, Basque enterprises adopted large-scale teleworking measures when possible to continue economic activity. Not all activities, however, can be performed remotely due to the nature of tasks performed, creating inequalities between occupations and sectors. The Basque Country appears as the Spanish region with the third-largest share of jobs that can be performed remotely. In the region, an estimated 32% of total jobs can be carried out remotely, compared to 31% average in Spain. The share of jobs that can be carried out remotely is only larger in Catalonia and the Madrid region, where 33% and 41% of jobs respectively can be done remotely (Figure 2.2).

The relatively high share of jobs amenable to remote work in the Basque Country may be explained by different factors. In particular, the Basque Country’s high level of educational attainment may support its teleworking capacity, as a strong statistical correlation has been found between educational attainmant and teleworking capacity (Özgüzel, Veneri and Ahrend, 2020[5]). The Basque Country’s teleworking capacity is also supported by its high urban density, as cities typically benefit from more developed internet infrastructure, enabling the region to leverage teleworking capacity (Özgüzel, Veneri and Ahrend, 2020[5]).

In a cross-national comparison, however, the share of jobs amenable to teleworking in the Basque Country is below averages in neighbouring countries. Across the OECD, an average of 34% of jobs can be carried out remotely, 2% above the proportion in the Basque Country. In France, Germany and Portugal the share of jobs that can be carried out remotely reaches national averages of 39%, 36% and 34% respectively, compared to 31% in Spain (Özgüzel, Veneri and Ahrend, 2020[5]).

Large-scale remote work has also revealed differences between sectors and occupations. Across the EU-27,the European Commission’s Joint Research Centre (JRC) estimated 40% of IT and communication service workers already worked remotely regularly or with some frequency before COVID-19, while this rate was low in sectors such as manufacturing (JRC, 2020[6]). This divide between higher and lower skill occupations can help guide policy decisions about employment protection and support for teleworking among occupations most vulnerable to lockdown measures.

Driven by the collapse of a real estate bubble and a global decline in trade, after 2008 job loss in the Basque labour market were concentrated in construction and industrial manufacturing. Jobs in construction fell from representing nearly 10% of the Basque Country’s labour market in 2008 to under 5% in 2017, now lower than both the Spanish and OECD averages (Figure 2.3). The collapse of this sector has had a lasting influence on the composition of unemployed workers, as in 2016, 19.3% of the very long-term unemployed and 9.2% of the long-term unemployed in Spain still came from the construction sector (Bentolila, Jansen and García-Pérez, 2017[7]). The Basque Country also lost nearly 2.5 percentage points of its industrial manufacturing jobs over this period, compared to 3.2 percentage points in Spain. In the region, these losses represented 50 300 construction jobs and 51 300 in industrial manufacturing. Meanwhile, employment in public administration, defence, education, human health and social work activities grew, representing 27 200 jobs, or a growth of 1.4 percentage points.

As employment decreases sharply in manufacturing and non-tradeable sectors over the 2008-2017 period, productivity stayed positive. Between 2008 and 2011, labour productivity in manufacturing increased by 3.4 percentage points while it increased by 3 percentage points in non-tradeable services, including the region’s construction sector (Figure 2.3). These increases, however, were likely driven by large job suppression in these sectors, entailing a passive form of productivity growth (Orkestra, 2019[8]). In the manufacturing sector, employment loss and productivity rises showed signs of continuing through the 2008-2017 period, with a 0.8 percentage point loss of employment and an increase of 2.7 percentage points in productivity, indicating the sector was still experiencing the effects of the 2008 and 2011 downturns. In tradeable services, meanwhile, job loss also accompanied productivity decline between 2008 and 2011, as productivity fell by 1.2 percentage points and the sector lost 2 800 jobs. Between 2008 and 2017, a partial recovery in non-tradeable service employment accompanied by productivity growth of 1.4 percentage points may indicate a non-passive form of productivity growth driven by technology absorption, training or skill acquisition (OECD, 2018[9]).

Initial evidence from the COVID-19 crisis shows that lockdown measures will effect employment disproportionately in the industrial manufacturing, tourism and retail sectors. The Spanish government lifted its initial lockdown measures from 10 May 2020 onwards, though has not lifted large-scale Spanish Short Term Work (STW) schemes. Indeed, Expedientes de Regulación Temporal de Empleo (ERTE), Spanish STW schemes, can serve as a gauge of the most distressed sectors.

Employment in food services and accommodation shows one of the highest signs of distress as lockdown measures prevented restaurants, bars and hotels from operating during March-May 2020. This sector, heavily driven by tourism in Spain, accounted for about one-fifth of STW requested in the Basque Country to Spain’s government as of 10 June 2020, for a sector that represents around 6.2% of the region’s jobs (Figure 2.5). This sector is likely to face a prolonged recovery as an uncertain recovery unfolds, especially in the prospect of new lockdown measures. Indeed, OECD analysis on the initial effects of lockdown measures show large differences in unemployment risk across regions may be partially accounted for by the size of the tourism sector (OECD, 2020[1]).

As in the previous crisis, the Basque Country’s large industrial manufacturing sector was also severely impacted. As of 10 June 2020, around one-third of STW requested in the Basque Country came from industrial manufacturing, for a sector representing 20.4% of total employment. As STW and other policy measures are lifted, employment in sectors such as retail and wholesale trade will also be at particular risk of destruction, as trade demand is set for a slow recovery in the face of uncertainty and possible new lockdown measures. According to OECD estimates, up to 10% of employment in the Basque Country involves retail and wholesale trade (Figure 2.6). Other key sectors at risk include art and entertainment, which the OECD estimates accounts for nearly 7% of employment in the region. Construction, on the forefront of the 2008 crisis, meanwhile, accounts for only 3.6% of STW requested as of 10 June 2020, for a sector that represents 6.1% of employment.

These sectors have been particularly vulnerable to COVID-19 as they have not have been able to turn to large-scale teleworking. Some have also been the most directly impacted by the shutdowns, as consumers have been unable to access services. As the government progressively lifts STW schemes, these sectors will require particular attention in terms of long-term support and reskilling opportunities for workers, particularly if demand does not return to pre-COVID levels.

Automation has the potential to raise competitiveness and improve working conditions, though it can also supress jobs. The OECD considers a job at significant risk of change if 50% to 70% of the tasks within the job are vulnerable to automation, while those at high risk have more than 70% of tasks that could be replaced by a machine (Nedelkoska and Quintini, 2018[10]). When considering both jobs at high and significant risk, a smaller proportion of the overall labour market is vulnerable to automation in the Basque Country than all other Spanish regions, outside of Madrid, Ceuta and Melilla (Figure 2.7). Indeed, in Spain, 55% of jobs are at overall risk of automation compared to 54% in the Basque Country.

The Basque Country, however, has a significantly higher portion of jobs at high risk of automation compared to the OECD average. In the Basque Country, 22.2% are at high risk of automation compared to 14% across OECD countries, putting over 205 000 jobs in the region at high risk of suppression (Figure 2.7). Concerning high risk jobs, only Slovakia, Slovenia and Greece have a larger share of jobs at high risk of automation than Spain. The importance of industrial manufacturing as an employer in the Basque Country could be driving the region’s vulnerability to job automation. The sector tends to include a large share of jobs involving routine and non-cognitive tasks, at higher risk of replacement by technology. Moreover, evidence from past recessions indicate the region’s vulnerability to automation may increase with the COVID-19 crisis, as firms turn to automation to restructure production and cut costs (Box 2.1).

The region, meanwhile, has a nearly equal share of jobs at risk of significant change due to automation as the OECD average, with 293 000 jobs at risk, or 31.8% of total jobs, compared to 31.6% across the OECD. For those at high risk, this entails a risk of job suppression, while those at significant risk face change in the way these jobs are performed as many tasks becomes automated, calling for new skills to remain in the job (Nedelkoska and Quintini, 2018[10]) (see Box 2.2 for more information on the OECD methodology).

Indeed, the digitalisation of the workplace involves changes to the workplace beyond suppression that require the attention of policymakers. In Spain as in the Basque Country, evidence suggests these changes may be accelerating. Data on imports of multipurpose industrial robots indicates shipments increased by 12% between 2017 and 2018 in Spain, higher than all western European countries except Italy (International Federation of Robotics, 2018[11]). New technologies can harm the working conditions of manufacturing workers when algorithms send real-time information on their performance to centralised systems, damaging their autonomy and privacy, but may improve job quality when they reduce workplace accidents and decrease isolating and tedious tasks (Eurofound, 2018[12]). New workplace regulations will be required to ensure the working conditions of employees are upheld, while ensuring appropriate training measures are in place to ensure workers adapt and seize the productive advantages brought by technology.

Automation is also likely to generate inequalities between population groups within the Basque Country, as different groups tend to occupy jobs at higher or lower risk of automation. In the region, 51% of men and 57% of immigrants occupy jobs at risk of automation, making them particularly vulnerable (Figure 2.8). Men and immigrants tend to be overrepresented in the construction and the manufacturing sectors, where AI and other technologies may restructure production processes. 48% of women, meanwhile, occupy jobs at some risk of automation. Women may be at less risk as this groups tends to occupy less routine service jobs, in which less tasks that may be replaced by technology.

Multiple factors influence and structure job supression and change, determining the actual displacement of automatable jobs. Indeed, the effects of automation are determined by the rate at which technology is introduced, the way workers adapt as well as multiple differences in work organisation across countries and regions (Orkestra, 2019[15]). The social acceptability or the economic profitability of automation, also help weigh into the actual supression of a task or job at risk of automation (Le Ru, 2016[16]). Demand-side policies also play a role in the way automation unfolds. In the Basque Country, industrial and innovation strategies such as Basque Industry 4.0 and the region’s Smart Specialisation Strategy (RIS3) are encouraging this process of automation within firms, calling for attention on its effects on the workplace.

The three occupations at high risk of automation with the greatest number of workers are all closely associated with the Basque industrial manufacturing sector (Table 2.2). These include:

  • Stationary plant and machine operators constitute the largest pool of workers at high risk of automation, representing over 23 000 workers in the region;

  • Metal, machinery and related trades workers represent the second-largest occupation group at high risk from automation in terms of number of workers, with 19 700 jobs at high risk.

  • Drivers and mobile plant operators represent the third-largest group, constituting 17 500 jobs at high risk of automation.

Automation of key industrial occupations may accelerate the relative and absolute decrease in industrial employment already underway in the region. This should be of particular concern in the Basque Country, as the region’s industrial base has been at the heart of its growth model since the 1980s, when the region leaned on industrial policies to redevelop its manufacturing sector (Box 2.3). Since 2000, industry, including the energy sector, has decreased from nearly 28% of total employment to 20% in 2017, compared to a smaller decrease in Spain, from 18% in 2000 to 12.3% in 2017 (Figure 2.9). During the 2008 economic crisis and its aftermath, between 2008 and 2015, the Basque Country lost 64 000 jobs in the sector, representing nearly 25% of sectoral employment.

The Basque Government has put industrial development at the heart of its new industrial strategy, seeing the sector a means to reduce unemployment, consolidate recovery, and raise social cohesion (Gobierno Vasco, 2017[19]). To do so, the region has put in place an Industry 4.0 policy, a process in which “the physical world of industrial production merges with the digital world of information technology – in other words, the creation of a digitized and interconnected industrial production, also known as cyber-physical systems” (UNIDO, 2017[20]). This involves supporting struggling firms and reinforcing financing instruments, particularly related to digitalisation, for example by promoting new industrial-technological projects and supporting digitalisation. The region, however, recognises the loss of lower-skilled industrial jobs as a major risk of the fourth industrial revolution in the Basque Country’s Employment Strategy 2020 (Gobierno Vasco, 2016[21]). In order for Industry 4.0 to reinforce its potential as a tool for job growth and social cohesion, regional innovation policies can work in tandem with employment policies to help workers prepare for a 4.0 setting. For instance, in the province of Ontario, Canada, the regional government has put in place a Second Career Program to help fund adult education of industrial workers who have lost their jobs (Box 2.4).

Although less concentrated by sector, multiple service-related occupations in the Basque Country face automation risks. Cleaners and helpers constitute the largest category of people at high risk of seeing their occupation disappear or change significantly, with 15 100 people at high risk and 26 900 at significant risk, representing 32% and 56% of helper and cleaner jobs in the region respectively (Table 2.3). These positions are associated with low skilled jobs in both the service and good-producing sectors, that can involve routine tasks such as watching, cleaning or washing. Such tasks may be particularly vulnerable to automation as risks related to COVID-19 continue. Given the need for increasing sanitary measures due to the COVID-19 crisis, there could be an acceleration of the use of machines in this occupational category to mitigate health risks.

Occupations requiring middle-level skills are also at risk. Such occupations include personal care or personal service workers, representing 14 000 and 11 500 jobs at high risk of automation in the region, and 11 400 and 17 000 at significant risk of change, respectively. These occupations often require care for individuals, such as personal assistance, travel or housekeeping, requiring both human contact and middle-level skills. Although societal, legal and cultural factors are likely to influence the automation of such human-facing tasks, particularly those involving personal care, elements of these occupations are likely to change, requiring the mastery of new tools and skills to perform the job. Sales workers, customer service clerks and food preparation assistants also constitute large groups of workers facing high risks of automation in the region, with 11 700, 7 500 and 4 100 jobs at high risk and 24 300, 22 200 and 1 200 at significant risk. Jobs such as clerks are also particularly at risk as secretarial tasks, word processing and other routine data manipulation often constitute a large part of their duties, tasks that are highly susceptible to digitalisation. Although these jobs cover a wide range of service sectors, they are particularly concentrated in sectors showing early and persistent signs of distress due to COVID-19, such as retail trade, accommodation and food services.

Three main trends can be identified concerning job creation and automation in the Basque Country between 2008 and 2018.

  • (1) First, the Basque Country has been creating jobs in a number of middle skill occupations which are at risk of automation, particularly occupations related to industrial manufacturing.

Job creation in the Basque Country’s industrial base is a welcome sign of recovery from the 2008 crisis, and may indicate the region’s recent industrial policies have helped restore industrial employment and slow long term trends concerning this sector. However, increases in jobs in these occupations may constitute a risk for these workers as they are among the highest risk occupations, all the more as the region’s industrial policies support the sector’s digitalisation. For instance, the region created over 12 280 stationary plant and machine operator positions and over 19 000 metal, machinery and related trades workers since 2008 (Figure 2.10).

The region has also created low skill service jobs, including over 13 000 customer service clerks, which are also at high risk of automation. The creation of low skill service jobs has been a pattern seen across Spanish regions, characteristic of Spain’s recovery from the 2008 crisis. These occupations are also at particularly risk due to the COVID-19, as sectors such as tourism, accommodation and food services may shed jobs as these sectors undergo a prolonged recovery.

  • (2) Second, the region lost employment in certain low and middle-skill occupations at high risk of automation, such as low-skill services.

The region lost 20 298 cleaners and helper positions and 23 845 building and related trades workers (excluding Electricians). These jobs also include occupations linked to industrial manufacturing at high risk of automation, such as drivers and mobile plant operators, an occupation which lost over 7 500 jobs. These changes can reflect structural, technological and policy changes in the Basque Country and Spain since the 2008 and 2010 crises, such as the sharp downturn in the construction sector. As many of the region’s unemployed workers may hold the skills from these occupations, this evidence could serve as a basis to tailor adult learning policies and can constitute an opportunity to upskill these parts of the Basque workforce.

  • (3) Third, the Basque Country has tended to lose high-skilled jobs at lower risk of automation, with the exception of jobs in education and health.

Principally, this concerns occupations such as business and administration associate professionals, business and administration professionals and legal, social and cultural professional lost employment. The region’s RIS3 specialisation strategy, with a volley of policies dedicated to energy and bio-health, may help reverse some of these trends, as growth in these areas may foster increases in high skill occupations at lower risk of automation.

Examples from regions across the OECD could help deepen strategic planning around skills development and demand-side policies to diversify the region’s economic base in ways that are complementary to its industrial core. For example, officials in the city of Southampton, United Kingdom, drafted an action plan on the future of work which involved mapping applicable international practices and meeting with city business leaders (Box 2.5). In the same way, in Washington-state United States, a task force made up of elected officials, labour and firms formulated policy recommendations related to the future of work. These involved a wide range of consultations among different stakeholders, ranging from online surveys and meetings to events and in-person consultations with different local actors.

The Basque public employment service (PES), Lanbide, launched Futurelan, an innovative tool to track the evolution of occupations in the face of the future of work. Futurelan uses past labour market trends to make predictions about the future. This tool provides real and predicted data on evolution, the distribution of employment occupation and the evolution of contracts. Information can be selected according to occupation or sector. Although the COVID-19 crisis is likely to modify conjectures, Futurelan predictions set prior to the crisis foresee nearly 57 000 new jobs in food service, health and safety/security sectors, as well as over 41 000 jobs as accountants, administrative staff and other office employment (Figure 2.11). Meanwhile, the tool predicts a decrease of nearly 19 000 in machine and facility operators and assemblers. Other occupations, such as qualified workers in agriculture, livestock, forestry and fishing and technical and professional staff are also predicted to decrease over time, shedding nearly 7 000 and 5 500 jobs respectively between 2018 and 2030. Futurelan predictions correspond with OECD calculations which suggests a high likelihood of job suppression in machine and facility operators and assemblers.

The tool’s prediction model, however, may need to adapt to integrate predictions related to COVID-19. Indeed, Futurelan’s prediction of job growth in food services and sales occupations may change significantly as early estimates on the impact of COVID-19 show a significant, and likely prolonged, downturn in the sector. The region could also take this tool further to provide more data on skills trends, beyond sectors and occupations. In this way, tools such as Futurelan could help the region develop policies on how those holding those jobs can retrain for other jobs, putting in place appropriate training to assist job transition. For instance, in Wallonia, Belgium, the region has put in place a sectoral skill analysis that involves carrying out field and expert interviews to identify skills that could arise from emerging sectors (Box 2.6). Reinforcing Futurelan’s quantitative predictions with a wider qualitative approach would complement the tool’s predictions, receiving direct information from companies and key actors on how they see their sector evolving.

Technology-influenced changes in the workplace are likely to create more part-time, temporary or self-employed jobs as the possibility of new, remote or modified working arrangements becomes possible. Some of these changes may be accelerated by the COVID-19 crisis as remote work arrangements persist or become mainstreamed in the workplace. Such developments could support workers who require more flexible arrangements but they could also lead to increased employment insecurity (Orkestra, 2019[8]). In the same way, technology can improve job quality for some workers, by increasing earnings, improving safety, or reducing tedious tasks. New technologies in the workplace, however, can also reduce the well-being of workers by increasing monitoring, reducing autonomy and accentuating job strain (OECD, 2019[23]). Low job quality can harm labour productivity by lowering worker motivation and by discouraging firms from investing in the skill development of employees (Askenazy and Erhel, 2017[24]).

Recognising jobs as a central part of peoples’ well-being, the OECD has sought to place the quality of employment, and not only its quantity, at the centre of policy discussions on employment (OECD, 2014[25]). The OECD Job Quality Framework considers job quality can be broadly divided into earning quality, labour market security and the quality of the working environment, such as tasks performed (OECD, 2014[25]). According to these gauges, Spain records amongst the lowest job quality indicators in the OECD, a pattern followed by the Basque Country along key indicators (OECD, 2019[23]). In terms of earnings quality, Spanish and Basque wages fell sharply during the crisis and did not recover fully, recovering only partially in real terms in 2019 for the first time since 2015 (European Commission, 2020[26]). At the national level, raises in the minimum wage in 2019 and higher negotiated wages through social dialogue helped recover wages (European Commission, 2020[26]).

Although the Basque Country benefits from a lower rate of temporary employment compared to most other Spanish regions, it remains much higher than EU and OECD averages. Indeed, in 2019, 92% of work contracts signed in the Basque Country were temporary, while in 2018, over 22% of employees were on temporary contracts in Spain, compared to just over 11% in the EU-28 (Lanbide website) (Figure 2.12). According to the European Commission, over 32% of those on temporary contracts in Spain have an agreement that lasts less than 6 months, while over 17% have a contract that last less than 1 month, highlighting the precariousness of working arrangements (European Commission, 2019[27]). Moreover, the number of very short contracts has increased in recent years in Spain. For example, 30% of all contracts signed in Spain in 2019 were less than one week long, compared to 17% in 2007 (European Commission, 2020[26]). The Commission also highlights that fixed-term contracts are not only pervasive in seasonal jobs, but also in education, health and manufacturing along with other higher-skilled occupations. Temporary contracts have also proliferated in the public sector, with over 27% of public sector employees on temporary contracts in Spain at the end of 2019, according to European Commission.

The high rate of temporary contracts in Spain causes difficulties attaining benefits and participating in training. Over 23% of workers on temporary contracts in Spain were at risk of poverty, while the share of workers suffering from in-work poverty in the overall economy increased from 10.8% in 2012 to 13.1% in 2017, higher than the EU-28 average of 9.4% (European Social Policy Network, 2019[28]). In Spain, young, low skilled and non-EU immigrant workers were disproportionately affected by temporary work and in-work poverty, compounding automation risks (European Commission, 2019[27]). The academic literature has put forth different possible causes of high rates of fixed-term work in Spain, ranging from labour market flexibility, or rigidity, to firm strategies and contract abuse. The Spanish Government has put in place the Plan director por un trabajo digno 2018-2020, a national strategy to curb to curb fixed-term work across the country (Box 2.7).In particular, the plan reinfroces the capacities of the Spanish labour inspectorate to identify abuses, while also opening avenues for cooperation between the national and regional labour inspectorates.

Part-time employment increased significantly in Spain and the Basque Country after the 2008 downturn, suggesting part-time employment may rise again following the COVID-19 crisis (OECD, 2019[23]). Although part-time employment remained under the OECD average throughout the crisis in Spain, it increased from under 11% of total jobs in 2008 to over 14% in 2013-4, a share that fell to approximatively 13% in 2018 (Figure 2.13). Notably, part-time employment trends have been stronger in the Basque Country than in Spain, with a difference that rose throughout the crisis. Although the rate is lower than the EU average, the majority of part-time workers in Spain are involuntarily working part-time: over 55% of part-time workers were working part-time while wishing to work longer in 2018, relative to 26% in the EU the same year (Figure 2.14). Although Spain already registered a higher involuntary part-time unemployment rate than the EU-28 average in 2008, the gap between the EU-28 average and Spain has increased significantly. Positively, the share of involuntary part-time employment as a share of part-time employment began to decrease in Spain in 2014, though this trend may be at risk due to COVID-19. As Basque firms are faced with reduced margins as the COVID-19 crisis reduces demand, particularly in sectors such as tourism, the past reaction of Basque firms may indicate a renewed proliferation of involuntary part-time contracts. In the face of such prospects, encouraging “high road” firm strategies can serve as a way to improve productivity through job quality, while encouraging firms to pool training investments, move into value added products and develop other skills utilisation strategies (Box 2.8).

The COVID-19 is likely to accelerate automation in the Basque Country. In 2020, the region will face steep economic challenges, requiring the region to transition short-term economic aid into targeted support for companies and workers most at risk, particularly for sectors reliant on tourism and trade. As the region recovers, a higher number of Basque jobs will face a high risk of automation, particularly those linked to the region’s historic industrial base and service jobs entailing risks related to COVID-19. These include not only occupations such as station, plant and machine operators, metal, machinery and related trades workers, but also sales workers or cleaners.

The Basque Country has already taken actions to mitigate these risks. Tools such as Futurelan can be expanded to lean on international skills mapping practices. The Basque Country can mobilise its historic cluster-based development to encourage better skills utilisation by Basque firms and acting early to train and upskill workers into quality jobs. These changes will call for effective support to displaced workers. In this way, Chapter 2 explores the way the region’s public employment service, Lanbide, plays a central role support these labour market transitions.


[24] Askenazy, P. and C. Erhel (2017), Qualité de l’emploi et productivité, Éditions Rue d’Ulm/Presses de l’École normale supérieur, http://www.cepremap.fr/depot/2017/06/Opuscule_CEPREMAP43-Emploi_Productivite.pdf.

[7] Bentolila, S., M. Jansen and J. García-Pérez (2017), Are the Spanish Long-Term Unemployed Unemployable?, http://ftp.iza.org/dp10580.pdf.

[12] Eurofound (2018), Automation, digitalisation and platforms: implications for work and employment, https://www.eurofound.europa.eu/publications/report/2018/automation-digitisation-and-platforms-implications-for-work-and-employment.

[26] European Commission (2020), Country Report Spain 2020, https://ec.europa.eu/info/sites/info/files/2020-european_semester_country-report-spain_en_0.pdf.

[2] European Commission (2020), European Economic Forecast, Summer 2020 (Interim), https://ec.europa.eu/info/sites/info/files/economy-finance/ip132_en.pdf.

[27] European Commission (2019), Country Report Spain 2019, https://ec.europa.eu/info/sites/info/files/file_import/2019-european-semester-country-report-spain_en.pdf.

[28] European Social Policy Network (2019), In-work poverty in Spain, Directorate General for Employment, social affairs and inclusion.

[17] Frey, C. and M. Osborne (2013), The future of employment: how susceptible are jobs to computerisation?, https://ora.ox.ac.uk/objects/uuid:4ed9f1bd-27e9-4e30-997e-5fc8405b0491/download_file?safe_filename=future-of-employment.pdf&file_format=application%2Fpdf&type_of_work=Journal%2Barticle.

[4] Gobierno Vasco (2020), EDIDAS programa COVID19, https://bideoak2.euskadi.eus/2020/03/24/news_61075/COVID19_Medidas_Neurriak.pdf.

[19] Gobierno Vasco (2017), Plan de Industrialización 2017-2020 “Basque Industry 4.0”, https://www.irekia.euskadi.eus/uploads/attachments/10018/Plan_de_Industrializacion.pdf?1500453186.

[21] Gobierno Vasco (2016), Estrategia vasca de empleo, https://www.euskadi.eus/contenidos/informacion/eve2020/es_def/adjuntos/EVE2020.pdf.

[22] Gobierno Vasco (2009), The Basque Country: Insight into its culture, history, society and institutions, http://www.euskadi.eus/gobierno-vasco/contenidos/informacion/ezagutu_eh/es_eza_eh/adjuntos/eza_en.pdf.

[13] Hershbein, B. and L. Kahn (2018), “Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings”, American Economic Review, Vol. 108/7, pp. 1737–1772, https://doi.org/10.1257/aer.20161570.

[11] International Federation of Robotics (2018), Executive Summary World Robotics 2018 Industrial Robots, https://ifr.org/downloads/press2018/Executive_Summary_WR_2018_Industrial_Robots.pdf.

[6] JRC (2020), Telework in the EU before and after the COVID-19: where we were, where we head to, European Commission, Joint Research Centre (JRC), https://ec.europa.eu/jrc/sites/jrcsh/files/jrc120945_policy_brief_-_covid_and_telework_final.pdf.

[16] Le Ru, N. (2016), L’effet de l’automatisation sur l’emploi : ce qu’on saitet ce qu’on ignore, https://www.strategie.gouv.fr/sites/strategie.gouv.fr/files/atoms/files/na-49-automatisation-emploi.pdf.

[14] Muro, M., R. Maxim and J. Whiton (2020), The robots are ready as the COVID-19 recession spreads, https://www.brookings.edu/blog/the-avenue/2020/03/24/the-robots-are-ready-as-the-covid-19-recession-spreads/?preview_id=791044.

[10] Nedelkoska, L. and G. Quintini (2018), “Automation, skills use and training”, OECD Social, Employment and Migration Working Papers, No. 202, OECD Publishing, Paris, https://dx.doi.org/10.1787/2e2f4eea-en.

[1] OECD (2020), Coronavirus (COVID-19)From pandemic to recovery: Local employment and economic development, https://read.oecd-ilibrary.org/view/?ref=130_130810-m60ml0s4wf&title=From-pandemic-to-recovery-Local-employment-and-economic-development.

[3] OECD (2020), Country Policy Tracker, Spain (updated 1 June 2020), http://www.oecd.org/coronavirus/fr/.

[23] OECD (2019), OECD Employment Outlook 2019, OECD Publishing, Paris, https://dx.doi.org/10.1787/9ee00155-en.

[18] OECD (2018), Job Creation and Local Economic Development 2018: Preparing for the Future of Work, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264305342-en.

[9] OECD (2018), Productivity and Jobs in a Globalised World: (How) Can All Regions Benefit?, OECD Publishing, Paris, https://doi.org/10.1787/9789264293137-e.

[25] OECD (2014), Employment Outlook, https://www.oecd-ilibrary.org/docserver/empl_outlook-2014-en.pdf?expires=1576750060&id=id&accname=ocid84004878&checksum=08CD510F15872539BCF15C239C6F668D.

[15] Orkestra (2019), El futuro del empleo en la CAPV.

[8] Orkestra (2019), The Basque Country Competitiveness Report 2019: Are skills the panacea?.

[5] Özgüzel, C., P. Veneri and R. Ahrend (2020), Potential for remote working across different places, VOX EU CEPR, https://voxeu.org/article/potential-remote-working-across-different-places.

[20] UNIDO (2017), Accelerating clean energy through Industry 4.0: Manufacturing the next revolution, https://www.unido.org/sites/default/files/2017-08/REPORT_Accelerating_clean_energy_through_Industry_4.0.Final_0.pdf.

Metadata, Legal and Rights

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. Extracts from publications may be subject to additional disclaimers, which are set out in the complete version of the publication, available at the link provided.

© OECD 2020

The use of this work, whether digital or print, is governed by the Terms and Conditions to be found at http://www.oecd.org/termsandconditions.