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This chapter shifts the focus to the regional level. The 2008 crisis stopped the relative regional convergence that Europe had been experiencing since the 1980s. In the Eurozone, a relatively straightforward institutional framework governs policy: a single currency is managed by the ECB with the sole mandate of controlling inflation. Fiscal policy is fragmented, with no unified budget or common debt and constrained by the Stability and Growth Pact. Industrial policies are non-existent, subordinated to market competition, while labour market flexibility is presented as the primary mechanism for absorbing shocks. The question is whether this governance is adequate to manage the transformations driven by technological change. This chapter presents two empirical analyses. The first examines the relationship between resilience to the 2008 crisis (measured by employment recovery) and the economic structure and structural changes observed in regions between 1998 and 2019. The second investigates the relationship between resilience to the ‘negative’ effects of robotisation (measured by reductions in employment and income levels) and the implementation of policies related to education and R&D.
The chapter introduces and argues (again using data) the Extended Crises Theory, through which the Great Recession can be read. The theory illustrated is based on possible bottlenecks in structural change and policies that could speed up transitions and direct them towards more positive dynamics. In this reading, the sectoral composition of economies and the distinction between high- or low-tech manufacturing sectors and high or low knowledge-intensive service sectors is crucial.
This chapter expands the analysis of Great Decoupling and Jobless Growth to twenty-four major OECD economies, shifting from a sectoral to an aggregate and country-level perspective. While this aggregate approach provides a valuable macro-level overview, it risks obscuring the nuanced realities of these phenomena. Although Jobless Growth and the Great Decoupling appear widespread across OECD countries at the aggregate level, they arise from diverse and complex dynamics that vary significantly across sectors and regions. These divergent trends are rooted in different labour market, sectoral composition, human and physical capital endowments, and the broader socio-economic networks within which firms operate. The apparent homogeneity of these trends at the aggregate level masks a complex interplay of resource allocation, path dependency, and policy choices. Consequently, while triggered by common technological advancements and globalisation, Jobless Growth and the Great Decoupling will manifest differently across countries, necessitating tailored policy interventions.
In this book, we have interpreted the long-term economic trends of recent decades through the lens of structural dynamics, based on what the available data may (or may not) reveal. Clark’s (1940) analysis of capitalist economies, which established the foundation for the structuralist approach, identifies three dominant sectors at different stages of development: agriculture first, followed by manufacturing, and finally services. This approach has also been articulated in terms of dualistic development from the beginning: Lewis’s (1954) model highlighted the challenges that can arise in transitioning from ‘traditional’ to ‘advanced’ sectors and underscores the positive and active role the state can play in facilitating these transitions. Rosenstein-Rodan (1943) explicitly discussed the need for ‘big pushes’ by public authorities to avoid vicious circles that can hinder structural change, specifically towards industrialisation.
This chapter is a sort of an introduction to the book. The Chapter introduces and briefly explains some crucial topics and concepts: Jobless Growth, the Great Decoupling, the decline of the Labour Share. The treatment always relies on economic data from different countries. These arguments are related to the growing income inequality and to the idea of a New Great Transformation (which updates Polanyi’s corresponding theory).
This chapter explores the issue of technological change from a historical perspective, drawing lessons from past experiences to shed light on the current context and the challenges associated with the Fourth Industrial Revolution. An empirical analysis is then presented to contribute to the debate on the future of employment, focusing on the ongoing process of robotisation. Using data from the OECD-STAN database and the International Federation of Robotics (IFR), we examine how the effects of robotisation on key economic variables vary across sectors and regions. The supposed divide between pessimistic and optimistic views of the future of work is not truly oppositional. Instead, these perspectives reflect the absence of predetermined trajectories. The key issue, therefore, is not whether to adopt an optimistic or pessimistic stance but whether we choose to passively ‘suffer’ the economic effects of innovation by leaving them to market forces or actively guiding these processes through appropriate policies.
Technological change and innovation have long fueled economic growth and employment. Yet, in recent decades, productivity gains have increasingly failed to translate into more jobs and higher wages. Jobless Growth and the New Great Transformation investigates this apparent paradox, by examining the theoretical and empirical evidence about the relationship between innovation and structural change. It combines rigorous and cutting-edge data analysis with EU case studies to reveal how recent technological breakthroughs, far from driving shared prosperity, have slowed growth, widened spatial divides and fueled societal polarization, partly due to excessive confidence in market deregulation. Drawing on data-driven analyses, the book explains why impacts of innovation vary so widely between regions and how history, institutions, and policy-not just market forces-determine who benefits from technological advances and who is left behind.
Marked increases in mental health services utilisation across university settings mean that students often spend long periods waiting for evaluation and treatment.
Aims
To assess whether digital unguided self-help delivered while waiting for face-to-face therapy could reduce anxiety and depression and improve functioning in university students.
Method
We retrospectively analysed routinely collected data from the student mental health service at the University of Padua, Italy. From June 2022, all students waiting for clinical evaluation and treatment received a self-help stress management booklet (The World Health Organization’s Doing What Matters in Time of Stress (DWM)). The clinical evaluation included depression (Patient Health Questionnaire-9), anxiety (Generalised Anxiety Disorder-7) and functional impairment (Work and Social Adjustment Scale). Single-group interrupted time series (ITS) analyses compared outcomes in users contacting the service between October 2021 and 23 June 2022 (pre-intervention) and, respectively, between 24 June 2022 and 18 November 2023 (post-intervention).
Results
Seven hundred and forty-nine Italian students (77% women, median age 23 years) were included; of these, 411 (55%) received the intervention and 338 (45%) did not. ITS indicated that the intervention introduction coincided with immediate and sharp decreases in depression (level change, β = −2.26, 95% CI −3.89, −0.64), anxiety (β = −1.50, 95% CI −3.89, −0.65) and impaired functioning (β = −2.66, 95% CI −4.64, −0.60), all largely maintained over time.
Conclusions
In the absence of a control group, no causal inferences about intervention effects could be drawn. DWM should be studied as a promising candidate for bridging waiting time for face-to-face treatment.
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