Category Archives: Policy Note

Working from home and income inequality in the time of COVID-19. GLO Policy Note No. 4. By GLO Fellows Luca Bonacini, Giovanni Gallo and Sergio Scicchitano.

GLO Policy Note No. 4
Theme 2: Inequalities and labor markets
Theme 3: Future of Work

Working from home and income inequality in the time of COVID-19

A case study of Italy

by Luca Bonacini, Giovanni Gallo, Sergio Scicchitano

  • Luca Bonacini (University of Modena and Reggio Emilia, GLO)
  • Giovanni Gallo (Sapienza University of Rome, University of Modena and Reggio Emilia, GLO)
  • Sergio Scicchitano (National Institute for Public Policies Analysis – INAPP, GLO)

In a recent GLO Discussion Paper and just published in the Journal of Population Economics (Bonacini et al., 2021), we explore the potential consequences in labour income distribution of long-lasting increase in Working From Home (WFH) among Italian employees. Results show that an increase in WFH would be associated with an increase in the average labour income, but this potential benefit would not be equally distributed among employees. Specifically, an increase in WFH would favour male, older, high-educated, and high-paid employees. This “forced innovation” thus risks to exacerbate pre-existing inequalities in the labour market. As a consequence, this study suggests a series of policies aimed at alleviating inequality in the short run and, more importantly, that should play a rebalancing role, in the long run.

What we should know

  • To limit the number of deaths and hospitalisations due to the novel coronavirus, most governments decided to suspend many economic activities and restrict people’s freedom of mobility.
  • In this context, the opportunity to work from home (hereinafter called WFH) became of great importance, since it allows: employees to continue working and thus receiving wages, employers to keep producing services and revenues, and overall limits infection spread risk and pandemic recessive impacts.
  • Recent estimates for the US show that between February and May 2020 over one third of the labour force switched to WFH, resulting in about half of workers working remotely during the pandemic. Remote workers have quadrupled to 50% of US workforce (Brynjolfsson et al., 2020). Due to uncertainty about the duration of the health emergency and future contagion waves, the role of WFH in the labour market is further emphasized by the fact that it might become a new standard (rather than an unconventional) way of working in many economic sectors, possibly resulting in structural effects on the labour market worldwide (Baert et al., 2020).
  • Because of the WFH sudden prominence and growth, several studies recently investigated this phenomenon, especially with the objective of identifying the number of jobs that can be done remotely (Adams-Prassl et al., 2020; Dingel and Neiman, 2020; Mongey at al., 2020). However, the literature neglects potential effects of WFH on wage distribution and on income inequality in general.

What we do

  • This study is a first to show how a future increase in WFH would be related to changes in labour income levels and inequality.
  • We analyse to what extent an increase in the number of employees who have the opportunity to WFH (or at least an increase in the likelihood their professions can be performed from home) would influence the wage distribution, under the hypothesis that this WFH feasibility shift is long lasting.
  • We focus on Italy as an interesting case study because before the pandemic, the WFH practice was not widespread and it is the first Western country to adopt a lockdown of economic activities (on March 11). Barbieri et al. (2020) estimated that at least 3 million employees started to WFH because of lockdown measures, and  a large number started even earlier due to the closure of schools and universities on March 5. Moreover, Italy was the European country with the lowest share of teleworkers before the crisis (Eurofound and ILO, 2017) and, because of the pandemic, it had to face a massive increase in WFH in a very short time without precise legislation and adequate policies.
  • Our analysis relies on a uniquely detailed dataset relying on the merge of two sample surveys: the Survey on Labour Participation and Unemployment (INAPP-PLUS) for the year 2018, which contains information on incomes, skills, education level, and employment conditions of approximately 45,000 working-age Italians and the  Italian Survey of Professions (ICP) for the year 2013, which  provides detailed information on the task-content of occupations. The analysis is conducted through an influence function regression method which allows to estimate the impact of marginal changes on an outcome variable distribution (see the paper for more details on the method).

What we find

  • Employees with high WFH feasibility levels are more often female, older, highly educated, and among those living in metropolitan areas.
  • Economic sectors being characterized by greater shares of employees with high WFH feasibility are: Finance and Insurance, Information and Communications, and Other Business Services (e.g., car renting, travel agencies, employment agencies).
  • Figure 1 shows the wage gap between employees with high and low WFH feasibility and the share of WFH feasibility along the income deciles. The figure clearly shows that the wage gap is increasing along the distribution and reaches highest values in the last two decile groups, as well as the same incidence of high WFH feasibility among employees.

Figure 1 – Incidence of high WFH feasibility and wage gap in favor of employees with high feasibility levels by decile of annual income

What we suggest

WFH risks to exacerbate pre-existing inequalities in the labour market. In this respect, while during the current emergency, policies aimed at alleviating inequality in the short run (e.g. income support measures for the most vulnerable), should be implemented, long-term interventions are even more necessary in order to prevent future rise of inequalities in the labour market. These long-term policies go in three interrelated directions:

  • The necessary massive reorganisation of work, particularly in the field of reengineering of production processes based on new digital technologies and on the possibility offered in terms of work from home requires new and more widespread skills.
  • We need to promote through adequate  economic and cultural incentives, non-compulsory education for youth coming from poorer households. This would include training courses, which would play an important role in reducing future unequal distribution of benefits related to an increase of WFH opportunities, by increasing human capital and favouring its complementarities with technology.
  • Our study highlights that while most of the increase in WFH will concern women, the wage premium would be borne by male employees. In this perspective, a possible, non-exhaustive solution could be offered by policies aimed at improving work–family reconciliation, that continues  to be shouldered more significantly by  women. In particular, we stress the importance of an improving of public childcare and financial support to households with children.

Our study brings out several policy issues for tackling inequalities that will arise in the labour market because of the current pandemic in particular the more than probable  increase in Working From Home. Our results are based on Italian data, but they may be useful to policymakers in other countries as well and, in general, where COVID-19 has forced governments and businesses to rethink production processes with a more intense and stable use of WFH.


Adams-Prassl, A., Boneva, T., Golin M., Rauh C., (2020). Inequality in the Impact of the Coronavirus Shock: Evidence from Real Time Surveys. IZA Discussion Paper No. 13183.

Baert, S. Lippens, L. Moens, E. Sterkens, P. Weytjens, J. (2020), How do we think the COVID-19 crisis will affect our careers (if any remain)?, GLO Discussion Paper, No. 520, Global Labor Organization (GLO), Essen.

Barbieri, T., Basso, G., Scicchitano, S., (2020). Italian Workers at Risk during the COVID-19 Epidemic, GLO Discussion Paper, No. 513, Global Labor Organization (GLO), Essen.

Bonacini, L., Gallo, G. & Scicchitano, S. (2021). Working from home and income inequality: risks of a ‘new normal’ with COVID-19. J Popul Econ 34, 303–360.

Brynjolfsson, E., Horton, J. Ozimek, A. Rock, D. Sharma, G. and Yi Tu Ye, H. (2020). Covid-19 and remote work: An early look at U.S. data. NBER Working Paper 27344.

Dingel, J. I. and B. Neiman (2020). How many jobs can be done at home? Journal of Public Economics 189, 104235.

Eurofound and the International Labour Office (2017), Working anytime, anywhere: The effects on the world of work, Publications Office of the European Union, Luxembourg, and the International Labour Office, Geneva.

Mongey, S., Pilossoph, L., Weinberg. A., (2020). Which Workers Bear the Burden of Social Distancing Policies?. NBER Working Paper No. 27085.

Note: The opinions expressed here are those of the authors and not of the GLO, which has no institutional position.
Featured image: Charles-Deluvio-on-Unsplash


Eugenio Levi, Rama Dasi Mariani & Fabrizio Patriarca on ‘Hate at first sight only. The presence of immigrants, electoral outcomes and policy insights.’ GLO Research for Policy Note No. 3.

GLO Research for Policy Note No. 3 – Theme 10. Migration

Hate at first sight only. The presence of immigrants, electoral outcomes and policy insights.

by Eugenio Levi, Rama Dasi Mariani & Fabrizio Patriarca

Most of the studies on how electoral outcomes in Western Europe and in the US are influenced by the presence of immigrants in the neighborhood provide evidence that living in an area with a greater number of immigrants increases the probability of voting for anti-immigrant parties. The immediate policy implication would be that people want to restrict immigration tout court. But is this so?

In a recent GLO Discussion Paper and forthcoming in the Journal of Population Economics, we contribute to the debate on this topic by analyzing the dynamic aspects related to this effect. This is to investigate if policies should be concerned with the time and geographical concentration of new arrivals more than on their number and focus on integration as well as coping ability of local populations. In particular, we formulate the hypothesis that hostility toward immigration is temporary: there is “hate at first sight” only.

We focus on the 2004, 2009 and 2014 European elections in the United Kingdom, a country in which the immigration issue has been central to all of the latest electoral outcomes.  The UK Independent Party (Ukip), a party founded in 1993 by Conservatives who were cross with the EU, became a strongly anti-immigration party under the leadership of Nigel Farage. It boosted its votes from 15.6% in 2004 to 26.8% in 2014 in correspondence with an increase in the number of immigrants from 8% to 11% of the total population.

What we do.

  • We first test for a short-run effect of the presence of immigrants on votes for Ukip. In our statistical model we add to the share of immigrants the 2-year migration flows, as this is the time lag suggested by time series tests. After having verified that the appropriate statistical conditions for time consistency are satisfied, we proceed to our main analysis. Our models control for unemployment, demographic variables, and population and include specifications with fixed effects for each area and with an instrumental variable approach.
  • Previous studies on Denmark and Italy find that hostility is stronger in rural areas. Immigration to larger urban centers has generally started before immigration to more rural areas, which can explain why previous studies have found a different effect in these two different contexts. Therefore, we test if this difference is completely explained by the time path of immigration or if there is something more, maybe related to political and cultural factors.
  • We explore potential issues related to integration. Do changes in unemployment, welfare expenditures per capita or in the number of crimes explain the short-run effect of the presence of immigrants? These are very common explanations, as individuals may feel that immigrants are to be blamed for increased unemployment, for reduced access to welfare or for an increasing number of crimes.

What we find.

  • The effect of immigration on anti-immigrant votes is indeed a short-run effect. Areas where there has been an acceleration of new arrivals by 1 percentage point see an increase in votes for Ukip by 1.1-1.2 p.p.. In other words, immigration flows boost Ukip votes. In contrast, an increase of 1 p.p. in the share of immigrants corresponds to 1.7-1.9 p.p. fewer votes for Ukip.
  • There is something more to hostility in rural areas than just the time path of immigration. First, we replicate previous evidence that the long-run effect of immigration is declining by population density. Second, if we look at heterogeneity by socioeconomic characteristics, we find that the effect of immigration flows, although positive and significant in all UK, is different in magnitude across areas and reaches a peak of 2.1 p.p. in the “English and Welsh Countryside” (see Figure 1). Only in “London cosmopolitan, Suburban traits and Business and Education centres” and “Mining Heritage and Manufacturing” the share of immigrants has a negative significant effect. This further suggests that political and cultural factors may be more relevant in explaining the difference in votes across areas than the difference between urban and rural areas.
  • Looking more closely at integration issues, in areas that have diminishing welfare benefits per capita immigration flows have a stronger effect on votes for Ukip. Increase in unemployment and in crimes do not seem to matter in relation to hostility to immigration. It is to note that the coefficient of immigration flows always stays significant, suggesting that there is substantially more that is left unexplained.

Figure 1 – UKIP votes by supergroups of area: estimated coefficients and confidence intervals for immigrant share and flows.


Our findings clearly substantiate that the “hate at first sight” effect , e.g the impact of immigration on the ascent of anti-immigrant parties as the result of the short-term material consequences and/or identity reactions induced by migration flows, is indeed a temporary phenomenon. Two main policy implications follow. First, there is a need to pay closer attention to how flows are distributed over time and space: it is probably better to allow immigrants to arrive in small waves and distribute recent arrivals in a homogeneous manner and based on local political and cultural factors, rather than in large ones and concentrated in certain areas. Second, policies should focus more on integration across its cultural, social and economic dimensions. Clearly, in the long run, social forces can drive toward integration; however, policies can expedite this process. In fact, we find that the electoral impact of immigration is weaker and shortly reverted when more welfare resources become available. Therefore, policies and  resources should aim both at facilitating the integration process of migrants as well as the local population’s ability to cope with the changes.


Barone G, D’Ignazio A, De Blasio G, Naticchioni P (2016). Mr. Rossi, Mr. Hu and politics. The role of immigration in shaping natives’ voting behavior. J Public Econ 136: 1–13.

Brunner B, Kuhn A (2018). Immigration, cultural distance and natives’ attitudes Towards immigrants: Evidence from Swiss voting results. Kyklos 71(1): 28-58.

Dustmann C, Vasiljeva K, Damm AP (2018). Refugee migration and electoral outcomes. Rev Econ Stud online.

Halla M, Wagner AF, Zweimüller J (2017). Immigration and voting for the far right. J Eur Econ Assoc 15(6): 1341-1385.

Harmon NA (2018). Immigration, ethnic diversity, and political outcomes: Evidence from Denmark. Scand J Econ 120(4): 1043-1074.

Levi, E, Mariani, RD, Patriarca, F (2019). Hate at first sight? Dynamic aspects of the electoral impact of migration: the case of Ukip. GLO Discussion Paper No. 364. Journal of Population Economics online.

Otto AH, Steinhardt MF (2014). Immigration and election out-comes—evidence from city districts in Hamburg. Reg Sci Urban Econ 45: 67–79.

NOTE: Opinions expressed here are those of the authors and not of the GLO, which has no institutional position.


Friederike Welter & André Pahnke on: The German Mittelstand: an antithesis to Silicon Valley entrepreneurship? GLO Research for Policy Note No. 2

Since 2013, GLO Fellow Friederike Welter is head of the Institut für Mittelstandsforschung (IfM) Bonn, a policy-oriented independent research institute on small business and entrepreneurship issues ( She also holds a professorship at the University of Siegen. Friederike Welter has broad experiences in applied and policy-related research on entrepreneurship and small business, much of it in an international context. She is a member of several policy-related advisory boards for federal and state ministries and for international bodies. She was President of the European Council for Small Business and Entrepreneurship (2007-2009). For her work on small business and entrepreneurship, she has been honored as ECSB Fellow (2011), as Wilford L. White Fellow of the International Council of Small Business (ICSB, 2014) and she recently received the Greif Research Impact Award (2017). The Frankfurter Allgemeine Zeitung regularly lists her among the most influential economists in Germany.

André Pahnke has studied economics at the Leibnitz University Hannover. First, he worked as a research fellow at the Institut für Arbeitsmarkt- und Berufsforschung, Nuremberg. Since 2011, Dr. Pahnke is a researcher at the Institut für Mittelstandsforschung (IfM), Bonn. His main research fields are International Comparative SME Research, Finance and Apprenticeship Training.

GLO Research for Policy Note No. 2 – Theme 3. Future of work

The German Mittelstand: an antithesis to Silicon Valley entrepreneurship?

by Friederike Welter & André Pahnke

At the international level, many policy makers, academics and business observers are interested in understanding Germany’s “secret economic weapon”, its Mittelstand. It is therefore not at all surprising that foreign officials and business people are making pilgrimages to Germany to learn from the Mittelständler. At the same time, German politicians, journalists, and entrepreneurs travel to the Silicon Valley, to learn from what they perceive to be a vibrant start-up ecosystem, fostering the seemingly endless creation of highly innovative, technology-orientated, venture capital-backed gazelles and unicorns. In meetings with policy makers, one of us is regularly asked why Germany could not have its own Microsoft, Google, Amazon or Facebook. Such statements reflect a current debate in Germany: some perceive the German Mittelstand as a low growth, low-tech and non-innovative approach while in contrast the Silicon Valley entrepreneurship is regarded as the salvation for a doomed German economy. In our recent paper (Pahnke and Welter, 2019), we therefore set out to critically review the assumption of the Mittelstand as an antithesis to Silicon Valley entrepreneurship. We suggest that future research and policies should stand back from dichotomies such as “Mittelstand versus Silicon Valley entrepreneurship” and instead acknowledge the vibrant diversity and heterogeneity of entrepreneurship.

What we should know

  • Mittelstand is not just about size. There is some confusion about the meaning of the term “Mittelstand”, not only in the media but also among academia. It is often used as a synonym to Small Medium Entreprises (SMEs). However, the small size of Mittelstand businesses is rather a by-product of other key characteristics. Mittelstand entrepreneurs should be first characterized by their independent ownership. They are typically owned by an individual or a family, who is actively involved in the strategic development and management decision-making of their companies and bears the entrepreneurial risks and liabilities of these decisions. The identity of ownership and management should therefore be seen as a key feature when studying Mittelstand ventures.
  • Mittelstand is a mindset. The ideal business model of the Mittelstand combines ownership, leadership and organizational characteristics with individual value systems and attitudes. Due to a number of positive connotations with the term “Mittelstand” in Germany, even large companies – in which the identity feature of the ownership and management is not present – still perceive themselves as Mittelstand. Therefore, emotions, passion and feelings of belonging, play an important role for understanding the Mittelstand.
  • Mittelstand is important for the economy and the society. The Mittelstand is generally considered to be the backbone of the German economy because of its economic contribution in terms of annual sales, export turnover, net value added, employment generation and apprenticeship training. Many studies illustrate, in addition, its substantial contribution to both the economy and the society. Beyond the provision of employment, goods and services, the specific ownership-management structure of the Mittelstand is associated with high levels of social, inter-generational, and regional responsibilities.
  • Mittelstand is as innovative but often in a different way. Regarding the perceived lack of “innovativeness” in Mittelstand firms in comparison to Silicon Valley entrepreneurship, we argue that this is related to a narrow view of innovation. As soon as we apply a wider understanding of what constitutes innovation, the Mittelstand is by no means less innovative. Mittelstand and Silicon Valley entrepreneurship differ with respect to innovations because of different industry structures and target groups. While Silicon Valley innovations are very consumer-oriented and visible to all of us, Germany’s digital and disruptive technologies are first and foremost “deep tech” hidden in products and processes of other companies.
  • Mittelstand has different patterns of employment growth. Silicon Valley entrepreneurship is generally seen as creating many jobs in a relatively short period of time. In contrast, employment growth in Mittelstand ventures has been slower and happening over a longer period of time; although there are also gazelles in Germany. Such comparisons between the Silicon Valley and the Mittelstand are however problematic: they compare apples (a single high-growth company) to oranges (a whole segment of the German economy).

We need more, not less attention to the Mittelstand!

For obvious reasons, the Mittelstand is often seen as an exclusively German phenomenon: it has deep roots in the German history; it stands for a specific German variety of capitalism; and it is strongly influenced by previous and current institutional arrangements in Germany. In our view, however, the Mittelstand is an excellent example of every day entrepreneurship, demonstrating how entrepreneurship that builds on a deep sense of responsibility and solidarity can shape an economy and society and contribute to its world standing. In this regard, the core characteristics of the Mittelstand stand in stark contrast to Silicon Valley entrepreneurship; although one should not overlook important similarities, too. Overall, the Mittelstand is a vibrant segment of the economy. It is competitive, innovative as well as growth oriented; sometimes by other means that are less visible than the well-known uni- or decacorns from the Silicon Valley.


Berghoff, H. (2006). The End of Family Business? The Mittelstand and German Capitalism in Transition, 1949-2000. The Business History Review,

Fear, J. (2014). The secret behind Germany’s thriving ‘Mittelstand’ businesses is all in the mindset. The Conversation. 28 November 2017.

Gantzel, K.-J. (1962). Wesen und Begriff der mittelständischen Unternehmung. Abhandlungen zur Mittelstandsforschung, 4. Wiesbaden: Springer.

Gärtner, C. (2016). Deep-tech in good old Germany: digitale hidden champions. XING Insider. Accessed 28 Nov 2017.

Pahnke, A.; Welter, F. (2019): The German Mittelstand: antithesis to Silicon Valley entrepreneurship?, Small Business Economics,  52 (2), 345-358.

Ross Range, P. (2012). The German Model. Report. Handelsblatt.
/6966662.html. Accessed 28 November 2017.

Logue, D. M., Jarvis, W. P., Clegg, S., & Hermens, A. (2015). Translating models of organization: Can the Mittelstand move from Bavaria to Geelong? Journal of Management & Organization, 21(01), 17-36.

The Economist (2014). German lessons: Many countries want a Mittelstand like Germany’s. It is not so easy to copy. Accessed 28 November 2017.

NOTE: Opinions expressed here are those of the authors and not of the GLO, which has no institutional position.


Francesco Pastore & Marco Pompili on their research for Italy ‘What works for youth employment?’. GLO Research for Policy Note No. 1

Francesco Pastore is Associate Professor of Political Economy at the University of Campania Luigi Vanvitelli & Fellow and Country Lead for Italy of the Global Labor Organization (GLO).

Marco Pompili is Researcher at Ismeri Europa and GLO Fellow.

GLO Research for Policy Note No. 1 – Theme 4. Population dynamics: youth employment and participation

What works for youth employment? An evaluation of an Italian regional integrated program of active labour market policies

by Francesco Pastore & Marco Pompili

In a recent GLO Discussion Paper, we have studied the effect of PIPOL (Piano integrato di politiche per l’occupazione e il lavoro), an integrated programme of active labour market policies, launched by the Italian Region of Friuli Venezia Giulia in 2014, to facilitate the increasingly difficult school to work transitions for young people. The programme grouped different funding sources, including those originating from the European Social Fund (ESF) and the Youth Employment Initiative (YEI), (an initiative supporting young people in European Union countries, living in regions with high young unemployment rate). The Programme provided employment and training services to increase the employability of participants.

What we should know

  • PIPOL is targeted at different groups of people with different needs: Group 1 includes young people aged 15-19 years at risk of dropping out of school; Group 2 includes young NEETs (Not-in-Education-Employment-or-Training) under the age of 30; Group 3 includes under-30 youngsters with a high-school diploma or a professional qualification attained within the last 12 months; Group 4 includes young people under-30 with a university degree obtained at least 12 months earlier; Group 5 includes unemployed people or at risk of unemployment.
  • The participation in PIPOL is structured in three phases. Phase one is registration: young participants who think to be eligible can register on-line or go to a Public Employment Service (PES) or other institutions for specific groups. In phase two, orientation services are provided  and  participants are profiled according to their needs band; this service has to be offered to people within 60 days from the registration to the PESs. An individual action plan is established, showing the type of active policies to be administered. Phase three is the implementation of active measures, such as on-the-job training, classroom traineeship, labour incentives, support to business creation.
  • Our evaluation focussed on the first stage of PIPOL, in particular on the interventions of off-the-job and on-the-job training completed by the end of 2016.
  • Our analysis focused on 4,962 off-the-job training courses and 3,361 internships, that were completed by the end of 2016. In terms of participants, the study covered 7,175 young people, of which 4,059 women. Overall, 3,911 attended off-the-job training; 2,945 attended on-the-job training; and 319 both types of intervention.
  • To assess the impact, we have resorted to a counterfactual approach: a control group is extracted by means of PSM or Mahalanobis matching among those who registered in the program over the years 2014-16, but have never benefited of the program. In other words, the econometric procedure is organized in two steps. In step one, we draw a random sample of individuals from the group of those who registered in the program but did not attend because of the lack of suitable financial resources. The selection is done in such a way that the target and control group have exactly the same characteristics.
  • The Mahanobis matching is more accurate since it implies that only individuals with exactly the same characteristics are selected. In step two, we compare the probability to find a job by the program participants and the control group to see whether the former has a higher probability of employment than the latter. This allowed us controlling for observed heterogeneity through a battery of control variables (age, gender, citizenship, education, province of residence and also pre-program work experience) and for unobserved heterogeneity, by extracting the control group using the same pool of individuals registered in the program.
  • We used data from two main sources: 1) different data banks from the administration of the program and 2) information on outcome variables obtained from compulsory communications  that employers have to make to employment services whenever any labour contract is signed or completed/ended.

What works? On-the-job training has the greatest impact!

  • We found that the net impact of PIPOL is equal to 5 percentage point (pp) on average, meaning that people who benefited from the Programme have an average  probability to be employed 5 percentage points higher than people who did not.
  • The greatest impact was found for on-the-job training, and no significant impact  was observed for in-room training. On-the Job training  also  increased the probability of finding permanent work (+3pp). This is consistent with the view of a youth labour market where young people have excellent theoretical competences, but very little work experience and work-related competences (Pastore, 2015; 2018).
  • The off-the-job training programs did not show statistically significant impact on employment, but did affect the probability to experience at least one labour contract after 2016.
  • These results are partly due to a lock-in effect, namely the tendency of those who attend training programs to put off their effort in job search.
  • Interestingly, we found that the program has a different impact for different typologies of recipients and different types of intervention. The scheme seems to have a greater net impact in the case of women, foreigners and young people with lower education.
  • Some forms of off-the-job training still have a positive net impact on employment chances (training to gain a qualification).
  • Internships in manufacturing and construction show a greater impact than in the service sector, although the service sector is experiencing a larger expansion overall.

This study represents an important addition to the Italian and global literature on programme evaluation regarding school to work transitions,  considering the small number of such studies, noted also in the recent review of the literature by Card et al. (2010). It is one of the first analysis of the effect of interventions  implemented within the YEI. To our knowledge, there is only a previous paper assessing the impact of YEI in Latvia (Bratti M. et al. 2018) and the evaluation of the Italian YEI (Isfol, 2016), the latter focusing on the very short-term effects. Our findings suggest that active labour market policies for youth are more effective in Italy when they are directly related to the production of work-related competences.

Angrist, D. & J. Pischke (2009). Mostly Harmless Econometrics. Princeton University Press, Princeton.
Bratti, M. & al. (2018). Vocational Training for Unemployed Youth in Latvia: Evidence from a Regression Discontinuity Design, IZA Discussion Paper No. 1187.
Card, D., J. Kluwe and A. Weber (2010). Active Labor Market Policy Evaluations: A Meta-Analysis. Economic Journal, 120 (548): F452-F477.
Card, D., & al. (2018). What Works? A Meta Analysis of Recent Active Labor Market Program Evaluations. Journal of the European Economic Association, 16(3): 894-931.
Isfol. (2016). Primo Rapporto di valutazione del Piano italiano Garanzia Giovani. Roma: Ministero del Lavoro.
Pastore, F. (2018). Why So Slow? The School-to-Work Transition in Italy. Forthcoming in Studies in Higher Education.
Pastore, F. (2015). The Youth Experience Gap. Explaining National Differences in the School-to-Work Transition, Springer Briefs in Economics, Physica Verlag, Heidelberg.
Patore, F. & M. Pompili (2019). Assessing the Impact of Off- and On-the-job Training on Employment Outcomes. A Counterfactual Evaluation of the PIPOL Program, GLO Discussion Paper No. 333.

NOTE: Opinions expressed here are those of the authors and not of the GLO, which has no institutional position.