The first session of the EUI Social Investment Working Group features paper presentations by Researchers Heta Pöyliö and Tiago Alexandre Ferraz Vieira.
Heta PÖYLIÖ (European University Institute and University of Turku)
Holy Trinity of Social Investment: Empirical evidence on the impacts of stock, flow and buffer policies on poverty in Germany
Discussant: Leon David KÜSTERMANN (Doctoral researcher, EUI)
Abstract:
One key aim of modern welfare states is to reduce poverty and inequality. Many welfare states have adopted elements of the social investment (SI) paradigm, featuring prevention of social risks and employment promotion together with the more traditional income compensation measures. At the aggregate level, strong family policies and active labour market policies are found to be associated with lower poverty rates. However, there is still a void of empirical evidence in explaining how social investment, or welfare state policies in general, alleviate poverty, particularly at the individual level. Launching from the policy function approach where policies are aimed to foster life-long human capital stock, to promote the flow of work-life transitions and buffer the impacts of labour market failures and personal events, the analyses examine their varying influence in a complex social phenomenon of poverty. In other words, this paper studies whether these policy functions of social investment can be empirically proven to reduce the poverty risk of individuals and families.
Considering the drastic changes in the German welfare state moving away from the male-breadwinner model with major reforms in family and unemployment policies since the beginning of the 2000s, it creates an interesting case to analyse the impact of social investment policies on poverty. Using the German Socio-Economic Panel data with various policy measures for years 2001-2018, the analyses disentangle the impacts of stock, flow and buffer policies on the poverty risk of the individuals born 1983-53. Particular focus is put on the vulnerable groups, i.e., single parents and those with low educational attainment, in addition to examining policy complementarities between different policy functions.
The results from logistic regression models with panel-clustered standard errors demonstrate distinct impacts of stock, flow and buffer policies based on their policy function. The poverty risk of married fathers and divorced mothers were found to be reduced with strong stock and buffer policies. However, unfortunately the policy packages did not seem to have a particularly positive impact of the poverty risk of single mothers or low-educated individuals. The strongest poverty reduction mechanism was found when two policy packages were strong, being particularly beneficial for families reducing child poverty risk. The results support the notion of poverty being a complex issue, and alleviation measures ought to reflect its complexity by providing differing policy functions to promote the wellbeing of people.
Tiago Alexandre FERRAZ VIEIRA (European University Institute)
The machine that wore no clothes: Insights into the algorithmic employment relationship
(co-authored with Phoebe Moore (University of Essex) and Robert Donoghue (University of Bath)
Discussant: Elena PISANELLI (Doctoral researcher, EUI)
Abstract
This article interrogates notions of the traditional employment relationship of the industrial period as having two major players, a known boss, and a known worker. The use of machines for management is a notable difference, leading to the birth of ‘algorithmic management’ studies. However, the case study of one airline company’s restructuring programme during the early Covid 19 era demonstrates the need for updating these studies, where the ‘algorithmic employment relationship’ introduces a new and surprising feature, where machines may not even exist at all, within that relationship, but are being used to make decisions, nevertheless. This new version of humans in command, where phantom technology aids management, does not lead to the liberatory future of enabling and empowering technologies. Instead, specific characteristics of this new formation of the employment relationship exacerbate tensions and through quantification and are creating qualified problems for workers, where the algorithm that wore no clothes can be revealed.