Tuesday 14th July      Wednesday 15th July      Thursday 16th July      Friday 17th July     

Wednesday 15th July, 09:00 - 10:30 Room: N-131

The use of survey data to study well-being and economic outcomes
Convenor	Mr Francesco Sarracino (STATEC, HSE-LCSR )
Coordinator 1	Ms Chiara Peroni (STATEC)
Coordinator 2	Mr Cesare Riillo (STATEC)

Session Details

Despite the popularity of well-being measures in economic studies, the relation between subjective well-being and economic performance is still an open issue.

Several empirical studies based on survey data collected on individuals suggest that happier people are more productive and more committed to their work. Happier workers are more pragmatic, less absent, more cooperative and friendly (Bateman and Organ, 1983; Judge et al., 2001) change their job less often and they are more accurate and willing to help others (Spector, 1997). Moreover, happier people earn more money and have better relationships with colleagues and clients, all aspects that contribute to work productivity (George and Brief, 1992; Pavot and Diener, 1993; Wright and Cropanzano, 2000). These results have been confirmed also in experimental settings (Oswald et al., 2009). Further evidence suggests that increased life satisfaction has a positive impact on firms’ economic outcomes (Edmans, 2012).


However, the evidence on the relation between well-being and economic performance is not conclusive. For example, this literature would benefit from new analysis linking survey data to auxiliary data sources on economic outcomes as well as from widening the scope of economic indicators used (Dimaria et al. 2014).

This session aims at collecting contributions analysing the role of well-being and/or job satisfaction on economic outcomes.
We welcome applications on life satisfaction, job satisfaction, productivity, entrepreneurship, innovation, employment, inequality, economic growth.


4th organizer: Dr. Wladimir Raymond, Wladimir.Raymond@statec.etat.lu, STATEC, Luxembourg

Paper Details

1. Modelling survey data to analyze the perception of work–related stress
Ms Stefania Capecchi (Department of Political Sciences, University of Naples Federico II)

A statistical approach to model ordinal responses is presented to detect subjective evaluations through expressed ratings. The paper explores the relationship between personal, economic and age-dependent covariates as determinants of work-related stress perception in a large sample survey, implementing CUB Models.
This class of mixture models (Piccolo, 2003) stems from the consideration that two latent components move the psychological process of selection among discrete ordered alternatives: attractiveness towards the item and uncertainty. Specifically, we discuss results on perceived stress in a cross-country perspective, using data collected in the 5th EWCS carried out by Eurofound in 2010.

2. Returning to work after childbirth: The role of job satisfaction
Dr Julia Gumy (University of Bristol)
Dr Anke Plagnol (City University London)

The study explores whether job satisfaction is an important determinant of female labour market attachment after childbirth in the United Kindgom and Germany. By using two longitudinal European datasets – the British Household Panel Survey (BHPS) and the German Socio Economic Panel (GSOEP) – and event history models, the study finds that in both countries job satisfaction positively affects re-entry into the labour market by reducing the time spent in non-employment after childbirth. This effect is, however, observable for British mothers only twenty months after childbirth, suggesting the importance of other factors during the first months of the child.

3. Happiness matters: the role of well-being in productivity
Mr Charles-henri Dimaria (STATEC)
Ms Chiara Peroni (STATEC)
Mr Francesco Sarracino (STATEC and HSE)

This article is about the link between people’s subjective well-being, defined as an evaluation of one’s own life, and productivity. Our aim is to test the hypothesis that subjective well-being contributes to productivity using a two step approach: first, we establish whether subjective well-being can be a candidate variable to study Total Factor Productivity; second, we assess how much subjective well-being contributes to productivity at aggregate level through efficiency gains. We adopt Data Envelopment Analysis to compute total factor productivity and efficiency indices using European Social Survey and AMECO data for 20 European countries.