Behavioural Economics Research

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					A Multidimensional approach to worklessness: a matter of opportunities, social factors
and individual’s idiosyncrasies.

Gabriella Cagliesi*, Riccardo De Vita*, and Denise Hawkes*
*The University if Greenwich
 Maritime Campus
 London, UK

In this empirical study we propose to use a new cross-disciplinary approach among labour
economics, behavioural economics (BE) and social networking analysis (SNA) to explain
agents’ functioning over employment, non employment and across various inactivity
categories in the labour market. We abandon the traditional welfare approach and use the
more general framework of capabilities and refined functioning proposed by Amartya Sen to
interpret how different types of constraints - ranging from socioeconomic conditions and
environmental background to specific features of individual processes of choices and
decision making- affect preferences and functionings. In our model labour market’s
opportunities, choices and achievements are all affected by the interrelations and interactions
of individual’s demographic and psychological characteristics (such as age, gender, heuristic,
perceptions, beliefs, attitude, goals and ambitions) with external factors (such as
geographical, socio- cultural and economic conditions). To explain worklessness, we
propose to apply a range of BE principles, directly relevant to the labour market, to
investigate “inaction” choices. These principles can be broadly grouped into two dimensions
which represent two levels of departure from rationality: dimension of judgment (information
processing and probability estimation), and dimension of choice/preference (evaluation of
options. alternative and selection of actions). These elements affect individual’s refined
functioning set and interact with the agent’s social capital and with the strength of its
embeddedness in the social environment. Social norms and “close ties” represent vital
additional elements of the analysis. These newly identified constraints impact on the set of
refined functioning and shape ultimately agent’s decisions. We show that patterns of social
interactions influence behavioural attitudes and perceptions, and thus affect human behaviour
and social outcomes. We use the British Household Panel Study data and a sequential
empirical approach to investigate the UK labour market. We start from a static representation
of the labour market’s choices to move subsequently into a dynamic setting. In the static
representation we use a static Probit model for male and female to estimate the probability of
being non employed, controlling for various constraints. We proceed further by using a series
of simultaneous Multinomial models, each for a different age group, to estimate the
probabilities of belonging to some specific category among the non employment. In the
dynamic approach, we estimate probabilities of changing labour marker statuses, linking
these probabilities to changes in perceptions, status quo and reference point or to changes in
other socioeconomic characteristics. Our results indicate that the use of a cross disciplinary
approach of labour economics, behavioural economics and social networking analysis can
generates significant benefits in terms of policy making and policy prescriptions because it
provides useful insights into inaction that can better orientate the design of effective labour

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market policies. For instance a deeper understanding of how social networks impact
worklessness decisions and attitudes, and affect employment perceptions, social mobility,
and human capital investments, can have crucial implications for the labour market policies,
subsidization of education and decision on unemployment benefits.

Keywords: employment, capability, social networking, behavioural economics

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