Goals

We aim at a better understanding of the determinants of prosocial  behavior, deriving implications for policies designed to foster prosociality. 

We want  to bridge two important strands of scientific literature (one focusing on cognition, the other one focusing on social interactions) which have been so far substantially separated.

1 project - 3 work streams

WS1. Measuring the interplay of social sanctioning and cognition in the lab (Scientific coordinator: Ennio Bilancini)

We run incentivized laboratory experiments where experimental subjects have to choose between a prosocial and selfish behavior, aimed at identifying how cognition and social sanctioning jointly affect prosocial behavior.

To this purpose the experimental subjects are treated along both their reliance on a cognitive mode and their exposure to social sanctioning. 

Preliminary experiments  are run to validate the design of the treatments  that  have to be employed to manipulate the cognitive mode.

WS2. Building a field-and-lab dataset on prosocial behavior (Scientific coordinator: Emiliano Ricciardi)

Drawing from two a unique datasets, we want to investigate the cognitive and the social roots of prosociality at the same time, as well as their interplay.

The first dataset is about dozen of thousands of blood and plasma donors where prosociality is measured by blood and plasma donation as well as other behavioral and neuroscientific measures obtained from laboratory experiments. Moreover, we aim at  enriching the dataset  with information regarding the structure of social interactions.

The second dataset is about two thousands of students of 2nd-4th grade in Lucca where prosociality is measured by reported behavior on good practices in water usage as well as information regarding the structure of social interactions, ludic habits and preferences. Moreover, we aim at measureing the impact of gamed based learning policies aimed at promoting prosocial behavior, controlling for the structure of social interactions. 

WS3. Modeling the emergence of prosociality (Scientific coordinator: Rossana Mastrandrea)

We will study a model  with a large population of individual decision-makers, each characterized by a set of attributes (cognitive attitudes), who are connected to each other via a nontrivial social network structure. Both the individual attributes and the network structure can be heterogeneous and evolve in time.

The relevant dynamics at the aggregate level (i.e., the switching between selfish and prosocial behaviour of a sizeable fraction of the population) will have to emerge as a result of individual decision-making that, in turn, will depend on both individual attributes (cognition) and the interaction structure (peer effects)