Selection of the distributional rule as an alternative tool to foster cooperation in a Public Good Game

This paper presents an investigation about cooperation in a Public Good Game using an Agent Based Model calibrated on experimental data. Starting from the experiment proposed in Colasante and Russo (2016), we analyze the dynamic of cooperation in a Public Good Game where agents receive an heterogeneous income and choose both the level of contribution and the distribution rule. The starting point is the calibration and the output validation of the model using the experimental results. Once tested the goodness of fit of the Agent Based Model, we run some policy experiment in order to verify how each distribution rule, i.e. equidistribution, proportional to contribution and progressive, affects the level of contribution in the simulated model. We find out that the share of cooperators decreases over time if we exogenously set the equidistribution rule. On the contrary, the share of cooperators converges to 100% if we impose the progressive rule. Finally, the most interesting result refers to the effect of the progressive rule. We observe that, in the case of high inequality, this rule is not able to reduce the heterogeneity of income.This research has received funding from the European Union, Seventh Framework Programme under grant agreements n. SYMPHONY—ICT-2013-611875

Risk aversion, prudence and temperance. It is a matter of gap between moments

Higher order risk preferences are important determinants of choices under uncertainty. We build a questionnaire different from usually adopted ones: our questionnaire is simpler in order to reduce the number of random choices, and it includes questions with largely diversified stake sizes to observe different gaps between moments. Moreover, we collect results from a large and heterogeneous population to provide more general and unbiased results. Our results confirm the preference of the majority of the respondents for higher odd and lower even moments of the expected return distribution. However, we highlight three features: (i) the importance of the gap between the values of the corresponding moments of the two choices, (ii) the behavioral change in presence of a positive/zero/negative expected value, (iii) the huge heterogeneity in behaviors, also due to the complexity of the choice as an important driver of the propensity to switch from choosing on the basis of preferences to choosing randomly. We also find that age and geographical location are important determinants of risk propensity

Financial and non-financial risk attitudes: What does it matter?

In this paper we try to: (i) study the personal features of the subjects that can influence the risk attitude in financial and non-financial contexts, (ii) understand the correspondences among some behaviors in financial and non-financial choices. We start from the questionnaire used by Colasante and Riccetti (2020), that investigates how subjects take into account the first four moments of the return distribution in making risky decisions, and that collects data from a very large and heterogeneous population. We find that age and geographical location are important determinants of risk propensity in all domains. Moreover, we find that risk attitudes in financial and non-financial contexts are correlated, but correlation is far from 1, with a larger risk aversion in non-financial contexts. Therefore, there is a common underlying risk trait, but the context is also relevant. Interestingly, the financial risk propensity is positively correlated to the propensity to perform illegal activities

Evolution of Cooperation in Public Good Game

This paper presents an investigation about cooperation in a Public Good Game using an Agent Based Model calibrated on experimental data. Starting from the experiment proposed in Colasante and Russo (2016), we analyze the dynamic of cooperation in a Public Good Game where agents receive an heterogeneous income and choose both the level of contribution and the distribution rule. The starting point is the calibration and the output validation of the model using the experimental results. Once tested the goodness of fit of the Agent Based Model, we run some policy experiment in order to verify how each distribution rule, i.e. equidistribution, proportional to contribution and progressive, affects the level of contribution in the simulated model. We find out that the share of cooperators decreases over time if we exogenously set the equidistribution rule. On the contrary, the share of cooperators converges to 100% if we impose the progressive rule. Finally, the most interesting result refers to the effect of the progressive rule. We observe that, in the case of high inequality, this rule is not able to reduce the heterogeneity of income

Heuristic Switching Model and Exploration-Exploitation Algorithm to Describe Long-Run Expectations in LtFEs: a Compariso

We elicit individual expectations in a series of Learning-to-Forecast Experiments (LtFEs) with different feedback mechanisms between expectations and market price: positive and negative feedback markets. We implement the EEA proposed by Colasante et al. (J Evol Econ 2018b. https://doi.org/10.1007/S00191-018-0585-1). We compare the performance of two learning algorithms in replicating individual short and long-run expectations: the Exploration-Exploitation Algorithm (EEA) and the Heuristic Switching Model (HSM). Moreover, we modify the existing version of the HSM in order to incorporate the long run predictions. Although the two algorithms provide a fairly good description of prices in the short run, the EEA outperforms the HSM in replicating the main characteristics of individual expectation in the long-run, both in terms of coordination of individual expectations and convergence of expectations to the fundamental value

Voluntary contributions in a system with uncertain returns: a case of systemic risk

This paper investigates systemic risk that emerges from the interplay between uncertain returns to individual actions, uncertainty on others’ behavior and all this filtered through individual attitudes toward risk. We design a finitely repeated linear public good experiment based on a voluntary contribution mechanism and analyze the effect of risky and uncertain returns on subjects’ contributions. Results from a baseline treatment without uncertainty are compared with two risky treatments characterized by different values for the marginal per capita return. In the treatments with risk, subjects are randomly assigned to one out of three feasible marginal per capita returns, independently of what their individual contribution was. Results show that a sufficient level of uncertainty leads to significantly lower individual contributions. Furthermore, in a system with lower contributions due to uncertainty, subjects’ risk aversion enhances the systemic risk, leading the system to collapse

Adaptive expectations versus rational expectations: Evidence from the lab

The aim of the present work is to shed light on the extensive debate about expectations in financial markets. We analyze the behaviors of subjects in an experimental environment in which it is possible to observe expectations directly, since the sole task of each player is to predict the future price of an asset. We investigate the mechanism of expectation formation in two different contexts: first, where the fundamental value is constant; second, where the fundamental price increases over repetitions. First of all, we look at whether there is a convergence to the rational equilibrium even if agents have adaptive expectations, according to the main results of Palestrini and Gallegati (2015). Moreover, we concentrate on the accuracy of aggregate forecasts compared with individual forecasts. We find that there is collective rationality instead of individual rationality. In the context of an increasing fundamental value, contrary to theoretical predictions, players are able to capture the trend, but underestimate that value. This implies that there is no full convergence to the rational expectations equilibrium if all agents make their forecasts according to an adaptive scheme

Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: a comparison

We compare the performance of two learning algorithms in replicating individual short and long-run expectations: the Exploration-Explotation Algorithm (EEA) and the Heuristic Switching Model (HSM). Individual expectations are elicited in a series of Learning-to-Forecast Experiments (LtFEs) with different feedback mechanisms between expectations and market price: positive and negative feedback markets. We implement the EEA proposed by Colasante et al. (2018c). Moreover, we modify the existing version of the HSM in order to incorporate the long-run predictions. Although the two algorithms provide a fairly good description of marker prices in the short-run, the EEA outperforms the HSM in replicating the main characteristics of individual expectation in the long-run, both in terms of coordination of individual expectations and convergence of expectations to the fundamental value

Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: a comparison

We compare the performance of two learning algorithms in replicating individual short and long-run expectations: the Exploration-Explotation Algorithm (EEA) and the Heuristic Switching Model (HSM). Individual expectations are elicited in a series of Learning-to-Forecast Experiments (LtFEs) with different feedback mechanisms between expectations and market price: positive and negative feedback markets. We implement the EEA proposed by Colasante et al. (2018c). Moreover, we modify the existing version of the HSM in order to incorporate the long-run predictions. Although the two algorithms provide a fairly good description of marker prices in the short-run, the EEA outperforms the HSM in replicating the main characteristics of individual expectation in the long-run, both in terms of coordination of individual expectations and convergence of expectations to the fundamental value