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This paper aims to perform an analytical analysis on portfolio allocation when a tracking error volatility (TEV) constraint holds, drawing specific attention to the portfolio efficiency issue. Indeed, it is well known that investors can assign part of their funds to asset managers who are given the task of beating a benchmark portfolio. However, the risk management office often imposes a TEV constraint to the asset managers’ activity to maintain the portfolio risk near to the risk of the benchmark. This situation could lead asset managers to select non efficient portfolios in the total return and absolute risk perspective. However, the risk management office can impose further constraints, such as on maximum variance or maximum value at risk (VaR) to maintain the overall portfolio risk under control.

First the authors define the TEV constrained-efficient frontier (ECTF), a set of TEV constrained portfolios that are mean–variance efficient. Second, they define two new portfolio frontiers analyzing how the imposition of a maximum variance or maximum VaR restriction can reduce the ECTF. Third, they investigate the feasibility of such portfolio frontiers and their relationships.

The authors find that variance or VaR constraint can force asset managers to pursue portfolio efficiency.

This is a practically important issue given that asset managers often receive a constraint on TEV from the risk management office, but the risk management office does not ask them to minimize the TEV as often assumed in the optimizations performed in the literature on this topic.

This work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there are omitted variable biases and endogeneity biases and also evaluates if there are heterogeneous effects among provinces with different income levels.

We use a multi-input and output bootstrap data envelopment analysis to assess public health efficiency. Then, we measure well-being indices using the min-max linear scaling transformation technique. A two-stage least squares model is used to identify the causal effect of improving public health efficiency on well-being to account for time-invariant heterogeneity, omitted variable bias and endogeneity bias.

After controlling for important economic factors, the results show a significant effect of an accountable and efficient public health system on well-being. Those effects are concentrated in the North, the most economically, geographically and environmentally advantageous areas.

The use of the sample mean, probably the oldest and most used method for aggregating the indicators, could be affected by variable compensation, with consequent misleading results in the process of constructing the well-being index. Another limitation is the use of lagged values of the main predictor as an instrument in the instrumental variables setting because it could lead to information loss. Finally, the availability of data over a long period of time.

The findings could help policymakers adopt measures to strengthen the public health system, encourage private providers and inspire countries worldwide.

These results draw the attention of local authorities, who play an important role in designing and implementing policies to stimulate local public health efficiency, which puts individuals in the conditions of achieving overall well-being in their communities.

For the first time in Italy, a panel of well-being indices was constructed by developing new methodologies based on microeconomic theory. Furthermore, for the first time, the assessment of the relationship between public health efficiency and well-being is carried out using a panel of 102 Italian provinces.

The purpose of this paper is to explore how psychological variables are related to real-life insurance consumption. Specifically, the authors focus on whether emotions and psychological traits can improve the predictability of insurance demand, taking traditional socioeconomic variables under control.

The approach used was in-person survey, based on a traditional questionnaire, the Barratt Impulsiveness Scale and a psycho-physiological task (Iowa Gambling Task (IGT)).

A selective role of emotions and psychological traits has been proven to exist when comparing different insurance policies. Life and casualty insurance are affected by emotional arousal to losses; indemnity insurance by fear of the unknown, whereas health insurance by impulsivity.

The findings indicate that individual insurance consumption may be amplified by not cognitive components. Future research should concentrate on testing the effect of further psychological traits related to pure risk coverage.

The results may be of interest for insurers in order to know what drives insurance demand with respect to different kinds of pure risks.

For policymakers, it is important to understand how psychological factors affect consumer behavior in order to incorporate such perspective into modern insurance policy measures. An analysis of such factors may also increase the self-consciousness of insurance consumers and enrich consumer self-protection.

The authors propose an interdisciplinary approach to analyze insurance demand and test different kinds of insurance coverage, suggesting not homogenous hedging behaviors in relation to specific ambiguous events.