Needs Based Model to Measure Well-being
Challenges: Production-centric society, political and social alienation, physical and mental health inequality
Proposal: A new model for measuring value
We developed an econometric model which aims at formulating a new measurement of value within an alternative economic framework. This analysis will enable policy-makers to periodically evaluate individuals’ well-being and monitor the impact of economic policy proposals in relation to this.
For the purpose of this model, data would be collected regionally through surveys every six months and respondents would be asked to answer a number of questions to quantify well-being. The regression serves both a positive and normative purpose, estimating on the one hand welfare discrepancies across various societal groups and, on the other, it serves as a basis to advise governments on effective fiscal policy.
The estimated regression model is the following:

Where wellbeing is an aggregate measure of the individuals’ welfare estimated by merging more specific disaggregated variables. Variables measuring respondents’ wellbeing include a set of indicators that will then be aggregated in the final index.
The variables age, gender, and race were introduced in the model to capture wellbeing differentials across society. However, there is potential for flexibility, for example including factors such as employed/unemployed or citizen/migrant.
Gender is a binary variable assuming value 1 if the individual is female and 0 otherwise, therefore, 2 coefficient quantifies how wellbeing is higher or lower for females compared to males. The same reasoning applies to coefficients 1 and 3 which instead capture wellbeing differential across different ethnicities and age classes.
To include nonlinear returns to income on wellbeing, both income and income2 were included in the model. This has been done specifically to capture the Easterlin Paradox, the idea that, past a certain point, wealth has a negative correlation with happiness. This is thus captured by coefficients 4 and 5which measure how once a certain level of income is met, individuals reach a “satiation point” and income no longer has a positive correlation with happiness levels. As a consequence, we are expecting to find positive and negative estimates for 4 and 5 respectively. The variable inequality was introduced in the regression to capture the impact that inequality has on wellbeing and is calculated as the difference between an individual’s income and the average income of the richest decile of the distribution.
Factor X is fundamental to the normative purpose of the model, it is a matrix containing variables for all the services we aim at directing our public spending towards, including education, safety, health, transportation, social welfare and environment.
Factor Y is a matrix containing well-being measurements, variables expressing individuals’ perceptions of economic sufficiency and stability, access to education, physical and mental health, safety and the environmental situation in their region or country.