The Many Facets of Social Inequality

Income inequality and poverty have become increasingly pressing issues in developed countries over the past few decades. Despite various policy efforts, these problems persist, and their underlying causes remain poorly understood. This project aims to gain new insights into these causes of inequality and poverty and develop effective policy solutions. To achieve this, the project proposes the use of Mean Field Games theory, a cutting-edge mathematical model in macroeconomics. By fostering interdisciplinary and exploratory discussions among scholars from all four Faculties of Durham University, as well as distinguished fellows, the project seeks to identify the fundamental driving forces of social inequality and poverty. With these insights, the project aims to develop innovative models and approaches that can help shape a more equitable and just global community. The ultimate goal is to establish Durham as a world-class research hub on inequality and poverty. The project’s evidence-base research will inform policymakers and the wider community and contribute to creating a more inclusive and equal society. Overall, this project aims to provide a lasting legacy that will help to tackle one of the most pressing challenges facing our world today.

In developed countries, several empirical studies have documented significant changes in the distribution of household incomes over the past five decades. These studies show  that societies have become increasingly unequal, with a significant shrinkage of the middle class and a rise in both the upper and lower classes. Over time, the distribution of  household incomes has become flatter with fatter tails (see for example FT article). This  fact is also confirmed by a dramatic increase in the Gini coefficient, which is an index  capturing the degree of inequality in a society (a Gini coefficient of 0 indicates perfect  income equality, while a Gini coefficient of 1 reflects maximal inequality).

The question of what mechanisms are driving developed societies towards greater  income inequality and increasing poverty has been central to economics and numerous  other disciplines. However, only recent advances in mathematics (e.g., mean field games1, Huang et al. 2006, Lasry and Lions 2007) could make the rigorous economic analysis of these facts viable. 

It is now possible to study macroeconomic models that include both aggregate shocks to the economy, such as a recession, as well as individual-specific (idiosyncratic) shocks,  for example, the varying likelihood across individuals to become unemployed. 

Consequently, these models perform much better in reproducing the actual evolution of  the households’ income distribution (see Achdou et al. 2022) than previous generations  of models (see Caselli and Ventura 2000, among others).  So far, this new approach has been applied to study models which are relatively simplistic on several dimensions. The PIs aim to enhance these models to explain facts which are  relevant not only for economists but also for other disciplines like sociology, psychology, 
etc. Several key questions will be addressed: 

1. Big Shocks: In the existing literature, the income shocks are assumed to be small  (approximatively 5% deviation from the trend). How would a big shock (about 20%  deviation from the trend), such as a pandemic’s impact, affect the income distribution? 
   
   
2.  Behavioural Aspects and Wellbeing: Existing literature on income distribution does  not account for behavioural aspects, such as habits, loss aversion, and present-biased  behaviour among the poor. Empirical studies have found that these factors contribute to an increase in poverty. A crucial question is to what extent these behavioural aspects affect the income distribution and the wellbeing of lower-income groups (with wellbeing measured as a lifetime utility of individuals).
   
   
3. Inequality and Social Trust: The economic literature has rarely incorporated social  trust, social identity, and similar measures into models of income inequality. Our objective  is to enrich this new class of models to better understand the negative effects of increasing inequality on social measures.
   
   
4. Inequality and Distributive Justice: Can this new approach either fit with theories of distributive justice (Mill, Rawls, Sen, Nussbaum) or requires a new way of thinking about justice and inequalities? To investigate and make progress on these questions, we will follow a roadmap with well-defined objectives and milestones in mind.

Notes:

1) Mean Field Games theory is a mathematical framework that allows for the modelling of large  populations of interacting agents who seek to optimise their behaviour in response to the behaviour of  others.

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