Simone Landini – författare

This Element presents the κ-generalized distribution, a statistical model tailored for the analysis of income distribution. Developed over years of collaborative, multidisciplinary research, it clarifies the statistical properties of the model, assesses its empirical validity and compares its effectiveness with other parametric models. It also presents formulas for calculating inequality indices within the κ-generalized framework, including the widely used Gini coefficient and the relatively lesser-known Zanardi index of Lorenz curve asymmetry. Through empirical illustrations, the Element criticizes the conventional application of the Gini index, pointing out its inadequacy in capturing the full spectrum of inequality characteristics. Instead, it advocates the adoption of the Zanardi index, accentuating its ability to capture the inherent heterogeneity and asymmetry in income distributions.

This Element works as non-technical overview of Agent-Based Modelling (ABM), a methodology which can be applied to economics, as well as fields of natural and social sciences. This Element presents the introductory notions and historical background of ABM, as well as a general overview of the tools and characteristics of this kind of models, with particular focus on more advanced topics like validation and sensitivity analysis. Agent-based simulations are an increasingly popular methodology which fits well with the purpose of studying problems of computational complexity in systems populated by heterogeneous interacting agents.

This Element works as non-technical overview of Agent-Based Modelling (ABM), a methodology which can be applied to economics, as well as fields of natural and social sciences. This Element presents the introductory notions and historical background of ABM, as well as a general overview of the tools and characteristics of this kind of models, with particular focus on more advanced topics like validation and sensitivity analysis. Agent-based simulations are an increasingly popular methodology which fits well with the purpose of studying problems of computational complexity in systems populated by heterogeneous interacting agents.

Neoclassical economics is heavily based on a formalistic method, primarily centred on mathematical deduction. Consequently, mainstream economists became overfocused on describing the states of an economy rather than understanding the processes driving these states. However, many phenomena arise from the intricate interactions among diverse elements, eluding explanation solely through micro-level rules. Such systems, characterised by emergent properties arising from interactions, are defined as complex. This Element delves into the complexity approach, portraying the economy as an evolving system undergoing structural changes over time.

Neoclassical economics is heavily based on a formalistic method, primarily centred on mathematical deduction. Consequently, mainstream economists became overfocused on describing the states of an economy rather than understanding the processes driving these states. However, many phenomena arise from the intricate interactions among diverse elements, eluding explanation solely through micro-level rules. Such systems, characterised by emergent properties arising from interactions, are defined as complex. This Element delves into the complexity approach, portraying the economy as an evolving system undergoing structural changes over time.

One of the major problems of macroeconomic theory is the way in which the people exchange goods in decentralized market economies. There are major disagreements among macroeconomists regarding tools to influence required outcomes. Since the mainstream efficient market theory fails to provide an internal coherent framework, there is a need for an alternative theory. The book provides an innovative approach for the analysis of agent based models, populated by the heterogeneous and interacting agents in the field of financial fragility. The text is divided in two parts; the first presents analytical developments of stochastic aggregation and macro-dynamics inference methods. The second part introduces macroeconomic models of financial fragility for complex systems populated by heterogeneous and interacting agents. The concepts of financial fragility and macroeconomic dynamics are explained in detail in separate chapters. The statistical physics approach is applied to explain theories of macroeconomic modelling and inference.