Bøger af Giuseppe Arbia

This textbook offers a practical and engaging introduction to spatial econometric modelling, detailing the key models, methodologies and tools required to successfully apply a spatial approach. The second edition contains new methodological developments, new references and new software routines in R that have emerged since the first edition published in 2014. It also extends practical applications with the use of the software STATA and of the programming language Python. The first software is used increasingly by many economists, applied econometricians and social scientists while the software Python is becoming the elective choice in many scientific applications. With new statistical appendices in R, STATA and Python, as well as worked examples, learning questions, exercises and technical definitions, this is a significantly expanded second edition that will be a valuable resource for advanced students of econometrics.

This book focuses on economic inequality, its measurement, and its relationship with economic growth and development. The current literature uses multiple points of view, ranging from ethical, legal, philosophical, to political and economic, to understand the nature of (in)equality. Presenting the problem objectively, this book shows how to measure the phenomenon statistically along with an international comparison of the level of income inequality and economic growth and of their complex relationship. The book also analyzes three decades of theoretical and empirical evidence to understand this phenomenon and discusses a number of political measures to reduce economic disparities while stimulating economic growth.

This book aims at meeting the growing demand in the field by introducing the basic spatial econometrics methodologies to a wide variety of researchers. It provides a practical guide that illustrates the potential of spatial econometric modelling, discusses problems and solutions and interprets empirical results.

This book bridges the gap between economic theory and spatial econometric techniques. The volume provides a rigorous treatment of the basic spatial linear model, and it discusses the violations of the classical regression assumptions that occur when dealing with spatial data.

Takes a broad view of spatial econometrics and introduces some of the basic concepts. After an introduction, the book introduces methods for the spatial econometric analysis of regional data, explores the new emerging field of microeconometrics, and applies the general SARAR paradigm to the case of spatial interaction models.

Figure 1. 4: First order neighbours (a) and second order neighbours (b) of a reference area. a shows the first-order neighbours of a reference area, while Figure 1. While it is clear that the dependence is strongest between immediate neighbouring areas a certain degree of dependence may be present among higher-order neighbours.

Figure 1. 4: First order neighbours (a) and second order neighbours (b) of a reference area. a shows the first-order neighbours of a reference area, while Figure 1. While it is clear that the dependence is strongest between immediate neighbouring areas a certain degree of dependence may be present among higher-order neighbours.