iii. The Pigou-Daltonian Principle: “Inequality is a Bad Thing”
iv. Polarization
v. Social Exclusion
vi. Equality of Opportunity
vii. The Rawlsian Principle and the Focus on Poverty
viii. What to Do Now?
Chapter 2: Statistical Matters
i. Introduction
ii. Probability Distributions
iii. Parametric and Non-Parametric Distributions
iv. Kernel Estimation
v. Stochastic Dominance Relations
vi. Comparing Distributions
vi. The Test Inconsistency Problem
Chapter 3: Complete Orderings: Index Types and the Ambiguity Problem
i. Introduction
ii. Indices for The Level of Wellbeing
iii. Some Unit Free Inequality Measures
iv. Inequality Adjusted Wellbeing Levels
v. Polarization Measures
vi. Multivariate Polarization Indices
vii. Poverty Measurement
viii. Equal Opportunity and Mobility Indices
ix. Exploring the Impact of Ambiguity
Chapter 4: Partial Orderings
i. Introduction
ii. Stochastic Dominance Criteria
iii. On Restricting the Criterion Space
iv. Stochastic Dominance and Inequality Orderings
v. Stochastic Dominance and Poverty Orderings
vi. Stochastic Dominance and Polarization
vii. The Problem of Ambiguity and Conditions for its Absence
viii. Determination of Ambiguity Groupings: Non-Ambiguity Cuts and Groups
ix. Tools for Ordering Groups and Quantifying Their Differences
Chapter 5: Comparing Latent Subgroups
i. Introduction
ii. Semi-Parametric Mixture Distributions
iii. The Probability of Class Membership of an Agent with an Income x
iv. Estimating the Model
v. Determining the Number of Classes
vi. Studying the Probability of Class Membership
vii. Comparing the Subgroups
Chapter 6: Ambiguity Comparability Segmentation and All That
i. Introduction
ii. An “Absence of Ambiguity” Criteria
iii. Dealing with Ambiguity with Two Groups
iv. Two Ambiguity Indices
v. Ambiguity in inequality measures
vi. Determination of Ambiguity Groupings: Un-Ambiguous Cuts and Groups
vii. An Empirical Application
viii. Conclusions
Chapter 7: Some Applications
i. Introduction
ii. An Example of Canadian Unidimensional Income Distribution Analysis
iii. A Multidimensional Equal Opportunity Example: German Educational Attainment
iv. An Example in Portfolio Choice
v. A Study of Net Crop Returns and Access to Land in Sub Sahara African Irrigation Schemes
vi. A Multidimensional Human Development Example
Gordon Anderson is a member of the Governing Councils and Editorial Boards of The International Association for Research in Income and Wealth, and ECINEQ (Society for the Study of Economic Inequality). He has held Chair positions at the University of Toronto and was also a Professor at McMaster University, both in Canada. He received the Bowley Prize in 1983 and the Sayers Prize in 1984, the Journal of Applied Econometrics' Distinguished Author Award in 2004, and the Connaught Senior Research Fellowship in 2005 and is a Fellow of the Journal of Econometrics.
This book addresses the disparities that arise when measuring and modeling societal behavior and progress across the social sciences. It looks at why and how different disciplines and even researchers can use the same data and yet come to different conclusions about equality of opportunity, economic and social mobility, poverty and polarization, and conflict and segregation. Because societal behavior and progress exist only in the context of other key aspects, modeling becomes exponentially more complex as more of these aspects are factored into considerations. The content of this book transcends disciplinary boundaries, providing valuable information on measuring and modeling to economists, sociologists, and political scientists who are interested in data-based analysis of pressing social issues.