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.

Autorentext
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.

Inhalt

Chapter 1: Measuring the Wellbeing of Groups

i. The Social Welfare Function

ii. The Benthamite (Utilitarian) Tradition

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