Fuzzy set approach to multidimensional poverty measurement / edited by Achille Lemmi and Gianni Betti.

Format:

Book

Contributor:

Lemmi, Achille.

Betti, Gianni.

Language:

English

Subjects (All):

Poverty--Measurement.

Poverty.

Fuzzy sets--Data processing.

Fuzzy sets.

Physical Description:

xv, 279 pages : illustrations ; 25 cm

Place of Publication:

[New York] : Springer, 2006.

Summary:

Recent theoretical and empirical studies have concluded that in order to be accurate, poverty and deprivation must be measured within a multidimensional framework that is consistent, efficient, and statistically robust. The fuzzy set approach to poverty measurement was developed in the early 1990s and continues to be refined by scholars of economics and sociology who find the traditional "monetary-only" indicators to be inadequate and arbitrary.

This volume brings together advanced thinking on the multidimensional measurement of poverty, including the theoretical background, applications to cross-sections using contemporary European examples, and longitudinal aspects of multidimensional fuzzy poverty analysis that pay particular attention to the transitory, or impermanent, conditions that often occur during transitions to market economies. This book will be of interest to scholars and researchers and will be a useful text on poverty for advanced students in applied statistics, urban planning, economics, and sociology.

Contents:

1 Philosophical Accounts of Vagueness, Fuzzy Poverty Measures and Multidimensionality 9

/ Mozaffar Qizilbash 9

1.2 The Vagueness of "Poor" 10

1.3 Three Views of Vagueness 12

1.4 Epistemic and Fuzzy Set Theoretic Views and the Measurement of Poverty 17

1.5 Supervaluationism and the Measurement of Poverty 20

2 The Mathematical Framework of Fuzzy Logic 29

/ Bernard Fustier 29

2.2 The graduality principle 30

2.2.1 Fuzzy propositions 30

2.2.2 Fuzzy subsets, fuzzy numbers 31

2.3 The connectors of fuzzy logic 33

2.3.1 Zadeh's operators 33

2.3.2 Other fuzzy logical connectives 38

2.4 Decision-making and evaluation in a fuzzy context 41

2.4.1 Optimal fuzzy decision: the Bellman and Zadeh's model 41

2.4.2 "Fuzzy" aggregation in evaluation problems 42

3 An Axiomatic Approach to Multidimensional Poverty Measurement via Fuzzy Sets 49

/ Satya R Chakravarty 49

3.2 Fuzzy Membership Function 52

3.3 Properties for a Fuzzy Multidimensional Poverty Index 56

3.4 The Subgroup Decomposable Fuzzy Multidimensional Poverty 61

3.4.1 Poverty Indices 61

4 On the Convergence of Various Unidimensional Approaches 73

/ Ehud Menirav 73

4.2 Basic components of the unidimensional approach 74

4.3 The choice of definition and the scope of poverty 78

4.3.1 Impact of the weighting procedures 78

4.3.2 Impact of the economic well-being variables 79

4.3.3 Impact of equivalence scales 81

4.4 Choice of definition and identification of the poor 82

4.4.1 Looking at the poorest quintile 82

4.4.2 The population defined as poor 85

4.4.3 Identifying the poor according to more than two distributions 87

5 Capability Approach and Fuzzy Set Theory: Description, Aggregation and Inference Issues 93

/ Enrica Chiappero Martinetti 93

5.2 Brief remarks on distinctive features of the capability approach 95

5.3 Describing multidimensional poverty and well-being through fuzzy membership functions 98

5.4 Aggregating well-being dimensions through fuzzy operators 105

5.4.1 Standard complement or negation 106

5.4.2 Standard intersection and standard union 106

5.4.3 Other common fuzzy sets operators 107

5.5 Assessing multidimensional well-being through fuzzy inference systems 108

6 Multidimensional and Longitudinal Poverty: an Integrated Fuzzy Approach 115

/ Gianni Betti, Bruno Cheli, Achille Lemmi, Vijay Verma 115

6.2 Income poverty 117

6.3 Non-monetary deprivation ("Fuzzy Supplementary") 120

6.4 Fuzzy set operations appropriate for the analysis of poverty and deprivation 122

6.4.1 Multidimensional measures 122

6.4.2 Definition of poverty measures according to both monetary and non-monetary dimensions 123

6.4.3 Income poverty and non-monetary deprivation in combination: Manifest and Latent deprivation 127

6.5 On longitudinal analysis of poverty conceptualized as a fuzzy state 128

6.5.1 Longitudinal application of the Composite fuzzy operation 128

6.5.2 The general procedure 129

6.6 Application to specific situations 132

6.6.1 Persistence of poverty 132

6.6.2 Rates of exit and re-entry 134

7 French Poverty Measures using Fuzzy Set Approaches 139

/ Valerie Berenger, Franck Celestini 139

7.2 Application of the TFR approach using data from the French Surveys on Living Conditions for the years 1986 and 1993 140

7.3 Statistical sensitivity analysis of the TFR poverty index on the number of attributes 144

7.4 Extracting a law from multidimensional poverty scores analogous to the Pareto Law for income distribution: a method based on the TFR approach 145

Appendix List of deprivation indicators selected from the INSEE-French Surveys of Living Conditions 1986 and 1993 153

8 The "Fuzzy Set" Approach to Multidimensional Poverty Analysis: Using the Shapley Decomposition to Analyze the Determinants of Poverty in Israel 155

/ Joseph Deutsch, Jacques Silber 155

8.2 Theoretical Background 156

8.3 The Case of Israel in 1995 157

8.3.1 Selecting the Indicators 157

8.3.2 The Data Sources 158

8.3.3 Computing the percentage of poor according to the various approaches 158

8.3.4 The Determinants of multi-dimensional poverty 159

8.3.5 The Shapley Approach to Index Decomposition and its Implications for Multidimensional Poverty Analysis 168

Appendix List of Variables available in the 1995 Israeli Census 172

9 Multidimensional Fuzzy Set Approach Poverty Estimates in Romania 175

/ Maria Molnar, Filofteia Panduru, Andreea Vasile, Viorica Duma 175

9.2 Socio-economic and demographic context 176

9.3 Monetary dimension of poverty 179

9.3.1 National method 179

9.3.2 Relative method 182

9.4 Multidimensional estimation of poverty 183

9.4.1 Poverty and occupational status 184

9.4.2 Poverty and education 186

9.4.3 Poverty and demographic characteristics of households 186

9.4.4 Territorial distribution of poverty 188

10 Multidimensional and Fuzzy Poverty in Switzerland 195

/ David Miceli 195

10.2 Poverty in Switzerland 196

10.3 Decompositions of poverty 201

10.3.1 Poverty by employment status 202

10.3.2 Poverty by household composition 205

11 A Comparison of Poverty According to Primary Goods, Capabilities and Outcomes. Evidence from French School Leavers' Surveys 211

/ Josiane Vero 211

11.2 Three concepts of poverty 212

11.2.1 Clarifying basic features 212

11.2.1 Describing connections between the three concepts 215

11.3 A multidimensional measure of poverty: the fuzzy logic 216

11.3.1 Data processing: income, qualitative and continuous indicators 218

11.3.2 The proposed membership function 220

11.3.3 Example: calculation of a composite membership function 221

11.4 Empirical comparison on French Youth Panel Survey from 1996 to 1999 222

11.4.2 The informational basis of primary goods 223

11.4.3 The informational basis of primary social outcomes 225

11.4.4 The informational basis of refined functionings 226

11.4.5 Analyse recovery of the three populations 227

Appendix 1 The CEREQ Panel Data Surveys 229

Appendix 2 French Educational Level 230

12 Multidimensional Fuzzy Relative Poverty Dynamic Measures in Poland 233

/ Tomasz Panek 233

12.3 Methods of Analysis 235

12.3.1 Multidimensional Analysis of Poverty 235

12.3.2 Evaluation of the Poverty Nature 239

12.3.3 Poverty Determinants 241

12.4 Changes in the Poverty Sphere in Poland from 1996 to 1999 242

12.4.1 Degree of the Poverty Threat 242

12.4.2 Poverty Nature 245

12.4.3 Poverty Determinants 248

13 Modelling Fuzzy and Multidimensional Poverty Measures in the United Kingdom with Variance Components Panel Regression 257

/ Gianni Betti, Antonella D'Agostino, Laura Neri 257

13.2 Fuzzy and multidimensional poverty definitions 259

13.3 Panel regression models with variance components 260

13.4 Cross-sectional empirical analysis 262

13.5 Longitudinal empirical analysis 264

13.5.1 Trend estimation 266

13.5.2 The effect of covariates 269.

Notes:

Includes bibliographical references and index.

ISBN:

0387342494

OCLC:

72763464

Publisher Number:

9780387342498