Lemmi / Betti Fuzzy Set Approach to Multidimensional Poverty Measurement

1. Auflage 2006
ISBN: 978-0-387-34251-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 3, 285 Seiten

Reihe: Economic Studies in Inequality, Social Exclusion and Well-Being

This volume brings together advanced thinking on the multidimensional measurement of poverty. This includes 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. The research is up-to-date and international.

Achille Lemmi is Professor of Economic Statistics at the University of Siena. His areas of interest and research include personal income distribution models, poverty and living conditions estimation and analysis, and poverty dynamics. Gianni Betti is Associate Professor of Economic Statistics at the University of Siena. His areas of interest and research include poverty and living conditions analysis, equivalence scales, small area estimation and poverty mapping.

Autoren/Hrsg.

Lemmi, Achille

Betti, Gianni

Lemmi, Achille A.

Inhaltsverzeichnis

1;List of contributing authors;11
2;Introduction;16
3;1 Philosophical Accounts of Vagueness, Fuzzy Poverty Measures and Multidimensionality;23
3.1;1.1 Introduction;23
4;2 The Mathematical Framework of Fuzzy Logic;43
4.1;2.1 Introduction;43
4.1.1;2.2.1 Fuzzy propositions;44
4.1.2;2.2.2 Fuzzy subsets, fuzzy numbers;45
4.2;2.3 The connectors of fuzzy logic;47
4.2.1;2.3.1 Zadeh's operators;47
4.2.2;2.3.2 Other fuzzy logical connectives;52
4.3;2.4 Decision-making and evaluation in a fuzzy context;55
4.3.1;2.4.1 Optimal fuzzy decision: the Bellman and Zadeh's model;55
4.3.2;2.4.2 "Fuzzy" aggregation in evaluation problems.;56
4.4;References;60
5;3 An Axiomatic Approach to IVIultidimensional Poverty IVIeasurement via Fuzzy Sets;62
5.1;3.1 Introduction;62
5.2;3.2 Fuzzy Membership Function;65
5.3;3.3 Properties for a Fuzzy Multidimensional Poverty Index;69
5.4;3.4 The Subgroup Decomposable Fuzzy Multidimensional Poverty;74
5.5;3.5 Conclusions;80
5.6;References;82
6;4 On the Convergence of Various Unidimensional Approaches;86
6.1;4.1 Introduction;86
6.2;4.2 Basic components of the unidimensional approach;87
6.3;4.3 The choice of definition and the scope of poverty;91
6.3.1;4.3.1 Impact of the weighting procedures;91
6.3.2;4.3.2 Impact of the economic well-being variables;92
6.4;4.4 Choice of definition and identification of the poor;95
6.4.1;4.4.1 Looking at the poorest quintile;95
6.4.2;4.4.2 The population defined as poor;98
6.4.3;4.4.3 Identifying the poor according to more than two distributions;100
6.5;4.5 Concluding comments;101
7;5 Capability Approach and Fuzzy Set Theory: Description, Aggregation and Inference Issues;105
7.1;5.1 Introduction;105
7.2;5.2 Brief remarks on distinctive features of the capability approach;107
7.3;5.3 Describing multidimensional poverty and well-being through fuzzy membership functions;110
7.4;5.4 Aggregating well-being dimensions through fuzzy operators;117
7.5;5.5 Assessing multidimensional well-being through fuzzy inference systems;120
7.6;5.6 Conclusion;123
7.7;References;124
8;6 Multidimensional and Longitudinal Poverty: an Integrated Fuzzy Approach;126
8.1;6.1 Introduction;126
8.2;6.2 Income poverty;128
8.3;6.3 Non-monetary deprivation ("Fuzzy Supplementary");131
8.4;6.4 Fuzzy set operations appropriate for the analysis of poverty and deprivation;133
8.4.1;6.4.1 Multidimensional measures;133
8.4.2;6.4.2 Definition of poverty measures according to both monetary and non-monetary dimensions;134
8.4.3;6.4.3 Income poverty and non-monetary deprivation in combination: IVIanifest and Latent deprivation;138
8.5;6.5 On longitudinal analysis of poverty conceptualized as a fuzzy state;139
8.5.1;6.5.1 Longitudinal application of the Composite fuzzy operation;139
8.5.2;6.5.2 The general procedure;140
8.6;6.6 Application to specific situations;143
8.6.1;6.6.1 Persistence of poverty;143
8.6.2;6.6.2 Rates of exit and re-entry;145
8.7;6.7 Concluding remarks;146
8.8;References;146
9;7 French Poverty Measures using Fuzzy Set Approaches;149
9.1;7.1 Introduction;149
9.2;7.2 Application of tiie TFR approach using data from the French Surveys on Living Conditions for the years 1986 and 1993;150
9.3;7.3 Statistical sensitivity analysis of the TFR poverty index on the number of attributes;154
9.4;7.4 Extracting a law from multidimensional poverty scores analogous to the Pareto Law for income distribution: a method based on the TFR approach;155
9.5;7.5 Concluding comments;161
9.6;References;162
9.7;Appendix: List of deprivation indicators selected from the INSEE-French Surveys of Living Conditions 1986 and 1993 ;163
10;8 The "Fuzzy Set" Approach to Multidimensional Poverty Analysis: Using the Shapley Decomposition to Analyze the Determinants of Poverty in Israel;165
10.1;8.1 Introduction;165
10.2;8.2 Theoretical Background;166
10.3;8.3 The Case of Israel in 1995;167
10.3.1;8.3.1 Selecting the Indicators;167
10.3.2;8.3.2 The Data Sources;168
10.3.3;8.3.3 Computing the percentage of poor according to the various approaches;168
10.3.4;8.3.4 The Determinants of multi-dimensional poverty;169
10.3.5;8.3.5 The Shapley Approach to Index Decomposition and its Implications for Multidimensional Poverty Analysis;178
10.4;8.4 Concluding Comments;180
10.5;Bibliography;181
10.6;Appendix: List of Variables available in the 1995 Israeli Census;182
11;9 Multidimensional Fuzzy Set Approach Poverty Estimates in Romania;185
11.1;9.1 Introduction;185
11.2;9.2 Socio-economic and demographic context;186
11.3;9.3 Monetary dimension of poverty;189
11.3.1;9.3.1 National method;189
11.3.2;9.3.2 Relative method;192
11.4;9.4 Multidimensional estimation of poverty;193
11.4.1;9.4.1 Poverty and occupationat status;194
11.4.2;9.4.2 Poverty and education;196
11.4.3;9.4.3 Poverty and demographic characteristics of households;196
11.4.4;9.4.4 Territorial distribution of poverty;198
11.5;9.5 Conclusions;199
11.6;References;204
12;10 Multidimensional and Fuzzy Poverty in Switzerland;205
12.1;10.1 Introduction;205
12.2;10.2 Poverty in Switzerland;206
12.3;10.3 Decompositions of poverty;211
12.3.1;10.3.1 Poverty by employment status;212
12.3.2;10.3.2 Poverty by household composition;215
12.4;10.4 Concluding remarks;217
12.5;References;218
13;11 A Comparison of Poverty According to Primary Goods, Capabilities and Outcomes. Evidence from Frencli School Leavers' Surveys;220
13.1;11.1 Introduction;220
13.2;11.2 Three concepts of poverty;221
13.2.1;11.2.1 Clarifying basic features;221
13.2.2;11.2.1 Describing connections between tlie three concepts;224
13.3;11.3 A multidimensional measure of poverty: the fuzzy logic;225
13.3.1;11.3.1 Data processing: income, qualitative and continuous indicators;227
13.3.2;11.3.2 The proposed membership function;229
13.3.3;11.3.3 Example: calculation of a composite membership function;230
13.4;11.4 Empirical comparison on French Youth Panel Survey from 1996 to 1999;231
13.4.1;11.4.1 Preliminaries;231
13.4.2;11.4.2 The informational basis of primary goods;232
13.4.3;11.4.3 The informational basis of primary social outcomes;234
13.4.4;11.4.4 The informational basis of refined functionings;235
13.4.5;11.4.5 Analyse recovery of the three populations;236
13.5;11.5 Conclusion;238
13.6;Appendix 1 - The CEREQ Panel Data Surveys;238
13.7;Appendix 2 - French Educational Level;239
13.8;References;239
14;12 Multidimensional Fuzzy Relative Poverty Dynamic Measures in Poland;241
14.1;12.1 Introduction;241
14.2;12.2 Sources of Data;242
14.3;12.3 Methods of Analysis;243
14.3.1;12.3.1 Multidimensional Analysis of Poverty;243
14.3.2;12.3.2 Evaluation of the Poverty Nature;247
14.3.3;12.3.3 Poverty Determinants;249
14.4;12.4 Changes in the Poverty Sphere in Poland from 1996 to 1999;250
14.4.1;12.4.1 Degree of the Poverty Threat;250
14.4.2;12.4.2 Poverty Nature;253
14.4.3;12.4.3 Poverty Determinants;256
14.5;12.5 Summary;261
14.6;References;262
15;13 Modelling Fuzzy and Multidimensional Poverty Measures in the United Kingdom with Variance Components Panel Regression;264
15.1;13.1 Introduction;264
15.2;13.2 Fuzzy and multidimensional poverty definitions;266
15.3;13.3 Panel regression models with variance components;267
15.4;13.4 Cross-sectional empirical analysis;269
15.5;13.5 Longitudinal empirical analysis;271
15.5.1;13.5.1 Trend estimation;273
15.5.2;13.5.2 The effect of covariates;276
15.6;13.6 Concluding remarks;280
15.7;References;280
16;Index;283

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