Index
Research on Economic Inequality: Poverty, Inequality and Shocks
ISBN: 978-1-80071-558-5, eISBN: 978-1-80071-557-8
ISSN: 1049-2585
Publication date: 2 December 2021
This content is currently only available as a PDF
Citation
(2021), "Index", Bandyopadhyay, S. (Ed.) Research on Economic Inequality: Poverty, Inequality and Shocks (Research on Economic Inequality, Vol. 29), Emerald Publishing Limited, Leeds, pp. 297-304. https://doi.org/10.1108/S1049-258520210000029014
Publisher
:Emerald Publishing Limited
Copyright © 2022 Emerald Publishing Limited
INDEX
Index
Note: Page numbers followed by “n” indicate notes.
Absolute change
, 108
Absolute polarization curve (APC)
, 140–141
Adjusted headcount ratio
, 111
Age pension schemes
, 14
Aggregate effect
, 117
Aging
, 7, 14–16
empirical analysis
, 16–27
populations
, 6
theoretical background
, 7–14
Alternative parametric models for Lorenz curves
, 40
Alternative solution
, 32
Annualized absolute change
, 113–114
Argentina
household characteristics of VRSII sample visá-vis city and urban
, 273–277
microdata used for matching
, 272
urban agglomerations of
, 269
Asignación Universal por Hijo (AUH)
, 280
At-risk-of-poverty (ARP)
, 208
threshold
, 252
Atkinson indices
, 79
Attrition bias testing
, 191–193, 201–205
Average partial effects (APEs)
, 191
of state dependence
, 191–193
Bahia Blanca
, 269–270
Basic Monthly Current Population Survey
, 249
Bayesian framework
, 2, 32
Bayesian inference
, 32
approach based on parametric assumptions of income distribution
, 37–39
data and context
, 45–46
direct approach based on parametric Lorenz curves
, 40–43
empirical illustration using UK data
, 45
GICs for subgroups
, 48–49
GICs for whole population
, 46–48
for log-linear regression model
, 53
measuring pro-poor growth
, 33–37
for mixture of log-normals
, 54–55
Monte Carlo simulation
, 43–45
and tests for GIC
, 38–39
Bennett and Hatzimasoura index
, 2
Bipolarization index
, 139
Brent algorithm
, 50n2
Cardinal entities
, 2
Cardinalized ordinal data
, 9
Cardiovascular disease
, 78
Cash transfer benefits, matrix of
, 280–283
Catholic Church
, 270
Censored headcount ratio (CH)
, 112
Chile
, 170
intragenerational income mobility in
, 168
persistence at extremes of income distribution in
, 176–182
Chilean P-CASEN
, 173
China Health and Retirement Longitudinal Study (CHARLS)
, 15
Classic descriptive statistics
, 272
Classic Mintzer-type equations
, 16
Combined n-poverty indicator
, 250
Complementary Social Salary
, 287
Confidence intervals
, 32
Consumption equation
, 17–18
Contextual predictors
, 58
Country-specific threshold
, 252
COVID-19
, 249
basic household characteristics of VRSII sample visá-vis city and urban Argentina
, 273–277
living conditions in slum area during lockdown
, 277–289
lockdown measures
, 268–269
methodology for analysis
, 272–273
other microdata used for matching
, 272
pandemic
, 1, 3–4
pandemic
, 208
Rosas II Area and Bahia Blanca at Glance
, 269–270
survey design and data collection protocols
, 270–272
COVID-19, MEntal HEalth, Resilience, and Self-regulation (COME-HERE)
, 209, 210, 214, 226
longitudinal survey
, 210–211
Cumulative density functions (CDFs)
, 10
Cumulative distribution
, 38
Data quality
, 271
DCV
, 11
Demographic Health Survey (DHS)
, 106
Dibao effect
, 16
Dibao program
, 14
Dibao receipt
, 23
Dimensional inclusiveness
, 108, 116–118
Direct approach based on parametric Lorenz curves
, 40–43
Distribution-free empirical PGC
, 35
Distribution-free estimator
, 32–33
Distribution-free inference
, 34–37
Distribution-free method
, 43
Distributional change
, 150–154
Distributional effect
, 117
Distributional Gini coefficient (DISGINI)
, 11
“Divide by 4 rule”
, 73n6
Downward-looking status
, 96
Dynamic discrete choice models
, 173
Dynamic hierarchical model
, 60
Dynamic logistic hierarchical model
, 2
Dynamic logistic model
, 63
Dynamic ordered probit models based on random effects specifications
, 186–187
Earned income tax credit (EITC)
, 148
Econometric analysis
, 224–226
Econometric models
, 58
Econometric strategies
, 169, 182
initial conditions and correlated random effects problems in short-period panel data
, 185–186
modeling joint low-income and high-income persistence
, 182–184
Economic growth
, 32
Economic reforms
, 14
Economic security
, 138
Economic shocks
, 170
Economic strain
, 249–250
measures of
, 252–254
Economic uncertainty
, 170
Education
, 209, 289
Elasticity
, 108, 113–114
growth
, 120–127
Emergency family income (IFE)
, 280
Employment
, 209, 278–280
Epidemic shock
, 250
Equivalization
, 174
Euro-area households
, 250
EUROMOD
, 208
Europe, poverty in
, 208
Europe 2020 strategy
, 249, 252
European households
, 248
incomes
, 252
Eurostat
, 79
Eurosystem HFCS
, 251
Ex ante harmonization
, 251
Explanatory variables
, 58
Extreme hypothetical shock
, 250, 255
Face-to-face activities
, 268
Family Expenditure Survey (FES)
, 32
Finances of European households
economic strain
, 249–250
empirical evidence
, 254–260
HFCS
, 251–252
measures of economic strain
, 252–254
nationwide lockdown
, 248
pandemic shock
, 248–249
Financial assets
, 256
First-order Markov process
, 173
First-order Utopia–Dystopia index (FOUDI)
, 10
Food (in)security
, 285–289
Food insufficiency
, 4
Food poverty line
, 73n2
Food security
, 284, 288
Forecasts and mobility analysis
, 71–72
Foster–Greer–Thorbecke family (FGT family)
, 209
index
, 78
Foster–Wolfson bipolarization curve
, 140
Functional forms
, 41–42
and implied quantile functions
, 42
Gini coefficient
, 28n5, 283
Gini decompositions
, 20
Gini indices
, 79
Gini’s transvariation
, 11
Greatest degree of precedence (PRE-G)
, 81
Gross income
, 251
Gross national income (GNI)
, 106
Gross national product (GNP)
, 58
Growth incidence curve (GIC)
, 32–33
Bayesian inference and tests for
, 38–39
Bayesian inference for
, 42–43
for log-normal model
, 37–38
for mixtures of log-normal densities
, 38
pro-poor judgments using
, 33–34
for subgroups
, 48–49
for whole population
, 46–48
Harmonized survey
, 4
Hasse diagram
, 83
Hazard rate models
, 172
Headcount ratio
, 208
Health
, 6
inequality
, 78
“Health poor” category
, 81
Health poverty
, 80
bootstrap confidence intervals for first-and second-order stochastic dominance
, 93
on ordinal variables and health poverty measurement
, 80–83
SAH category
, 78–79
SAH in 29 European countries in 2009 and 2018
, 83–91
Seth and Yalonetzky index
, 79
Heterogeneity analysis
, 209, 219–224
High-income persistence
, 171–172
Horizontal inclusiveness
, 108, 116
Household Wealth and Finance Consumption Survey
, 4
Households
, 248
characteristics of VRSII sample visá-vis city and urban Argentina
, 273–277
demographic variable
, 272
deprivation indicators
, 272
economic income
, 157n4
income
, 208–209, 211
labor incomes
, 249
labor market attachment
, 176
poverty status
, 58
Human capital
, 16, 176
Human development
, 78
Human Development Report
, 111
Implied quantile functions
, 42
In-kind food aid
, 283–285
Incidence
, 211
of multidimensional poverty
, 112
Inclusiveness
, 111
Income distribution
approach based on parametric assumptions of
, 37
Bayesian inference and tests for GIC
, 38–39
GIC for log-normal model
, 37–38
GIC for mixtures of log-normal densities
, 38
Income inequality
, 168
Income losses for middle class groups
, 268
Income mobility
, 168, 170–171
Income of financially poor households
, 256
“Income poor” households
, 254
Income position in Chile
annual income position at t conditional of income position
, 220
average partial effect of state dependence
, 191–193
background
, 170–173
data and definitions
, 173–176
econometric strategy
, 182–186
estimates of dynamic ordered probit models based on random effects specifications
, 186–187
estimation results
, 186
initial conditions and state dependence in both low income and high income
, 187–190
intragenerational income mobility
, 169–170
P-CASEN
, 168–169
persistence at extremes of income distribution in Chile
, 176–182
testing attrition bias
, 201–205
Income poverty
, 4, 106, 110, 253
Income quintile group (IQG)
, 174
Income-based measures of poverty risk
, 253
India
, 106
performance in income and other social indicators
, 107
Indices
, 95–96
Individual heterogeneity
, 171
Individual wellbeing
, 14–15
Inequality
, 1–2, 32, 95, 139–140, 168, 211, 268
as distance from equality
, 96–97
index
, 96
Intensity
, 211
Intensity of multidimensional poverty
, 112
Inter-temporal dependency
, 170
Intermediate bipolarization
indices
, 140
in Israel
, 144–145
Intermediate median income
, 3
Intermediate polarization
, 140
pro-middle class growth using approach to
, 141–144, 162–165
Intermittent slowdowns
, 106
International poverty line
, 106
Intragenerational income mobility in Chile
, 168
Inverse probability weights (IPW)
, 169
Israel, intermediate bipolarization in
, 144–145
Israeli equivalence scale
, 144
Kernel estimator
, 35
Kyrgyz Republic Integrated Sample Household Budget and Labor Force Survey (KIHS)
, 62
Kyrgyzstan, modeling poverty dynamics in
, 62–72
Labor force participation
, 139, 146
Latin America
, 168
Life satisfaction
, 100
Likelihood function
, 53
Likelihood ratio tests
, 18–19
Livelihoods during lockdown
, 277–278
Living conditions in slum area
education
, 289
employment
, 278–280
food (in)security
, 285–289
in-kind food aid
, 283–285
livelihoods during lockdown
, 277–278
during lockdown
, 277
matrix of cash transfer benefits
, 280–283
Location
, 7
Lockdown measures
, 268–270
living conditions in slum area during lockdown
, 277–289
Log-linear regression model, Bayesian inference for
, 53
Log-normal model
, 38, 43
Bayesian inference for mixture of
, 54–55
GIC for
, 37–38
Log-normal probability density function
, 37
Lorenz curve
, 2, 32–34, 95
alternative parametric models for
, 40
Bayesian inference for GIC
, 42–43
direct approach based on parametric
, 40–43
functional forms and implied quantile functions
, 42
three usual functional forms
, 41–42
M-point Gauss–Hermite quadrature
, 184
Macro-conditions
, 58
Macroeconomic forecasts
, 73n7
Main respondent (MR)
, 15
Marginal effects
, 19
Markov chain Monte Carlo techniques (MCMC techniques)
, 2, 59, 65
Markov models
, 185
of transition to poverty
, 173
Matching procedures
, 273
Material deprivation
, 250
Matrix of cash transfer benefits
, 280–283
Maximum inequality
, 97–100
application
, 100–102
Maximum likelihood estimation
, 61–62
Mean–variance adaptive Gauss–Hermite quadrature
, 184
meoprobit command
, 184
Meta-regression
, 60
Micro-determinants
, 58
Middle class in economic development
, 138
Mincer equations
, 16
Minimum and maximum inequality
, 2–3
Minimum inequality
, 96–97
Mixture model method
, 38, 139
Mobility
, 170, 195n1
Monetary poverty
, 106
Monte Carlo simulations
, 2, 32, 43–45
MPI elasticity of censored headcount ratio (e(CH
d
;MPI))
, 117
Multidimensional distributional comparison techniques
, 7
Multidimensional indices
, 7
Multidimensional poverty
, 106, (see also Health poverty)
data
, 118
dimensional inclusiveness
, 116–118
elasticities and semi-elasticities
, 113–114
growth elasticities
, 120–127
horizontal inclusiveness
, 116
India’s performance in income and other social indicators
, 107
India’s performance in various social indicators
, 109–111
methodology
, 112
methodology
, 3, 111
MPI
, 112–113, 118–120
MPI elasticity of censored headcount ratios across states
, 135
per capita state domestic product and net national product
, 134
relative changes in state-wise MPIs and incidences
, 133
results
, 118
uncensored elasticity of censored headcount ratios across states
, 136
vertical inclusiveness
, 108, 114–116
Multidimensional poverty index (MPI)
, 3, 106, 112
indicators
, 269
Multidimensional wellbeing measurement
, 6
Multilevel/hierarchical models
, 58
n-financially poor households
, 253–254
National Family Health Survey (NFHS)
, 111
National growth
elasticity
, 114
semi-elasticity
, 114
Nationwide lockdown
, 248
Net disposable income
, 251
Non-Dibao recipients
, 19
Non-parametric tool
, 139
Non-contributive pensions (NCP)
, 280
OLS Regression analysis
, 272
Ordered probit Regression analysis
, 272
Ordering
, 9–10, 12–13, 24
Ordinal health inequality
, 79
Ordinal monotonicity
, 80
Ordinal Poverty Index
, 80–81
Oster and Wolfson’s index
, 157n2
Outcome value function (OVF)
, 8, 10
Own-state traps/shields
, 182
Pandemic crisis
, 249
Parametric models
, 32
Partial orderings
, 82–83
Pensions
, 253
Percentage change
, 108
Persistence at extremes of income distribution in Chile
, 176–182
Personal income
, 16
Physical assets
, 176
Polarization curves
, 139
Polarization measures
, 139
“Population-average” coefficients
, 66
Positional income mobility
, 171
Positional inconsistency
, 182
Positional movement
, 169–170
Posterior predictive checks
, 65
PovcalNet dataset
, 249
Poverty
, 1, 32, 138, 182, (see also Multidimensional poverty)
ARP rates by NUTS 1 areas and time
, 236
ARP thresholds by country and household type
, 237
COME-HERE longitudinal survey
, 210–211
in COVI D-19 era
, 208
data
, 210
econometric analysis
, 224–226
in Europe
, 208
heterogeneity analysis
, 209–210, 219–224
household income
, 208–209
indices
, 41
main results
, 214–219
measurement
, 139–140
methodology
, 211–213
persistence
, 195n2
poverty across countries and interview dates
, 235, 238, 246
poverty status and individual characteristics
, 244–245
poverty-contributing factors
, 57–59
relative TIP curves by country, interview date, and age
, 232
relative TIP curves by country, interview date, and employment status
, 233
selection in analysis sample
, 234
sensitivity analysis
, 226–228
in single explicative model
, 58
subgroup decomposition of poverty measures in France
, 239
subgroup decomposition of poverty measures in Germany
, 240
subgroup decomposition of poverty measures in Italy
, 241
subgroup decomposition of poverty measures in Spain
, 242
subgroup decomposition of poverty measures in Sweden
, 243
traps
, 171, 172
varying effects of poverty determinants
, 59–62
Poverty dynamics
, 173
data and model choice
, 62–66
main empirical results
, 66–72
modeling in Kyrgyzstan
, 62
Poverty growth curve (PGC)
, 35
Prioritarianism
, 81
Pro-middle class growth
, 138
on absolute measure of
, 160–162
using approach to intermediate polarization
, 141–144
database
, 144
deriving absolute measure of
, 140–141
distributional change
, 150–154
downward trend in relative polarization
, 145
economic security
, 138
factors affecting change in polarization over time
, 145–149
intermediate bipolarization in Israel
, 144–145
intermediate polarization and
, 162–165
intermediate polarization and crucial role of parameter
, 145
intermediate polarization curves
, 156
poverty measurement
, 139–140
results
, 144
upward trend in absolute polarization
, 145
Pro-poor growth
, 47, 138
distribution-free inference
, 34–37
GIC
, 33
measuring
, 33–37
pro-poor judgments using GIC
, 33–34
Probability density function (pdf)
, 9, 12
Probability forecasts
, 72
Quality of life
, 78
Quantile functions
, 32, 42
Quantitative variables
, 78
Questionnaire
, 251, 271
R function uniroot searches
, 50n2
Random effect dynamic ordered probit model (REDOP model)
, 170, 173, 182–183, 188, 191
Ravallion and Chen growth incidence curve
, 1–2
Regression analysis
, 272
Regression coefficients
, 73n1
Relative distribution
, 139
Relative index
, 140
Relative polarization
, 139
Repeated cross-sectional surveys
modeling poverty dynamics in Kyrgyzstan
, 62–72
poverty-contributing factors
, 57–58
structure of Kyrgyz society
, 75–76
study of poverty dynamics
, 58
varying effects of poverty determinants
, 59–62
Residuals plot
, 65
Responsiveness
, 108
Restricted minimum inequality
, 97
Restrictive property
, 79
Root mean square error (RMSE)
, 43
Rural Dibao program
, 14
Scale independent ordered categorical analysis
, 21
Scarring effect
, 171
Self-assessed health (SAH)
, 78
in 29 European countries in 2009 and 2018
, 83
computing family of indices
, 83–88
stochastic dominance analysis
, 88–91
Self-rated health
, 78
Self-reported health or happiness (SRH)
, 6
Semi-elasticities
, 113–114
Sensitivity analysis
, 226–228
Seth and Yalonetzky index
, 79, 83–87
SF-6D index
, 78
Single-category deprivation
, 80
Slum households
, 270
living conditions in slum area during lockdown
, 277–289
Social assistance
, 14
Social distancing
, 248
Social indicators
, 106
Societal wellbeing calculus
, 6
Society
, 169
Socioeconomic Household Panel Survey (P-CASEN)
, 168–169, 173–174
Stan (programming language)
, 73n5
Static poverty analysis
, 58
Statistical tests
, 32
Status
, 96
Stochastic dominance analysis
, 88–91
Stochastic dominance conditions
, 13
Structural predictors
, 58
Subgroup decomposability
, 81
Surface separation index (SS)
, 11
Sustainable Development Goals (SDGs)
, 106
Theil index
, 45, 79
Three “i”s of poverty (TIP)
, 211–212
Time–space varying intercepts
, 67–68
Time–space varying slopes
, 68–71
Total gross income
, 252
Trickle-down
, 138
True state dependence
, 171
Un-modeled coefficients
, 66
Uncensored headcount ratio (UH)
, 113
Unemployment
insurance
, 171
rate
, 67–68
Uniform distribution
, 97
Union-based identification
, 111
United Nations Development Program (UNDP)
, 106
Universal Child Allowance
, 287
Upper-middle-income
, 175
Upward-looking status
, 96, 103n2
Urban agglomerations of Argentina
, 269
US Current Population Survey (CPS)
, 209
Utopia–Dystopia ordering
, 9
Vertical inclusiveness
, 108, 114–116
Villa Rosas II (VRII)
, 269, 273
household characteristics of VRSII sample visá-vis city and urban Argentina
, 273–277
Rosas II Area and Bahia Blanca at Glance
, 269–270
Vulnerability as expected poverty (VEP)
, 72
Wealth
, 249–253
poverty
, 4, 250
Welfare policy
, 149, 157
Welfare programs
, 6
Wellbeing
, 1
value function
, 8
Wellbeing evaluation function (WEF)
, 12
Wooldridge’s method
, 185
World Health Organization
, 78
World Values Survey
, 100
Zoning laws
, 172
- Prelims
- Introduction
- Chapter 1: Multilateral Wellbeing and Inequality Measurement with Ordered Categorical Data: Health, Consumption and the Aging Process in China
- Chapter 2: Bayesian Inference for Parametric Growth Incidence Curves
- Chapter 3: Modeling Household Poverty Status Using Repeated Cross-sectional Surveys
- Chapter 4: On the Measurement of Health Poverty in the Case of Ordinal Variables: The Case of 29 European Countries in 2009 and 2018
- Chapter 5: Maximum Inequality: The Case of Categorical Data
- Chapter 6: Multidimensional Poverty and Inclusive Growth in India: An Analysis Using Growth Elasticities and Semi-elasticities
- Chapter 7: On the Measurement of Relative, Absolute and Intermediate Pro-middle Class Growth
- Chapter 8: Poverty Traps and Affluence Shields: Modeling the Persistence of Income Position in Chile
- Chapter 9: Poverty in the COVID-19 Era: Real-time Data Analysis on Five European Countries
- Chapter 10: The Finances of European Households Throughout the Pandemic
- Chapter 11: The Covid-19 Crisis and Lockdown Measures: A Portrait from a Slum in Urban Argentina
- Index