Index

Abstract

Citation (2023), "Index", Bandyopadhyay, S. and Rodríguez, J.G. (Ed.) Mobility and Inequality Trends (Research on Economic Inequality, Vol. 30), Emerald Publishing Limited, Bingley, pp. 267-275. https://doi.org/10.1108/S1049-258520230000030012 Publisher: Emerald Publishing Limited Copyright © 2023 Sanghamitra Bandyopadhyay and Juan Gabriel Rodríguez INDEX Absolute inequality, 140 Agriculture hukous, 188 Aid to Dependent Children (ADC), 77 Aid to Families with Dependent Children (AFDC), 77 Autonomous Community, 221–222, 231 Auxiliary database, 120–121 relation between age of respondent and wave to impute fathers’ income, 121 summary statistics of imputed fathers’ income for EPF waves, 122 Bad distributional inequality, 55–56 Bad income inequality measurement Canadian example, 56–61 distributional equality, 54–56 Gini coefficient and coefficient of variation, 52–54 Bad inequalities, 50–51, 56 Baseline regression, 249 Bayes’ theorem, 196 Between-category commonalities, 58 BGini, 52–53, 58–59 Blinder and Oaxaca approach, 209 breakdown of variance of logarithms of incomes, 215 decomposition, 188–189, 195 Canadian example, 56–61 coefficients of variation, 59 DCV Analysis, 61 DGI Analysis, 60 Gini Decomposition Analysis, 58 good and bad inequality analysis, 59 inequality modulated income well-being measures, 61 subgroup average income and category shares, 57 Capital income, 4–5, 9, 24, 76 Centro de Investigaciones Sociológicas (CIS), 110, 115 Children’s outcomes, 66, 70, 93 China analysing results of RIF Regressions, 195 comparing dispersion of logarithm of incomes in two groups, urban locals and migrants, 195–197 data sources and summary statistics, 189–191 determinants of logarithm of incomes, 191–195 differences between provinces in Mincerian earnings functions, 197–198 income inequality in urban areas in, 189 pattern of urban inequality changes in, 190–191 China Family Panel Study (CFPS), 188 China Household Income Project (CHIP), 185–186 data, 187 dataset, 189 survey, 187 Circumstances, 66, 77 as ‘parental effort’, 99, 108 variables, 79–80 Coefficient of variation, measuring good and bad inequality with, 52–54 Collective bargaining structures, 8 COME-HERE database, 220 Comparison theory, 110, 112–113, 125–126 Composition effects, 7, 210 Control variables, 117–118, 126, 245, 248–249, 264–265 Corporate debt markets, 244 Correlates of War (COW v3.0), 17 Covariates, descriptive trends of, 18–19 COVID-19 baseline regression, 249 crisis, 220 data, 245–247 descriptive statistics, 246 empirical results, 249 heterogeneity test in developed and developing countries, 249–252 methodology, 247–249 pandemic and economic stimulus policies, 245 robustness test, 252–253 Cross-border investment, 5, 35 Cross-country analysis, 151 Cross-National Equivalent File 1970–2016 (CNEF 1970–2016), 169 Cumulative distribution functions (CDFs), 175 d-inequality approach, 154 Data circumstance variables, 79–80 control variables, 117–118 cross-section statistics in United States and West Germany, 170 dependent variable, 114–115 generation process, 120 on income inequality, 10–12 intergenerational immobility, 75 intergenerational mobility and life satisfaction in Spain, 114 intergenerational mobility variables, 115–117 multifaceted approach to earnings mobility comparisons, 169–173 outcome variables, 76–79 pattern of urban inequality changes in China, 190–191 processing, 45 sources, 10–19, 189 Decile ratios, 10, 12, 14, 29, 45 Decomposition approach, 70, 74, 97 framework, 69–70 Degree of dominance, 176 Dependent variables, 19, 28, 114–115, 209 developing economies, 30 high-income OECD, 29 lagged, 20 Deprivation, 144 average, 144–145 society, 153, 156 Descriptive statistics, additional details in, 257–262 Descriptive trends of covariates, 18–19 of income inequality, 12–14 Determinants of logarithm of incomes, 191–195 regression results, 193 RIF regression results, 194 Developing countries, 26–27 dispersion of wages in, 5 education inequality in, 15 income inequality in, 6 Difference-in-differences framework (DID framework), 247–248 Directional mobility, 166, 168, 177 (see also Positional mobility) as earnings risk, 179–180 as equaliser of long-term earnings, 177–179 as individual earnings growth, 177 Dispersion of logarithm of incomes, 195–197 Dissociative theory, 126 Distributional coefficient of variation (DCV), 54–55 Distributional Equality, 54–56 Distributional Gini coefficient (DGI), 54–55 Distributions, 55, 123 Downward mobility, 110, 112–113, 123–129, 131 Earlier week (EW), 247, 257 Earnings, 170 mobility as earnings flux, 166, 169 mobility as earnings risk, 169, 179–180 Econometric method, 20–21 Economic inequality, 244 pandemic on, 245 Economic policies, 253 Economic relevance of finance, 6–7 Economic stimulus policies baseline regression, 249 data, 245–247 descriptive statistics, 246 empirical results, 249 heterogeneity test in developed and developing countries, 249–252 methodology, 247–249 robustness test, 252–253 Education, 7–9, 15–16, 31, 70, 75 Gini coefficient, 15–16 and income inequality, 30–34 Empirical analysis, 2, 10, 169, 173 data on income inequality, 10–12 descriptive trends of covariates, 18–19 descriptive trends of income inequality, 12–14 directional mobility, 177–180 drivers of income inequality, 15–18 positional mobility, 173–176 summary statistics of income inequality series, 12 Empirical results additional, 263–266 baseline regression with short-term effect, 263 short-term effect in developed countries, 265–266 Employment status, 110 Encuesta de Presupuestos Familiares (EPF), 111, 120 Equal pay, 51, 56 Equalising mobility, 178–179 Estimated Household Income Inequality (EHII), 10 Estimation methods, 10–11, 19–21, 81 sample, 45–46 EUROMOD, 221, 224, 231 European Centre for Disease Prevention and Control (ECDC), 246 European countries ranking, 151–155 Ebert’s index of inequality for sample of 36 countries, 155 pairwise comparisons, 152 Pearson correlation coefficients for different rankings of countries, 154 welfare and inequality indicators, 153 European Union (EU), 220 European Union Statistics on Income and Living Conditions (EU-SILC), 151 Eurostat, 151 Exogenous circumstances, 99 Family Identification Mapping System (FIMS), 76 Family income, 68, 76–77 Finance, economic relevance of, 6–7 Financialisation, 6, 17–18 Fiscal policy, 244–246 Fisher-type unit-root test, 21 Fit for purpose inequality measurement, 50 Fixed-effect estimation, 20 Foreign direct investment (FDI), 3 Foster–Greer–Thorbecke poverty measures (FGT poverty measures), 221 Functional income inequality, 9–10, 16 Gâteaux derivative, 206 Gender, 110 General least squares (GLS), 20 Generalised method of moments estimator (GMM estimator), 20 German labour market, 169 German Socio-Economic Panel (GSOEP), 166 Gini, 3, 15, 20 index, 139, 141–143, 151, 186, 199, 206–207 mean difference, 142 social welfare function, 141 transvariation measure, 54 Gini coefficients, 2, 11–12, 28, 58 measuring good and bad inequality with, 52–54 Globalisation, 5–6, 17 financial, 3 variables, 20 Good income inequality measurement Canadian example, 56–61 distributional equality, 54–56 Gini coefficient and coefficient of variation, 52–54 Good inequality, 50, 56 Governments redistributive policies, 9 Great Depression, 243 Gross domestic product (GDP), 16, 186, 245 Health policies, 9 Heckscher–Ohlin model, 5, 26 Hedonic adaptation theory, 110, 112 Heterogeneity baseline regression with cumulative effect, 250 cumulative effect in developed countries, 251–252 developing economies, 30 high-income OECD, 29 across income distribution, 28–30 test in developed and developing countries, 249–252 High-income countries, 5, 15, 145 High-income OECD countries, 34 High-income parents, 66 Household Budget Survey, 120 Household Registration System, 186 Human capital model, 7 Human resource categories, 58 Immobility, 69 measure, 167 Imputation, 121–122 Incidence, 229–231 Income (s), 70, 76, 166 concept, 169 determinants of logarithm of, 191–195 Gini coefficient, 10 Gini series, 12 income-based measures, 11 income-sharing unit, 45 mobility, 166 per capita, 141 survey data, 141 variation, 50 Income distribution, 151 comparison of, 143–145 heterogeneity across, 28–30 Income inequality, 50, 139, 150, 154 data on, 10–12 datasets, 10 descriptive trends of, 12–14 developing economies, 26 drivers of, 8, 15 economic relevance of finance, 6–7 education, 7–8, 15–16 education and income inequality, 30–34 effect, 7 empirical analysis, 10–19 estimation method, 19–21 financialisation, 17–18 functional and personal income inequality, 9–10 global sample, 24 globalisation, 5–6, 17 heterogeneity across income distribution, 28–30 high-income OECD, 25 labour market institutions and welfare state redistribution, 8–9, 18 regional heterogeneity, 34–38 results, 21–23 technological change, 4–5, 16–17 theory and empirical evidence, 3–4, 23–28 Index of inequality, 148 Individual earnings, 68, 166 growth, 168 individual labour earnings, 76 Inequality, 229–231 comparison of income distributions, 143–145 comparisons, 142–145 equivalence criterion, 146 European countries, 151–155 Gini index and social welfare, 142–143 inequality comparisons of distributions x and y using relative and absolute Gini indices, 144 inequality-neutral changes, 145 intermediate inequality comparisons, 145–151 mean income and Gini index for 36 European Countries in 2018, 160–161 modulated well-being measurement, 51 pairwise income differences for hypothetical distribution, 142 and social welfare, 142 values αx for sample of 36 Countries, 162–163 Inequality of opportunity (IOp), 66 accounting for direct influence of preceding circumstances, 73–74 accounting for preceding and mediating circumstances, 70–73 conventional definition of, 74 decomposition framework, 69–70 decomposition of IGE elasticity, 69 literature, 69, 79 on similarities between IGE and, 74–75 Influence function (IF), 206 Information and communication technology (ICT), 4 capital, 22 ICT-intensive branches, 4 Information technology (IT), 4 Institutionalised wage bargaining, 8 Instituto Nacional de Estadística (INE), 120 Intensity, 229–231 of poverty, 229 Intergenerational education (al) mobility, 117, 124 Intergenerational elasticity (IGE), 66, 69 decomposition analysis, 80, 97, 101 direct and indirect influence of preceding circumstances, 90–92 estimates, 80–92 for family income, 81, 88–89 for individual earnings, 69, 81, 86–87 IOp decomposition of IGE elasticity, 69–75 mediating circumstances, 82–84 preceding and mediating circumstances, 84–90 on similarities between IOp and, 74–75 Intergenerational immobility data, 75–80 IGE estimates and decomposition analysis, 80–92 IOp decomposition of IGE elasticity, 69–75 Intergenerational income mobility computation, 118 literature, 118 measurement, 115 Intergenerational mobility, 113 approaches, 110 auxiliary database, 120–121 data, 114–118 imputation, 121–122 intergenerational elasticity, 137 intergenerational income transition matrix, 122 literature review and hypothesis, 111–114 methods, 118 results, 125–130 in Spain, 122–124 summary statistics of control variables, 118 summary statistics of education of respondents and fathers, 118 summary statistics of household per capita adjusted income, 116 summary statistics of occupation of respondents and fathers, 117 transition matrix of occupation, 123 variables, 115–117 Intergenerational occupation mobility, 116 Intermediate inequality comparisons, 145–151 indices of intermediate inequality, 148–150 ranking procedure, 150–151 sharing inequality equivalence, 145–148 Intermediate inequality views, 140–141, 145, 150 International Food Policy Research Institute (IFPRI), 18 International Institute for Applied Systems Analysis and the Vienna Institute of Demography (IIASA/VID), 15 International Labour Organization (ILO), 2, 6 International Standard Classification of Education (ISCED), 15 IQ score, 92 Labour Contract Law, 188 Labour market institutions, 8–9, 18 direct equalising effect of, 9 Labour support regulations, 8 Later week (LW), 257 Least Absolute Shrinkage and Selection Operator (LASSO), 135 Least developed countries (LDCs), 4 Least-squares-dummy variable approach, 20 Life expectancy, 245, 264 Life satisfaction in Spain data, 114–118 and educational mobility, 129–130 and income mobility, 127 literature review and hypothesis, 111–114 methods, 118–122 and occupational mobility, 128–129 results, 125–130 Linear regression for outcome, 105–106 Logarithm of incomes determinants of, 191–195 dispersion of groups, 195–197 Logarithmic GDP per capita (LGDPpc), 245 Logit model, 211 Long-term earnings, mobility as equaliser of, 168–169, 177–179 Longitudinal survey on Rural Urban Migration in China (Longitudinal Survey on RUMIC), 188 Lorenz criterion, 146 Low-income countries, 46 Lower-middle-income cluster (LLM-income cluster), 34, 46 Luxembourg Income Study (LIS), 11 Machine learning, 110 algorithms, 111 Market capitalisation (Mcapit), 17–18, 20 Mean incomes, 140–141, 151 Mean squared errors (MSE), 135 Median incomes, 151 Mediating circumstances (C2), 66, 82–90 accounting for, 70–73 IGE decomposition, 83 inclusion of, 82 Medical risks, 82 Microsimulation analysis, 188 methodology, 221, 224–226 Migrants, 195–197 and total urban population, 212 Migration, 110 Mincerian earnings functions, 191, 197 differences between provinces in, 197–198 heterogeneity of labour inflow and outflow provinces, 198 Mincerian Equation, 120 Minimum income schemes in Spain change in general poverty measures, 229 inequality and redistributive effects, 227–231 inequality and redistributive power for simulated policies, 227 microsimulation methodology, 224–226 national arm to fight against poverty, 222–224 poverty effects, 229–231 results, 226–231 Minimum Insertion Income, 221 Minimum squared error (MSE), 119 Minimum vital income (MVI), 220–221 Minimum wages, 8 Mobility, 125 concepts, 166–167 directional, 168 as earnings risk or flux, 169 as equaliser of long-term earnings, 168–169 intensity, 126 measures, 167–169 positional, 167 variable, 125 Monetary policy, 245–246 Multi-source Gini observations (MS Gini observations), 11 Multifaceted approach to mobility analysis, 166 data, 169–173 empirical analysis, 173–180 mobility concepts and measures, 167–169 summary of multifaceted earnings mobility rankings, 182 National scheme, 222, 226, 228 Net inflows, 216 Non-agriculture hukous, 188 Non-conventional monetary policy tools, 244 Non-economic policies, 245, 253 Non-governmental organisations (NGOs), 224 Non-labour market attributes, 76 Non-linear decomposition, 98 Non-segmentation factor (NSF), 52 Occupation, 75 Occupational mobility, 123 matrixes, 116 Ordinary least squares (OLS), 20, 70, 119, 125, 207 Organisation for Economic Co-operation and Development (OECD), 2, 9, 220 Outcome variables, 76–79 Oxford COVID-19 Government Response Tracker Stringency Index, 245 Panel Study of Income Dynamics (PSID), 68, 75, 166 Parental education, 66, 90, 92 influence of, 92 Parental effort, circumstances as, 99 Parental income, 66–67, 69, 92 Parental occupation, 66 Pay-equity law, 56 Pearson correlation coefficients, 171 Penn World Tables (PWT), 16 Personal income inequality, 9–10 Pooled sample, summary statistics of, 214 Positional mobility, 166–167, 173–176 (see also Directional mobility) transition matrix of positional mobility for United States earnings, 173–175 transition matrix of positional mobility for West German earnings, 174–176 Positional mobility measure (Mp), 167 Poverty, 233 effects, 229–231 minimum guaranteed income based on household characteristics, 224 national arm to fight against, 222–224 Preceding circumstances (C1), 67, 72, 79, 84–90 accounting for direct influence of, 72–74 direct and indirect influence of, 90–92 influence of preceding circumstances not in IGE, 91 total influence of, 98 Private debt (PDebt), 6, 20 Probit model, 211 Public policy, 8 Public sector legislation, 56 Public spending policies, 35 Purchasing power standard (PPS), 151 Quantile regression approach, 98 Quantity-based measures of education, 34 Quasi-structural model, 70 R-square, 92 of linear regression, 66 Recentred influence function (RIF), 189, 206–208 analysing results of, 195 decompositions, 208–211 regressions, 208 RIF-OLS regression, 207 Regional heterogeneity, 34–38 Regional Minimum Income (RMI), 221, 232 Regional scheme (RMI), 226 Regressions, 192 equation, 46 Relative Gini index, 143 Relative income differentials, 140 Relative inequality, 140 Residents hukous, 188 Reverse causation, 46 Reweighting effect, 211 Robustness checks and extensions, 97 IGE decomposition, 97 non-linear decomposition, 98 robustness check for influence of C1, 104 robustness check–outcome averages and age cut-offs, 103 total influence of preceding circumstances, 98 treating circumstances as ‘parental effort’, 99 Robustness test, 252–253 in cumulative effect, 253 Rural migrants, 188 Rural–urban migration, 186 Rural–urban temporary migrants, 190 SEDLAC, 11 Shareholder approach, 7 Sharing inequality equivalence, 145–148 hypothetical example, 147 Single-source Gini (SS Gini), 12, 45 Social Inequality and Social Mobility in Spain’ module, 114 Social protection (SP), 20 spending, 27 Social security transfers, 27 Social transfers, 76 Social welfare, 141–143 evaluation functions, 141 Spain average monthly values of different incomes in, 237 changes in extreme poverty measures in, 240, 242 changes in general poverty measures in, 241 changes in inequality in, 238 changes in redistributive power in, 239 Spanish Independent Fiscal Responsibility Authority, 221 Spanish Public Accounts, 222 Specification error, 196 Standard inequality measures, 50 State Council, 188 State owned enterprise (SOE), 187 Statistics of Public Expenditure for Economic Development (SPEED), 18 Stolper–Samuelson theorem (SST), 5 Supplemental Nutrition Assistance Program (SNAP), 82 Technological change, 4–5, 8, 16–17 Temporary Assistance for Needy Families (TANF), 77 Tertiary education, 34 Time dependence concept, 171 Total Economy Database (TED), 17 Total factor productivity (TFP), 16, 20 Total family income, 76 Trace (T), 167 Trade openness, 8 Trade unions, 8 Transition matrix, 173 Treatment variable, 245 Two-Sample Two-Stage Least Squares (TSTSLS), 111, 119 Unconditional partial effect (UPE), 208 Unemployment, 8 UNESCO Institute of Statistics (UIS), 15 Unions, 8 United States, 167, 169, 171, 173–174, 176–177, 179 earnings mobility in, 166 Universal Basic Income, 222 University of Texas Inequality Project (UTIP), 10 UNU-WIDER World Income Inequality Database, Version 3. 4 (WIID3. 4), 11, 45 Urban China, 186 average income in, 190 income inequality in, 189 Urban inequality changes in China difference in average income at decile groups, 192 pattern of, 190–191 Urban locals, 195–197 Variance, 207 Wage effects, 7 Wealth, 93 Welfare state redistribution, 8–9, 18 West Germany, 167, 169, 173–174, 177 growth rate of earnings in, 170 inequality in, 171 WGini, 52 World Development Indicators (WDI), 17 World Income Inequality Database (WIID), 2 World regions, 2, 4, 10, 14, 34 World Wealth and Income Database (WID), 11 Zhejiang Province, 187 Book Chapters Prelims Chapter 1: Explaining Income Inequality Trends: An Integrated Approach Chapter 2: On Measuring ‘Good’ and ‘Bad’ Income Inequality Chapter 3: How Much of Intergenerational Immobility Can be Attributed to Differences in Childhood Circumstances? Chapter 4: Intergenerational Mobility and Life Satisfaction in Spain Chapter 5: ‘Mingling’ the Gini Index and the Mean Income to Rank Countries by Inequality and Social Welfare Chapter 6: A Multifaceted Approach to Earnings Mobility Comparisons Chapter 7: On Income Inequality in Urban Areas in China During the Period 2002–2013: Comparing the Case of Urban Locals With That of Rural Migrants Chapter 8: National Versus Regional: Distributional and Poverty Effects of Minimum Income Schemes in Spain Chapter 9: COVID-19 Pandemic and Economic Stimulus Policies: Evidence From 156 Economies Index