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Janina Engel
- 6 November 2023
- WORKING PAPER SERIES - No. 2865Details
- Abstract
- The Household Finance and Consumption Survey (HFCS) provides valuable information for the monetary policy and financial stability purposes. The dataset shows, however, inconsistencies with National Account (NtlA) statistics, as the aggregated HFCS micro data do usually not match the corresponding NtlA macro data. Therefore, we suggest a solution to close the gap via an optimization problem that aims at preserving for each wealth instrument the level of inequality measured by the Gini coefficient. In addition, a lower and an upper bound of inequality are derived, that can be reached by extreme allocations of the wealth discrepancies across the households. Finally, based on the German HFCS, we compare the findings with another approach suggested in the literature that uses a “multivariate calibration”. The comparison indicates that the multivariate calibration may reallocate households’ wealth beyond the observed discrepancies, thereby leading to Gini coefficients that exceed the analytically derived upper bound of inequality.
- JEL Code
- C46 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Specific Distributions, Specific Statistics
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
G51 : Financial Economics
N34 : Economic History→Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy→Europe: 1913- - Network
- Household Finance and Consumption Network (HFCN)
- 26 July 2022
- WORKING PAPER SERIES - No. 2687Details
- Abstract
- Distributional accounts for households enable measurement, study developments andidentify drivers of inequality. Distributional information on households’ wealth is availablefrom the Household Finance and Consumption Survey only for three points in time (2009 –2018), while aggregates are available quarterly. This paper presents a novel methodology forderiving quarterly distributional national wealth by (i) improving the alignment of surveyfieldwork periods with the national accounts’ dates; (ii) correcting for differences in severalconcepts; (iii) estimating missing wealthy households; (iv) developing time series; and (v)computing euro area aggregates. This paper finds an increase in the net wealth Gini of mosteuro area countries since 2009; that the richest 1% holds 28% of total net wealth, while thebottom 50% holds 4%; and that the net wealth of the top 1% has grown by almost 50%,compared to 28% for the remaining 99%, with a decrease in the bottom 20%.
- JEL Code
- C46 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Specific Distributions, Specific Statistics
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications
G51 : Financial Economics
N34 : Economic History→Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy→Europe: 1913-