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Peter Lindner

1 April 2014
WORKING PAPER SERIES - No. 1663
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Abstract
We study the link between household structure and cross country differences in the wealth distribution using a recently compiled data set for the euro area (HFCS). We estimate counterfactual distributions using non-parametric re-weighting to examine the extent to which differences in the unconditional distributions of wealth across euro area countries can be explained by differences in household structure. We find that imposing a common household structure has strong effects on both the full unconditional distributions as well as its mappings to different inequality measures. For the median 50% of the differences are explained for Austria, 15% for Germany, 25% for Italy, 14% for Spain and 38% for Malta. For others as Belgium, France, Greece, Luxembourg, Portugal, Slovenia and Slovakia household structure masks the differences to the euro area median and Finland and the Netherlands change their position from below to above the euro area median. The impact on the mean and percentile ratios is similarly strong and varies with regard to direction and level across countries and their distributions. We can confirm the finding of Bover (2010) that the effect on the Gini is somewhat less pronounced, but might mask relevant information by being a net effect of different accumulated effects along the distribution. Country rankings based on almost all of these measures are severely affected alluding to the need for cautious interpretation when dealing with such rankings. Furthermore, the explanatory power of household structure changes along the net wealth distribution. Therefore we argue for more flexible controls for household structure. We provide such a set of controls to account for household type fixed effects which are based on the number of household members as well as possible combinations of age categories and gender.
JEL Code
D30 : Microeconomics→Distribution→General
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
Network
Household Finance and Consumption Network (HFCN)
Annexes
1 April 2014
ANNEX
13 May 2014
WORKING PAPER SERIES - No. 1673
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Abstract
This paper compares the survey results on savings deposits and estimates on total financial assets from the Household Finance and Consumption Survey (HFCS) in Austria with administrative records from the national accounts for the household sector. The micro data newly generated through the HFCS and the detailed (internally available) breakdowns of savings deposits in the existing macro data (Financial Accounts) lend themselves to a more in-depth analysis of the similarities and differences in these two sources than what has been done in the literature so far. Cross-checking the data shows that the HFCS-based aggregate estimates differ from the financial accounts data, which is line with evidence from the literature, but additionally the paper adds to the literature that the underlying patterns have been captured adequately by the survey at the micro level. Moreover, a simulation based on the HFCS data serves to demonstrate the effect that the inclusion of savings deposits in the most affluent tail of the distribution has on common statistics. Undercoverage above all of the upper deposit ranges suggests an underestimation or bias in the statistics. This underestimation, however, can be shown to be relatively minor, in particular in the case of robust statistical measures such as the median or percentile ratios.
JEL Code
C80 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→General
D30 : Microeconomics→Distribution→General
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
Network
Household Finance and Consumption Network (HFCN)
20 August 2014
WORKING PAPER SERIES - No. 1722
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Abstract
Using the first wave of the Eurosystem Household Finance and Consumption Survey (HFCS), a large micro-level dataset on households
JEL Code
D1 : Microeconomics→Household Behavior and Family Economics
D3 : Microeconomics→Distribution
Network
Household Finance and Consumption Network (HFCN)
18 April 2019
WORKING PAPER SERIES - No. 2270
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Abstract
We use cross-country microdata to analyse the risk taking of households in Europe and the US. Concerning the extensive as well as the intensive margin of risky assets, European households differ substantially from US households; but also inside Europe we document substantial differences. Furthermore, average risk aversion is strongly correlated with the share of households holding risky assets across countries. We decompose the observed differences into two parts. A part explainable by household characteristics as well as differences in risk aversion and a remainder. We employ the unexplained part resulting from our microeconometric decomposition analysis together with country-level variables on the economic environment to relate observed differences in risky asset holdings to institutional ones. We find that institutional differences such as shareholder protection are strongly correlated with the unexplainable differences with regard to holdings of risky assets.
JEL Code
D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
D14 : Microeconomics→Household Behavior and Family Economics→Household Saving; Personal Finance
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
Network
Household Finance and Consumption Network (HFCN)
2 October 2020
WORKING PAPER SERIES - No. 2474
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Abstract
Using a dedicated set of questions in the 2014 Luxembourg Household Finance and Consumption Survey (LU-HFCS), we show that a substantial share of households contributes their own labour to the acquisition of their main residence. These contributions help households faced with credit constraints, since they reduce the need for external financing. We develop a simple theoretical model and show that own labour contributions decrease with the level of financial resources available, while they increase with the mortgage interest rate. These theoretical results are supported by empirical analysis, which also shows that own labour contributions vary by household characteristics (age, gender, profession) and by type of dwelling (house, apartment).
JEL Code
D14 : Microeconomics→Household Behavior and Family Economics→Household Saving; Personal Finance
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
R21 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Household Analysis→Housing Demand
Network
Household Finance and Consumption Network (HFCN)
5 January 2021
STATISTICS PAPER SERIES - No. 39
Details
Abstract
This study examines interviewer effects on household non-response in the three waves of the Household Finance and Consumption Survey (HFCS) in Austria. We exploit the rare opportunity to combine this wealth survey data, accompanied by a large set of paradata on all households including non-respondents, with two other sets of data, namely (i) an administrative dataset on income and (ii) a survey on interviewer characteristics. These characteristics include measures of the social background, income and wealth, and personality traits of the interviewers. Our multilevel benchmark model shows that the proportion of the variation in response behaviour that can be explained at the interviewer level has decreased from about one-third in the first wave of the HFCS to about 7% in the third wave. Using further specifications of our multilevel model we find that the following interviewer characteristics are positively related to household response: having a university degree, being married, being a homeowner and having a less open personality. At the same time, we find a highly significant negative relationship between survey participation and mean wage in the household’s municipality
JEL Code
X01 :
X02 :
X03 :