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The Luxembourg Household Finance and Consumption Survey (LU-HFCS): Introduction and Results

Author

Listed:
  • Thomas Y. Mathä
  • Alessandro Porpiglia
  • Michael Ziegelmeyer

Abstract

This paper introduces the Luxembourg Household Finance and Consumption Survey (LU-HFCS), presents its background and aim, the field phase, the data treatment, including editing, imputation, and anonymisation, and some basic descriptive findings. The estimated average (median) total net wealth of Luxembourg households is about EUR 733,000 (EUR 403,000) - an extremely high value by international standards, which is likely to be driven by high incomes and correspondingly high prices of real estate in Luxembourg. Average total gross income and total net wealth generally increase with household size, with age up to retirement age and with education. On average, total gross income of Luxembourg national and foreign households do not seem to differ significantly. This cannot be said for total net wealth and net real wealth, which, on average, is more than double as high for Luxembourg households than for foreign households.

Suggested Citation

  • Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2012. "The Luxembourg Household Finance and Consumption Survey (LU-HFCS): Introduction and Results," BCL working papers 73, Central Bank of Luxembourg.
    • Handle: RePEc:bcl:bclwop:bclwp073
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    File URL: https://www.bcl.lu/fr/Recherche/publications/cahiers_etudes/73/BCLWP073.pdf
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    References listed on IDEAS

    as
    1. The Eurosystem Household Finance and Consumption Network, 2009. "Survey data on household finance and consumption - research summary and policy use," Occasional Paper Series 100, European Central Bank.
    2. Joachim R. Frick & Markus M. Grabka & Eva M. Sierminska, 2007. "Representative Wealth Data for Germany from the German SOEP: The Impact of Methodological Decisions around Imputation and the Choice of the Aggregation Unit," Discussion Papers of DIW Berlin 672, DIW Berlin, German Institute for Economic Research.
    3. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, January.
    4. Michael Ziegelmeyer, 2013. "Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 49-76, January.
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    Cited by:

    1. Luca Marchiori & Olivier Pierrard, 2012. "LOLA 2.0: Luxembourg OverLapping generation model for policy Analysis," BCL working papers 76, Central Bank of Luxembourg.
    2. Yiwen Chen & Thomas Y. Mathä & Giuseppe Pulina & Barbara Schuster & Michael Ziegelmeyer, 2020. "The Luxembourg Household Finance Consumption Survey: Results from the third wave," BCL working papers 142, Central Bank of Luxembourg.
    3. Kukk, Merike, 2016. "How did household indebtedness hamper consumption during the recession? Evidence from micro data," Journal of Comparative Economics, Elsevier, vol. 44(3), pages 764-786.
    4. Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2012. "Income, Wealth and Consumption of Cross-Border Commuters to Luxembourg," BCL working papers 78, Central Bank of Luxembourg.
    5. Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2014. "Wealth differences across borders and the effect of real estate price dynamics: Evidence from two household surveys," BCL working papers 90, Central Bank of Luxembourg.
    6. Necker, Sarah & Ziegelmeyer, Michael, 2016. "Household risk taking after the financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 141-160.
    7. Michael Ziegelmeyer & Julius Nick, 2013. "Backing out of private pension provision: lessons from Germany," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(3), pages 505-539, August.
    8. Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2018. "Wealth differences across borders and the effect of real estate price dynamics: Evidence from two household surveys," Journal of Income Distribution, Ad libros publications inc., vol. 26(1), pages 1-35, March.
    9. Eurosystem Household Finance and Consumption Network, 2013. "The Eurosystem Household Finance and Consumption Survey - Methodological report," Statistics Paper Series 1, European Central Bank.
    10. Andreasch Michael & Lindner Peter, 2016. "Micro- and Macrodata: a Comparison of the Household Finance and Consumption Survey with Financial Accounts in Austria," Journal of Official Statistics, Sciendo, vol. 32(1), pages 1-28, March.
    11. Alessio Fusco & Philippe Kerm & A. Alieva & L. Bellani & F. Etienne-Robert & A.-C. Guio & I. Kyzyma & K. Leduc & P. Liégeois & M.N.P. Alperin & A. Reinstadler & E. Sierminska & D. Sologon & P. Thill &, 2013. "GINI Country Report: Growing Inequalities and their Impacts in Luxembourg," GINI Country Reports luxembourg, AIAS, Amsterdam Institute for Advanced Labour Studies.
    12. Anastasia Girshina & Thomas Y. Mathä & Michael Ziegelmeyer, 2017. "The Luxembourg Household Finance and Consumption Survey: Results from the 2nd wave," BCL working papers 106, Central Bank of Luxembourg.
    13. repec:jid:journl:y:2018:v:26:i:3:p:15-49 is not listed on IDEAS
    14. Michael Ziegelmeyer, 2015. "Other real estate property in selected euro area countries," BCL working papers 99, Central Bank of Luxembourg.
    15. Osier, Guillaume, 2016. "Unit non-response in household wealth surveys," Statistics Paper Series 15, European Central Bank.

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    More about this item

    Keywords

    household; survey; editing; multiple imputation; wealth; income;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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