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Preparation of Data from the New SOEP Consumption Module: Editing, Imputation, and Smoothing

Author

Listed:
  • Jan Marcus
  • Rainer Siegers
  • Markus M. Grabka

Abstract

This documentation describes the data preparation of the new consumption module in the German Socio-Economic Panel Study (SOEP) and introduces the content and structure of the generated dataset "hconsum." In 2010, the SOEP for the first time included a detailed consumption module in the household questionnaire. This documentation discusses several methodological challenges of the new module and suggests possible remedies. The methodological challenges include inconsistencies between monthly and annual consumption information, missing values, and a high incidence of heaping.

Suggested Citation

  • Jan Marcus & Rainer Siegers & Markus M. Grabka, 2013. "Preparation of Data from the New SOEP Consumption Module: Editing, Imputation, and Smoothing," Data Documentation 70, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwddc:dd70
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    File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.428029.de/diw_datadoc_2013-070.pdf
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    References listed on IDEAS

    as
    1. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    2. McDonald, James B, 1984. "Some Generalized Functions for the Size Distribution of Income," Econometrica, Econometric Society, vol. 52(3), pages 647-663, May.
    3. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
    4. Royston, Patrick & White, Ian R., 2011. "Multiple Imputation by Chained Equations (MICE): Implementation in Stata," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i04).
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Heinz-Herbert Noll & Stefan Weick, 2015. "Consumption expenditures and subjective well-being: empirical evidence from Germany," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 62(2), pages 101-119, June.
    2. repec:bla:revinw:v:63:y:2017:i:3:p:542-563 is not listed on IDEAS
    3. Groß, Marcus & Rendtel, Ulrich, 2015. "Kernel density estimation for heaped data," Discussion Papers 2015/27, Free University Berlin, School of Business & Economics.
    4. Loeffler, Max & Peichl, Andreas & Pestel, Nico & Siegloch, Sebastian & Sommer, Eric, 2014. "Documentation IZA?MOD v3.0: The IZA Policy Simulation Model," IZA Discussion Papers 8553, Institute for the Study of Labor (IZA).
    5. Lamarche, Pierre, 2017. "Estimating consumption in the HFCS: Experimental results on the first wave of the HFCS," Statistics Paper Series 22, European Central Bank.
    6. Stefan Bach & Martin Beznoska & Viktor Steiner, 2016. "An Integrated Micro Data Base for Tax Analysis in Germany," Data Documentation 86, DIW Berlin, German Institute for Economic Research.
    7. Nico Pestel & Eric Sommer, 2017. "Shifting Taxes from Labor to Consumption: More Employment and more Inequality?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(3), pages 542-563, September.

    More about this item

    Keywords

    SOEP; consumption; heaping; imputation; generalized beta of the second kind;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D30 - Microeconomics - - Distribution - - - General
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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