IDEAS home Printed from https://ideas.repec.org/p/lev/wrkpap/wp_885.html
   My bibliography  Save this paper

Quality of Statistical Match of Household Budget Survey and SILC for Turkey

Author

Listed:
  • Ozlem Albayrak
  • Thomas Masterson

Abstract

This paper presents the quality analysis of the statistical matching conducted for a research study on household consumption behavior, household indebtedness, and inequality for Turkey. The match has been done for four years (2005, 2008, 2009, and 2012) of Household Budget Surveys (HBS) and the Survey for Income and Living Conditions (SILC). The aim of the statistical matching is to transfer household expenditure data from the HBS to the SILC to create synthetic data sets that have information on household consumption expenditures as well as household income and indebtedness. We are following the methodology of constrained statistical matching, using estimated propensity scores developed in Kum and Masterson (2010) to produce the synthetic data sets that we need. The analysis shows that the match is of high quality.

Suggested Citation

  • Ozlem Albayrak & Thomas Masterson, 2017. "Quality of Statistical Match of Household Budget Survey and SILC for Turkey," Economics Working Paper Archive wp_885, Levy Economics Institute.
    • Handle: RePEc:lev:wrkpap:wp_885
    as

    Download full text from publisher

    File URL: http://www.levyinstitute.org/pubs/wp_885.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Holly Sutherland & Rebecca Taylor & Joanna Gomulka, 2002. "Combining Household Income and Expenditure Data in Policy Simulations," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(4), pages 517-536, December.
    2. Baris Ucar & Gianni Betti, 2016. "Longitudinal statistical matching: transferring consumption expenditure from HBS to SILC panel survey," Department of Economics University of Siena 739, Department of Economics, University of Siena.
    3. Ramon Gomez-Salvador & Adriana Lojschova & Thomas Westermann, 2011. "Household Sector Borrowing in the Euro Area: A Micro Data Persective," BCL working papers 58, Central Bank of Luxembourg.
    4. Hyunsub Kum & Thomas Masterson, 2008. "Statistical Matching Using Propensity Scores: Theory and Application to the Levy Institute Measure of Economic Wellbeing," Economics Working Paper Archive wp_535, Levy Economics Institute.
    5. Ramon Gomez-Salvador & Adriana Lojschova & Thomas Westermann, 2011. "Household Sector Borrowing in the Euro Area: A Micro Data Persective," BCL working papers 58, Central Bank of Luxembourg.
    6. Sutherland, Holly & Taylor, Rebecca & Gomulka, Joanna, 2002. "Combining Household Income and Expenditure Data in Policy Simulations," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(4), pages 517-536, December.
    7. Silvia Magri & Raffaella Pico & Cristiana Rampazzi, 2011. "Which households use consumer credit in Europe?," Questioni di Economia e Finanza (Occasional Papers) 100, Bank of Italy, Economic Research and International Relations Area.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chiara Elena Dalla & Menon Martina & Perali Federico, 2019. "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, vol. 35(3), pages 531-576, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cristina Borra & Almudena Sevilla & Jonathan Gershuny, 2013. "Calibrating Time-Use Estimates for the British Household Panel Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(3), pages 1211-1224, December.
    2. Mocetti, Sauro & Viviano, Eliana, 2017. "Looking behind mortgage delinquencies," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 53-63.
    3. Schaefer, Thilo & Peichl, Andreas, 2006. "Documentation FiFoSiM: integrated tax benefit microsimulation and CGE model," FiFo Discussion Papers - Finanzwissenschaftliche Diskussionsbeiträge 06-10, University of Cologne, FiFo Institute for Public Economics.
    4. Lamarche, Pierre, 2017. "Estimating consumption in the HFCS: Experimental results on the first wave of the HFCS," Statistics Paper Series 22, European Central Bank.
    5. Piotr Bialowolski & Dorota Weziak-Bialowolska, 2014. "The Index of Household Financial Condition, Combining Subjective and Objective Indicators: An Appraisal of Italian Households," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(1), pages 365-385, August.
    6. van Sonsbeek, J.M. & Gradus, R.H.J.M., 2006. "A microsimulation analysis of the 2006 regime change in the Dutch disability scheme," Economic Modelling, Elsevier, vol. 23(3), pages 427-456, May.
    7. Ochnio Luiza & Rokicki Tomasz & Koszela Grzegorz & Klepacki Bogdan, 2019. "Diversification of Lamb Meat Imports in EU Countries and its Trends," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(4), pages 96-111, December.
    8. Matěj Bajgar & Petr Janský & Klára Kalíšková, 2019. "The poor outside the lamplight: on the prevalence of poverty among population groups not included in household surveys," Post-Communist Economies, Taylor & Francis Journals, vol. 31(2), pages 181-199, March.
    9. Lenarčič, Črt, 2022. "Drivers of household arrears: an euro area country panel data analysis," MPRA Paper 114558, University Library of Munich, Germany.
    10. Ramon Gomez-Salvador & Adriana Lojschova & Thomas Westermann, 2011. "Household Sector Borrowing in the Euro Area: A Micro Data Persective," BCL working papers 58, Central Bank of Luxembourg.
    11. Luca Tasciotti & Natascha Wagner, 2018. "How Much Should We Trust Micro-data? A Comparison of the Socio-demographic Profile of Malawian Households Using Census, LSMS and DHS data," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(4), pages 588-612, September.
    12. Francesco D. d’Ovidio & Paola Perchinunno & Laura Antonucci, 2021. "Data Integration Techniques for the Identification of Poverty Profiles," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 515-531, August.
    13. McCarthy, Yvonne & McQuinn, Kieran, 2017. "Credit conditions in a boom and bust property market: Insights for macro-prudential policy," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 171-182.
    14. Pestel, Nico & Sommer, Eric, 2013. "Shifting Taxes from Labor to Consumption: Efficient, but Regressive?," IZA Discussion Papers 7804, Institute of Labor Economics (IZA).
    15. Petr Janský & Klára Kalíšková & Daniel Münich, 2016. "Does the Czech Tax and Benefit System Contribute to One of Europe’s Lowest Levels of Relative Income Poverty and Inequality?," Eastern European Economics, Taylor & Francis Journals, vol. 54(3), pages 191-207, May.
    16. Georgarakos, Dimitris & Popov, Alexander, 2024. "I (don’t) owe you: sovereign default and borrowing behavior," Working Paper Series 2893, European Central Bank.
    17. Merike Kukk, 2014. "Distinguishing the components of household financial wealth: the impact of liabilities on assets in Euro Area countries," Bank of Estonia Working Papers wp2014-2, Bank of Estonia, revised 10 Oct 2014.
    18. Immervoll, Herwig, 2002. "The distribution of average and marginal effective tax rates in European Union Member States," EUROMOD Working Papers EM2/02, EUROMOD at the Institute for Social and Economic Research.
    19. Annie Abello & Sharyn Lymer & Laurie Brown & Ann Harding & Ben Phillips, 2008. "Enhancing the Australian National Health Survey Data for Use in a Microsimulation Model of Pharmaceutical Drug Usage and Cost," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-2.
    20. David ARISTEI & Manuela Gallo, 2012. "The Drivers of Household Over-Indebtedness and Delinquency on Mortgage Loans: Evidence from Italian Microdata," Quaderni del Dipartimento di Economia, Finanza e Statistica 105/2012, Università di Perugia, Dipartimento Economia.

    More about this item

    Keywords

    Statistical Matching; Consumer Economics: Empirical Analysis; Personal Income; Wealth; and Their Distribution; Turkey;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:lev:wrkpap:wp_885. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Elizabeth Dunn (email available below). General contact details of provider: http://www.levyinstitute.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.