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

Author

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  • 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
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    References listed on IDEAS

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    1. Gómez-Salvador, Ramón & Westermann, Thomas & Lojschová, Adriana, 2011. "Household sector borrowing in the euro area - a micro data perspective," Occasional Paper Series 125, European Central Bank.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. repec:bla:revinw:v:48:y:2002:i:4:p:517-36 is not listed on IDEAS
    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.
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    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.

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    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

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