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Combining Household Income and Expenditure Data in Policy Simulations

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  • Sutherland, H.
  • Taylor, R.
  • Gomulka, J.

Abstract

Analysis of the distributional impact of fiscal policy proposals often requires information on household expenditures and incomes. It is unusual to have one data source with high quality information on both, and this problem is generally overcome with statistical matching of independent data sources. In this paper Grade Correspondence Analysis (GCA) is investigated as a tool to improve the matching process. An evaluation of alternative methods is conducted using datasets from the UK Family Expenditure Survey (FES), which is unusual in containing both income and expenditure at a detailed level of disaggregation. Imputed expenditures are compared with actual expenditures through the use of indirect tax simulations using the UK microsimulation model, POLIMOD. The most successful methods are then employed to enhance income data from the Family Resources Survey (FRS) and the synthetic dataset is used as a microsimulation model dataset.

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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0110.

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Length: 22
Date of creation: Jul 2001
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Handle: RePEc:cam:camdae:0110

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Related research

Keywords: statistical matching; clustering; income and expenditure micro-data; microsimulation;

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  1. Dayal N & Gomulka J & Mitton L & Sutherland H, 2000. "Enhancing Family Resources Survey income data with expenditure data from the Family Expenditure Survey: data comparisons," Microsimulation Unit Research Notes MU/RN/40, Microsimulation Unit at the Institute for Social and Economic Research.
  2. Taylor R & Sutherland H & Gomulka J, 2001. "Using POLIMOD to evaluate alternative methods of expenditure imputation," Microsimulation Unit Research Notes MU/RN/38, Microsimulation Unit at the Institute for Social and Economic Research.
  3. Redmond,Gerry & Sutherland,Holly & Wilson,Moira, 1998. "The Arithmetic of Tax and Social Security Reform," Cambridge Books, Cambridge University Press, number 9780521632249, April.
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Cited by:
  1. repec:ese:emodwp:em2-02 is not listed on IDEAS
  2. 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.
  3. Dayal N & Gomulka J & Mitton L & Sutherland H, 2000. "Enhancing Family Resources Survey income data with expenditure data from the Family Expenditure Survey: data comparisons," Microsimulation Unit Research Notes MU/RN/40, Microsimulation Unit at the Institute for Social and Economic Research.
  4. Andreas Peichl & Thilo Schaefer, 2009. "FiFoSiM - an integrated tax benefit microsimulation and CGE model for Germany," International Journal of Microsimulation, Interational Microsimulation Association, vol. 2(1), pages 1-15.
  5. Herwig Immervoll, 2003. "The Distribution Of Average And Marginal Effective Tax Rates In European Union Member States," Public Economics 0302005, EconWPA.
  6. Nico Pestel & Eric Sommer, 2013. "Shifting Taxes from Labor to Consumption: Efficient, but Regressive?," SOEPpapers on Multidisciplinary Panel Data Research 624, DIW Berlin, The German Socio-Economic Panel (SOEP).
  7. 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.
  8. Cristina Borra & Almudena Sevilla & Jonathan Gershuny, 2013. "Calibrating Time-Use Estimates for the British Household Panel Survey," Social Indicators Research, Springer, vol. 114(3), pages 1211-1224, December.

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