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Imputing consumption from income and wealth information

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  • Martin Browning
  • S¯ren Leth-Petersen

Abstract

We investigate the feasibility of deriving a measure of total expenditure at the household level from administrative micro-data on income and wealth. We use Danish administrative data that provides measures of disposable income and the holding of different assets at the end of the year. The ability to link the households in the 1994-6 Danish Expenditure Survey to their administrative data for the years around the survey year offers a unique possibility for constructing a measure of total expenditure and of checking directly on the reliability of the imputation. The results are promising. Copyright 2003 Royal Economic Society.

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Economic Journal.

Volume (Year): 113 (2003)
Issue (Month): 488 (06)
Pages: F282-F301

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Handle: RePEc:ecj:econjl:v:113:y:2003:i:488:p:f282-f301

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Cited by:
  1. Francesco Giavazzi & Michael F. McMahon, 2008. "Policy Uncertainty and Precautionary Savings," CEP Discussion Papers dp0863, Centre for Economic Performance, LSE.
  2. José Casado, 2011. "From income to consumption: measuring households partial insurance," Empirical Economics, Springer, vol. 40(2), pages 471-495, April.
  3. Richard Blundell & Luigi Pistaferri & Ian Preston, 2004. "Imputing consumption in the PSID using food demand estimates from the CEX," IFS Working Papers W04/27, Institute for Fiscal Studies.
  4. Bingley, Paul & Lanot, Gauthier, 2007. "Public pension programmes and the retirement of married couples in Denmark," Journal of Public Economics, Elsevier, vol. 91(10), pages 1878-1901, November.
  5. Thomas F. Crossley & Joachim K. Winter, 2014. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures National Bureau of Economic Research, Inc.
  6. Khorunzhina, Natalia, 2013. "Structural estimation of stock market participation costs," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2928-2942.
  7. S�ren Leth-Petersen, 2010. "Intertemporal Consumption and Credit Constraints: Does Total Expenditure Respond to an Exogenous Shock to Credit?," American Economic Review, American Economic Association, vol. 100(3), pages 1080-1103, June.
  8. George M. Korniotis & Alok Kumar, 2008. "Do behavioral biases adversely affect the macro-economy?," Finance and Economics Discussion Series 2008-49, Board of Governors of the Federal Reserve System (U.S.).
  9. Antoine Bozio & Guy Laroque & Cormac O'Dea, 2013. "Heterogeneity in time preference in older households," IFS Working Papers W13/02, Institute for Fiscal Studies.
  10. Salvador Navarro, 2011. "Using Observed Choices to Infer Agent's Information: Reconsidering the Importance of Borrowing Constraints, Uncertainty and Preferences in College Attendance," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20118, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  11. Martin Wittenberg, 2005. "Testing for a common latent variable in a linear regression: Or how to "fix" a bad variable by adding multiple proxies for it," SALDRU/CSSR Working Papers 132, Southern Africa Labour and Development Research Unit, University of Cape Town.

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