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Measurement Error and the Flow of Funds Accounts: Estimates of HouseholdAsset Demand Equations


  • Carl E. Walsh


In the household sector of the Flow of Funds Accounts, the difference between net acquisition of financial assets and net financial savings is equal to a statistical discrepancy which is often quite large relative to the reported changes in asset holdings. This means that the budget restrictions emphasized in the Brainard-Tobin approach to specifying asset demand equations are not satisfied by the data commonly used to estimate such equations. The view adopted in this paper is that the statistical discrepancy should be thought of as resulting from measurement error in the Flow of Funds data. By imposing a structure on the measurement error, a consistent estimator is developed and used to estimate asset demand equations for the household sector. The demand equations are similar in specification to those used by others so that the results allow a direct assessment of the effects of alternative treatments of the statistical discrepancy. The empirical results suggest that qualitative conclusions about the effects of financial flows and interest rates on asset demands are not affected by the way the statistical discrepancy is treated. Quantitative conclusions are, however, affected.

Suggested Citation

  • Carl E. Walsh, 1981. "Measurement Error and the Flow of Funds Accounts: Estimates of HouseholdAsset Demand Equations," NBER Working Papers 0732, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:0732
    Note: ME

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    References listed on IDEAS

    1. Pagan, Adrian, 1973. "Efficient estimation of models with composite disturbance terms," Journal of Econometrics, Elsevier, vol. 1(4), pages 329-340, December.
    2. Saito, Mitsuo, 1977. "Household Flow-of-Funds Equations: Specification and Estimation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 9(1), pages 1-20, February.
    3. Hsiao, Cheng, 1976. "Identification and Estimation of Simultaneous Equation Models with Measurement Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 17(2), pages 319-339, June.
    4. Backus, David, et al, 1980. "A Model of U.S. Financial and Nonfinancial Economic Behavior," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 12(2), pages 259-293, Special I.
    5. Barten, A. P., 1969. "Maximum likelihood estimation of a complete system of demand equations," European Economic Review, Elsevier, vol. 1(1), pages 7-73.
    6. Backus, David & Purvis, Douglas, 1980. "An Integrated Model of Household Flow-of-Funds Allocations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 12(2), pages 400-421, Special I.
    7. Fair, Ray C, 1970. "The Estimation of Simultaneous Equation Models with Lagged Endogenous Variables and First Order Serially Correlated Errors," Econometrica, Econometric Society, vol. 38(3), pages 507-516, May.
    8. V. Vance Roley, 1980. "A Disaggregated Structural Model of the Treasury Securities, Corporate Bond, and Equity Markets: Estimation and Simulation Results," NBER Technical Working Papers 0007, National Bureau of Economic Research, Inc.
    9. Denton, Frank T., 1978. "Single-equation estimators and aggregation restrictions when equations have the same sets of regressors," Journal of Econometrics, Elsevier, vol. 8(2), pages 173-179, October.
    10. Paul Wachtel, 1972. "A Model of Interrelated Demand for Assets by Households," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 1, number 2, pages 129-140 National Bureau of Economic Research, Inc.
    11. Berndt, Ernst R & Savin, N Eugene, 1975. "Estimation and Hypothesis Testing in Singular Equation Systems with Autoregressive Disturbances," Econometrica, Econometric Society, vol. 43(5-6), pages 937-957, Sept.-Nov.
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