Reconciling Household Surveys and National Accounts Data Using a Cross Entropy Estimation Method
This paper presents an approach to reconciling household surveys and national accounts data. The problem is how to use the information provided by the national accounts data to re-estimate the household weights used in the survey so that the survey results are consistent with the aggregate data. The estimation approach uses an estimation criterion based on an entropy measure of information. The survey household weights are treated as a prior. New weights are estimated that are close to the prior and that are also consistent with the additional information. This approach is implemented to reconcile household survey data and macro data for Madagascar. The results indicate that the approach is powerful and flexible, supporting the efficient use of information from a variety of sources to reconcile data at different levels of aggregation in a consistent framework. Copyright 2003 by the International Association for Research in Income and Wealth.
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Volume (Year): 49 (2003)
Issue (Month): 3 (09)
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- Rutherford, Thomas F., 1995. "Extension of GAMS for complementarity problems arising in applied economic analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 19(8), pages 1299-1324, November.
- Pyatt, Graham, 1991. "SAMs, the SNA and National Accounting Capabilities," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 37(2), pages 177-98, June.
- van Tongeren, Jan W, 1986. "Development of an Algorithm for the Compilation of National Accounts and Related Systems of Statistics," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 32(1), pages 25-47, March.
- Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
- Zellner, A., 1988. "Optimal Information-Processing And Bayes' Theorem," Papers m8803, Southern California - Department of Economics.
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