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Aggregate vs Disaggregate Data Analysis — A Paradox in the Estimation of a Money Demand Function of Japan Under the Low Interest Rate Policy

  • Cheng Hsiao
  • Yan Shen
  • Hiroshi Fujiki

We use Japanese aggregate and disaggregate money demand data to show that conflicting inferences can arise. The aggregate data appears to support the contention that there was no stable money demand function. The disaggregate data shows that there was a stable money demand function. Neither was there any indication of the presence of a liquidity trap. Possible sources of discrepancy are explored and the diametrically opposite results between the aggregate and disaggregate analysis are attributed to the neglected heterogeneity among micro units. We provide necessary and sufficient conditions for the existence of cointegrating relations among aggregate variables when heterogeneous cointegration relations among micro units exist. We also conduct simulation analysis to show that when such conditions are violated, it is possible to observe stable micro relations, but unit root phenomenon among macro variables. Moreover, the prediction of aggregate outcomes, using aggregate data is less accurate than the prediction based on micro equations and policy evaluation based on aggregate data ignoring heterogeneity in micro units can be grossly misleading.

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File Function: First version, 2004
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Paper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 04.1.

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Length: 39 pages
Date of creation: Feb 2004
Date of revision:
Handle: RePEc:scp:wpaper:04-1
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Web page: http://www.usc.edu/dept/LAS/economics/IEPR/

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  1. Zellner, Arnold, 1996. "Models, prior information, and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 75(1), pages 51-68, November.
  2. Friedman, Milton & Schwartz, Anna J, 1991. "Alternative Approaches to Analyzing Economic Data," American Economic Review, American Economic Association, vol. 81(1), pages 39-49, March.
  3. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
  4. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1975. "Transcendental Logarithmic Utility Functions," American Economic Review, American Economic Association, vol. 65(3), pages 367-83, June.
  5. Fujiki, Hiroshi & Hsiao, Cheng & Shen, Yan, 2002. "Is There a Stable Money Demand Function under the Low Interest Rate Policy? A Panel Data Analysis," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 20(2), pages 1-23, April.
  6. Hashem Pesaran, M., 2003. "Aggregation of linear dynamic models: an application to life-cycle consumption models under habit formation," Economic Modelling, Elsevier, vol. 20(2), pages 383-415, March.
  7. Hausman, Jerry A, 1978. "Specification Tests in Econometrics," Econometrica, Econometric Society, vol. 46(6), pages 1251-71, November.
  8. Abadir, Karim & Talmain, Gabriel, 2002. "Aggregation, Persistence and Volatility in a Macro Model," Review of Economic Studies, Wiley Blackwell, vol. 69(4), pages 749-79, October.
  9. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
  10. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
  11. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  12. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  13. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  14. Pesaran, M Hashem & Pierse, Richard G & Kumar, Mohan S, 1989. "Econometric Analysis of Aggregation in the Context of Linear Prediction Models," Econometrica, Econometric Society, vol. 57(4), pages 861-88, July.
  15. Forni, Mario & Lippi, Marco, 1997. "Aggregation and the Microfoundations of Dynamic Macroeconomics," OUP Catalogue, Oxford University Press, number 9780198288008, March.
  16. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
  17. Bohn, Henning, 1995. "The Sustainability of Budget Deficits in a Stochastic Economy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(1), pages 257-71, February.
  18. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
  19. Goldfeld, Stephen M. & Sichel, Daniel E., 1990. "The demand for money," Handbook of Monetary Economics, in: B. M. Friedman & F. H. Hahn (ed.), Handbook of Monetary Economics, edition 1, volume 1, chapter 8, pages 299-356 Elsevier.
  20. Lewbel, Arthur, 1994. "Aggregation and Simple Dynamics," American Economic Review, American Economic Association, vol. 84(4), pages 905-18, September.
  21. Hsiao, Cheng, 1997. "Statistical Properties of the Two-Stage Least Squares Estimator under Cointegration," Review of Economic Studies, Wiley Blackwell, vol. 64(3), pages 385-98, July.
  22. Brewer, K. R. W., 1973. "Some consequences of temporal aggregation and systematic sampling for ARMA and ARMAX models," Journal of Econometrics, Elsevier, vol. 1(2), pages 133-154, June.
  23. Lewbel, Arthur, 1992. "Aggregation with Log-Linear Models," Review of Economic Studies, Wiley Blackwell, vol. 59(3), pages 635-42, July.
  24. Cheng Hsiao, 1997. "Cointegration and Dynamic Simultaneous Equations Model," Econometrica, Econometric Society, vol. 65(3), pages 647-670, May.
  25. Bennett T. McCallum & Marvin S. Goodfriend, 1987. "Money: Theoretical Analysis of the Demand for Money," NBER Working Papers 2157, National Bureau of Economic Research, Inc.
  26. Poirier, Dale J & Melino, Angelo, 1978. "A Note on the Interpretation of Regression Coefficients within a Class of Truncated Distributions," Econometrica, Econometric Society, vol. 46(5), pages 1207-09, September.
  27. Forni, Mario & Lippi, Marco, 1999. "Aggregation of linear dynamic microeconomic models," Journal of Mathematical Economics, Elsevier, vol. 31(1), pages 131-158, February.
  28. Stoker, Thomas M, 1993. "Empirical Approaches to the Problem of Aggregation Over Individuals," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1827-74, December.
  29. Anderson, T. W., 2002. "Reduced rank regression in cointegrated models," Journal of Econometrics, Elsevier, vol. 106(2), pages 203-216, February.
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