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Distributed Lags, Aggregation and Compounding: Some Econometric Implications

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  • P. K. Trivedi

Abstract

This paper considers the aggregation of discrete distributed lags in the spirit of Houthakker and Johansen. Well-known distributed lag models in econometrics are shown to arise from aggregation across heterogeneous microeconomic units. The technique of analysis is based on the statistical theory of compound distributions. The paper goes on to consider how consistently estimated macro distributed lags may be decomposed into two components which represent, respectively, the microeconomic response and the heterogeneity in that response. Related problems of identification and estimation and the interpretive value of the approach are also discussed and illustrations provided.

Suggested Citation

  • P. K. Trivedi, 1985. "Distributed Lags, Aggregation and Compounding: Some Econometric Implications," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 52(1), pages 19-35.
  • Handle: RePEc:oup:restud:v:52:y:1985:i:1:p:19-35.
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    File URL: http://hdl.handle.net/10.2307/2297468
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    Cited by:

    1. Hamermesh, Daniel S, 1989. "Labor Demand and the Structure of Adjustment Costs," American Economic Review, American Economic Association, vol. 79(4), pages 674-689, September.
    2. Marcellino, Massimiliano, 2000. "Linear aggregation with common trends and cycles," Research in Economics, Elsevier, vol. 54(2), pages 117-131, June.
    3. 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.
    4. Balaguer, Jacint & Ripollés, Jordi, 2016. "Asymmetric fuel price responses under heterogeneity," Energy Economics, Elsevier, vol. 54(C), pages 281-290.
    5. Yan Shen & Cheng Hsiao & Hiroshi Fujiki, 2005. "Aggregate vs. disaggregate data analysis-a paradox in the estimation of a money demand function of Japan under the low interest rate policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 579-601.
    6. George C. Davis, 1999. "The science and art of promotion evaluation," Agribusiness, John Wiley & Sons, Ltd., vol. 15(4), pages 465-483.
    7. Scott Schuh, "undated". "Evidence on the Link between Firm-Level and Aggregate Inventory Behavior," Finance and Economics Discussion Series 1996-46, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
    8. Fratantoni, Michael & Schuh, Scott, 2003. "Monetary Policy, Housing, and Heterogeneous Regional Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 557-589, August.
    9. Hamermesh, Daniel S, 1992. "A General Model of Dynamic Labor Demand," The Review of Economics and Statistics, MIT Press, vol. 74(4), pages 733-737, November.
    10. Stephan von Cramon-Taubadel & Jens-Peter Loy & Jochen Meyer, 2006. "The impact of cross-sectional data aggregation on the measurement of vertical price transmission: An experiment with German food prices," Agribusiness, John Wiley & Sons, Ltd., vol. 22(4), pages 505-522.
    11. Forni, Mario & Lippi, Marco, 1999. "Aggregation of linear dynamic microeconomic models," Journal of Mathematical Economics, Elsevier, vol. 31(1), pages 131-158, February.
    12. Pesaran, M. H., 1999. "On Aggregation of Linear Dynamic Models," Cambridge Working Papers in Economics 9919, Faculty of Economics, University of Cambridge.
    13. Michael Fratantoni & Scott Schuh, 2000. "Monetary policy, housing investment, and heterogeneous regional markets," Working Papers 00-1, Federal Reserve Bank of Boston.

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