High Inflation, Seasonal Commodities, And Annual Index Numbers
AbstractThis paper studies the problems of measuring economic growth under conditions of high inflation. Traditional bilateral index number theory implicitly assumes that variations in the price of acommodity within a period can be ignored. To justify this assumption under conditions ofhigh inflation, the accounting period must be shortened to a quarter, a month, or possibly a week. However, once the accounting period is less than a year, the problem of seasonal commodities isencountered; i.e., in some subannual periods, many seasonal commodities will be unavailable and hence the usual bilateral index number theory cannot be applied. The paper systematicallyreviews the problems of index number construction when there are seasonal commodities and highinflation. Various index number formulas are justified from the viewpoint of the economic approach to index number theory by making separability assumptions on consumers intertemporal preferences. Wefind that accurate economic measurement under conditions of high inflation is very complex.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Macroeconomic Dynamics.
Volume (Year): 2 (1998)
Issue (Month): 04 (December)
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- Robert C. Feenstra & Erwin W. Diewert, .
"Imputation and Price Indexes: Theory and Evidence from the International Price Program,"
Department of Economics
00-12, California Davis - Department of Economics.
- Robert Feenstra & Erwin Diewert, 2003. "Imputation and Price Indexes: Theory and Evidence from the International Price Program," Working Papers 012, University of California, Davis, Department of Economics.
- Carol Corrado & Wendy Dunn & Maria Otoo, 2006. "Incentives and prices for motor vehicles: what has been happening in recent years?," Finance and Economics Discussion Series 2006-09, Board of Governors of the Federal Reserve System (U.S.).
- W. Diewert & Alice Nakamura, 2003. "Index Number Concepts, Measures and Decompositions of Productivity Growth," Journal of Productivity Analysis, Springer, vol. 19(2), pages 127-159, April.
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