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Some New Evidence on the Timing of Consumption Decisions and on Their Generating Process


  • Ermini, Luigi


While quarterly consumption data are known to be well fitted by an integrated first-order moving average process--IMA(1, 1)--with a positive coefficient, monthly consumption data are found to be well fitted by an IMA(1, 1) process with a negative coefficient. Without measurement errors, one implication is that, if R. Hall's (1978) random walk model of consumption behavior is true, then the agents' decision interval must be greater than a month. (In particular, this evidence rejects the possibility of continuously taken decisions.) Another implication is that, if consumption decisions are generated by an IMA(1, 1) process at intervals shorter than a month, the coefficient must be negative. The paper also discusses the case of monthly data corrupted by measurement errors. Copyright 1989 by MIT Press.

Suggested Citation

  • Ermini, Luigi, 1989. "Some New Evidence on the Timing of Consumption Decisions and on Their Generating Process," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 643-650, November.
  • Handle: RePEc:tpr:restat:v:71:y:1989:i:4:p:643-50

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    References listed on IDEAS

    1. Balassa, Bela, 1978. "Exports and economic growth : Further evidence," Journal of Development Economics, Elsevier, vol. 5(2), pages 181-189, June.
    2. Orley Ashenfelter & David Card, 1982. "Time Series Representations of Economic Variables and Alternative Models of the Labour Market," Review of Economic Studies, Oxford University Press, vol. 49(5), pages 761-782.
    3. Feder, Gershon, 1983. "On exports and economic growth," Journal of Development Economics, Elsevier, vol. 12(1-2), pages 59-73.
    4. Leamer, Edward E., 1985. "Vector autoregressions for causal inference?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 22(1), pages 255-304, January.
    5. Raymond Vernon, 1966. "International Investment and International Trade in the Product Cycle," The Quarterly Journal of Economics, Oxford University Press, vol. 80(2), pages 190-207.
    6. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    7. Jagdish N. Bhagwati, 1978. "Anatomy and Consequences of Exchange Control Regimes," NBER Books, National Bureau of Economic Research, Inc, number bhag78-1, January.
    8. Kunst, Robert & Neusser, Klaus, 1986. "A forecasting comparison of some var techniques," International Journal of Forecasting, Elsevier, vol. 2(4), pages 447-456.
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    Cited by:

    1. Jeffrey C. Fuhrer, 1998. "An Optimising Model for Monetary Policy Analysis: Can Habit Formation Help?," RBA Research Discussion Papers rdp9812, Reserve Bank of Australia.
    2. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    3. Malgarini, Marco & Margani, Patrizia, 2005. "Psychology, consumer sentiment and household expenditures: a disaggregated analysis," MPRA Paper 42443, University Library of Munich, Germany.
    4. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310 Edward Elgar Publishing.
    5. Wu, C.C. & Lee, Jack C., 2007. "Estimation of a utility-based asset pricing model using normal mixture GARCH(1,1)," Economic Modelling, Elsevier, vol. 24(2), pages 329-349, March.
    6. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
    7. Hari Luitel & Mehmet Tosun, 2014. "A reexamination of state fiscal health and amnesty enactment," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 21(5), pages 874-893, October.

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