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"S-shaped" Economic Dynamics. The Logistic and Gompertz curves generalized

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Author Info
Gloria Jarne, Julio Sánchez-Chóliz, Francisco Fatás-Villafranca
Abstract

Over the years "S-shaped" evolutions have regularly been incorporated in economic models, and indeed in those of other sciences, by way of the logistic or Gompertz equations. However, both equations have noteworthy shortcomings when fitting some empirical features of economic growth: the logistic equation is characterized by strong symmetries, whilst the growth rate is decreasing in the case of both equations. In this paper, we have set out to overcome these limitations by defining a family of unimodal differential equations which includes the logistic and Gompertz equations and covers practically the whole spectrum of sigmoid curves. We have identified three sub-families of these differential equations, all offering good mathematical expressions. Using these, it is possible to obtain an acceptable fit for any S-shaped curve. The results are applied to various economic series, successfully replicating certain well-known economic phenomena.

Mathematical analysis: Unimodal differential equations. Empirical analysis: Non-linear adjustment to the USA Capacity Index time series.

We have defined a family of unimodal differential equations covering practically the whole spectrum of "S-shaped" curves. We have selected three sub-families mathematically manageable and which depend on five easily interpretable parameters. It is shown that any one of them may adequately replicate empirically relevant S-shaped phenomena (overcoming certain limitations of the logistic and Gompertz curves). In order to assess the power of these families to replicate real economic events we have calculate the fit with the USA Capacity Index for Total Industry (1967/02-2003/01) and the US Capacity Index series for Durables, Manufacturing, Computers and Primary processing. Then, we have drawn conclusions on capital accumulation and investment patterns in the period that would appear to be in line with recent historical facts in the US economy.

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Article provided by IFReDE - Université Montesquieu Bordeaux IV in its journal The Electronic Journal of Evolutionary Modeling and Economic Dynamics.

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Handle: RePEc:jem:ejemed:1048

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Related research
Keywords: "S-shaped" curves; Logistic equation; Gompertz equation; Economic growth;

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Find related papers by JEL classification:
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General
O39 - Economic Development, Technological Change, and Growth - - Technological Change - - - Other

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  3. Aoki, Masanao & Yoshikawa, Hiroshi, 2002. "Demand saturation-creation and economic growth," Journal of Economic Behavior & Organization, Elsevier, vol. 48(2), pages 127-154, June. [Downloadable!] (restricted)
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  6. Foster, John & Wild, Phillip, 1999. "Econometric Modelling in the Presence of Evolutionary Change," Cambridge Journal of Economics, Oxford University Press, vol. 23(6), pages 749-70, November.
  7. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October. [Downloadable!] (restricted)
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