Uncertainty and economic growth in a stochastic R&D model

Fuke Wu, Xuerong Mao, Juliang Yin

Research output: Contribution to journalArticle

3 Citations (Scopus)
101 Downloads (Pure)

Abstract

The paper examines an R&D model with uncertainty from the population growth, which is a stochastic cooperative Lotka-Volterra system, and obtains a suciently condition for the existence of the globally positive solution. The long-run growth rate of the economic system is ultimately bounded in mean and fluctuation of its growth will not be faster than the polynomial growth. When uncertainty of the population growth, in comparison with its expectation, is suciently large, the growth rate of the technological progress andthe capital accumulation will converge to zero. Inversely, when uncertainty of the population growth is suciently small or its expected growth rate is suciently high, the economic growth rate will not decay faster than the polyno-mial speed. The paper explicitly computes the sample average of the growth rates of both the technology and the capital accumulation in time and compares them with their counterparts in the corresponding deterministic model.
Original languageEnglish
Pages (from-to)1306-1317
Number of pages11
JournalEconomic Modelling
Volume25
Issue number6
DOIs
Publication statusPublished - 3 Jun 2008

Keywords

  • volterra system
  • brownian motion
  • R&D model
  • polynomialgrowth
  • stochastic differential equation
  • Ito formula

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