nep-evo New Economics Papers
on Evolutionary Economics
Issue of 2007‒06‒02
four papers chosen by
Matthew Baker
City University of New York

  1. When do Thick Venture Capital Markets Foster Innovation? An Evolutionary Analysis By Luca Colombo; Herbert Dawid; Kordian Kabus
  2. High-Speed Natural Selection in Financial Markets with Large State Spaces By Fedyk, Yuriy; Walden, Johan
  3. Trust and Social Collateral By Markus Mobius; Adam Szeidl
  4. Intentions, Insincerity, and Prosocial Behavior By Amegashie, J.

  1. By: Luca Colombo (DISCE, Università Cattolica); Herbert Dawid (Bielefeld University); Kordian Kabus (Bielefeld University)
    Abstract: In this paper we examine the trade off between different effects of the availability of venture capital on the speed of technological progress in an industry. We consider an evolutionary industry simulation model based on Nelson and Winter (1982) where R&D efforts of an incumbent firm generate technological know-how embodied in key R&D employees, who might use this know-how to found a spinoff of the incumbent. Venture capital is needed to finance a spinoff, and therefore the expected profits from founding a spinoff depend on how easily venture capital can be acquired. Accordingly, thick venture capital markets might have two opposing effects. First, incentives of firms to invest in R&D might be reduced and, second, if spinoff formation results in technological spillovers between the parent firm and the spinoffs, the generation of spinoff firms might positively influence the future efficiency of the incumbent's innovation efforts. We study how this tradeoff influences the effect of venture capital on the innovation expenditures, speed of technological change and the evolution of industry concentration in several scenarios with different industry characteristics.
    Keywords: Venture Capital, Technological Progress, R&D Effort, Spinoff, Industry Evolution
    JEL: O30 J30 L20
    Date: 2007–03
    URL: http://d.repec.org/n?u=RePEc:ctc:serie3:ief0074&r=evo
  2. By: Fedyk, Yuriy (Olin School of Business); Walden, Johan (Haas School of Business)
    Abstract: Recent research has suggested that natural selection in financial markets may be a very slow process, taking hundreds of years. We show in a general equilibrium model that it may be much faster in markets with large state spaces. In many cases, the time it takes to wipe out irrational investors is inversely proportional to the number of stocks in the market, i.e., if it takes about 500 years with one stock, it takes about one year with 500 stocks. Thus, theoretically, natural selection can be very efficient even when there is high market uncertainty. The speed of the natural selection process is a known function of irrational investors' sentiment and of the real characteristics of the stock market. According to a calibration to U.S. stock data, it takes about fifty years for an irrational investor to be wiped out. This is in line with studies of individual investor underperformance.
    Keywords: Asset pricing; Market selection hypothesis; Natural selection
    JEL: G11 G12
    Date: 2007–04–15
    URL: http://d.repec.org/n?u=RePEc:hhs:sifrwp:0052&r=evo
  3. By: Markus Mobius; Adam Szeidl
    Abstract: This paper builds a theory of informal contract enforcement in social networks. In our model, relationships between individuals generate social collateral that can be used to control moral hazard when agents interact in a borrowing relationship. We define trust between two agents as the maximum amount that one can borrow from the other, and derive a simple reduced form expression for trust as a function of the social network. We show that trust is higher in more connected and more homogenous societies, and relate our trust measure to commonly used network statistics. Our model predicts that dense networks generate greater welfare when arrangements typically require high trust, and loose networks create more welfare otherwise. Using data on social networks and behavior in dictator games, we document evidence consistent with the quantitative predictions of the model.
    JEL: D02 D23
    Date: 2007–05
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:13126&r=evo
  4. By: Amegashie, J.
    Date: 2007
    URL: http://d.repec.org/n?u=RePEc:gue:guelph:2007-3&r=evo

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