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Success breeds success. The dynamics of the innovation process


  • Flaig, Gebhard
  • Stadler, Manfred


This paper presents a dynamic random effects probit model for the realization of private firms’ product and process innovations. We estimate the model with panel data collected by the Ifo Institute in Munich. The data covers the period between 1979 and 1986 and includes 301 firms of the West German manufacturing sector. It turns out that firms’ probabilities of innovation depend on market structure, demand and cost expectations, unobserved heterogeneity, and realized innovations in the previous year. The positive significant influence of past innovations indicates that there is strong state dependence in the innovation process. This result supports the ’success breeds success’ hypothesis suggesting a positive impact of innovative success to further innovations in the following years.

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  • Flaig, Gebhard & Stadler, Manfred, 1994. "Success breeds success. The dynamics of the innovation process," Munich Reprints in Economics 20366, University of Munich, Department of Economics.
  • Handle: RePEc:lmu:muenar:20366

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    References listed on IDEAS

    1. Jeffrey I. Bernstein & M. Ishaq Nadiri, 1989. "Research and Development and Intra-industry Spillovers: An Empirical Application of Dynamic Duality," Review of Economic Studies, Oxford University Press, vol. 56(2), pages 249-267.
    2. König, Heinz & Laisney, François & Lechner, Michael & Pohlmeier, Winfried, 1993. "On the dynamics of process innovative activity: an empirical investigation using panel data," ZEW Discussion Papers 93-08, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    3. Kamien,Morton I. & Schwartz,Nancy L., 1982. "Market Structure and Innovation," Cambridge Books, Cambridge University Press, number 9780521293853, March.
    4. Laisney, Francois & Lechner, Michael & Pohlmeier, Winfried, 1992. "Innovation activity and firm heterogeneity: Empirical evidence from West Germany," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 301-320, December.
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