nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2011‒08‒15
three papers chosen by
Rui Baptista
Technical University of Lisbon

  1. Are R&D subsidies provided optimally? Evidence from a simulated agency-firm stochastic dynamic game By Cerulli Giovanni
  2. Optimal Capital Structure and Industry Dynamics By Jianjun Miao
  3. Temporal and spatial relations between patents and scientific journal articles: the case of nanotechnologies By Finardi Ugo

  1. By: Cerulli Giovanni (Ceris - Institute for Economic Research on Firms and Growth, Rome, Italy)
    Abstract: By means of a simulated funding-agency/supported-firm stochastic dynamic game, this paper firstly shows that not only the level of R&D performed by firms is underprovided (as maintained by traditional literature on the subject), but also the level of the subsidy provided by the funding (public) agency (used to correct exactly for the corporate R&D shortage). This event is due to externalities generated by the agency-firm strategic relationship. Two versions of the model are simulated and compared: one assuming rival behaviors between companies and agency, and one associated to the Social-planner (or cooperative) strategy. Secondly, the paper looks at what “welfare” implications are associated to different degree of funding effect’s persistency. Three main conclusions are drawn: (i) the relative quota of subsidy to R&D is undersized in the rival compared to the Social-planner model; (2) the rivalry strategy generates distortions that favor the agency compared to firms; (3) when passing from less persistent to more persistent R&D additionality/crowding-out effect, the lower the bias the greater the variance is and vice versa. As for the management of R&D funding policies, all the elements favouring greater collaboration between agency and firm objectives can help current R&D support to reach its social optimum.
    Keywords: R&D subsidies, Rivalry vs. cooperation, Dynamic-stochastic games, Simulations
    JEL: O38 H2 C73 C63
    Date: 2010–12
  2. By: Jianjun Miao
    Abstract: This paper provides a competitive equilibrium model of capital structure and industry dynamics. In the model, firms make financing, investment, entry, and exit decisions subject to idiosyncratic technology shocks. The capital structure choice reflects the tradeoff between the tax benefits of debt and the associated bankruptcy and agency costs. The interaction between financing and production decisions influences the stationary distribution of firms and their survival probabilities. The analysis demonstrates that the equilibrium output price has an important feedback effect. This effect has a number of testable implications. For example, high growth industries have relatively lower leverage and turnover rates.
    Keywords: capital structure, agency costs, firm turnover, stationary equilibrium
    Date: 2011
  3. By: Finardi Ugo (Università di Torino - Dipartimento di Chimica I.F.M. and NIS - Centre of Excellence)
    Abstract: Patent citations have been widely used in order to study inter-technology and science-technology relations. The present work aims at: i) exploring time relations and distance between technical/innovative activities and scientific knowledge, using journal articles citations in patents as a proxy; ii) exploring the origin of the knowledge cited in patents. The study is performed on a field particularly relevant both on the scientific and technological side, that of nanosciences and nanotechnologies. In parallel a field less on the edge of research (polymers) is studied in order to compare results and shed better light on what is happening in nanotech. Studied items show a common behaviour and a higher rate of citations and a shorter time lag between citing patents and cited articles for nanotechnologies rather than for polymers. Knowledge cited in patents shows in many cases a common origin with that of citing documents. Conclusions on these behaviours are drawn.
    Keywords: Patent-research relations, Patent, Journal Article, Nanoscience, Nanotechnologies, Polymers, Technological trajectories, Data mining, Innovation, Knowledge diffusion
    JEL: L6 O31 O33
    Date: 2010–12

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