nep-net New Economics Papers
on Network Economics
Issue of 2006‒09‒30
four papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Household Demand, Network Externality Effects and Intertemporal Price Discrimination By Winston T.H. Koh
  2. Legal vs Ownership Unbundling in Network Industries By CRÉMER, Jacques; CREMER, Helmuth; DE DONDER, Philippe
  3. Identification of Peer Effects Using Group Size Variation By Laurent Davezies; Xavier d’Haultfoeuille; Denis Fougère
  4. What do we know about Firms’ Research Collaboration with Universities? New Quantitative and Qualitative Evidence By Broström, Anders; Lööf, Hans

  1. By: Winston T.H. Koh (School of Economics and Social Sciences, Singapore Management University)
    Abstract: This paper examines the optimality of intertemporal price discrimination when network externality effects are present in the consumption of a durable good. We conduct our study in two settings. In a model with two household types, utilities are dependent on the cumulative proportion of households that have purchased the durable good. Next, in a model with a continuum of household types, we extend the analysis to the case where households consume both a durable good and a stream of non-durable goods. We show that in both settings, the presence of network externalities facilitates a sales strategy with intertemporal price discrimination.
    Keywords: intertemporal price discrimination, durable good, household demand, network externality
    JEL: D40
    Date: 2005–03
  2. By: CRÉMER, Jacques; CREMER, Helmuth; DE DONDER, Philippe
    Date: 2006–07
  3. By: Laurent Davezies (DEPP and CREST-INSEE); Xavier d’Haultfoeuille (ENSAE, CREST-INSEE and Université Paris I-Panthéon-Sorbonne); Denis Fougère (CNRS, CREST-INSEE, CEPR and IZA Bonn)
    Abstract: This paper considers the semiparametric identification of endogenous and exogenous peer effects based on group size variation. We show that Lee (2006)’s linear-in-means model is generically identified, even when all members of the group are not observed. While unnecessary in general, homoskedasticity may be required in special cases to recover all parameters. Extensions to asymmetric responses to peers and binary outcomes are also considered. Once more, most parameters are semiparametrically identified under weak conditions. However, recovering all of them requires more stringent assumptions. Eventually, we bring theoretical evidence that the model is more adapted to small groups.
    Keywords: social interactions, linear-in-means model, semiparametric identification
    JEL: C14 C21 C25
    Date: 2006–09
  4. By: Broström, Anders (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology); Lööf, Hans (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)
    Abstract: This chapter provides an integrated view of knowledge transfer between university and industry by combining two different approaches. First, we report results from an econometric analysis, where recent matching techniques are used on a dataset of 2,071 Swedish firms. Our findings from this analysis strongly suggest that university collaboration has a positive influence on the innovative activity of large manufacturing firms. In contrast, there appears to be an insignificant association between university collaboration and the average service firm’s innovation output. Second, in the pursuit of credible explanations for these findings, we apply a semi-structured interview methodology on 39 randomly selected firms collaborating with two research universities in Stockholm, Sweden. We identify three ideas for how collaboration may help firms become more innovative in the literature of innovation studies. In analysis of the interviews, we find very weak support for the first idea; that firms are able to exploit and market innovations originating in the university. The second idea – that firms improve their internal innovative capability by collaboration – is found to apply to about half of the investigated firms. Innovation efficiency gains in the form of reduced cost and risk for innovation projects, which is a third idea suggested by the literature, are also suggested to be a major factor behind firms’ benefits. Finally, we offer tentative explanations for the lack of measurable effects of collaboration for service firms.
    Keywords: University-Industry Link; Innovation; Technology transfer; R&D; Research collaboration
    JEL: C10 I23 O31 O33
    Date: 2006–08–28

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