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on Technology and Industrial Dynamics |
| By: | Tseveen Gantumur; Andreas Stephan |
| Abstract: | In response to global market forces such as deregulation and globalization, technological change and digital convergence, the telecommunications in the 1990s witnessed an enormous worldwide round of Mergers & Acquisitions (M&A). Given both M&A and Innovation a major means of today’s competitive strategy development, this paper examines the innovation determinants of M&A activity and the consequences of M&A transactions on the technological potential and the innovation performance. We examine the telecommunications equipment industry over the period 1988-2002 using a newly constructed data set with firm-level data on M&A and innovation activity as well as financial characteristics. By implementing a counterfactual technique based on a matching propensity score procedure, the analysis not only controls for merger endogeneity and ex-ante observable firms characteristics but also takes account of unobserved heterogeneity. The study provides evidence that M&A realize significantly positive changes to the firm’s post-merger innovation performance. The effects of M&A on innovation performance are in turn driven by both the success in Research and Development (R&D) activity and the deterioration in internal technological capabilities at acquiring firms prior to a merger. |
| Keywords: | Mergers & Acquisitions, Innovation Performance, Telecommunications Equipment Industry. |
| JEL: | L63 O30 L10 |
| Date: | 2007–08 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2007-051&r=tid |
| By: | David Greenstreet |
| Abstract: | This paper develops a sequential learning estimator of production functions and productivity dynamics for unbalanced establishment panels. Extending an idea from the literature on dynamic industry models, establishments are uncertain about their own idiosyncratic productivities and update productivity beliefs using information revealed by their production experience. The estimator relies on the structure of this iterative learning process and thereby avoids placing any restriction on establishment strategic behavior. Consequently, the estimator is suitable for comparative studies of the behavioral sources of technological change across all types of industry. Estimation of productivity dynamics and of behavioral decision rules are separated into recursive stages. Using sequential learning estimates of productivity beliefs from the first stage, decision rules for exit, investment, and innovation effort can be estimated in a second stage. A test application with four Chilean industries confirms that the estimator produces plausible estimates with small standard errors. Decision rule estimates show that productivity beliefs affect investment and exit hazards in the expected direction. |
| Keywords: | Microeconomic Productivity Dynamics, Unbalanced Panels, Sequential Learning, Exit Hazard, Investment Rates, Chilean Manufacturing. |
| JEL: | D24 L25 C23 D83 L60 |
| Date: | 2007 |
| URL: | http://d.repec.org/n?u=RePEc:oxf:wpaper:345&r=tid |
| By: | Mary Benner; Joel Waldfogel |
| Abstract: | Patent data have been widely used in research on technological innovation to characterize firms' locations as well as the proximities among firms in knowledge space. Researchers could measure proximity among firms with a variety of measures based on patent class data, including Euclidean distance, correlation, and angle between firms' patent class distributions. Alternatively, one could measure proximity using overlap in cited patents. We point out that measures of proximity based on small numbers of patents are imprecisely measured random variables. Measures computed on samples with few patents generate both biased and imprecise measures of proximity. We explore the effects of larger sample sizes and coarser patent class breakdowns in mitigating these problems. Where possible, we suggest that researchers increase their sample sizes by aggregating years or using all of the listed patent classes on a patent, rather than just the first. |
| JEL: | O31 |
| Date: | 2007–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:13322&r=tid |
| By: | Andersson, Martin (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology); Johansson, Börje (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology) |
| Abstract: | This paper focuses on how characteristics of regions pertaining to local information about product varieties and markets as well as networks for the transmission of information about innovation opportunities influence the arrival of innovation ideas to existing and potential entrepreneurs. We formulate a model where entrepreneurs or innovating firms introduce new products in a quasi-temporal setting. Market conditions are characterized by monopolistic competition between varieties belonging to the same product group, in which there is entry and exit of varieties. Firms innovate in response to the arrival of innovation ideas. To realize these ideas firms have to make an R&D investment and a firm’s decision to export a variety to a new market is associated with a market channel investment. The theoretical model is used as a reference when formulating two regression models, with which we estimate factors that can explain the introduction of new export varieties by firms in different regional milieus. In one model we examine the emergence of new export firms, and in the second model we investigate the appearance of new export varieties. Results are consistent with the assumption that knowledge and information flows have a positive influence on the frequency of arrival of innovation ideas to firms. |
| Keywords: | innovation ideas; exports; entrepreneurship; location; knowledge spillovers |
| JEL: | O31 R11 R12 |
| Date: | 2007–08–08 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:cesisp:0095&r=tid |
| By: | Wilhelmsson, Mats (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology) |
| Abstract: | Innovation networking has become both more feasible with improved telecommunication and more important as it usually produces research of higher quality. However, the spatial distribution of academic networks and innovative networks are not uniform. Despite overwhelming evidence on the benefits of collaboration, patent data from 1994-2001 in Sweden demonstrate that innovation networks are not very common. In addition, the pattern of innovative networks is very fragmented. Our results indicate that innovation networks are more likely to exist in densely populated areas with a diversified industry. Face-to-face contacts in such areas seem to promote networking. Moreover, science-oriented industries appear to benefit more from proximity to universities when it comes to collaboration. However, the size of the market does not matter at all when it comes to collaboration, more important is the density and diversity of the market. |
| Keywords: | innovation; networks; patent; collaboration |
| JEL: | N34 O31 R11 |
| Date: | 2007–08–08 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:cesisp:0091&r=tid |
| By: | Andrew Atkeson; Ariel Burstein |
| Abstract: | We present a general equilibrium model of the decisions of firms to innovate and to engage in international trade. We use the model to analyze the impact of a reduction in international trade costs on firms' process and product innovative activity. We first show analytically that if all firms export with equal intensity, then a reduction in international trade costs has no impact at all, in steady-state, on firms' investments in process innovation. We then show that if only a subset of firms export, a decline in marginal trade costs raises process innovation in exporting firms relative to that of non-exporting firms. This reallocation of process innovation reinforces existing patterns of comparative advantage, and leads to an amplified response of trade volumes and output over time. In a quantitative version of the model, we show that the increase in process innovation is largely offset by a decline in product innovation. We find that, even if process innovation is very elastic and leads to a large dynamic response of trade, output, consumption, and the firm size distribution, the dynamic welfare gains are very similar to those in a model with inelastic process innovation. |
| JEL: | F1 L11 L16 O3 |
| Date: | 2007–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:13326&r=tid |