 Dataset Design and Estimation MethodsChapter Chapter 6 in Innovation Networks in the German Laser Industry, 2015, pp 123-134 from Springer Abstract: Abstract The phenomenon under investigation guides the data collection process, the structural design of the dataset as well as the choice of empirical methods (Blossfeld et al. 2007, p. 4). The data collection process for the German laser industry database was described above. Now, we will turn our attention to the two latter points. Chapter 6 is divided into two sections: Section 6.1 presents the two compiled datasets. On the one hand, an event history dataset was constructed to analyze the propensity and timing of laser source manufacturers to cooperate and enter the German laser industry innovation network. On the other hand, a panel dataset was employed to analyze the determinants of firms in the German laser industry from various angles. Section 6.2 provides an overview and general discussion of estimation methods which were applied in Part IV of this book. We start with a brief discussion on non-parametric event history analysis models using continuous time, followed by an introduction of econometric models for panel count data. Keywords: Fixed Effect Model; Cooperation Event; Panel Count Data; Random Effect Estimator; Panel Data Method (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:eccchp:978-3-319-07935-6_6 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-07935-6_6 Access Statistics for this chapter More chapters in Economic Complexity and Evolution from Springer |
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