208 research outputs found
Supplementary data and research materials for "Early-stage spatial disease surveillance of novel SARS-CoV-2 variants of concern in Germany with crowdsourced data"
No full textThis folder contains study data, protocols and STATA programming codes to replicate the empirical analysis presented in:"Early-stage spatial disease surveillance of novel SARS-CoV-2 variants of concern in Germany with crowdsourced data"by Timo Mitze and Johannes Rode.Accepted for publication in "Scientific Reports" (with DOI: 10.1038/s41598-021-04573-1)Please see the README file before using the study data and replication codes. In the case of questions contact: Timo Mitze ([email protected])</div
sj-docx-1-iei-10.1177_14657503241248284 - Supplemental material for Resilience of rural businesses in times of crisis: Firm survival during the COVID-19 pandemic in Finland
No full textSupplemental material, sj-docx-1-iei-10.1177_14657503241248284 for Resilience of rural businesses in times of crisis: Firm survival during the COVID-19 pandemic in Finland by Timo Mitze and Teemu Makkonen in The International Journal of Entrepreneurship and Innovation</p
Supplementary data and research materials for "Geopolitical conflicts, sanctions, and international knowledge flows: EU-Russia collaboration during the Ukraine crisis"
No full textZIP-File with study data, STATA replication codes, and supplementary research materials for:
"Geopolitical conflicts, sanctions, and international knowledge flows: EU-Russia collaboration during the Ukraine crisis"
by Teemu Makkonen and Timo Mitze (2023)
published in: The World Economy.
Contact: [email protected]</p
Supplemental Material, IRSR_Online_Appendix - Public Research, Local Knowledge Transfer, and Regional Development: Insights from a Structural VAR Model
No full textSupplemental Material, IRSR_Online_Appendix for Public Research, Local Knowledge Transfer, and Regional Development: Insights from a Structural VAR Model by Jonathan Eberle, Thomas Brenner and Timo Mitze in International Regional Science Review</p
Supplementary data and research materials for "SARS-CoV-2 outbreaks on Danish mink farms and mitigating public health interventions"
No full textThis 7-ZIP file contains data and Stata codes to replicate the results presented in:"SARS-CoV-2 outbreaks on Danish mink farms and mitigating public health interventions"written by Torben Dall Schmidt and Timo Mitze (2021).Accepted for publication in: European Journal of Public HealthArticle DOI: 10.1093/eurpub/ckab182<br
Modeling interregional research collaborations in German biotechnology using industry directory data
No full textThis article describes a data set to map and model research collaborations in German biotechnology. Underlying micro-data for firms and institutions in the biotech sector together with information on their research collaboration partners have been extracted from a commercial industry directory, the BIOCOM Year and Address book, for 2005 and 2009. The data have been processed and aggregated to the level of NUTS3 regions. This core data set has been linked to regional covariates which measure the regional endowment with biotech-related research capacities, sector-specific S&T policy support and the strength of a region׳s overall local innovation system. The full data set, which is attached to this article, offers applied researchers an alternative source of information for empirical analyses of knowledge flows in research networks and for studying their determinants. Potential fields of application include social network and regression analysis. First empirical results are reported in “Determining factors of interregional research collaboration in Germany׳s biotech network: Capacity, proximity, policy?” (Mitze and Strotebeck, 2018) and “Centrality and get-richer mechanisms in interregional knowledge networks” (Mitze and Strotebeck, 2018). Keywords: Biotechnology, Research collaborations, Industry directory data, Regional innovation system, S&T polic
Supplementary data and research materials for "Can large-scale RDI funding stimulate post-crisis recovery growth? Evidence for Finland during COVID-19"
No full textThis project folder contains supplementary data files and software codes (for STATA) to replicate the estimation results documented in:
"Can large-scale RDI funding stimulate post-crisis recovery growth? Evidence for Finland during COVID-19"
by Mitze, T. and Makkonen, T. (2022).
A previous working paper version of this research can be found in the arXiv repository with ID: arXiv:2112.11562
Link to working paper: https://arxiv.org/abs/2112.11562
</p
Supplementary data and research materials for "The complex regional effects of macro-institutional change: Evidence from EU enlargement over three decades"
No full textThis folder contains study data and a variable list for the empirical analysis in:"The complex regional effects of macro-institutional change: Evidence from EU enlargement over three decades" by: Mitze, T., and Breidenbach, P.Current Version: March 8, 2024Published in: Review of World Economics, forthcoming</p
Does Cluster Policy Trigger R&D Activity? – Evidence from German Biotech Contests
No full textThis paper evaluates the R&D enhancing effects of two large public grant schemes for the German biotechnology industry (BioRegio, BioProfile). Both grant schemes are organized in the form of contents for cooperation with the goal to foster the performance of innovative firms by their organization in research clusters. We apply a Differencein Differences estimation technique in a generalized linear model framework, which allows us to control for different initial regional conditions in R&D activity of the biotech sector. Our econometric findings support the view that winners generally outperform non-winning participants during the treatment period, thus indicating that exclusive funding as well as the stimulating effect of being a 'winner' have positive eff ects on R&D activity in the short-term. Apart from this direct winner effect, for the non-winning participants no beneficial indirect effect due to a mobilization of local actors during the application phase could be detected. Finally, first attempts in estimating the long-term effects of the contests for cooperation approach on the winner regions'R&D activity in the post-treatment period show ambiguous results.Diese Arbeit analysiert die regionalen Fördereffekte des BioRegio- und BioProfile-Wettbewerbs für die deutsche Biotechnologie bezogen auf private FuE-Tätigkeit. Beide Förderprogramme zeichnen sich durch einen expliziten Wettbewerbscharakter aus und verfolgen das Ziel, die Leistungsfähigkeit von innovativen Unternehmen der Biotechnologie durch ihre Organisation und Zusammenarbeit in regionalen Clustern zu erhöhen. Für die empirische Analyse verwenden wir einen Differenz-in-Differenzen-Schätzansatz im Rahmen eines generalisierten linearen Modells, welcher es uns ermöglicht, für unterschiedliche regionale Ausgangsbedingungen und gemeinsame sektorale Zeittrends in der Biotechnologie zu kontrollieren. Unsere empirischen Ergebnisse zeigen, dass Gewinnerregionen während der Förderung sowohl input- als auch outputseitig gemessen eine überproportional höhere FuE- und Innovationsaktivität aufweisen als erfolglose Teilnehmer- und nicht-teilnehmende Regionen. Der mit den Wettbewerben einhergehende privilegierte Zugang zu Fördermitteln und der zusätzliche Prestigegewinn zeigen somit positive Effekte in der kurzen Frist. Demgegenüber kann für erfolglose Teilnehmer in den Wettbewerben kein indirekter Effekt der Förderung gegenüber Nicht-Teilnehmern in der Form festgestellt werden, dass eine zusätzliche Mobilisierung der regionalen Akteure im Rahmen der Wettbewerbsteilnahme stattfindet. Ebenfalls hinterlässt eine erste Analyse der Langfristwirkungen in den Gewinnerregionen nach der Förderperiode einen eher gemischten Gesamteindruck
Network Dependency in Migration Flows – A Space-time Analysis for Germany since Re-unification
No full textThe contribution of this paper is to analyse the role of network interdependencies in a dynamic panel data model for German internal migration fl ows since re-unification. So far, a capacious account of spatial patterns in German migration data is still missing in the empirical literature. In the context of this paper, network dependencies are associated with correlations of migration flows strictly attributable to proximate flows in geographic space. Using the neoclassical migration model, we start from its aspatial specification and show by means of residual testing that network dependency eff ects are highly present. We then construct spatial weighting matrices for our system of interregional flow data and apply spatial regression techniques to properly handle the underlying space-time interrelations. Besides spatial extensions to the Blundell-Bond (1998) system GMM estimator in form of the commonly known spatial lag and unconstrained spatial Durbin model, we also apply system GMM to spatially filtered variables. Finally, combining both approaches to a mixed spatial filteringregression specification shows a remarkably good performance in terms of capturing spatial dependence in our migration equation and at the same time qualify the model to pass essential IV diagnostic tests. The basic message for future research is that space-time dynamics is highly relevant for modelling German internal migration flows.Internal migration, dynamic panel data; Spatial Durbin Model; GMM
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