Do Cooperative Research and Development (R&amp;D) Subsidies Stimulate Regional Innovation Efficiency? Evidence from Germany

Broekel, Tom

doi:10.1080/00343404.2013.812781

Cited by 101 publications

(97 citation statements)

References 41 publications

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“…Delving deeper into regional micro data, Fritsch and Slavtchevc (2011) and Broekel (2015), in studying the innovation efficiency in Germany, have examined a number of regional factors such as knowledge networkings and collaboration among regional organizations. For example, Fritsch and Slavtchevc (2011) consider a number of factors, namely the density and industrial composition of regional actors, region's accessibility, the technological, industrial and institutional infrastructure (networks) of a region that may shape the innovation efficiency differentials across regions.…”

Section: How Efficient Is the Productions Of Output And Ideas?mentioning

confidence: 99%

“…The study concludes that spillovers from private as well as from universities and other public institutions have a positive effect on the innovation efficiency, and regions that are dominated by large establishments tend to be less efficient compared to regions with a lower average establishment size. Further, Broekel (2015) uses a rich panel dataset, covering 270 German labour market regions and four industries to examine whether subsidies for R&D cooperation are a suitable policy measure for stimulating the innovation efficiency of regions. The study shows that cooperation among regional firms and subsidized links to non-regional public research institutes benefit regions with low innovation capacities while subsidization of cooperation with non-regional universities is more important for regions with large innovation capacities.…”

Section: How Efficient Is the Productions Of Output And Ideas?mentioning

confidence: 99%

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Production of output and ideas: efficiency and growth patterns in the United States

2017

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This paper examines efficiency and growth patterns in the production of output and ideas in the US. We employ frontier techniques and jointly estimate the production of output and the production of ideas. We find states to be particularly efficient in the use of their inputs in the production of output process, whereas there is more waste in the use of innovation resources to produce new knowledge. Our results do not lend support to the common perception that richer (more innovative) states are more efficient than less richer (less innovative) states for every dollar spent. Furthermore, an efficient in producing knowledge state is not necessarily efficient in producing goods and services. Finally, a consistent finding is that input accumulation is an important source of growth both for output and for the knowledge.

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Section: How Efficient Is the Productions Of Output And Ideas?mentioning

confidence: 99%

Section: How Efficient Is the Productions Of Output And Ideas?mentioning

confidence: 99%

Production of output and ideas: efficiency and growth patterns in the United States

2017

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“…East German regions (still) tend to be characterized by lower innovation performance (Broekel et al 2013). Moreover, regions in East Germany might benefit from a number of public programs being especially designed to decrease the innovation performance gap between the two parts of Germany.…”

Section: Data On Randd Employees Patents and Regional Characteristicsmentioning

confidence: 99%

“…The relative magnitude of the co-financing is however unknown and may potentially bias the results. The studies by Fornahl et al (2011) andBroekel (2013) support this decision, as they find effects on innovation activities being related to project counts rather than to the sum of project grants.…”

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confidence: 97%

“…Second, Broekel (2013) argues that subsidies for joint R&D additionally influence the embeddedness of organizations into such systems and thereby impact its entire working and set-up, since subsidized R&D collaboration are one way of how organizations interact with the innovation systems. In addition, the availability of subsidized R&D collaboration alters the attraction of other modes of interaction (e.g.…”

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Joint R&D Subsidies, Related Variety, and Regional Innovation

Broekel

Brachert

Duschl

et al. 2016

International Regional Science Review

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Abstract:Subsidies for R&D are an important tool of public R&D policy, which motivates extensive scientific analyses and evaluations. The paper adds to this literature by arguing that the effects of R&D subsidies go beyond the extension of organizations' monetary resources invested into R&D. It is argued that collaboration induced by subsidized joint R&D projects yield significant effects that are missed in traditional analyses. An empirical study on the level of German labor market regions substantiates this claim showing that collaborative R&D subsidies impact regions' innovation growth when providing access to related variety and embedding regions into central positions in cross-regional knowledge networks.

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Regularized Poisson regressions predict regional innovation output

Yang

2023

Journal of Forecasting

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Regional innovation output is influenced by many factors such as macroeconomic environments, residents consumption, fixed asset investment, foreign trade, fiscal revenue and expenditure, education, and research and development (R&D) input. Correctly predicting regional innovation output is an important subject in the economic field. In this paper, we propose four regularized Poisson regressions to forecast regional innovation output for 31 provinces in China. Firstly, we screen out 20 important factors and combine with four penalties: ridge penalty , least absolute shrinkage and selection operator penalty (LASSO), smoothly clipped absolute deviation penalty (SCAD), and minimax concave penalty (MCP) to construct four regularized Poisson regressions. Secondly, we introduce the cyclic coordinate descent (CCD) algorithm and the training set to complete variable selection and obtain the least squares weighted iterative estimators and make model selection by introducing three criterions to compare goodness of fit to different models. Finally, we apply the testing set and the learned regressions to exhibit the prediction performances and found that SCAD/MCP regularized Poisson regression predicts better than /LASSO regularized Poisson regression in terms of root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). In particular, MCP regularized Poisson regression outperforms the other three regularized Poisson regressions in predicting the number of granted patents in the three regions.

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Do Cooperative Research and Development (R&D) Subsidies Stimulate Regional Innovation Efficiency? Evidence from Germany

Cited by 101 publications

References 41 publications

Production of output and ideas: efficiency and growth patterns in the United States

Production of output and ideas: efficiency and growth patterns in the United States

Joint R&D Subsidies, Related Variety, and Regional Innovation

Regularized Poisson regressions predict regional innovation output

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