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on Knowledge Management and Knowledge Economy |
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Issue of 2020‒07‒13
seven papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Grytten, Ola Honningdal (Dept. of Economics, Norwegian School of Economics and Business Administration) |
| Abstract: | Existing historical GDP series for Norway do not always coincide with our historical knowledge of the economic development. This is to a large extent a result of lack of calculations from the production side and in addition to insufficient data sets upon which these series rest. The present paper offers new knowledge of historical national accounting in Norway in several ways. Firstly, a new and novel set of annual gross domestic product series by industry are presented for the period 1816-2019. Secondly, the new estimations suggest revision of the long-run GDP series. Thirdly, this implies it is necessary to revise our understanding of parts of Norwegian economic history. |
| Keywords: | Historical national accounting; national accounts; industrial development; Norwegian economic history |
| JEL: | N13 N14 O11 O14 O16 |
| Date: | 2020–06–22 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:nhheco:2020_010&r=all |
| By: | Corinne Autant-Bernard (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - CNRS - Centre National de la Recherche Scientifique - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UL2 - Université Lumière - Lyon 2 - ENS Lyon - École normale supérieure - Lyon); Ruben Fotso (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - CNRS - Centre National de la Recherche Scientifique - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UL2 - Université Lumière - Lyon 2 - ENS Lyon - École normale supérieure - Lyon); Nadine Massard (GAEL - Laboratoire d'Economie Appliquée de Grenoble - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | Large firms dominate R&D investment in most countries and receive the majority of public R&D funding. Due to methodological difficulties, however, evaluation of the effect of government-sponsored R&D programmes mainly focuses on small-and medium-sized enterprises. The scarcity of large firms and their heterogeneity hampers the ability to find proper counterfactuals for very large companies and makes it difficult to use proper inference methods to measure the impact of a specific policy. In order to address these methodological issues, we propose using the synthetic control method, initially developed by Abadie et al. (2010) to evaluate programmes on a regional scale. We apply this method to evaluate the impact of a new French science-industry transfer initiative and compare the results with the random trend model and more standard counterfactual approaches. Based on data covering a long pre-treatment period (1998-2011) and ongoing treatment period (2012-2015), we reveal a convergence between the results obtained with the synthetic control method and the random trend model, and demonstrate that traditional counterfactual evaluation methods are not appropriate for large firms. Moreover, the synthetic control method has the advantage of providing an individual assessment of the policy impact on each firm. In the specific case of the French science-industry transfer initiative, it reveals that the impact on private R&D is highly heterogenous both on RD inputs and cooperation behaviours. Beyond this specific transfer policy, this study suggests that the synthetic control method opens new research perspectives in policy impact evaluation at the firm level. Abstract: Large firms dominate R&D investment in most countries and receive the majority of public R&D funding. Due to methodological difficulties, however, evaluation of the effect of government-sponsored R&D programmes mainly focuses on small-and medium-sized enterprises. The scarcity of large firms and their heterogeneity hampers the ability to find proper counterfactuals for very large companies and makes it difficult to use proper inference methods to measure the impact of a specific policy. In order to address these methodological issues, we propose using the synthetic control method, initially developed by Abadie et al. (2010) to evaluate programmes on a regional scale. We apply this method to evaluate the impact of a new French science-industry transfer initiative and compare the results with the random trend model and more standard counterfactual approaches. Based on data covering a long pre-treatment period (1998-2011) and ongoing treatment period (2012-2015), we reveal a convergence between the results obtained with the synthetic control method and the random trend model, and demonstrate that traditional counterfactual evaluation methods are not appropriate for large firms. Moreover, the synthetic control method has the advantage of providing an individual assessment of the policy impact on each firm. In the specific case of the French science-industry transfer initiative, it reveals that the impact on private R&D is highly heterogenous both on RD inputs and cooperation behaviours. Beyond this specific transfer policy, this study suggests that the synthetic control method opens new research perspectives in policy impact evaluation at the firm level. |
| Keywords: | impact evaluation,R&D policy,large firms,synthetic control method,Technological Research Institutes (TRIs) |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-02733210&r=all |
| By: | Sasaki, Hiroaki |
| Abstract: | In economic growth theory, product innovation and process innovation are important factors behind technological progress. This study builds an economic growth model that considers product and process innovation and theoretically investigates how these two types of innovation affect the economic growth rate and unemployment rate. Our model, based on that developed by Zagler (2004), allows us to make the following three main findings. We find that (1) an increase in the efficiency of product innovation increases both the economic growth rate and the unemployment rate; (2) an increase in the efficiency of process innovation increases the economic growth rate and does not affect the unemployment rate; and (3) in the R\&D sector, a decrease in the labor allocation to product innovation and an increase in the labor allocation to process innovation increase the economic growth rate and decrease the unemployment rate depending on the conditions. These findings suggest that to both raise employment and increase economic growth, we need not only a policy for fostering product innovation but also another policy to improve employment. |
| Keywords: | effective demand; notional demand; unemployment; economic growth; product and process innovation; monopolistic competition |
| JEL: | E12 O31 O41 |
| Date: | 2020–06–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:101031&r=all |
| By: | Pietro Santoleri; Andrea Mina; Alberto Di Minin; Irene Martelli |
| Abstract: | Direct public support for business R&D is a well-established remedy to market failures, yet empirical evidence on its effectiveness yields conflicting results. The paper investigates the impact of the first European public R&D grant program targeting small and medium enterprises (i.e. the SME Instrument) on a wide range of firm outcomes. We leverage the assignment mechanisms of the policy and employ a sharp regression discontinuity design to provide the broadest quasi-experimental evidence on R&D grants over both geographical and sectoral scopes. Results show that grants trigger sizable impacts. They increase investment, notably in intangibles, and innovation outcomes as measured by cite-weighted patents; they trigger faster growth in assets, employment and revenues; they lead to higher likelihood of receiving follow-on equity financing and lower failure chances. These effects tend to be larger for firms that are smaller and younger, or operating in sectors characterized by higher financial frictions. Furthermore, responses are stronger in countries and regions with lower economic development. The paper provides extensive evidence that the beneficial effects of R&D grants materialize through funding rather than certification effects. |
| Keywords: | Regression discontinuity design; Research and development; Innovation Policy; SMEs. |
| Date: | 2020–06–29 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2020/18&r=all |
| By: | Dolphin, G.; Pollitt, M. |
| Abstract: | The recent history of the Electricity Supply Industry (ESI) of major western economies was marked by two fundamental changes: a transition toward liberalised electricity markets and a policy-led push to decarbonise the electricity generation portfolio. These changes not only affected the pace and nature of innovation activity in the sector but also altered the set of innovative actors. The present paper provides a methodology to identify these actors, which we apply to priority patents filed at the UK Intellectual Property Office over the period 1955-2016. The analysis also indicates that (i) the recent increase in innovation activity originates overwhelmingly from upstream Original Equipment Manufacturers and (ii) innovation activity in `green' electricity supply technologies slowed down in recent years. |
| Keywords: | innovation, electricity sector, machine learning |
| JEL: | L94 O31 O38 |
| Date: | 2020–03–03 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2013&r=all |
| By: | Bronwyn H. Hall |
| Abstract: | I survey some recent research on the role of patents in encouraging innovation and growth in developing economies, beginning with a brief history of international patent systems and facts about the current use of patents around the world. I discuss research on the implications of patents for international technology transfer and domestic innovation. This is followed by a review of recent work by myself and co-authors on regional patent systems, the impact of patents on firm performance, and the impact on pharmaceutical patenting and domestic innovation. The conclusion suggests that patents may be relatively unimportant in development, even for middle income countries. |
| JEL: | L65 O25 O30 O34 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27203&r=all |
| By: | Heng, Stefan |
| Abstract: | Industry 4.0 is a subject with global implications. Essentially, the concept comes down to the reorganisation and automation of value chains. If successfully implemented, industry 4.0 sets out to revolutionise the way goods and services are created and distributed, reshaping the industrial landscape on a national and global scale. Thus, China is determined to seize the opportunities of the digital evolution. Chinas government actively promotes the transformation towards an innovation-led growth model through large policy programs. The scope of funding for seven Strategic Emerging Industries is placed in the Five-Year-Plan. Thus, the government unveiled its “Made in China 2025” program. Here, China is considered the most mature adopter of industry 4.0 worldwide. Aside from world leaders such as Huawei and ZTE, myriads of Chinese small and medium enterprises create an updated version of German Mittelstand for Far East. Notwithstanding, the rank and file of China’s companies did still not embrace the benefits of previous industrial stages. The country is and will remain highly heterogeneous. Therefore, industry 4.0 is realised locally and in an evolutionary fashion. Overall, China’s implementation of industry 4.0 is still in its infancy. Nevertheless, by managing to extrapolate the momentum, China is pulling into the fast lane. |
| Keywords: | industry 4.0; digitalization; innovation; automatization; China; globalization; industry |
| JEL: | F60 L0 O14 O25 O31 O32 O33 |
| Date: | 2019–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:100868&r=all |