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on Technology and Industrial Dynamics |
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Issue of 2013‒10‒11
nine papers chosen by Fulvio Castellacci Norwegian Institute of International Affairs (NUPI) |
| By: | Acemoglu, Daron (MIT, CEPR and NBER); Akcigit, Ufuk (University of Pennsylvania and NBER); Bloom , Nicholas (Stanford University, NBER and CEPR); Kerr , William (Harvard University, Bank of Finland, and NBER) |
| Abstract: | We build a model of firm-level innovation, productivity growth and reallocation featuring endogenous entry and exit. A key feature is the selection between high- and low-type firms, which differ in terms of their innovative capacity. We estimate the parameters of the model using detailed US Census micro data on firm-level output, R&D and patenting. The model provides a good fit to the dynamics of firm entry and exit, output and R&D, and its implied elasticities are in the ballpark of a range of micro estimates. We find industrial policy subsidizing either the R&D or the continued operation of incumbents reduces growth and welfare. For example, a subsidy to incumbent R&D equivalent to 5% of GDP reduces welfare by about 1.5% because it deters entry of new high-type firms. On the contrary, substantial improvements (of the order of 5% improvement in welfare) are possible if the continued operation of incumbents is taxed while at the same time R&D by incumbents and new entrants is subsidized. This is because of a strong selection effect: R&D resources (skilled labor) are inefficiently used by low-type incumbent firms. Subsidies to incumbents encourage the survival and expansion of these firms at the expense of potential high-type entrants. We show that optimal policy encourages the exit of low-type firms and supports R&D by high-type incumbents and entry. |
| Keywords: | entry; growth; industrial policy; innovation; R&D; reallocation; selection |
| JEL: | E02 L11 O31 O32 O33 |
| Date: | 2013–09–25 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofrdp:2013_022&r=tid |
| By: | Angus C.Chu (University of Liverpool United Kingdom); Yuichi Furukawa (Chukyo University Japan); Lei Ji (Shanghai University of finance and economics China) |
| Abstract: | This study explores the different implications of patent breadth and RD subsidies on economic growth and endogenous market structure in a Schumpeterian growth model. We fend that when the number of firms is fixed in the short run, patent breadth and R&D subsidies serve to increase economic growth as in previous studies. However, when the number of firms adjusts endogenously in the long run, RD subsidies increase economic growth but decrease the number of firms,whereas patent breadth expands the number of firms but reduces economic growth. Therefore, RD subsidy is perhaps a more suitable policy instrument than patent breadth for the purpose of stimulating long-run economic growth. |
| Keywords: | economic growth,endogenous market structure, patents rd subsidies |
| JEL: | O30 O40 |
| Date: | 2013–09 |
| URL: | http://d.repec.org/n?u=RePEc:fce:doctra:1319&r=tid |
| By: | Lei Ji (Ofce sciences-po, Skema Business School) |
| Abstract: | I develop a multi-industry endogenous growth model with the endogenous market structure. Industries are heterogeneous in production unit costs, research and development RD productivities, fixed operating costs and industry level market sizes. The endogenous market structure allows an empirically realistic and theoretically important determination of the individual firms’ market sizes and distinguishes the model from the previous literatures. There are two sets of results. First, the balanced growth rate depends positively on RD productivities and firm market size of both industries but not industry market size. Surprisingly, the steady state total factor productivity TFP level ratio between industry 1 and 2 depends negatively on RD productivity and fixed costs in industry 1 and positively on those parameters in industry 2. Second, industry differences in both TFP growth and R&D intensity mainly reflect differences in quality-adjusted gross profits and RD productivities. Such differences depend on RD productivities and fixed operating cost parameters in general equilibrium. The industry with a higher RD productivity and fixed cost has a lower TFP growth and research intensity compared to the other industry. Differences in production unit costs and industry level market sizes do not to contribute to cross-industry TFP growth differences. These results are substantially different from what is found in the existing literature. Model also offers novel explanations for directed technical change and structural change, and it offers a structure for analyzing the interaction between trade and growth. |
| Keywords: | Cross-industry TFP growth differences, endogenous growth, asymmetric industries,endogenous market structure |
| Date: | 2013–09 |
| URL: | http://d.repec.org/n?u=RePEc:fce:doctra:1317&r=tid |
| By: | Maxim Kotsemir (National Research University Higher School of Economics, Institute for Statistical Studies and Economics of Knowledge, Research Laboratory for Science and Technology Studies, Junior Research Fellow.); Alexander Abroskin (National Research University Higher School of Economics; Institute for Statistical Studies and Economics of Knowledge, Department for Strategic Foresight, Chief Research Fellow, Associate Professor, Doctor of science); Dirk Meissner (National Research University Higher School of Economics, Institute for Statistical Studies and Economics of Knowledge, Research Laboratory for Science and Technology Studies, Deputy Laboratory Head.) |
| Abstract: | This paper is devoted to the analysis of evolution of innovation concepts, aspects and types. First emergence and evolution of different aspects and concepts of innovation are analyzed, and then the development of innovation concepts from a historical perspective and finally an overview of the types of innovation classifications developed in the literature are given. Complementary the different definitions of innovation are described and analyzed in detail. The main goal of the article is to identify, describe and visualize the development trend of innovation conceptualization and understanding over time |
| Keywords: | innovation concepts, innovation types, aspects of innovation, innovation systems, innovation ecosystems, typology of innovation, product innovation, process innovation, service innovation, marketing innovation, organization innovation, business innovation |
| JEL: | B10 B20 O31 O32 O33 Q55 |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:wpbrp05sti2013&r=tid |
| By: | G. Parmentier (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre-Mendès-France - Grenoble II); Vincent Mangematin (MTS - Management Technologique et Strategique - Grenoble École de Management (GEM)) |
| Abstract: | The digital creative industries exemplify innovation processes in which user communities are highly involved in product and service development, bringing new ideas, and developing tools for new product uses and environments. We explore the role of user communities in such co-innovation processes via four case studies of interrelations between firms and their communities. The digitization and virtualization of firm/community interactions are changing how boundaries are defined and how co-innovation is managed. The transformation of innovation management is characterized by three elements: opening and redefining firm boundaries; opening of products and services to community input and reducing property rights; and reshaping organization and product identities. Innovation in collaboration with user communities requires firms to orchestrate their communities and their inter-relationships to encourage the creativity and motivation of users, and develop the community's innovatory capacity. |
| Keywords: | Online communities; User; Innovation; Video game; Community management; Co-innovation |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:hal:gemptp:halshs-00848861&r=tid |
| By: | Stadler, Manfred |
| Abstract: | We develop a dynamic stochastic general-equilibrium model of science, education and innovation to explain the simultaneous emergence of innovation clusters and stochastic growth cycles. Firms devote human-capital resources to research activities in order to invent higher quality products. The technological requirements in climbing up the quality ladders increase over time but this hampering effect is compensated for by an improving qualification of researchers allowing for a sustainable process of innovation and scale-invariant growth. Jumps in human capital, triggered by scientific breakthroughs, induce innovation clusters across industries and generate long-run growth cycles. -- |
| Keywords: | Science,Education,Innovation clusters,Stochastic growth cycles |
| JEL: | C61 E32 O33 |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:tuewef:60&r=tid |
| By: | Chienyu Huang (Southwestern University of Finance and economics); Juin Jen Chang (Institute of economics, Academia Sinica Taiwan); Lei Ji (Ofce sciences-po,skema Business School) |
| Abstract: | In this paper we explore the effects of monetary policy on the number of firms, firm market size, inflation and growth in a Schumpeterian growth model with endogenous market structure and cash-in-advance CIA constraints on two distinct types of RD investment in-house RD and entry investment. This allows us to match the empirical evidence and provides novel implications to the literature. We show that if in-house RD (quality improvement-type R&D) is subject to the CIA constraint, raising the nominal interest rate increases the number of firms and inflation, but decreases the firm size and economic growth. By contrast, if entry investment variety expansion-type RD is subject to the CIA constraint, these variables adversely respond to such a monetary policy. Besides, our model generates rich transitional dynamics in response to a change in monetary policy, when RD entry is restricted by a cash constraint. |
| Keywords: | CIA constraints on RD, endogenous market structure,monetary policy,economic growth |
| JEL: | O30 O40 E41 |
| Date: | 2013–09 |
| URL: | http://d.repec.org/n?u=RePEc:fce:doctra:1316&r=tid |
| By: | Schön, Benjamin; Pyka, Andreas |
| Abstract: | With mergers & acquisitions playing an increasingly important role in today's business world, academic research has strived to follow this trend by investigating their underlying causes and consequences. For a long time this research focused on the analysis of the financial effect of mergers & acquisitions as measured by market value or debt level. Thus, despite being a major vehicle of industry concentration and method of reallocation of resources, the technological impact of mergers & acquisitions remained comparatively underinvestigated for a long time. This, however, has changed in recent years. With the prevalence of the resource-based view and its derivates as the dominant logic in analysing today's knowledge-intensive industries the focus shifted towards the technological aspects of mergers & acquisitions. With both mergers & acquisitions and innovation being centrepieces of competitive strategies in the modern economy, it is of central importance to understand the consequences of mergers & acquisitions for the innovative potential of firms. After more than twenty years of research in this field, it is time to take stock of what we know about the technological impact of mergers & acquisitions and its determinants. The aim of this paper is to provide an overview of the respective research by performing a meta-analysis of the empirical studies in the field. The intuitive setup allows for a detailed analysis of the individual determinants while differentiating between the impact on innovation input and output. We identify the knowledge characteristics of the partnering firms as being essential to the technological success of mergers & acquisitions. Important implications for policy makers, practitioners and future research are derived. -- |
| Keywords: | Innovation,Mergers and Acquisitions |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fziddp:782013&r=tid |
| By: | Leonid Gokhberg (National Research University Higher School of Economics, First Vice Rector; Institute for Statistical Studies and Economics of knowledge); Tatiana Kuznetsova (National Research University Higher School of Economics. Institute for Statistical Studies and Economics of knowledge. Director of the Centre for S&T, Innovation and Information Policies); Vitaly Roud (National Research University Higher School of Economics. Institute for Statistical Studies and Economics of knowledge. Research assistant); Stanislav Zaichenko (National Research University Higher School of Economics. Institute for Statistical Studies and Economics of knowledge. Senior research assistant) |
| Abstract: | “Monitoring innovation activities of innovation process participants” is a project which has been carried out by the Higher School of Economics (HSE) for several years to promote monitoring and analysis of innovation issues in general, and on specific activities of its particular actors from a scientific research perspective. The project is aimed at accumulating empirical knowledge about the nature and types of interaction between various actors of the national innovation system. In 2009-2010 the study was targeted at manufacturing and service sector companies while the 2010-2011 study targeted at R&D organisations. The specific objective for 2011 was studying various aspects of applied research organisations’ involvement in the innovation process (application of R&D results in the economy). The study yielded the following results: - A concept for monitoring R&D organisations’ innovation activities was proposed, including operational definition of such activities; - Survey programme and tools to monitor Russian R&D organisations were developed, including advanced methodological and procedural approaches as well as practical experience; - Results of R&D organisations’ innovation activities survey were analysed and compared with available statistical data; the collected data also allows to identify and systematise various factors and conditions affecting innovation activities of these organisations; Eventually areas for updating the survey’s concept and tools were identified |
| Keywords: | R&D institutions, public research institutes, S&T results, knowledge transfer, technology transfer, innovation, research management, innovation management, microdata, Russia |
| JEL: | O31 O32 O33 O38 |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:wpbrp06sti2013&r=tid |