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on Technology and Industrial Dynamics |
| By: | Montresor, Sandro; Quatraro, Francesco (University of Turin) |
| Abstract: | This paper investigates the move of regions towards sustainable growth through their specialisation in new green technologies. In particular, we analyse the role that smart specialisation strategies (S3) can have in this respect by addressing two research questions. First of all, we investigate whether the environmental diversification of regional technologies is, according to the S3 logic, driven by their “relatedness” to existing knowledge of green and non-green nature. Second, we analyse the role of the Key Enabling Technologies (KETs) that S3 policies recommend regions to prioritise, not only in fostering the adoption of environmental technologies, but also in affecting its dependence on the pre-existing knowledge-base. Combining regional patent and economic data for a 34-year panel (1980-2013) of 180 European regions, we find that the relatedness to the existing technological-base of the region actually makes the acquisition of a new green-tech specialisation more probable. This holds true with respect to both the green and non-green extant knowledge, pointing to a regional diversification that also benefits from the “hybridisation” of non-environmental technologies. The latter however requires a higher degree of relatedness than a “pure” green branching process. Regional KETs also help the transition towards sustainable technologies. What is more, they negatively moderate the green impact of the relatedness to pre-existing technologies, of both green and non-green nature, and thus attenuate the boundaries the latter could pose to regions in their environmental specialisation. These results confirm that S3 policies can actually boost the intertwining of a smart and sustainable kind of growth, and that the KETs inclusion within S3 can amplify the virtuous interaction between these two objectives. |
| Date: | 2018–04 |
| URL: | http://d.repec.org/n?u=RePEc:uto:labeco:201804&r=tid |
| By: | Nikolaus Thumm (European Commission – JRC - IPTS); Vincenzo Butticè (School of Management, Politecnico di Milano); Federico Caviggioli (Department of Management and Production Engineering, Politecnico di Torino); Chiara Franzoni (School of Management, Politecnico di Milano); Giuseppe, Scellato (Department of Management and Production Engineering, Politecnico di Torino) |
| Abstract: | Counterfeiting activities target companies in various sectors, including digital technology companies, defined as companies that produce and/or commercialize at least one physical product that incorporates a digital technology, excluding the merchandising related to the company brands. Counterfeiting is a fraudulent activity that potentially damages the economic and innovation performance of companies and can pose major threats to global competition and economic growth. However, the actual impact of counterfeiting on the performance of companies has not been tested empirically, due to methodological problems, including the lack of data on counterfeiting at the firm-level. Furthermore, prior theoretical studies have speculated that counterfeiting could have in part a beneficial effect on the performance of companies, due to indirect advertising, calling for empirical investigations to shed light on the issue. The goal of the present study is to provide empirical evidence on the impact of counterfeiting on both the economic and innovative performance of digital technology companies at the firm-level and on the global scale. To this aim, a new database was created combining data on counterfeiting activities during 2011-2013 (OECD-EUIPO, 2016) with financial information and patent data from 2009 to 2015. The result is a firm-level database that enables unprecedented analyses on the impact of counterfeiting on performance of digital technology companies. About 9% of the seizures of counterfeits that were illegally traded across borders during 2011 2013 involved goods commercialized by digital technology companies, equivalent to about the 9.1% of the total value of seizures. Collectively, about 11% of companies affected by illegal international trade of counterfeits are digital technology companies. The majority of these (58%) are big corporations with Operating Revenues greater than USD 1 bn. These account for 77% of the number of total seizures, and 84% of the value of seizures related to the digital technology companies. SMEs, defined as those with Operating Revenues up to USD 50 million, represent 21% of digital technology companies targeted and account for 5% of total seizures and 6% of the total value of seizures. The industries mostly targeted are electronics (both consumers’ electronics and electronics for industrial use), automotive and digital media. The digital technology products commercialized in frauds of IPRs include computer hardware and electronic components, batteries, sensors, autoparts, optical instruments, videogames, and recording of movies and motion picture. About 34% of digital technology companies affected by international trade of counterfeits are located in the EU28 or EFTA, 41% are located in North America, 23% are located in Asia. Within the EU28, UK, Germany, France and Italy are the countries hosting the largest number of targeted digital technology companies. Within the EU28, Germany and UK, followed by Belgium and Ireland, are the most-common country of destination of seized counterfeits. The overwhelming majority of seized goods related to digital technology companies is imported from Asia. 51% of these are imported from China, 41% comes from Hong Kong, China, 3% from Singapore. Other economies of provenance account each for less than 1% of the seizures. The vast majority (93%) of seizures affecting digital technology companies are due to violations of trademarks, and only a minority are due to violations of design models (4%), and copyrights (2%). Less than 1% of the seizures are due to violations of patents. However, seizures enacted in defence of patents are those that have the highest mean value. The analysis of infringed companies with respect to a control samples of non-infringed companies indicates that counterfeiting targets specifically highly profitable companies, with high propensity to innovate. Indeed, digital technology companies are more likely to become target of counterfeiting when they have larger Operating Revenues, and when they perform at a higher level in terms of profitability (return on total assets), prior to the window of observation. Target companies also have on average larger patent portfolios, prior to the observation of counterfeiting activities. Digital technology companies located in EU28 are on average less likely than companies located outside of EU28 to be the target of counterfeiting activities. Results from impact analyses indicate lower growth rates of operating profits for digital technology companies targeted by counterfeiting with respect to control samples of firms not affected by counterfeiting. In particular the econometric models provide evidence of a negative impact of counterfeiting on both EBITDA (Earnings before interest taxes depreciation and amortisation) and EBIT (Earnings before interest taxes). This result is robust across different estimation methods, model specifications and time windows. The data reveals only a weak negative impact on operating revenues, with limited statistical confidence. Conversely, there is no significant evidence that counterfeiting affected the investment in Fixed Assets of targeted firms with respect to the control sample. The results about the negative impact of counterfeiting activities on operating profits are in line with reports of greater costs incurred by these companies to enact anti-counterfeiting strategies, reported in prior descriptive literature. These practices include the broadening of product ranges, with fewer scale-economies and the enactment of anti-infringement procedures, such as ‘conspicuous packaging’, more screening and origin certifications, development of licensing downstream retailers and direct self-enforcement aimed at limiting the circulation of counterfeits. Results do not provide support for the existence of indirect positive spillover effects, as hypothesised by the theoretical literature, according to which infringed companies might benefit from an advertising effect due to the greater diffusion of brands from the counterfeiting activities. Indeed, at least for what concerns digital technology companies, there is no evidence of any positive effect of infringement on sales of original products. The digital technology companies that were affected by counterfeiting on average increased their patent portfolios during the observation period, but less than the digital technology companies that were not affected by counterfeiting. However, the result is not robust to the inclusion of control variables and to the adoption of alternative measures of innovation performance (Intangible Assets). It certainly merits further research, once more data on counterfeiting become available. Overall, the results indicate that counterfeiting activities harm the economic performance of targeted digital technology companies, by eroding their operating profits. The effect on innovative performance is negative, but still inconclusive due to insufficient dataset, and cannot exclude that counterfeiting may harm the propensity to innovate of digital technology companies. The analysis rules-out the existence of any positive spillover from counterfeiting. |
| Keywords: | Counterfeiting, trade, trade seizures, digital technologies, economic performance, innovative performance, patents, trademarks |
| JEL: | F1 K42 L63 O25 O31 O32 O34 O39 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:decwpa:2018-03&r=tid |
| By: | Dolores Añón Higón (Department of Economic Structure, University of Valencia, Avda. dels Tarongers s/n, 46022 Valencia (Spain).); Juan A. Mañez (Department of Economic Structure, University of Valencia, Avda. dels Tarongers s/n, 46022 Valencia (Spain).); María E. Rochina-Barrachina (Department of Economic Structure, University of Valencia, Avda. dels Tarongers s/n, 46022 Valencia (Spain).); Amparo Sanchis (Department of Economic Structure, University of Valencia, Avda. dels Tarongers s/n, 46022 Valencia (Spain).); Juan A. Sanchis (Department of Economic Structure, University of Valencia, Avda. dels Tarongers s/n, 46022 Valencia (Spain).) |
| Abstract: | In this article we characterize Total Factor Productivity (TFP) frontier firms at the industry level within the European Union during the period 2003-2014, and explore the determinants of the firms’ distance to the frontier. We find that larger, more capital-intensive, and more labour skilled firms are closer to the productivity frontier. In contrast, older firms are further away from the frontier. In addition, we obtain that a number of countries' economic and institutional factors, such as tertiary education, trade openness, R&D stock, easiness in getting credit and governance quality, affect positively the catching up of laggards towards the productivity frontier. We also examine the moderating effect of the Great Recession as well as the effect of productivity improvements at the frontier. |
| Keywords: | TFP, frontier firms, laggard firms, Great Recession, European Union countries |
| JEL: | F43 O47 O52 |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:eec:wpaper:1806&r=tid |
| By: | Antonelli, Cristiano; Feder, Christophe; Quatraro, Francesco (University of Turin) |
| Abstract: | Technological congruence implements the analysis of directed technological change showing how the match between the relative size of outputs’ elasticity and the relative abundance and cost of production factors has powerful effects on total factor productivity (TFP). Smart specialization strategies can rely upon technological congruence to support the introduction and diffusion of new directed technologies characterized by the best mix of factors relative cost -as determined by pecuniary externalities in the regional factor markets- and output elasticity. The evidence of 278 European regions in the years 1980-2011 confirms that the levels and the changes in technological congruence, brought about by the introduction of directed technological changes, have significant effects on the levels and the changes of TFP. The key policy implication is that the optimal S3 policy mix should not only look at the history of local industrial or technological specializations, but it should also take into account the pecuniary externalities that characterize local factor markets to promote technological changes directed to augmenting the output elasticity of the cheaper regional production factors. |
| Date: | 2018–04 |
| URL: | http://d.repec.org/n?u=RePEc:uto:labeco:201801&r=tid |
| By: | Konon, Alexander (DIW Berlin); Fritsch, Michael (University of Jena); Kritikos, Alexander S. (DIW Berlin) |
| Abstract: | We analyze whether start-up rates in different industries systematically change with business cycle variables. Using a unique data set at the industry level, we mostly find correlations that are consistent with counter-cyclical influences of the business cycle on entries in both innovative and non-innovative industries. Entries into the large-scale industries, including the innovative part of manufacturing, are only influenced by changes in the cyclical component of unemployment, while entries into small-scale industries, like knowledge intensive services, are mostly influenced by changes in the cyclical component of GDP. Thus, our analysis suggests that favorable conditions in terms of high GDP might not be germane for start-ups. Given that both innovative and non-innovative businesses react counter-cyclically in 'regular' recessions, business formation may have a stabilizing effect on the economy. |
| Keywords: | new business formation, entrepreneurship, business cycle, manufacturing, services, innovative industries |
| JEL: | E32 L16 L26 R11 |
| Date: | 2018–04 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp11501&r=tid |
| By: | Teresa C. Fort; Justin R. Pierce; Peter K. Schott |
| Abstract: | We use relatively unexplored dimensions of US microdata to examine how US manufacturing employment has evolved across industries, firms, establishments, and regions from 1977 to 2012. We show that these data provide support for both trade- and technology-based explanations of the overall decline of employment over this period, while also highlighting the difficulties of estimating an overall contribution for each mechanism. Toward that end, we discuss how further analysis of these trends might yield sharper insights. |
| Keywords: | Employment ; Manufacturing ; Output ; Technology ; Trade |
| Date: | 2018–04–13 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2018-23&r=tid |
| By: | Bachmann, Ronald; Cim, Merve; Green, Colin |
| Abstract: | The past four decades have witnessed dramatic changes in the structure of employment. In particular, the rapid increase in computational power has led to large-scale reductions in employment in jobs that can be described as intensive in routine tasks. These jobs have been shown to be concentrated in middle skill occupations. A large literature on labour market polarisation characterises and measures these processes at an aggregate level. However to date there is little information regarding the individual worker adjustment processes related to routine-biased technological change. Using an administrative panel data set for Germany, we follow workers over an extended period of time and provide evidence of both the short-term adjustment process and medium-run effects of routine task intensive job loss at an individual level. We initially demonstrate a marked, and steady, shift in employment away from routine, middle-skill, occupations. In subsequent analysis, we demonstrate how exposure to jobs with higher routine task content is associated with a reduced likelihood of being in employment in both the short term (after one year) and medium term (five years). This employment penalty to routineness of work has increased over the past four decades. More generally, we demonstrate that routine task work is associated with reduced job stability and more likelihood of experiencing periods of unemployment. However, these negative effects of routine work appear to be concentrated in increased employment to employment, and employment to unemployment transitions rather than longer periods of unemployment. |
| Keywords: | polarization,occupational mobility,worker flows,tasks |
| JEL: | J23 J24 J62 E24 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:rwirep:748&r=tid |
| By: | Réka Juhász; Claudia Steinwender |
| Abstract: | This paper studies how information and communication technology (ICT) improvements affect trade along the value chain and international technology diffusion. We examine the impact of a revolutionary technology, the roll-out of the global telegraph network, on the 19th century cotton textile industry. First, we show that connection to the telegraph disproportionately increased trade in intermediate goods relative to final goods. We document that this was due to differences in codifiability; that is, the extent to which product specifications could be communicated at a distance using only words (and thus by sending telegrams) as opposed to inspecting a sample of the product. Second, adoption of the telegraph also facilitated international technology diffusion through the complementary mechanisms of importing machinery and acquiring knowledge of the production process and local demand through importing intermediates. These results shed light on how ICT facilitates the formation of global value chains and the diffusion of frontier technology. |
| JEL: | F14 N7 O14 O33 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24590&r=tid |
| By: | Howell, Anthony (Asian Development Bank Institute) |
| Abstract: | We adopt a structural framework to study the process of indigenous innovation and its impact on firm performance in the People’s Republic of China (PRC). In our analysis we use a rich source of panel data comprising almost 70,000 private Chinese firms operating in the PRC from 2004 to 2007. Relying on a structural innovation framework, we estimate the effects of technological learning during each phase of the structural model: (i) the firm’s decision to innovate, (ii) the innovation effort, (iii) the innovation throughput, and (iv) the firm performance. We show that in the early stages of innovation, Chinese firms fail to incorporate learning spillovers into their innovation effort, even when considering their absorptive capacity. Conversely, we found that in the later stages of innovation, learning spillovers positively increase firms’ innovation output as well as their performance, especially for firms with high absorptive capacity. |
| Keywords: | innovation; firm performance; learning; agglomeration; institutions; People’s Republic of China |
| JEL: | O30 |
| Date: | 2018–02–08 |
| URL: | http://d.repec.org/n?u=RePEc:ris:adbiwp:0805&r=tid |
| By: | Bernardo Bortolotti; Veljko Fotak; Brian Wolfe |
| Abstract: | We investigate the impact of state ownership on the innovativeness of firms, as measured by the number, quality, and value of the patents produced. In a sample of listed European firms, we find that minority government ownership increases investment in research and development, especially for financially constrained firms and during “normal” macroeconomic conditions. Yet, government control leads to the opposite effect, by imposing myopic goals and complicating access to private equity markets. Overall, state owned enterprises (SOEs) produce fewer patents per dollar invested and about 10% fewer patents in absolute terms. When comparing SOE patents to private-sector patents, we find no difference in patent quality as measured by the number of citations received per patent or by the market reaction at patent publication. Furthermore, we find no increase in the number of patents focused on sustainable technologies, suggesting that SOEs do not emphasize innovation that produces public goods or social spillovers. |
| Keywords: | Innovation, state ownership |
| JEL: | G32 G15 G38 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:baf:cbafwp:cbafwp1872&r=tid |
| By: | Diego Restuccia |
| Abstract: | Productivity is at the core of the large differences in income per capita across countries. What accounts for international productivity differences? I discuss cross-country differences in the allocation of inputs across heterogeneous production units-misallocation-as a potential factor in accounting for aggregate productivity. Policies and institutions generating misallocation are prevalent in poor and developing countries and may also be responsible for differences in the selection of operating producers and technology used, contributing substantially to aggregate productivity differences across countries. |
| Keywords: | productivity, misallocation, selection, technology, regulation, trade, financial frictions, agriculture. |
| JEL: | O11 O14 O4 |
| Date: | 2018–06–11 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-608&r=tid |
| By: | Daniel A. Dias; Carlos Robalo Marques; Christine Richmond |
| Abstract: | Recent empirical studies document that the level of resource misallocation in the service sector is significantly higher than in the manufacturing sector. We quantify the importance of this difference and study its sources. Conservative estimates for Portugal (2008) show that closing this gap, by reducing misallocation in the service sector to manufacturing levels, would boost aggregate gross output by around 12 percent and aggregate value added by around 31 percent. Differences in the effect and size of productivity shocks explain most of the gap in misallocation between manufacturing and services, while the remainder is explained by differences in firm productivity and age distribution. We interpret these results as stemming mainly from higher output-price rigidity, higher labor adjustment costs, and higher informality in the service sector. |
| Keywords: | Misallocation ; Productivity ; Firm-level data ; Structural transformation ; Gelbach decomposition |
| JEL: | D24 O11 O41 O47 |
| Date: | 2018–05–29 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:1229&r=tid |