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on Technology and Industrial Dynamics |
| By: | YAMASHITA Nobuaki; YAMAUCHI Isamu |
| Abstract: | This paper examines innovation response of a panel of Japanese firms to the intensified import competition from China for the period 1994-2009. We build a comprehensive firm-level dataset linking innovation activities including patenting and research and development (R&D) merged to cross-industry measures of Chinese import competition. Carefully accounting for a simultaneity bias between innovation and importing and the possible heterogeneous effects across firms, it is found that firms filed for more patents in response to increased import competition from China. However, this effect is only evident for a group of globally engaged firms. At the same time, Chinese import competition has adversely affected the quality of innovation as measured by citations. Overall, firms with a more domestic market focus are the ones who have felt most of the Chinese import competition, which is also reflected in their declined R&D efforts. |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:17126&r=tid |
| By: | Pugsley, Benjamin; Sedlacek, Petr; Sterk, Vincent |
| Abstract: | Only half of all startups survive past the age of five and surviving businesses grow at vastly different speeds. Using micro data on employment in the population of U.S. businesses, we estimate that the lion's share of these differences is driven by ex-ante heterogeneity across firms, rather than by ex-post shocks. We embed such heterogeneity in a firm dynamics model and study how ex-ante differences shape the distribution of firm size, ``up-or-out'' dynamics, and the associated gains in aggregate output. ``Gazelles'' --a small subset of startups with particularly high growth potential-- emerge as key drivers of these outcomes. Analyzing changes in the distribution of ex-ante firm heterogeneity over time reveals that the birth rate and growth potential of gazelles has declined, creating substantial aggregate losses. |
| Keywords: | Big Data; Firm Dynamics; Macroeconomics; Startups |
| JEL: | D22 E23 E24 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12670&r=tid |
| By: | Pellens, Maikel; Peters, Bettina; Hud, Martin; Rammer, Christian; Licht, Georg |
| Abstract: | The paper investigates the reaction of public R&D spending on economic crises. We are interested in two counteracting motives: On the one hand, public R&D spending can be seen as a means to fight the crisis, and governments may decide to increase their R&D budgets. On the other hand, a crisis reduces public income and urges governments to cut spending, which may negatively affect public R&D budgets. Using panel data from 26 OECD countries over the period 1995 to 2015, we investigate how public R&D expenditure changes over the business cycle for different types of government R&D expenditure. On average, we find evidence for a strong pro-cyclical effect on public R&D investments. But country heterogeneity matters. Whereas European innovation leaders and non-EU countries pursue a counter-cyclical strategy, innovation followers and moderate innovators behave pro-cyclical. This leads to an increasing innovation gap in Europe. Short-run and long-run financing conditions (budget surplus and government debt levels) also significantly affect public R&D spending. However, there is no evidence that economic crises systematically affect the composition of public R&D spending along different thematic areas or by beneficiaries. |
| Keywords: | public R&D expenditure,economic crisis,OECD,panel data |
| JEL: | H54 H12 H61 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:18005&r=tid |
| By: | Edquist, Charles (CIRCLE, Lund University) |
| Abstract: | A holistic innovation policy is defined in this article as a policy that integrates all public actions that influence or may influence innovation processes. The Swedish National Innovation Council (NIC) was created by the Swedish Prime Minister, Stefan Löfven, in February 2015. It is personally chaired by the Prime Minister, which is unusual for similar councils in other countries. Another atypical characteristic of the Swedish NIC is that it has a dominant and wide focus on innovation policy. In other countries, such councils focus predominantly on science and/or research policy and treat innovation policy, if at all, as an “appendix” to research policy. The purpose of this article is to answer the following four questions: A. Has Swedish innovation policy recently been moving in the direction of a more holistic innovation policy? If so, how and in what respects? B. Has the Swedish National Innovation Council (NIC) had an influence on Swedish innovation policy and has it played a role in the transition towards a holistic innovation policy? Which role and how? C. Have conceptual specifications and advancements, such as innovation systems (in a broad sense), functional public procurement, additionality, and holistic innovation policy played a role in the changes in Swedish innovation policy? D. Can Sweden serve as a role model for other countries in these respects? |
| Keywords: | Innovation; Innovation policy; Holistic innovation policy; Research policy; Linear view; Systems of innovation |
| JEL: | O30 O38 O49 O52 |
| Date: | 2018–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2018_002&r=tid |
| By: | Peters, Bettina; Riley, Rebecca R.; Siedschlag, Iulia; Vahter, Priit; McQuinni, John |
| Abstract: | This paper examines the links between internationalisation, innovation and productivity in service enterprises. For this purpose, we use micro data from the Community Innovation Survey 2008 in Germany, Ireland and the United Kingdom, and estimate an augmented structural model. Our empirical evidence highlights the importance of internationalisation in the context of innovation outputs in all three countries. Our results indicate that innovation in service enterprises is linked to higher productivity. Among the innovation types that we consider, the largest productivity returns were found for marketing innovations. |
| Keywords: | internationalisation of services,innovation,productivity |
| JEL: | L25 O31 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:18009&r=tid |
| By: | Grillitsch, Markus (Lund University) |
| Abstract: | This paper proposes a conceptual and analytical framework for the development of place-based entrepreneurship and innovation policies aiming at industrial diversification. The starting point for this paper is the entrepreneurial ecosystem concept, which is frequently used to inform such policies. However, this concept does not specify the causal mechanisms driving industrial diversification. Furthermore, it remains questionable to what extent the concept can be applied to different regional contexts. In order to address these shortfalls, this paper i) discusses the barriers and opportunities for industrial diversification in different regional contexts, and ii) introduces a place-based policy framework for new industrial path development through entrepreneurship and innovation policies. |
| Keywords: | economic diversification; new industrial path development; innovation; entrepreneurship; entrepreneurial ecosystems; place-based policy |
| JEL: | L50 O10 O30 O38 R10 R58 |
| Date: | 2018–02–06 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2018_003&r=tid |
| By: | Shandre Mugan Thangavelu; Wang Wenxiao; Sothea Oum |
| Abstract: | The paper studies the degree of servicification (or the role of services as inputs in manufacturing) of selected 61 Asian countries in terms of global value chain (GVC) activities at the sectoral level using domestic and foreign services from 1995 to 2011. We explore empirically the possible sources of servicification of the economies in terms of the factors driving the expansion of servicification. We categorize servicification activities into two types: (a) domestic servicification using domestic services and (b) foreign servicification using foreign value-added content in domestic exports. Servicification is confirmed in selected Asian countries, particularly in 16 East Asian countries associated with the Regional Comprehensive Economic Partnership (RCEP) negotiation. However, the selected Asian countries tend to have lower domestic servicification levels, but higher foreign servicification levels as compared to the overall sample of countries in the study. Countries with higher participation rates and lower positions in GVCs tend to have higher levels of foreign servicification across the sectors. In contrast, countries with higher participation rates and higher positions in GVCs tend to use more domestic services in manufacturing exports. The effect is larger for Asian countries as compared to the developed countries in the sample. The study also highlights the role of technical improvement and institutional as key factors in the development of services in the global production value chain. |
| Keywords: | global value chains, servicification, institutions, RCEP countries |
| JEL: | F14 F55 |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:era:wpaper:dp-2017-12&r=tid |
| By: | Barany, Zsofia; Siegel, Christian |
| Abstract: | To study the drivers of the employment reallocation across sectors and occupations between 1960 and 2010 in the US we propose a model where technology evolves at the sector-occupation cell level. Since the framework does not a priori impose a specific form of technological change, it allows us to quantify the respective role of sector-specific and of occupation-specific technological change. We implement a novel method to extract changes in sector-occupation cell productivities from the data. Using a factor model we find that occupation and sector factors jointly explain 74-87 percent of cell productivity changes, with the occupation component being by far the most important. While in our general equilibrium model both factors imply similar reallocations of labor across sectors and occupations, quantitatively the bias in technological change across occupations is much more important than the bias across sectors. |
| Keywords: | biased technological change; employment polarization; structural change |
| JEL: | J24 O33 O41 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12663&r=tid |
| By: | Lewis, Logan T. (Federal Reserve Board); Monarch, Ryan (Federal Reserve Board); Sposi, Michael J. (Federal Reserve Bank of Dallas); Zhang, Jing (Federal Reserve Bank of Chicago) |
| Abstract: | Since 1970, services has risen from 50 percent of the world’s final consumption expenditures to nearly 80 percent. Services are also far less traded between countries than goods. Thus, as consumers become more service-oriented, the world will become “less open”, affecting international trade volumes. Using a general equilibrium trade model with non-homothetic preferences and endogenous shifts in consumption behavior, we quantify the impact of such structural change on global trade across 27 countries. We find that world trade as a fraction of GDP would have been about 23 percentage points or 70 percent higher by 2015 if country-level expenditure patterns were unchanged from 1970 onwards. Income effects explain about one-quarter of this counterfactual. Without input-output linkages in production, the counterfactual increase in world trade with no structural change would be even greater. Finally, the process of structural transformation toward services systematically impedes the gains from trade. |
| JEL: | F41 L16 O41 |
| Date: | 2018–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:feddgw:333&r=tid |
| By: | Robert Seamans; Manav Raj |
| Abstract: | We summarize existing empirical findings regarding the adoption of robotics and AI and its effects on aggregated labor and productivity, and argue for more systematic collection of the use of these technologies at the firm level. Existing empirical work primarily uses statistics aggregated by industry or country, which precludes in-depth studies regarding the conditions under which robotics and AI complement or are substituting for labor. Further, firm-level data would also allow for studies of effects on firms of different sizes, the role of market structure in technology adoption, the impact on entrepreneurs and innovators, and the effect on regional economies amongst others. We highlight several ways that such firm-level data could be collected and used by academics, policymakers and other researchers. |
| JEL: | B4 O3 O4 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24239&r=tid |
| By: | James Bessen |
| Abstract: | Artificial intelligence (AI) technologies will automate many jobs, but the effect on employment is not obvious. In manufacturing, technology has sharply reduced jobs in recent decades. But before that, for over a century, employment grew, even in industries experiencing rapid technological change. What changed? Demand was highly elastic at first and then became inelastic. The effect of artificial intelligence on jobs will similarly depend critically on the nature of demand. This paper presents a simple model of demand that accurately predicts the rise and fall of employment in the textile, steel and automotive industries. This model provides a useful framework for exploring how AI is likely to affect jobs over the next 10 or 20 years. |
| JEL: | J2 N10 O3 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24235&r=tid |
| By: | Matt Taddy |
| Abstract: | We have seen in the past decade a sharp increase in the extent that companies use data to optimize their businesses. Variously called the `Big Data' or `Data Science' revolution, this has been characterized by massive amounts of data, including unstructured and nontraditional data like text and images, and the use of fast and flexible Machine Learning (ML) algorithms in analysis. With recent improvements in Deep Neural Networks (DNNs) and related methods, application of high-performance ML algorithms has become more automatic and robust to different data scenarios. That has led to the rapid rise of an Artificial Intelligence (AI) that works by combining many ML algorithms together – each targeting a straightforward prediction task – to solve complex problems. We will define a framework for thinking about the ingredients of this new ML-driven AI. Having an understanding of the pieces that make up these systems and how they fit together is important for those who will be building businesses around this technology. Those studying the economics of AI can use these definitions to remove ambiguity from the conversation on AI's projected productivity impacts and data requirements. Finally, this framework should help clarify the role for AI in the practice of modern business analytics and economic measurement. |
| JEL: | C01 C1 O33 |
| Date: | 2018–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24301&r=tid |