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on Innovation |
| By: | Tom Kemeny; Sergio Petralia; Michael Storper |
| Abstract: | Although technological change is widely credited as driving the last two hundred years of economic growth, its role in shaping patterns of inequality remains under-explored. Drawing parallels across two industrial revolutions in the United States, this paper provides new evidence of a relationship between highly disruptive forms of innovation and spatial inequality. Using the universe of patents granted between 1920 and 2010 by the U.S. Patent and Trademark Office, we identify disruptive innovations through their rapid growth, complementarity with other innovations, and widespread use. We then assign more- and less-disruptive innovations to subnational regions in the geography of the U.S. We document three findings that are new to the literature. First, disruptive innovations exhibit distinctive spatial clustering in phases understood to be those in which industrial revolutions reshape the economy; they are increasingly dispersed in other periods. Second, we discover that the ranks of locations that capture the most disruptive innovation are relatively unstable across industrial revolutions. Third, regression estimates suggest a role for disruptive innovation in regulating overall patterns of spatial output and income inequality |
| Keywords: | technological change; regional development; industrial revolutions; innovation; inequality |
| JEL: | O30 O33 O51 J31 |
| Date: | 2022–07 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2211&r= |
| By: | Giotopoulos, Ioannis; Kritikos, Alexander S.; Tsakanikas, Aggelos |
| Abstract: | We use the prolonged Greek crisis as a case study to understand how a lasting economic shock affects the innovation strategies of firms in economies with moderate innovation activities. Adopting the 3-stage CDM model, we explore the link between R&D, innovation, and productivity for different size groups of Greek manufacturing firms during the prolonged crisis. At the first stage, we find that the continuation of the crisis is harmful for the R&D engagement of smaller firms while it increased the willingness for R&D activities among the larger ones. At the second stage, among smaller firms the knowledge production remains unaffected by R&D investments, while among larger firms the R&D decision is positively correlated with the probability of producing innovation, albeit the relationship is weakened as the crisis continues. At the third stage, innovation output benefits only larger firms in terms of labor productivity, while the innovation-productivity nexus is insignificant for smaller firms during the lasting crisis. |
| Keywords: | Small firms,Large firms,R&D,Innovation,Productivity,Long-term Crisis |
| JEL: | L25 L60 O31 O33 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:1122&r= |
| By: | Sander Sõna; Jaan Masso; Shakshi Sharma; Priit Vahter; Rajesh Sharma |
| Abstract: | This paper investigates which of the core types of innovation can be best predicted based on the website data of firms. In particular, we focus on four distinct key standard types of innovation – product, process, organisational, and marketing innovation in firms. Web-mining of textual data on the websites of firms from Estonia combined with the application of artificial intelligence (AI) methods turned out to be a suitable approach to predict firm-level innovation indicators. The key novel addition to the existing literature is the finding that web-mining is more applicable to predicting marketing innovation than predicting the other three core types of innovation. As AI based models are often black-box in nature, for transparency, we use an explainable AI approach (SHAP - SHapley Additive exPlanations), where we look at the most important words predicting a particular type of innovation. Our models confirm that the marketing innovation indicator from survey data was clearly related to marketing-related terms on the firms' websites. In contrast, the results on the relevant words on websites for other innovation indicators were much less clear. Our analysis concludes that the effectiveness of web-scraping and web-text-based AI approaches in predicting cost-effective, granular and timely firm-level innovation indicators varies according to the type of innovation considered. |
| Keywords: | Innovation, Marketing Innovation, Community Innovation Survey (CIS), Machine learning, Neural network, Explainable AI, SHAP |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:mtk:febawb:143&r= |
| By: | Góes, Carlos; Bekkers, Eddy |
| Abstract: | Geopolitical conflicts have increasingly been a driver of trade policy. We study the potential effects of global and persistent geopolitical conflicts on trade, technological innovation, and economic growth. In conventional trade models the welfare costs of such conflicts are modest. We build a multi-sector multi-region general equilibrium model with dynamic sector-specific knowledge diffusion, which magnifies welfare losses of trade conflicts. Idea diffusion is mediated by the input-output structure of production, such that both sector cost shares and import trade shares characterize the source distribution of ideas. Using this framework, we explore the potential impact of a "decoupling of the global economy," a hypothetical scenario under which technology systems would diverge in the global economy. We divide the global economy into two geopolitical blocs -East and West -based on foreign policy similarity and model decoupling through an increase in iceberg trade costs (full decoupling) or tariffs (tariff decoupling). Results yield three main insights. First, the projected welfare losses for the global economy of a decoupling scenario can be drastic, as large as 12% in some regions and are largest in the lower income regions as they would benefit less from technology spillovers from richer areas. Second, the described size and pattern of welfare effects are specific to the model with diffusion of ideas. Without diffusion of ideas the size and variation across regions of the welfare losses would be substantially smaller. Third, a multi-sector framework exacerbates diffusion inefficiencies induced by trade costs relative to a single-sector one. |
| Keywords: | Innovation,International trade,international relations |
| JEL: | F12 F13 O33 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:wtowps:ersd20229&r= |
| By: | Mundt, Philipp; Savin, Ivan |
| Abstract: | We revisit the debate on the role of technological improvement and market share reallocation in determining aggregate productivity gains. Contrary to previous work that neglects dependencies between suppliers in global value chains, we explicitly account for input linkages that impact both channels of productivity improvement. Using sector-level data from the World Input-Output Database, we show that market share reallocation has a markedly larger effect on productivity change than innovation. |
| Keywords: | input-output analysis,market share reallocation,productivity decomposition,production network,technological improvement |
| JEL: | C67 E24 L14 L16 O47 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bamber:179&r= |