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on Economic Growth |
| By: | Erik Hornung (University of Cologne); Julius Koschnick (London School of Economics); Francesco Cinnirella (University of Bergamo) |
| Abstract: | Sustained technological progress was at the heart of the Industrial Revolution. This column argues that access to knowledge was crucial for innovation and technological diffusion during this period. Inventors and entrepreneurs needed access to useful knowledge to generate new ideas and continue innovating. Such access was provided by the ‘economic societies’ – associations of individuals interested in improving the local economy. These societies became drivers of knowledge diffusion and innovation. |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:ajk:ajkpbs:041&r=gro |
| By: | Simon Bruhn; Thomas Grebel; Lionel Nesta (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po) |
| Abstract: | This paper argues that the typical practice of performing growth decompositions based on log-transformed productivity values induces fallacious conclusions: using logs may lead to an inaccurate aggregate growth rate, an inaccurate description of the microsources of aggregate growth, or both. We identify the mathematical sources of this log-induced fallacy in decomposition and analytically demonstrate the questionable reliability of log results. Using firm-level data from the French manufacturing sector during the 2009-2018 period, we empirically show that the magnitude of the log-induced distortions is substantial. Depending on the definition of accurate log measures, we find that around 60-80% of four-digit industry results are prone to mismeasurement. We further find significant correlations of this mismeasurement with commonly deployed industry characteristics, indicating, among other things, that less competitive industries are more prone to log distortions. Evidently, these correlations also affect the validity of studies that investigate the role of industry characteristics in productivity growth. |
| Keywords: | productivity decomposition, growth, log approximation, geometric mean, arithmetic mean |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:hal:spmain:hal-03474838&r=gro |
| By: | Takao Asano (Okayama University); Akihisa Shibata (Kyoto University); Masanori Yokoo (Okayama University) |
| Abstract: | We incorporate the external effects of capital in production and endogenous technology choice into the standard overlapping generations model. We demonstrate that our model can exhibit a poverty trap, a middle-income trap, and perpetual growth paths. We also show that, under some economic conditions, an economy exhibits all three of these phenomena, depending on its initial capital level, and that the economy caught in the middle-income trap can exhibit chaotic fluctuations in the long run. In obtaining these results in the standard overlapping generations model, the combination of technology choice and externalities in production plays a crucial role. |
| Keywords: | External effect; Technology choice; Overlapping generations model, Middle-income trap; Chaos |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:kyo:wpaper:1090&r=gro |
| By: | Bergeaud, Antonin; Verluise, Cyril |
| Abstract: | Innovation is an important driver of potential growth but quantitative evidence on the dynamics of innovative activities in the long-run are hardly documented due to the lack of data, especially in Europe. In this paper, we introduce PatentCity, a novel dataset on the location and nature of patentees from the 19th century using information derived from an automated extraction of relevant information from patent documents published by the German, French, British and US Intellectual Property offices. This dataset has been constructed with the view of facilitating the exploration of the geography of innovation and includes additional information on citizenship and occupation of inventors. |
| Keywords: | history of innovation; patent; text as data |
| JEL: | R14 J01 J1 |
| Date: | 2022–04–28 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:117858&r=gro |
| By: | Wang, Shanchao; Alston, Julian M.; Pardey, Philip G. |
| Abstract: | Quite different R&D lag structures predominate in studies of agricultural R&D compared with studies of R&D in other industries, and compared with studies of economic growth more broadly. Here we compare the main models and their implications using long-run data for U.S. agriculture. We reject the models predominantly used in studies of economic growth and industrial R&D both on prior grounds and using various statistical tests. The preferred model is a 50-year gamma lag distribution model. The estimated elasticity of MFP with respect to the knowledge stock is 0.28 and the implied marginal benefit-cost ratio is 23:1. |
| Keywords: | Agricultural and Food Policy, Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods |
| Date: | 2023–01–21 |
| URL: | http://d.repec.org/n?u=RePEc:ags:umaesp:330085&r=gro |