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on Economic Geography |
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Issue of 2022‒07‒11
seven papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Duygu Buyukyazici; Leonardo Mazzoni; Massimo Riccaboni; Francesco Serti |
| Abstract: | The literature reaches a unanimous agreement that industrial diversification is path-dependent because new industries build on preexisting capabilities of regions that are partly embodied and reflected in the skills of regions’ workforce. This paper explicitly accounts for regional capabilities as workforce skills to build skill relatedness and complexity measures, skill-spaces, for 107 Italian regions for the period 2013-2019. Data-driven techniques we use reveal that skill-spaces form two highly polarised clusters into social-cognitive and technical-physical skills. We show that industries have a higher (lower) probability of developing comparative advantage if their required skill set is (not) similar to those available in the region regardless of the skill type. We find evidence that similarity to technical-physical skills and higher complexity in social cognitive skills yields the highest probabilities of regional competitive advantage. |
| Keywords: | Skill relatedness; Economic complexity; Industrial specialisation; Regional capabilities; Regional diversification. |
| JEL: | J24 O18 R10 R23 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2210&r= |
| By: | Mairi Spowage; Sharada Nia Davidson |
| Abstract: | The UK's departure from the EU as well as increased devolution have heightened the policy requirement for data on interregional trade. This paper develops a framework for interregional trade data collection and estimation in the UK by: (i) reviewing the academic literature and current international practise, (ii) contrasting the trade surveys currently deployed by the four nations of the UK, (iii) undertaking a series of webinars and interviews to explore businesses’ perceptions of trade surveys and (iv) illustrating how interregional trade statistics consistent with the national accounts can be constructed. We provide a number of recommendations for collecting interregional trade data including the introduction of a new survey or survey questions to capture trade flows between England and the remaining three nations of the UK. |
| Keywords: | interregional trade flows, origin destination data, regional supply use tables, trade surveys |
| JEL: | C83 F15 F17 R12 |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:nsr:escoet:escoe-tr-13&r= |
| By: | Tsang, Andrew |
| Abstract: | This paper applies causal machine learning methods to analyze the heterogeneous regional impacts of monetary policy in China. The method uncovers the heterogeneous regional impacts of different monetary policy stances on the provincial figures for real GDP growth, CPI inflation and loan growth compared to the national averages. The varying effects of expansionary and contractionary monetary policy phases on Chinese provinces are highlighted and explained. Subsequently, applying interpretable machine learning, the empirical results show that the credit channel is the main channel affecting the regional impacts of monetary policy. An imminent conclusion of the uneven provincial responses to the "one size fits all" monetary policy is that different policymakers should coordinate their efforts to search for the optimal fiscal and monetary policy mix. |
| Keywords: | China,monetary policy,regional heterogeneity,machine learning,shadow banking |
| JEL: | E52 C54 R11 E61 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:uhhwps:62&r= |
| By: | Stefan Jestl (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | This paper explores the effects of industrial robots and information and communication technology (ICT) on regional employment in EU countries. The empirical analysis relies on a harmonised comprehensive regional dataset, which combines business statistics and national and regional accounts data. This rich dataset enables us to provide detailed insights into the employment effects of automation and computerisation in EU regions for the period 2001-2016. The results suggest relatively weak effects on regional total employment dynamics. However, employment effects differ between manufacturing and non-manufacturing industries. Industrial robots show negative employment effects in local manufacturing industries, but positive employment effects in local non-manufacturing industries. While the negative effect is concentrated in particular local manufacturing industries, the positive effect operates in local service industries. IT investments show positive employment effects only in local manufacturing industries, while CT investments are shown to be irrelevant for employment dynamics. In contrast, software and database investments have had a predominantly negative impact on local employment in both local manufacturing and non-manufacturing industries. |
| Keywords: | Industrial robots, ICT, EU labour markets, employment effects |
| JEL: | J23 L60 O33 R11 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:wii:wpaper:215&r= |
| By: | Chowdhury, Farhat (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics); van Hasselt, Martijn (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | A spatial distributional analysis of the population of Phase II research projects funded by the U.S. SBIR program in FY 2020 shows differences across states in projects focused on Artificial Intelligence (AI). AI is a relatively new research field, and this paper contributes to a better understanding of government support for such research. We find that AI projects are concentrated in states with complementary AI research resources available from universities nationally ranked in terms of their own AI research. To achieve a more diverse spatial distribution of AI-related technology development, the availability of complementary AI research resources must be expanded. We suggest that the National Science Foundation’s National AI Research Institutes represents an important step in this direction. |
| Keywords: | Artificial intelligence (AI); Public sector program management; Small Business Innovation Research (SBIR); Agglomeration; University research; |
| JEL: | H54 O31 O38 R11 |
| Date: | 2022–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2022_004&r= |
| By: | Antonin Bergeaud; Cyril Verluise |
| 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 |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1850&r= |
| By: | Robert Lehmann; Ida Wikman |
| Abstract: | To date, only annual information on economic activity is published for the 16 German states. In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to 2020, thereby improving the regional database in Germany. The new data set will regularly be updated when quarterly economic growth for Germany becomes available. We use the new data for an in-depth business cycle analysis and find large heterogeneities in the duration and amplitudes of state-specific business cycles as well as in the degrees of cyclical concordance. |
| Keywords: | Regional economic activity, mixed-frequency vectorautoregression, concordance, regional business cycles, Bayesian methods |
| JEL: | C32 C53 E32 R11 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ifowps:_370&r= |