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Report NEP-GEO-2021-10-25
This is the archive for NEP-GEO, a report on new working papers in the area of Economic Geography. Andreas Koch issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-GEO
The following items were announced in this report:
- Anthony Frigon & David L. Rigby, 2021, "Geographies of Knowledge Sourcing and the Value of Knowledge in Multilocational Firms," Papers in Evolutionary Economic Geography (PEEG), Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, number 2132, Oct, revised Oct 2021.
- Hervás-oliver, José-luis & Parrilli, Mario Davide & Rodríguez-pose, Andrés & Sempere-ripoll, Francisca, 2021, "The drivers of SME innovation in the regions of the EU," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 112486, Nov.
- Moritz Kuhn & Iourii Manovskii & Xincheng Qiu, 2021, "The Geography of Job Creation and Job Destruction," ECONtribute Discussion Papers Series, University of Bonn and University of Cologne, Germany, number 122, Oct.
- David Card & Jesse Rothstein & Moises Yi, 2021, "Location, Location, Location," Working Papers, Center for Economic Studies, U.S. Census Bureau, number 21-32, Oct.
- Richard Bluhm & Christian Lessmann & Paul Schaudt, 2021, "The Political Geography of Cities," SoDa Laboratories Working Paper Series, Monash University, SoDa Laboratories, number 2021-11, Oct.
- Florian Bonnet & Aurélie Sotura, 2021, "Regional Income Distributions in France,1960 2018," Working papers, Banque de France, number 832.
- Daniel Meierrieks & David Stadelmann, 2021, "Is temperature adversely related to economic growth? Evidence on the short-run and the long-run links from sub-national data," CREMA Working Paper Series, Center for Research in Economics, Management and the Arts (CREMA), number 2021-36, Oct.
- Zhu, Di & Liu, Yu & Yao, Xin & Fischer, Manfred M., 2021, "Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions," Working Papers in Regional Science, WU Vienna University of Economics and Business, number 2021/02, Oct.
- Kyle Butts, 2021, "Difference-in-Differences with Geocoded Microdata," Papers, arXiv.org, number 2110.10192, Oct.