The Global Macroeconomic Impacts of COVID-19: Seven Scenarios
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- SSRN Electronic Journal
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doi.org/10.2139/ssrn.3547729 →Countries where authors are citing The Global Macroeconomic Impacts of COVID-19: Seven Scenarios
This map shows the geographic impact of The Global Macroeconomic Impacts of COVID-19: Seven Scenarios. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by The Global Macroeconomic Impacts of COVID-19: Seven Scenarios with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The Global Macroeconomic Impacts of COVID-19: Seven Scenarios more than expected).
Fields of papers citing The Global Macroeconomic Impacts of COVID-19: Seven Scenarios
This network shows the impact of The Global Macroeconomic Impacts of COVID-19: Seven Scenarios. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The Global Macroeconomic Impacts of COVID-19: Seven Scenarios.
About The Global Macroeconomic Impacts of COVID-19: Seven Scenarios
This paper, published in 2020, received 994 indexed citations . Written by Warwick J. McKibbin and Roshen Fernando covering the research area of Global and Planetary Change, Economics and Econometrics and Modeling and Simulation. It is primarily cited by scholars working on Economics and Econometrics (592 citations), Modeling and Simulation (253 citations) and Sociology and Political Science (152 citations). Published in SSRN Electronic Journal.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.2139/ssrn.3547729.