Shock-Based Causal Inference in Corporate Finance and Accounting Research
- Journal
- RePEc: Research Papers in Economics
In The Last Decade
doi.org/10.1561/104.00000036 →Countries where authors are citing Shock-Based Causal Inference in Corporate Finance and Accounting Research
This map shows the geographic impact of Shock-Based Causal Inference in Corporate Finance and Accounting Research. 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 Shock-Based Causal Inference in Corporate Finance and Accounting Research with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shock-Based Causal Inference in Corporate Finance and Accounting Research more than expected).
Fields of papers citing Shock-Based Causal Inference in Corporate Finance and Accounting Research
This network shows the impact of Shock-Based Causal Inference in Corporate Finance and Accounting Research. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Shock-Based Causal Inference in Corporate Finance and Accounting Research.
About Shock-Based Causal Inference in Corporate Finance and Accounting Research
This paper, published in 2016, received 334 indexed citations . Written by Vladimir A. Atanasov and Bernard S. Black covering the research area of Safety Research, Economics and Econometrics and Accounting. It is primarily cited by scholars working on Accounting (268 citations), Finance (109 citations) and Economics and Econometrics (102 citations). Published in RePEc: Research Papers in Economics.
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/10.1561/104.00000036.