Sylvia Kaufmann
- Economics and Econometrics top 5%
- General Economics, Econometrics and Finance top 2%
- Finance top 5%
- Artificial Intelligence
- Statistics and Probability top 5%
- Co-authors
- Sylvia Frühwirth‐SchnatterJohann ScharlerChristian SchumacherUwe DulleckMaría Teresa ValderramaGeorg WincklerPeter KüglerMartin Scheicher
- Topics
- Monetary Policy and Economic Impact (24 papers)Italy: Economic History and Contemporary Issues (8 papers)Banking stability, regulation, efficiency (8 papers)
- Partner nations
- AustriaSwitzerlandGermany
In The Last Decade
Sylvia Kaufmann
31 papers receiving 522 citations
Peers
Comparison fields: 5 of 67
- Economics and Econometrics 330
- General Economics, Econometrics and Finance 263
- Finance 221
- Artificial Intelligence 80
- Statistics and Probability 65
Countries citing papers authored by Sylvia Kaufmann
This map shows the geographic impact of Sylvia Kaufmann's 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 Sylvia Kaufmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sylvia Kaufmann more than expected).
Fields of papers citing papers by Sylvia Kaufmann
This network shows the impact of papers produced by Sylvia Kaufmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sylvia Kaufmann. The network helps show where Sylvia Kaufmann may publish in the future.
Co-authorship network of co-authors of Sylvia Kaufmann
This figure shows the co-authorship network connecting the top 25 collaborators of Sylvia Kaufmann. A scholar is included among the top collaborators of Sylvia Kaufmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sylvia Kaufmann. Sylvia Kaufmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 31 | |
| 7 | 6 | |
| 8 | 23 | |
| 9 | 20 | |
| 10 | 3 | |
| 11 | 117 | |
| 12 | 20 | |
| 13 | 5 | |
| 14 | 13 | |
| 15 | 9 | |
| 16 | Growth and Stability in the EU | 1 |
| 17 | 26 | |
| 18 | The Role of Bank Lending in Market-Based and Bank-Based Financial Systems | 3 |
| 19 | 42 | |
| 20 | 2 |
About Sylvia Kaufmann
Sylvia Kaufmann is a scholar working on Computational Mathematics, General Economics, Econometrics and Finance and Finance, having authored 33 papers that have together received 571 indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (24 papers), Italy: Economic History and Contemporary Issues (8 papers) and Banking stability, regulation, efficiency (8 papers). The work is most often cited by research in General Economics, Econometrics and Finance (263 citations), Finance (221 citations) and Computational Mathematics (12 citations). Sylvia Kaufmann has collaborated with scholars based in Austria, Switzerland and Germany. Frequent co-authors include Sylvia Frühwirth‐Schnatter, Johann Scharler, Christian Schumacher, Uwe Dulleck, María Teresa Valderrama, Georg Winckler, Peter Kügler, Martin Scheicher, Monica Billio and Roberto Casarin. Their work appears in journals such as Energy Policy, Journal of Econometrics and Journal of Business and Economic Statistics.
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.