Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Network topology of the interbank market
2004534 citationsMichael Boss, Helmut Elsinger et al.Quantitative Financeprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Martin Summer'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 Martin Summer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Summer more than expected).
This network shows the impact of papers produced by Martin Summer. 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 Martin Summer. The network helps show where Martin Summer may publish in the future.
Co-authorship network of co-authors of Martin Summer
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Summer.
A scholar is included among the top collaborators of Martin Summer 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 Martin Summer. Martin Summer is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Pichler, Paul, Martin Summer, & Beat Weber. (2020). Does digitalization require Central Bank Digital Currencies for the general public. RePEc: Research Papers in Economics. 40–56.4 indexed citations
2.
Agur, Itai, Michael D. Bordo, Alessandra Cillo, et al.. (2018). Do We Need Central Bank Digital Currency? Economics, Technology and Institutions. RePEc: Research Papers in Economics.6 indexed citations
3.
Summer, Martin, et al.. (2017). The financial system of the future. RePEc: Research Papers in Economics. 34–42.
Breuer, Thomas, et al.. (2009). How to Find Plausible, Severe and Useful Stress Scenarios. Repository of the University of Ljubljana (University of Ljubljana).52 indexed citations
9.
Summer, Martin. (2008). The Financial Crisis in 2007 and 2008 Viewed from the Perspective of Economic Research. RePEc: Research Papers in Economics. 85–100.1 indexed citations
10.
Summer, Martin. (2008). The Economics of Financial Stability: Research Workshop at the OeNB. RePEc: Research Papers in Economics. 104–112.1 indexed citations
Elsinger, Helmut, Alfred Lehar, & Martin Summer. (2005). Using Market Information for Banking System Risk Assessment. International journal of central banking. 2(1).4 indexed citations
15.
Eichberger, Jürgen & Martin Summer. (2005). Bank Capital, Liquidity, and Systemic Risk. Journal of the European Economic Association. 3(2-3). 547–555.27 indexed citations
16.
Boss, Michael, Helmut Elsinger, Martin Summer, & Stefan Thurner. (2004). Network topology of the interbank market. Quantitative Finance. 4(6). 677–684.534 indexed citations breakdown →
Boss, Michael, Helmut Elsinger, Martin Summer, & Stefan Thurner. (2003). An Empirical Analysis of the Network Structure of the Austrian Interbank Market 1. RePEc: Research Papers in Economics. 77–87.45 indexed citations
Summer, Martin. (1984). THE IMPACT OF STOCK RELIEF. Oxford Bulletin of Economics and Statistics. 46(2). 169–179.3 indexed citations
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.