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.
This map shows the geographic impact of Antonio Fatás'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 Antonio Fatás with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonio Fatás more than expected).
This network shows the impact of papers produced by Antonio Fatás. 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 Antonio Fatás. The network helps show where Antonio Fatás may publish in the future.
Co-authorship network of co-authors of Antonio Fatás
This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Fatás.
A scholar is included among the top collaborators of Antonio Fatás 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 Antonio Fatás. Antonio Fatás is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cerra, Valerie, Antonio Fatás, & Sweta Saxena. (2021). Fighting the scarring effects of COVID-19. Industrial and Corporate Change. 30(2). 459–466.2 indexed citations
5.
Bénassy‐Quéré, Agnès, Giancarlo Corsetti, Antonio Fatás, et al.. (2020). COVID-19 economic crisis : Europe needs more than one instrument. Cadmus - EUI Research Repository (European University Institute).4 indexed citations
Fatás, Antonio, et al.. (2009). EMU efter tio år : ska Danmark, Sverige och Storbritannien ansluta sig?. Medical Entomology and Zoology.
8.
Irwin, Timothy, Federico Sturzenegger, Guillermo Perry, et al.. (2008). Fiscal Policy, Stabilization, and Growth : Prudence or Abstinence. World Bank Publications.22 indexed citations
9.
Fatás, Antonio, Ilian Mihov, & Andrew K. Rose. (2007). Quantitative Goals for Monetary Policy. Journal of money credit and banking. 39(5). 1163–1176.50 indexed citations
10.
Fatás, Antonio & Ilian Mihov. (2005). Policy Volatility, Institutions and Economic Growth. SSRN Electronic Journal.32 indexed citations
11.
Fatás, Antonio & Ilian Mihov. (2004). The Macroeconomic Effects of Fiscal Rules in the US States. SSRN Electronic Journal.9 indexed citations
Fatás, Antonio. (2002). The Effects of Bussiness Cycles on Growth. RePEc: Research Papers in Economics. 6. 191–220.37 indexed citations
15.
Begg, Iain, Fabio Canova, Paul De Grauwe, Antonio Fatás, & Philip R. Lane. (2002). Surviving the slowdown. London School of Economics and Political Science Research Online (London School of Economics and Political Science).18 indexed citations
16.
Fatás, Antonio & Ilian Mihov. (2002). The Case for Restricting Fiscal Policy Discretion. SSRN Electronic Journal.38 indexed citations
17.
Fatás, Antonio & Ilian Mihov. (2001). Política Fiscal y Ciclos Económicos: Una Investigación Empírica. Moneda y crédito. 167–210.1 indexed citations
18.
Fatás, Antonio & Andrew K. Rose. (2001). Do Monetary Handcuffs Restrain Leviathan? Fiscal Policy in Extreme Exchange Rate Regimes. RePEc: Research Papers in Economics.15 indexed citations
Fatás, Antonio. (1997). EMU: Countries or Regions? Lessons from the EMS Experience. SSRN Electronic Journal.12 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.