Computational Economics

2.1k papers and 19.7k indexed citations

About

The 2.1k papers published in Computational Economics in the last decades have received a total of 19.7k indexed citations. Papers published in Computational Economics usually cover Economics and Econometrics (1.1k papers), Finance (704 papers) and Management Science and Operations Research (645 papers) specifically the topics of Complex Systems and Time Series Analysis (407 papers), Market Dynamics and Volatility (341 papers) and Monetary Policy and Economic Impact (340 papers). The most active scholars publishing in Computational Economics are Christopher A. Sims, Thomas F. Rutherford, Ken Pearson, W. Jill Harrison, Thomas Lux, Manfred Gilli, Evis Këllezi, Giorgio Fagiolo, Joshua M. Epstein and Daniel Fricke.

In The Last Decade

Computational Economics

1.7k papers receiving 18.4k citations

Fields of papers published in Computational Economics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computational Economics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Computational Economics.

Countries where authors publish in Computational Economics

Since Specialization
Citations

This map shows the geographic impact of research published in Computational Economics. 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 papers published in Computational Economics with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computational Economics more than expected).

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.

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2026