Michael D. McCarthy

426 citations
27 papers · 251 · h-index 11

Impact in

Papers in

Michael D. McCarthy

27 papers receiving 191 citations

Peers

Michael D. McCarthy
Comparison fields: 5 of 72
  • General Economics, Econometrics and Finance 104
  • Economics and Econometrics 125
  • Finance 28
  • Management Science and Operations Research 23
  • Statistics and Probability 13
Replace Péter Erdős with:
Péter Erdős Hungary
Leopold Sögner Austria
Charles Nelson United States
Regina Kaiser Spain
Kiyoshi Kuga Japan
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Dawn Hunter United Kingdom
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Sergey Slobodyan Czechia
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Citations per field
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Citations per year

Countries citing papers authored by Michael D. McCarthy

Since Specialization
Citations

This map shows the geographic impact of Michael D. McCarthy'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 Michael D. McCarthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. McCarthy more than expected).

Fields of papers citing papers by Michael D. McCarthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. McCarthy. 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 Michael D. McCarthy. The network helps show where Michael D. McCarthy may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael D. McCarthy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael D. McCarthy Line = papers co-authored together Michael D. McCarthy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 197335
2 197429
3 197324
4 197220
5 201218
6 196717
7 201913
8 197413
9 196513
10 197112
11 197410
12 20109
13 20128
14 19785
15
The Use of Almon- and Other Dummy Variable Procedures to Increase the Efficiency of Maximization Algorithms in Economic Control
19774
16 19923
17 20092
18 19782
19 19672
20 19662

About Michael D. McCarthy

Michael D. McCarthy is a scholar working on Economics and Econometrics, General Economics, Econometrics and Finance, Clinical Psychology, Applied Mathematics and Infectious Diseases, having authored 27 papers that have together received 251 indexed citations. Recurring topics across this work include Statistical and numerical algorithms (3 papers), Economic Growth and Productivity (3 papers), Economic theories and models (2 papers), Posttraumatic Stress Disorder Research (2 papers), Economic Theory and Policy (2 papers), Monetary Policy and Economic Impact (2 papers), Child Abuse and Trauma (1 paper) and American and British Literature Analysis (1 paper). The work is most often cited by research in General Economics, Econometrics and Finance (104 citations), Economics and Econometrics (125 citations), Finance (28 citations), Management Science and Operations Research (23 citations) and Statistics and Probability (13 citations). Michael D. McCarthy has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Michael D. Hurd, Lawrence R. Klein, Ray C. Fair, E. Philip Howrey, Sanna J. Thompson, Kerry L. Knox, Vijaya G. Duggal, Kenneth R. Conner, Eric D. Caine and Xin Tu. Their work appears in journals such as International Economic Review, The Review of Economics and Statistics, Journal of the American Statistical Association, Journal of Econometrics and The Journal of Finance.

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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