Brendan McCabe

2.4k total citations
65 papers, 1.6k citations indexed

About

Brendan McCabe is a scholar working on Statistics and Probability, Finance and General Economics, Econometrics and Finance. According to data from OpenAlex, Brendan McCabe has authored 65 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Statistics and Probability, 28 papers in Finance and 26 papers in General Economics, Econometrics and Finance. Recurrent topics in Brendan McCabe's work include Monetary Policy and Economic Impact (26 papers), Financial Risk and Volatility Modeling (26 papers) and Advanced Statistical Methods and Models (21 papers). Brendan McCabe is often cited by papers focused on Monetary Policy and Economic Impact (26 papers), Financial Risk and Volatility Modeling (26 papers) and Advanced Statistical Methods and Models (21 papers). Brendan McCabe collaborates with scholars based in United Kingdom, Australia and Canada. Brendan McCabe's co-authors include Stephen J. Leybourne, R. Keith Freeland, David Harris, Michael Harrison, A. R. Tremayne, Gael M. Martin, Ruijun Bu, Kaddour Hadri, Terence C. Mills and Garry D.A. Phillips and has published in prestigious journals such as Journal of the American Statistical Association, Biometrika and The Review of Economics and Statistics.

In The Last Decade

Brendan McCabe

60 papers receiving 1.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Brendan McCabe United Kingdom 23 764 750 682 571 230 65 1.6k
Jean‐Marie Dufour Canada 24 718 0.9× 1.2k 1.6× 1.1k 1.6× 763 1.3× 212 0.9× 106 2.3k
Herman J. Bierens United States 23 765 1.0× 1.2k 1.7× 1.1k 1.6× 798 1.4× 195 0.8× 64 2.3k
Zhijie Xiao United States 22 1.0k 1.3× 1.6k 2.1× 979 1.4× 629 1.1× 199 0.9× 104 2.5k
Marine Carrasco Canada 17 706 0.9× 517 0.7× 495 0.7× 424 0.7× 126 0.5× 39 1.2k
Juan Carlos Escanciano United States 20 709 0.9× 661 0.9× 386 0.6× 523 0.9× 136 0.6× 63 1.3k
Chung‐Ming Kuan Taiwan 19 801 1.0× 1.2k 1.6× 642 0.9× 213 0.4× 510 2.2× 63 2.0k
Ulrich K. Müller United States 20 530 0.7× 767 1.0× 734 1.1× 448 0.8× 112 0.5× 45 1.4k
Benedikt M. Pötscher Austria 20 467 0.6× 631 0.8× 496 0.7× 951 1.7× 270 1.2× 53 1.9k
Yuichi Kitamura United States 19 393 0.5× 521 0.7× 399 0.6× 698 1.2× 135 0.6× 55 1.6k
T. W. Epps United States 17 1.3k 1.8× 1.1k 1.5× 289 0.4× 408 0.7× 230 1.0× 34 1.9k

Countries citing papers authored by Brendan McCabe

Since Specialization
Citations

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

Fields of papers citing papers by Brendan McCabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brendan McCabe. 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 Brendan McCabe. The network helps show where Brendan McCabe may publish in the future.

Co-authorship network of co-authors of Brendan McCabe

This figure shows the co-authorship network connecting the top 25 collaborators of Brendan McCabe. A scholar is included among the top collaborators of Brendan McCabe 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 Brendan McCabe. Brendan McCabe 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.
Silva, Maria Eduarda, et al.. (2023). Time Series of Counts under Censoring: A Bayesian Approach. Entropy. 25(4). 549–549.
2.
Sun, Jiajing, Yuying Sun, Xinyu Zhang, & Brendan McCabe. (2021). Model Averaging of Integer-Valued Autoregressive Model With Covariates. SSRN Electronic Journal. 2 indexed citations
3.
McCabe, Brendan & Christopher L. Skeels. (2020). Distributions You Can Count On …But What’s the Point?. Econometrics. 8(1). 9–9. 1 indexed citations
4.
Harris, David & Brendan McCabe. (2018). SEMIPARAMETRIC INDEPENDENCE TESTING FOR TIME SERIES OF COUNTS AND THE ROLE OF THE SUPPORT. Econometric Theory. 35(6). 1111–1145. 1 indexed citations
5.
McCabe, Brendan, et al.. (2017). The Effect of Regression Design on Optimal Tests for Finding Break Positions. SSRN Electronic Journal.
6.
Forbes, Catherine, et al.. (2013). Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models. International Journal of Forecasting. 29(3). 411–430. 9 indexed citations
7.
McCabe, Brendan, et al.. (2008). FaSTR DNA: A new expert system for forensic DNA analysis. Forensic Science International Genetics. 2(3). 159–165. 7 indexed citations
8.
Harris, David, Stephen J. Leybourne, & Brendan McCabe. (2006). Panel Stationarity Tests for Purchasing Power Parity with Cross-Sectional Dependence. SSRN Electronic Journal. 1 indexed citations
9.
McCabe, Brendan, et al.. (2004). Testing for Dependence in Non-Gaussian Time Series Data. RePEc: Research Papers in Economics. 3 indexed citations
10.
McCabe, Brendan, Stephen J. Leybourne, & David Harris. (2003). Testing for Stochastic Cointegration and Evidence for Present Value Models. RePEc: Research Papers in Economics. 7 indexed citations
11.
Harris, David, Brendan McCabe, & Stephen J. Leybourne. (2003). SOME LIMIT THEORY FOR AUTOCOVARIANCES WHOSE ORDER DEPENDS ON SAMPLE SIZE. Econometric Theory. 19(5). 31 indexed citations
12.
Leybourne, Stephen J. & Brendan McCabe. (1999). Modified Stationarity Tests with Data-Dependent Model-Selection Rules. Journal of Business and Economic Statistics. 17(2). 264–264. 22 indexed citations
13.
McCabe, Brendan & Stephen J. Leybourne. (1998). ON ESTIMATING AN ARMA MODEL WITH AN MA UNIT ROOT. Econometric Theory. 14(3). 326–338. 10 indexed citations
14.
Leybourne, Stephen J. & Brendan McCabe. (1994). A Consistent Test for a Unit Root. Journal of Business and Economic Statistics. 12(2). 157–166. 184 indexed citations
15.
Leybourne, Stephen J. & Brendan McCabe. (1992). A simple test for parameter constancy in a nonlinear time series regression model. Economics Letters. 38(2). 157–162. 1 indexed citations
16.
McCabe, Brendan. (1990). An extension of Anderson's multiple decision procedure. Statistics & Probability Letters. 9(2). 119–124. 1 indexed citations
17.
McCabe, Brendan. (1986). Testing for heteroscedasticity occuring at unknown points. Communication in Statistics- Theory and Methods. 15(5). 1597–1813. 2 indexed citations
18.
Harrison, Michael & Brendan McCabe. (1979). A Test for Heteroscedasticity Based on Ordinary Least Squares Residuals. Journal of the American Statistical Association. 74(366a). 494–499. 71 indexed citations
19.
McCabe, Brendan, et al.. (1979). A Test for Heteroscedasticity Based on Ordinary Least Squares Residuals. Journal of the American Statistical Association. 74(366). 494–494. 33 indexed citations
20.
O’Hagan, John & Brendan McCabe. (1975). Tests for the Severity of Multicolinearity in Regression Analysis: A Comment. The Review of Economics and Statistics. 57(3). 368–368. 18 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.

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