Robert Taylor

4.9k total citations
146 papers, 3.1k citations indexed

About

Robert Taylor is a scholar working on General Economics, Econometrics and Finance, Economics and Econometrics and Finance. According to data from OpenAlex, Robert Taylor has authored 146 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in General Economics, Econometrics and Finance, 96 papers in Economics and Econometrics and 71 papers in Finance. Recurrent topics in Robert Taylor's work include Monetary Policy and Economic Impact (103 papers), Market Dynamics and Volatility (67 papers) and Financial Risk and Volatility Modeling (67 papers). Robert Taylor is often cited by papers focused on Monetary Policy and Economic Impact (103 papers), Market Dynamics and Volatility (67 papers) and Financial Risk and Volatility Modeling (67 papers). Robert Taylor collaborates with scholars based in United Kingdom, Italy and Portugal. Robert Taylor's co-authors include Giuseppe Cavaliere, Stephen J. Leybourne, David I. Harvey, Linda M. Chatters, J. L. Levin, Fabio Busetti, Anders Rahbek, Paulo M.M. Rodrigues, Peter Burridge and Richard J. Smith and has published in prestigious journals such as Nature, Econometrica and The Economic Journal.

In The Last Decade

Robert Taylor

137 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert Taylor United Kingdom 29 1.8k 1.6k 1.2k 381 352 146 3.1k
Denise R. Osborn United Kingdom 31 2.0k 1.1× 1.6k 1.0× 1.0k 0.8× 135 0.4× 50 0.1× 100 3.1k
mw United Kingdom 9 1.4k 0.8× 906 0.6× 591 0.5× 108 0.3× 26 0.1× 11 2.8k
Morten Ørregaard Nielsen Denmark 29 1.8k 1.0× 937 0.6× 1.5k 1.2× 242 0.6× 31 0.1× 85 2.7k
Kajal Lahiri United States 27 1.5k 0.8× 1.2k 0.7× 492 0.4× 94 0.2× 54 0.2× 151 2.2k
Mike K. P. So Hong Kong 26 1.2k 0.6× 399 0.2× 1.2k 1.0× 250 0.7× 18 0.1× 141 2.6k
Susanne M. Schennach United States 18 813 0.4× 268 0.2× 131 0.1× 523 1.4× 66 0.2× 33 2.3k
William A. Barnett United States 31 3.0k 1.7× 1.9k 1.2× 769 0.6× 97 0.3× 13 0.0× 163 4.2k
Victor Ng Canada 23 4.7k 2.5× 2.0k 1.2× 4.8k 3.9× 129 0.3× 20 0.1× 64 6.5k
Benjamin F. King United States 7 487 0.3× 109 0.1× 456 0.4× 373 1.0× 124 0.4× 13 2.2k
Jason Abrevaya United States 22 737 0.4× 151 0.1× 145 0.1× 505 1.3× 139 0.4× 50 1.9k

Countries citing papers authored by Robert Taylor

Since Specialization
Citations

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

Fields of papers citing papers by Robert Taylor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Taylor

This figure shows the co-authorship network connecting the top 25 collaborators of Robert Taylor. A scholar is included among the top collaborators of Robert Taylor 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 Robert Taylor. Robert Taylor 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.
Harris, David, et al.. (2020). Level shift estimation in the presence of non-stationary volatility with an application to the unit root testing problem. Journal of Econometrics. 219(2). 354–388. 3 indexed citations
2.
Kapetanios, George, et al.. (2019). A Generalised Fractional Differencing Bootstrap for Long Memory Processes. Journal of Time Series Analysis. 40(4). 467–492. 7 indexed citations
3.
Cavaliere, Giuseppe, et al.. (2018). UNIT ROOT INFERENCE FOR NON-STATIONARY LINEAR PROCESSES DRIVEN BY INFINITE VARIANCE INNOVATIONS. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 11 indexed citations
4.
Harvey, David I., et al.. (2018). Real‐Time Monitoring for Explosive Financial Bubbles. Journal of Time Series Analysis. 39(6). 863–891. 20 indexed citations
5.
Harvey, David I., et al.. (2018). Testing for parameter instability in predictive regression models. Journal of Econometrics. 204(1). 101–118. 16 indexed citations
6.
Castro, Tomás del Barrio, Paulo Rodrigues, & Robert Taylor. (2017). SEMI-PARAMETRIC SEASONAL UNIT ROOT TESTS. Econometric Theory. 34(2). 447–476. 9 indexed citations
7.
Nagy, Janice A., et al.. (2017). New electrical impedance methods for the in situ measurement of the complex permittivity of anisotropic biological tissues. Physics in Medicine and Biology. 62(22). 8616–8633. 25 indexed citations
8.
Harvey, David I., et al.. (2017). Tests for an end-of-sample bubble in financial time series. Econometric Reviews. 36(6-9). 651–666. 28 indexed citations
9.
Leybourne, Stephen J., et al.. (2016). Testing for a Change in Mean under Fractional Integration. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 9(1). 2 indexed citations
10.
Cavaliere, Giuseppe, David I. Harvey, Stephen J. Leybourne, & Robert Taylor. (2014). Testing for Unit Roots Under Multiple Possible Trend Breaks and Non‐Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics. Journal of Time Series Analysis. 36(5). 603–629. 3 indexed citations
11.
Cavaliere, Giuseppe, Morten Ørregaard Nielsen, & Robert Taylor. (2013). Bootstrap Score Tests for Fractional Integration in Heteroskedastic ARFIMA Models, with an Application to Price Dynamics in Commodity Spot and Futures Markets. Econstor (Econstor). 25 indexed citations
12.
Leybourne, Stephen J., et al.. (2012). ON THE BEHAVIOR OF FIXED-bTREND BREAK TESTS UNDER FRACTIONAL INTEGRATION. Econometric Theory. 29(2). 393–418. 4 indexed citations
13.
Cavaliere, Giuseppe, et al.. (2011). Wild bootstrap of the mean in the infinite variance case. RePEc: Research Papers in Economics. 1 indexed citations
14.
Cavaliere, Giuseppe & Robert Taylor. (2009). Bootstrap M Unit Root Tests. Econometric Reviews. 28(5). 393–421. 25 indexed citations
15.
Harvey, David I., Stephen J. Leybourne, & Robert Taylor. (2009). REJOINDER. Econometric Theory. 25(3). 658–667. 1 indexed citations
16.
Taylor, Robert. (2005). On the limiting behaviour of augmented seasonal unit root tests. Economics bulletin. 3(3). 1–10. 2 indexed citations
17.
Taylor, Robert & Stephen J. Leybourne. (2004). Some New Tests for a Change in Persistence. Economics bulletin. 3(39). 1–10. 3 indexed citations
18.
Taylor, Robert, Linda M. Chatters, & J. L. Levin. (2004). Religion in the Lives of African Americans: Social, Psychological, and Health Perspectives. 437 indexed citations
19.
Taylor, Robert. (2003). Locally Optimal Tests Against Unit Roots in Seasonal Time Series Processes. SSRN Electronic Journal.
20.
Taylor, Robert & Stephen J. Leybourne. (1999). Detecting Seasonal Unit Roots: an Approach Based on the Sample Autocorrelation Function. Manchester School. 67(3). 261–286. 2 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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