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.
A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration
2006697 citationsAndrew J. G. Cairns, David Blake et al.profile →
A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States
2009469 citationsAndrew J. G. Cairns, David Blake et al.North American Actuarial Journalprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of David Blake'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 David Blake with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Blake more than expected).
This network shows the impact of papers produced by David Blake. 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 David Blake. The network helps show where David Blake may publish in the future.
Co-authorship network of co-authors of David Blake
This figure shows the co-authorship network connecting the top 25 collaborators of David Blake.
A scholar is included among the top collaborators of David Blake 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 David Blake. David Blake is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Blake, David, Andrew J. G. Cairns, Malene Kallestrup‐Lamb, & Jesper Rangvid. (2023). Longevity risk and capital markets: the 2021–22 update. CBS Research Portal (Copenhagen Business School). 89(3). 299–312.3 indexed citations
Blake, David, et al.. (2014). How do savers think about and respond to risk? Evidence from a population survey and lessons for the investment industry. City Research Online (City University London).1 indexed citations
11.
Harrison, Debbie, David Blake, & Kevin Dowd. (2014). VfM: Assessing value for money in defined contribution default funds. City Research Online (City University London).1 indexed citations
Harrison, David, et al.. (2013). Returning to the Core - Rediscovering a Role for Real Estate in Defined Contribution Pension Schemes. City Research Online (City University London).2 indexed citations
Coughlan, Guy, Marwa Khalaf-Allah, Sumit Kumar, et al.. (2011). Longevity Hedging 101. North American Actuarial Journal. 15(2). 150–176.103 indexed citations
16.
Blake, David, Edmund Cannon, & Ian Tonks. (2010). Ending Compulsory Annuitisation: Quantifying the Consequences. City Research Online (City University London).2 indexed citations
17.
Dowd, Kevin, Andrew J. G. Cairns, David Blake, et al.. (2010). Backtesting Stochastic Mortality Models. North American Actuarial Journal. 14(3). 281–298.96 indexed citations
Blake, David, et al.. (2006). There's No Time Like the Present: The Cost of Delaying Retirement Saving. Strathprints: The University of Strathclyde institutional repository (University of Strathclyde). 15(3). 213–231.7 indexed citations
20.
Lunde, Asger, David Blake, & Allan Timmermann. (1998). The Hazards of Mutual Fund Underperformance: A Cox Regression Analysis. eScholarship (California Digital Library).10 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.