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.
Benchmark priors for Bayesian model averaging
2001675 citationsCarmen Fernández, Eduardo Ley et al.Journal of Econometricsprofile →
Model uncertainty in cross‐country growth regressions
2001582 citationsCarmen Fernández, Eduardo Ley et al.Journal of Applied Econometricsprofile →
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 Eduardo Ley'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 Eduardo Ley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eduardo Ley more than expected).
This network shows the impact of papers produced by Eduardo Ley. 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 Eduardo Ley. The network helps show where Eduardo Ley may publish in the future.
Co-authorship network of co-authors of Eduardo Ley
This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Ley.
A scholar is included among the top collaborators of Eduardo Ley 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 Eduardo Ley. Eduardo Ley is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ley, Eduardo, et al.. (2010). The Taxation of Motor Fuel. The World Bank eBooks.4 indexed citations
4.
Ley, Eduardo, et al.. (2009). The Taxation of Motor Fuel: International Comparison. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich).6 indexed citations
5.
Ley, Eduardo & Mark F. J. Steel. (2009). On the effect of prior assumptions in Bayesian model averaging with applications to growth regression This article was published online on 30 March 2009. An error was subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected l6 April 2009&rsqb. Journal of Applied Econometrics. 24(4). 651–674.98 indexed citations
6.
Ley, Eduardo. (2009). Fiscal (and external) sustainability. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich).24 indexed citations
Ley, Eduardo. (2002). On Plutocratic and Democratic CPIs. Economics bulletin. 4(3). 1–5.3 indexed citations
11.
Fernández, Carmen, Eduardo Ley, & Mark F. J. Steel. (2002). Bayesian modeling of catch in a Northwest Atlantic fishery. Data Archiving and Networked Services (DANS). 51(3). 257–280.5 indexed citations
12.
Ruiz‐Castillo, Javier, Eduardo Ley, & Mario Izquierdo. (2000). The plutocratic bias in the CPI : evidence from Spain. OpenGrey (Institut de l'Information Scientifique et Technique).5 indexed citations
Ley, Eduardo, Molly K. Macauley, & Stephen W. Salant. (2000). Restricting the Trash Trade. American Economic Review. 90(2). 243–246.7 indexed citations
Ley, Eduardo. (1995). On the Peculiar Distribution of the U.S. Stock Indices' Digits. SSRN Electronic Journal.12 indexed citations
18.
Ley, Eduardo. (1991). Eficiencia productiva: un estudio aplicado al sector hospitalario. Respuesta. Investigación Económica. 15(3). 755–756.1 indexed citations
19.
Ley, Eduardo. (1991). Eficiencia productiva: un estudio aplicado al sector hospitalario. Investigación Económica. 15(1). 71–88.24 indexed citations
20.
Ley, Eduardo. (1991). Essays on applied production analysis.. Deep Blue (University of Michigan).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.