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.
Countries citing papers authored by Edward E. Leamer
Since
Specialization
Citations
This map shows the geographic impact of Edward E. Leamer'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 Edward E. Leamer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward E. Leamer more than expected).
Fields of papers citing papers by Edward E. Leamer
This network shows the impact of papers produced by Edward E. Leamer. 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 Edward E. Leamer. The network helps show where Edward E. Leamer may publish in the future.
Co-authorship network of co-authors of Edward E. Leamer
This figure shows the co-authorship network connecting the top 25 collaborators of Edward E. Leamer.
A scholar is included among the top collaborators of Edward E. Leamer 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 Edward E. Leamer. Edward E. Leamer is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Leamer, Edward E.. (2016). The Sensitivity of International Comparisons of Capital Stock Measures to Different "Real" Exchange Rates. American Economic Review. 78(2). 479–483.1 indexed citations
4.
Leamer, Edward E.. (2012). The Craft of Economics: Lessons from the Heckscher-Ohlin Framework. RePEc: Research Papers in Economics. 1.8 indexed citations
Leamer, Edward E., et al.. (1998). Efforts and Wages: A New Look at the Inter-Industry Wage Differentials. National Bureau of Economic Research. 37–84.2 indexed citations
9.
Leamer, Edward E.. (1997). Revisiting Tobin's 1950 Study of Food Expenditure: Reply. Journal of Applied Econometrics. 12(5). 559–561.1 indexed citations
10.
Leamer, Edward E.. (1996). Wage Inequality from International Competition and Technological Change: Theory and Country Experience. American Economic Review. 86(2). 309–314.113 indexed citations
11.
Leamer, Edward E.. (1995). The Heckscher-Ohlin Model in Theory and Practice. RePEc: Research Papers in Economics.132 indexed citations
12.
Leamer, Edward E.. (1994). Trade, Wages and Revolving Door Ideas. National Bureau of Economic Research.95 indexed citations
13.
Leamer, Edward E.. (1993). Factor-supply differences as a source of comparative advantage. American Economic Review. 83(2). 436–439.21 indexed citations
14.
Hendry, David F., Edward E. Leamer, & Dale J. Poirier. (1990). The ET Dialogue: A Conversation on Econometric Methodology.. Econometric Theory. 6.26 indexed citations
15.
Bowen, Harry P., Edward E. Leamer, & Leo Sveikauskas. (1986). Multicountry, Multifactor Tests of the Factor Abundance Theory. American Economic Review. 77(5). 791–809.241 indexed citations
16.
Leamer, Edward E.. (1985). Sensitivity Analyses Would Help. American Economic Review. 75(3). 308–313.367 indexed citations
Leamer, Edward E. & Harry P. Bowen. (1981). Cross-Section Tests of the Heckscher-Ohlin Theorem: Comment [Factor Abundance and Comparative Advantage].. American Economic Review. 71(5). 1040–1043.42 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.