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.
Regressive Sin Taxes, with an Application to the Optimal Soda Tax*
2019185 citationsHunt Allcott, Benjamin Lockwood et al.The Quarterly Journal of Economicsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Dmitry Taubinsky
Since
Specialization
Citations
This map shows the geographic impact of Dmitry Taubinsky'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 Dmitry Taubinsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry Taubinsky more than expected).
Fields of papers citing papers by Dmitry Taubinsky
This network shows the impact of papers produced by Dmitry Taubinsky. 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 Dmitry Taubinsky. The network helps show where Dmitry Taubinsky may publish in the future.
Co-authorship network of co-authors of Dmitry Taubinsky
This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Taubinsky.
A scholar is included among the top collaborators of Dmitry Taubinsky 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 Dmitry Taubinsky. Dmitry Taubinsky is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Allcott, Hunt, Benjamin Lockwood, & Dmitry Taubinsky. (2019). Regressive Sin Taxes, with an Application to the Optimal Soda Tax*. The Quarterly Journal of Economics. 134(3). 1557–1626.185 indexed citations breakdown →
9.
Royer, Heather, et al.. (2019). How are Preferences For Commitment Revealed.4 indexed citations
10.
Rees-Jones, Alex & Dmitry Taubinsky. (2019). Measuring “Schmeduling”. The Review of Economic Studies. 87(5). 2399–2438.67 indexed citations
11.
Rees-Jones, Alex & Dmitry Taubinsky. (2016). Heuristic Perceptions of the Income Tax: Evidence and Implications for Debiasing. SSRN Electronic Journal.5 indexed citations
12.
Herz, Holger & Dmitry Taubinsky. (2016). What Makes a Price Fair? An Experimental Analysis of Market Experience and Endogenous Fairness Views. SSRN Electronic Journal.3 indexed citations
Chabris, Christopher F., David Laibson, Carrie L. Morris, Jonathon P. Schuldt, & Dmitry Taubinsky. (2009). The Allocation of Time in Decision-Making. Journal of the European Economic Association. 7(2-3). 628–637.65 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.