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 review of tax research
20102.0k citationsMichelle Hanlon, Shane HeitzmanJournal of Accounting and Economicsprofile →
The Effects of Executives on Corporate Tax Avoidance
20101.1k citationsScott Dyreng, Michelle Hanlon et al.The Accounting Reviewprofile →
What does tax aggressiveness signal? Evidence from stock price reactions to news about tax shelter involvement
2008828 citationsMichelle Hanlon, Joel SlemrodJournal of Public Economicsprofile →
Incentives for Tax Planning and Avoidance: Evidence from the Field
2013620 citationsJohn R. Graham, Michelle Hanlon et al.The Accounting Reviewprofile →
The Persistence and Pricing of Earnings, Accruals, and Cash Flows When Firms Have Large Book-Tax Differences
Countries citing papers authored by Michelle Hanlon
Since
Specialization
Citations
This map shows the geographic impact of Michelle Hanlon'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 Michelle Hanlon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michelle Hanlon more than expected).
This network shows the impact of papers produced by Michelle Hanlon. 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 Michelle Hanlon. The network helps show where Michelle Hanlon may publish in the future.
Co-authorship network of co-authors of Michelle Hanlon
This figure shows the co-authorship network connecting the top 25 collaborators of Michelle Hanlon.
A scholar is included among the top collaborators of Michelle Hanlon 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 Michelle Hanlon. Michelle Hanlon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hanlon, Michelle, Jeffrey L. Hoopes, & Joel Slemrod. (2018). Tax Reform Made Me Do It!. SSRN Electronic Journal.2 indexed citations
8.
Dyreng, Scott, Michelle Hanlon, Edward L. Maydew, & Jacob R. Thornock. (2016). Changes in Corporate Effective Tax Rates Over the Past 25 Years. ScholarsArchive (Brigham Young University).7 indexed citations
Hanlon, Michelle & Joel Slemrod. (2008). What Does Tax Aggressiveness Signal? Evidence from Stock Price Reactions to News about Tax Shelter Involvement. SSRN Electronic Journal.99 indexed citations
14.
Hanlon, Michelle, Edward L. Maydew, & Terry Shevlin. (2008). An Unintended Consequence of Book-Tax Conformity: A Loss of Earnings Informativeness. SSRN Electronic Journal.26 indexed citations
15.
Hanlon, Michelle & Joel Slemrod. (2008). What does tax aggressiveness signal? Evidence from stock price reactions to news about tax shelter involvement. Journal of Public Economics. 93(1-2). 126–141.828 indexed citations breakdown →
16.
Dyreng, Scott, Michelle Hanlon, & Edward L. Maydew. (2008). Long-Run Corporate Tax Avoidance. The Accounting Review. 83(1). 61–82.143 indexed citations
17.
Hanlon, Michelle & Terry Shevlin. (2005). Bank-Tax Conformity for Corporate Income: An Introduction to the Issues. SSRN Electronic Journal.23 indexed citations
18.
Erickson, Merle, Michelle Hanlon, & Edward L. Maydew. (2005). Is There a Link Between Executive Equity Incentives and Accounting Fraud. SSRN Electronic Journal.408 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.