Abel Brodeur

36 papers receiving 1.4k citations

Abel Brodeur's Hit Papers

Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics 2020 · 164 citations
1640+2+4Years since publication100200300400

Peers

Abel Brodeur
Comparison fields: 5 of 112
  • Modeling and Simulation 214
  • General Decision Sciences 62
  • Economics and Econometrics 593
  • Statistics, Probability and Uncertainty 142
  • Health 130
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Countries citing papers authored by Abel Brodeur

Since Specialization
Citations

This map shows the geographic impact of Abel Brodeur'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 Abel Brodeur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abel Brodeur more than expected).

Fields of papers citing papers by Abel Brodeur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Abel Brodeur. 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 Abel Brodeur. The network helps show where Abel Brodeur may publish in the future.

Co-authors

The 25 scholars most cited alongside Abel Brodeur, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Abel Brodeur Line = papers co-authored together Abel Brodeur links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1
COVID-19, lockdowns and well-being: Evidence from Google Trends
Hit paper breakdown →
2020423
2 2015251
3
Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics
Hit paper breakdown →
2020164
4 2020162
5 202066
6 202065
7 202046
8 202044
9 202041
10 202040
11 202236
12 202324
13 201820
14 202016
15 202413
16 201812
17 201912
18 202011
19 202410
20 20249

About Abel Brodeur

Abel Brodeur is a scholar working on Economics and Econometrics, Statistics, Probability and Uncertainty, Modeling and Simulation, General Health Professions and Artificial Intelligence, having authored 39 papers that have together received 1.5k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (10 papers), COVID-19 Pandemic Impacts (10 papers), Meta-analysis and systematic reviews (9 papers), Employment and Welfare Studies (7 papers), Advanced Causal Inference Techniques (5 papers), scientometrics and bibliometrics research (4 papers), Psychological Well-being and Life Satisfaction (2 papers) and Data Analysis with R (2 papers). The work is most often cited by research in Modeling and Simulation (214 citations), General Decision Sciences (62 citations), Economics and Econometrics (593 citations), Statistics, Probability and Uncertainty (142 citations) and Health (130 citations). Abel Brodeur has collaborated with scholars based in Canada, Germany and United Kingdom. Frequent co-authors include Sarah Flèche, Nattavudh Powdthavee, Louis‐Philippe Beland, Taylor Wright, Andrew E. Clark, Nikolai Cook, Anthony Heyes, Yanos Zylberberg, Mathias Lé and Marc Sangnier. Their work appears in journals such as American Economic Review, The Economic Journal, Research & Politics, Journal of Economic Surveys and Economic Inquiry.

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.

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