Jörg Stoye
- Economics and Econometrics top 5%
- General Decision Sciences top 5%
- Management Science and Operations Research top 10%
- Education top 10%
- Statistics and Probability top 5%
- Co-authors
- Stefan HoderleinFrancesca MolinariDouglas McKeeJames BerryThomas J. DiCiccioAlex Rees-JonesTyler RansomYuichi Kitamura
- Topics
- Decision-Making and Behavioral Economics (12 papers)Economic and Environmental Valuation (9 papers)Bayesian Modeling and Causal Inference (5 papers)
- Cited by
- General Decision SciencesStatistics and ProbabilityManagement Science and Operations Research
- Partner nations
- United StatesSingaporeCanada
In The Last Decade
Jörg Stoye
17 papers receiving 347 citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Economics and Econometrics 172
- General Decision Sciences 92
- Management Science and Operations Research 78
- Education 75
- Statistics and Probability 64
Countries citing papers authored by Jörg Stoye
This map shows the geographic impact of Jörg Stoye'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 Jörg Stoye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jörg Stoye more than expected).
Fields of papers citing papers by Jörg Stoye
This network shows the impact of papers produced by Jörg Stoye. 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 Jörg Stoye. The network helps show where Jörg Stoye may publish in the future.
Co-authorship network of co-authors of Jörg Stoye
This figure shows the co-authorship network connecting the top 25 collaborators of Jörg Stoye. A scholar is included among the top collaborators of Jörg Stoye 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 Jörg Stoye. Jörg Stoye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | Learning during the COVID-19 pandemic: It is not who you teach, but how you teachbreakdown → | 105 |
| 3 | 4 | |
| 4 | 36 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 9 | |
| 8 | 7 | |
| 9 | Nonparametric Analysis of Random Utility Models: Testing | 1 |
| 10 | 11 | |
| 11 | 38 | |
| 12 | 5 | |
| 13 | 13 | |
| 14 | 43 | |
| 15 | 40 | |
| 16 | Revealed Preference When Agents Can Randomize | 3 |
| 17 | 37 | |
| 18 | Statistical Decisions under Ambiguity: An Axiomatic Analysis | 2 |
About Jörg Stoye
Jörg Stoye is a scholar working on General Decision Sciences, Economics and Econometrics and Management Science and Operations Research, having authored 18 papers that have together received 365 indexed citations. Recurring topics across this work include Decision-Making and Behavioral Economics (12 papers), Economic and Environmental Valuation (9 papers) and Bayesian Modeling and Causal Inference (5 papers). The work is most often cited by research in General Decision Sciences (92 citations), Statistics and Probability (64 citations) and Management Science and Operations Research (78 citations). Jörg Stoye has collaborated with scholars based in United States, Singapore and Canada. Frequent co-authors include Stefan Hoderlein, Francesca Molinari, Douglas McKee, James Berry, Thomas J. DiCiccio, Alex Rees-Jones, Tyler Ransom, Yuichi Kitamura, Rahul Deb and John Quah. Their work appears in journals such as Econometrica, The Review of Economics and Statistics and Journal of Econometrics.
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.