Howard Bloom
Impact in
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
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- Poverty, Education, and Child Welfare
Papers in
-
- Advanced Causal Inference Techniques 5
- Statistical Methods and Inference 1
- Statistical Methods and Bayesian Inference 1
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- School Choice and Performance 3
- Co-authors
- Marie‐Andrée Somers (3 shared papers)Robin Jacob (3 shared papers)Pei Zhu (4 shared papers)Johannes M. Bos (1 shared paper)Lisa A. Gennetian (1 shared paper)Pamela Morris (1 shared paper)Francis Fukuyama (1 shared paper)Andrew Bell (1 shared paper)
- Journals
- Evaluation Review (1 paper)Foreign Affairs (1 paper)Journal of Research on Educational Effectiveness (1 paper)SSRN Electronic Journal (1 paper)MDRC (2 papers)
- Partner nations
- United States
In The Last Decade
Howard Bloom
7 papers receiving 213 citations
Peers
Comparison fields: 5 of 88
- Statistics and Probability 45
- Safety Research 29
- Economics and Econometrics 58
- Education 55
- Gender Studies 17
Countries citing papers authored by Howard Bloom
This map shows the geographic impact of Howard Bloom'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 Howard Bloom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Howard Bloom more than expected).
Fields of papers citing papers by Howard Bloom
This network shows the impact of papers produced by Howard Bloom. 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 Howard Bloom. The network helps show where Howard Bloom may publish in the future.
Co-authors
The 9 scholars most cited alongside Howard Bloom, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A Practical Guide to Regression Discontinuity | 2012 | 138 |
| 2 | The Validity and Precision of the Comparative Interrupted Time Series Design and the Difference-in-Difference Design in Educational Evaluation | 2013 | 35 |
| 3 | 2016 | 28 | |
| 4 | Using Instrumental Variables Analysis to Learn More from Social Policy Experiments | 2002 | 22 |
| 5 | 1995 | 7 | |
| 6 | The Open-Source Everything Manifesto: Transparency, Truth, and Trust | 2012 | 6 |
| 7 | 2020 | 2 | |
| 8 | 2012 | 0 |
About Howard Bloom
Howard Bloom is a scholar working on Statistics and Probability, Education, General Economics, Econometrics and Finance, Management Science and Operations Research and Soil Science, having authored 8 papers that have together received 238 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (5 papers), School Choice and Performance (3 papers), Statistical Methods and Inference (1 paper), Statistical Methods and Bayesian Inference (1 paper), Agricultural risk and resilience (1 paper), Monetary Policy and Economic Impact (1 paper), Gender, Labor, and Family Dynamics (1 paper) and Evaluation and Performance Assessment (1 paper). The work is most often cited by research in Statistics and Probability (45 citations), Safety Research (29 citations), Economics and Econometrics (58 citations), Education (55 citations) and Gender Studies (17 citations). Howard Bloom has collaborated with scholars based in United States. Frequent co-authors include Marie‐Andrée Somers, Robin Jacob, Pei Zhu, Johannes M. Bos, Lisa A. Gennetian, Pamela Morris, Francis Fukuyama, Andrew Bell and Sean F. Reardon. Their work appears in journals such as Evaluation Review, Foreign Affairs, Journal of Research on Educational Effectiveness, SSRN Electronic Journal and MDRC.
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.