Michela Bia
- Economics and Econometrics top 10%
- Sociology and Political Science
- Statistics and Probability top 5%
- General Agricultural and Biological Sciences top 5%
- Safety Research top 10%
- Co-authors
- Alessandra MatteiCarlos A. FloresAlfonso Flores‐LagunesLukáš LafférsMartin HuberPer KallestrupCharilaos LygidakisClaus Vögele
- Topics
- Advanced Causal Inference Techniques (7 papers)Diabetes Management and Education (4 papers)Statistical Methods and Inference (4 papers)
- Partner nations
- LuxembourgItalyUnited States
In The Last Decade
Michela Bia
16 papers receiving 335 citations
Peers
Comparison fields: 5 of 86
- Economics and Econometrics 140
- Sociology and Political Science 66
- Statistics and Probability 62
- General Agricultural and Biological Sciences 43
- Safety Research 43
Countries citing papers authored by Michela Bia
This map shows the geographic impact of Michela Bia'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 Michela Bia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michela Bia more than expected).
Fields of papers citing papers by Michela Bia
This network shows the impact of papers produced by Michela Bia. 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 Michela Bia. The network helps show where Michela Bia may publish in the future.
Co-authorship network of co-authors of Michela Bia
This figure shows the co-authorship network connecting the top 25 collaborators of Michela Bia. A scholar is included among the top collaborators of Michela Bia 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 Michela Bia. Michela Bia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 14 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 8 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 13 | |
| 13 | The impact of growing up poor in Europe | 2 |
| 14 | 38 | |
| 15 | 2 | |
| 16 | Semiparametric estimators of dose-response functions | 1 |
| 17 | Measuring intergenerational transmission of poverty | 2 |
| 18 | 40 | |
| 19 | DOSERESPONSE: Stata module to estimate dose-response function through adjustment for the generalized propensity score | 4 |
| 20 | 209 |
About Michela Bia
Michela Bia is a scholar working on Statistics and Probability, Economics and Econometrics and Endocrinology, Diabetes and Metabolism, having authored 20 papers that have together received 355 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (7 papers), Diabetes Management and Education (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Statistics and Probability (62 citations), General Agricultural and Biological Sciences (43 citations) and Safety Research (43 citations). Michela Bia has collaborated with scholars based in Luxembourg, Italy and United States. Frequent co-authors include Alessandra Mattei, Carlos A. Flores, Alfonso Flores‐Lagunes, Lukáš Lafférs, Martin Huber, Per Kallestrup, Charilaos Lygidakis, Claus Vögele, Jeanine Condo and Brenda Asiimwe‐Kateera. Their work appears in journals such as Journal of Business and Economic Statistics, BMJ Open and Health and Quality of Life Outcomes.
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.