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Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Projects
- 1 Active
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RESPOND: Rescuing Democracy from Political Corruption in Digital Societies
Fazekas, M. (PI)
1/05/24 → 30/04/29
Project: Research
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Collusion risk in corporate networks
Villamil, I., Kertész, J. & Fazekas, M., 7 Feb 2024, In: Scientific Reports. 14, 1, p. 3161 3161.Research output: Contribution to journal › Article › peer-review
Open Access -
Correction: Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning
Fazekas, M., Veljanov, Z. & de Oliveira, A. B., 15 Aug 2024, In: BMC Public Health. 24, 1, p. 2220 1 p.Research output: Contribution to journal › Comment/debate
Open Access -
Data analytics for anti-corruption in public procurement
Poltoratskaia, V. & Fazekas, M., 27 Mar 2024, Routledge Handbook of Public Procurement Corruption. Taylor and Francis, p. 42-59 18 p.Research output: Contribution to Book/Report types › Chapter › peer-review
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Global Contract-level Public Procurement Dataset
Fazekas, M., Tóth, B., Abdou, A. & Al-Shaibani, A., 1 Jun 2024, In: Data in Brief. 54, p. 110412 110412.Research output: Contribution to journal › Article › peer-review
Open Access -
Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning
Fazekas, M., Veljanov, Z. & de Oliveira, A. B., 15 Jul 2024, In: BMC Public Health. 24, 1, p. 1888 1888.Research output: Contribution to journal › Article › peer-review
Open Access
Datasets
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Replication data for: Anti-corruption in aid-funded procurement: Is corruption reduced or merely displaced?
Fazekas, M. (Creator), David-Barrett, E. (Creator) & Fazekas, M. (Contributor), Harvard Dataverse, 2020
DOI: 10.7910/dvn/brznjg, https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/BRZNJG
Dataset
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Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning
Fazekas, M. (Creator), Veljanov, Z. (Creator) & de Oliveira, A. B. (Creator), Figshare, 2024
DOI: 10.6084/m9.figshare.c.7350478.v1
Dataset
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Replication Data for: Lights on the Shadows of Public Procurement - Transparency as an antidote to corruption
Czibik, A. (Creator), Fazekas, M. (Creator), Bauhr, M. (Creator), De Fine Licht, J. (Creator) & Czibik, A. (Contributor), Harvard Dataverse, 2019
DOI: 10.7910/dvn/ieyezb, https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/IEYEZB
Dataset
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Replication Data for: Agency independence, campaign contributions, and favouritism in US federal government contracting
Fazekas, M. (Creator), Ferrali, R. (Creator), Wachs, J. (Creator) & Wachs, J. (Contributor), Harvard Dataverse, 2022
DOI: 10.7910/dvn/3u07ee, https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/3U07EE
Dataset
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Replication Data for: Partisan Procurement: Contracting with the United States Federal Government, 2003–2015
Dahlström, C. (Creator), Fazekas, M. (Creator), Lewis, D. E. (Creator), Dahlström, C. (Contributor) & Lewis, D. E. (Contributor), Harvard Dataverse, 2020
DOI: 10.7910/dvn/4nepi7, https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/4NEPI7
Dataset