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Global Contract-level Public Procurement Dataset.
Fazekas, Mihály; Tóth, Bence; Abdou, Aly; Al-Shaibani, Ahmed.
Affiliation
  • Fazekas M; Central European University, Quellenstraße 51, 1100, Wien, Austria.
  • Tóth B; University College London, Gower Street, London WC1E 6BT, UK.
  • Abdou A; Government Transparency Institute, 6000 Kecskemét, Futár u. 48., Hungary.
  • Al-Shaibani A; Government Transparency Institute, 6000 Kecskemét, Futár u. 48., Hungary.
Data Brief ; 54: 110412, 2024 Jun.
Article de En | MEDLINE | ID: mdl-38698797
ABSTRACT
One-third of total government spending across the globe goes to public procurement, amounting to about 10 trillion dollars a year. Despite its vast size and crucial importance for economic and political developments, there is a lack of globally comparable data on contract awards and tenders run. To fill this gap, this article introduces the Global Public Procurement Dataset (GPPD). Using web scraping methods, we collected official public procurement data on over 72 million contracts from 42 countries between 2006 and 2021 (time period covered varies by country due to data availability constraints). To overcome the inconsistency of data publishing formats in each country, we standardized the published information to fit a common data standard. For each country, key information is collected on the buyer(s) and supplier(s), geolocation information, product classification, price information, and details of the contracting process such as contract award date or the procedure type followed. GPPD is a contract-level dataset where specific filters are calculated allowing to reduce the dataset to the successfully awarded contracts if needed. We also add several corruption risk indicators and a composite corruption risk index for each contract which allows for an objective assessment of risks and comparison across time, organizations, or countries. The data can be reused to answer research questions dealing with public procurement spending efficiency among others. Using unique organizational identification numbers or organization names allows connecting the data to company registries to study broader topics such as ownership networks.
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Data Brief Année: 2024 Type de document: Article Pays d'affiliation: Autriche

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Data Brief Année: 2024 Type de document: Article Pays d'affiliation: Autriche