Dataset presenting ten years of spending data for central and decentralized entities, and five years for local governments.
Central government expenditure data can be identified by location thanks to a geographic (regional) identifier.
Different classification types: administrative, economic, functional, programmatic, etc.
As part of the 2013 Public Expenditure Review, the World Bank built, with the guidance and support of Paraguay's Ministry of Finance, a BOOST database. As part of the reforms carried out by the Government of Paraguay, the BOOST dataset was released to the public through an open-source interactive pivot table interface. After the introduction fo the database to the public, the Government of Paraguay organized a series of workshops and capacity-building events aimed to create capacity among journalists involved in budget and public policy analysis.
The Paraguay BOOST is divided in two files. The first file contains initial, revised, released and executed spending figures for the central government and the decentralized agencies. The years covered for this part of the dataset range from 2003 to 2012. The data was provided by the Ministry of Finance and came from the IFMIS. This file classifies the data in economic, administrative, functional, and programmatic classifications. in addition to variables created by World Bank technicians aimed to identify the source of financing of each budget line. Additionally, the file includes a geographic identifier for each line of the budget.
The second file presents expenditure data for municipal governments. The period covered in this dataset ranges from 2006 and 2010. The municipal government data in Paraguay is currently not included in that country’s IFMIS (The municipal governments are legally mandated to send written reports on municipal finances for every budget cycle to the Ministry of Finance; however the process of collecting and processing this municipal data is still no automatic).
Database users should be aware of the potential limitations of the datasets. We urge users to consult the users’ manuals to learn more about these limitations and take them into account when analyzing their countries’ budgets.