Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports
This paper undertakes a detailed examination of the availability and quality of data on public expenditures in agriculture in Africa. We consider the case of Mozambique, a country characterised by low income and low administrative capacity, but also by a policy environment that has turned a focused...
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doaj-d3e814bc98e34867bbe1d01458d9b5482020-11-24T22:30:37ZengUbiquity PressData Science Journal1683-14702018-04-011710.5334/dsj-2018-009667Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget ReportsTewodaj Mogues0Leonardo Caceres1Development Strategy and Governance Division, International Food Policy Research Institute (IFPRI), Washington DCBureau of Agricultural Studies and Policies, Ministry of Agriculture, SantiagoThis paper undertakes a detailed examination of the availability and quality of data on public expenditures in agriculture in Africa. We consider the case of Mozambique, a country characterised by low income and low administrative capacity, but also by a policy environment that has turned a focused lens on public funding to agriculture. We explore the extent to which domestic analysts may be able to access and use such data to reliably quantify public resource allocation to the sector, and to unpack the ‘black box’ of what goes into country-level public expenditure statistics. We find that data are, surprisingly, freely available in great abundance. This has encouraging aspects but also pitfalls: On the one hand, data that are often out of public sight are openly accessible for Mozambican researchers to draw upon. But the drawback of high abundance emanates from its manifestation in the form of a proliferation of multiple classification systems used to create a fine disaggregation of public funds data; given Mozambique’s limited public sector capacity, this has meant that each classification system leaves a lot to be desired, making it hard to use any single one to accurately and fully reliably reconstruct the amount of public resources going to agriculture. Making the hard choice to eliminate some of the classification systems, and dedicate this freed-up capacity to be more thorough on the retained ones, would better serve domestic users of such data, as well as the government, which is both a consumer and producer of these data.https://datascience.codata.org/articles/723public expenditurebudgetfinancial dataagriculturegovernment spendingMozambique |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tewodaj Mogues Leonardo Caceres |
spellingShingle |
Tewodaj Mogues Leonardo Caceres Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports Data Science Journal public expenditure budget financial data agriculture government spending Mozambique |
author_facet |
Tewodaj Mogues Leonardo Caceres |
author_sort |
Tewodaj Mogues |
title |
Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports |
title_short |
Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports |
title_full |
Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports |
title_fullStr |
Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports |
title_full_unstemmed |
Unpacking the ‘Black Box’ of Public Expenditure Data in Africa: Quantification of Agricultural Spending Using Mozambique’s Budget Reports |
title_sort |
unpacking the ‘black box’ of public expenditure data in africa: quantification of agricultural spending using mozambique’s budget reports |
publisher |
Ubiquity Press |
series |
Data Science Journal |
issn |
1683-1470 |
publishDate |
2018-04-01 |
description |
This paper undertakes a detailed examination of the availability and quality of data on public expenditures in agriculture in Africa. We consider the case of Mozambique, a country characterised by low income and low administrative capacity, but also by a policy environment that has turned a focused lens on public funding to agriculture. We explore the extent to which domestic analysts may be able to access and use such data to reliably quantify public resource allocation to the sector, and to unpack the ‘black box’ of what goes into country-level public expenditure statistics. We find that data are, surprisingly, freely available in great abundance. This has encouraging aspects but also pitfalls: On the one hand, data that are often out of public sight are openly accessible for Mozambican researchers to draw upon. But the drawback of high abundance emanates from its manifestation in the form of a proliferation of multiple classification systems used to create a fine disaggregation of public funds data; given Mozambique’s limited public sector capacity, this has meant that each classification system leaves a lot to be desired, making it hard to use any single one to accurately and fully reliably reconstruct the amount of public resources going to agriculture. Making the hard choice to eliminate some of the classification systems, and dedicate this freed-up capacity to be more thorough on the retained ones, would better serve domestic users of such data, as well as the government, which is both a consumer and producer of these data. |
topic |
public expenditure budget financial data agriculture government spending Mozambique |
url |
https://datascience.codata.org/articles/723 |
work_keys_str_mv |
AT tewodajmogues unpackingtheblackboxofpublicexpendituredatainafricaquantificationofagriculturalspendingusingmozambiquesbudgetreports AT leonardocaceres unpackingtheblackboxofpublicexpendituredatainafricaquantificationofagriculturalspendingusingmozambiquesbudgetreports |
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