1. Introduction

Public expenditures on agriculture, health, and other sectors influence long-run growth rates, productivity, and welfare (). For instance, government spending on creating agricultural public goods has a significant rate of return (; ), and the effects of agricultural expenditures can be pronounced in developing regions like Africa with a large rural population (). Because of the importance of government investments as a policy tool to effect economic growth, development, and redistribution, the proper measurement and quantification of public expenditures has warranted academic attention, though it has received it to only a limited extent. Ironically, it is in the context of advanced countries, with a rather robust data environment regarding public resource allocation, that research has been conducted on the limitations to measurement and data systems on public spending, such as in the US () and the UK (). In the developing country context on the other hand, where data quality is poorer, to the best of our knowledge there is no peer reviewed literature that undertakes a detailed examination of the quality and availability of public expenditure measurement in Africa—whether in the aggregate or for specific sectors such as agriculture. Two exceptions are Mwabutwa () in the context of Malawi, and Mogues and Anson () who analyse the quality and consistency of cross-country (including African countries) agricultural public expenditure datasets.

This very issue is the primary enterprise of this study. We seek to unpack the ‘black box’ of public expenditure data in the African context, using as a case study Mozambique, a low-resource economy that is in the poorest quartile of Sub-Saharan African countries (). This article analyses Mozambique’s budget reports, in-year expenditure reports, and financial statements, to determine to what extent, with what level of detail, and with what degree of within-report and cross-report consistency, data are available on public expenditures. We focus especially on public spending in the agricultural sector, given the importance of agriculture in Mozambique in particular and Africa in general, where this sector continues to be a mainstay of employment, exports, and the economy as a whole. However, lessons from our examination of the quality, consistency and accessibility of agricultural public spending data can be easily extended, and are highly relevant, to African researchers concerned with public expenditures in other sectors, such as health, education, or transport infrastructure.

Specifically, the study addresses three questions: If Mozambican researchers seek to access and use data on agricultural spending in the country, what are the primary government data sources they would have to navigate, how accessible are these data, and how do expenditures differ across these data sources? Second, what methods of expenditure classification would they encounter in these data sources, how useful are the different classification approaches for analysts, and to what extent are the different classification methods consistent with each other when seeking to quantify agricultural public expenditures? Finally, what are potential approaches to improve the quality, consistency, and usability of public expenditure data in these primary sources, accounting for the low-resource and low-capacity environment characterising Mozambique?

Addressing these questions has broader policy relevance. Measurement challenges with regard to sectoral public expenditures have come strongly to the fore in the policy arena in Africa. A prominent case in this regard is within the context of an Africa-wide initiative to boost the agricultural sector: the Comprehensive Africa Agriculture Development Programme (CAADP). CAADP, a major initiative of the African Union, was launched in 2003 to promote agriculture-driven economic growth to reduce hunger, malnutrition, and poverty across Africa. One of its most prominent guidelines calls for African countries to expend 10 percent of total public resources on agriculture. In Mozambique, CAADP has been adopted and is manifested through the Mozambique-specific 2012 CAADP investment plan (the National Programme for Investment in the Agricultural Sector: Programa Nacional de Investimento do Sector Agrário, or PNISA). Prompted by the CAADP guideline on public spending, the attention of Mozambican government agencies, donor organisations, and civil society groups in the country turned to the question of how agricultural expenditures can be properly measured, quantified, and tracked. Different reports by different bodies reflected conflicting information on this front, raising the question of the reliability and transparency underlying these data and the way they were compiled.

Beyond Mozambique, a systematic review of public expenditure multi-country databases found several cases of starkly differing numbers for agricultural public expenditures in Africa for the same countries and years but across different datasets (). This of course is problematic, given that African consumers of such public expenditure data—whether they be scientists and researchers, or members of the policy and civil society community—do not have the time and capacity to carefully investigate the various methodologies underlying such data sources, which may explain the differences in quantities. And these differences matter when they are used to inform policy analysis or policy itself.

The next section in this paper explores and situates Mozambique’s expenditure data reports within the budget cycle, distinguishing data on initial budget allocations, revised budgets, preliminary expenditure data, and final realised spending. Section 3 documents the way that these data are organised in Mozambique’s data reports, focusing on the classification systems employed to disaggregated public resource allocations. We generate figures on agricultural public expenditures derived from the different classification systems, compare these different measures, and discuss the opportunities and the weaknesses that each classification system harbours, but also remark on the overburdened classification system that seeks to do too much and thus does not generate good and easily intelligible data along any single classifier. We summarise and draw broader conclusions in the final section.

2. Public Expenditure Data Along the Budget Cycle

Budgeting is a critical yearly activity in the policy and budget process, specifically in making a transition from development plans to resource allocations. There are two main types of government reports in the overall planning and budget process of Mozambique: the planning documents—such as the Government Five-Year Plan (Programa Quinquenal do Governo, or PQG), the poverty reduction strategy, the medium-term expenditure framework, and the Economic and Social Plan (Plano Económico e Social, or PES)—and the budgeting and public expenditure execution reports. Some of these are issued quarterly; some annually, covering the fiscal year, January 1st to December 31th; and others at multi-year intervals.

In order for the types of stakeholders described in the earlier section to be able to conduct budgetary evaluation, fiscal policy analysis, and ultimately examine the government’s performance, it is necessary to have access to and analyse public expenditure data and their sources. The currently existing modalities of recording and reporting budget and expenditure data are a result of an integrated financial management system that the government began developing in 2002, called SISTAFE (Sistema Electrónico de Administração Financeira do Estado), and its electronic counterpart, e-SISTAFE, which started to be rolled out in 2007 by the Ministry of Economy and Finance (MEF). e-SISTAFE generates three core reports in which state budget and public expenditure data are captured across the different stages of the budget cycle. The reports are the State Budget Laws (Lei Orçamento do Estado, or LOE), the Budget Execution Reports (Relatório de Execução Orçamental, or REO), and the General State Accounts (Conta Geral do Estado, or CGE).

Remarkably, all of these data, in their full detail, are publicly accessible on the website of MEF’s National Directorate of Budget (Director Nacional do Orçamento, or DNO). This is not a common occurrence in Africa, given that often one may at best be able to access highly aggregated summaries of budgets and expenditures freely online, and needing to rely on contacts within the ministries of finance or other responsible agencies for any hope of access to more detailed data. A limitation exists in the physical accessibility of Mozambique’s data, however, in that these are available online as PDF files, and not also as databases easily transferred into spreadsheets. This may limit Mozambican researchers’ ability to conveniently undertake data analysis without an extensive data entry effort. Nonetheless, even the availability in the current form is impressive in continental comparison. Consistent with this, a survey of budget transparency shows that of the 29 African countries reviewed, only four countries performed better than or equal to Mozambique in terms of making key budget documents available to the public (). We next examine in more detail the nature of the data available in the LOE, REO, and CGE reports.

State Budget Laws (LOE)

LOE is a tool that financially quantifies the resources needed to achieve the policy goals defined in the PES. The LOE predicts revenues and expenditures, and consequently serves as an economic forecast for the state’s revenue and spending over the period of a year. Planned expenditures are presented according to administrative and economic classifications (more on these in Section 3). The Ministry of Planning and Development (MPD) writes the PES, and based on that, MEF formulates the annual proposed LOE. Once the budget is published, ministries and agencies are authorised to spend money, consistent with the legal appropriations for each agencies and the categories as per the economic classification.

Budget Execution Reports (REO)

The REO is a government document that aims to review on a periodic basis the implementation of public expenditure within the period in reference. It is issued quarterly by MEF’s National Directorate of Public Accounts (Direcção Nacional de Contabilidade Pública, or DNCP). The report presents data on the execution of revenues and expenses for all public sector institutions. One of the main responsibilities of MEF is to monitor and manage in-year changes to the budget. Unforeseen circumstances or poor budgeting may make it necessary to adjust the budget (). In the course of the fiscal year, ministries and government agencies can request reprogramming to receive additional funds if a need arises. To accomplish such reprogramming requests, usually the National Directorate of Budget (DNO) has to reallocate funds among different ministries and agencies, with an eye to preserving macroeconomic stability and fiscal responsibility principles. Consequently, the REO compares the original budget allocations (LOE) with the current in-year budget allocations. REO is a snapshot that shows the situation at the time it is issued. It is worth noting that the REO could contain data that is at the time only partially processed by the electronic system e-SISTAFE, and thus could represent only partial budget execution. Also, some units are processed in e-SISTAFE before being incorporated into an expenditure item in the REO.

General State Accounts (CGE)

The CGE, also issued by MEF’s DNCP, is the government’s annual consolidated financial statement, compiled after the end of the fiscal year. This data report highlights budget implementation and financial management, containing collected revenue, paid expenses, and tables of budget execution, and these data are juxtaposed against the original budget allocations also recaptured in the CGE. The CGE, after being issued, is sent to parliament and the auditor-general. The parliament forwards these accounts to the auditor-general for external audit together with parliament’s suggestions on areas requiring attention. The auditor-general submits its report on the CGE financial statements back to parliament, following which the CGE is presented to the parliament’s plenary, where it usually is not discussed until March, i.e. about 15 months after the budget year, due to lack of capacity within parliament to analyse this report and the budget proposal for the upcoming year at the same time.

A quantitative elucidation of the relationship between LOE, REO, and CGE

We compile and analyse aggregated data from 2010 to 2013 in order to provide a quantitative elucidation of the relationship between the data across the three core reports, LOE, REO and CGE. This analysis discusses the differences among the reports, as well as factors that may explain those differences. It is important to keep in mind that differences in the numbers between the three documents exist because each report corresponds to a different stage along the budget cycle. The aggregated data for the years 2010 to 2013 with regard to the LOE, REO, and CGE are shown in the upper panel of Table 1. The LOE reports the approved predicted expenditure for each respective year (line [1]). The REO accounts for the quarterly executed budget as well as the budget reallocations. The budget reallocation constitutes the updated spending ceiling, or final budget allocation, within the period in reference (line [3]). The CGE accounts for all the budget reallocations and all the transactions, including those that within the budget year were registered neither on e-SISTAFE nor in the REO (line [6]).

Table 1

Comparison of expenditure data in the three reports (in millions of Mozambican meticaisa).

Data included in the report

Total Expenditures

     Budget [1]117,977132,403163,035174,955
     Initial budget allocation [2]117,977132,403163,035174,955
     Current budget [3]117,977141,757163,035194,873
     Realised expenditures [4]107,710131,248139,838180,988
     Initial budget allocation [5]117,977132,403163,035174,955
     Final budget allocation [6]117,977141,757163,035196,372
     Realised expenditures [7]109,820125,932144,590190,564
Execution rate [7]/[1]93.09%95.11%88.69%108.92%
Agriculture expenditures

     Budget [8]6,1776,3965,1558,124
     Agriculture (adm. code 35) 4,6943,7814,0576,832
     Fisheries (adm. code 37) 1,4832,6151,0981,292
     Final budget allocation [9]5,2107,7426,1046,633
     Budget execution [10]4,0454,0133,8174,938
     Final budget allocation [11]5,7035,6665,4206,331
     Realised expenditures [12]4,2834,0923,9065,045
Execution rate [12]/[8]69.34%63.98%75.77%62.10%
Ag+Fisheries/Total [12]/[7]3.90%3.25%2.70%2.65%

Notes:a Unless otherwise indicated. b Cumulative data from the fourth quarter report.

Several factors explain the discrepancy between budgeted and actual values, which result in an aggregate execution rate reflecting under- or overspending, as seen in the last line of table’s upper panel. In addition to the earlier discussed reallocations, deviations from the planned disbursement of funds by donors, shortfalls or unanticipated excess in government revenue collection, and availability of supplementary funds, among others, can result in an execution rate above or below 100%. The initial allocation is first reported in the LOE [1], and repeated in the REO [2] and CGE [5] data reports. The reallocated budgets [3] and [6] did not result in any changes in some of the years, specifically in 2010 and 2012. However, in 2011, the budget was revised upwards once, and in 2013 twice (the second time reflected in the CGE), mainly due to an increase in revenues driven by foreign aid and international loans, and because the CGE report accounted for the previous year’s ending balance.

As is apparent from lines [5] to [7], the CGE contains all the relevant information of the whole budget cycle. However, that only applies to public expenditures in the aggregate. If there is interest in analysing data on a specific sector or ministry along the full budget cycle, CGE and REO do not provide such a comprehensive snapshot because they do not contain the initial budget allocations by sector, so it becomes necessary for the analyst to resort to all three reports. The bottom panel of Table 1 presents data for spending on agriculture and fisheries from 2010 to 2013 available in the three data reports.

Contrary to the relatively minor differences in public expenditure along the budget cycle in the aggregate, public expenditure on agriculture varies quite significantly among the three reports. In particular, pronounced upward as well as downward adjustments are made to the budget along the budget cycle, from initial budget, to revised budgets, to final realised expenditures. Especially notable is that the execution rate of the original budget is strikingly low, ranging from about 62% to 76%, compared to the much higher execution rate of the aggregate budget. Indeed, the Public Expenditure and Financial Accountability (PEFA) evaluations have pointed out that the absence of clear and strict rules regarding budget reallocations has reduced the credibility of the institutional budgets ().

3. The Classification and Coding Systems for Budgets and Expenditures

A state budget should be classified and presented in a way that facilitates policy analysis and promotes accountability (). A budget classification system is a public finance management tool designed to provide statistics that allow policymakers and analysts to study developments in the financial operations, financial position, and liquidity situation of the public sector in a consistent and systematic fashion (), as well as to determine the manner in which the budget is recorded, presented and reported. As such, the classification system has a direct impact on the transparency and coherence of the budget. Table 2 summarises and briefly describes the expenditure and budget classification systems available in Mozambique’s e-SISTAFE electronic system for public finance management.

Table 2

Classifiers available on e-SISTAFE.


FunctionalOrganises public spending based on the purpose underlying the expenditures. The functional classification is based on the internationally developed Classification of the Functions of Government (COFOG), in use by the United Nations, the International Monetary Fund, and the Organisation for Economic Co-operation and Development (OECD), among other international organisations. This classifier categorises public spending into, for example, health, education, defence, etc.
AdministrativeIdentifies the government body or institution responsible for budget formulation and execution. Administrative classification organises public spending, for example, in spending undertaken by the ministry of agriculture, ministry of public works, the president’s office, etc.
EconomicAllows identification of the economic nature or type of the expenditure. Like the functional classification, international standards have also been developed for the economic classification. The two broad categories are recurrent and capital spending, within recurrent spending are salaries, expenses on goods and services, subsidies to stakeholders, etc.
ProgrammaticExpresses public expenditures in terms of the government’s programmatic objectives, goals, and outcomes to be achieved. Components of expenditures by this classification often map directly into specific governmental policies. Examples are spending on: good governance, poverty reduction, combatting HIV/AIDS, etc.
TerritorialAllows registration of expenditure according to the territorial division of the country (central, provincial and district, and allocation to each jurisdiction at the provincial and district levels).
Priority sectorsIs used according to Mozambique’s Government Five-Year Plan and its Poverty Reduction Strategy.
CurrencyUsed for coding of the currency used by donor and lenders of the state.
Budget unitIdentifies the state body or institution responsible for budget formulation and execution. This is very similar to, though not identical with, the administrative classification.
Budget coverageClassifies according to the legal administration of the institution. Its main objective is to comprehensively incorporate all the central government and subnational institutions as well as state enterprises.
SectoralIs an extension of the programmatic classifier. It details the actions that are part of sectoral, provincial, or local plans.
SectionalIs an extension of the sectoral classifier. It details the actions need to be implemented by a cost centre.
ManagementAllows for individual accounts as defined by SISTAFE law: public institutions, autonomous institutions, municipalities, and state companies.
Financial statusIdentifies the financial status according to its financial and administrative autonomy.

Note: e-SISTAFE = Sistema Electrónico de Administração Financeira do Estado (Mozambique’s integrated financial management information system).

However, many of these are not in active use. Expenditures are most commonly recorded against the administrative, economic, functional, and programmatic classifications (). We next describe these systems and their use in Mozambique, provide insight into how the budget and expenditure items are coded within these classifiers, and discuss the likely utility and clarity of these classifications for data-users in the country.

Administrative classification

The administrative classification links budget allocation and spending to a governmental organisation, such as a ministry, directorate, or other cost centre, thus allowing the data user to identify agencies’ responsibilities in public expenditure management. In Mozambique, the codes for the administrative classification are detailed up to nine digits. However, most of the reports use only up to the six-digit code level. Under the two-digit code level, ministry of agriculture is coded as 35, while the ministry of fisheries is coded as 37. Appendix Table A.1 presents for an overview this classification system at the two-digit code level for the whole public sector, while Table 3 provides the basic structure of this classification system up to the four-digit level (in terms of the coding system in operation through 2012) for the ministries of agriculture and fisheries. Each four digit code pertains to a distinct agency. For example, 3501 references the ‘mother’ ministry of agriculture, while 3503 pertains to the food security secretariat, 3505 the institute of irrigation, etc. These two are separate agencies, although subordinate to the mother ministry.

Table 3

Administrative classification of the Ministry of Agriculture and Ministry of Fisheries, up to the four-digit level of the 2012 coding system.

Description [1]Coding structure
Until 2012 [2]As of 2013 [3]

Ministry of Agriculture3535
Ministry of Agriculture350135A00 0141
Food and Nutritional Security Technical Secretariat350335A00 1541
National Institute of Irrigation350535A00 5041
Provincial Directorate of Agriculture3521(01–11)35(B-L) 00(0141/2141)a
Cotton Institute delegation352235(C-I)00 1941
Delegation of the National Cashew Institute352835(C-K)00 2041
Provincial Delegation of Agriculture Promotion352935(D-J)00(1241/1341/1541)
Mozambique Cotton Institute358135A00 1641
National Cashew Institute358235A00 2141
Agrarian Research Institute of Mozambique358635A00 3641
Agriculture Promotion Centre359035A00 4341
Training Institute on Land and Cartography Administration359135A00 3341
National Centre for Cartography and Remote Sensing359235A00 4841
Agricultural Development Fund359335A00 4941
Ministry of Fisheries3737
Ministry of Fisheries370137A00 0141
National Board of Fisheries370237A00 0641
School of Fisheries370737A00 0541
Provincial Fisheries372137(B-K)00 0141
Delegations of National Aquaculture Development372637(B-G)00 0341
Fisheries Development Fund378137A00 0841
National Institute for Fisheries Research378237(A-K)00(1241/0541)
National Institute for Development of Small-Scale Fisheries378337(A-K)00(0941/2041)
National Institute of Fish Inspection378437(A-K)00(1141/0441)
National Institute of Aquaculture Development378637A00 1041

a Here, and analogously elsewhere in this table, ‘35(B-L) 00(0141/2141)’ means that, depending on the province in question, the code may be 35B00 0141 or 35B00 0141 for the Niassa or the Cabo Delgado Provincial Ministry of Agriculture, respectively, etc. Furthermore, the code for the central or provincial mother ministry of agriculture changed, so that depending on the year, for example, Niassa’s provincial mother ministry of agriculture was coded either as 35B00 0141 or 35B00 2141.

Until the 2012 LOE, the administrative classification up to the six-digit level linked the administrative classifier to the territorial classifiers (for an overview of the latter, see Appendix Table A.2). In other words, just adding the territorial two-digit suffix to any government agency leads to the six-digit administrative classifier. For example, the ministry of agriculture’s Provincial Directorate of Agriculture in Nampula province used to be coded as 352103, where 35 stands for the ministry of agriculture and its subordinate institutions, 21 for Provincial Directorates, and 03 for Nampula province. As of the year 2013, the administrative classification has changed, by replacing the territorial suffix with a letter after the ministry level (see Table 3, column [3]). Consequently, the 2013 code for the ministry of agriculture’s Provincial Directorate of Agriculture in Nampula province is 35D 00 0141, where D represents Nampula province and 0141 represents the primary agency for agriculture (which would be the ministry at the central level, and the directorate at the provincial level).

It is apparent that the administrative coding of public expenditures, both before and after 2013, is able to identify the distinct agency and the government tier and jurisdiction where it operates. It does not, however, identify units within the agencies. For example, the mother ministry of agriculture is subdivided into directorates, such as the directorate for veterinary services, directorate for agricultural extension, etc. The administrative classification does not provide unique codes to these directorates. This is an important shortcoming, in light of the value of obtaining public expenditure information by the different activities the various directorates of a ministry undertake.

Table 4 shows the levels of public expenditures for agriculture based on the administrative classification, and using data from the three main reports. Columns [2] and [4] account for the budget reallocations in each report, while [3] and [5] account for the executed spending reported.

Table 4

Public expenditures on agriculture in 2013, by administrative classification (in millions of Mozambican meticaisa).

Administrative classifierb LOE [1]REO realloc. [2]REO exec. [3]CGE realloc. [4]CGE realised [5]Execution rate [5]/[1]

35Ministry of Agriculture6,8325,4183,9985,0124,11160.2%
3501Ministry of Agriculture1,5161,7101,3431,5081,37190.4%
3503Food and Nutritional Security Technical Secretariat1513131717113.3%
3505National Institute of Irrigation3300382987.9%
3521Provincial Directorate of Agriculture1,1371,2701,0291,4281,09796.5%
3522Cotton Institute Delegation282220212175.0%
3528Delegation of the Cashew Institute1019995989897.0%
3529Provincial Delegation of Agriculture Promotion292827272793.1%
3581Mozambique Cotton Institute18718217918017995.7%
3582National Cashew Institute161126712007144.1%
3586Agrarian Research Institute of Mozambique31947714929914545.5%
3590Agriculture Promotion Centre26126413315913451.3%
3591Training Institute on Land and Cartography Administration292625252586.2%
3592National Centre for Cartography and Remote Sensing898451484853.9%
3593Agricultural Development Fund2,9291,11886296184829.0%
37Ministry of Fisheries1,2921,2159401,31893472.3%
3701Ministry of Fisheries175227201220201114.9%
3702National Board of Fisheries667363746395.5%
3707School of Fisheries303129542996.7%
3721Provincial Fisheries105110108464643.8%
3726Delegations of National Aquaculture Development195621451052.6%
3781Fisheries Development Fund148200178175163110.1%
3782National Institute for Fisheries Research12013710313210789.2%
3783National Institute for Development of Small-Scale Fisheries46317411136518740.4%
3784National Institute of Fish Inspection969473937578.1%
3786National Institute of Aquaculture Development71113511135171.8%
Agriculture + Fisheries8,1246,6334,9386,3315,04562.1%

Notes:a Unless otherwise indicated. b This table references the administrative coding system that was in place through 2012, although the coding system subsequently changed effective 2013 (for further details on this change, see Table 3). The previous coding structure is used here for easier subsequent comparison with the data in Table 10.

As discussed in Section 2, there is relatively weak control over agricultural budgeting, resulting in realised expenditures amounting to just slightly more than 60% of the initial budget allocation. This mean aggregates a wide distribution of budget execution, with less than a third of the Agricultural Development Fund budget spent, the agricultural programme with the single largest size in the original budget, and on the other hand the mother ministry of fisheries spending 15% above the original allocation. The table shows that there are nontrivial differences in the budget figures along the budget cycle, not only between initial allocation and final expenditures, but also between the reallocated budgets in the REO versus CGE (columns [2] vs. [4]), and between realised/executed spending in the REO vs. CGE ([3] vs. [5]). Thus, analysts need to be well aware of how the figures in the columns represent different stages in the budget cycle—an issue ignored in a good deal of public expenditure analysis.

Economic classification

The economic classification of expenditures links the budget to economic categories, such as expenditures for goods and services or capital expenditures. The economic classifier of expenditures in Mozambique aims to identify the nature of the expenditure, according to the following five levels: The first level indicates the economic categories of current and capital expenditures (see Table 5, which presents the economic classification up to the three-digit code level). The second level indicates the aggregate group of expenditure, such as personnel costs (code 11 in Table 5) or goods and services (code 12). The third, fourth, and fifth levels indicate further economic breakdown of expenditure. For instance, the retirement expenditure category is coded as 143101, where the first level (code 1) is current expenditure, second is current transfers (code 14), third is current transfers to households (code 143), fourth is civil servants’ pensions (code 1431), and finally the fifth level is retirement spending for civil servants, for a complete code of 143101. The formal economic classification system for Mozambique provides a breakdown to the level of a six-digit code (five levels).

Table 5

Economic classification, up to the three-digit code level.


1Current Expenditure2Capital Expenditure
11     Personnel costs21     Capital goods
111          Wages and salaries 211          Construction
112          Other staff costs 212          Machinery, equipment, and furniture
12     Goods and services213          Means of transport
121          Goods 214          Other capital goods
122          Services 22     Capital transfers
13     Debt burden221          Capital transfers to public administrations
14     Current transfers222          Capital transfers private administrations
141          Current transfers to public administrations 223          Capital transfers to households
142          Current transfers to private administrations 224          Other capital transfers
143          Current transfers to households 23     Financial operations
144          Current transfers abroad 231          Active financial operations
15     Subsidies232          Passive financial operations
16     Years ended24     Other expenses of capital
161          Pay back
162          Back payments of goods and services
163          Pension retroactive
164          Other payments for six-month periods ended
17Other current expenditure

It is important to highlight that the economic classification of expenditure, as shown in Table 5, is not to be confused with another categorisation widely used in Mozambique, which distinguishes between operational (funcionamento in Portuguese) and investment (investimento) expenditures. The ‘investment’ category should not be assumed to represent expenditures contributing to public capital formation, or capital expenditures. This ‘operational/investment’ categorisation is a long-standing approach in Mozambique and is used in all the data reports (that is, the LOE, the REO, and the CGE). It was agreed on with the International Monetary Fund and the World Bank in order to differentiate in the state budget the expenditures funded by donors, at the time typically associated with the ‘investment’ category, from those financed domestically, associated with the ‘operational’ category. However, the definition of this categorisation has been diluted over time: the ‘investment’ category began to include domestic funding sources, given government counterpart funding in donor-supported projects.

Table 6 shows the agriculture and fisheries public expenditures in 2013 by economic classification as well as by operational/investment categorisation, comparing LOE and CGE reports. While the public finance data reports disaggregated ‘operational’ expenditures by economic classification, the same is not done for the (far larger in size) ‘investment’ category. The fact that, as the table shows, it is the investment category that contributes the most to a poor budget execution rate strengthens the argument that this category would need to be further disaggregated by economic classification, in order to gain meaningful insights into the reasons for the large degree of underspending, so that the DNO can exercise more effective monitoring and spending control.

Table 6

Agriculture and fisheries public expenditure in 2013 by economic classification and operational/investment distinction (in millions of Mozambican meticais).

Operational/investment categorisation and economic classifier (categories)LOE [6]CGE realloc. [7]CGE realised [8]Execution rate [7]/[6]

Operational category (funcionamento)1,7601,6621,38878.9%
       Staff expenses1,00495791491.0%
       Good and services67161542262.9%
       Current transfers83733744.6%
       Capital goods22150.0%
Investment category (investimento)a 6,3644,6693,65757.5%

Functional classification

The functional classification (Classification of the Functions of Government, or COFOG) has shown to be of relevance to a broad variety of analyses (). It classifies expenditures according to their socioeconomic purposes. In Mozambique, the internationally defined COFOG system was officially adopted in 2005, although the functional presentation of the budget is not formally approved by parliament and therefore is not legally binding.

The distinction between economic and functional classifications can be summarised as the difference between what expenditures are spent on versus what expenditures are for. The economic classification described above details the particular items on which resources are expended—that is, expenditures on salaries, goods and services, capital formation, and so on—while COFOG organises public expenditures in such a way as to provide information about the purposes toward which these expenditures are undertaken, that is, expenditures to provide agricultural services, health-care, road infrastructure, and so forth. The functional classification often is close, but rarely equivalent, to the administrative structure of government. This is because public expenditures in an agency, such as the President’s office, may pertain to a sector such as agriculture. In principle, then, the functional classification would gather public expenditure data on agriculture (as one example of a function), irrespective of which agency is responsible for the budget item.

Appendix Table A.3 outlines the internationally established functional classification of public expenditures according to COFOG and includes subcategories below the first COFOG level only for functions related to agriculture expenditure: those that either constitute or encompass agriculture-related functions. There are 10 broad categories, which are at COFOG level 1. Several familiar functions, such as health (COFOG code 07) or education (COFOG code 09) are level 1 categories. Agriculture and related functions are collectively treated as a category at the second and lower levels. Specifically, agriculture is found below the level 1 category of ‘economic affairs’ (coded as 04). The main agriculture-related category (coded as 042) groups together crop and livestock agriculture, forestry, and fishing and hunting. Another level 2 subcategory under economic affairs is R&D, with code 048; under that, at level 3, is agricultural R&D (code 0482). For an easy overview of both the levels and the functions of the categories related to agriculture, level 1 categories are shaded in Appendix Table A.3, level 2 categories are unshaded, and level 3 categories are italicised. The last column of the table summarises the relation to agriculture functions.

Mozambique’s organisation of expenditure data by functional classification is broadly consistent with the Government Finance Statistics Manual 2014 (), except for minor variations at the third and fourth levels of the classification. For example, this classification scheme includes agriculture-related function codes such as 04213 ‘Prices and Agricultural Productivity’ or 04214 ‘Rural Extension.’ The functional classification and coding used in Mozambique up to level 4 is shown in Table 7. In Mozambique, expenditure by functional categorisation down to level 2 (which identifies agriculture) is reported in the REOs and CGEs, but not in the LOE. Table 7 summarises the functional classification of realised agricultural expenditures obtained from the CGEs for the years 2010 to 2013. A review of this table shows that roughly 60 percent of the total agricultural expenditure is aggregated in an ‘Other’ type of category, namely ‘Agriculture, Forestry, Fishing, and Hunting NEC’, where NEC stands for ‘not elsewhere classified’ (code 04291). This means that the existing de facto functional breakdown does not provide the meaningful insights it was intended to have.

Table 7

Agricultural public expenditures (CGE realised expenditure), by functional classification level 4 (in millions of Mozambican meticais).


04211Land managementa 0
04212Agrarian reform5244513
04213Prices and agricultural productivity34
04214Rural extension63158107405
04216Pest control402552
04219Other services NEC297275226166
04232Huntinga 0
04291Agriculture, forestry, fishing, and hunting NEC2,1052,0171,8942,972
042Agriculture, forestry, fishing, and hunting3,5023,3863,1244,687

Notes: NEC = not elsewhere classified. a Zero in 2010 in Land Management and Hunting are positive values rounded. The actual numbers are 0.072 MMT and 0.215 MMT respectively.

Programmatic classification

The programmatic classification organises expenditures according to programmes that are designed to meet particular government policy objectives. A programmatic classification is intended to be supportive of the priority setting of the budget by being based on outputs (). Mozambique’s programmatic classification of strategic planning has the following hierarchical structure: (i) at the highest stage in this classification hierarchy is the Central Objective for the Government Five-Year Plan (Objetivo Central do Programa Quinquenal do Governo, or OCPQG), (ii) next below that are Strategic Areas (Áreas Estratégicas, or AE), then (iii) Strategic sub-areas (Subárea Estratégico, or SAE), (iv) Programmes of Government (Programas de Governo, or PG), (v) Subprogrammes of Government (Subprogramas de Governo, or SPG), (vi) and finally at the bottom of the hierarchy, Budget Actions.

The Central Objective for the Government Five-Year Plan (OCPQG) classifier aims to show the organisation of the strategic macro objectives of the government, which are defined in the PQG. This classifier captures six objectives in three-letter codes (BGD, CPD, DEC, DHS, RCI, and RDS) the descriptions of which are shown in Table 8. If a programme does not fit into one of these six defined OCPQG objectives, additional codes are used for such programmes. The Strategic Area (AE) classifier organises categories under each OCPQG objective, each Strategic Area (AE) is further broken down into Strategic Sub-Areas (SAE), and so forth (Table 8 shows codes and descriptions only up to the AE level).

Table 8

Programmatic classification categories.

OCPQG CodeAE CodeAE Description

OCPQG Objective BGD: Good Governance, Decentralisation, Combatting Corruption and Promotion of a Culture of Accountability
BGDAAEAdministration of State Apparatus
BGDDALDecentralisation and Development of Local Government
BGDICSInformation and Media
BGDOSTOrder, Public Safety and Tranquillity
BGDRSJReform of the Justice Sector
BGDRSPPublic Sector Reform
OCPQG Objective CPD: Consolidation of National Unity, Peace, and Democracy
CPDUNINational Unity
OCPQG Objective DEC: Combatting Poverty and Promoting the Culture of Work: Economic Development
DECAGRAgriculture, Fishery, Forestry and Livestock
DECDIEDevelopment of Infrastructure
DECDRURural Development
DECGMDMacroeconomic Management and Financial Systems Development
DECPAIPromotion and Attraction of Investment
DECRCMMineral Resources
DECTHEWork, Health and Safety and Employment
DECTRCTransport and Communications
OCPQG Objective DHS: Combatting Poverty and Promoting the Culture of Work: Human and Social Development
DHSAGSWater and Sanitation
DHSCTIScience, Technology and Innovation
DHSLDDNational Liberation and Defence of Sovereignty and Democracy and the War-Disabled—Demobilisation
DHSMASWomen, Family, and Social Action
OCPQG Objective RCI: Reinforcing International Co-operation
RCIREXExternal Relations
OCPQG Objective RDS: Strengthening Sovereignty
RDSDSNDefence of National Sovereignty

A programmatic classification is rather complex to define, and even more so to apply. Because of this, this classification is not applied with as high a degree of comprehensiveness as the concept of functions of government could in principle be applied (the de facto application of the functional categories and its shortcomings has been discussed above). When a functional classification is applied properly, all of the activities of government are categorised inside one function or another, in a mutually exclusive and exhaustive fashion. The programmatic classifiers, on the other hand, refer only to certain types of public expenditure that are of particular interest to government strategy, and thus do not exhaustively capture all public expenditure related to a specific function.

According to the actually applied programmatic classification in Mozambique, in 2013, the only clearly traceable strategic area (AE) linked to the agricultural sector is that of ‘Agriculture, Livestock, Forestry, and Wildlife,’ with allocations to both central and provincial levels for a total of 5,436 million meticais, as shown in Table 9 (see code DEC-AGR). Expenditure data classified using these programmatic classification codes as shown in Table 9 are only available in the LOE. Expenditure information in the REO and CGE documents do not use this programmatic classification system anywhere, making it impossible to trace actual expenditures by these programmatic codes, or to determine budget execution rates based on these codes.

Table 9

LOE 2013 Agricultural budget, by programmatic classification (in million Mozambican Meticais).


OCPQG Objective DECa Combating poverty and promoting the culture of work – economic development38,58050,37169,30561,427
Strategic Area (AE)DEC-AGRAgriculture, livestock, forestry and wildlife3,1632,7313,0195,436
Strategic Subarea (SAE)DEC-AGR-00Agriculture, livestock, forestry and wildlife2,2072,7313,0195,436
DEC-AGR-00-AGR01Administrative institutional support68353299
DEC-AGR-00-AGR02Agricultural production and productivity1992,396121
DEC-AGR-00-AGR03Management of natural resources2,008
DEC-AGR-00-AGR04Production oriented market245312
DEC-AGR-00-AGR06Use and utilisation of land22270
DEC-AGR-00-AGR11Agricultural production1,4244,266
DEC-AGR-00-AGR12Agricultural productivity90172
DEC-AGR-00-AGR13Natural resource management879565
DEC-AGR-01Food security956
DEC-AGR-01-AGR02Agricultural productivity929
DEC-AGR-01-AGR03Natural resource management27
DEC-DRU-00Rural development3,0282,7861,998
TotalDEC-AGR + DEC-DRU-00Agriculture, livestock, forestry and wildlife + rural development3,1635,7595,8057,434

Note:a The total expenditure at the DEC level contains more than the AE level expenditures shown here. The other AE level expenditures of DEC are not shown here for economy of space, since they do not relate to agriculture.

Priority-sector classification

While the programmatic classifier is not present in the REO and CGE, a similar-in-spirit classifier is reported in the REO and CGE documents. This is an organisation of expenditures that are considered ‘priority sectors’ according to poverty reduction strategies of the government. The priority sectors according to which expenditures are reported in, for example, the CGE 2013 are: Education; Health; Infrastructure; Millennium Challenge Account; Agricultural and Rural Development; Governance, Security and Judicial System; and Other Priority Sectors. In this case, the priority programmes do not have designated codes, but only titles (e.g. Education, etc. as denoted above). Then, under each such title/sector are organised public expenditures by administrative classification, with the corresponding administrative codes.

For example, the agriculture and rural development priority-sector expenditure is meant to correspond to the sum of spending related to the agricultural sector and rural development undertaken within all institutions, not only in the ministries of agriculture and fisheries. Table 10 presents the expenditures with their corresponding administrative codes that are considered to fall under the ‘agriculture and rural development’ priority-sector.

Table 10

Agricultural and rural development realized expenditure (CGE), by priority-sector and administrative classification (in millions of Mozambican meticais).

Broad priority-sector categories and administrative classification2010201120122013b


    01 Office of the President14395,4466,923
    0122 District Administrations14395,4466,923
    03 Office of the Prime Minister10034
    0311 Development Agency of the Zambeze valley10034
    26 Ministry of Planning and Developmentc 2255581,1011,446
    2601 Ministry of Planning and Development225220191267
    2607 National Institute of Statistics268
    2609 Millennium Challenge Account Program338462548
    2628 Special Economic Zones18
    2681 Development Agency of the Zambeze valley65558
    2683 Centre for Investment Promotion47
    2685 Office for Accelerated Development Economic Areas48
    2687 Fund for Economic Rehabilitation172
    35 Ministry of Agriculture3,3803,3492,9984,024
    3501 Ministry of Agriculture1,1861,1851,2181,364
    3503 Food and Nutritional Security Technical Secretariat7717
    3521 Provincial Directorate of Agriculture1,3161,0038171,032
    3522 Cotton Institute Delegation181421
    3528 Delegation of the Institute for Promotion of Cashew Nuts29375298
    3529 Provincial Delegation of Agriculture Promotion2327
    3581 Mozambique Cotton Institute486291179
    3582 Institute of promotion of cashew nuts, INCAJU19429111571
    3586 Agrarian Research Institute of Mozambique306265177149
    3590 Agriculture Promotion Centre196245110134
    3591 Training Institute on land and cartography adm.16212025
    3592 National Centre for Cartography and Remote Sensing25362551
    3593 Agricultural Development Fund (FDA)63190327854
    37 Ministry of Fisheries813961
    3701 Ministry of Fisheries241201
    3702 National Board of Fisheries4563
    3707 School of Fisheries1929
    3721 Provincial Fisheries69108
    3726 Delegations of the National Aquaculture Development821
    3781 Fisheries Development Fund151163
    3782 National Institute for Fisheries Research78107
    3783 National Institute for Development of Small Scale Fisheries121142
    3784 National Institute of Fish Inspection4475
    3786 National Institute of Aquaculture Development3751
Rural Development198194

    25 Ministry of State Administration8179
    2501 Ministry of State Administration7768
    2509 National Institute of Disaster Management48
    2521 Provincial Directorate of Support and Control4
    41 Ministry of Industry and Trade118115
    4101 Ministry of Industry and Trade110109
    4121 Provincial Directorate of Industry and Tradea 0
    4185 Institute for Promotion of small and medium enterprises75
Total Agricultural and Rural Development3,7193,98010,55713,548

Notes:a Zero in 2013 Provincial Directorate of Industry and Trade stands for a rounding issue. The actual number is 0.30 MMT. b The 2013 data was matched to the administrative coding system that was in place through 2012, although the coding system subsequently changed effective 2013 (for further details on this change, see Table 3). This is done for easier comparison of the data across years in this table.

c This also includes rural development expenditure.

Within the administrative classifiers categorised under the Office of the President, there is spending by government through local development funds by the district administrations), in which agriculture related spending may be significant (see Table 10). At the district level, institutions are not represented using the traditional administrative classifiers found at central or provincial levels. Instead, at this local level the key agencies are referred to as ‘services’, and one service may cater to more than one sector. For example, agricultural activities are undertaken both under District Services for Economic Activities (SDAE) as well as under District Services for Planning and Infrastructure (SDPI). Both services also undertake non-agricultural activities. This, of course, can make it difficult to know how much goes just for agriculture at the district level, given that district expenditure data are reported primarily at the level of the services.

The priority-sector classification system, as it is used in Mozambique, is fairly nonformal in its nature. Despite changes in the accounting rules over the past few years, this classification system still does not provide a reliable instrument to comprehensibly aggregate agricultural expenditure. For example, since 2012, agricultural expenditure by priority sector classification has shown a greater than three-fold increase (see Table 10). Indeed, district administrations (code 0122), through the district development fund, made an extreme jump to more than 139-fold from 2011 to 2012. Both the increase of agricultural spending from one year to the next by over 250%, driven by the increase of one component by about 13,000%, raises serious questions about whether this is a genuine increase in spending of given categories, or a reclassification to boost the reported aggregate agricultural spending figures.

Promises and pitfalls of using public expenditure data along Mozambique’s classification systems

Mozambique’s public financial management system has improved substantially since the 1990s, with the introduction of e-SISTAFE. One of the outcomes of reform efforts is the abundant availability of highly detailed public finance data to any Mozambican analyst, through free online access of data reports over multiple years. But the existence of so many classifiers reduces the public expenditure data reports’ usability. First, there are a number of classifiers within Mozambique’s accounting system that are not in fact actively used in the official reports (see Table 2). Second, even some of those classifiers on the basis of which official reports present spending data are only very partially applied—for example, only for budgets but not realised expenditures (or vice versa), or only to a subsection of the overall budget. Consequently, in order to precisely define the expenditure of the ministry of agriculture and its agencies by administrative and economic classification, one must reconstruct public expenditures across hundreds of report pages. This renders the task of quantifying agricultural public expenditures unwieldy for analysts who are not technical staff in MEF or MPD, or otherwise do not have the capacity and time to dedicate to developing a very intimate acquaintance with the detailed methods in the LOE, REO and CGE reports.

In particular, the functional classification of government expenditures would be of significant interest to a wide range of policy analysts. However, Mozambique agricultural expenditure organised along COFOG lines provides a breakdown of agricultural spending for less than half of what it considers to fall under this function. This may not be a barrier to those analysts who are solely interested in deriving the totality of agricultural spending. However, even for them it is not possible to verify what type of agricultural activities over 60% of these expenditures support. As a result, it is not optimal for use in an aggregation process for policy or analytical purposes.

There is greater disaggregation in the organisation of government public accounts along administrative lines, with expenditures grouped by the ministries and agencies undertaking the expenditures. Also, the administrative classification is applied fully along the budget cycle, from the initial budget allocation to realised expenditures in audited financial statements. Perhaps the most significant shortcoming of this classification in Mozambique’s data reports is that the breakdown stops at whole agencies, and does not continue to major units or divisions within agencies. To see why this may be a problem, the National Directorate for Promotion of Rural Development (DNDPR), which is part of the Ministry of State Administration, should be accounted for in agriculture, given its large focus on providing agricultural extension to farmers. However, since it is a directorate within a different ministry that does not otherwise focus on agriculture, there is no administrative classification that identifies DNDPR’s activities. So, adding a budgetary allocation code at the sub-agency level would allow one to clearly identify functionally differentiated actions within an agency, as well as to explicitly define transparent rules to aggregate expenditure. Consequently, strengthening the administrative classifier by further disaggregating it to directorates within agencies seems a reasonably simple and plausible way to enhance the quality and usability of the public expenditure data.

The economic classification, in use across all of Mozambique’s major public expenditure data reports, is helpful for gaining insights on how expenditures on functions or sectors break down by salaries, capital equipment, operational expenditures such as goods and services, etc. However, the active use in Mozambique of the ‘operational/investment’ classifier (funcionamento and investimento in Portuguese), in parallel to the more conventional economic classifier, functions as a source of high potential confusion for analysts, given that it seems close to the recurrent/capital distinction of the economic classification, but this is not so. If the operational/investment categorisation is to be retained, it should be reconceived as a category that can be directly mapped into the existing economic classification, to avoid the potential confusion. Furthermore, when examining the data underlying the operational and investment categories, the latter is currently the largest source of underspending in agriculture, which clearly impacts midterm planning. The proper mapping of the operational and investment categories into the economic classification may allow MEF and the legislative body to increase their control over budget execution by increasing clarity about the concrete sources of low budget execution, and thus reduce budget underspending.

In the absence of administrative coding of directorates within ministries, as discussed above, one source for identifying these additional agricultural expenditures is the so-called priority sectors classifier, which was detailed in Table 10, and includes, for example, spending by government through local development funds, where agriculture-related spending may be significant. However, caution is warranted in the process of extracting agricultural expenditure data undertaken by other ministries in this way, since doing so relies on the assumption that the government has properly identified such public expenditures as being properly associated with agriculture. Both the trends observed in Table 10, such as the more than 130-fold increase in the expenditures of district administrations claimed to be associated with agriculture from one year to the next, as well as the possibility that policy dialogue and external mandates to spend more on agriculture could create incentives to assign more budget items to the sector, are examples of why care is needed in relying on the priority-sector categorisation in correctly identifying agricultural public expenditures.

Figure 1 gathers and compares figures on total realised expenditures on agriculture obtained from CGE reports, calculated based on the functional, administrative, and priority-sector classification systems—as well as agricultural expenditure figures obtained from two major cross-country public expenditure databases, namely the International Monetary Fund’s Government Finance Statistics, and the International Food Policy Research Institute’s SPEED database (Statistics on Public Expenditures for Economic Development) (). The latter two sources did not have data available for the last two years, 2012 and 2013, at the time of this research. Overall, we see that the figures vary across the different classification systems used, in some cases wildly so. For example, while the lowest figures in 2010 and 2011 were 82% and 83%, respectively, of the highest figures—reflecting a nontrivial variation, in 2012 and 2013 the analogue shares were more dramatic, 30% and 35% respectively. The outsized estimates derive from the priority-sector classification, which jumped drastically from its two previous years. A more in-depth examination beyond the scope of this analysis would be warranted to determine whether this was a real increase on agricultural spending at the local government level, or a reclassification of previously existing spending that used to not be considered as agriculture, possibly in response to the imperative from the Africa-wide CAADP (Comprehensive Africa Agriculture Development Programme) process to spend more on agriculture.

Figure 1 

Comparison of agricultural public expenditures across different data sources, 2010–2013 (in millions of Mozambican meticais).

Notes: GFS = Government Finance Statistics; SPEED = Statistics on Public Expenditures for Economic Development.

It should be expected that the agriculture COFOG includes expenditures from agencies besides the ministries of agriculture and of fisheries. This is because expenditures on a particular function are often undertaken by government agencies that have a partial mandate for the particular function. Agriculture is a good example of the dispersion of functional spending across various agencies. For instance, the Ministry of Water Resources invests in irrigation for crop production, and the Ministry of Education funds agricultural training. Consequently, COFOG’s agricultural expenditure should be larger than the expenditure of the ministries of agriculture and fisheries combined. However, contrary to expectation, the functional-classification based figures are lower than the administrative-classification based figures. In fact, the figures based on the functional classification are the lowest across all measures.

4. Discussion

Public expenditures can serve as a prime instrument in Africa to spur development and economic growth, especially for the continent’s vast rural population. Ever since the African Union adopted a guidance in 2003 for African countries to spend at least 10% of their budgets on agriculture, the lens of African researchers, policy makers, and civil society has been focused on the data needed to measure and quantify agricultural public expenditures across countries. However, there have been persistent inconsistencies in reports on the amount that is spent on agriculture across Africa and to some extent other developing countries.

These academic and policy concerns motivate this paper, which empirically examines an African case study—Mozambique, a low-resourced economy even by the continent’s standards—to determine what primary data are in fact available to quantify the volume and make-up of government fund allocation in the agricultural sector. Our examination of detailed primary data on Mozambique’s public expenditures sheds broader light on measures that could be taken across African countries, so that researchers can at least partially overcome the twin challenges of inconsistency and lack of clarity about already available and reported agricultural spending figures.

We find that there is a surprising degree of openly available and highly detailed data on government budgets, budget executions, and final realised expenditures in Mozambique. Thus, like in some other African countries (e.g. Kenya and Malawi), but unlike in others, physical inaccessibility is not always the primary constraint that data users face. However, data users will have to carefully navigate multiple indicators of public resources that vary along the budget cycle, from initial budget allocation to realised expenditures. Such navigation will naturally require a solid understanding of the country’s budgetary processes. Furthermore, for any stage in the budget process, public expenditures are disaggregated in multiple different ways—along administrative, economic, functional, programmatic, and priority-sector related classification systems. In our analysis, using each of these to re-aggregate up agricultural public funds results in different figures. In some cases these figures differ by a nontrivial but still manageable amount (at least for those analysts who are interested in ballparks rather than precise figures). In other cases, however, these different methods of re-aggregations produce wildly different results. These mainly emanate from the priority-sector classification, in which one budget item classified as being part of agriculture spending increased more than 130-fold, at the time when Mozambique joined the African Union initiative mandating that 10% of total expenditures go to agriculture.

In the environment of low income and low administrative capacity that characterises the public sector of many African countries, including Mozambique, these systems must guard against the use of too many classification systems in use. With data on public spending broken down in fine detail for each classification, it is not surprising that deficiencies in the consistency and organisation of any one classification leaves much to be desired. For example, the effort and time spent by ministries of finance and other officials in African nations disaggregating public expenditures along programmatic and priority-sector classifications—which in our empirical analysis are already fairly incomplete, available only for one or two stages in the budget cycle, not particularly transparent, and thus of little use—could be saved by dropping these two classifications from public expenditure classification systems, even though they tend to be popular with donor agencies and thus often requested by them. If instead this time were dedicated to refining those classification systems of most direct value to ministries of finance and line ministries—such as the administrative classification—by assigning budget codes not only to whole agencies but to directorates within agencies, such data could be highly useful for more credibly identifying public expenditures on agriculture, and for that matter on other functions and sectors. This will also free up capacity to to strengthen the currently weakly implemented, but analytically and conceptually important, functional classification system.

Generally, with the remarkable detail on public funds data available to the public in Mozambique and selected other African countries, despite some of the data’s drawbacks and the demands on ability to use them, it behoves higher-capacity domestic researchers to undertake the effort to use the existing detailed primary data to re-aggregate sectoral spending, rather than to solely rely on secondary figures, especially given the ‘black box’ nature of much of such readily available statistics.

Additional Files

The additional files for this article can be found as follows:

Table A.1

Administrative classification at the Two-digit code level. DOI: https://doi.org/10.5334/dsj-2018-009.s1

Table A.2

Territorial classification at the Two-digit code level. DOI: https://doi.org/10.5334/dsj-2018-009.s1

Table A.3

Classification of the Functions of Government (COFOG), with details on agriculture. DOI: https://doi.org/10.5334/dsj-2018-009.s1