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Unpacking the ‘Black Box’ of Public Expenditure Statistics; Lessons from a Diagnostic Analysis of Agricultural Sector Public Expenditures
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Unpacking the ‘Black Box’ of Public Expenditure Statistics
Lessons from a Diagnostic Analysis of Agricultural Sector Public Expenditures
Agriculture Public Expenditure Workshop8. October 2014, Golden Peacock Hotel
Lilongwe, Malawi
Objective of this Research Programme
• Several major policy initiatives requiring measurement and tracking of public expenditures in support of the agriculture sector (e.g. CAADP, country strategies, IDPs)
• However, how to measure the quantity of agricultural expenditures?• Inconsistencies: Different reports and databases report different
figures (for the same country and year)• Non-transparent aggregates: Not always clear what “ingredients
went into the soup”
• This research programme seeks to offer approaches for country analysts to quantify agPEs in a consistent and transparent way
• 4 country cases: Ghana, Kenya, Malawi, Mozambique
Tracking Aggregate Ag. PE over Time– Growth of Funds or of Coverage?
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CAADP guideline: 10 % ag spending share
• Data in earlier years didn’t include public expenditures related to cocoa, debt servicing; subsequently included
• Most recent data started including local government funds, and feeder roads
Ghana
What the Research Programme Is Not
• What this IFPRI programme is not primarily about:• Econometric analysis of the returns to and impact of public
expenditures in agriculture
other longstanding research on this in IFPRI and elsewhere• A database or dataset of public expenditures in agriculture
several initiatives have generated such datasets (especially cross-country), by IFPRI, IMF, FAO, OECD, etc.
• Descriptive review of trends and patterns of agricultural expenditures
other well established work on this through World Bank AgPERs, and through other initiatives (however, complementary, and Malawi AgPER to be presented here)
Unpacking the ‘Black Box’ of Public Expenditures in Agriculture:
A Case Study of Mozambique
Tewodaj Mogues, Senior Research Fellow, IFPRI, Washington DC
(Collaboration w/ Leonardo Caceres, Francisco Fernandes, Mariam Umarji)
Agriculture Public Expenditure Workshop8. October 2014, Golden Peacock Hotel
Lilongwe, Malawi
World Bank AgPER:PE in Ag. 20073,281 MMT2,773 MMT (excluding OILL)
Different figures in different reports
IMF Article IV Consultation: PE in Ag. & Rural Dev’t 20072,067 MMT
Different figures in different reports
Step 1:
Decide on the scope of expenditures to fall under “agriculture”
Proposal to undertake a “DIY” approach, using the existing government public accounts
Step 2:
Understand nature of expenditure data along the budget process
Understanding expenditure data along the budget process
Step 3:
Understand the types and quality of the classification systems in use
A multiplicity of classification systems: Too much of a good thing?
Functional classification: COFOG (IMF GFSM 2001)
COFOG Level 1
Functional classification: COFOG (IMF GFSM 2001)
COFOG Level 2 COFOG Level 3 No int’l coding for Level 4
Not
Functional classification: COFOG (IMF GFSM 2001)
Functional classification: COFOG (IMF GFSM 2001)
Functional classification: COFOG (IMF GFSM 2001)
Functional classification: Great in principle … but limited usefulness as practiced
Mozambique applies Level 4 codes
Not used in the budget data, but only in the execution and actual expenditure data
Administrative classification: Detailed, and of relevance to government for its operations
However, changing coding system over time, and no dedicated codes for units within a ministry
Programmatic classification
Useful, though not a comprehensive system
Step 4:
Reconstruction of agricultural public expenditures using the most appropriate
classification system(s)
Illustration of reconstruction using administrative and programmatic classification
Illustration of reconstruction using administrative and programmatic classification
Illustration of reconstruction using administrative and programmatic classification
Step 5:
Accounting for domestic and donor spending that is not captured in the public accounts
Comparison with international and national expenditure data sources (2010)
Comparison with international and national expenditure data sources (2011)
Some key take-aways
• Analysts and others wanting to obtain time-consistent information on how much PE is going to agriculture need to work with the appropriate classification and coding systems of government accounts
• The administrative system of classification tends to be most versatile for reconstruction of agPE
• But coding system should be more detailed, follow a clear logic, and be consistent over time
• IDPs should be aware of capacity constraints, and asking for too many classification systems reduces their quality
Unpacking the ‘Black Box’ of Public Expenditures in Agriculture:
A Case Study of Mozambique
Presented by: Tewodaj Mogues, Senior Research Fellow, IFPRI, Washington DC
Agriculture Public Expenditure Workshop8. October 2014, Golden Peacock Hotel
Lilongwe, Malawi