The document discusses the collection of data from SADC countries for monitoring and evaluating progress towards the CAADP goals of allocating 10% of national budgets to agriculture and achieving 6% agricultural growth. It notes low response rates and gaps in the data collected. The data collection process involved consultants collecting data from government departments with some issues around clarity of the questionnaire and validation of data. The gaps in the data mean it is difficult to produce comprehensive regional statistics or meaningful analysis of progress towards the CAADP goals.

1. 2011 CAADP M&E :Data Response Analysis
By
Raymond Nkululeko Maseko
Regional Strategic Analysis and Knowledge Support System for Southern Africa (ReSAKSS-SA)
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

2. Content
• Introduction
• Rational
• Data Collection Process
• Observations – Data collection & collected data
• Results of Analysis
• Suggestions
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

3. Introduction
In June 2011 SADC country consultants were contracted to
collect data for the purpose of Monitoring and Evaluating
CAADP process; in particularly, progress made towards
achieving the 10% allocation of national budget to
agriculture and 6% growth in agricultural output.
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

4. Rational
The main objective of the response analysis is to establish:
a. the overall response rate for all the SADC countries that collected data which are
Angola, Botswana, DRC, Lesotho, Malawi, Mozambique, Namibia, South Africa,
Swaziland, Tanzania, Zambia and Zimbabwe;
b. a response rate per question and section with a view to identifying gaps in the
data;
c. which critical questions and sections are affected by gaps in the data;
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

5. Data Collection Process
IWMI IWMI & Consultants Consultants
Step 1 Step 6 Step 7 Step 8
Finalise questionnaire Workshop Questionnaire Develop Resource Setup data Collection
preparation Methodology Schedule by Country Appointment Schedule
Step 2 Step 5 Step 10 Step 9
Normalise Issue an electronic Collect Data and Confirm Schedule
questionnaire (Format, Questionnaires and Complete Questionnaire
questions, validation) Checklist
Step 3 Step 11
Step 4 Step 12
Develop Questionnaire Perform High Level Data
Design Computer Carry out spot checks
Completion Checklist Validation, Complete Checklist and
Database Structure
provide weekly status update
Step 16 Step 15 Step 14
Step 13
Capture Data into a Project Coordinator Record Submit electronic
Complete Checklist
Regional Database Receipt of Questionnaires Questionnaire and Checklist
Step 17 Step 18 Step 19
Validate Captured Data Update Checklist Handover Database to Analysts
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

6. Observations on data collection and collected data
1. Most country consultants outsourced collection of data or submitted requests to various government departments to fill
out the questionnaire;
2. In some cases there is no evidence to suggest that the questionnaire was thoroughly discussed with subcontractors or
departments that were requested to complete the questionnaire or sections of the questionnaire;
3. Not all countries responded to all spot check issues that were raised with them. In fact some consultants choose to address
the data issues in their country reports;
4. There is no evidence to suggest that some country consultants checked data before it was submitted to IWMI Project Co-
ordinator;
5. When country consultants presented their draft reports during the workshop, most of the reports were not based on
collected data but a different data source;
6. Questions that were asked by some country consultants during the second data workshop suggested that either the
questionnaire was not clear or there was a communication breakdown / problem;
7. Some country consultants could not explain some of the ambiguities in the data because it was transcribed from source as
is and without any explanation;
8. It is not clear:
a. if data is not available; or
b. at source it is not stored / collected in a manner that can easily relate to the way questions are structured in the
questionnaire; or
c. there is inadequate skill to extract data in the manner it is required on the questionnaire.
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

7. Impact of gaps in the data
It is not possible to produce comprehensive combined regional statistics for
meaningful analysis and the table below is one of the example
Agriculture expenditure as a percentage of AgGDP
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Botswana 57.39536 58.87476 67.53936 53.47036 55.69629 59.10841 49.41439 41.81901 40.43799 32.32517
Malawi 28.81457 34.73428 49.74135 46.966 3.422355 8.573295 13.47078 17.45058 19.05711 26.43682
Swaziland 8.329403 11.11626 11.0481 15.94108 17.66625 14.57973 13.32836 25.01819 30.36949 24.40279
South Africa 16.44749 16.23911 13.92657 16.20926 18.05014 22.92123 24.14941 26.36115 24.57718 23.77911
Zambia 3.696304 6.429125 5.2664 6.855124 6.573276 7.733492 9.25641 13.05252 16.52246 10.52671
Lesotho 15.36789 8.462462 14.15812 13.62344 13.40708
Mozambique 1.904167 6.363125 5.811887 8.506668 11.40644 10.37076 10.26641 5.553242 6.75931
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

8. The percentage in each column represents available data measured against an
expected 100% response rate for each indicator. This table must be read in
conjunction with indicator bar charts showing gaps in the data
Indicator
Mozambique
South Africa
Zimbabwe
Swaziland
Botswana
Tanzania
Namibia
Average
Lesotho
Malawi
Zambia
Angola
DRC
B1. OVERVIEW OF REVENUES AT NATIONAL LEVEL 52% 60% 49% 56% 59% 51% 8% 62% 52% 30% 33% 60% 48%
B2. BUDGET ALLOCATION AT NATIONAL LEVEL 67% 50% 41% 67% 67% 61% 33% 67% 83% 64% 61% 67% 60%
B3. BUDGET ALLOCATION BY AGRICULTURAL SUB-SECTOR 25% 23% 26% 30% 78% 18% 49% 52% 74% 5% 58% 44% 40%
B4. BUDGET ALLOCATION BY FUNCTION/DEPARMENT 7% 53% 26% 41% 0% 43% 30% 27% 70% 10% 46% 55% 34%
B5. ACTUAL PUBLIC EXPENDITURE AT NATIONAL LEVEL 53% 50% 0% 48% 67% 44% 15% 68% 83% 39% 64% 38% 47%
B6. ACTUAL PUBLIC EXPENDITURE BY AGRICULTURAL SUB-SECTOR 0% 23% 0% 20% 75% 18% 0% 50% 74% 21% 7% 36% 27%
B7. ACTUAL PUBLIC EXPENDITURE BY FUNCTION/DEPARMENT 0% 43% 10% 33% 0% 42% 0% 42% 75% 0% 0% 39% 24%
B8. PRIVATE SECTOR EXPENDITURE ON AGRICULTURE 0% 0% 25% 0% 0% 48% 0% 27% 0% 0% 0% 0% 8%
B9. PRIVATE SECTOR EXPENDITURE ON AGRICULTURE BY 0% 0% 20% 0% 0% 0% 0% 0% 0% 10% 0% 0% 2%
SUBSECTOR
B10. INWARD FOREIGN DIRECT INVESTMENT 0% 0% 50% 38% 0% 48% 10% 32% 50% 49% 38% 0% 26%
B11. INWARD FDI ON AGRICULTURE BY SUBSECTOR 0% 0% 80% 0% 0% 0% 0% 0% 0% 5% 0% 0% 7%
B12. NON-GOVERNMENTAL ORGANIZATIONS INVESTMENT 6% 0% 13% 0% 0% 0% 0% 25% 0% 0% 0% 11% 5%
B13. NON-GOVERNMENTAL ORGANIZATIONS INVESTMENT BY 0% 0% 30% 0% 0% 0% 0% 0% 0% 0% 0% 5% 3%
SUBSECTOR
Average 16% 23% 28% 26% 27% 29% 11% 35% 43% 18% 24% 27% 26%
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

9. Extract from country questionnaire
Specify Calendar Year: __________ or Fiscal Year from: month __________ year________ to month __________ year________
Please note: All monetary values should be in the Local Currency Unit (LCU). In case an alternative currency is used, please state
explicitly. Agriculture is defined to include crops, livestock, fisheries (captured and farmed) and forestry.
B1. OVERVIEW OF REVENUES AT NATIONAL LEVEL
B1.1 Internally generated B1.2 Externally generated
B1.1.1 Tax-revenue B1.1.2 Domestic loans B1.2.1 grant B1.2.2 loan (Doações) Usd
Usd Usd Usd
2000 17,43 ND 188,5 30,0
2001 45,6 ND 324,5 ND
2002 162,46 ND 528,5 24,0
2003 288,8 ND 34,9 55,0
2004 496,7 ND 5,54 117,4
2005 95,0 248,1 496.7 32,0
2006 14,0 360,9 3.21 ND
2007 2,1 323,2 260.6 ND
2008 3200,0 1288,5 5223,6 52,0
2009 1900,0 3000,0 4801,8
2010 2290,0 3118,6 4910,4 383,5
Note: Tax revenue includes for example taxes on income and profits, payroll and workforce, domestic goods and services, taxes on
international trade and transactions as well as stamp duties and fees
Note: Specify currency ___Millions USD______________________________________________
in: Thousands (1,000) Millions (1,000,000) Billions (1,000,000,000)
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

10. Spot check report
B1. OVERVIEW OF REVENUES AT NATIONAL LEVEL
B1.1Internallygenerated B1.2Externallygenerated B1.1Internally B1.2Externally
generated generated
B1.1.1Tax- B1.1.2Domestic B1.2.1grant B1.2.2loan B1.1.1 B1.1.2 B1.2.1 B1.2.2
revenue loans (Doações)Usd Tax- Domestic grant loan
revenue loans (Doações)
Usd Usd Usd Usd Usd Usd Usd
2000 17,43 ND 188,5 30,0 2000 17.43 ND 188.5 30 235.93
2001 45,6 ND 324,5 ND 2001 45.6 ND 324.5 ND 370.1
2002 162,46 ND 528,5 24,0 2002 162.46 ND 528.5 24 714.96
2003 288,8 ND 34,9 55,0 2003 288.8 ND 34.9 55 378.7
2004 496,7 ND 5,54 117,4 2004 496.7 ND 5.54 117.4 619.64
2005 95,0 248,1 496.7 32,0 2005 95 248.1 496.7 32 871.8
2006 14,0 360,9 3.21 ND 2006 14 360.9 3.21 ND 378.11
2007 2,1 323,2 260.6 ND 2007 2.1 323.2 260.6 ND 585.9
2008 3200,0 1288,5 5223,6 52,0 2008 3200 1288.5 5223.6 52 9764.1
2009 1900,0 3000,0 4801,8 2009 1900 3000 4801.8 9701.8
2010 2290,0 3118,6 4910,4 383,5 2010 2290 3118.6 4910.4 383.5 10702.5
Taxrevenueincludesforexample taxesonincomeandprofits,payrollandworkforce,domesticgoodsandservices,taxeson internationaltradeandtransactionsaswell asstampdutiesand
Note: fees
Note: Specifycurrency___MillionsUSD______________________________________________
in:Thousands(1,000) Millions(1,000,000) Billions(1,000,000,000)
Issuesthatneedclarification
1.WhatdoesNDmean?
2.Whatdoesablankmean?
3.Arethefiguresinyellowexpected,i.e.thefluctuation?
4.Arethefiguresrealornominal?
5.Ifrealwhichoneisusedasthebaseyear?
6.Pleasespecifysource?
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

11. Database Extract
Question No. / Question 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
B1.a Overview of revenues - Specify Calendar year
B1.b Overview of revenues - Specify Year
B1.c Overview of revenues - Specify Currency USD$ USD$ USD$ USD$ USD$ USD$ USD$ USD$ USD$ USD$ USD$
B1.d Overview of revenues - Specify accounting denomination 100000 100000 100000 100000 100000 100000 100000 100000 100000 100000 100000
(1 000 or 1 000 000 or 1 000 000 000) 0 0 0 0 0 0 0 0 0 0 0
B1.e Overview of revenues - Specify if nominal or real values
B1.f Overview of revenues -If real, which one is used as the
base year?
B1.1.1 Overview of Revenues at National Level – Internally 17.43 45.6 162.46 288.8 496.7 95 14 2.1 3200 1900 2290
generated Tax revenue
B1.1.2 Overview of Revenues at National Level – Internally 248.1 360.9 323.2 1288.5 3000 3118.6
generated Domestic loans
B1.2.1 Overview of Revenues at National Level – Externally 188.5 324.5 528.5 34.9 5.54 496.7 3.21 260.6 5223.6 4801.8 4910.4
generated grants
B1.2.2 Overview of Revenues at National Level – Externally 30 24 55 117.4 32 52 383.5
generated loans
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

12. B1. OVERVIEW OF REVENUES AT NATIONAL LEVEL
6000
5000
4000
USD$ (Millions)
3000
2000
1000
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
B1.1.1 Overview of Revenues at National Level
– Internally generated Tax revenue 17.43 45.6 162.46 288.8 496.7 95 14 2.1 3200 1900 2290
B1.1.2 Overview of Revenues at National Level
– Internally generated Domestic loans 248.1 360.9 323.2 1288.5 3000 3118.6
B1.2.1 Overview of Revenues at National Level
– Externally generated grants 188.5 324.5 528.5 34.9 5.54 496.7 3.21 260.6 5223.6 4801.8 4910.4
B1.2.2 Overview of Revenues at National Level
– Externally generated loans 30 24 55 117.4 32 52 383.5
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

13. The percentage in each column represents available data measured against an
expected 100% response rate for each indicator. This table must be read in
conjunction with indicator bar charts showing gaps in the data
Indicator
Mozambique
South Africa
Zimbabwe
Swaziland
Botswana
Tanzania
Namibia
Average
Lesotho
Zambia
Malawi
Angola
DRC
C1. USE OF IMPROVED VARIATIES AND CHEMICAL (INORGANIC) FERTILIZER 26% 20% 90% 7% 0% 41% 0% 32% 7% 85% 18% 0% 27%
BY CROP
C2. TOTAL AREA UNDER IMPROVED LAND MANAGEMENT 45% 0% 0% 3% 100% 27% 0% 39% 6% 100% 33% 9% 30%
C3. USE OF IMPROVED LIVESTOCK TECHNOLOGY 0% 7% 50% 75% 0% 74% 0% 0% 31% 100% 0% 0% 28%
C4. USE OF AGRICULTURAL INPUTS 5% 12% 86% 6% 20% 21% 3% 29% 23% 49% 24% 20% 25%
C5. HUMAN CAPITAL 25% 53% 31% 68% 25% 11% 2% 18% 54% 50% 0% 20% 30%
Average 20% 18% 51% 32% 29% 35% 1% 24% 24% 77% 15% 10% 28%
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

14. The percentage in each column represents available data measured against an
expected 100% response rate for each indicator. This table must be read in
conjunction with indicator bar charts showing gaps in the data
Mozambique
South Africa
Zimbabwe
Swaziland
Botswana
Tanzania
Namibia
Average
Lesotho
Zambia
Malawi
Angola
DRC
Indicator
D1. LAND AND LABOUR 41% 36% 50% 55% 50% 43% 27% 91% 0% 80% 95% 5% 48%
D2. GDP BY SECTOR 70% 55% 42% 75% 60% 59% 45% 80% 85% 80% 62% 65% 65%
D3. AGRICULTURE GDP BY SUB-SECTOR 50% 48% 36% 59% 63% 52% 45% 61% 72% 75% 50% 0% 51%
D4. OUTPUT/PRODUCTION BY CROP 38% 13% 45% 20% 90% 34% 44% 70% 17% 69% 51% 46% 45%
D5. LIVESTOCK PRODUCTION BY LIVESTOCK TYPE 40% 23% 59% 15% 50% 54% 43% 57% 40% 80% 9% 30% 42%
D6. TOTAL FISHERIES PRODUCTION 20% 0% 40% 4% 100% 37% 16% 64% 0% 0% 47% 22% 29%
D7. TOTAL FORESTRY PRODUCTION 17% 0% 17% 6% 17% 18% 12% 48% 74% 100% 0% 0% 26%
D8. AGRICULTURAL TRADE 35% 42% 13% 45% 75% 66% 58% 75% 63% 0% 75% 50% 50%
D9. AGRICULTURAL TRADE VOLUME BY CROP 8% 39% 78% 62% 23% 38% 0% 59% 19% 0% 77% 12% 35%
D10. MEAT TRADE 17% 6% 77% 3% 0% 23% 17% 75% 41% 0% 92% 19% 31%
D11. FISHERIES TRADE (both aquaculture and captured fish) 2% 55% 32% 5% 50% 11% 35% 18% 13% 0% 75% 5% 25%
Average 31% 29% 44% 32% 52% 40% 31% 63% 38% 44% 58% 23% 40%
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

15. The percentage in each column represents available data measured against an
expected 100% response rate for each indicator. This table must be read in
conjunction with indicator bar charts showing gaps in the data
Indicator
Mozambique
South Africa
Zimbabwe
Swaziland
Botswana
Tanzania
Namibia
Average
Lesotho
Zambia
Malawi
Angola
DRC
E1. MACRO-ECONOMIC INDICATORS 25% 7% 30% 78% 100% 35% 45% 72% 64% 100% 67% 31% 54%
E2. POPULATION STRUCTURE 50% 0% 60% 15% 62% 82% 10% 92% 35% 5% 80% 68% 47%
E3. NUMBER OF PEOPLE LIVING WITH HIV/AIDS 0% 2% 10% 5% 0% 60% 10% 37% 60% 0% 4% 18% 17%
E4. NUMBER OF PEOPLE LIVING BELOW THE NATIONAL POVERTY LINE 0% 2% 0% 3% 33% 2% 9% 9% 36% 0% 5% 0% 8%
E5. NUMBER OF PEOPLE LIVING WITH DIETARY ENERGY CONSUMPTION 0% 1% 0% 2% 0% 33% 0% 0% 36% 0% 0% 0% 6%
BELOW 2100 KCAL PER DAY
E6. NUMBER OF CHILDREN UNDER THE AGE OF 5 WHOSE WEIGHT-FOR- 0% 2% 0% 10% 100% 5% 0% 0% 36% 0% 0% 0% 13%
AGE IS LEASS THAN MINUS TWO STANDARD DEVIATIONS FROM MEDIAN
OF THE WHO REFERENCE POPULATION
E7. NUMBER OF CHILDREN UNDER THE AGE OF 5 WHO ARE STUNTED 0% 1% 0% 4% 100% 0% 0% 8% 36% 0% 5% 0% 13%
Average 11% 2% 14% 17% 56% 31% 11% 31% 44% 15% 23% 17% 23%
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

16. Suggested Data Sources
Section Possible Data Source as per CAADP
Framework
A. CAADP implementation process i. CAADP Focal point
B. Expenditure and investment indicators i. Ministry of Finance
ii. Accountant General’s Office
iii. Ministry of Agriculture
iv. Donor Offices
v. Chamber of Commerce
C. Output indicators (Agricultural technology, diffusion, and human i. Ministry of Agriculture
capital indicators ii. Environmental protection Agencies
iii. National Statistics Office
D. Agricultural sector performance indicators (Agricultural production i. Ministry of Agriculture
and trade indicators) ii. Ministry of Trade
iii. Food Balance Sheets
iv. Export promotions
v. National accounts
E. Macro- and socio-economic indicators (Welfare indicators) i. Ministry of Finance
ii. Ministry of Trade
iii. National accounts
iv. Ministry of Health
F. Agricultural development strategies, policies and / or plan i. Ministry of Agriculture
ii. Ministry of Finance
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)

17. Q&A
Strategic Analysis and Knowledge Support System for Southern Africa (SAKSS-SA)