ASSESSMENT OF NATIONAL AGRICULTURAL ASSESSMENT OF NATIONAL AGRICULTURAL

STATISTICAL SYSTEMSSTATISTICAL SYSTEMS IN AFRICA IN AFRICA

byby

Prof. Ben KiregyeraProf. Ben KiregyeraPARIS21 CONSULTANTPARIS21 CONSULTANT

UGANDA BUREAU OF STATISTICSUGANDA BUREAU OF STATISTICS

COVERAGECOVERAGECOVERAGECOVERAGE 1

I.I. IntroductionIntroduction

II.II. Review of Current National Review of Current National

Agricultural Statistical Systems (NASSs)Agricultural Statistical Systems (NASSs)

III.III. Way Forward - Paradigm shiftWay Forward - Paradigm shift

IV.IV. RecommendationsRecommendations

• Millennium Development Goals (MDGs)Millennium Development Goals (MDGs) 8 goals 8 goals Eradication of extreme poverty and hungerEradication of extreme poverty and hunger

• Poverty Reduction Strategy Papers (PRSPs) Poverty Reduction Strategy Papers (PRSPs) national planning frameworks and developmentnational planning frameworks and development strategiesstrategies instruments for relations with donorsinstruments for relations with donors basis for concessional lending/debt relief (HIPC)basis for concessional lending/debt relief (HIPC)

• PRSP and Agriculture LinkagePRSP and Agriculture Linkage agriculture plays a central role in economy agriculture plays a central role in economy

((see next slidesee next slide))

agric. sector central to improved economic agric. sector central to improved economic performance, increased incomes, raising standards of performance, increased incomes, raising standards of living and poverty reduction.living and poverty reduction.

I. INTRODUCTIONI. INTRODUCTIONI. INTRODUCTIONI. INTRODUCTION2

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Contribution of agriculture to national economiesContribution of agriculture to national economies

Country Contribution of agriculture to:Country Contribution of agriculture to:

GDP ExportsGDP Exports Employment Employment

EthiopiaEthiopia 50 90 80 50 90 80

Kenya 30 50 75Kenya 30 50 75

Tanzania 49 85 80Tanzania 49 85 80

Malawi 37 85 90Malawi 37 85 90

Rwanda 44 - 90Rwanda 44 - 90

Uganda 43 90 80Uganda 43 90 80

II.II. REVIEW OF NATIONAL AGRICULTURAL REVIEW OF NATIONAL AGRICULTURAL STATISTICAL SYSTEMS (NASSs)STATISTICAL SYSTEMS (NASSs)

II.II. REVIEW OF NATIONAL AGRICULTURAL REVIEW OF NATIONAL AGRICULTURAL STATISTICAL SYSTEMS (NASSs)STATISTICAL SYSTEMS (NASSs)

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A:A: Forty years on, no satisfactory NASSsForty years on, no satisfactory NASSs

o project and piecemeal ad hoc approachproject and piecemeal ad hoc approach

Success of projects = success of NASSsSuccess of projects = success of NASSs

Quotation FAO (1997)Quotation FAO (1997)

B:B: Audit/scan of NASSAudit/scan of NASS

Triple dilemmaTriple dilemma• agendas made elsewhere agendas made elsewhere • weak capacity to deliverweak capacity to deliver

• seemingly intractable methodological problemsseemingly intractable methodological problems

What has gone wrong?What has gone wrong?

C:C: Summary of what has gone wrongSummary of what has gone wrong

• NSSs are unstructured with no strategic directionNSSs are unstructured with no strategic direction

• NSSs largely donor funded and driven with limited NSSs largely donor funded and driven with limited government commitmentgovernment commitment

• uncoordinated and prioritizeduncoordinated and prioritized

• wide use of “wide use of “quick fixquick fix or ad hocor ad hoc” approach with ” approach with long-term planning taking a back seatlong-term planning taking a back seat

• inadequate data – inaccurate, conflicting, inadequate data – inaccurate, conflicting,

insufficiently processed and analyzed, insufficiently processed and analyzed, insufficiently disaggregated and not easily insufficiently disaggregated and not easily accessibleaccessible• no lasting benefits – capacity building and raisingno lasting benefits – capacity building and raising the profile of statisticsthe profile of statistics• methodological problemsmethodological problems

4B

D:D: Paradox of data gapsParadox of data gaps

SupplySupplyof good of good

datadata

Demand for Demand for good datagood data

Data Demand outstrips SupplyData Demand outstrips Supply

Demand versus ResourcesDemand versus Resources

demanddemand

resourcesresources

TimeTime

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Paradox of data gapsParadox of data gaps

Yawning gaps on some indicators and a plethora of data Yawning gaps on some indicators and a plethora of data on other indicators which are not used.on other indicators which are not used.

Quotation - Cisse (1990)Quotation - Cisse (1990) Critical data gapsCritical data gaps

o profile of rural populations profile of rural populations o household food security household food security o nutrition nutrition o on-farm stocks on-farm stocks o disaggregated poverty levels disaggregated poverty levels o post-harvest losses post-harvest losses o yields for staples such as cassava and bananas yields for staples such as cassava and bananas o horticultural production horticultural production o environment and forestry environment and forestry o gender (especially role of women), etc.gender (especially role of women), etc.

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E: Lack of coordination – a serious problemE: Lack of coordination – a serious problem

• horizontal coordination to avoid working at horizontal coordination to avoid working at cross-purpose cross-purpose

generally poorgenerally poor destructive rivalry between MOA and CSO destructive rivalry between MOA and CSO

• technical coordination to ensure mutual consistencytechnical coordination to ensure mutual consistency of data from different sources of data from different sources

generally poorgenerally poor leads to conflicting dataleads to conflicting data

Quotation – Blackwood (1997)Quotation – Blackwood (1997)

F:F: Main sources of dataMain sources of data

Agricultural Reporting ServicesAgricultural Reporting Services• reports by extension staffreports by extension staff• administrative registersadministrative registers Generally data suspectGenerally data suspect

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Agricultural censusesAgricultural censuses

• Countries participating in World Census ProgrammeCountries participating in World Census Programme

1930 1950 1960 1970 1980 19901930 1950 1960 1970 1980 1990

1 3 16 22 17 141 3 16 22 17 14

• Few countries been able to repeat the censusFew countries been able to repeat the census

• Long period between censuses Long period between censuses

lack of census data constrained long-term lack of census data constrained long-term

planning and investment decisionsplanning and investment decisions unable to build expertise; dependence unable to build expertise; dependence syndromesyndrome

• Based on small samples; unable to provide small Based on small samples; unable to provide small

area statisticsarea statistics

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8B

WCA Programme Country

1960 1970 1980 1990 2000

Ethiopia - - - - 2001/2

Malawi - - - 1992/3 -

Mozambique 1962/70 - - - 2000/2

Tanzania - 1972 - 1993/5 -

Uganda 1963/5 - - 1990/1 -

AAgricultural sample surveysgricultural sample surveys• timelinesstimeliness• less costless cost• increased data qualityincreased data quality• unable to provide small area statisticsunable to provide small area statistics• lack of expertise and dependence on TAlack of expertise and dependence on TA

Data collection methodologiesData collection methodologies• guess estimatesguess estimates• self-enumerationself-enumeration• farmer interviewsfarmer interviews• physical (objective) measurement physical (objective) measurement • household budget surveyshousehold budget surveys• special problems of data collectionspecial problems of data collection

cropping systems (mixed cropping, cropping systems (mixed cropping, continuous planting and harvesting, etc)continuous planting and harvesting, etc) production of root crops production of root crops

In production environment that occurs in family In production environment that occurs in family smallholder sector in Africa, neither objective nor smallholder sector in Africa, neither objective nor subjective methods have proved reliablesubjective methods have proved reliable

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Data managementData management

• data processing data processing

computer hardware & software no computer hardware & software no longer a longer a problem problem problem is with computer personnel problem is with computer personnel ((livewareliveware) )

• data analysisdata analysis

((see next slidesee next slide))

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PlanningPlanning

Implementation

Implementation

ProcessingProcessing

AnalysisAnalysis/Interpretation/Interpretation

ReportingReporting

Dissemination

Dissemination

Feedbac

k

Feedbac

k

11G:G: Data cycleData cycle

Data Data ProducersProducers

End End UsersUsers

Raw DataRaw Data(low level (low level

information)information)

DataDataAnalysisAnalysis

InformationInformation

IntermediateIntermediateUserUser

(researchers)(researchers)

Add value Add value to datato data

12H:H: Data versus InformationData versus Information

Raw DataRaw Data

TablesTables

Basic AnalysisBasic Analysis

Policy-related AnalysisPolicy-related Analysis End usersEnd users

Policy/Policy/decision-decision-

makermaker

information

13Policy-related informationPolicy-related information

• involvement of of subject-matter specialists and involvement of of subject-matter specialists and

experts (experts (starting in some countriesstarting in some countries))• production of new analytical products e.g. povertyproduction of new analytical products e.g. poverty

and vulnerability maps using GIS functionalityand vulnerability maps using GIS functionality

((starting in a few countriesstarting in a few countries))

• Databases and data warehousesDatabases and data warehouses

((recognized but not enough donerecognized but not enough done))

I:I: Other issuesOther issues

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• limited political commitment limited political commitment

• organizational problemsorganizational problems

insufficient coordination/collaboration/networking insufficient coordination/collaboration/networking andand information sharinginformation sharing • limited coordinationlimited coordination

user/producer, producer-produce, producer/research/ user/producer, producer-produce, producer/research/ training institutionstraining institutions

• Human resourcesHuman resources shortage of critical skills and expertiseshortage of critical skills and expertise• MethodologicalMethodological

given abovegiven above• Data quality problemsData quality problems

inconsistency, incompleteness (data gaps), inconsistency, incompleteness (data gaps), inaccuracy,inaccuracy, lack of timeliness; insufficient small area statisticslack of timeliness; insufficient small area statistics• Data management problemsData management problems

15J:J: Major problems and constraintMajor problems and constraint

• knowledge managementknowledge management

A way of promoting integrated approach to identifying, A way of promoting integrated approach to identifying, capturing, retrieving, sharing and evaluating capturing, retrieving, sharing and evaluating organization’s information assets.organization’s information assets.

Information assetsInformation assets:: databasesdatabases documentsdocuments policies and procedurespolicies and procedures library serviceslibrary services tacit expertise & experience stored in peoples’ tacit expertise & experience stored in peoples’ headsheads

Experience in countriesExperience in countries poor or no documentation of methods/procedurespoor or no documentation of methods/procedures no institutional memoryno institutional memory experience in people’s headsexperience in people’s heads datasets and no databasesdatasets and no databases

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III.III. PARADIGM SHIFT: WINDOW I WINDOW IIPARADIGM SHIFT: WINDOW I WINDOW II

APPROACH Ad hocAd hoc

INPUTS

OUTPUTS

Largely donor driven, limited Largely donor driven, limited government commitmentgovernment commitment

• data which are inadequatedata which are inadequate• no databaseno database• yawning gapsyawning gaps

WINDOW IWINDOW I

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WINDOW II

Coordinated System• Identify Partners• Master Plan

Main Feature

user drivenownershiplong-termpartnershipsprioritized Capacity building

Inputs

OutputsOutputs

governmentdonor

adequate data data base sustainable system

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ProcessProcess

AnalysisAnalysis PlanningPlanning Implementation Implementation monitoring monitoring

evaluationevaluation

• external external environmentenvironment

• users and users and

producersproducers

• coordination coordination arrangementsarrangements

• current and current and future data future data needsneeds

• establish long-establish long- tem objectivestem objectives• generating generating actionable actionable strategiesstrategies• development of development of statistical statistical programmeprogramme

• identify identify activitiesactivities outputsoutputs indicatorsindicators planplan

• budgetsbudgets

• crate awarenesscrate awareness

• positioning the NSSpositioning the NSS

• sticking to priorities and sticking to priorities and implementation planimplementation plan

• track inputs, activities, track inputs, activities, outputsoutputs

• monitoring schedulemonitoring schedule

• evaluationevaluation

A: Develop an Integrated FrameworkA: Develop an Integrated Framework 19

All National Statistical Systems grappling with All National Statistical Systems grappling with governance-related questions:governance-related questions:

• What is our mission?What is our mission?• How do we perform and can we do better?How do we perform and can we do better?• How do we convince government that statistics How do we convince government that statistics useful and adequate resources are needed?useful and adequate resources are needed?

Some governance issues:Some governance issues:• Improving relevanceImproving relevance• Improving coordination, networking, Improving coordination, networking, partnershipspartnerships• Benefiting from technical assistanceBenefiting from technical assistance• Knowledge managementKnowledge management• Improving data qualityImproving data quality

• Improving data analysis, dissemination, accessImproving data analysis, dissemination, access• Better data management (Databases)Better data management (Databases)

B: Address statistical governance IssuesB: Address statistical governance Issues 20

Advocacy for statisticsAdvocacy for statistics raise awareness about and create demandraise awareness about and create demand raise profile of statisticsraise profile of statistics resource mobilizationresource mobilization

create partnerships for statisticscreate partnerships for statistics

stakeholders to take ownershipstakeholders to take ownership

increase relevance and funding for NSSincrease relevance and funding for NSS

make national statistics demand-drivenmake national statistics demand-driven

User-producer CommitteesUser-producer Committees

C: Improving relevanceC: Improving relevance

D: Improving coordination, partnerships & D: Improving coordination, partnerships & collaborationcollaboration

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NSONSO

Other data Other data producersproducers

Research/Training OrgansResearch/Training Organs

Main data Main data producerproducerss

• government (s)• public/private sector• NGOs• research/training orgs.• donors/international orgs.• press• wider public

PartnershipsPartnerships

Improving Coordination, partnerships and collaborationImproving Coordination, partnerships and collaboration

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E: Improve benefits from technical assistanceE: Improve benefits from technical assistance

Follow UN guidelinesFollow UN guidelines exchange expertiseexchange expertise development of skills & expertisedevelopment of skills & expertise demand drivendemand driven not distort national prioritiesnot distort national priorities not undermine national institutions and not undermine national institutions and authorityauthority

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F: Improve knowledge managementF: Improve knowledge management

Especially Especially

documentation of methodologies and documentation of methodologies and proceduresprocedures develop writing and reporting skillsdevelop writing and reporting skills

ConsistencyConsistency - - improved coordinationimproved coordination - system-wide adoption/standardization of - system-wide adoption/standardization of concepts, definitions, classificationsconcepts, definitions, classifications

CompletenessCompleteness - - Strategic Plan for the Statistical InstituteStrategic Plan for the Statistical Institute - comprehensive programme (Master Plan)- comprehensive programme (Master Plan) AAccuracyccuracy - - use of “best methods” use of “best methods”

- human resources/capacity - human resources/capacity development development

- proper handling of data after collection- proper handling of data after collection - need for adaptation/research- need for adaptation/research

TimelinessTimeliness - - release calendar and sticking to itrelease calendar and sticking to it

Small area statisticsSmall area statistics

- - increase sample sizeincrease sample size - combine data from surveys and censuses- combine data from surveys and censuses

G: Improving data qualityG: Improving data quality 25

Enable Enable

networkingnetworking

sharing of informationsharing of information

data archivingdata archiving

creation of user-friendly and accessible creation of user-friendly and accessible

databasesdatabases creation of data warehouses/data miningcreation of data warehouses/data mining

H: Improve data managementH: Improve data management 26

Role of NSORole of NSO

• set standards, promote “best practices”set standards, promote “best practices”• need realignment of Statistics Actneed realignment of Statistics Act

Role of Technical AssistanceRole of Technical Assistance• need f to follow UN Guidelinesneed f to follow UN Guidelines• many countries not following guidelinesmany countries not following guidelines• Capacity is not built as it shouldCapacity is not built as it should

Opportunities for developing NASSsOpportunities for developing NASSs• great demand for statistics to track progressgreat demand for statistics to track progress• increased international partnershipincreased international partnership

Quotation – Clare ShortQuotation – Clare Short PARIS21PARIS21

• advances in information technology (IT)advances in information technology (IT)

I: OthersI: Others 27

IV:IV: RECOMMENDATIONSRECOMMENDATIONS

International CommunityInternational Community Multi-country methodological research project Multi-country methodological research project World Training and research Centre for Food and World Training and research Centre for Food and

Agricultural StatisticsAgricultural Statistics Statistical advocacyStatistical advocacy Technical cooperationTechnical cooperation

CountriesCountries Role of National Statistical OfficeRole of National Statistical Office Development and implementation of IntegratedDevelopment and implementation of Integrated FrameworkFramework Staying ahead of demandStaying ahead of demand Role of technical assistanceRole of technical assistance Improve knowledge managementImprove knowledge management improve statistical products and servicesimprove statistical products and services

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Thank YouThank You

ENDEND

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