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UGANDA BUREAU OF STATISTICS. ASSESSMENT OF NATIONAL AGRICULTURAL STATISTICAL SYSTEMS IN AFRICA by Prof. Ben Kiregyera PARIS21 CONSULTANT. 1. COVERAGE. I.Introduction Review of Current National Agricultural Statistical Systems (NASSs) III.Way Forward - Paradigm shift

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ASSESSMENT OF NATIONAL AGRICULTURAL STATISTICAL SYSTEMS IN AFRICA by Prof. Ben Kiregyera

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Assessment of national agricultural statistical systems in africa by prof ben kiregyera

UGANDA BUREAU OF STATISTICS

ASSESSMENT OF NATIONAL AGRICULTURAL STATISTICAL SYSTEMS IN AFRICA

by

Prof. Ben Kiregyera

PARIS21 CONSULTANT


Assessment of national agricultural statistical systems in africa by prof ben kiregyera

1

COVERAGE

  • I.Introduction

  • Review of Current National

  • Agricultural Statistical Systems (NASSs)

  • III.Way Forward - Paradigm shift

  • IV.Recommendations


Assessment of national agricultural statistical systems in africa by prof ben kiregyera

2

I. INTRODUCTION

  • Millennium Development Goals (MDGs)

    • 8 goals

    • Eradication of extreme poverty and hunger

  • Poverty Reduction Strategy Papers (PRSPs)

    • national planning frameworks and development

      strategies

    • instruments for relations with donors

    • basis for concessional lending/debt relief (HIPC)

  • PRSP and Agriculture Linkage

    • agriculture plays a central role in economy

      (see next slide)

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


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    Contribution of agriculture to national economies

    Country Contribution of agriculture to:

    GDP Exports Employment

    Ethiopia 50 90 80

    Kenya 30 50 75

    Tanzania 49 85 80

    Malawi 37 85 90

    Rwanda 44 - 90

    Uganda 43 90 80

    3


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    4

    II.REVIEW OF NATIONAL AGRICULTURAL STATISTICAL SYSTEMS (NASSs)

    • A:Forty years on, no satisfactory NASSs

      • project and piecemeal ad hoc approach

      • Success of projects = success of NASSs

    • Quotation FAO (1997)

  • B:Audit/scan of NASS

  • Triple dilemma

    • agendas made elsewhere

    • weak capacity to deliver

    • seemingly intractable methodological problems

    • What has gone wrong?


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    4B

    • C:Summary of what has gone wrong

      • NSSs are unstructured with no strategic direction

      • NSSs largely donor funded and driven with limited

      • government commitment

      • uncoordinated and prioritized

      • wide use of “quick fixor ad hoc” approach with

      • long-term planning taking a back seat

      • inadequate data – inaccurate, conflicting,

      • insufficiently processed and analyzed,

      • insufficiently disaggregated and not easily

      • accessible

      • no lasting benefits – capacity building and raising

      • the profile of statistics

      • methodological problems


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    5

    D:Paradox of data gaps

    • Data Demand outstrips Supply

    Demand for good data

    Supply

    of good data

    • Demand versus Resources

    demand

    resources

    Time


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    6

    • Paradox of data gaps

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

      Quotation - Cisse (1990)

    • Critical data gaps

      • profile of rural populations

      • household food security

      • nutrition

      • on-farm stocks

      • disaggregated poverty levels

      • post-harvest losses

      • yields for staples such as cassava and bananas

      • horticultural production

      • environment and forestry

      • gender (especially role of women), etc.


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    7

    E: Lack of coordination – a serious problem

    • horizontal coordination to avoid working at

    • cross-purpose

      • generally poor

      • destructive rivalry between MOA and CSO

  • technical coordination to ensure mutual consistency

  • of data from different sources

    • generally poor

    • leads to conflicting data

  • Quotation – Blackwood (1997)

  • F:Main sources of data

  • Agricultural Reporting Services

    • reports by extension staff

    • administrative registers

  • Generally data suspect


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    8

    • Agricultural censuses

    • Countries participating in World Census Programme

      1930 1950 1960 1970 1980 1990

      1 3 16 22 17 14

    • Few countries been able to repeat the census

    • Long period between censuses

      • lack of census data constrained long-term

        planning and investment decisions

      • unable to build expertise; dependence

        syndrome

  • Based on small samples; unable to provide small

  • area statistics


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    8B


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    • Agricultural sample surveys

      • timeliness

      • less cost

      • increased data quality

      • unable to provide small area statistics

      • lack of expertise and dependence on TA

  • Data collection methodologies

    • guess estimates

    • self-enumeration

    • farmer interviews

    • physical (objective) measurement

    • household budget surveys

    • special problems of data collection

      • cropping systems (mixed cropping,

        continuous planting and harvesting, etc)

      • production of root crops

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

  • 9


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    10

    • Data management

      • data processing

        • computer hardware & software no longer a

          problem

        • problem is with computer personnel

          (liveware)

      • data analysis

      • (see next slide)


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    11

    G:Data cycle

    Planning

    Stage 1

    Stage 2

    Implementation

    Dissemination

    Feedback

    Stage 3

    Reporting

    Processing

    Analysis/Interpretation


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    12

    H:Data versus Information

    End Users

    Intermediate

    User

    (researchers)

    Data Producers

    Raw Data

    (low level information)

    Data

    Analysis

    Information

    Add value to data


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    13

    Policy-related information

    information

    End users

    Policy/

    decision-

    maker

    Policy-related Analysis

    Basic Analysis

    Tables

    Raw Data


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    14

    I:Other issues

    • involvement of of subject-matter specialists and

    • experts (starting in some countries)

    • production of new analytical products e.g. poverty

    • and vulnerability maps using GIS functionality

    • (starting in a few countries)

    • Databases and data warehouses

    • (recognized but not enough done)


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    15

    J:Major problems and constraint

    • limited political commitment

    • organizational problems

    • insufficient coordination/collaboration/networking and

    • information sharing

    • limited coordination

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

    • Human resources

    • shortage of critical skills and expertise

    • Methodological

    • given above

    • Data quality problems

    • inconsistency, incompleteness (data gaps), inaccuracy,

    • lack of timeliness; insufficient small area statistics

    • Data management problems


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    16

    • knowledge management

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

      Information assets:

    • databases

    • documents

    • policies and procedures

    • library services

    • tacit expertise & experience stored in peoples’

      heads

      Experience in countries

    • poor or no documentation of methods/procedures

    • no institutional memory

    • experience in people’s heads

    • datasets and no databases


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    17

    • PARADIGM SHIFT: WINDOW I WINDOW II

    WINDOW I

    APPROACH

    Ad hoc

    Largely donor driven, limited government commitment

    INPUTS

    • data which are inadequate

    • no database

    • yawning gaps

    OUTPUTS


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    18

    WINDOW II

    • Identify Partners

    • Master Plan

    Coordinated System

    • user driven

    • ownership

    • long-term

    • partnerships

    • prioritized

    • Capacity building

    Main Feature

    • government

    • donor

    Inputs

    • adequate data

    • data base

    • sustainable

      system

    Outputs


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    19

    A: Develop an Integrated Framework

    • Process

    Analysis

    Planning

    Implementation

    monitoring

    evaluation

    • establish long-

    • tem objectives

    • generating

    • actionable

    • strategies

    • development of

    • statistical

    • programme

    • identify

      • activities

      • outputs

      • indicators

      • plan

    • budgets

    • external environment

    • users and

    • producers

    • coordination arrangements

    • current and future data needs

    • crate awareness

    • positioning the NSS

    • sticking to priorities and

    • implementation plan

    • track inputs, activities,

    • outputs

    • monitoring schedule

    • evaluation


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    20

    B: Address statistical governance Issues

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

      • What is our mission?

      • How do we perform and can we do better?

      • How do we convince government that statistics

      • useful and adequate resources are needed?

  • Some governance issues:

    • Improving relevance

    • Improving coordination, networking,

    • partnerships

    • Benefiting from technical assistance

    • Knowledge management

    • Improving data quality

    • Improving data analysis, dissemination, access

    • Better data management (Databases)


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    21

    C: Improving relevance

    • Advocacy for statistics

      • raise awareness about and create demand

      • raise profile of statistics

      • resource mobilization

    • create partnerships for statistics

    • stakeholders to take ownership

    • increase relevance and funding for NSS

    • make national statistics demand-driven

    • User-producer Committees

    D: Improving coordination, partnerships &

    collaboration


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    22

    Improving Coordination, partnerships and collaboration

    National Statistical System

    DATA PRODUCERS

    Main data producers

    DATA USERS

    Other data producers

    • government (s)

    • public/private sector

    • NGOs

    • research/training orgs.

    • donors/international orgs.

    • press

    • wider public

    NSO

    Research/Training Organs

    Partnerships


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    23

    E: Improve benefits from technical assistance

    Follow UN guidelines

    • exchange expertise

    • development of skills & expertise

    • demand driven

    • not distort national priorities

    • not undermine national institutions and

      authority

    • F: Improve knowledge management

      Especially

      • documentation of methodologies and

        procedures

      • develop writing and reporting skills


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    25

    G: Improving data quality

    • Consistency- improved coordination

  • - system-wide adoption/standardization of

  • concepts, definitions, classifications

    • Completeness- Strategic Plan for the Statistical Institute

      - comprehensive programme (Master Plan)

    • Accuracy- use of “best methods”

      • - human resources/capacity development

  • - proper handling of data after collection

  • - need for adaptation/research

    • Timeliness- release calendar and sticking to it

    • Small area statistics

      - increase sample size

      - combine data from surveys and censuses


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    26

    H: Improve data management

    Enable

    • networking

    • sharing of information

    • data archiving

    • creation of user-friendly and accessible

      databases

    • creation of data warehouses/data mining


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    27

    I: Others

    • Role of NSO

      • set standards, promote “best practices”

      • need realignment of Statistics Act

  • Role of Technical Assistance

    • need f to follow UN Guidelines

    • many countries not following guidelines

    • Capacity is not built as it should

  • Opportunities for developing NASSs

    • great demand for statistics to track progress

    • increased international partnership

      • Quotation – Clare Short

      • PARIS21

    • advances in information technology (IT)


  • Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    • IV:RECOMMENDATIONS

      International Community

    • Multi-country methodological research project

    • World Training and research Centre for Food and

      Agricultural Statistics

    • Statistical advocacy

    • Technical cooperation

      Countries

    • Role of National Statistical Office

    • Development and implementation of Integrated

      Framework

    • Staying ahead of demand

    • Role of technical assistance

    • Improve knowledge management

    • improve statistical products and services

    28


    Assessment of national agricultural statistical systems in africa by prof ben kiregyera

    29

    Thank You

    END


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