Trends in Public and Private Agricultural R

1
Trends in Public and Private Agricultural RD
Investments

• Nienke Beintema
• Agricultural Science Technology Indicators
  (ASTI) initiative

Presentation at Rutgers UniversityNew Brunswick,
5 February 2009
2
Outline of presentation

• Background of the Agricultural ST Indicators
  (ASTI) initiative
• Revised investment trends in global public
  agricultural RD
• Some regional perspectives on Africa, Asia, and
  Latin America

3
Background of theASTI initiative
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Relevance of agricultural ST indicators

• Important to measure and monitor inputs, outputs,
  and performance of agricultural ST systems
• Important tool to assess the contribution of
  agricultural ST to agricultural and overall
  economic growth
• Assist RD managers and policymakers in policy
  formulation and decision-making
• Provide information on the state of agricultural
  ST at national, regional, and international
  levels

5
Relevance of agricultural ST indicators (contd)

• Development of institutional capacity and methods
  for collecting national ST indicators by
  industrialized countries (OECD, UNESCO)
• National ST indicators are still scarce in
  developing countries (except for some Asian and
  Latin American countries, South Africa)
• NEPAD recently initiated the African Science,
  Technology, and Innovation Indicators Initiative
  (ASTII)
• Difficult to extract full set of agricultural ST
  indicators from national ST indicators

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Agricultural ST Indicators (ASTI) Initiative

• Objective To provide internationally comparable
  information in the investment, capacity, and
  institutional environment surrounding
  agricultural RD, thereby informing and improving
  research policy decisions around the world
• Collaborative network with large number of
  national, regional and international partners
  led by IFPRI
• Collects national-level investment and
  capacitydata on agricultural RD
  (input/resources data)
• Focused on developing countries
• Through institutional survey rounds
• Linked with OECD ST indicators for developed
  countries

7
Agricultural ST Indicators (ASTI) Initiative
(contd)

• Aim is to provide
• Trends (to measure progress/digress over
  time)
• Comparative information (superior/inferior
  relative to others) across countries and
  regions
• Dataset includes country and regional-level
  trends on researchers (by degree gender), other
  staff, spending, sources of funding, research
  focus
• Outputs country briefs, regional and global
  reports, datasets, other publications are
  available on the ASTI website (www.asti.cgiar.org)
  

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New directions of the ASTI initiative

• Traditional ASTI dataset for Sub-Saharan Africa
  currently being updated
• Datasets for South Asia, and (if funded) Middle
  East and North Africa updated within the next 2
  years
• In-depth quantitative information on agricultural
  research capacity in Africa
• Expansion of indicator set to include output,
  process, and other indicators
• Improved data dissemination and usage
• New ASTI website with data mapping tool
• Increased focus on analytical activities

9
Revised Global Trends in Agricultural RD
Investments
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Measuring expenditures across countries

• Comparing economic data across countries is
  highly complex due to differences in price levels
• Largest components of national agricultural RD
  spending are staff salaries and local operating
  costs
• Market exchange rates measure financial flows
  while purchasing power parity (PPP) indices
  measure the relative purchasing power of
  currencies across countries
• World Bank revision of PPP indexes led to major
  adjustments in economic comparisons across
  countries/ regions (WB, IMF, ASTI)

11
Revision in 2000 global pictureWhy?

• World Bank revisions in PPP indexes for the year
  2005, which affected actual and relative levels
  of investments
• World Bank revised its GDP deflators for a number
  of countries, affecting growth estimates for
  certain regions
• ASTI reclassification of its global dataset into
  high-, middle-, and low-income country categories
  (defining developing countries as low middle
  income countries)
• Release of new quantitative information by ASTI
  for a number of Asian and Latin American
  countries, which included an increase in
  institutional data coverage for a few large
  countries (such as Iran and Mexico)

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Revision in 2000 global pictureMain
implications?

• Global public agricultural RD investment levels
  ASTIs estimates of global public agricultural
  RD investments have been revised downward by
  one-tenth.
• As a result high-income countries as a group
  still invest more in public agricultural RD than
  do developing countries as a group

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Public agricultural RD investmenttrends
globally, 1981 and 2000
developing low- and middle income countries
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Spatial concentration of publicagricultural RD
spending, 2000
Agr. RD
Agr.
Agr.
Spending




Population
Land

GDP
percentage


(
)
Top 5
23


48



52


47

33
52
Top 10


62



56


Bottom 80


6




11
14
6

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Public and private sector investmentin
agricultural RD
developing low- and middle income countries
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Public agricultural RD investment trendsin
developing countries, 1981-2006
developing low- and middle income countries
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Global annual growth rates in public agricultural
RD investment, 1976-2000
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Intensity of public agricultural RDinvestments,
1981-2000
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Composition of funding sources, early 2000s (53
developing countries)
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Institutional classification of public
agricultural RD, Latin America and Africa
21
Diversity across countries within regions
Example Annual growth rates in Latin American
spending, 1996-2006
22
Diversity across countries within regions
(contd)
Example Latin American spending as a of
agricultural GDP, 2006
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Concluding remarks

• Growth in public agricultural RD has declined in
  most regions (except in some Asian countries)
• Growing global divide with the poorest countries
  falling behind
• The government is still the main provider and
  funder of agricultural RD
• Importance of reliable / up to date quantitative
  information to ensure rigorous analysis and
  improved decision-making and policy formulation
• RD systems, however, are becoming more complex
  and so the underlying datasets