This document presents data and statistics on research and development (R&D) expenditures and their relationship to development outcomes. It shows that average gross expenditures on R&D as a percentage of GDP vary by region, with Latin America and the Caribbean spending less than Europe and Central Asia or East Asia and Pacific. Data at the country level indicates varying levels of investment in basic research, applied research, and experimental development. Charts show Brazil's increasing R&D expenditures have outpaced GDP growth. Global competitiveness rankings from the World Economic Forum also vary significantly between countries and regions. Analysis of the data found institutional quality to be highly correlated with R&D measures like university-industry collaboration.

1. BRINGING DATA INTO THE
DEVELOPMENT CONVERSATION
MARY ZIEMBA, DUKE UNIVERSITY, B.S. COMPUTER
SCIENCE ‘18

2. “Increase the use of scientific research for
improved development outcomes.”
–Global Development Lab results framework, science DO

3. Why I’m here
Collect data about science’s role in development
to inform development decisions
Make this data available to CDR, the Lab,
missions, others in USAID who would find it useful

4. MY QUESTION:
WHAT DOES DATA SAY
ABOUT THE ROLE OF
SCIENCE AND RESEARCH IN
DEVELOPMENT?

5. SUMMARY STATISTICS

6. Expenditures for research and development are
current and capital expenditures (both public and
private) on creative work undertaken
systematically to increase knowledge, including
knowledge of humanity, culture, and society, and
the use of knowledge for new applications. R&D
covers basic research, applied research, and
experimental development.”
—World Bank GERD definition
current and capital expenditures (both public and
private) .
basic research, applied research, and
experimental development.”
Gross expenditure of research and development
(GERD):

7. THE WORLD BANK - WORLD DEVELOPMENT INDICATORS
METRIC
DATE SOURCE
2013
AVERAGE GROSS EXPENDITURE ON R&D
BY REGION, ALL REPORTING COUNTRIES, % OF GDP

8. UNESCO
METRIC
DATE SOURCE
2013
GERD BREAKDOWN BY CATEGORY
SELECT COUNTRIES ACROSS INCOME GROUPS
El Salvador KazakhstanIceland

9. UNESCO (GERD); GDP/CAPITA (WORLD BANK)
METRIC
DATE SOURCE
2000-2012
GROSS EXPENDITURE ON R&D AND GERD
RELATIONSHIP OVER TIME, BRAZIL
Thicker line = R&D expenditure
Thinner line = GDP/capita
Latin America/Caribbean (excluding high-
income)
Europe and Central Asia (excluding high-
income)
East Asia and Pacific (excluding high-income)
Nepal (South Asia)
Ethiopia (South Africa)
Egypt (North Africa)

10. Global Competitiveness
World Economic Forum:
“The set of institutions,
policies, and factors that
determine the level of
productivity of an economy,
which in turn sets the level
of prosperity that the
country can earn.”
Survey- and data-driven
numbers
1—7 scale

11. WORLD ECONOMIC FORUM
METRIC
DATE SOURCE
2015-2016
GLOBAL COMPETITIVENESS SUMMARY
LAC
Latin America/Caribbean Avg.
Peru
Upper-Middle Income Avg.
United States

12. WORLD ECONOMIC FORUM
METRIC
DATE SOURCE
2015-2016
EAST ASIA/PACIFIC
Cambodia
Vietnam
Indonesia
United States
GLOBAL COMPETITIVENESS SUMMARY

13. WORLD ECONOMIC FORUM
METRIC
DATE SOURCE
2015-2016
GLOBAL COMPETITIVENESS SUMMARY
MIDDLE EAST & NORTH AFRICA
Israel
Morocco
Jordan
United States

14. WORLD ECONOMIC FORUM
METRIC
DATE SOURCE
2015-2016
GLOBAL COMPETITIVENESS SUMMARY
EUROPE AND CENTRAL ASIA
France
Armenia
Kazakhstan
United States

15. WORLD ECONOMIC FORUM
METRIC
DATE SOURCE
2015-2016
GLOBAL COMPETITIVENESS SUMMARY
SUB-SAHARAN AFRICA
South Africa
Cote d’Ivoire
Tanzania
United States

16. WHAT I LEARNED

17. UNESCO/WORLD ECONOMIC FORUM
METRIC
DATE SOURCE
2015-16
INSTITUTIONAL QUALITY
GERD AND UNIVERSITY-INDUSTRY COLLAB. IN R&D
R-squared: 0.99
R-squared: 0.72

18. WORLD ECONOMIC FORUM, GLOBAL COMPETITIVENESS
DATASET
METRIC
DATE SOURCE
2015-2016
CORRELATIONS, GLOBAL COMPETITIVENESS DATA
WHAT IS RELATED TO INSTITUTIONAL QUALITY?
Availabili
ty of
Scientist
s and
engineer
s
Capacity
for
innovatio
n
Compan
y R&D
Spendin
g
Capacity
to attract
talent
Capacity
to retain
talent
Extent of
market
dominan
ce
Govern-
ment
procure-
ment of
advance
d tech.
Primary
educa-
tion
enrolme
nt
Quality
of Math
and
science
educ.
Quality
of
primary
educa-
tion
Quality
of edu-
cation
system
Second-
ary edu-
cation
enrol-
ment
Tertiary
educa-
tion
enrol-
ment
Univ.-
Industry
Collab.
in R&D
High-
income
0.492 0.823 0.807 0.282 0.385 0.4 0.26 0.117 0.399 0.474 0.522 0.19 0.09 0.86
Upper-
middle
income
0.405 0.518 0.611 0.178 0.194 0.526 0.169
Not
signif-
icant
Not
signif-
icant
Not
signif-
icant
0.152
Not
signif-
icant
Not
signif-
icant
0.681
Lower-
middle
income
0.542 0.678 0.765 0.272 0.296 0.496 0.523
Not
signif-
icant
0.502 0.443 0.622
Not
signif-
icant
Not
signif-
icant
0.511
Low
income
0.642 0.479 0.607 0.275 0.41 0.407 0.363
Not
signif-
icant
Not
signif-
icant
Not
signif-
icant
Not
signif-
icant
Not
signif-
icant
Not
signif-
icant
0.651
Darker green = more
closely correlated

19. Questions?