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Final presentation - USAID Internship
1. BRINGING DATA INTO THE
DEVELOPMENT CONVERSATION
MARY ZIEMBA, DUKE UNIVERSITY ‘18, B.S. COMPUTER
SCIENCE, CERTIFICATE INNOVATION AND ENTREPRENEURSHIP
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
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
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
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
