final presentation - usaid internship
TRANSCRIPT
BRINGING DATA INTO THE DEVELOPMENT CONVERSATIONMARY ZIEMBA, DUKE UNIVERSITY ‘18, B.S. COMPUTER SCIENCE, CERTIFICATE INNOVATION AND ENTREPRENEURSHIP
“Increase the use of scientific research for improved development outcomes.”
–Global Development Lab results framework, science DO
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
MY QUESTION:WHAT DOES DATA SAY ABOUT THE ROLE OF SCIENCE AND RESEARCH IN DEVELOPMENT?
SUMMARY STATISTICS
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):
THE WORLD BANK - WORLD DEVELOPMENT INDICATORS
METRIC
DATE SOURCE2013
AVERAGE GROSS EXPENDITURE ON R&DBY REGION, ALL REPORTING COUNTRIES, % OF GDP
UNESCO
METRIC
DATE SOURCE2013
GERD BREAKDOWN BY CATEGORYSELECT COUNTRIES ACROSS INCOME GROUPS
El Salvador KazakhstanIceland
UNESCO (GERD); GDP/CAPITA (WORLD BANK)
METRIC
DATE SOURCE2000-2012
GROSS EXPENDITURE ON R&D AND GERDRELATIONSHIP 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)
Global CompetitivenessWorld 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
WORLD ECONOMIC FORUM
METRIC
DATE SOURCE2015-2016
GLOBAL COMPETITIVENESS SUMMARYLAC
Latin America/Caribbean Avg.Peru
Upper-Middle Income Avg.United States
WORLD ECONOMIC FORUM
METRIC
DATE SOURCE2015-2016EAST ASIA/PACIFIC
CambodiaVietnam
IndonesiaUnited States
GLOBAL COMPETITIVENESS SUMMARY
WORLD ECONOMIC FORUM
METRIC
DATE SOURCE2015-2016
GLOBAL COMPETITIVENESS SUMMARYMIDDLE EAST & NORTH AFRICA
IsraelMoroccoJordan
United States
WORLD ECONOMIC FORUM
METRIC
DATE SOURCE2015-2016
GLOBAL COMPETITIVENESS SUMMARYEUROPE AND CENTRAL ASIA
FranceArmenia
KazakhstanUnited States
WORLD ECONOMIC FORUM
METRIC
DATE SOURCE2015-2016
GLOBAL COMPETITIVENESS SUMMARYSUB-SAHARAN AFRICA
South AfricaCote d’Ivoire
TanzaniaUnited States
WHAT I LEARNED
UNESCO/WORLD ECONOMIC FORUM
METRIC
DATE SOURCE2015-16
INSTITUTIONAL QUALITYGERD AND UNIVERSITY-INDUSTRY COLLAB. IN R&D
R-squared: 0.99R-squared: 0.72
WORLD ECONOMIC FORUM, GLOBAL COMPETITIVENESS DATASET
METRIC
DATE SOURCE2015-2016
CORRELATIONS, GLOBAL COMPETITIVENESS DATAWHAT IS RELATED TO INSTITUTIONAL QUALITY?
Availability of
Scientists and
engineers
Capacity for
innovation
Company R&D
Spending
Capacity to attract
talent
Capacity to retain
talent
Extent of market
dominance
Govern-ment
procure-ment of advanced 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 0.169Not
signif-icant
Not signif-icant
Not signif-icant
0.152Not
signif-icant
Not signif-icant
0.681
Lower-middle income
0.542 0.678 0.765 0.272 0.296 0.496 0.523Not
signif-icant
0.502 0.443 0.622Not
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
Questions?