Agency Date Project Country Project description Project Objective Major findings Data Methodology
IADB 2005 PROJoven Peru The overall objective of There are positive and Project dataset covering Propensity score
(Youth the program was to help statistically significant both beneficiaries and matching using a
vocational economically effects in terms of paid control. The selection of difference model, so
training) disadvantaged youths, jobs and formal the control group is also controls for time
of 16-24 years old, to employment based on the following invariant unobservables.
enter into the formal probabilities, as well as variables: age, sex,
labor market by in terms of monthly education, poverty level
providing them with earnings. We also find and geographic
training and an that female youngsters residence.
opportunity to acquire and 16-20 year olds
work experience, which seem to benefit more
is based on the needs from the program. In
of the private sector. general, they
experienced higher
PROJoven impacts on
paid job probabilities,
formal jobs probabilities
and monthly earnings
than their male and 21-
25 year olds
counterparts.
IADB 2006 IDB's Science Chile, A cross-country Regain competitiveness Findings on 1. crowding 1. Project-level data A variety of methods
and Columbia, evaluation of the in the new global and out 2. innovative (grouped by country) were used in the
Technology Uruguay, impacts of two science open economic outputs 3. firm evaluation. 1. Single
Programs: An Brazil, and technology environment. performance 4. difference with
Evlauation of Argentina investment instruments: scientific production propensity score
the Technology and Technology varied by matching 2. Doube
Development Panama Development Funds (to project/country and difference with and
Funds and spur productive controls used in without propensity score
Competitive innovation) and regressions. At the matching and 3. Panel
Research Competitive Research program level the data fixed effect IV
Grants Grants (funding basic evaluation found no estimation (beneficiaries
R&D). evidence of crowding and non-beneficiaries).
out. The results for
innovations were not
significant (no effect).
Mixed results (by
project/coutnry) for
productivity,
employment and sales;
number of publications
and citations; change in
publications and
citations.
Agency Date Project Country Project description Project Objective Major findings Data Methodology
IADB 2006 FONTAR Argentina Financial support for To increase efficiency, FONTAR program Regression with
(Technical scientific and productivity and increases private R&D controls, double-
Upgrading technological R&D. competitiveness expenditures difference and
Program) and through technological propensity score
FONCYT upgrading and support matching.
(Technical for innovation
Modernization processes, especially
II Program) for SMEs.
IADB 2006 PNDCyT Columbia Financial support for To strengthen Significant increases in Administrative data on Regression with
financing for science and technology Colombia's capacity to the number and quality PNDCyT program and controls, single-
basic and sector. conduct scientific of publications for secondary bibliometric difference and
applied research through financed researchers. data sources. Reistry of propensity score
research. ifrastructure and training Financed researchers researchers used to matching.
to facilitate sustainable published 1.18 times form comparison group.
development. the number of
publicaiton of non-
financed researchers.
Higher quality of
research, researcher
age and institutional
rank were also
positively related to
number of pulications.
IADB 2006 FONTEC Chile R&D support through To increase the Postive and statistically Survey data on 219 Double-difference with
Program public technology funds. competitiveness of significant effect of beneficiary firms and propensity score
(financing Chilean economy FONTEC on the level of 220 non-beneficiary matching. Regression
innovation in through tehcnological investment in R&D firms representing the discontinuity.
the private innovation in strategic (pesos) but no effect on sectoral and
sector) and productive sectors, in R&D intensity (R&D as geographical distribution
FONDECYT particular SMEs. a percent of sales). No of FONECT recipient
(financing statistically significant firms. FONDECYT
basic and effects were found specific database on all
applied relating FONDECYT to projects financed
research increases in either the between 1998 and 2004
activities). number or quality of including bibliometric
publications. information attributable
to the program. A
control group was
chosen from among the
group of rejected
proposals.