Abstract
Evaluation has become a regular practice in the management of science, technology and innovation (ST&I) programs. Several methods have been developed to identify the results and impacts of programs of this kind. Most evaluations that adopt such an approach conclude that the interventions concerned, in this case ST&I programs, had a positive impact compared with the baseline, but do not control for any effects that might have improved the indicators even in the absence of intervention, such as improvements in the socio-economic context. The quasi-experimental approach therefore arises as an appropriate way to identify the real contributions of a given intervention. This paper describes and discusses the utilization of propensity score (PS) in quasi-experiments as a methodology to evaluate the impact on scientific production of research programs, presenting a case study of the BIOTA Program run by FAPESP, the State of São Paulo Research Foundation (Brazil). Fundamentals of quasi-experiments and causal inference are presented, stressing the need to control for biases due to lack of randomization, also a brief introduction to the PS estimation and weighting technique used to correct for observed bias. The application of the PS methodology is compared to the traditional multivariate analysis usually employed.
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Note that by expressing potential outcomes as time differences in the number of publications we are able to control for unobserved individual heterogeneities that are fixed over time and that could be conditionally correlated with the treatment status.
Assumption (iii) is known as Stable Unit-Treatment Value Assumption (SUTVA). See, for example, Rosenbaum and Rubin (1983).
These categories differ basically in terms of the amount of funding awarded (Thematic Projects typically receive more, as well as involving more institutions and participants), duration (2 years on average for projects with Regular Awards, 4 years for Thematic Projects and two to 4 years for Young Investigators projects) and research profile (Young Investigators projects typically aim to establish a new line of research at the institution involved, besides targeting researchers who are starting their career).
These projects were selected by searching FAPESP’s database for projects that contained terms relating to biodiversity and then validating the results with the management of BIOTA and FAPESP.
FAPESP Analysts, researchers and managers of biodiversity research projects at public and private organizations.
In particular, see two paragraphs (and Assumption 3.2) right before section 3.1 on page 7, from Abadie (2005).
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Acknowledgments
This work was supported by the São Paulo Research Foundation (FAPESP) [Grant number 2008/58628-7]; and Coordination for the Improvement of Higher Level Personnel (CAPES) [Grant AUX-PE-PNPD- 1945/2008].
Conflict of interest
Authors declare none conflict of interest. FAPESP played no role in the design of the study, data analysis, or in manuscript preparation.
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Colugnati, F.A.B., Firpo, S., de Castro, P.F.D. et al. A propensity score approach in the impact evaluation on scientific production in Brazilian biodiversity research: the BIOTA Program. Scientometrics 101, 85–107 (2014). https://doi.org/10.1007/s11192-014-1397-1
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DOI: https://doi.org/10.1007/s11192-014-1397-1