Quantitative approaches play a vital role in the process of defining and analyzing public policies so that better results can be achieved when these policies are implemented. As well as using quantitative methods to evaluate public policies, we seek to promote and facilitate their use in policy design, planning, and management. Quantitative models can be used to carry out diagnostic exercises and evaluations and also for predictions and simulations. Evidence-based discussion allows us to close the gaps between different positions and viewpoints and forge collaborative connections.

To make public policy analysis more useful, we need to bring decision makers, data generators, and analysts together. This, in turn, renders new technologies and the models themselves more actionable. Data is not neutral: the process of selecting and gathering it can create biases that impact the conclusions we reach and thus the actions we take. Analyzing and reading data in context is a new skill that must be promoted through education and open discussion.


Daniel Yankelevich es informático, PhD de la Universidad de Pisa, realizó su postdoctorado en Carolina del Norte, EEUU. Docente universitario, con trayectoria en el sector privado y en proyectos de investigación.


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