Quantifying the Impact of Social Science Development Research: Is It Possible?. Kunal Sen IDPM and BWPI, University of Manchester Based on paper: Literature Review on Rates of Return to Research, available on DFID R4D website. Quantifying the impact of research: the rate of return to research.
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Quantifying the Impact of Social Science Development Research: Is It Possible?
IDPM and BWPI, University of Manchester
Based on paper: Literature Review on Rates of Return to Research, available on DFID R4D website.
The attribution problem can be broken down to the following components:
Since developmental outcomes may occur due to many reasons, and policy interventions is one possible cause of such outcomes among many others, it is often difficult to precisely identify whether the policy intervention can be causally related to the outcome in question.
There are three different aspects to the identification problem:
a) selection bias;
b) omitted variable bias;
c) Reverse causality.
An important requirement in the application of the rate of return approach is that all benefits, past, present and future, can be quantified and expressed in the same unit of value.
This leads to five problems in the measurement of these benefits:
a) valuing multiple outputs;
b) valuing intangible outcomes;
c) time-scale of measurement;
d) the degree of uncertainty on the size of the impact;
e) measuring effects, where there are macro-changes or strong spillover effects.