The primary goal of an impact evaluation study is to estimate the causal effect of a program, policy, or intervention. Randomized assignment of treatment enables the researcher to draw causal inference in a relatively assumption free manner. If randomization is not feasible there are more assumption driven methods, termed quasi-experimental, such as regression discontinuity or propensity score matching. For many of our readers this summary is nothing new. But fortunately in our “community of practice” new statistical tools are developed at a rapid rate.
Jed Friedman's blog
Often in IE (and in social research more generally) the researcher wishes to know respondent views or information regarded as highly sensitive and hence difficult to directly elicit through survey. There are numerous examples of this sensitive information – sexual history especially as it relates to risky or taboo practices, violence in the home, and political or religious views.
When Development Impact shut down for August, I had ambitious goals. Unfortunately I didn’t meet them all (why does that always happen?). However I did manage to madly review almost 60 proposals for the funding of prospective impact evaluations financed by various organizations and donors. Many of these proposals were excellent (unfortunately not all could be funded). However it was surprisingly informative to read so many proposals in such a condensed time.
- Proposal writing
Last week David linked to a virtual discussion involving Dave Giles and Steffen Pischke on the merits or demerits of the Linear Probability Model (LPM).
The short-term benefits of certain social support programs such as CCTs have been well documented –CCT programs tend to raise household consumption as well as the utilization of schools and health clinics. It is a natural question, and one of great interest, to think more dynamically and ask whether these programs also enable households to invest in productive assets.
Allow me to take the occasion of the 236th “birthday” of my native-born country (celebrated on July 4th here in the U.S.) to go far afield and discuss a topic that, while grounded in empirical social science, doesn’t touch directly on impact evaluation. The topic is how the personality traits of an individual may be related to his or her relative wealth.
This blog has previously explored the (somewhat rare) involvement of other social science disciplines in development economics research. Now a new book helps move the ball down the field a bit more. Entitled Children and Youth in Crisis, and edited by Mattias Lundberg and Alice Wuermli, the book combines various disciplinary perspectives on the impacts of economic shocks on human development.
Indoor smoke from cooking on an open fire has long been recognized as a major cause of ill health, especially for women and young children (those either most vulnerable or most likely to be exposed). Improved cooking stoves represent the hopes of development professionals in that their efficient design and vented smoke should improve health, lower mortality, and reduce fuel use.
Public sector reforms often attempt to mimic the “discipline” of the market in order to spur better performance among service providers. Examples include numerous variants of performance based financing for health, where health providers are compensated monetarily for achievement of specified health targets. At the heart of this approach is a standard view of economic agents induced to modify behaviors through pecuniary incentives.
Researchers have long recognized the importance of choosing interviewer characteristics while designing their fieldwork – for example female interviewers are often utilized to explore topics related to domestic violence and respondents of both sexes are more likely to disclose sexual abuse to female interviewers than to male ones. Another key consideration is the degree of familiarity between interviewer and respondent, but here the decision appears to be obvious.
- interviewer effects