Our Cambodia office continues to invest in local solutions to development challenges. For the past few months, they’ve been working to build capacity for local policy researchers by offering statistics training to government agencies.
Our partners at Mercy Corps referenced some research that ODI recently did on real-time resilience measurement and analysis (see paper here) in Myanmar. It’s not everyday that you can track resilience measurement every two months for a panel of 1,200
Building scalable and sustainable food systems presents many challenges along farming value chains – not least of which is the point where our small holder famers interact with agricultural inputs. For an isolated farmer with limited education, making wise choices about farming can be challenging, meaning that many farmers fall short of the mark when it comes to running successful commercial enterprises.
The coefplot command allows you to plot results from estimation commands. It is a user package, so you will have to find and install it by inputting into the Stata command line:
While using hashtags is simpler than generating the interaction term as a new variable, there is a necessary rule to remember: use the variable prefixes. In Stata, -i.[variable]- indicates that the variable is categorical, and -c.[variable]- indicates a continuous variable. Because the hashtag code assumes the variables in the interaction term are categorical, it is necessary to define numerical variables as numerical with the -c.- prefix.
Wage = β0 + β1Education + β2Minority + β3Education*Minority + ε
With the steady rise of the number of impact evaluations (IEs) per year, it should come as no surprise that not every single IE will show a positive impact.
We work with clients who are running poverty interventions in the field. These are not experiments – where the program is designed around an experiment – these are impact evaluations that have to be designed around a development program that
Introduction It is often the case in Impact Evaluation that we have a need to analyze binary, qualitative variables such as savings behavior (saves vs. does not save), voting behavior (votes vs. does not vote), or gender (male vs. female).
From MercyCorps.org: We are excited to release Mercy Corps’ newest research, in partnership with Causal Design, bringing more evidence on how households and communities can be resilient in the face of crisis. What Next for Nepal? Evidence of What Matters for
We are thrilled to announce that Dan Hudner has joined the Causal Design team as our Director of Research. Dan joins us from Mercy Corps where he has served as the Peacebuilding Evaluation Fellow and co-authored research on disaster resilience with Jon