CategoriesBlog PostThere is little about COVID-19 that is clear right now. It has torn through countries, though at varying rates. Death rates have varied, and as time has passed, initial assumptions about who is affected have been shredded, as even young, healthy people have succumbed to the disease. The uncertainty surrounding COVID-19 has been a challenge for everyone, whether a small business owner or public policy expert.
CategoriesBlog PostCOVID-19 is proving calamitous, with over 250,000 deaths globally, including 70,000 deaths within the United States, and 50,000 across the continent of Africa. Its economic impact is in the never-before-seen realm, and uncertainty, even amid talk of ‘opening up,’ is growing, as new hot spots emerge and as everything from schools to professional sports contemplate next-steps.
Among the outcomes up in the air? State-society relations, everywhere, with long-term, potentially generational implications for the trajectory of post-pandemic health, development and prosperity.
Over the past twenty years, the use of cash transfers in development and humanitarian interventions has experienced exponential growth. Both evidence and ethics have contributed to its rise. Extensive research has demonstrated how cash transfers can serve as critical lifelines in both acute humanitarian emergencies and more stable development contexts, whilst also providing recipients with […]
The Untapped Potential of Impact Evaluations in Humanitarian Contexts What is the right modality of program delivery? Does anticipatory action prior to a humanitarian emergency have a positive impact on a household’s ability to cope? Which methods are most cost-effective? Which methods lead to the most positive impact on long-term resilience? Are you interested in […]
Evaluating Humanitarian Response in Rapid Onset Crises: The Power of Pre-Positioning Research When it comes to evaluating humanitarian programming and emergency responses, we have a conundrum. The urgency of humanitarian response is widely thought to be at odds with lengthy evaluation processes. In the case of a rapid-onset humanitarian crisis, such as a natural disaster or armed conflict, setting up […]
CategoriesBlog PostAnnouncing the New Building Evidence for Decision-Making (BE4D) Program We are thrilled to announce the launch of the Building Evidence for Decision-Making (BE4D) program earlier this year, a ten-year initiative designed to advance evidence-based decision-making across USAID operating units and global Missions. This program is housed within USAID’s Bureau for Inclusive Growth, Partnerships, and Innovation (IPI) and […]
We are proud to announce that we have entered into an SBA-approved Mentor-Protégé Agreement with the Panagora Group. Together we will leverage our shared passion for turning evidence into action to grow, expand our work and impact with USAID, and help improve SDVOSB utilization at USAID.
This week’s blog will feature a set of Stata tricks we used to addresses a particular issue that we encountered in our dataset. Many of the variables were in string form and were not useable for Stata analysis. Furthermore, the values of the variables were not in the correct order for our purposes. A couple of commands came in handy here. Loops are useful for many different repetitive commands. They allowed us to quickly recode the values of a set of variables that have similar categorical values and also enabled us to destring sets of variables, setting them to numeric values. These numeric values were in turn reordered to fit a desired pattern. Finally, the labels for the numeric values were recoded to appear as the original text instead of just “1, 2, 3, etc”.
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:
findit coefplot
The OECD-DAC recently added to its list of evaluation criteria—the de facto norm through which organizations like Causal Design frequently organize evaluations and reporting. Specifically, after a multi-year process of considering how to best adapt its existing criteria, OECD added Coherence: How well does the intervention fit? to the existing and remaining five criteria.
Reactions around our proverbial dinner table were appropriately mixed: How does this further a wider learning agenda? How does this differ from the existing Relevance? (which at times already overlaps with Sustainability) What does “fit” actually mean, and how do we use it, and meaningfully?
