Is there persistence in the impact of emergency food aid? Evidence on consumption, food security, and assets in rural Ethiopia

"The primary goal of emergency food aid after an economic shock is often to bolster short-term food and nutrition security. However, these transfers also act as insurance against other shock effects, such as destruction of assets and changes in economic activity, which can have lasting deleterious consequences. Although existing research provides some evidence of small positive impacts of timely food aid disbursements after a shock on current food consumption and aggregate consumption, little is known about whether these transfers play a safety net role by reducing vulnerability and protecting assets into the future. We investigate this issue by exploring the presence of persistent impacts of two major food aid programs following the 2002 drought in Ethiopia: a food-for-work program known as the Employment Generation Schemes (EGS) and a program of free food distribution (FFD). Using rural longitudinal household survey data collected in 1999 and 2004, we estimate the impact of these programs on consumption growth, food security, and growth in asset holdings 18 months after the peak of the drought, when food aid transfers had substantially or entirely ceased in most program villages... Overall, these results suggest that emergency food aid played an important role in improving welfare, access to food, and food security for many households following the drought in 2002. However, improved targeting, especially in EGS, and larger, sustained transfers may be required to increase benefits, particularly to the poorest households. The impacts of food aid identified here indicate some persistence or accumulated effects of transfers on consumption growth over time. Although the time lag between receipt of transfers and observed consumption is not more than one year in most cases, the estimated impact on consumption growth relative to the size and timing of transfers suggests possible savings or multiplier effects of emergency food aid." -- Authors' AbstractFood aid, Treatment effects, Propensity score matching, Ethiopia, africa, East Africa, food security, Nutrition security

Competencies for educators in delivering digital accessibility in higher education

The aim of this paper is to critically review the capabilities of the European Framework for the Digital Competence of Educators (DigCompEdu) and the UNESCO ICT Competency Framework for in delivering greater accessibility for students with disabilities in a Higher Education landscape undergoing Digital Transformation. These frameworks describe what it means for educators to be digitally competent. However are there other competencies required to deliver Digital Accessibility in education. The particular focus of this paper is the role of the teachers in delivering Digital Accessibility in higher education. What should be expected of them and what are the required competencies to meet these expectations? Is it fair for example to expect teachers to cross boundaries where the effectiveness of general accessibility strategies such as UDL end for particular groups of students for example blind students in STEM subjects and where there is a need for individualised accommodations

The impact of Ethiopia's Productive Safety Net Programme and its linkages:

"This paper assesses the impact of Ethiopia's Productive Safety Nets Programme (PSNP), the largest social protection program in Sub-Saharan Africa outside of South Africa. Using Propensity Score Matching techniques, we find that the program has little impact on participants on average, due in part to transfer levels that fell far below program targets. Beneficiary households that received at least half of the intended transfers experienced a significant improvement in food security by some measures. However, households with access to both the PSNP and packages of agricultural support were more likely to be food secure, to borrow for productive purposes, use improved agricultural technologies, and operate their own nonfarm business activities. For these households, there is no evidence of disincentive effects in terms of labor supply or private transfers. However, estimates show that beneficiaries did not experience faster asset growth as a result of the programs. " from authors' abstractProductive Safety Net Programme, Impact evaluation, food security, Public works, Social protection,

Betting and Belief: Prediction Markets and Attribution of Climate Change

Despite much scientific evidence, a large fraction of the American public doubts that greenhouse gases are causing global warming. We present a simulation model as a computational test-bed for climate prediction markets. Traders adapt their beliefs about future temperatures based on the profits of other traders in their social network. We simulate two alternative climate futures, in which global temperatures are primarily driven either by carbon dioxide or by solar irradiance. These represent, respectively, the scientific consensus and a hypothesis advanced by prominent skeptics. We conduct sensitivity analyses to determine how a variety of factors describing both the market and the physical climate may affect traders' beliefs about the cause of global climate change. Market participation causes most traders to converge quickly toward believing the "true" climate model, suggesting that a climate market could be useful for building public consensus.Comment: All code and data for the model is available at http://johnjnay.com/predMarket/. Forthcoming in Proceedings of the 2016 Winter Simulation Conference. IEEE Pres

The impact of agricultural extension and roads on poverty and consumption growth in fifteen Ethiopian villages:

"This paper investigates whether public investments that led to improvements in road quality and increased access to agricultural extension services led to faster consumption growth and lower rates of poverty in rural Ethiopia. Estimating an instrumental variables model using Generalized Methods of Moments and controlling for household fixed effects, we find evidence of positive impacts with meaningful magnitudes. Receiving at least one extension visit reduces headcount poverty by 9.8 percentage points and increases consumption growth by 7.1 percent. Access to all-weather roads reduces poverty by 6.9 percentage points and increases consumption growth by 16.3 percent. These results are robust to changes in model specification and estimation methods." from authors' abstractPublic investment, roads, agricultural extension, income growth, Poverty,

Topic Modeling the President: Conventional and Computational Methods

Legal and policy scholars modeling direct actions into substantive topic classifications thus far have not employed computational methods. To compare the results of their conventional modeling methods with the computational method, we generated computational topic models of all direct actions over time periods other scholars have studied using conventional methods, and did the same for a case study of environmental-policy direct actions. Our computational model of all direct actions closely matched one of the two comprehensive empirical models developed using conventional methods. By contrast, our environmental-case-study model differed markedly from the only empirical topic model of environmental-policy direct actions using conventional methods, revealing that the conventional methods model included trivial categories and omitted important alternative topics. Provided a sufficiently large corpus of documents is used, our findings support the assessment that computational topic modeling can reveal important insights for legal scholars in designing and validating their topic models of legal text. To be sure, computational topic modeling used alone has its limitations, some of which are evident in our models, but when used along with conventional methods, it opens doors towards reaching more confident conclusions about how to conceptualize topics in law. Drawing from these results, we offer several use cases for computational topic modeling in legal research. At the front end, researchers can use the method to generate better and more complete topic-model hypotheses. At the back end, the method can effectively be used, as we did, to validate existing topic models. And at a meta-scale, the method opens windows to test and challenge conventional legal theory. Legal scholars can do all of these without the machines, but there is good reason to believe we can do it better with them in the toolkit