Journal ArticleDOI
Do Different Implementing Partnerships Lead to Different Project Outcomes? Evidence from the World Bank Project-Level Evaluation Data
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TLDR
In this article, the authors examined the relationship between the number of state and non-state partners interacting in a project and the subsequent project outcome. And they showed that an increased number of non-State actor participants leads to a better project outcome; this positive participatory effect, however, diminishes as a number of governmental implementers increases.About:
This article is published in World Development.The article was published on 2017-07-01. It has received 28 citations till now. The article focuses on the topics: Participatory development & International development.read more
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Haiti in the Balance – Why Foreign Aid Has Failed and What We Can Do About It
TL;DR: In this paper, Haiti in the Balance takes a refreshingly honest and rounded view of what can only be described as a catastrophic failure of develop-or-failure of develop...
Journal ArticleDOI
Why Does Aid Not Target the Poorest
TL;DR: The authors show that, conditional on local population, World Bank (WB) project aid targets richer parts of countries and this relationship holds over time and across world regions, and suggest that tweaks to WB incentive structures to make ease of project implementation less important may encourage aid to flow to poorer parts of the world.
Journal ArticleDOI
Too Many Cooks in the Kitchen? The Division of Financing in World Bank Projects and Project Performance
TL;DR: In this article, the authors argue that too many funding streams in a project can reduce project effectiveness by creating delays, increasing transaction costs, and blurring lines of accountability, and they combine original data on the number and concentration of financial collaborators in World Bank projects with the World Bank ratings of project performance, looking at within-country variation across projects to explore whether or not there is evidence of reduced aid effectiveness in projects with more participants.
Journal ArticleDOI
Delegation of implementation in project aid
Silvia Marchesi,Tania Masi +1 more
TL;DR: In this paper, the authors explore the factors that determine delegation of implementation in project aid, focusing on the importance of informational asymmetry between levels of government, and empirically assess whether this choice is influenced by the relative importance of the local information at the recipient country level.
Journal ArticleDOI
Sustainable development in East Africa: impact evaluation of regional agricultural development projects in Burundi, Kenya, Rwanda, Tanzania, and Uganda
TL;DR: In this paper, the authors used panel data from 1,160 smallholder households including beneficiaries and non-beneficiaries from five countries in East Africa (Burundi, Kenya, Rwanda, Tanzania, and Uganda).
References
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Book
Regression Models for Categorical Dependent Variables Using Stata
J. Scott Long,Jeremy Freese +1 more
TL;DR: In this article, the authors present a brief tutorial for estimating, testing, fit, and interpretation of ordinal and binary outcomes using Stata. But they do not discuss how to apply these models to other estimation commands, such as post-estimation analysis.
Book
Applied Logistic Regression Analysis
TL;DR: The second edition of the Second Edition of the Logistic regression model as discussed by the authors is the most complete version of the first edition and includes a discussion of the relationship between linear regression and logistic regression.
Book
Regression Models for Categorical Dependent Variables Using Stata, Second Edition
J. Scott Long,Jeremy Freese +1 more
TL;DR: This book discusses models for ordinal and nominal independent variables, and describes the development of models for Nominal Outcomes with Case-Specific Data and its use in Stata.
Journal ArticleDOI
Computing Interaction Effects and Standard Errors in Logit and Probit Models
TL;DR: In this paper, the authors explain why computing the marginal effect of a change in two variables is more complicated in nonlinear models than in linear models, and explain how to compute the correct marginal effect in non-linear models.
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M. Falaleeva,Felix Rauschmayer +1 more