Team Incentives for Education in Developing Countries: A Randomized Field Experiment in Benin

2014 ◽  
Vol 6 (4) ◽  
pp. 90-109 ◽  
Author(s):  
Moussa P. Blimpo
Keyword(s):  
Developing Countries ◽  
Treatment Effect ◽  
Average Treatment Effect ◽  
The Other ◽  
Standard Errors ◽  
Incentive Structure ◽  
Monetary Rewards ◽  
Randomized Field Experiment ◽  
The Impact ◽  
Rule Out

I examine the impact of student incentives in Benin, using three different designs that can be implemented relatively cheaply and with administrative data. The first design is a standard incentive structure where students receive monetary rewards for reaching a performance target. In the other two designs, teams of four students receive incentives based on either their performance level as a group or in a team tournament scheme. I find a large and similar average treatment effect across designs, ranging from 0.27 to 0.34 standard deviations (Standard errors do not allow to rule out that the three designs are equally effective). (JEL C93, D82, I21, I28, O15)

Non-governmental Organisations and Democracy: An Empirical Analysis

2015 ◽  
Vol 21 (4) ◽  
pp. 489-496 ◽  
Author(s):  
Tania Masi
Keyword(s):  
Developing Countries ◽  
Propensity Score ◽  
United Nations ◽  
Propensity Score Matching ◽  
Empirical Analysis ◽  
Treatment Effect ◽  
Average Treatment Effect ◽  
Government Accountability ◽  
The United Nations ◽  
The Impact

AbstractThe United Nations established in 2005 the United Nations Democracy Fund (UNDEF), whose objective is to support projects submitted by national NGOs aimed at increasing government accountability. The purpose of this paper is to investigate the impact of NGOs activity on democracy exploiting the UNDEF database. An empirical analysis based on a propensity score matching (PSM) method is implemented on a sample of 102 developing countries. The findings indicate that the average treatment effect on the treated (ATT) is positive and significant only when countries receive UNDEF-funded NGOs projects for three rounds or more. In this case the Polity IV indicator improves by an average of 1.08 points with respect to the level of 2005.

Modernism, Empiricism, and Rationalism

2016 ◽  
Vol 46 (1) ◽  
pp. 38-47
Author(s):  
Geoffrey Squires
Keyword(s):  
Twentieth Century ◽  
The Other ◽  
Modern Poetry ◽  
Philosophical Perspective ◽  
Irish Poetry ◽  
Dimensional Spectrum ◽  
Culture History ◽  
The World ◽  
The Impact ◽  
Rule Out

Modernism is usually defined historically as the composite movement at the beginning of the twentieth century which led to a radical break with what had gone before in literature and the other arts. Given the problems of the continuing use of the concept to cover subsequent writing, this essay proposes an alternative, philosophical perspective which explores the impact of rationalism (what we bring to the world) on the prevailing empiricism (what we take from the world) of modern poetry, which leads to a concern with consciousness rather than experience. This in turn involves a re-conceptualisation of the lyric or narrative I, of language itself as a phenomenon, and of other poetic themes such as nature, culture, history, and art. Against the background of the dominant empiricism of modern Irish poetry as presented in Crotty's anthology, the essay explores these ideas in terms of a small number of poets who may be considered modernist in various ways. This does not rule out modernist elements in some other poets and the initial distinction between a poetics of experience and one of consciousness is better seen as a multi-dimensional spectrum that requires further, more detailed analysis than is possible here.

scholarly journals Adoption of Conservation Practices: Its Impact on Input Use and Performance in the Northern Region of Ghana

2018 ◽  
Vol 11 (5) ◽  
pp. 149
Author(s):  
Mavis Boimah ◽  
Akwasi Mensah-Bonsu ◽  
Yaw Osei-Asare ◽  
Daniel B. Sarpong
Keyword(s):  
Treatment Effect ◽  
Environmental Sustainability ◽  
Technical Assistance ◽  
Negative Impact ◽  
Maize Yield ◽  
Average Treatment Effect ◽  
Inorganic Fertilizer ◽  
Switching Regression ◽  
Average Treatment ◽  
The Impact

Conservation Agriculture (CA) is promoted worldwide on the basis of its contribution to economic, social, and environmental sustainability of agricultural production. In Ghana, despite the increasing interest in the promotion of CA and its practices, its rate of adoption is still low, mainly due to the conflicting evidences regarding its effectiveness. This paper contributes to the numerous debates by examining the impact of CA practices on hired labour, rates of inorganic fertilizers applied by adopters, maize yield, and profit of adopters. Using a cross-sectional data, a multinomial endogenous switching regression (MESR) model was employed to compute the Average Treatment Effect (ATE) and Average Treatment Effect on Treated (ATET) for yield, hired labour, inorganic fertilizer rate, and profit of adopters of CA practices. The study reveals that CA practices impact positively on hired labour employed on the farm, but have a negative impact on profits of adopters. No impact whatsoever of adoption of CA practices is observed on maize yield and also inorganic fertilizer application rates. Technical assistance, and training of farmers on strategies that minimize costs of production must be intensified to raise profits of adopters.

Propensity score specification for optimal estimation of average treatment effect with binary response

2020 ◽  
Vol 29 (12) ◽  
pp. 3623-3640
Author(s):  
John A Craycroft ◽  
Jiapeng Huang ◽  
Maiying Kong
Keyword(s):  
Propensity Score ◽  
Treatment Effect ◽  
Propensity Scores ◽  
Optimal Estimation ◽  
Theoretical Explanation ◽  
Average Treatment Effect ◽  
Adaptive Lasso ◽  
Confounding Bias ◽  
Average Treatment ◽  
The Impact

Propensity score methods are commonly used in statistical analyses of observational data to reduce the impact of confounding bias in estimations of average treatment effect. While the propensity score is defined as the conditional probability of a subject being in the treatment group given that subject’s covariates, the most precise estimation of average treatment effect results from specifying the propensity score as a function of true confounders and predictors only. This property has been demonstrated via simulation in multiple prior research articles. However, we have seen no theoretical explanation as to why this should be so. This paper provides that theoretical proof. Furthermore, this paper presents a method for performing the necessary variable selection by means of elastic net regression, and then estimating the propensity scores so as to obtain optimal estimates of average treatment effect. The proposed method is compared against two other recently introduced methods, outcome-adaptive lasso and covariate balancing propensity score. Extensive simulation analyses are employed to determine the circumstances under which each method appears most effective. We applied the proposed methods to examine the effect of pre-cardiac surgery coagulation indicator on mortality based on a linked dataset from a retrospective review of 1390 patient medical records at Jewish Hospital (Louisville, KY) with the Society of Thoracic Surgeons database.

Unbiased Estimation of the Average Treatment Effect in Cluster-Randomized Experiments

2015 ◽  
Vol 6 (1-2) ◽  
Author(s):  
Joel A. Middleton ◽  
Peter M. Aronow
Keyword(s):  
Treatment Effect ◽  
Average Treatment Effect ◽  
Unbiased Estimation ◽  
Random Allocation ◽  
Randomized Experiments ◽  
Average Treatment ◽  
Randomized Field Experiment ◽  
The Difference ◽  
Biased Estimators ◽  
Cluster Randomized

AbstractMany estimators of the average treatment effect, including the difference-in-means, may be biased when clusters of units are allocated to treatment. This bias remains even when the number of units within each cluster grows asymptotically large. In this paper, we propose simple, unbiased, location-invariant, and covariate-adjusted estimators of the average treatment effect in experiments with random allocation of clusters, along with associated variance estimators. We then analyze a cluster-randomized field experiment on voter mobilization in the US, demonstrating that the proposed estimators have precision that is comparable, if not superior, to that of existing, biased estimators of the average treatment effect.

Impact of the production of underutilized vegetables on the livelihood of farmers in Southwestern Nigeria

2017 ◽  
Vol 44 (12) ◽  
pp. 1669-1682
Author(s):  
Oluwatosin Adejoke Oyedele ◽  
Kemisola O. Adenegan
Keyword(s):  
Treatment Effect ◽  
Nutritive Value ◽  
Average Treatment Effect ◽  
Current Status ◽  
Special Focus ◽  
Vegetable Production ◽  
Southwestern Nigeria ◽  
Content Type ◽  
Average Treatment ◽  
The Impact

Purpose African indigenous vegetables have high nutritive value which contains high levels of minerals. The current status of indigenous vegetable production in developing countries shows that these crops are “under-recognized” and “underutilized” with respect to nutritional value and opportunities for food security. The purpose of this paper is to examine the impact of the production of underutilized vegetables on the livelihood of farmers in South Western Nigeria. Design/methodology/approach The population for the study includes all the vegetable farmers in South Western Nigeria with a special focus on farmers’ groups formed by the NICANVEG project in Osun, Oyo, Ondo and Ekiti states. Descriptive statistics and propensity score matching (PSM) was used to analyze the objective. Findings Perceptions on individual household income reveal that the majority of participating respondents perceived higher production and harvesting density. This is due to the fact that harvesting is done by cutting the stems of the vegetables. The probability score shows that the dependent variables have an average effect of 44.6 percent on the probability of farmers participating in NICANVEG project. The PSM results reveal that average treatment effect on the treated is ₦269,254.87. Average treatment on the untreated is ₦11,990.63 while average treatment effect is ₦139,336.43. The total income of the participants from all the various livelihood strategies is increased by 29.73 percent because of their participation in the NICANVEG project. Originality/value This work has not been carried out by any other person before. This work will add to the existing knowledge on the impact of evaluation in agricultural economics.

scholarly journals Integrating expert opinions with clinical trial data to analyse low-powered subgroup analyses: a Bayesian analysis of the VeRDiCT trial

2020 ◽  
Author(s):  
Russell Thirard ◽  
Raimondo Ascione ◽  
Jane Blazeby ◽  
Chris A Rogers
Keyword(s):  
Bayesian Analysis ◽  
Usual Care ◽  
Treatment Effect ◽  
Average Treatment Effect ◽  
Trial Data ◽  
Diabetic Patients ◽  
Expert Opinions ◽  
Subgroup Analyses ◽  
The Impact ◽  
Subgroup Effects

Abstract BackgroundTypically, subgroup analyses in clinical trials are conducted by comparing the intervention effect in each subgroup by means of an interaction test. However, trials are rarely, if ever, adequately powered for interaction tests, so clinically important interactions may go undetected. We discuss the application of Bayesian methods by using expert opinions alongside the trial data. We applied this methodology to the VeRDiCT trial investigating the effect of preoperative volume replacement therapy (VRT) versus no VRT (usual care) in diabetic patients undergoing cardiac surgery. Two subgroup effects were of clinical interest, a) preoperative renal failure and b) preoperative type of antidiabetic medication. MethodsClinical experts were identified within the VeRDiCT trial centre in the UK. A questionnaire was designed to elicit opinions on the impact of VRT on the primary outcome of time from surgery until medically fit for hospital discharge, in the different subgroups. Prior beliefs of the subgroup effect of VRT were elicited face-to-face using two unconditional and one conditional questions per subgroup analysis. The robustness of results to the ‘community of priors’ was assessed. The community of priors was built using the expert priors for the mean average treatment effect, the interaction effect or both in a Bayesian Cox proportional hazards model implemented in the STAN software in R. ResultsExpert opinions were obtained from 7 clinicians (6 cardiac surgeons and 1 cardiac anaesthetist). Participating experts believed VRT could reduce the length of recovery compared to usual care and the greatest benefit was expected in the subgroups with the more severe comorbidity. The Bayesian posterior estimates were more precise compared to the frequentist maximum likelihood estimate and were shifted toward the overall mean treatment effect. Conclusions In the VeRDiCT trial, the Bayesian analysis did not provide evidence of a difference in treatment effect across subgroups. However, this approach increased the precision of the estimated subgroup effects and produced more stable treatment effect point estimates than the frequentist approach. Trial methodologists are encouraged to prospectively consider Bayesian subgroup analyses when low-powered interaction tests are planned.Trial registration ISRCTN, ISRCTN02159606. Registered 29th October 2008.

scholarly journals EXPRESS: Treatment Effect Heterogeneity in Randomized Field Experiments: A Methodological Comparison and Public Policy Implications

2021 ◽  
pp. 074391562110327
Author(s):  
Yixing Chen ◽  
Shrihari Sridhar ◽  
Vikas Mittal
Keyword(s):  
Public Policy ◽  
Treatment Group ◽  
Treatment Effect ◽  
Field Experiments ◽  
Average Treatment Effect ◽  
Policy Implications ◽  
Control Group ◽  
Policy Studies ◽  
Randomized Field Experiment ◽  
Effect Heterogeneity

Many public-policy studies (Martin and Scott 2020) use randomized field experiments for drawing causal conclusions (e.g., Chen et al. 2020). A typical randomized field experiment involves a control group and a treatment group to which individual units (e.g., consumers, patients) are randomly assigned, after which an intervention is implemented in the treatment group. An intervention could be a marketing program to which only units in the treatment group are exposed. To assess the intervention's efficacy, researchers typically estimate the average treatment effect computed as the mean difference in the outcome between the units in the treatment group and the control group. When applying the results of a randomized experiment, it is assumed that the treatment effect within the manipulated condition is the same for all the units assigned to the treatment condition. This may not always be the case, as the effect may differ for subgroups within a treatment (subgroup differences).

The impact of collective use rights on share contracts: the case of the Extractive Artisanal Regime (RAE) in Chilean hake fisheries

2020 ◽  
Vol 25 (4) ◽  
pp. 355-377
Author(s):  
César Salazar ◽  
Jorge Dresdner
Keyword(s):  
Income Distribution ◽  
Regression Model ◽  
Treatment Effect ◽  
Census Data ◽  
Regulatory Reform ◽  
Average Treatment Effect ◽  
Artisanal Fisheries ◽  
Switching Regression ◽  
Factor Income ◽  
The Impact

AbstractShare contracts are the dominant remuneration system in artisanal fisheries. Introducing regulations based on collective use rights may affect the way profits are distributed. The literature on the effect of regulatory reform on factor income distribution, however, is scarce. In this paper, we look at differences in the implementation of the Extractive Artisanal Regime in Chilean hake artisanal fisheries to test its effect on share contracts. We estimated a switching regression model using census data to calculate the average treatment effect. Our results show that crewmembers in communities regulated by some form of collective use rights receive, on average, 6 per cent more of total net incomes compared to those regulated by a limited access with global quota regime. Differences in the relation between crew size and labor rewards, as well as in the negotiating power of crewmembers under different regimes, may explain the results.

Trademarks in Developing Countries

1976 ◽  
Vol 14 (2) ◽  
pp. 297-309 ◽  
Author(s):  
Peter O'Brien
Keyword(s):  
Developing Countries ◽  
Significant Proportion ◽  
Appropriate Technology ◽  
The Other ◽  
Industrial Property ◽  
Production Processes ◽  
Other Hand ◽  
The One ◽  
The Impact

The concern with the impact of industrial property legislation and practices on the developing countries, at both the national and international levels, has so far been confined almost entirely to patents and patent-related transactions. This focus on the protection of knowledge concerning production processes reflects, on the one hand, a preoccupation with the terms and conditions which owners of technology may be able to obtain for its sale or lease, when their proprietary position is reinforced by legal instruments; and on the other hand, a recognition that unless the developing countries can themselves control the generation of a significant proportion of the technology they employ, it is unlikely either that appropriate technology will be produced, or that good use will be made of what is already available and relevant.

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