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.

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.

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 Farmers’ Exposure to Climate Hazards and Reforestation in Selected African Villages: An Endogenous-Switching Regression Model

2019 ◽  
Author(s):  
Tolulope Olayemi Oyekale ◽  
Abayomi Oyekale
Keyword(s):  
Burkina Faso ◽  
Treatment Effect ◽  
Smallholder Farmers ◽  
Average Treatment Effect ◽  
Tree Planting ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Hazard Exposure ◽  
Endogenous Switching ◽  
Household Headship

Abstract Background: Deforestation remains a serious concern for Africa’s economic development and global climatic stability. Emphases are now placed on promoting some essential adaptive and mitigation strategies among smallholder farmers. This paper analyzed the effect of exposure to climate-related hazards on tree planting among smallholder farmers in nine selected African countries. The data were from baseline surveys which were conducted by the CGIAR’s research programme on Climate Change, Agriculture and Food Security (CCAFS). The included countries were Burkina Faso, Ethiopia, Ghana, Kenya, Mali, Niger, Senegal, Tanzania and Uganda. Data were analyzed with Endogenous Switching regression considering the endogeneity potentials of climate-hazard exposure. Results: The results showed that Uganda and Ethiopia had the highest average numbers of tree planting with 1.082 and 1.000 respectively, while Senegal (89.86%), Kenya (87.77%), Burkina Faso (82.86%) and Ethiopia (82.86%) had the highest exposure to climate-related hazards. Endogenous Switching regression results showed that climate hazard exposure was truly endogenous going by statistical significance of the Wald Chi Square test (p<0.05) and it was significantly influenced by female household headship, perception of more droughts, floods and low ground water. The number of tree that were planted increased significantly (p<0.05) with climate hazard exposure, degraded land areas, asset indices and residence in East Africa, while it reduced with female household headship. In addition, Average Treatment Effect (ATE) result indicated that an average household will plant 0.745 trees more when it had been previously exposed to climate shocks while Average Treatment Effect on the Treated (ATET) revealed that an average household that was exposed to climate hazards would plant 0.54 more trees than it would if it had not been exposed to hazards. Conclusion: The major implication of the findings is that without having previously experienced some climatic adversities, farmers may not see the need to engage in tree planting as a mitigating strategy. It was concluded that many farmers had been affected by climate-related shocks and efforts to safeguard future climate through tree planting should be gender sensitive and concentrated among previously affected farmers.

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.

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.

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)

scholarly journals A Text-As-Data Approach for Using Open-Ended Responses as Manipulation Checks

2020 ◽  
Author(s):  
Jeffrey Ziegler
Keyword(s):  
Treatment Effect ◽  
Average Treatment Effect ◽  
Continuous Measure ◽  
Causal Inferences ◽  
Online Surveys ◽  
Manipulation Check ◽  
Potential Variation ◽  
Average Treatment ◽  
The Impact

Participants that complete online surveys and experiments may be inattentive, which can hinder researchers’ ability to draw substantive or causal inferences. As such, many practitioners include multiple factual or informational closed-ended manipulation checks to identify low-attention respondents. However, closed-ended manipulation checks are either correct or incorrect, which allows participants to more easily guess and it reduces the potential variation in attention between respondents. In response to these shortcomings, I develop an automatic and standardized methodology to measure attention that relies on the text that respondents provide in an open-ended manipulation check. There are multiple benefits to this approach. First, it provides a continuous measure of attention, which allows for greater variation between respondents. Second, it reduces the reliance on subjective, paid humans to analyze open-ended responses. Last, I outline how to diagnose the impact of inattentive workers on the overall results, including how to assess the average treatment effect of those respondents that likely received the treatment. I provide easy-to-use software in R to implement these suggestions for open-ended manipulation checks.

An Empirical Assessment of the Impact of Access to Credit on Farm Output: A Case Study of Sefwi-Wiawso Municipality Ghana

2019 ◽  
Vol 6 (1) ◽  
pp. 20-33
Author(s):  
David Tanoh Aduhene ◽  
Sylvester Boadu ◽  
Ernest Obeng
Keyword(s):  
Regression Model ◽  
Financial Institutions ◽  
Primary Data ◽  
Easy Access ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Access To Credit ◽  
Agriculture Sector ◽  
Endogenous Switching ◽  
The Impact

The study examined the socio-demographic features of farmers and credit accessibility in the Sefwi-Wiawso Municipality Ghana. It also identifies the sources and factors influencing access to credit in the Sefwi-Wiawso Municipality. Primary data were obtained from 1,200 households and farmers within the Sefwi-Wiawso Municipal. The empirical analysis employed a logistic regression technique, the Tobit model and Endogenous Switching Regression Model (ESRM) to explore the accessibility of credit on productivity in the agriculture sector. The results revealed that age and gender are statistically significant in determining access to credit from both the logit and the endogenous regression models. The endogenous switching regression model further reveals that educational status, land ownership, access to knowledge on credit significantly influences the amount of credit received by a particular farmer within the Sefwi-Wiawso Municipality. These findings have practical implications for the modernizations of the Agriculture sector in Ghana. It is therefore important for various stakeholders to increase financial literacy among farming communities and the financial institutions to increase the credit accessibility by the Agriculture sector. It is therefore recommended that extension services provision, diversification of agriculture production and easy access to credit from financial institutions in the Municipality be established to ensure increased agriculture production.

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