Evaluating the distributional impacts of drought-tolerant maize varieties on productivity and welfare outcomes: an instrumental variable quantile treatment effects approach

2019 ◽  
Vol 12 (10) ◽  
pp. 865-875 ◽  
Author(s):  
Kehinde Oluseyi Olagunju ◽  
Adebayo Isaiah Ogunniyi ◽  
Bola Amoke Awotide ◽  
Adewale Henry Adenuga ◽  
Waheed Mobolaji Ashagidigbi
Keyword(s):  
Instrumental Variable ◽  
Treatment Effects ◽  
Drought Tolerant ◽  
Quantile Treatment Effects ◽  
Maize Varieties ◽  
Distributional Impacts

Local Average and Quantile Treatment Effects Under Endogeneity: A Review

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Martin Huber ◽  
Kaspar Wüthrich
Keyword(s):  
Instrumental Variable ◽  
Treatment Effects ◽  
Randomized Experiments ◽  
Quantile Treatment Effects ◽  
Indirect Treatment ◽  
Treatment Effect Models ◽  
Multiple Treatments ◽  
The Relationship ◽  
Local Average ◽  
Heterogeneous Treatment Effect

Abstract This paper provides a review of methodological advancements in the evaluation of heterogeneous treatment effect models based on instrumental variable (IV) methods. We focus on models that achieve identification by assuming monotonicity of the treatment in the IV and analyze local average and quantile treatment effects for the subpopulation of compliers. We start with a comprehensive discussion of the binary treatment and binary IV case as for instance relevant in randomized experiments with imperfect compliance. We then review extensions to identification and estimation with covariates, multi-valued and multiple treatments and instruments, outcome attrition and measurement error, and the identification of direct and indirect treatment effects, among others. We also discuss testable implications and possible relaxations of the IV assumptions, approaches to extrapolate from local to global treatment effects, and the relationship to other IV approaches.

Quantile Treatment Effects in the Presence of Covariates

2020 ◽  
Vol 102 (5) ◽  
pp. 994-1005 ◽  
Author(s):  
David Powell
Keyword(s):  
Quantile Regression ◽  
Instrumental Variable ◽  
Treatment Effects ◽  
Simultaneous Equations ◽  
Quantile Treatment Effects ◽  
Simultaneous Equations Models ◽  
Special Cases ◽  
Instrumental Variable Quantile Regression

This paper proposes a method to estimate unconditional quantile treatment effects (QTEs) given one or more treatment variables, which may be discrete or continuous, even when it is necessary to condition on covariates. The estimator, generalized quantile regression (GQR), is developed in an instrumental variable framework for generality to permit estimation of unconditional QTEs for endogenous policy variables, but it is also applicable in the conditionally exogenous case. The framework includes simultaneous equations models with nonadditive disturbances, which are functions of both unobserved and observed factors. Quantile regression and instrumental variable quantile regression are special cases of GQR and available in this framework.

scholarly journals Impact of adoption of drought-tolerant maize varieties on total maize production in south Eastern Zimbabwe

2017 ◽  
Vol 11 (1) ◽  
pp. 35-46 ◽  
Author(s):  
Rodney Witman Lunduka ◽  
Kumbirai Ivyne Mateva ◽  
Cosmos Magorokosho ◽  
Pepukai Manjeru
Keyword(s):  
Maize Production ◽  
South Eastern ◽  
Drought Tolerant ◽  
Maize Varieties

Bounding Treatment Effects with Contaminated and Censored Data: Assessing the Impact of Early Childbearing on Children

2005 ◽  
Vol 5 (1) ◽  
Author(s):  
Charles H Mullin
Keyword(s):  
Censored Data ◽  
Treatment Effect ◽  
Instrumental Variable ◽  
Treatment Effects ◽  
Child Outcomes ◽  
Well Being ◽  
Teenage Mothers ◽  
Age At First Birth ◽  
First Birth ◽  
The Impact

AbstractEmpirical researchers commonly invoke instrumental variable (IV) assumptions to identify treatment effects. This paper considers what can be learned under two specific violations of those assumptions: contaminated and corrupted data. Either of these violations prevents point identification, but sharp bounds of the treatment effect remain feasible. In an applied example, random miscarriages are an IV for women’s age at first birth. However, the inability to separate random miscarriages from behaviorally induced miscarriages (those caused by smoking and drinking) results in a contaminated sample. Furthermore, censored child outcomes produce a corrupted sample. Despite these limitations, the bounds demonstrate that delaying the age at first birth for the current population of non-black teenage mothers reduces their first-born child’s well-being.

Estimating Treatment Effects in the Presence of Noncompliance and Nonresponse: The Generalized Endogenous Treatment Model

2011 ◽  
Vol 19 (2) ◽  
pp. 205-226 ◽  
Author(s):  
Kevin M. Esterling ◽  
Michael A. Neblo ◽  
David M. J. Lazer
Keyword(s):  
Treatment Effect ◽  
Instrumental Variable ◽  
Treatment Effects ◽  
Mean Squared Error ◽  
Principal Stratification ◽  
Squared Error ◽  
Treatment Effect Heterogeneity ◽  
Causal Treatment ◽  
Effect Heterogeneity ◽  
And Control

If ignored, noncompliance with a treatment or nonresponse on outcome measures can bias estimates of treatment effects in a randomized experiment. To identify and estimate causal treatment effects in the case where compliance and response depend on unobservables, we propose the parametric generalized endogenous treatment (GET) model. GET incorporates behavioral responses within an experiment to measure each subject's latent compliance type and identifies causal effects via principal stratification. Using simulation methods and an application to field experimental data, we show GET has a dramatically lower mean squared error for treatment effect estimates than existing approaches to principal stratification that impute, rather than measure, compliance type. In addition, we show that GET allows one to relax and test the instrumental variable exclusion restriction assumption, to test for the presence of treatment effect heterogeneity across a range of compliance types, and to test for treatment ignorability when treatment and control samples are balanced on observable covariates.

scholarly journals PENGEMBANGAN USAHA BENIH JAGUNG TAHAN KERING

2018 ◽  
Vol 17 (1) ◽  
pp. 70
Author(s):  
S.M. Sarwadana ◽  
B.R.T. Putri ◽  
K.K. Dinata
Keyword(s):  
Raw Materials ◽  
Science And Technology ◽  
Raw Material ◽  
Maize Seed ◽  
Seed Corn ◽  
Entrepreneurial Spirit ◽  
Drought Tolerant ◽  
Production Processes ◽  
Maize Varieties ◽  
Made In

Activities of science and technology for innovation and creativity campus aims are: (1) thecommercialization of science and technology campus creativity as a source of financing for the developmentof institutions; (2) stimulate the entrepreneurial spirit among beings campus, and (3) help people get seeds ofdrought-tolerant maize varieties. Methods of execution include the business aspects of the planned businessactivities consist of: provision of raw materials, production processes, management, marketing, humanresources, facilities, and financial. The raw material is obtained from units of science and technology fornovation and creativity campus and through partnerships with farmers' seed corn. The production processstarted from seed, sorting, and packaging. Marketing is done directly, partnerships with local governmentsand konsiniasi with kiosk / farm shop. Results show that the activities of science and technology unit forinnovation and creativity campus drought-tolerant maize seed has gone well characterized by supportinfrastructure adequate maize seed production; IbIKK unit operates under the management of PSAgroecotechnology Faculty of Agriculture, University of Udayana; Of investment made in 2014 amountingto Rp. 39,550,000; Result of sales corn seeds turnover in 2014 amounted to 400 kg (Rp. 12 million); and netcash flow amounted to 17,672,400.

scholarly journals Evaluation of saline-alkali and drought tolerance in maize varieties

2019 ◽  
Vol 48 (4) ◽  
pp. 1047-1063
Author(s):  
Huili Zhang ◽  
Chuang Yuan ◽  
Guillian Mao ◽  
Xue Gao ◽  
Liu Zhu ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Drought Stress ◽  
Drought Tolerance ◽  
Growth And Development ◽  
Stress Condition ◽  
Stress Factors ◽  
Alkali Stress ◽  
Yield Attributes ◽  
Drought Tolerant ◽  
Maize Varieties

Saline-alkali and drought stresses are one of the abiotic stress factors that limit the normal growth and development of plants. In this work, various agronomic indexes including growth physiology and yield attributes were studied under saline-alkali and drought stress treatments. It was found that the limit of plant growth and development caused by drought stress is much higher than that of saline-alkali stress (p < 0.01). Based on the comprehensive evaluation value (D value), under saline-alkali stress condition, 36 maize varieties could be divided into four groups by cluster analysis (CA): High saline-alkali tolerance (3 varieties), medium saline-alkali tolerant(10 varieties), saline-alkali sensitive (19 varieties), high saline-alkali sensitive (4 varieties). In drought stress condition, 36 maize varieties could be divided into five groups by cluster analysis (CA): High drought-tolerance (2 varieties), medium drought-tolerant (14 varieties), low drought-tolerant (15 varieties), drought-sensitive (4 varieties), high drought-sensitive (1 variety). Therefore, this study provides a comprehensive screening of maize varieties under saline-alkali and drought stresses.

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