scholarly journals Combining parenthood and work: transmission channels and heterogeneous returns to early public childcare

2021 ◽  
Author(s):  
Eric Schuss ◽  
Mohammed Azaouagh
Keyword(s):  
Treatment Effect ◽  
Average Treatment Effect ◽  
Individual Treatment ◽  
Full Time ◽  
Maternal Labor Supply ◽  
Transmission Channels ◽  
Average Treatment ◽  
Part Time ◽  
Effect Heterogeneity ◽  
Marginal Returns

AbstractWe exploit local and temporal variation in the availability of public childcare for children under the age of three that induces exogenous variation in childcare attendance. We find a weak, positive average treatment effect (ATE) on maternal labor supply. The estimation of the average treatment effect is interesting – however, possibly masking important effect heterogeneity. Examining selection behavior and estimating marginal treatment effects along the distribution of observables and unobservables that drive individual treatment decisions reveal transmission channels and uncover substantial heterogeneity in marginal returns from public childcare reforms. By estimating marginal returns, we detect reverse selection on gains at the intensive margin, whereas a substantial share (40 percent) of mothers with median desire to public childcare react with increased probability to work full time. Thus, if the supply of public childcare is expanded from a modest to a more generous level of coverage, those with average resistance towards early public childcare do gain. At the extensive margin, positive selection on gains is found; however, only a small fraction of mothers with the lowest distaste for early public childcare shift from non-employment to part-time jobs.

scholarly journals On the treatment effect heterogeneity of antidepressants in major depression. A Bayesian meta-analysis

2020 ◽  
Author(s):  
Constantin Volkmann ◽  
Alexander Volkmann ◽  
Christian A. Müller
Keyword(s):  
Major Depression ◽  
Random Effects ◽  
Treatment Effect ◽  
Clinical Relevance ◽  
Meta Analysis ◽  
Placebo Response ◽  
Average Treatment Effect ◽  
Average Treatment ◽  
Treatment Effect Heterogeneity ◽  
Effect Heterogeneity

AbstractBackgroundThe average treatment effect of antidepressants in major depression was found to be about 2 points on the 17-item Hamilton Depression Rating Scale, which lies below clinical relevance. Here, we searched for evidence of a relevant treatment effect heterogeneity that could justify the usage of antidepressants despite their low average treatment effect.MethodsBayesian meta-analysis of 169 randomized, controlled trials including 58,687 patients. We considered the effect sizes log variability ratio (lnVR) and log coefficient of variation ratio (lnCVR) to analyze the difference in variability of active and placebo response. We used Bayesian random-effects meta-analyses (REMA) for lnVR and lnCVR and fitted a random-effects meta-regression (REMR) model to estimate the treatment effect variability between antidepressants and placebo.ResultsThe variability ratio was found to be very close to 1 in the best fitting models (REMR: 95% HPD [0.98, 1.02], REMA: 95% HPD [1.00, 1.02]). The between-study variance τ2 under the REMA was found to be low (95% HPD [0.00, 0.00]). Simulations showed that a large treatment effect heterogeneity is only compatible with the data if a strong correlation between placebo response and individual treatment effect is assumed.ConclusionsThe published data from RCTs on antidepressants for the treatment of major depression is compatible with a near-constant treatment effect. Although it is impossible to rule out a substantial treatment effect heterogeneity, its existence seems rather unlikely. Since the average treatment effect of antidepressants falls short of clinical relevance, the current prescribing practice should be re-evaluated.

scholarly journals Generalizability of heterogeneous treatment effect estimates across samples

2018 ◽  
Vol 115 (49) ◽  
pp. 12441-12446 ◽  
Author(s):  
Alexander Coppock ◽  
Thomas J. Leeper ◽  
Kevin J. Mullinix
Keyword(s):  
Treatment Effect ◽  
Treatment Effects ◽  
Average Treatment Effect ◽  
Partial Explanation ◽  
Convenience Sample ◽  
Conditional Average ◽  
Replication Studies ◽  
Average Treatment ◽  
Average Treatment Effects ◽  
Effect Heterogeneity

The extent to which survey experiments conducted with nonrepresentative convenience samples are generalizable to target populations depends critically on the degree of treatment effect heterogeneity. Recent inquiries have found a strong correspondence between sample average treatment effects estimated in nationally representative experiments and in replication studies conducted with convenience samples. We consider here two possible explanations: low levels of effect heterogeneity or high levels of effect heterogeneity that are unrelated to selection into the convenience sample. We analyze subgroup conditional average treatment effects using 27 original–replication study pairs (encompassing 101,745 individual survey responses) to assess the extent to which subgroup effect estimates generalize. While there are exceptions, the overwhelming pattern that emerges is one of treatment effect homogeneity, providing a partial explanation for strong correspondence across both unconditional and conditional average treatment effect estimates.

scholarly journals On the treatment effect heterogeneity of antidepressants in major depression: A Bayesian meta-analysis and simulation study

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241497
Author(s):  
Constantin Volkmann ◽  
Alexander Volkmann ◽  
Christian A. Müller
Keyword(s):  
Major Depression ◽  
Random Effects ◽  
Treatment Effect ◽  
Clinical Relevance ◽  
Meta Analysis ◽  
Placebo Response ◽  
Average Treatment Effect ◽  
Average Treatment ◽  
Treatment Effect Heterogeneity ◽  
Effect Heterogeneity

Background The average treatment effect of antidepressants in major depression was found to be about 2 points on the 17-item Hamilton Depression Rating Scale, which lies below clinical relevance. Here, we searched for evidence of a relevant treatment effect heterogeneity that could justify the usage of antidepressants despite their low average treatment effect. Methods Bayesian meta-analysis of 169 randomized, controlled trials including 58,687 patients. We considered the effect sizes log variability ratio (lnVR) and log coefficient of variation ratio (lnCVR) to analyze the difference in variability of active and placebo response. We used Bayesian random-effects meta-analyses (REMA) for lnVR and lnCVR and fitted a random-effects meta-regression (REMR) model to estimate the treatment effect variability between antidepressants and placebo. Results The variability ratio was found to be very close to 1 in the best fitting models (REMR: 95% highest density interval (HDI) [0.98, 1.02], REMA: 95% HDI [1.00, 1.02]). The between-study standard deviation τ under the REMA with respect to lnVR was found to be low (95% HDI [0.00, 0.02]). Simulations showed that a large treatment effect heterogeneity is only compatible with the data if a strong correlation between placebo response and individual treatment effect is assumed. Conclusions The published data from RCTs on antidepressants for the treatment of major depression is compatible with a near-constant treatment effect. Although it is impossible to rule out a substantial treatment effect heterogeneity, its existence seems rather unlikely. Since the average treatment effect of antidepressants falls short of clinical relevance, the current prescribing practice should be re-evaluated.

scholarly journals Evaluación de impacto académico y social en egresados universitarios

2019 ◽  
Vol 30 (3) ◽  
pp. 695-712
Author(s):  
Gabriel González ◽  
Luisa Díez-Echavarría ◽  
Elkin Zapa ◽  
Danilo Eusse
Keyword(s):  
Treatment Effect ◽  
Average Treatment Effect ◽  
Educación Superior ◽  
Educacion Superior ◽  
Average Treatment

Las instituciones de educación superior deben formar a sus estudiantes según requerimientos del contexto en que se desenvuelven, ya que, sobre la base de su desempeño, es donde se medirá si las políticas de desarrollo socioeconómico son efectivas. Para lograrlo, es necesario identificar el impacto de esa educación en sus egresados, y hacer los ajustes necesarios que generen mejora continua. El objetivo de este artículo es estimar el impacto académico y social de egresados del Instituto Tecnológico Metropolitano – Medellín, a través de un análisis multivariado y la estimación del modelo Average Treatment Effect (ATE). Se encontró que la educación ofrecida a esta población ha generado un impacto académico, asociado a los estudios de actualización, y dos impactos sociales, asociados a la situación laboral y al nivel de ingresos percibidos por los egresados. Se recomienda usar esta metodología en otras instituciones, ya que suele arrojar resultados más informativos y precisos que los estudios tradicionales de caracterización, y se puede medir el efecto de cualquier estrategia.

The Effect of Extension Services and Credit on Agricultural Production in Bolivia, Peru, and Colombia

2021 ◽  
Author(s):  
Mateus C. R. Neves ◽  
Felipe De Figueiredo Silva ◽  
Carlos Otávio Freitas
Keyword(s):  
Travel Time ◽  
Treatment Effect ◽  
Agricultural Production ◽  
Treatment Effects ◽  
Geographic Information ◽  
Average Treatment Effect ◽  
Extension Services ◽  
Average Treatment ◽  
Andean Countries ◽  
Average Treatment Effects

In this paper we estimate the average treatment effect from access to extension services and credit on agricultural production in selected Andean countries (Bolivia, Peru, and Colombia). More specifically, we want to identify the effect of accessibility, here represented as travel time to the nearest area with 1,500 or more inhabitants per square kilometer or at least 50,000 inhabitants, on the likelihood of accessing extension and credit. To estimate the treatment effect and identify the effect of accessibility on these variables, we use data from the Colombian and Bolivian Agricultural Censuses of 2013 and 2014, respectively; a national agricultural survey from 2017 for Peru; and geographic information on travel time. We find that the average treatment effect for extension is higher compared to that of credit for farms in Bolivia and Peru, and lower for Colombia. The average treatment effects of extension and credit for Peruvian farms are $2,387.45 and $3,583.42 respectively. The average treatment effect for extension and credit are $941.92 and $668.69, respectively, while in Colombia are $1,365.98 and $1,192.51, respectively. We also find that accessibility and the likelihood of accessing these services are nonlinearly related. Results indicate that higher likelihood is associated with lower travel time, especially in the analysis of credit.

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