Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 23 for “"average treatment effects"”.
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Essays on average treatment effects
… consists of three essays on estimating average treatment effects (ATE) under counterfactual framework. In Chapter 1, I compare the performances of single-step and two-step estimators for estimating the ATE in a linear model when treatment assignment depends on unobservables. Recent …
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Causal Inference Beyond Estimating Average Treatment Effects
… and control groups that is often called the average treatment effect (ATE), and rely on identifying assumptions to allow causal interpretation. However, more specific treatment effects beyond the ATE can be estimated under the same assumptions. For example, instead of estimating the mean of …
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Essays on Optimal Transport Theory and Causal Inference: A Theoretical and Empirical Approach
… The first chapter explores identifying average treatment effects for the treated in the region where the covariate distributions across treatment and control groups have non-overlap support. We make a natural domain shift assumption for the non-overlap region based on the optimal …
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Essays On Peer Effects And Network Econometrics
… dissertation proposes new estimators of program treatment effects in the presence of spillovers, a situation where one person's treatment can affect another's outcome.The first chapter focuses on a setting where treatment decisions depend on observables and there are spillovers from friends in a …
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Human-machine teaming for intelligent demand planning
… method, this research empirically analyzes the average treatment effects of three different human-machine decision-making structures: Full human to AI delegation, Hybrid AI-Human with adequate human intervention, and Hybrid AI-Human with all steps of demand planning overrides.
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The socioeconomic impacts of the Superfund program
The student, Alexander Stevens, submitted this Dissertation for approval on 2019-07-08 at 10:48.
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On Cluster Robust Models
… considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects …
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Causal inference for complex data: randomization inference for treatment effect heterogeneity, network outcomes, and subgroup specific effects
… the total of the difference of outcomes if the treatment group had instead been assigned to the control condition, to count and continuous data using a fast approximation algorithm. Alternative approaches are limited to binary data, require asymptotic approximations, or are computationally …
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Where trees grow, assets grow: applying spatial matching to evaluate agroforestry’s household welfare impacts in Kenya
… implementing NGO are used as the indicator of treatment exposure to calculate intention to treat and local average treatment effects of the agroforestry program. The agroforestry program is found to result in modest but significant gains in asset wealth and expenditure. The pre-survey spatial …
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Words Can Change Worlds: An impact evaluation of Shine Literacy
… impact evaluation by estimating the treatment effect of Shine Literacy via difference-in-differences and propensity score matching. By using the available data which included (1) Shine’s diagnostic test scores, (2) attendance data and (3) Grade 3 Systemic test score data obtained from …
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Causal Inference with Measurement Errors: with Applications to Experimental and Observational Studies
… inability of investigators to fully observe the treatment take-up status of a respondent in an experiment is equivalent to a measurement error for the treatment indicator. Such errors prevent researchers from a correct estimation for average treatment effects. The new framework considers whether …
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Power influence in horizontal collaboration relationships
… estimator method (AIPW) is used to analyze the average treatment effects empirically. A set of 16 experiments were conducted to understand the influence of the different asymmetries in the horizontal collaboration performance. The statistically significant results show that power asymmetries …
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Three Essays on Causal Inference With Model Averaging
… derivation of a model-averaging-based average treatment effect estimator. The second essay provides comparison of predictability of treated counterfactual outcome between model averaging and other methods. The third essay is an empirical study evaluating the economic impact of Ukraine's …
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Essays in Empirical Development Economics
… development economics. Chapter 1 focuses on the effects of civil wars on the welfare of individuals. I use a unique data set that contains information on war casualties of the 1992-1995 Bosnian War, and exploit the variation in war intensity and birth cohorts of children, to identify the effects …
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Education Policy Factors Contributing to Special Education Identification
… comprise this dissertation aim to analyze the effects that educational policies have on special education identification and subsequent enrollment. Specifically, the studies cover the special education finance, school accountability, and school choice policies. </p> <p>The special education …
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Language Models as Opinion Models: Techniques and Applications
… to forecast persuasion and predict heterogeneous treatment effects (HTEs). Study I — Media tempo and tone. Using 518,000 hours of U.S. talk-radio broadcasts and 26.6 million tweets from elite and mass users, we show that Twitter discourse (i) moves faster at both take-off and fade-out stages of a …
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Three essays on Native American economic development
… investment was not productive. Behind the poor average performance lies much cross-sectional variation which I explore using models from development theory and political economy. In a multi-sector framework, local business ventures based on the traditional economy earned positive returns, but …
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Essays on semi-/non-parametric methods in econometrics
… on the individual structural parameters and the average treatment effects. Numerical studies suggest the sensitivity of parametric specification and the robustness of semiparametric estimation. This paper also shows that the absence of excluded instruments may result in the failure of …
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Machine Learning for Causal Estimation
… novel ML-based methods for estimating causal effects, with a focus on flexibility, robustness, and valid statistical inference. The first chapter addresses the challenge of regularization and model selection bias that arises when ML is used to estimate nuisance parameters. We propose a new …
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Topics in conditional causal inference
… and precise. For example, one might ask if the treatment is effective at a particular time point, or if the treatment is effective for a particular individual. To answer many questions of this kind, this thesis concerns conditional causal inference, generally referring to techniques of …
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