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Essays in Econometrics.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Essays in Econometrics./
作者:	Ober-Reynolds, Daniel Steven.
面頁冊數:	1 online resource (254 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:	Dissertations Abstracts International85-11B.
標題:	Public policy. -
電子資源:	click for full text (PQDT)
ISBN:	9798382774763

Essays in Econometrics.
Ober-Reynolds, Daniel Steven.

Essays in Econometrics. - 1 online resource (254 pages)

Source: Dissertations Abstracts International, Volume: 85-11, Section: B.

Thesis (Ph.D.)--University of California, Los Angeles, 2024.

Includes bibliographical references

This dissertation contains two chapters. The first chapter studies causal parameters that depend on a moment of the joint distribution of potential outcomes. Such parameters are especially relevant in policy evaluation settings, where noncompliance is common and accommodated through the model of Imbens & Angrist (1994). The sharp identified set for these parameters is an interval with endpoints characterized by the value of optimal transport problems. Sample analogue estimators are proposed based on the dual problem of optimal transport. These estimators are √ n-consistent and converge in distribution under mild assumptions. Inference procedures based on the bootstrap are straightforward and computationally convenient. The ideas and estimators are demonstrated in an application revisiting the National Supported Work Demonstration job training program. Estimates suggest that workers who would see below average earnings without treatment tend to see above average benefits from treatment.The second chapter proposes a methodology for studying the robustness of results drawn from incomplete datasets. Selection is measured as the squared Hellinger divergence between the distributions of complete and incomplete observations, which has a natural interpretation. The breakdown point is defined as the minimal amount of selection needed to overturn a given result. Reporting point estimates and lower confidence intervals of the breakdown point is a simple, concise way to communicate a result's robustness. An estimator of the breakdown point of results drawn from GMM models is proposed and shown √ n-consistent and asymptotically normal under mild assumptions. Lower confidence intervals of the breakdown point are simple to construct. The chapter concludes with a simulation study illustrating the good finite sample performance of the procedure.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382774763Subjects--Topical Terms:

1002398
Public policy.
Subjects--Index Terms:

EconometricsIndex Terms--Genre/Form:

554714
Electronic books.

Essays in Econometrics.
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504 $a Includes bibliographical references
520 $a This dissertation contains two chapters. The first chapter studies causal parameters that depend on a moment of the joint distribution of potential outcomes. Such parameters are especially relevant in policy evaluation settings, where noncompliance is common and accommodated through the model of Imbens & Angrist (1994). The sharp identified set for these parameters is an interval with endpoints characterized by the value of optimal transport problems. Sample analogue estimators are proposed based on the dual problem of optimal transport. These estimators are √ n-consistent and converge in distribution under mild assumptions. Inference procedures based on the bootstrap are straightforward and computationally convenient. The ideas and estimators are demonstrated in an application revisiting the National Supported Work Demonstration job training program. Estimates suggest that workers who would see below average earnings without treatment tend to see above average benefits from treatment.The second chapter proposes a methodology for studying the robustness of results drawn from incomplete datasets. Selection is measured as the squared Hellinger divergence between the distributions of complete and incomplete observations, which has a natural interpretation. The breakdown point is defined as the minimal amount of selection needed to overturn a given result. Reporting point estimates and lower confidence intervals of the breakdown point is a simple, concise way to communicate a result's robustness. An estimator of the breakdown point of results drawn from GMM models is proposed and shown √ n-consistent and asymptotically normal under mild assumptions. Lower confidence intervals of the breakdown point are simple to construct. The chapter concludes with a simulation study illustrating the good finite sample performance of the procedure.
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