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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:	Chen, Jiafeng.
面頁冊數:	1 online resource (288 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Contained By:	Dissertations Abstracts International85-12B.
標題:	Mathematics. -
電子資源:	click for full text (PQDT)
ISBN:	9798382786216

Essays in Econometrics.
Chen, Jiafeng.

Essays in Econometrics. - 1 online resource (288 pages)

Source: Dissertations Abstracts International, Volume: 85-12, Section: B.

Thesis (Ph.D.)--Harvard University, 2024.

Includes bibliographical references

This dissertation consists of three essays in econometrics. A common throughline is decision theory, defined here broadly as the formal considerations justifying, informing, or undermining choices of statistical procedures.The first chapter proposes a new interpretation of synthetic control methods as instances of online convex optimization algorithms. Viewed in a certain way, synthetic control methods implement an algorithm called Follow-The-Leader. Mathematical guarantees of Follow-The-Leader then translate into new guarantees for synthetic control. Specifically, over long time horizons, synthetic control methods predict almost as well as the best weighted average of untreated units chosen ex post. The second chapter proposes new empirical Bayes methods that improve statistical decision-making. It shows that conventional empirical Bayes methods embed an assumption called prior independence; this assumption frequently fails to hold; and imposing this assumption incorrectly can harm the performance of standard empirical Bayes methods. Motivated by these observations, the chapter proposes new empirical Bayes methods and proves some new decision-theoretic guarantees.The third chapter is a paper co-authored with Jonathan Roth. Empirical researchers frequently want to estimate some causal effect in terms of the log transformation of their outcome variables. However, when the outcome variable can take the value zero, its log is not well-defined. In such situations, empirical researchers often resort to certain "logarithm-like" transformations that are defined at zero and continue to interpret results as approximate log or percentage effects. We show that such interpretations are inappropriate. We also show that there exists no estimand satisfying certain desirable properties simultaneously, and one has to forgo at least one of these properties.

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

Mode of access: World Wide Web

ISBN: 9798382786216Subjects--Topical Terms:

527692
Mathematics.
Subjects--Index Terms:

Statistical proceduresIndex Terms--Genre/Form:

554714
Electronic books.

Essays in Econometrics.
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