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Essays on Design of Applied Economics Studies.
Essays on Design of Applied Economics Studies.

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자료유형  
 학위논문
Control Number  
0017162247
International Standard Book Number  
9798383173183
Dewey Decimal Classification Number  
330.015
Main Entry-Personal Name  
Bagilet, Vincent.
Publication, Distribution, etc. (Imprint  
[S.l.] : Columbia University., 2024
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2024
Physical Description  
151 p.
General Note  
Source: Dissertations Abstracts International, Volume: 85-12, Section: A.
General Note  
Advisor: Shrader, Jeffrey G.
Dissertation Note  
Thesis (Ph.D.)--Columbia University, 2024.
Summary, Etc.  
요약Applied economics studies target effects that can be relatively small. This dissertation delves into some statistical obstacles to the accurate estimation of such effects, with a particular focus on the concepts of statistical power and exaggeration-imprecise studies tend to produce inflated estimates of the effect of interest. It explores implications of low power and exaggeration that are specific to applied economics studies and their design. Through the example of studies on the acute health effects of air pollution, the first chapter identifies tangible drivers of exaggeration that extend beyond small effects and a limited sample size. This analysis uncovers an overarching mechanism, studied in Chapter 2, that induces exaggeration when using causal identification strategies. This subsequent chapter emphasizes that causal approaches only focus on a subset of the variation-the exogenous part-reducing the precision of the study and increasing risks of exaggeration. The final chapter further broadens the discussion to analyze design choices in light of the multiple goals of causal inference studies; these studies aim not only to identify an average effect but also differentiated effects across subgroups, as well as producing insights that extend beyond the population considered. Overall, this dissertation underlines the manifold implications of design choices on non-experimental economic studies, with the aim of contributing to more accurate estimations of effects to better inform policymaking.
Index Term-Uncontrolled  
Applied economics
Index Term-Uncontrolled  
Causal inference
Index Term-Uncontrolled  
Empirical design
Index Term-Uncontrolled  
Statistical power
Added Entry-Corporate Name  
Columbia University Sustainable Development
Host Item Entry  
Dissertations Abstracts International. 85-12A.
Electronic Location and Access  
로그인을 한후 보실 수 있는 자료입니다.
Control Number  
joongbu:657908

MARC

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■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a330.015
■1001  ▼aBagilet,  Vincent.
■24510▼aEssays  on  Design  of  Applied  Economics  Studies.
■260    ▼a[S.l.]▼bColumbia  University.  ▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a151  p.
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  85-12,  Section:  A.
■500    ▼aAdvisor:  Shrader,  Jeffrey  G.
■5021  ▼aThesis  (Ph.D.)--Columbia  University,  2024.
■520    ▼aApplied  economics  studies  target  effects  that  can  be  relatively  small.  This  dissertation  delves  into  some  statistical  obstacles  to  the  accurate  estimation  of  such  effects,  with  a  particular  focus  on  the  concepts  of  statistical  power  and  exaggeration-imprecise  studies  tend  to  produce  inflated  estimates  of  the  effect  of  interest.  It  explores  implications  of  low  power  and  exaggeration  that  are  specific  to  applied  economics  studies  and  their  design.  Through  the  example  of  studies  on  the  acute  health  effects  of  air  pollution,  the  first  chapter  identifies  tangible  drivers  of  exaggeration  that  extend  beyond  small  effects  and  a  limited  sample  size.  This  analysis  uncovers  an  overarching  mechanism,  studied  in  Chapter  2,  that  induces  exaggeration  when  using  causal  identification  strategies.  This  subsequent  chapter  emphasizes  that  causal  approaches  only  focus  on  a  subset  of  the  variation-the  exogenous  part-reducing  the  precision  of  the  study  and  increasing  risks  of  exaggeration.  The  final  chapter  further  broadens  the  discussion  to  analyze  design  choices  in  light  of  the  multiple  goals  of  causal  inference  studies;  these  studies  aim  not  only  to  identify  an  average  effect  but  also  differentiated  effects  across  subgroups,  as  well  as  producing  insights  that  extend  beyond  the  population  considered.  Overall,  this  dissertation  underlines  the  manifold  implications  of  design  choices  on  non-experimental  economic  studies,  with  the  aim  of  contributing  to  more  accurate  estimations  of  effects  to  better  inform  policymaking.
■590    ▼aSchool  code:  0054.
■653    ▼aApplied  economics
■653    ▼aCausal  inference
■653    ▼aEmpirical  design
■653    ▼aStatistical  power
■690    ▼a0501
■690    ▼a0438
■690    ▼a0511
■71020▼aColumbia  University▼bSustainable  Development.
■7730  ▼tDissertations  Abstracts  International▼g85-12A.
■790    ▼a0054
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17162247▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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