題  目: 社會科學研究中的健康問題及其度量

時  間：5月30日 周三 13:30-15:00

地  點：意昂体育3注册B203東森報告廳

主講人👆：Aparajita Dasgupta

講座摘要🔮：

在健康為議題的研究中，關鍵挑戰之一是問卷中健康的度量及該主觀指標的可比性。這裏存在系統性錯誤，由於個體理解和回答存在差異，一個給定的問題個人可能使用不同的參考點，並在自己特定的上下文中解釋問題🍔。怎麽樣糾正跨群體、個體的異質性系統差異呢🤿？Aparajita 將通過自己的研究給大家講述社會科學研究中，如何更好的度量健康，避免系統性誤差差異引發的研究估計偏誤。除了分享學術研究的思想，Aparajita也會跟大家分享留學經驗和學術規劃👩🏿‍🚀。

主講人介紹：

Aparajita Dasgupta🍿，印度阿育王大學助理教授，應用微觀經濟學家，研究專長是在發展經濟學，衛生經濟學和公共政策領域⛔️。她目前的研究考察了早期兒童沖擊對發展中國家的人力資本積累的長期影響⏬👂🏻，探討了在這方面可以發揮的公共政策的作用。近期論文發表在Economic Development and Cultural Change, Review of Development Economics, IZA Journal of Development and Migration等重要SSCI雜誌。

Title: Health Measure in Social Science: Correcting Systematic Measurement Error

Time and Location：May 30^th , Wednesday; 13:30-15:00

Room B203 School of Media and Communication

Presenter: Aparajita Dasgupta, Assistant Professor of Economics in University of Ashoka

Aparajita is an applied micro economist by training and her research expertise are in the area of development economics, health economics and public policy. Her current research examines the long term consequences of early childhood shocks on human capital accumulation in developing country setting, exploring the role of public policies that can play in this regard. She has published in Economic Development and Cultural Change, Review of Development Economics, IZA Journal of Development and Migration.

She may be contacted at aparajita.dasgupta@ashoka.edu.in.

Abstract：this paper studies the pattern of non-random measurement error in self-assessed health responses across population subgroups and examines whether anchoring of vignettes can be used to identify this bias. It uses unique data from the World Health Survey (WHS)-SAGE survey(wave 1) from India, that has self-reported assessments of health linked to anchoring vignettes as well as objective measures like measured anthropometrics and performance tests on a range of health domains. Both estimations using individual fixed effects and anchored-vignettes response reveal strong systematic reporting bias across subgroups. Controlling for a battery of objective health measures, we implicitly test and confirm the validity of the ‘response consistency’ assumption used in vignettes technique. Further analysis using individual fixed effects in a two-stage regression estimation reveals substantial individual reporting bias even after accounting for the usual covariates controlled in a regression.