题  目: 社会科学研究中的健康问题及其度量

时  间：5月30日 周三 13:30-15:00

地  点：太阳集团tyc5997B203东森报告厅

主讲人：Aparajita Dasgupta

讲座摘要：

在健康为议题的研究中，关键挑战之一是问卷中健康的度量及该主观指标的可比性。这里存在系统性错误，由于个体理解和回答存在差异，一个给定的问题个人可能使用不同的参考点，并在自己特定的上下文中解释问题。怎么样纠正跨群体、个体的异质性系统差异呢？Aparajita 将通过自己的研究给大家讲述社会科学研究中，如何更好的度量健康，避免系统性误差差异引发的研究估计偏误。除了分享学术研究的思想，Aparajita也会跟大家分享留学经验和学术规划。

主讲人介绍：

Aparajita Dasgupta，印度阿育王大学助理教授，应用微观经济学家，研究专长是在发展经济学，卫生经济学和公共政策领域。她目前的研究考察了早期儿童冲击对发展中国家的人力资本积累的长期影响，探讨了在这方面可以发挥的公共政策的作用。近期论文发表在Economic Development and Cultural Change, Review of Development Economics, IZA Journal of Development and Migration等重要SSCI杂志。

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.