不可分面板数据下结构与因果效应的线性估计
发布时间：2026-08-13
7月
08
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时间和日期
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2026-07-08 (星期三) 15:30 下午
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17:00 下午
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| 标题 | 不可分面板数据下结构与因果效应的线性估计 |
| 日期和时间 |
2026年7月8日（周三） |
| 地点 | 综合教学楼D904会议室 |
| 主讲人 |
Whitney K. Newey |
| 摘要 | This paper develops linear estimators for structural and causal parameters in nonparametric, non-separable models using panel data. These models incorporate unobserved, time-varying, individual heterogeneity, which may be correlated with the regressors. Estimation is based on an approximation of non-separable functions by linear sieve specifications with individual-specific parameters. Effects of interest are estimated by a bias corrected average of individual ridge regressions. We demonstrate how this approach can be applied to estimate causal effects, counterfactual consumer welfare, and averages of individual taxable income elasticities. We show that the proposed estimator has an empirical Bayes interpretation and possesses a number of other useful properties. We formulate large-T asymptotics that can accommodate discrete regressors and which bypass partial identification in this case. We employ the methods to estimate average equivalent variation and deadweight loss for potential price increases using data on grocery purchases. |
| 主讲人简介 |
Whitney K. Newey现任麻省理工学院经济学福特讲席教授，是2026年经济学欧文·普莱因·内默斯奖（Erwin Plein Nemmers Prize in Economics）获得者。他同时担任美国经济协会杰出会士、美国艺术与科学院院士，以及计量经济学会会士。Newey教授在诸多计量经济学领域做出重要贡献，包括方差估计量、非参数联立方程、动态与非线性面板估计、依赖于未知函数的半参数估计、一般异质性条件下的消费者剩余估计，以及去偏机器学习等。相关成果已发表于Econometrica、Journal of Political Economy、The Review of Economic Studies、Journal of the American Statistical Association、Journal of Econometrics等国际顶尖学术期刊。他目前的研究方向包括：去偏机器学习、不可分面板模型的线性估计，以及面板数据中的经济需求估计。 |
