|
主讲人 |
Xu Cheng |
简介 |
<p>This paper provides a new multi-dimensional clustering approach for unobserved heterogeneity in panel data models. Each unit is associated with multiple clusters. For example, a firm can belong to the high productivity group and the low output elasticity group. In contrast, the standard one-dimensional clustering approach would be based on separate groups for each productivity-elasticity pair. Our approach provides substantial gains in estimation accuracy when unobserved features have sparse interactions, e.g., there are only a few firms with high productivity and low output elasticity. We propose an estimator for the unobserved group memberships and the group-specific and common parameters in a nonlinear GMM framework and derive its large sample properties. In particular, we provide the first classification consistency result in a nonlinear GMM setup. We re-evaluate the rise of aggregate markup in De Loecker, Eeckhout, and Unger (2018) by replacing their sector-specific production functions with a cluster-based one. We find that the upward trajectory persists, but the magnitude is less pronounced after accounting for multi-dimensional heterogeneity.</p> |
|
时间 |
2022-12-13 (Tuesday) 10:00-11:30 |
地点 |
Room N302, Econ Bldg, XMU; Zoom Meeting: 89377867510 |
|
主讲人简介 |
<p>Xu Cheng is an associate professor of economics at the University of Pennsylvania, Her research covers a wide range of topics in econometrics, such as identification issues of econometric models, likelihood and moment based estimation and inference, as well as shrinkage estimation. Her research has appeared on<em> Econometrica, Review of Economic Studies, Quantitative Economics, Journal of Econometrics, Econometric Theory, and Journal of Business & Economic Statistics</em>, among others. She currently serves as the Co-editor of <em>Econometric Theory</em>, and an associate editor of<em> Quantitative Economics, Econometrics Journal </em>and <em>Econometrics Review</em>, and was an associate editor of<em> Journal of Econometrics, Econometric Theory</em> and <em>Journal of Business & Economic Statistics</em>.</p> |
期数 |
”邹至庄讲座”青年学者论坛（第44期） |
