Estimation in linear models with clustered data (joint work with Mikkel Solvsten and Baiyun Jing)
Anna Mikusheva, Massachusetts Institute of Technology
We study linear regression models with clustered data, high-dimensional controls, and a complicated structure of exclusion restrictions. We propose a correctly centered internal IV estimator that accommodates a variety of exclusion restrictions and permits within-cluster dependence. The estimator has a simple leave-out interpretation and remains computationally tractable. We derive a central limit theorem for its quadratic form and propose a robust variance estimator. We also develop inference methods that remain valid under weak identification. Our framework extends classical dynamic panel methods to more general clustered settings. An empirical application of a large-scale fiscal intervention in rural Kenya with spatial interference illustrates the approach.
| Building: | North Quad |
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| Website: | |
| Event Type: | Workshop / Seminar |
| Tags: | Econometrics, Economics, seminar |
| Source: | Happening @ Michigan from Department of Economics, Econometrics, Department of Economics Seminars |
