Kirill Borusyak
Biographic Data
| ID | 2127739 |
|---|---|
| NAME | Kirill Borusyak |
| GIVEN NAMES | Kirill |
| FAMILY NAME | Borusyak |
| SIGNATURE | BORUSYAK K |
| AFFILIATIONS | Kirill Borusyak is Assistant Professor of Agricultural and Resource Economics, University of California Berkeley, Berkeley, California. |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 3 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
A Practical Guide to Shift-Share Instruments
A recent econometric literature shows two distinct paths for identification with shift-share instruments, leveraging either many exogenous shifts or exogenous shares. We present the core logic of both paths and practical takeaways via simple checklists. A variety of empirical settings illustrate key points
Revisiting Event-Study Designs
We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects. We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent strong restrictions on treatment-effect homogeneity. We then derive the efficient estimator addressing this challenge, which takes an intuitive “imputation” form when treatment-effect heterogeneity is un…
Quasi-Experimental Shift-Share Research Designs
Many studies use shift-share (or “Bartik”) instruments, which average a set of shocks with exposure share weights. We provide a new econometric framework for shift-share instrumental variable (SSIV) regressions in which identification follows from the quasi-random assignment of shocks, while exposure shares are allowed to be endogenous. The framework is motivated by an equivalence result: the orthogonality between a shift-share instrument and an …
A Practical Guide to Shift-Share Instruments
A recent econometric literature shows two distinct paths for identification with shift-share instruments, leveraging either many exogenous shifts or exogenous shares. We present the core logic of both paths and practical takeaways via simple checklists. A variety of empirical settings illustrate key points
Quasi-Experimental Shift-Share Research Designs
Many studies use shift-share (or “Bartik”) instruments, which average a set of shocks with exposure share weights. We provide a new econometric framework for shift-share instrumental variable (SSIV) regressions in which identification follows from the quasi-random assignment of shocks, while exposure shares are allowed to be endogenous. The framework is motivated by an equivalence result: the orthogonality between a shift-share instrument and an …
Revisiting Event-Study Designs
We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects. We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent strong restrictions on treatment-effect homogeneity. We then derive the efficient estimator addressing this challenge, which takes an intuitive “imputation” form when treatment-effect heterogeneity is un…
A Practical Guide to Shift-Share Instruments
A recent econometric literature shows two distinct paths for identification with shift-share instruments, leveraging either many exogenous shifts or exogenous shares. We present the core logic of both paths and practical takeaways via simple checklists. A variety of empirical settings illustrate key points
Computer Science (2 works) · Econometrics (2 works) · Economics (2 works) · Mathematics (2 works) · Regression (2 works) · Statistics (2 works) · Advanced Causal Inference Techniques (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Average treatment effect (1 works)