Aureo de Paula (UCL): Estimating Production Functions with Expectations Data
Abstract:
Standard methods for estimating production functions in the Olley and Pakes (1996) tradition require assumptions on input choices. We introduce a new method that exploits expectations data, which is increasingly available, and allows us to relax these input demand assumptions to obtain consistent production function parameter estimates. In contrast to dynamic panel data methods, our proposed estimator can be implemented on very short panels (including a single cross-section), and Monte Carlo simulations show it outperforms alternative estimators when firms' material and/or investment choices are subject to optimization error. We also implement our estimation strategy on UK data.
Audience
- Faculty/Staff
- Student
- Post Docs/Docs
- Graduate Students
Interest
- Academic (general)