Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/180872
Authors: 
Gandhi, Amit
Navarro, Salvador
Rivers, David A.
Year of Publication: 
2018
Series/Report no.: 
CHCP Working Paper 2018-1
Abstract: 
We study the nonparametric identification of gross output production functions under the environment of the commonly employed proxy variable methods. We show that applying these methods to gross output requires additional sources of variation in the demand for flexible inputs (e.g., prices). Using a transformation of the firm's first-order condition, we develop a new nonparametric identification strategy for gross output that can be employed even when additional sources of variation are not available. Monte Carlo evidence and estimates from Colombian and Chilean plant-level data show that our strategy performs well and is robust to deviations from the baseline setting.
Document Type: 
Working Paper
Social Media Mentions:

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.