Arbeitspapier

On the identification of gross output production functions

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.

Language
Englisch

Bibliographic citation
Series: CHCP Working Paper ; No. 2018-1

Classification
Wirtschaft

Event
Geistige Schöpfung
(who)
Gandhi, Amit
Navarro, Salvador
Rivers, David A.
Event
Veröffentlichung
(who)
The University of Western Ontario, Centre for Human Capital and Productivity (CHCP)
(where)
London (Ontario)
(when)
2018

Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Gandhi, Amit
  • Navarro, Salvador
  • Rivers, David A.
  • The University of Western Ontario, Centre for Human Capital and Productivity (CHCP)

Time of origin

  • 2018

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