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.
- Sprache
-
Englisch
- Erschienen in
-
Series: CHCP Working Paper ; No. 2018-1
- Klassifikation
-
Wirtschaft
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Gandhi, Amit
Navarro, Salvador
Rivers, David A.
- Ereignis
-
Veröffentlichung
- (wer)
-
The University of Western Ontario, Centre for Human Capital and Productivity (CHCP)
- (wo)
-
London (Ontario)
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Gandhi, Amit
- Navarro, Salvador
- Rivers, David A.
- The University of Western Ontario, Centre for Human Capital and Productivity (CHCP)
Entstanden
- 2018
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