Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/22105
Title: Technical efficiency in competing panel data models: A study of Norwegian grain farming
Contributor(s): Kumbhakar, Subal C (author); Lien, Gudbrand (author); Hardaker, John Brian  (author)
Publication Date: 2014
DOI: 10.1007/s11123-012-0303-1
Handle Link: https://hdl.handle.net/1959.11/22105
Abstract: Estimation of technical efficiency is widely used in empirical research using both cross-sectional and panel data. Although several stochastic frontier models for panel data are available, only a few of them are normally applied in empirical research. In this article we chose a broad selection of such models based on different assumptions and specifications of heterogeneity, heteroskedasticity and technical inefficiency. We applied these models to a single dataset from Norwegian grain farmers for the period 2004-2008. We also introduced a new model that disentangles firm effects from persistent (time-invariant) and residual (time-varying) technical inefficiency. We found that efficiency results are quite sensitive to how inefficiency is modeled and interpreted. Consequently, we recommend that future empirical research should pay more attention to modeling and interpreting inefficiency as well as to the assumptions underlying each model when using panel data. © 2012 Springer Science+Business Media, LLC.
Publication Type: Journal Article
Source of Publication: Journal of Productivity Analysis, 41(2), p. 321-337
Publisher: Springer New York LLC
Place of Publication: United States of America
ISSN: 1573-0441
0895-562X
Fields of Research (FoR) 2008: 140201 Agricultural Economics
Fields of Research (FoR) 2020: 380101 Agricultural economics
Socio-Economic Objective (SEO) 2008: 919999 Economic Framework not elsewhere classified
Socio-Economic Objective (SEO) 2020: 159999 Other economic framework not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article

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