EconPapers    
Economics at your fingertips  
 

Comparison of production risks in the state-contingent framework: application to balanced panel data

Kota Minegishi ()
Additional contact information
Kota Minegishi: University of Minnesota

Journal of Productivity Analysis, 2016, vol. 46, issue 2, No 2, 138 pages

Abstract: Abstract In a balanced panel data setting, this article proposes an empirical application of the state-contingent (SC) framework for production uncertainty. The SC approach (e.g., Chambers and Quiggin 2000) casts production decisions under uncertainty as the decision to select a portfolio of Arrow-Debreu SC outputs, scheduled to be delivered in the contingent states of nature. Under some stationarity assumptions on the SC decisions (i.e., no technical change, time-invariant states of nature, time-invariant SC portfolio decisions) and regularity assumptions on the data generating process (i.e., cross-sectionally homogeneous state realizations), SC technology can be estimated from balanced panel data that are framed as cross-sectional data of partially-revealed SC portfolio decisions. This allows one to simulate an optimal SC portfolio, determined by the interaction between the estimated SC technology and given risk preferences. In the application to Maryland dairy production data, the stochastic technologies of confinement and intensive-grazing dairy systems are compared. Of the two time intervals (years 2000–2004 and ye0ars 2006–2009) separately analyzed, the optimal production decision has generally become riskier for the confinement system and less risky for the grazing system. These contrasting trends appear directly related to the volatile milk prices, feed cost hikes, and increasing organic milk production during 2006–2009. The risk associated with the optimal portfolio is substantially lower under the SC analysis compared to a typical residual-as-uncertainty approach, suggesting that the typical approach may overstate the risk due to uncertainty.

Keywords: State contingent production; Uncertainty; Panel data analysis; Data envelopment analysis; Agricultural economics (search for similar items in EconPapers)
JEL-codes: C44 D22 Q12 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s11123-016-0483-1 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:46:y:2016:i:2:d:10.1007_s11123-016-0483-1

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2

DOI: 10.1007/s11123-016-0483-1

Access Statistics for this article

Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski

More articles in Journal of Productivity Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2023-11-13
Handle: RePEc:kap:jproda:v:46:y:2016:i:2:d:10.1007_s11123-016-0483-1