Explaining the German hog price cycle: A nonlinear dynamics approach

Ernst Berg and Ray Huffaker

No 206210, 2015 International European Forum (144th EAAE Seminar), February 9-13, 2015, Innsbruck-Igls, Austria from International European Forum on System Dynamics and Innovation in Food Networks

Abstract: We investigated German hog-price dynamics with an innovative ‘diagnostic’ modeling approach. Hog-price cycles are conventionally modeled stochastically—most recently as randomly-shifting sinusoidal oscillations. Alternatively, we applied nonlinear time series analysis to empirically reconstruct a deterministic, low-dimensional, and nonlinear attractor from observed hog prices. We next formulated a structural (explanatory) model of the pork industry to synthesize the empirical hog-price attractor. Model simulations demonstrate that low price-elasticity of demand contributes to aperiodic price cycling – a well know result – and further reveal two other important driving factors: investment irreversibility (caused by high specificity of technology), and liquidity-driven investment behavior of German farmers.

Keywords: Agribusiness (search for similar items in EconPapers)
Pages: 21
Date: 2015-05
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ageconsearch.umn.edu/record/206210/files/03-Berg_Huffaker-paper.pdf (application/pdf)

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:ags:iefi15:206210

DOI: 10.22004/ag.econ.206210

Access Statistics for this paper

More papers in 2015 International European Forum (144th EAAE Seminar), February 9-13, 2015, Innsbruck-Igls, Austria from International European Forum on System Dynamics and Innovation in Food Networks Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().