Model choice and size distribution: a Bayequentist approach
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
Standard
in: American Journal of Agricultural Economics, Jahrgang 97, Nr. 3, 04.2015, S. 978-997.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - Model choice and size distribution: a Bayequentist approach
AU - Engler, John-Oliver
AU - Baumgärtner, Stefan
PY - 2015/4
Y1 - 2015/4
N2 - We propose a new three-step model-selection framework for size distributions in empirical data. It generalizes a recent frequentist plausibility-of-fit analysis (Step 1) and combines it with a relative ranking based on the Bayesian Akaike Information Criterion (Step 2). We enhance these statistical criteria with the additional criterion of microfoundation (Step 3) which is to select the size distribution that comes with a dynamic micro model of size dynamics. A numerical performance test of Step 1 shows that our generalization is able to correctly rule out the distribution hypotheses unjustified by the data at hand. We then illustrate our approach, and demonstrate its usefulness, with a sample of commercial cattle farms in Namibia. In conclusion, the framework proposed here has the potential to reconcile the ongoing debate about size distribution models in empirical data, the two most prominent of which are the Pareto and the lognormal distribution.
AB - We propose a new three-step model-selection framework for size distributions in empirical data. It generalizes a recent frequentist plausibility-of-fit analysis (Step 1) and combines it with a relative ranking based on the Bayesian Akaike Information Criterion (Step 2). We enhance these statistical criteria with the additional criterion of microfoundation (Step 3) which is to select the size distribution that comes with a dynamic micro model of size dynamics. A numerical performance test of Step 1 shows that our generalization is able to correctly rule out the distribution hypotheses unjustified by the data at hand. We then illustrate our approach, and demonstrate its usefulness, with a sample of commercial cattle farms in Namibia. In conclusion, the framework proposed here has the potential to reconcile the ongoing debate about size distribution models in empirical data, the two most prominent of which are the Pareto and the lognormal distribution.
KW - Sustainability sciences, Management & Economics
KW - cattle farming
KW - environmental risk
KW - Gibrat's Law
KW - hypothesis testing
KW - model choice
KW - model selection
KW - Pareto distribution
KW - rank-size rule
KW - semiarid rangelands
KW - size distributions
UR - http://www.scopus.com/inward/record.url?scp=84928315992&partnerID=8YFLogxK
U2 - 10.1093/ajae/aau034
DO - 10.1093/ajae/aau034
M3 - Journal articles
VL - 97
SP - 978
EP - 997
JO - American Journal of Agricultural Economics
JF - American Journal of Agricultural Economics
SN - 0002-9092
IS - 3
ER -