TY - JOUR
T1 - Crop-yield distributions revisited
AU - Ramirez, Octavio A.
AU - Misra, Sukant
AU - Field, James
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2003/2
Y1 - 2003/2
N2 - This article revisits the issue of crop-yield distributions using improved model specifications, estimation, and testing procedures that address the concerns raised in recent literature, which could have invalidated previous findings of yield nonnormality. It concludes that some aggregate and farm-level yield distributions are nonnormal, kurtotic, and right or left skewed, depending on the circumstances. The advantages of utilizing nonnormal versus normal probability distribution function models, and the consequences of incorrectly assuming crop-yield normality are explored.
AB - This article revisits the issue of crop-yield distributions using improved model specifications, estimation, and testing procedures that address the concerns raised in recent literature, which could have invalidated previous findings of yield nonnormality. It concludes that some aggregate and farm-level yield distributions are nonnormal, kurtotic, and right or left skewed, depending on the circumstances. The advantages of utilizing nonnormal versus normal probability distribution function models, and the consequences of incorrectly assuming crop-yield normality are explored.
KW - Corn Belt
KW - Crop-yields
KW - Nonnormality
KW - Probability distributions
KW - Texas cotton
UR - http://www.scopus.com/inward/record.url?scp=0037327160&partnerID=8YFLogxK
U2 - 10.1111/1467-8276.00106
DO - 10.1111/1467-8276.00106
M3 - Article
AN - SCOPUS:0037327160
VL - 85
SP - 108
EP - 120
JO - American Journal of Agricultural Economics
JF - American Journal of Agricultural Economics
SN - 0002-9092
IS - 1
ER -