TITLE:
Applying Multivariate Multilevel Models to Explore Arable Land Quality in Sub-Saharan Africa: A Case Study in Kenya
AUTHORS:
Davies D. Onduru, Fred Onyango
KEYWORDS:
Meta-Analysis, Multilevel Models, Nutrient Balance, Sub-Saharan Africa, Kenya
JOURNAL NAME:
Open Journal of Statistics,
Vol.7 No.6,
December
13,
2017
ABSTRACT: Controversy exists on the magnitude and variability of farm nutrient
balances and quality of arable land in sub-Saharan Africa with Kenya among
those affected negatively. This study investigates quality of arable land by
fitting multivariate multilevel model to farm nutrient balance data collected
from five agro-climatic zones of Kenya (arable lands). Objectives of the study
were to investigate the magnitude and variability of Nitrogen, Phosphorus and
Potassium (NPK) farm nutrient balances in arable lands of Kenya, study effects
of agro-climatic zones on nutrient balances and to determine effects of household
resource endowments on NPK nutrient balances. The study concludes that
agro-climatic zones differ with respect to farm nutrient balances; that
livestock resource endowments and hired labour have positive effects on the
magnitude and direction of farm nutrient balances; and that household ownership
of large capital resources do not guarantee
a positive effect on farm nutrient balances. The study recommends integration
of sound livestock practices and application of agro-climatic zone
differentiated interventions in future strategies for addressing farm nutrient
balances and arable land quality, and the use of large sample sizes and
relevant factors/covariates in future analysis to shed additional insights on
farm nutrient balances and on how arable land quality can be improved.