Abstract:
The study makes use of time-dependent displaying components and
structural equation modelling to determine the price levels of key local food
items on several markets in Ghana over non-consecutive time periods. The
application of the techniques to this multiple multivariate complex data
structure identifies suitable dimensions along which to assess the major influence of the price data over
a time-period and highlight possible extreme
prices simultaneously. It also examines multiple sets of data-generating
variables that may be put together in a single model. These variables include a ‘vectorised’ factor solution and some market-feature covariates. The
displaying components comprise the principal component and the outlier
displaying component (ODC). The study has provided necessary extensions
that would make the components suitable for the study. The plots for the first
five components in addition to the preliminary results give the set of suspect
outlying markets. Using this set, the Modified 1-ODC is applied based on the
pooled reduced sample Sum of Squares and Cross Product matrix. Markets 17
and 65 are clearly identified as the most consistently low and high priced, respectively, over the period. Using the factor solution and two covariates, a
structural model is obtained for determining the price levels. Even though the
factors constitute a significant model by themselves, they are not significant in
the model that contains significant covariates, which are ‘Region’ and the
‘number of days’ of trading. The model shows that extreme markets, which
are few, are predominantly associated with large number of market days.
Equitable and increased production of cereals and spices in particular in all
regions could reduce price variations across markets and enhance well-being.
