TITLE:
Univariate Time-Series Analysis of Second-Hand Car Importation in Zambia
AUTHORS:
Stanley Jere, Bornwell Kasense, Bwalya Bupe Bwalya
KEYWORDS:
Zambia, Importation, Second Hand Car, Exponential Smoothing Models, ARIMA Models, Forecasting
JOURNAL NAME:
Open Journal of Statistics,
Vol.7 No.4,
August
29,
2017
ABSTRACT: Zambia largely depends on the international second-hand car (SHC) market
for their motor vehicle supply. The importation of Second hand Cars in Zambia
presents a time series problem. The data used in this paper is monthly data on
SHC importation from 1st January, 2014 to 31st December,
2016. Data was analyzed using Exponential Smoothing (ES) and Autoregressive Integrated
Moving Average (ARIMA) models. The results showed that ARIMA (2, 1,
2) was the
best fit for the SHC importation since its errors were smaller than those of
the SES, DES and TES. The four error measures used were Root-mean-square error (RMSE), Mean absolute error (MAE), Mean percentage error (MPE)
and Mean absolute percentage
error (MAPE). The forecasts were also produced using the
ARIMA (2, 1, 2) model for the next 18 months from January 2017. Although there
is percentage increase of 90.6% from November 2015 to December 2016, the SHC
importation generally is on the decrease in Zambia with percentage change of 59.5% from January
2014 to December 2016. The forecasts also show a gradual percentage decrease of
1.12% by June 2018. These results are more
useful to policy and decision makers of Government departments such as Zambia
Revenue Authority (ZRA) and Road Development Agency (RDA) in a bid to plan and
execute their duties effectively.