Effect of Missing Observations on Buys-Ballot Estimates of Time Series Components

Abstract


 This study discusses the effects of missing observations on Buys-Ballot estimate when trend-cycle component of time series is linear. The method adopted in this study is Decomposing Without the Missing Value (DWMV) which is used to estimate missing observations in time series decomposition when data are arranged in a Buys-Ballot table. The model structure used is multiplicative. Results show that the trend parameters with and without missing observations have insignificant effect while there are significant differences in the seasonal indices only at the season points where missing observations occurred in the Buys-Ballot table.

Comparison of Trend Parameters and Seasonal Indices in the Presence and Absence of Missing Values of Exponential Trend-Cycle in Time Series Analysis

“…The method adopted for this article is the Buys-Ballot method. For details of this method, see Iwueze et.al [4], Nwogu et.al [9], Dozie and Uwaezuoke [10], Dozie and Ibebuogu [11], Dozie et.al [12], Dozie and Ijomah [13], Dozie and Nwanya [14], Dozie [15], Dozie and Uwaezuoke [16], Dozie and Ihekuna [17], Dozie and Ibebuogu [18], Akpanta and Iwueze [19]. Dozie and Ihekuna [20], Dozie [21] and Dozie and Uwaezuoke [22].…”