Jan 30, 2018
DOI: 10.1504/IJMTM.2018.090063
Published in: Int. J. Manufacturing Technology and Management, Vol. 32, No. 2, 2018
Publisher: Inderscience
Abstract: The study analyses the seasonal variation and forecasts the output of the beverage industry in Khyber Pakhtunkhwa (KPK) province of Pakistan, using a seven-year (month-wise) data from July 2007 to April 2014. Tramo Seats version of Demetra+ software has been used on log-transformed data with the distinct feature of automatic model identification to capture seasonal differences in output of the beverage industry in KPK. Results suggest wider fluctuations in the original series as compared to seasonal adjusted series which was mainly due to seasonal component in the time series instead of the irregular component; thus, confirming the principle of canonical decomposition of the data set in question. Results of non-parametric tests revealed a strong and stable seasonality pattern in the output of the beverage industry. Further, a significant difference between original and seasonal adjusted series has also been observed in the output. The results have implications for policy planners both at micro as well as macro level.
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