Using Time Series Methods To Modify The Seasonal Variations in the Consumer Price Index

Authors

  • عبد اللطيف حسن شومان
  • هيثم حسن ماجد

DOI:

https://doi.org/10.33095/jeas.v19i74.1439

Keywords:

استخدام أساليب السلاسل الزمنية لمعالجة الاختلافات الموسمية في الرقم القياسي لسعر المستهلك, Using Time Series Methods To Modify The Seasonal Variations in the Consumer Price Index

Abstract

     As is  known that the consumer price index (CPI) is one of the most important  price indices because of its direct effect on the welfare of the individual and his living.

       We have been address the problem of Strongly  seasonal  commodities in calculating  (CPI) and identifying some of the solution.

   We have  used an actual data  for a set of commodities (including strongly seasonal commodities) to calculate the index price by using (Annual Basket With Carry Forward Prices method) . Although this method can be successfully used in the context of seasonal  commodities  the  index  does not  get  rid  of  the  tremendous  season  fluctuations  .       

     In order to use (CPI) in  measuring  the general inflation and monthly or quarterly comparison ,we must  first  decompose the seasonal component and eliminate  its effect on the (CPI) series to get  a seasonal adjusted series of (CPI) .

     Many statistical methods are used to analysis (CPI) series, and one of these methods is the method of time series that takes into account the seasonal variations in the study of phenomena.

test to  Ljung-Box  We have used Box-Jenkens method in models building and then test the modesl ,also we have found the seasonal adjusted series by using time series  method

Downloads

Download data is not yet available.

Published

2013-12-01

Issue

Section

Statistical Researches

How to Cite

“Using Time Series Methods To Modify The Seasonal Variations in the Consumer Price Index” (2013) Journal of Economics and Administrative Sciences, 19(74), p. 360. doi:10.33095/jeas.v19i74.1439.

Similar Articles

1-10 of 1779

You may also start an advanced similarity search for this article.