PPT-Ratio Transformation for Stationary Time Series with Special Application in Consumer Price

Special Application in Consumer Price Index in Qatar By Adil Yousif Hind Alrkeb Doha Alhashmi Department of Mathematics and Statistics Qatar University Doha Qatar Abstract This article was intended to perform a comprehensive. Regression with Time-Series Data:. Nonstationary Variables. Walter R. Paczkowski . Rutgers . University. 12.1 . Stationary and Nonstationary Variables. 12.2 . Spurious Regressions. 12. .3 . Unit Root Tests for . CPI is the government’s “most important” statistic. Announced monthly by Bureau of Labor Statistics. Measures changes in prices of goods and services over time. Affects elections, economy, government policies, Social Security, pensions. Dr Allan Tucker. Intelligent Data Analytics Group,. Department of Computer Science, Brunel University London.. The Talk. The IDA Group at Brunel. 1 Challenges of modelling longitudinal data. Non-stationary state space . The Average Weekly Earnings of an Australian Employee. . Multiplying or dividing all the values in a time series by the same constant is called . scaling the series. . . Scaling a series does not affect the percentage changes in the series. It is often convenient to scale a series to have a value of 100 in some period. Such a scaled series is called an . Some Basic Concepts. Reference : Gujarati, Chapters 21. Course . Incharge. : . Prof. Dr. . Himayatullah. Khan. Time Series Data. One of the . important. and . frequent. types of data used in empirical .  . Mark Carney. Governor of The Bank of Canada. Inflation. refers to the general rise in prices from year to year.. Statistics Canada measures inflation using the CPI, which tracks price changes in consumer goods.. Some Basic Concepts. Reference : Gujarati, Chapters 21. Course . Incharge. : . Prof. Dr. . Himayatullah. Khan. Time Series Data. One of the . important. and . frequent. types of data used in empirical . 2. Contents – Session I. Introduction. . – purpose and use of Price Index. What . is an Index number . Aggregate . index. . Introduction – Purpose and Use. What is Price Index?. Main uses. Common price indices. Index. Session IV. 3. Contents – Session IV. Constructing Price Index . - Part I. Issues . involved. . Price Index . – Purpose,. . Scope and Coverage. Periodicity and Timeliness. . Constructing Price . Book: Time Series Analysis Univariate and Multivariate. http://ruangbacafmipa.staff.ub.ac.id/files/2012/02/Time-Series-Analysis-by.-. Wei.pdf. https://wiki.math.ntnu.no/tma4285/2011h/start. http://astro.temple.edu/~wwei/data.html. Special Application in Consumer Price Index in Qatar. By:. Adil. . Yousif. , Hind . Alrkeb. , Doha . Alhashmi. Department of Mathematics and Statistics. Qatar University. Doha, Qatar. Abstract. This article was intended to perform a comprehensive time series analysis for Consumer Price Index (CPI) in Qatar. The data was obtained from the Statistics Authority in Qatar. For the period between: (2002-2009) a quarterly data was analyzed using several time series techniques such as Exponential Trend method, Holts’ Trend method, and ARIMA. These methods were used to examine trends and built a forecast model. Ratio transformation technique was used to obtain a stationary time series and found to be efficient with small size of data.. Recap. Mean Reversion . Belief that an asset will revert back to an . equilibrium point. Drawn from inter/intraday data of stocks, ETFs vs. their components, currency pairs, futures calendar/intermarket spreads. Index. Session IV. 3. Contents – Session IV. Constructing Price Index . - Part I. Issues . involved. . Price Index . – Purpose,. . Scope and Coverage. Periodicity and Timeliness. . Constructing Price . Materials . for lecture 12. Read Chapter 15 pages 30 to 37. Lecture . 12 . Time . Series.XLSX. Lecture . 12 . Vector . Autoregression.XLSX. Time Series Model Estimation. Outline for this lecture. Review .