Index Number and Time Series

Paper Code: 
DSTT 601(A)
Credits: 
4
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

Index Number and Time Series Analysis" is to explore the use of index numbers and time series methods for analyzing economic data.

 

Students will be able to:

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

 DSTT 601(A)

Index Number and Time Series

 

CO 60: Interpret and use a range of index numbers commonly used and also to Evaluate other indices used in the business sector.

 

CO 61: Apply the Factor reversal and time reversal tests in various conditions.

 

CO 62:  Develop the ability to apply the method of moving averages, detrending techniques, and estimation of seasonal components using the method of simple averages in time series analysis.

 

CO 63: Apply time series methods for forecasting values of a time series at future time points and also apply them on real world models.

 

CO 64: Acquire proficiency in applying ratio to trend, ratio to moving averages, and link relative methods for deseasonalization in time series analysis, and understand the variate component method for analyzing random components in time series data.

Approach in teaching:

 

Interactive Lectures,

Group Discussion,

Classroom Assignment

Problem Solving Sessions

 

 

 

Learning activities for the students:

 

Assignments

Seminar

Presentation

Subject based Activities

 

Classroom Quiz

Assignments

Class Test

Individual Presentation

 

 

 

12.00
Unit I: 

Index Numbers: Definition, construction of index numbers and problems thereof for weighted and unweighted index numbers including Laspeyre, Paasche, Drobish and Bowley, Edgeworth-Marshall, Fisher, Walsch and Kelly.

12.00
Unit II: 

Tests and Errors for Index Numbers, Chain index numbers, conversion of fixed based to chain based index numbers and vice-versa. Consumer price index numbers.

12.00
Unit III: 

Introduction to times series data, application of time series from various fields. Components of a times series, Decomposition of time series. Trend: Estimation of trend by free hand curve method, method of semi averages, fitting a various mathematical curve, and growth curves.

12.00
Unit IV: 

Method of moving averages. Detrending. Effect of elimination of trend on other components of the time series. Seasonal Component: Estimation of seasonal component by Method of simple averages.

12.00
Unit V: 

Ratio to Trend. Ratio to Moving Averages and Link Relative method, Deseasonalization. Random Component: Variate component method. 

Essential Readings: 
  • Goon, A.M., Gupta, M.K. and Dasgupta, B. (1991): Fundamentals of Statistics,  Volume II, The World Press Pvt Ltd, Calcutta
  • Gupta, S.C. and Kapoor, V.K.(2000): Fundamentals of Applied Statistics, S Chand & Company, New Delhi
References: 

SUGGESTED READINGS:

  • Croxton, F.E. and Cowden, D.J. (1969): Applied General Statistics, Prentice Hall Of India
  • Srivastava, O.S.(1998): A Textbook of Demography, Vikas Publishing.
  • Shrinivasan, K. and Srinivasan, K.(1998): Basic Demographic Techniques and Applications.
  • Anderson, T.W. (1971): The Statistical Analysis of Time Series, Wiley, N.Y.
  • Montgemory, D.C. and Johnson, L.A. (1977): Forecasting and Time Series Analysis, McGraw Hill.
  • Kendall, Sir Maurice and Ord, J.K. (1990): Time Series (Third Edition), Edward Arnold.
  • Brockwell, P.J. and Davis, R.A.(1991): Time Series: Theory and Methods (Second Edition), Springer- Verlag.
  • Fuller, W.A. (1976): Introduction to Statistical Time Series, John Wiley, N.Y.
  • Granger, C.W.J. and Newbold (1984): Forecasting Econometric Time Series, Third Edition, Academic Press.
  • Priestley, M.B. (1981): Spectral Analysis & Time Series, Griffin, London.
  • Kendall, M.G. and Stuart A. (1966): The Advanced Theory of Statistics, Volume 3, Charles Griffin, London. 

e-RESOURCES:

JOURNALS:

  • Sankhya The Indian Journal of Statistics, Indian Statistical Institute
  • Aligarh Journal of Statistics, Department of Statistics and Operations Research, Aligarh Muslim University
  • Afrika Statistika, Saint-Louis Senega University
  • International Journal of Statistics and Reliability Engineering, Indian Association for Reliability and Statistic
  • Journal of the Indian Society for Probability and Statistics, Indian Society for Probability and Statistics
  • Journal of the Indian Statistical Association, Indian Statistical Association
  • Statistica, Department of Statistical Sciences Paolo Fortunato, University of Bologna
  • Statistics and Applications, Society of Statistics, Computer and Applications
  • Stochastic Modeling and Applications, MUK Publications and Distributions
Academic Year: 
2023-2024
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