Statistical Treatment of Data
Code
400018
Academic unit
NOVA Information Management School
Credits
6.0
Teacher in charge
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
The curricular unit of "Treatment of Statistical Data" aims to provide skills in the domain of evolution of economic time series, in particular in the field of index numbers, seasonal correction and outliers and missing values treatment.
Prerequisites
Not applicable
Subject matter
1. Introduction to índex number
1.1. Index numbers problem
1.2. Taxonomy of approaches to índex number
1.3. Implicit and direct number indexes
1.4. Index number formulation
1.5. Basic concepts of índex number calculation
1.6. Contemporary issues
2. Statistical/axiomátic approaches
2.1. Bilateral indexes
2.2. Fixed base and chain indexes
3. Productivity indicators
3.1. Partial productivity indexes of production factors
3.2. Total productivity indexes of production factors
4. Seasonal adjustment methods
4.1. Bried introduction to time series
4.2. Seasonality and its determinants
4.3. Decomposition models
4.4. Exploition tools
4.5. Seasonal adjustment procedures
4.6. Outliers, calendar effects and its components
4.7. European Statistical System guidelines
4.8. Seasonal adjustment software
5. Treatment of outliers
6. Tratamen of missing data
a. Index numbers
- SNA08, Chapter 15: Price and volume measures
http://unstats.un.org/unsd/nationalaccount/docs/SNA2008.pdf
- International PPI Manual
http://www.imf.org/external/pubs/ft/ppi/2010/manual/ppi.pdf
- International CPI Manual
http://www.imfbookstore.org/ProdDetails.asp?ID=CPIMFT
- Practical Guide to Producing CPI
http://www.unece.org/fileadmin/DAM/stats/publications/Practical_Guide_to_Producing_CPI.pdf
- RECENT DEVELOPMENTS IN INDEX NUMBER THEORY AND PRACTICE
http://78.41.128.130/dataoecd/49/2/35619491.pdf
- MEASUREMENT OF AGGREGATE AND INDUSTRY-LEVEL PRODUCTIVITY GROWTH, OECD manual
www.oecd.org/std/productivity-stats/2352458.pdf
- THE MEASUREMENT OF AGGREGATE TOTAL FACTOR PRODUCTIVITY GROWTH
www.economics.ubc.ca/.../pdf_paper_erwin-diewert-02-05-measurementofaggregatetotalfactorproductivitygrowth
b. Missing data
- Allison, P. D. (2002). Missing Data. Thousand Oaks, CA: Sage
- Bryk, A. S. And Randenbush, S. W. (1992). Hierarchical linear models, thousands oaks, CA: Sage
- Cleveland, W. S. (1983), Visualizing data. Summit.
- Enders, C. K. (2010) – Applied missing data Analysis, New York, the Guilford Press
- Little, R. J. A. and Rubin (1987) – Statistical analysis with missing data, New York, Willey
- McKnight P., McKnight K., Sidani S. and Figueredo A. (2007) Missing data – A Gentle introduction, the Guilford Press
- Shaffer, J. L. and Graham, J.W. (2002) Missing data: our view of the state of the art.
- Shafer, J. L. (1997) – Analysis of incomplete data, Chapman and Hall, London
c. Outliers
- Barnett V. and Lewis T (1995) – Outliers in statistical data, 3rd edn. Wiley
- Brauman M. (1994), Sobre testes de deteção de outliers em populações exponenciais. Dissertação de douturamento, Universidade de Évora
- Cook, R. D. and Weisberg S. (1982) - Residuals and influence in Regression. Chapman and Hal
Bibliography
Please check couse contents; 0; 0; 0; 0
Teaching method
The course is based on theoretical and practical classes. The classes are aimed at solving problems and exercises.