Restricted least squares estimation

17–18 November 2022
3:00–6:00 PM CET     converter
Topic: courses

Instructor

Affiliated with CCS Haryana Agricultural University, Hisar, India. University of Dodoma, Dodoma, Tanzania. Eastern Africa Statistical Training Centre, Dar es Salaam. Invertis University, India.

Prof. Dr. Kuldeep Kumar Saxena worked for about 38 years in various capacities in the department of Statistics, CCS Haryana Agricultural University, Hisar, India and retired as Professor of Statistics in 2012. Then he joined University of Dodoma, Dodoma, Tanzania as Full Professor of Statistics and worked there from 2013 to 2019. Since then Prof. Dr. Kuldeep Kumar Saxena is delivering lectures on various topics of Statistics online in various universities in India and abroad.

Course description

This course on applied econometrics, has been prepared as an integration of mathematical economics and statistical methods with an objective of extracting the stochastic relationship among variables and their modelling.

Learning outcomes to be covered

The learning outcomes will be

  1. To get the knowledge of Linear and nonlinear modelling
  2. How to improve the estimation of regression coefficients by various restrictions.
  3. Knowledge of Restricted least squares estimation, Generalized and Weighted Least Squares Estimation.
  4. Knowledge about the difference between disturbances and measurement errors:
  5. Indicator variables versus quantitative explanatory variable
  6. Tests for Structural Change and Stability

Description of course materials

  1. Generalized and Weighted Least Squares Estimation.
  2. The estimation of regression coefficients by
    • exact linear restrictions
    • stochastic linear restrictions
    • inequality restrictions.
    • empirical investigations.
    • some extraneous sources etc.
  3. Restricted least squares estimation
  4. Indicator variables versus quantitative explanatory variable
  5. Tests for Structural Change and Stability
  6. Difference between disturbances and measurement errors:
    • Large and small measurement errors
    • Forms of measurement error model
      • Functional form models
      • Structural form models
      • Ultrastructural form models
  7. Simultaneous equations models
  8. Seemingly Unrelated Regressions

The course will be taught online through Power point presentation.

Prerequisites

Intermediate knowledge of:

  1. Probability theory and probability distributions
  2. Theory of estimation and testing of hypothesis
  3. Basics of economic theory