Econometrics course: light and dark side of the moon

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Econometrics courselight and dark side of the
moon

• Yaroslav Prytula
• Lviv Ivan Franko National University

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Presentation outlines

• Departments program
• The place of Econometrics course
• Econometrics course syllabus
• Light side of the moon
• Dark side of the moon
• Looking for the Golden section

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Departments program

• Languages (45 of students load)
• Economics (20 of students load)
• The rest (35 of students load)

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Place of the course
Before
After

• Mathematics
• Statistics
• Micro
• Macro
• International Econ.

• Forecasting
• Money and Banking
• Investments
• Risks
• International Econ.(2)
• Finance

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Econometrics course objective

• The course aims to provide an overview of the
  fundamentals of classic and modern econometrics
  to students who have not had any econometrics
  course before

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Econometrics course outline

• Session 1. Introduction to Econometrics. Key
  steps in conducting econometric analysis.
  Statistical inference.
• Parameters and estimators. Estimation of
  parameters method of moments, least square
  method, and maximum likelihood method. Hypothesis
  testing. Type I and type II errors.
• Session 2. Simple linear regression model.
  Classical conditions. Gauss-Markov theorem.
  Ordinary least squares method. A simple t-test.
• Estimation of residuals variance . Goodness of
  fit coefficient of determination .

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Econometrics course outline

• Session 3. Multivariate linear regression model.
  Testing one linear restriction. A joint test of
  significance of regression coefficients. Adjusted
  .
• Session 4. Dealing with nonlinear models.
  Comparing regression models.
• Session 5. Test Chow of structural changes. Dummy
  variables. Illustrations.

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Econometrics course outline

• Session 6. Heteroscedasticity. Testing for
  hetero-scedasticity. Dealing with
  heteroscedasticity. Illustrations.
• Autocorrelation. Testing for first order
  autocorrelation. Dealing with autocorrelation.
  Illustrations.
• Session 7. Problem of endogeneity. Notion of
  instrumental variable estimator.
• Session 8. Limited dependent variables models.
  Binary choice models. Estimation. Interpretation
  of coefficients. Illustrations.

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Econometrics course evaluation

• Attendance 10
• Two problem sets 10
• Mid-term 25
• Group project 25
• Final exam 30

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Econometrics course group project

• During the semester students will be asked to
  form groups of not more then four for doing a
  group project.
• Students should find appropriate data, process
  data, choose appropriate econometric model, make
  calculations, analyze the model using E-views 3.1
  and make conclusions.
• Model selection and analysis of regression
  results should be emphasized.

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Econometrics course group project

• Written report should include
• Introduction. Description of the investigated
  economic phenomena.
• Methods and/or sources of data collection.
• Data processing and analyzing.
• Selection of the model, its evaluation.
• Hypothesis testing and forecasting.
• Conclusions.
• Size of report should not exceed 5 pages that is
  equivalent to 1500 words.

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Econometrics course grade
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Light side of the moon

• I teach all quantitative courses
• All students know English I can use English
  language materials
• Students are (almost) required to use econometric
  methods in their term papers

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Dark side of the moon

• I teach all quantitative courses
• Econometrics course 1/13 of students load.
• Overidentification problem (who is our graduate?)
• To what extend it is optimal to use active
  teaching methods within this course?

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Research on Econometrics teaching

• William E. Becker Michael Watts Chalk and Talk
  A National Survey on Teaching Undergraduate
  Economics, AER, 1996
• William E. Becker Michael Watts Teaching
  Economics at the Start of the 21st Century Still
  Chalk-and-Talk, AER, 2001
• William E. Becker William H. Greene Teaching
  Statistics and Econometrics to Undergraduates,
  The Journal of Economic Perspectives, 2001
• Peter E. Kennedy Teaching Undergraduate
  Econometrics A Suggestion for Fundamental
  Change, AER, 1998.

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Research on Econometrics teaching

• Lecturing and chalkboard 83 (1996), a bit less
  in 2000
• Overhead projector 23 (1996), the same in 2000
• Cooperative teaching almost zero in 1996 and
  2000
• Small group cooperative learning 18 (1996), no
  info for 2000
• Scholarly readings almost zero in 1996 and 2000
• Importance of Mathematics extremely important
  in all courses, but especially in statistics and
  econometrics

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Looking for the Golden Section

• DOA (Data Oriented Approach)
• Case/research based teaching
• Monte Carlo simulations