Introduction to Econometrics :University of Oregon Online Course

Course Description :

This course looks at what happens when the conditions are less than ideal due to departures from the assumptions necessary for ordinary least squares to be the best linear unbiased estimator, and provides alternative regression techniques that address problems arising from the violations of the basic assumptions.

Lecture Details :

Economics 421 – Econometrics – Winter 2009 

Lecture by

Prof. Mark Thoma

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1. Economics 421 – Econometrics – Winter 2009 – Lecture 1
2. Economics 421 – Econometrics – Winter 2009 – Lecture 2
3. Economics 421 – Econometrics – Winter 2009 – Lecture 3
4. Economics 421 – Econometrics – Winter 2009 – Lecture 4
5. Economics 421 – Econometrics – Winter 2009 – Lecture 5
6. Economics 421 – Econometrics – Winter 2009 – Lecture 6
7. Economics 421 – Econometrics – Winter 2009 – Lecture 7
8. Economics 421 – Econometrics – Winter 2009 – Lecture 8
9. Economics 421 – Econometrics – Winter 2009 – Lecture 9
10. Economics 421 – Econometrics – Winter 2009 – Lecture 10
11. Economics 421 – Econometrics – Winter 2009 – Lecture 11
12. Economics 421 – Econometrics – Winter 2009 – Lecture 12
13. Economics 421 – Econometrics – Winter 2009 – Lecture 13
14. Economics 421 – Econometrics – Winter 2009 – Lecture 14
15. Economics 421 – Econometrics – Winter 2009 – Lecture 15
16. Economics 421 – Econometrics – Winter 2009 – Lecture 16
17. Economics 421 – Econometrics – Winter 2009 – Lecture 17
18. Economics 421 – Econometrics – Winter 2009 – Lecture 18

 

New Economic Papers : Econometrics

Edited by: Sune Karlsson

1. Estimation and Inference by the Method of Projection Minimum Distance
   Òscar Jordà; Sharon Kozicki
2. A Monte Carlo Study for Pure and Pretest Estimators of a Panel Data Model with Spatially Autocorrelated Disturbances
   Badi H. Baltagi; Peter Egger; Michael Pfaffermayr
3. Computationally feasible estimation of the covariance structure in Generalized linear mixed models(GLMM)
   Carling, Kenneth; Alam, Moudud
4. Are there Structural Breaks in Realized Volatility?
   Chun Liu; John M Maheu
5. Least squares volatility change point estimation for partially observed diffusion processes
   Alessandro De Gregorio; Stefano Iacus
6. Is neglected heterogeneity really an issue in logit and probit models? A simulation exercise for binary and fractional data
   Joaquim J.S. Ramalho; Esmeralda A. Ramalho
7. A Metropolis-in-Gibbs Sampler for Estimating Equity Market Factors
   Sarantis Tsiaplias
8. Estimating First-Price Auctions with an Unknown Number of Bidders: A Misclassification Approach
   Yingyao Hu; Matthew Shum
9. A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts
   Ralph D. Snyder; Adrian Beaumont
10. Loss distribution estimation, external data and model averaging
    Ethan Cohen-Cole; Todd Prono
11. Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression
    Kevin D. Hoover; Katarina Juselius; Søren Johansen
12. A Simple Representation of the Bera-Jarque-Lee Test for Probit Models
    Joachim Wilde
13. Structural breaks in point processes: With an application to reporting delays for trades on the New York stock exchange
    Andersson, Jonas; Moberg, Jan-Magnus
14. The Use of Encompassing Tests for Forecast Combinations
    Turgut Kisinbay
15. Identifying the Returns to Lying When the Truth is Unobserved
    Yingyao Hu; Arthur Lewbel
16. Solving Linear Rational Expectations Models with Lagged Expectations Quickly and Easily
    Alexander Meyer-Gohde

New Graduate level econometric textbook online

‘Marshall Jevons’ of the weblog The Bayesian Heresy alerts us to a new graduate-level econometrics textbook, available free online, by Professor Bruce E. Hansen from the University of Wisconsin. Here is a direct link to the PDF (1.2Mb).

Statistical Data Analysis: Prove It with Data

A resource site for statistical data analysis by Dr. Hossein Arsham, Wright Distinguished Research Professor of Management Science and Statistics at the University of Baltimore. It contains a list of useful sites for statistical data analysis, but most interestingly, summaries of information on statistical data modelling, including times series analysis and forecasting techniques, different distributions, sampling, parametric and non-parametric modelling.

Econometrics: Chapter Related Resources

John Kane of Department of Economics, SUNY-Oswego, developed this site. This site is designed to assist users of Econometrics: An Applied Approach and others who are interested in finding econometric resources on the internet. This page will be in better shape when the text is ready for release.

Resources for:

1. Introduction
2. Statistical Foundations
3. Estimators and Distributions
4. Bivariate Regression Model
5. Hypothesis Testing
6. Multiple Regression Model
7. Hypothesis Testing in the Multiple Regression Model
8. Functional Form I: Linearity
9. Functional Form II: Further topics
10. Specification and Measurement Error
11. Multicollinearity
12. Autocorrelation
13. Heteroskedasticity
14. Limited Dependent Variables
15. Systems of Equations
16. Distributed lag models
17. Random walks, unit roots, and cointegration
18. ARIMA Models

Applied Econometrics Supplementary Tutorial

You may be strong enough in econometrics or  you may want to learn the basics with practical example. Then this Tutorial is for you. Site contains numbers of exercise. These free econometrics exercises are linked to chapters of the textbook “Basic Econometrics” by Damodar N. Gujarati, of the Hong Kong Baptist University. They are divided into three parts: Single-Equation Regression Models; Relaxing the Assumptions of the Classical Model; Topics in Econometrics. Useful for lecturers who want some ready-made teaching materials.

Econometrics Journals

This site is connected with the Econometrics Journal, which is run by the Royal Economic Society and is based at Free University, Amsterdam. This is an extensive annotated site, updated monthly. It is divided into sections, among which are: general collections and preprint sites, departments and societies, software links, books, conferences, journals and mailing lists. The alphabetic list of econometrics journals is very extensive, and provides information about what is contained on the journal site (abstracts/full-text).