Předmět Econometrics I (JEB109)

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Materiál	Typ	Datum	Počet stažení

Cíl

The main aim of the course is to train students to be able to properly analyze a cross-sectional dataset using the OLS framework, construct models, and interpret the results as well as to prepare them for further Econometrics courses.

Sylabus

WEEK #1:- Course information- Statistics review- Steps Empirical Economic Analysis- Structure of Economic Data- Causality and Ceteris Paribus NotionWEEKS #2 - #4:- Simple regression analysis- Multiple Regression- Derivation of the Ordinary Least Squares (OLS) Estimates- Properties of OLS- Units of Measurement and Functional Form- Expected Values and Variances of the OLS Estimators- Interpretation of OLS- Efficiency of OLS: The Gauss-Markov TheoremWEEKS #5 - #6:- Sampling Distribution of the OLS Estimators- Testing Hypotheses: The <i>t</i> Test- Confidence Intervals- Testing Multiple Linear Restrictions: The <i>F</i> Test- Reporting Regression Results- Consistency- Asymptotic Normality and Large Sample Inference- Asymptotic Efficiency of OLSWEEK #7:- MIDTERM EXAMWEEKS #8 - #10:- Effects of Data Scaling on OLS Statistics- More on Functional Form- Goodness-of-Fit and Selection of Regressors- Prediction and Residual Analysis- A Single Dummy Independent Variable- Using Dummy Variables for Multiple Categories- Interactions Involving Dummy Variables- A Binary Dependent Variable: The Linear Probability Model- Interpreting Regression Results with Discrete Dependent VariablesWEEKS #11 - #12:- Consequences of Heteroskedasticity for OLS- Heteroskedasticity-Robust Inference after OLS Estimation- Testing for Heteroskedasticity- Weighted Least Squares (WLS) Estimation- Functional Form Misspecification- Using Proxy Variables for Unobserved Explanatory Variables- Models with Random Slopes- Properties of OLS under Measurement Error- Missing Data, Nonrandom Samples, and Outlying Observations- Least Absolute Deviations (LAD) EstimationWEEKS #13:- Revision

Literatura

CORE TEXT:Jeffrey M. Wooldridge (2012): Introductory Econometrics. A Modern Approach.CENGAGE Learning Custom Publishing, 5th EditionALTERNATIVE (A BIT ADVANCED):Greene, W. H. (1993): Econometric Analysis. Macmillam Press, NewYork.Baltagi, B. H. (1999): Econometrics. Springer, Berlin.Jeffrey M. Wooldridge, J. M. (2001):Econometric Analysis of Cross Section and Panel Data. MIT Press,Cambridge, Massachusetts, second edition 2008.Judge, G. G., W. E. Griffiths, R. C. Hill, H. T.C. Lee (1982):Introduction to the Theory and Practice of Econometrics. New York:J.Wiley & Sons. (any other book, our library or library of CERGE)

Požadavky

The final grade consists of three ingredients:- Midterm: 20- Home assignments: 15 (2*7.5)- Final exam: 65Grading scale:- A: above 80 (inclusive)- B: between 70 (inclusive) and 80 (not inclusive)- C: between 60 (inclusive) and 70 (not inclusive)- F: below 60- Necessary condition to pass: at least 33 points from the final exam Midterm exam: 1.4.2015, 15:30 - 16:50, rooms 109 & 206Final exam:- Pre-term: 18.5.2015, 9:30 - 11:00, room 109- Term 1: 2.6.2015, 9:30 - 11:00, room 109- Term 2: 15.6.2015, 9:30 - 11:00, room 109- Term 3: 29.6.2015, 9:30 - 11:00, room 109

Garant

PhDr. Ladislav Krištoufek, Ph.D.prof. RNDr. Jan Ámos Víšek, CSc.