Econometrics 2.

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Level: 
Master's
Course Status: 
Core
CEU code: 
ECON 5011 - Econometrics II
CEU credits: 
5
ECTS credits: 
10
Term: 
1st
Academic year: 
2009/2010
Academic year: 
2010/2011
Semester: 
Winter
Host Unit: 
Department of Economics
Academic Program: 
Master of Arts in Economics
Master of Arts in Economic Policy in Global Markets
CEU Instructor(s): 
Gábor Kézdi
Additional information: 
Course outline Week 1 Review of regression. Carrying out an empirical project. Term paper topic Chapter 19 Week 2 Specification and data problems. Proxy variables, measurement error. Chapter 9. Week 3 Introduction to time-series analysis: Stationarity, trends, seasonality. Chapters 11.1, 10.1, 10.5. Week 4 Introduction to time-series analysis: Specific univariate series. Chapter 11. Week 5 Regression on time-series data. Chapter 12. Week 6 Panel data methods: Pooled cross-sections, difference in differences Chapter 13 Week 7 Panel data methods: Fixed effects and random effects Chapter 14 Week 8 Instrumental variables: Identification. Chapter 15 Week 9 Instrumental variables: Estimation. Weak instruments. Chapter 15 Week 10 Probability models Chapter 17.1 Week 11 Corner solution and censored models Chapter 17.2, 17.4. Week 12 Summary and review
Learning Outcomes: 
Successful completion of the course enables students to Understand how econometric methods are used to estimate causal relationships from observational data. Possess a critical understanding of identification and estimation problems in economics and other social sciences. Formulate simple research questions and carry out independent analyses in order to answer those. Understand and evaluate the identification and estimation strategy of simpler papers, whether academic publications or applied works Argue for and against endogeneity of right-hand side variables. Prove consistency or find asymptotic bias of estimators. Understand the logic of sampling variance and distribution of estimators. Understand the role of stationarity and know various deviations from it. Understand the properties of specifict time-series. Carry out simple hypothesis tests in linear and non-linear models. Use econometric software in simple applications. Estimate the models covered in the course, and interpret their results. Write a short empirical paper around one’s own research question.
Assessment : 
Grading 20% from problem sets 20% from term paper 60% from final exam Formative assessment Individual consultations about the term paper
Full description: 

Econometrics 2 provides the basic tools of applied econometric analysis. The course is based on regression
analysis (covered in Econometrics 1), and it gives a thorough introduction to the problem of endogeneity with
possible treatments, time series regressions, linear panel models, and nonlinear probability and censoredoutcomes
models.