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Identical coursesEconometric Methods and Models (B-KUL-D0Q46A)
Aims
The aim of this course is to acquaint students with practical skills and a solid understanding of a wide range of commonly used econometric models and techniques for the analysis of panel data, time series and cross-sectional data used in contemporaneous empirical economic research.
The emphasis is on a practical understanding of the models and methods, and how to apply them. After following this course, students should be able to:
· have a good working knowledge of the key properties of standard methods of estimation (including OLS, IV, ML, GMM)
· be able to apply this estimation methods in a variety of models (linear models, models with endogeneity, discrete choice models, sample selection models, linear panel data models, differences-in-differences models, and time series models for prediction of economic time series and its variance);
· correctly interpret and critically evaluate the empirical results in those applications
· correctly apply these methods to empirical data sets using econometric software.
Previous knowledge
• a first course in econometrics (in particular, the linear regression model), at the level of Stock and Watson (2011), Introduction to econometrics, or Wooldridge (2009), Introductory Econometrics: A Modern Approach;
• some experience with an econometric software package such as Stata or EViews;
• a working knowledge of basic concepts in statistics and mathematics (calculus, linear algebra).
Identical courses
This course is identical to the following courses:
D0C09A : Econometric Methods and Models (No longer offered this academic year)
Is included in these courses of study
- Master of Economics (Leuven) 60 ects.
- Master in de economische wetenschappen (Leuven) 60 ects.
- Master handelsingenieur (Leuven) 120 ects.
- Master handelsingenieur (Leuven) (Minor: Economie) 120 ects.
- Master in de bio-ingenieurswetenschappen: landbouwkunde (Leuven) (Major bio-economie en beleid) 120 ects.
- Master of Business Engineering (Leuven) 120 ects.
- Master of Business Engineering (Leuven) (Minor: Economics) 120 ects.
- Master of Bioscience Engineering: Agro- and Ecosystems Engineering (Leuven) (Major Subject: Agricultural and Resource Economics) 120 ects.
- Courses for Exchange Students Faculty of Economics and Business (Leuven)
Activities
3 ects. Micro-econometric Models (B-KUL-D0C24a)
Content
Identifying causal relationships among variables is a key part of econometrics. These causal relationships may involve linear relationships but also discrete or censored outcome variables. Examples of these non-linear relationships can be found in many economics questions and fields, for example labor economics (the decision to work and hours worked), consumer demand (choices between different products), or investment theory (a firm’s investment and location choices). This course introduces students to the discussion of causality and the challenges of identification, different methods of estimation of models (OLS, IV, 2SLS, GMM and Maximum Likelihood) and its applications in linear models and non-linear models with discrete or censored dependent variables and selected samples.
Course material
Communication via Toledo
3 ects. Dynamic models and panel data (B-KUL-D0Q46a)
Content
Many datasets include also the time dimension, so we observe one or more economic agents over time. This feature opens the possibility of alternative specifications to allow for different causal relationships and the use of identification variation. Additionally, sometimes we do not have the cross-sectional dimension but only the times series dimension, and we are interested in using the data to predict either the level or the variance of a particular variable. Upon completion of this course, the student will be able to specify, estimate, and evaluate regression models with panel data and time series data, in order to forecast and quantify dynamic causal effects. The concepts in time series regressions include: lags and serial correlations, first differences, growth rates, autoregression, point forecasts and interval forecasts, deterministic vs. stochastic trends, unit roots and cointegration. The concepts in panel data regressions include: panel data estimation, random and fixed effects models, difference-in-differences identification and clustering of standard errors.
Course material
Communication via Toledo
Evaluation
Evaluation: Econometric Methods and Models (B-KUL-D2Q46a)
Explanation
Evaluation characteristics:
The exam is a written, closed-book exam. Students may use a pocket (not programmable) calculator. The exam is graded over 20 points. In addition, there are six take-home exercises, graded as follows: +1 point for 6 exercises handed in, 0 points for 1 to 5 exercises handed in, and -1 point for zero exercises handed in.
Determination of the end result:
If a student does not participate in the exam, he/she receives NA (not participated) for the whole course. The final grade is the sum of the grade of the exam plus any potential extra point obtained from handing in the exercises
Information about retaking exams
The features of the evaluation and determination of grades are identical to those of the first examination opportunity, as described in the tab 'Explanation'.