AØKA08084U Advanced Microeconometrics

Volume 2014/2015
Education
MSc in Economics
Content

The overall purpose of the course is to provide a fundamental understanding of microeconometric methods and their application. These methods consist of behavioral models and statistical techniques to estimate these models.


The course will cover the following methods of estimation:

  • Linear panel data models (Chapter 10-11)
  • Non-linear estimation methods (Chapter 12-14)
  • Non-parametric estimation methods (Lecture notes)
  • Discrete response models (Chapter 15-16)
  • Corner solution models (Chapter 17)
  • Censored data and sample selection models (Chapter 19)
  • Treatment effects (Chapter 21)


The course consists of a series of lectures and exercise classes. The lectures focus on theory whereas the class provides a hand on knowledge of estimation of the models.

Learning Outcome

Through their completion of the course, students should acquire the tools necessary to understand papers and undertake empirical analysis on microeconometric topics. The acquired skills in microeconometric theory and practice provide a strong background that enable students to do empirical analyses at a high level suitable for the master thesis, but also relevant for answering empirical economic questions that could be encountered in a government agency or in the private sector.


The purpose of the lectures and the exercise classes is that the student should

  • acquire knowledge about estimation methods
  • be able to review linear cross section and panel data models, and nonlinear models for discrete dependent variables, censored dependent variables and sample selection.
  • be able to give an account of how these techniques are applied to quantify effects of public policies.
  • be able to give an account of how such models are applied appropriately within different sampling schemes.

 

To obtain the maximum grade in the part of the course covered by lectures and exercises, students must excel in all of the areas listed above.

A parallel master’s seminar in microeconometrics will be set-up and students following the Advanced Microeconometrics course are encouraged to also taking this seminar. The purpose of the parallel seminar is to make students

  • pose a focused economic research question (inspired, for example, by an already published paper
  • find data that can be used to answer the question
  • estimate relevant models and test hypotheses using methods discussed in the course.
  • program the estimators applied in the paper using MATLAB
  • investigate the properties of the estimators and tests using Monte Carlo techniques
  • present the analysis in a short and focused term paper
  • Disseminate the analysis and discuss empirical strategies at a workshop

 

Students who want to take both the course in Advanced Microeconometrics as well as the master’s seminar, need to sign up for both separately.

 

SyllabusJeffrey Wooldridge (2010), "Econometric Analysis of Cross Section and Panel Data", Second Edition, MIT Press. chapters 10-17, 19 and 21.

 

Pre-requisites are Quantitative Methods 1-3 (Econometrics A-C)
4 hours of lectures and 2 hours of classes per week for 14 weeks.
The course consists of 42 hours of lectures and 24 hours of computer exercises

Note that all lectures and exercise classes are frontloaded in the beginning of the semester to give room for students to focus entirely on the term paper in the associated master’s seminar in microeconometrics.
  • Category
  • Hours
  • Class Exercises
  • 28
  • Exam
  • 1
  • Lectures
  • 56
  • Preparation
  • 121
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Oral examination under invigilation
The assessment is based on an oral exam.
Aid
Written aids allowed
Marking scale
7-point grading scale
Censorship form
External censorship
100 % censorship
Exam period
Will be updated before the start of the semester
Re-exam
Same as ordinary.
Criteria for exam assesment

The Student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.