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Syllabus:

# Econometrics I D12, 7.5 Credits

Swedish name: Ekonometri I D12

This syllabus is valid: 2022-01-03 and until further notice

Course code: 2NE005

Credit points: 7.5

Education level: Second cycle

Main Field of Study and progress level: Economics: Second cycle, has second-cycle course/s as entry requirements

Responsible department: Department of Economics

Revised by: Rector of Umeå School of Business and Economics, 2021-10-28

## Contents

The course covers the fundamental methods and concepts in econometrics, with a focus on: linear regression model, extensions to limited dependent variables (LDVs), notions of causality and endogeneity in econometrics and its simplest implementations in the Instrumental Variables (IV) and Difference-in-Difference frameworks. The role of basic assumptions for estimation, model specification and statistical inference are studied in the context of these models. The estimation frameworks emphasized are Least Squares (LS), including Generalized Least Squares (GLS), and Maximum Likelihood (ML). Fundamental tools of estimation and inference are developed in these frameworks, and applied to specific models. For many frameworks, including the linear LS case, the consequences for estimation and statistical inference of frequently appearing deviations from the standard assumptions are also considered. Some of the introduced concepts and frameworks will be illustrated with simple applications using Stata. The course will conclude with a brief introduction to specific methods for panel data or for dealing with endogeneity.

## Expected learning outcomes

After completing the course, students will be able to:

• Demonstrate an understanding of the fundamental concepts in econometrics, including: notions of causality and endogeneity, understanding estimation frameworks as well of testing between competing hypotheses;
• Demonstrate an understanding of the concepts, and use, of different goodness of fit measures along with their drawbacks;
• Evaluate and summarize an empirical study conducted by another person/researcher; and
• Be able to perform regressions and data analysis, including but not limited to: linear LS, ML-based probit/logit and Poisson models, and IV models; and to be able to understand and interpret the results and to test a variety of simple hypotheses.

## Required Knowledge

90 credits of which 75 credits in economics including 15 credits bachelor courses (G2F). Additionally, Mathematical Economics I D7 or the equivalent. Proficiency in English equivalent to the Swedish upper secondary course English 6.

## Form of instruction

The course is offered in the form of lectures, but there may be and seminars and exercise sessions.

## Examination modes

The examination consists of written assignments and a written examination at the end of the course. The results of assignments are valid only during the given semester.

A second exam opportunity is always offered within a short time span after the regular exam date for those students not achieving a Pass. The subsequent exam opportunity is either the re-take opportunity the week before the fall semester or the next regular exam date.

The following grading system will be used: Pass with Distinction (Väl godkänd), Pass (Godkänd) and Fail (Underkänd).

It is normally not possible to do additional examinations to reach a higher grade. Exceptions can be made for a student with the grade Fail on any of the examinations if the examiner (not the lecturer) finds this appropriate. The task must be a minor undertaking, closely related to the learning outcome not reached, and performed in close proximity to the original examination.

When a student has failed an examination on two occasions, he or she has a right to have another grading teacher. A written request for an alternative examiner should be handed to the Dean of the Business School.

Credit transfer
Academic credit transfers are according to the University credit transfer regulations.

## Literature

### Valid from: 2022 week 1

Greene William H.
Econometric analysis
7. ed. : Boston : Pearson : cop. 2012 : 1228 s. :
ISBN: 9780273753568 (pbk.)
Search the University Library catalogue