GRA 6648 Research Methodology - Economics

GRA 6648 Research Methodology - Economics

Course code: 
GRA 6648
Department: 
Economics
Credits: 
6
Course coordinator: 
Hilde Christiane Bjørnland
Product category: 
Master
Portfolio: 
MSc - Core course
Semester: 
2018 Spring
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

This course is a graduate level introduction to Econometrics.

Learning outcomes - Knowledge

Students will learn to use statistical methods for estimating economic relationship, testing economic theories, and using estimated models to analyze the effect of policy intervention for the public and the private sector.

Learning outcomes - Skills

The students will learn about the main estimation methods, using both time series and panel data. Projects using Big data will also be introduced. The students will learn details about time series econometrics with applications in macroeconomics and international finance. They will master univariate and multivariate models of stationary an non stationary time series, including structural VARs. Panel data techniques is covered, as well as the difference in difference methodology. In the end, they should be able to design applied econometric projects.

The students will also learn information search strategies. That is, acquaintance with methods for information search and know what a critical literature review is.

Learning Outcome - Reflection

Students should be able to reflect and understand the basic techniques used in applied econometrics, so that eventually they can master and produce sophisticated applied econometric analysis.

Course content

I Data Management

  • Traditional data (time series and panel data)
  • Big data
  • Data reduction
  • Web scraping

II Time series – Stationary and non-stationary univariate time series

  • White noise, moving average, autoregressive models
  • Forecasting
  • Deterministic and stochastic trends, unit roots, structural change
  • Applications

III Vector autoregression (VAR) methodology

  • Structural VARs specification and estimation
  • Identification, impulse responses, variance decomposition
  • Spurious regression and log run economic relationships
  • Applications

IV Panel data analysis

  • Difference in difference methodology
  • Fixed effects
  • Applications

V Introduction to information search strategies (3 hours in the pc-lab)

  • Acquaintance with methods for information, harvesting and search techniques
  • Know what a critical literature review is and how this type of articles may be searched for and used
  • Critical evaluation of sources

VI Setting up an econometric project

  • Research ethics, data handling, specification, modeling, policy analysis
Learning process and requirements to students

Lectures and practical exercises that must be solved on the computer.

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class that is not included on the course homepage/It's learning or text book.

This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course start.

At resit, all exam components must, as a main rule, be retaken during next scheduled course.

Software tools
Matlab
Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Activity
Form of assessment:
Presentation
Exam code:
GRA66486
Grading scale:
Point scale
Grading rules:
Internal examiner
Resit:
All components must, as a main rule, be retaken during next scheduled course
20No -Group (4 - 6)
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA66486
Grading scale:
Point scale
Grading rules:
Internal examiner
Resit:
All components must, as a main rule, be retaken during next scheduled course
10No 1 Week(s)Group/Individual ( 1 - 3)Library assignment
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA66486
Grading scale:
Point scale
Grading rules:
Internal and external examiner
Resit:
All components must, as a main rule, be retaken during next scheduled course
70Yes3 Hour(s)
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Individual Final written examination with supervision
Exams:
Exam category:Activity
Form of assessment:Presentation
Weight:20
Invigilation:No
Grouping (size):Group (4-6)
Support materials:
Duration: -
Comment:
Exam code:GRA66486
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:10
Invigilation:No
Grouping (size):Group/Individual (1-3)
Support materials:
Duration: 1 Week(s)
Comment:Library assignment
Exam code:GRA66486
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:70
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Duration:3 Hour(s)
Comment:Final written examination with supervision
Exam code:GRA66486
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam organisation: 
Continuous assessment
Grading scale: 
ECTS
Total weight: 
100
Talis literature

Obligatorisk/Compulsory

Book
Authors/Editors År Tittel Edition Publisher StudentNote
Bjørnland, Hilde Christiane; Thorsrud, Leif Anders 2015 Applied time series for macroeconomics 2. utg Gyldendal akademisk  
Chapter
Authors/Editors År Tittel Journal Edition Publisher StudentNote
Saunders, Mark   Critically reviewing the literature Critically reviewing the literature      
Angrist, Joshua D.; Pischke, Jörn-Steffen cop. 2009 Mostly harmless econometrics: an empiricist's companion Mostly harmless econometrics: an empiricist's companion   Princeton University Press Ch. 5
Document
Authors/Editors År Tittel Edition Publisher StudentNote
    Collection of articles     Articles supplementing the books will be suggested. These can be downloaded from the library.
    During the course there may be hand-outs and other material on additional topics relevant for the course and the examination.      

Anbefalt/Recommended

Book
Authors/Editors År Tittel Edition Publisher StudentNote
Favero, Carlo A. 2001 Applied macroeconometrics   Oxford University Press chapters 1,2,3 and 6
Greene, William H. cop. 2012 Econometric analysis 7th ed., International ed Pearson  
Chapter
Authors/Editors År Tittel Journal Edition Publisher StudentNote
Christiano, L.J.; Eichenbaum, M.; Evans, C.L.   Monetary policy shocks : what have we learned and to what end? Monetary policy shocks : what have we learned and to what end?