Econometrics and Programming

Course Overview

This course looks at statistical techniques in cross-sectional, panel and time-series analysis with particular focus on programming applications in the widely used software package R. Students learn how to carry out regression analysis in R and critique the results. The course covers key ideas in econometric theory to empirically evaluate a range of economic concepts and policy suggestions, using cases from around the world.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

Subject Specific Skills

Transferable and Employability Skills

Teaching and Learning

This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage students  in their  studies.
The scheduled teaching and learning activities for this course are:

Lectures/seminars

40 scheduled hours – typically including induction, consolidation or revision, and assessment activity hours.

Version 1:all sessions in the same sized group

OR

Version 2: most of the sessions in larger groups; some of the sessions in smaller groups

Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups. 

Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.

Dedicated mathematics support will be available to all students during teaching weeks.

Indicative total learning hours for this course: 150

Assessment

Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.

Summative Assessments

The course is assessed first by a written assignment, in which students will carry out an in-depth written analysis and use learnt econometric theory to empirically evaluate a meaningful causal relationship of the student’s choice. The examination will require  students to demonstrate their command of writing for both Economics specialists and non-specialists. and test students’ understanding of key concepts taught during the course and their ability to solve theoretical problems Further information about the assessments can be found in the Course Syllabus

Feedback

Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).

Indicative Reading

Note: Comprehensive and current reading lists are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is for a general guide and part of the approval/modification process only.

• Theory: Woolridge, J. (2009) Introductory Econometrics.
• Programming (optional): Gujarati, D. (2014), Econometrics by Example, Basingstoke: Palgrave Macmillan.

Indicative Topics

Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below is used as a general guide and part of the approval/modification process only.

• Linear Regression
• Sources of Endogeneity
• Panel Data Analysis
• Time series Analysis