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Module Specifications..

Current Academic Year 2024 - 2025

Please note that this information is subject to change.

Module Title
Module Code
School
Module Co-ordinatorSemester 1: Ann Largey
Semester 2: Ann Largey
Autumn: Ann Largey
Module TeachersAnn Largey
NFQ level 8 Credit Rating
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
None
Description

This module builds on the quantitative stream of the BSIF degree programme. In particular it extends the material covered in Econometrics 1, honing the skills required in multivariate regression analyses. You will learn how to identify and deal with problems that arise in practice when working with regression models, eg choice of functional form, non-adherence to Gauss Markov assumptions and interpretation of results. You will also start to work with more advanced discrete choice models that require MLE estimation. The course will involve practical data analysis using STATA and students will submit an independent group project involving analysis of data and interpretation of results

Learning Outcomes

1. Identify and correct for common problems in practical regression analysis and issues arising from non-adherence to Gauss Markov assumptions
2. Select appropriate econometric techniques to analyse continuous and discrete dependent variables
3. Conduct econometric analysis using STATA and comment on results
4. Evaluate empirical statistical work and assess econometric approaches



Workload Full-time hours per semester
Type Hours Description
Lecture28No Description
Laboratory12STATA practical sessions
Assignment Completion20Individual assignments
Assignment Completion30Group project
Independent Study35No Description
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Revision of Multivariate Regression theory
Review of semester 1 including exam questions

Introduction to STATA
Basic STATA commands

Common Practical Issues in Multivariate Regression
Specification Issues and Functional form, Multicollinearity, Use of Dummy Variables

Non-adherence to GM assumptions
Heteroscedasticity Autocorrelation Stochastic Regressors

Limited Dependent Variables
Logit/probit Ordered probit Multinomial logit

Assessment Breakdown
Continuous Assessment% Examination Weight%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentTake home individual assignment20%Week 4
AssignmentIndividual assignment20%n/a
Written ExamIn class test30%n/a
Group assignmentGroup project - Independent term paper30%n/a
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
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Indicative Reading List

    Other Resources

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