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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Econometrics and Forecasting
Module Code EF308
School DCUBS
Module Co-ordinatorSemester 1: Michael Dowling
Semester 2: Michael Dowling
Autumn: Michael Dowling
Module TeachersMichael Dowling
NFQ level 8 Credit Rating 5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None

The purpose of this module is to introduce students to basic regression methods that are used in analyzing social science data. The emphasis is on the application of statistical methods to analyze economic and/or financial data. In this module students will develop knowledge and skills in applying statistical methods to analyze data, using appropriate statistical software to analyze data, using regression models to test hypotheses, making and evaluating predictions based on statistical models. Students will participate in the following learning activities: attend and participate in lectures, familiarize themselves with the use of statistical software, work on take home assignments that replicate some previous empirical research, critically evaluate some of the literature in empirical research.

Learning Outcomes

1. carry out basic statistical inference procedures using regression models
2. use statistical software to produce and evaluate forecasts of real economic time series data
3. select appropriate econometric techniques to analyse particular data sets
4. evaluate empirical statistical work and critically assess econometric approaches
5. explain how to produce and evaluate forecasts using time series models

Workload Full-time hours per semester
Type Hours Description
Lecture20Lecture and discussion
Directed learning20Labs and computer work
Assignment Completion35Take home assignments
Independent Study50Readings and review of lectures; online learning exercises
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

Introduction to econometrics
review of statistical inference, data and data types, simple linear regression, hypothesis testing, dummy variables, the classical Linear Model.

Using econometric models
tests of model specification, multicollinearity, heteroscedasticity, serial correlation, stochastic regressors

Topics in time series econometrics
stationarity, cointegraton and error correction models, Granger causality, ARCH & GARCH, forecasting using regression and ARIMA models

Assessment Breakdown
Continuous Assessment100% Examination Weight0%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentComplete two worksheets100%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
This module is category 1
Indicative Reading List

  • Stock, James H; Watson, Mark W: 0, Introduction to econometrics,
  • Jeffrey M Wooldridge: 0, Introductory Econometrics,
Other Resources

Programme or List of Programmes
AFBA in Accounting and Finance
BSBachelor of Business Studies
BSEBachelor of Business Studies (Exchange)
BSIBusiness Studies ( with INTRA )
BSSAStudy Abroad (DCU Business School)
BSSAOStudy Abroad (DCU Business School)
EBBA in Global Business
EBCBA in Global Business (Canada)
EBFBA in Global Business (France)
EBGBA in Global Business (Germany)
EBSBA in Global Business (Spain)
EBTBA in Global Business (USA)
ECSAOStudy Abroad (Engineering & Computing)
HMSAStudy Abroad (Humanities & Soc Science)
HMSAOStudy Abroad (Humanities & Soc Science)
INTBBachelor Business Studies International
SHSAStudy Abroad (Science & Health)
SHSAOStudy Abroad (Science & Health)
Date of Last Revision23-SEP-11

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