Module Code - Title:
EC4307
-
ECONOMETRICS
Year Last Offered:
2026/7
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
This module provides an introduction to the theory and practice of econometrics using cross-sectional and time series data sets. The module concentrates on linear models and focuses on how the techniques can be applied in practice rather than taking a theory based approach. The essential purpose of the module is to meet the main empirical research needs of students who typically do not intend to specialise in econometric theory. However, the module also serves as a preparation for students who wish to proceed to more advanced econometrics courses.
Syllabus:
Introduction to econometrics; regression analysis; method of Ordinary Least Squares (OLS); the Classical Linear Regression Model; properties of OLS estimators - Gauss-Markov theorem; interval estimation and hypothesis testing; multiple regression analysis; heteroscedasticity; autocorrelation; multicollinearity; dynamic econometric models - autoregressive and distributed-lag models; time series econometrics (including stationarity, unit roots and cointegration).
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On completion of this module, students should be able to:
Formulate suitable econometric models for the empirical study of economic phenomena
Analyse economic data using appropriate models and methods using statistical software
Interpret the results of econometric analysis and test hypothesis
Present the estimated economic relationships verbally, graphically, and through equations.
Affective (Attitudes and Values)
On successful completion of this module, students should be able to:
Show a commitment to the value of empirical evidence in economic analysis by engaging critically and responsibly with real‑world data, upholding accuracy, transparency, and methodological integrity in applied econometric practice, and demonstrating openness to the deeper analytical challenges required for advanced study.
Psychomotor (Physical Skills)
N/A
How the Module will be Taught and what will be the Learning Experiences of the Students:
This module will be taught through a combination of lectures and practical computer laboratory classes, as well as private study hours. Students are expected to take responsibility for their own independent learning, and should be pro-active in their engagement with the learning materials. To promote self-learning and learning-by-doing, continuous assessment is built into the module. The learning experience includes the formulation and technical (mathematical and econometric) specification of research design, data sourcing, econometric software, results generation and interpretation as well as a demonstrated review of relevant analytical and empirical economics literature.
Prime Texts:
Gujarati, D. and D. Porter (2009)
Basic Econometrics, 5th edition
, McGraw-Hill
Other Relevant Texts:
Asteriou, D. and S. G. Hall (2021)
Applied Econometrics, 4th edition
, Macmillan International
Wooldridge, J. M. (2025)
Introductory Econometrics: A Modern Approach, 8th edition
, Cengage Learning
Programme(s) in which this Module is Offered:
BACHELOR OF ARTS IN ECONOMICS AND SOCIOLOGY
BACHELOR OF ARTS IN INTERNATIONAL BUSINESS
BACHELOR OF BUSINESS STUDIES
BACHELOR OF BUSINESS STUDIES WITH FRENCH
BACHELOR OF BUSINESS STUDIES WITH GERMAN
BACHELOR OF BUSINESS STUDIES WITH JAPANESE
BACHELOR OF BUSINESS STUDIES WITH SPANISH
BACHELOR OF SCIENCE IN ECONOMICS AND MATHEMATICAL SCIENCES
BACHELOR OF SCIENCE IN ECONOMICS AND MATHEMATICS
Semester(s) Module is Offered:
Autumn
Module Leader:
Declan.Dineen@ul.ie