Macroeconometrics
Module Code: ECP77432
- ECTS Credit: 10
- Mandatory/Optional: Mandatory
- Semester/Term Taught: Hilary Term
- Module Coordinator: Professor Cian O'Shea
Aims of Module
This module provides students with an introduction to the theory and practice of modern econometrics, with the primary focus on answering macroeconomic questions through data. The module builds on the fundamental concepts developed in the microeconometrics module and aims to extend students’ understanding of the subject to a more advanced level. The module will include topics on instrumental variables, simultaneous equation models, and stationary time-series models.
Learning Outcomes
On completion of the module, students will be able to:- Understand and discuss the identification problem in economics.
- Understand the fundamental methods of econometrics analysis.
- Estimate models using instrumental variables and two-stage least squares.
- Perform time-series analysis.
- Construct, estimate, and test econometric models using time-series or panel data.
- Formulate relevant research questions and econometrics models.
- Use statistical software to estimate econometric models.
Module Content
Topics covered in this module will include:
- Introduction to Time series regression and forecasting
- Autoregressive Models
- Vector Autoregressions
- Multivariate Regression
- Generalised Least Squares
- Instrumental Variables
Recommended Reading List
Primary Texts
- Enders, W. (2014), Applied Econometric Time Series, Wiley.
- J.M. Wooldridge, Introductory Econometrics: A Modern Approach, 7/e, Cengage, 2020
- Stock, J.H. and M.W. Watson. Introduction to Econometrics, Pearson (4e), 2019.
Secondary Reading
- Angrist, J.D. and Pischke, J. Mastering Metrics, Princeton University Press, 2015
- Huntington-Klein, N. The Effect, The Effect: An Introduction to Research Design and Causality, Routledge, 2021
Module Pre-Requisite
ECP77403: Introduction to Statistics and Regression Analysis
ECP77321: Microeconometrics
Assessment
The module will be assessed through a mixture of continuously assessed coursework and the final project.
Module Website
Blackboard