¹û¶³Ó°Ôº

XClose

¹û¶³Ó°Ôº Module Catalogue

Home
Menu

International Trade (ECON0023)

Key information

Faculty
Faculty of Social and Historical Sciences
Teaching department
Economics
Credit value
15
Restrictions
Final year Economics (L100 / L101 / L102), BSc Economics and Geography (LL17), BSc Economics and Statistics (LG13), BA Philosophy and Economics (VL51), PPE (Philosophy, Politics and Economics (4V86 ) and BASc students subject to satisfying the pre-requisites. Prerequisites:ÌýECON0013 MicroeconomicsÌýand ECON0019 Quantitative Economic &Ìý Econometrics modules or any ofÌýPOLS0008: Introduction to Quantitative Research Methods,ÌýÌýPOLS0010: Data Analysis, POLS0012: Causal Analysis in Data Science or POLS0013: Measurements in Data Science.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

Aims: To provide students with a framework for understanding modern ideas in the theory of international trade; to use this framework to analyse the major policy issues of world trade.

Suitable for: Final year Economics (L100 / L101 / L102), BSc Economics and Geography (LL17), BSc Economics and Statistics (LG13), BA Philosophy and Economics (VL51), PPE (Philosophy, Politics and Economics (4V86 ) and BASc students subject to satisfying the pre-requisites.

Prerequisites: Completion of ECON0013 Microeconomics and ECON0019 Quantitative Economic & Econometrics modules or any of POLS0008: Introduction to Quantitative Research Methods, POLS0010: Data Analysis, POLS0012: Causal Analysis in Data Science or POLS0013: Measurements in Data Science.Ìý

Assumed knowledge: Students coming into the course should understand concepts relating to profit maximisation under different market structures particularly perfect competition and monopolistic competition, consumer theory, supply and demand analysis, welfare effects of taxes and subsidies and other interventions in the market, basic game theory and the concept of a Nash equilibrium, and an understanding of how to interpret regression models (including with dummy variables and fixed effects).

Module deliveries for 2024/25 academic year

Intended teaching term: Term 1 ÌýÌýÌý Undergraduate (FHEQ Level 6)

Teaching and assessment

Mode of study
In Person
Methods of assessment
35% In-class activity
65% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
174
Module leader
Mr Lucas Conwell
Who to contact for more information
r.maskell@ucl.ac.uk

Last updated

This module description was last updated on 19th August 2024.

Ìý