Module code: ECOD022

Module Overview

The module introduces topics on recent developments in Econometrics. In particular: (i) spatial econometrics and network formation (ii) quantiles and mode regression, (ii) structural econometrics.

Module provider


Module Leader

CORRADI Valentina (Economics)

Number of Credits: 0

ECTS Credits: 0

Framework: FHEQ Level 8

JACs code: L140

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

Indicative content includes:

  • Spatial Econometrics

  • Econometrics of Networks

  • Quantile Regression

  • Mode Regression

  • Auction Models

  • Econometrics of Games

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Coursework (Problem Sets and Take Home Examination) 100

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their technical skills relating to the use of econometrics techniques to do innovative empirical work.


Thus, the summative assessment for this module consists of:


Problem sets and Take Home Examination, typically including a computer exercise.


Formative assessment

Due to the limited size of the cohort and the level of study , formal formative assesment is replaced with informal discussions during and outside lectures.

Module aims

  • To provide an overview of frontier topics in econometrics
  • To provide a guidance of possible topics for students interested in pursuing doctoral research Econometric Theory or Applied Econometrics
  • To enable students to conduct independent research in econometrics and its application

Learning outcomes

Attributes Developed
001 To reproduce the result of key papers CP
002 To engage in innovative research in structural economics/econometrics KCPT
003 To produce methodological contribution KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Overall student workload

Independent Study Hours: 128

Lecture Hours: 22

Methods of Teaching / Learning

The learning and teaching strategy is designed to: develop students’ independent research skills, by training them to effectively conduct critical analysis of papers in scientific journals. Problems set are assigned to ensure all concepts and methods are properly mastered.


The learning and teaching methods include:


Interactive lectures and class discussion

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list


Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2019/0 academic year.