BSc Global Development with International Study

Year of entry: 2024

Course unit details:
Further Statistical Methods for Global Development

Course unit fact file
Unit code MGDI30802
Credit rating 20
Unit level Level 3
Teaching period(s) Semester 2
Available as a free choice unit? No

Overview

The further statistics course unit builds on the intermediate statistics course unit. Its main aim is to ensure that students have (i) all of the generic skills necessary for an undergraduate dissertation which is rich in quantitative methods, and (ii) the ability to find information about additional statistical tools and to apply these tools in appropriate way.

Pre/co-requisites

Unit title Unit code Requirement type Description
Intermediate Statistical Methods MGDI20251 Pre-Requisite Compulsory

Aims

The unit builds on Intermediate Statistical Methods (MGDI20251), providing students with a grounding in techniques that can be used for the statistical analysis of time series and longitudinal data. The unit finishes with a section designed to equip students for lifelong statistical learning

Syllabus

Weeks 1-2: recap on binary outcomes and discrete choices (Greene chapter 17)

Weeks 3-4: multinomial choices and event counts (Greene chapter 18)

Weeks 5-6: introduction to time-series analysis (Greene chapter 20)

Weeks 7-8: cointegration and multivariate times-series modelling (Greene chapter 21)

Weeks 9-10: lifelong statistical learning

Teaching and learning methods

Teaching and learning will be based on lectures (twice per week) and hands-on classes (once per week). Lectures will combine presentation of the learning material with some interactive discussion. Reading lists, lecture slides and tutorial questions will be posted on Blackboard. Classes will provide students with the opportunity to grapple with data under with guidance from a tutor. Advice on how to prepare for each class will be posted on Blackboard.

Knowledge and understanding

  • Select longitudinal statistical methods that are appropriate, given the characteristics of their data
  • Identify the main properties of time series relevant to statistical analysis

Intellectual skills

  • Evaluate choices about statistical model selection in the context of longitudinal and time-series data
  • Critically analyse results from the estimation of time-series and panel data models

Practical skills

  • Use Stata to fit a longitudinal model appropriate to the data
  • Analyse the characteristics of a time series using Stata
  • Use Stata to fit a time-series model appropriate to the data

Transferable skills and personal qualities

  • Search effectively for literature on a statistical problem novel to them
  • Manage data using Stata

Assessment methods

  1. First draft of assignment 1, a report based on an analysis of a longitudinal dataset. (1,000 words) (Formative - no weighting)
  2. Second draft of assignment 1. (1,000 words) (weighting 35%)
  3. Assignment 2, a report based on an analysis of a time-series dataset. (1,000 words) (weighting 35%)
  4. Assignment 3, a short essay evaluating the statistical methods appropriate for a dataset with properties new to the student. (1,000 words) (weighting 30%)

Feedback methods

Written comments via Blackboard.

Recommended reading

William H. Greene (2017) Econometric Analysis (8th edition), Pearson: New York, NY

Study hours

Scheduled activity hours
Lectures 20
Practical classes & workshops 10
Independent study hours
Independent study 170

Teaching staff

Staff member Role
David Fielding Unit coordinator

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