Further Statistical Methods for Global Development

MGDI30802 Further Statistical Methods for Global Development 20 Semester 2 Undergraduate Level 3 David Fielding Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Last part of a Bachelors ' European Credit Transfer & Accumulation System Rating : 10.0 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. 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. There are three parts to the course.Weeks 1-4: panel data. This part of the course introduces methods used to analyze longitudinal data. Key components of this section include (i) understanding variation across different dimensions of the panel, (ii) understanding how the relative sizes of these dimensions determine which methods are appropriate, (iii) analyzing dynamics using panel data, and (iv) analyzing panels incorporating limited dependent variables.Weeks 5-8: time-series modelling. This part of the course introduces basic concepts in time-series statistics, focusing on (i) how to conceptualize dynamic processes, and (ii) the ways in which we can modify statistical tests and modelling techniques to allow for the fact that a time series is not a random sample. The aim is to give students some appreciation of the statistical theory underpinning time-series concepts such as stationarity, integration and co-integration, but also to develop an intuitive understanding of how these concepts can be sensibly applied to data from the Global South.Weeks 9-10: lifelong statistical learning. This part of the course provides an introduction to ways in which students can learn independently about methods to deal with non-standard statistical problems.Throughout the course, examples will use data from the Global South. 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 <ul> <li>Select longitudinal statistical methods that are appropriate, given the characteristics of their data</li> <li>Identify the main properties of time series relevant to statistical analysis</li></ul> <ul> <li>Evaluate choices about statistical model selection in the context of longitudinal and time-series data</li> <li>Critically analyse results from the estimation of time-series and panel data models</li></ul> <ul> <li>Use Stata to fit a longitudinal model appropriate to the data</li> <li>Analyse the characteristics of a time series using Stata</li> <li>Use Stata to fit a time-series model appropriate to the data</li></ul> <ul> <li>Search effectively for literature on a statistical problem novel to them</li> <li>Manage data using Stata</li></ul> 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 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. 0 Other 100% <ol> <li>First draft of assignment 1, a report based on an analysis of a longitudinal dataset. (1,000 words) (Formative - no weighting)</li> <li>Second draft of assignment 1. (1,000 words) (weighting 35%)</li> <li>Assignment 2, a report based on an analysis of a time-series dataset. (1,000 words) (weighting 35%)</li> <li>Assignment 3, a short essay evaluating the statistical methods appropriate for a dataset with properties new to the student. (1,000 words) (weighting 30%)</li></ol> Written comments via Blackboard. MGDI20251 Intermediate Statistical Methods Pre-Requisite Compulsory BSc Global Development BSc (Hons) Global Development Third Year Optional BSc Global Dev with Int Study BSc Global Dev with Int Study Fourth Year Optional N William H. Greene (2017) Econometric Analysis (8th edition), Pearson: New York, NY Lectures 20 Practical classes & workshops 10 0 170