MRes Criminology (Social Statistics)

To provide the knowledge and skills required to analyse the population structure and forecast the population change, including the context of the COVID-19 pandemic. Population change is driven by changes in mortality, fertility, and both international and internal migration. The pandemic impacted lives across the globe and made important contributions to the population change due to the highly selective fatality affecting persons at older ages, of male gender, and with comorbidities. Therefore, we derive, interpret and apply a range of demographic measures to the past and current populations with a critical appraisal in the light of the available data sources and their quality. We focus on measures of mortality, such as life tables, multiple decrement and cause-deleted life tables, bilinear and hierarchical models for estimating and forecasting mortality and other components of population change. Methods are applied to the real-world data focusing on outcomes of the COVID-19 pandemic in the UK and other countries, and critically interpreted.  

To provide the knowledge and skills required to analyse population structure and population change, focusing on mortality and fertility. We derive, interpret and apply a range of demographic measures to the past and current populations at various levels of geography with a critical appraisal of their accuracy in the light of the available data sources and their quality. Throughout the course we learn and apply various statistical techniques to estimate the demographic quantities of interest, which are then applied to the real world data and critically interpreted. 
 

Provisional

1. Population balance equation – main components of population change

2. Introduction to Bayesian inference  

3. Log-linear models and forecasting

4. Modelling age schedules and Lee-Carter model

5. The demographic and epidemiological transitions

6. Introduction to life tables and visualisations

7. Multiple decrement life tables  

8. Modelling fertility

8 x Asynchronous lectures + Q&A session (1 hour) + 8 x Tutorial - lab session (2 hours)

• Understanding of the key concepts and theories related to population change and population components  
• Understanding the key measures used to analyse population change  

• Understanding and critically appraise the methods and data used to measure and forecast population change 

• Being able to assess the quality of the data for a given source
• Being able to produce a range of demographic measures using statistical techniques and R (or similar) software
• Being able to evaluate the quality of the claims by the media and statistical authorities about the population change
   

• Being able to apply the learnt methods to the real world data and other settings such as at local authorities, governments and companies that utilise population estimation and forecasting as part of their activities

[Group work] Critical appraisal of one or two selected journal articles and presentation – worth a maximum of 1000 words (40%)

A structured essay and data analysis of a given population component by using various techniques learnt during class, on an example of a selected country/region; essay is accompanied by visualisations and computer code (in R) which are excluded from the word limit - 1500 words (60%)

Feedback available via Turnitin. 

Indicative Reading  

• Preston, S., Heuveline, P., & Guillot, M. (2000). Demography: measuring and modeling population processes.
• Castles, S., De Haas, H., & Miller, M. J. (2013). The age of migration: International population movements in the modern world. Palgrave Macmillan.
• Rowland, D. T. (2003). Demographic methods and concepts. OUP Catalogue.
• Bijak, J. (2010). Forecasting international migration in Europe: A Bayesian view (Vol. 24). Springer Science & Business Media.
• Gerland, P., Raftery, A. E., Ševčíková, H., Li, N., Gu, D., Spoorenberg, T., ... & Bay, G. (2014). World population stabilization unlikely this century. Science, 346(6206), 234-237.
• Wiśniowski, A., Smith, P. W., Bijak, J., Raymer, J., & Forster, J. J. (2015). Bayesian population forecasting: extending the Lee-Carter method. Demography, 52(3), 1035-1059.