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Postgraduate Module Descriptor


SOCM028: Policy Analytics: Data Driven Policy Analysis and Evidence Based Decision-making

This module descriptor refers to the 2018/9 academic year.

Module Content

Syllabus Plan

Whilst the module’s precise content and order of syllabus coverage may vary, it is envisaged that it will include the following topics:

 

 

Seminars:

  1. Policy analytics and evidence based decision making: definition and key themes
  2. The politics of the policy process and evidence-based decision making: The Policy Cycle & Problem Definition
  3. Decision making under uncertainty
  4. Causal Inference and Mechanisms – principles of research design
  5. Types of data for policy analytics: Open, administrative, secondary, primary (to include section on data quality)
  6. Applications of Policy Analytics: Analysis, Evaluation, Cost Benefit & Decision-making
  7. Policy Analytics Techniques I – RCTs and policy interventions
  8. Policy Analytics Techniques II -  Meta-analysis; combining evidence and multi-level analysis
  9. Policy Analytics Techniques III – Modelling Uncertainty
  10. Policy Analytics Techniques IV – Time series
  11. Policy Analytics Techniques V – Longitudinal Analysis

 

 

 

Computer Analytics Sessions

  1. Data Sources: Secondary Data Analysis
  2. Data Management & Extraction
  3. Designing Surveys – Qualtrics
  4. Basics of Analysis I  – Communicating Evidence
  5. Basic of Analysis II - Regression Discontinuity Designs
  6. Basic of Analysis II – Differences in Differences
  7. Basic of Analysis II – Logit & Probit Models 

Learning and Teaching

This table provides an overview of how your hours of study for this module are allocated:

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
382620

...and this table provides a more detailed breakdown of the hours allocated to various study activities:

CategoryHours of study timeDescription
Scheduled Learning and Teaching Activities2412*2 hours of lectures, seminars and practical labs lectures cover the main concepts and data analysis skills of the course. (Each 11x2 hour session will entail lecture time plus seminars to discuss the material introduced)
Scheduled Learning and Teaching Activities147 x 2 hour Computer lab sessions - Application of data analysis techniques to be demonstrated with by teaching assistant.
Guided Independent Study66Reading and preparing for seminars (around 4-6 hours per week);
Guided independent study196Researching and writing assessments and assignments (researching, planning and writing the course work).

Online Resources

This module has online resources available via ELE (the Exeter Learning Environment).

http://imai.princeton.edu/software/index.html

UK Data Services - https://www.ukdataservice.ac.uk

NCRM - http://www.ncrm.ac.uk

Other Learning Resources

There are a range of data sets that will be used in the course:

 

British Household Panel Survey: Waves 1-18, 1991-2009 

Understanding Society: Waves 1-6, 2009-2015 

Office for National Statistics Longitudinal Study, 1971- 

Supporting better evidence generation and use within social innovation in health in low- and middle-income countries

 

All of the above are available at UKDS