Module Specifications.
Current Academic Year 2024 - 2025
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Date posted: September 2024 No Banner module data is available
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Coursework Only To produce a research design and plan for the PAE. |
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Description This module is designed to prepare you to complete the Policy Analysis Exercise (PAE), which accounts for one third of your MPP. This is a pass/ fail module for which you will be expected to produce a research design for your PAE. To prepare you for that the moduule will introduce you to research design and some research methods. Often the PAE is designed around specific policy instruments, in an attempt to assess their efficacy. The policy is then a treatment. We will deal with causal inference, and look at methods that help establish causality. There will also be a practical guide to how to do a PAE. | |||||||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Create a research design for a piece of original policy research 2. Present their research proposal to a group 3. Critically evaluate other research designs | |||||||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and Learning Activities
What is the PAE?Finding a Public Policy Puzzle. Examples: Does education lead to an increase in income? Which hospital should I go to? Exercise: Making better questionsBuilding blocks for Theory TestingVariables, concepts, unit of analysis, theories, hypotheses.Collecting Evidence: MeasurementLevel of measurement, types of measures, measurement error, reliability and validity.Cause and Effect: Research DesignCovariance, temporal precedence, Internal and external validity, Regression to the Mean, causal mechanisms, control, Spurious relationships, DAGs, confounding, case or variable oriented design.Different types of studiesObservational studies, sampling, RCTs, Statistical analyses, case studies, surveys, meta-analysis, process tracing.Thinking StatisticallyEndogeneity, selection bias, Bayesian analysisA Practical Guide to the PAEHaving an argument, making it well | |||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||||||