Methods
We are a methods-led research and evaluation unit. We deploy a wide range of methods to help policy-makers answer important questions, from better understanding people’s needs to finding out whether a policy worked.
Making sure that we use the most appropriate method to answer a particular research or evaluation question is one of the most important parts of any project we undertake. We spend time discussing methods options with stakeholders and sometimes undertake a ‘Feasibility Study’ prior to starting a research project.
Methodological innovation is at the heart of what we do and we enjoy teaching and writing about methods. We teach methods to both undergraduate and post-graduate students at Manchester Metropolitan University and our writing on methods includes textbooks and articles published in academic journals.
Our Expertise
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In undertaking Evaluation, we often seekto answer four main research questions:
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We carry out microsimulation modelling to estimate the fiscal, distributional and poverty effects of tax and benefit policy and economic analysis to evaluate the costs and benefits of individual projects:
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PERU undertakes randomized field trials (RCTs or social experiments) in order to evaluate the impact of social interventions:
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We have extensive experience of designing, delivering and analysing surveys including:
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We often use the Rapid Evidence Assessment (REA) methodology to produce high-quality evidence assessments in a timescale that fits the needs of policy-makers:
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We focus on advancing novel methodological approaches in geostatistics, machine learning and agent-based simulation (ABM) to enable us to unlock the potential of big data:
Big data affords exciting new research opportunities, opening prospect of insight in to multiple policy issues that have hitherto remained impenetrable with traditional data sources. However, the sheer scale and high-dimensionality of big data pose significant methodological challenges, such as scalability, noise and spurious correlation. To address these challenges, there is a need for new statistical thinking and methodological development. We focus on advancing novel methodological approaches in geostatistics, machine learning and Agent-based simulation (ABM) to enable us to unlock the potential of big data to shed light on social policy problems.