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Master’s in Data-Driven Urban Policy Evaluation Engineering

Online master's programme of 1,900 hours in data-driven urban policy evaluation engineering. 12 modules covering evaluation design, data for urban evaluation, experimental, quasi-experimental and spatial methods, economic evaluation, mobility, housing and social policy evaluation, mixed methods and data science for evaluation, applying Law 27/2022, the European Commission CBA Guide and R, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Design urban policy evaluations with relevant questions.

02

Build evaluation databases from multiple sources.

03

Apply experimental and quasi-experimental methods.

04

Incorporate spatial methods into impact evaluation.

05

Carry out cost-benefit analyses of urban interventions.

06

Combine quantitative and qualitative methods.

07

Communicate evaluation results to public decision-makers.

Profile

Who it's for

  • Public policy evaluators.
  • Public sector data analysts.
  • Urban economists.
  • Evaluation consultants.
  • Municipal planning officers.
  • Urban policy researchers.
  • Engineering or science graduates seeking to enter public administration.
Standards & tools

What you'll work with

  • Law 27/2022 (institutionalisation of public policy evaluation in the Spanish General State Administration)
  • European Commission Guide to Cost-Benefit Analysis of Investment Projects (2014)
  • Regulation (EU) 2016/679 (GDPR)
  • Law 12/1989 (Spanish Public Statistics Act)
  • Law 19/2013 (transparency)
  • European Commission Better Regulation Guidelines (2021)
  • Law 39/2015 (Common Administrative Procedure)
  • R
  • Python (statsmodels, EconML)
  • Stata
  • QGIS
  • ATLAS.ti
Syllabus

12 modules · 1900 h

  1. 1.1Types of evaluation: design, process and impact
  2. 1.2Law 27/2022 on the institutionalisation of evaluation
  3. 1.3Evaluability of policies
  4. 1.4Programme theory
  5. 1.5Evaluation questions
  6. 1.6Criteria: relevance, effectiveness and efficiency
  7. 1.7Evaluators and independence
  8. 1.8Use of evaluation
  9. 1.9Evaluation culture in Spain
  10. 1.10Case study: evaluability of an urban plan
  1. 2.1Municipal administrative records
  2. 2.2Surveys and panels
  3. 2.3Geolocated data and georeferencing
  4. 2.4Sensor and platform data
  5. 2.5Integration of sources
  6. 2.6Microdata and statistical confidentiality
  7. 2.7Data quality and bias
  8. 2.8Construction of indicators
  9. 2.9Data dictionaries
  10. 2.10Lab: integration of municipal records in R
  1. 3.1Causal inference and the counterfactual
  2. 3.2Randomised controlled trials in policy
  3. 3.3Random assignment and stratification
  4. 3.4Statistical power calculation
  5. 3.5Ethics of public experiments
  6. 3.6Field experiments in cities
  7. 3.7Behavioural experiments
  8. 3.8Implementation and compliance
  9. 3.9Analysis of results
  10. 3.10Practical exercise: design of an experiment on separate waste collection
  1. 4.1Difference-in-differences
  2. 4.2Regression discontinuity designs
  3. 4.3Instrumental variable estimation
  4. 4.4Propensity score matching
  5. 4.5Synthetic control method
  6. 4.6Interrupted time series
  7. 4.7Assumptions and robustness checks
  8. 4.8Heterogeneity of effects
  9. 4.9Comparison of methods
  10. 4.10Lab: synthetic control for a low-emission zone
  1. 5.1Spatial econometric models
  2. 5.2Spatial autocorrelation and Moran's index
  3. 5.3Spillover effects
  4. 5.4Hedonic housing prices
  5. 5.5Accessibility as an outcome
  6. 5.6Hot-spot analysis
  7. 5.7Geographically weighted regression
  8. 5.8Spatial units and the MAUP problem
  9. 5.9Visualisation of effects
  10. 5.10Practical exercise: hedonic model of the effect of a park
  1. 6.1Social cost-benefit analysis
  2. 6.2Cost-effectiveness analysis of programmes
  3. 6.3Valuation of intangibles
  4. 6.4Shadow prices and corrections
  5. 6.5Social discount rate
  6. 6.6European cost-benefit guides
  7. 6.7Sensitivity analysis
  8. 6.8Distribution of costs and benefits
  9. 6.9Presentation of results
  10. 6.10Case study: cost-benefit analysis of a building renovation programme
  1. 7.1Mobility indicators
  2. 7.2Low-emission zones
  3. 7.3Cycle lanes and infrastructure
  4. 7.4Free public transport
  5. 7.5Parking pricing
  6. 7.6Air quality as an outcome
  7. 7.7Road casualties as an outcome
  8. 7.8Evaluation of superblocks
  9. 7.9Lessons from published evaluations
  10. 7.10Workshop: evaluation of a traffic-calming policy
  1. 8.1Affordable housing policies
  2. 8.2Rent subsidies
  3. 8.3Neighbourhood regeneration
  4. 8.4Social inclusion programmes
  5. 8.5Local employment policies
  6. 8.6Municipal social services
  7. 8.7Equity evaluation
  8. 8.8Well-being indicators
  9. 8.9Mixed evaluation methods
  10. 8.10Case study: evaluation of a rent subsidy
  1. 9.1Interviews and focus groups
  2. 9.2Content analysis
  3. 9.3Case studies
  4. 9.4Causal process tracing
  5. 9.5Qualitative comparative analysis (QCA)
  6. 9.6Integration of quantitative and qualitative evidence
  7. 9.7Participatory evaluation with stakeholders
  8. 9.8Qualitative analysis software
  9. 9.9Rigour and validity
  10. 9.10Practical exercise: analysis of interviews with managers using qualitative software
  1. 10.1Machine learning for causal inference
  2. 10.2Causal forests and machine learning
  3. 10.3Prediction in public policy
  4. 10.4Big data and evaluation
  5. 10.5Text processing of public documents
  6. 10.6Algorithmic bias in policy
  7. 10.7Reproducibility and open code
  8. 10.8Analysis tools
  9. 10.9Limits of prediction
  10. 10.10Lab: estimating heterogeneous effects with causal forests
  1. 11.1Evaluation reports
  2. 11.2Summaries for decision-makers
  3. 11.3Visualisation of effects
  4. 11.4Formulating actionable recommendations
  5. 11.5Dialogue with policy-makers
  6. 11.6Transparency and publication
  7. 11.7Evaluation repositories
  8. 11.8Meta-evaluation and quality of evaluations
  9. 11.9Institutionalisation of municipal evaluation
  10. 11.10Workshop: executive summary of an evaluation
  1. 12.1Selection of the urban policy
  2. 12.2Theory of change
  3. 12.3Evaluation design
  4. 12.4Data collection and processing
  5. 12.5Estimation of effects
  6. 12.6Economic valuation of effects
  7. 12.7Recommendations for decision-makers
  8. 12.8Conclusions and future lines of work
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

The programme is delivered 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it is compatible with full-time work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is R, Python (statsmodels, EconML), Stata, QGIS and ATLAS.ti, in free, academic or evaluation versions. You work on real procedures for quasi-experimental evaluation of urban policies, analysis of administrative records and design of field experiments. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Law 27/2022; European Commission Guide to Cost-Benefit Analysis of Investment Projects (2014); Regulation (EU) 2016/679; Law 12/1989; Law 19/2013; European Commission Better Regulation Guidelines (2021); Law 39/2015.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Law 27/2022, the European Commission Guide to Cost-Benefit Analysis and the GDPR applied to real cases, not as a theoretical annex.
Industry software:R, Python (statsmodels, EconML), Stata, QGIS and ATLAS.ti, in free, academic or evaluation versions.
Master's Thesis with defence:a complete impact evaluation of a real urban policy, from theory of change and data to effect estimation, economic valuation and recommendations, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Evaluability and theory of change
Assess the evaluability of an urban policy and set out its theory of change.
Evaluation database
Integrate municipal records and other sources into an evaluation dataset in R.
Impact estimation
Estimate policy effects with quasi-experimental methods such as synthetic control.
Economic valuation
Value the effects through a social cost-benefit analysis.
Master's Thesis
a complete impact evaluation of a real urban policy, from theory of change and data to effect estimation, economic valuation and recommendations, defended before a panel.
Career opportunities

Where this takes you

Public policy evaluatorPublic sector data analystUrban economistEvaluation consultantMunicipal planning officerUrban policy researcher
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • Internet connection and a computer capable of running the programme's software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with R, Python (statsmodels, EconML), Stata, QGIS and ATLAS.ti, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture, or equivalent professional experience, plus a computer able to run the software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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