Accessibility statement

Data, Evidence & Policy - ECO00019C

« Back to module search

  • Department: Economics and Related Studies
  • Credit value: 20 credits
  • Credit level: C
  • Academic year of delivery: 2023-24
    • See module specification for other years: 2024-25

Module summary

Why do we use data in economics? What data do we need to give sensible answers to our research questions and to evaluate policies? How can we describe, explore and communicate empirical evidence effectively?

Interactive lectures will help you grasp key concepts and methods of data analysis and encourage you to apply economic reasoning to policy issues.

You will also have the opportunity to use real-world data to investigate important policy problems: how to evaluate the effect of sugar taxes on health behaviours? Can we explain gender and racial gaps in education attainment? Can we improve access to credit for low-income households?

Related modules

For economics students, Data, Evidence and Policy will illustrate key areas of data description and analysis in ways that complement the theoretical treatment in Probability and Statistics. It will also prepare students for further development in the Econometrics module in stage 2.

 

For students who are not taking economics as a major subject, Data, Evidence and Policy will provide insights and hands-on experience on how to use empirical evidence to understand and address major policy issues.

Module will run

Occurrence Teaching period
A Semester 2 2023-24

Module aims

  • To introduce students to the sources and content of economic data and evidence and develop their appreciation of what methods might be appropriately applied to the analysis of such data

  • To introduce students to the skills required for collection, description and interpretation of economic data and evidence

  • To develop students’ proficiency in computing techniques appropriate for the collection, management, description and visualisation of economic data

  • To provide hands-on experience, using real-world data, and apply economic reasoning to policy issues

  • To help students develop skills that are transferable to other modules and to the workplace

Module learning outcomes

At the end of this module, you will:

  • Understand why data are important in economics and what kinds of data are used by economists

  • Be able to find or create data that is relevant for economic analysis

  • Understand how to manage data and assess its quality

  • Understand how to measure economic variables in a reliable way

  • Be able to describe and interpret data using statistical tools and exploratory data analysis

  • Be able to visualise data in a clear and meaningful way

  • Be proficient in Excel (data management, functions, pivot tables, graphical tools)

  • Understand how to interpret and critically assess empirical evidence and how it can be used to investigate important policy problems

  • Be able to communicate and present evidence to non-specialist audiences

  • Have developed experience of working in a team and meeting deadlines

Module content

Module organised around 5 blocks. Each block focuses on one policy issue and is structured in 4 parts (covered over 2 weeks):

  1. Policy issue: reflection / discussion - explore the possible causes/determinants and implications; reflect on the type of empirical evidence needed to investigate the issue and provide recommendations

  2. Focus on empirical methods - type of data needed, methods available

  3. Review of the evidence - interpretation of evidence, critical appraisal / Application - group work on a similar issue with real-world data [Doing Economics projects]

  4. Policy brief - review and critical appraisal of existing policy briefs (from IFS, ONS etc) / Application group work on writing a policy brief

Content (including opportunities for hands-on experience)

  • Health behaviours, obesity and sugar taxes

    • Application (DiD) - Doing Economics “Measuring the effect of a sugar tax”

  • Social mobility and education - gender and racial gaps

    • Writing a policy brief

  • Inequality

    • Application - Doing Economics “Measuring inequality”

  • Inflation, growth, wealth and wellbeing

    • Data collection, description, visualisation and policy brief

  • Banking systems and access to credit

    • Application - Doing Economics “Credit-excluded households in a developing country”

Running in parallel: York Strengths (Introduction in week 1 + online programme + development workshop led by career at the end).

Indicative assessment

Task % of module mark
Essay/coursework 10
Essay/coursework 90

Special assessment rules

None

Indicative reassessment

Task % of module mark
Essay/coursework 90

Module feedback

Feedback on both components of assessment

  • Qualitative individual feedback (marking grid) at the same time as the mark

  • Cohort feedback after the last submission

Indicative reading

Textbooks

Doing Economics, Tipoe E, Becker R - CoreEcon

Economy, Society, and Public Policy - CoreEcon

Articles, books

Blundell, R. and Etheridge, B., 2010. Consumption, income and earnings inequality in Britain. Review of Economic Dynamics, 13(1), pp.76-102.

Beaman, L., Duflo, E., Pande, R. and Topalova, P., 2012. Female leadership raises aspirations and educational attainment for girls: A policy experiment in India. science, 335(6068), pp.582-586.

Harford, T., 2010. The undercover economist. Hachette UK.

Schwabish, J.A., 2014. An economist's guide to visualizing data. Journal of Economic Perspectives, 28(1), pp.209-34.

Tufte, E.R., McKay, S.R., Christian, W. and Matey, J.R., 1998. Visual explanations: Images and quantities, evidence and narrative.


The information on this page is indicative of the module that is currently on offer. The University constantly explores ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary. In some instances it may be appropriate for the University to notify and consult with affected students about module changes in accordance with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.