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Unit information: Economic Data in 2018/19

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Economic Data
Unit code EFIM10016
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Hans Sievertsen
Open unit status Not open
Pre-requisites

None

Co-requisites

EFIM10009 Mathematical and Statistical Methods 2

School/department School of Economics
Faculty Faculty of Social Sciences and Law

Description

This unit focuses on obtaining, processing and presenting numerical economic information. The unit will introduce students to ways of accessing statistical databases from National Statistical Agencies, International Organizations, and other publicly available data sources. The students will learn concepts that are important for understanding and presenting economic data in a non-misleading way, for example the definition of GDP, price-indices, survey weights and log-scales. The unit will also introduce students to various ways to present the processed data (verbally, tables, graphs), and how to decide what presentation method to use. The students will be shown how to perform basic analyses of data using software packages such as MS Excel.

Topics covered will include

  • Obtaining data from publicly accessible databases
  • Critical assessments of data sources
  • Definitions of internationally used variables (GPD, Unemployment rates, consumer price index/inflation, Purchasing Power Parity)
  • Using and interpreting survey data
  • Measures of happiness and wellbeing
  • Presentation and visualization methods
  • Automation methods

The unit will draw on links that the department has with the Office for National Statistics.

Intended learning outcomes

Students will be able:

  • To obtain, process and describe data using verbal, numerical and visual methods;
  • To evaluate the quality of data;
  • To understand the conceptual issues in producing estimates of variables such as GDP, PPP or inflation;
  • To analyse data to answer an economic question;
  • To select appropriate visualization methods.

Teaching details

Large-group teaching (“Lectures”): a total of 18 hours to deliver the material

Small-group teaching in computer labs (“Classes”): 9 one-hour classes of groups of circa 15-20 students

Revision and additional lectures: 2 hours for revision and supplementary material (sometimes in enhancement week)

No significant e-learning components are envisaged at the moment, but the department is experimenting with additional teaching methods to improve the student learning experience.

Assessment Details

Formative Assessment

Formative assessment will consist of problem-solving and data-analysis questions, marked by the class tutor and returned with feedback.

In line with the department’s policy of augmenting traditional formative assessment with electronic assessment, formative assessment may be supplemented with small online quizzes or other electronic resources.

Summative Assessment

This will be a project to analyse economic data. The maximum project length will be 15 pages. This assesses all of the learning outcomes.

Reading and References

Schwabish, Jonathan A. 2014. "An Economist's Guide to Visualizing Data." Journal of Economic Perspectives, 28(1): 209-34. DOI: 10.1257/jep.28.1.209

Stephen Few: “Show Me the Numbers”, Analytics Press; 2nd New edition (30 Jun. 2012)

Edward R. Tufte: “The Visual Display of Quantitative Information”, Graphics Press USA; 2nd edition (31 Jan. 2001) (optional)

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