Quantitative Economics

This information is for the 2020/21 session.

Teacher responsible

Professor Mark Schankerman (Michaelmas term) 32L.4.30

Dr Xavier Jaravel (Lent term) 32L.3.14


This course is available on the MSc in Econometrics and Mathematical Economics. This course is available with permission as an outside option to students on other programmes where regulations permit.


Students must have completed Introductory Course for MSc EME (EC451).

A knowledge is expected of econometric theory and applied econometrics corresponding to Principles of Econometrics or Methods of Economic Investigation. Students must be prepared to read journal articles with a difficult mathematical and statistical content.

Course content

The course will focus on going through modern quantitative papers which demonstrate the application of econometric techniques to modelling the behaviour of individual economic agents (households and firms) and economies. The first half of the course will focus on papers in the empirical literature on productivity, innovation and intellectual property rights, illustrating the challenges of identification in both structural and reduced form models.  The lectures will cover a wide range of topics in applied micro-econometrics with a view to illustrating the interplay between models, data and methods.

The second part of the course focuses on macroeconomic questions using data and tools from applied microeconomics. We cover four styles of empirical work: (1) “reduced-form” approaches (including difference-in-differences, event studies instrumental variables and Bartik research designs); (2) structural models; (3) “sufficient statistics” research designs, at the intersection of structural and reduced-form methods; and (4) machine learning techniques. Topics covered include the effectiveness of fiscal stimulus, measurement of inflation, directed technical change, from trade, the macroeconomic impact of financial frictions over the business cycle, the macroeconomic impact of unemployment insurance, and the effect of Artificial Intelligence on the labour market.


20 hours of lectures and 10 hours of seminars in the MT. 20 hours of lectures and 10 hours of seminars in the LT.

This year at least for Michaelmas Term, some or all of this teaching may have to be delivered through a combination of virtual webinars, online videos, and virtual classes.

Formative coursework

During Michaelmas term, students are required to prepare a short (3-4 page) “referee report” on an assigned journal article each week. Two of these reports will be marked by the class teacher. In Lent term, there will be one marked assignment, a short research proposal (which will be developed based on the content of classes and based on feedback from the instructor).

Indicative reading

Articles in economic journals will be assigned at the start of Michaelmas and Lent terms. The course will also draw on methodological topics covered in Wooldridge, Econometric Analysis of Cross Section and Panel Data (2nd edition, 2010), and Angrist and Pischke, Mostly Harmless Econometrics (2009).


Exam (80%, duration: 2 hours, reading time: 15 minutes) in the summer exam period.
Report (10%) in the MT.
Research proposal (10%) in the LT.

The report will be two mark referee reports due in the MT. 

Important information in response to COVID-19

Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Economics

Total students 2019/20: 2

Average class size 2019/20: 2

Controlled access 2019/20: Yes

Value: One Unit

Guidelines for interpreting course guide information