If you want to, or need to, take econometrics while studying at LSE, you need to select the course that is appropriate for your existing quantitative skill set.
There are three different econometrics courses at LSE. Because of the level at which they operate and the quantitative skills they require, two of these are only available with permission from the course convenor.
The three courses are:
MG205 Learning From Quantitative Data
It may not sound like it, but this is an econometrics course in all but name. It is a year-long course taught within the Management Department but is available to General Course students.
The main aim of this course is to provide a thorough understanding of the quantitative techniques that guide evidence-based managerial decision-making. It seeks to develop a framework in which students can examine whether the predictions of managerial, social or economic theory are supported by empirical evidence.
The textbooks for the course are: J H Stock and M W Watson, Introduction to Econometrics 3rd ed (Peason: 2011) - this is the standard textbook used in most econometrics courses in most Econ departments in many US universities; and Jeffrey Woodbridge, Introductory Econometrics – A Modern Approach 5th ed
(Southwestern, 2013).
The course covers: simple and multiple regression; hypothesis testing; mechanics and limitations of OLS; causality; natural, field and laboratory experiments; panel data. Particular emphasis is placed on (a) illustrating the many ways in which evidence is abused in the academic or managerial debates, and (b) trying to establish causality in the relationship between variables. The approach of the course is both formal, making extensive use of econometric theorems and techniques, and grounded in real-world applications.
The course makes use of the STATA software package and you will learn the basics of data manipulation and running regressions.
The prerequisites for the course are a good introductory course in statistics and probability (similar to the content of the LSE course ST107) and an introductory course in algebra and calculus (similar in content to the LSE course MA107).
The failure rate for General Course students taking this course is about 14%.
EC220 Introduction to Econometrics
The name of this course might give you the false impression that it is an entry-level course on econometrics. It isn’t. Taught within the Economics Department it is a compulsory course for LSE Economics undergraduates.
It is taught at a higher level of mathematical sophistication than MG205 and presumes an additional fluency in statistics and probability theory. It draws extensively on Professor Steve Pischke and Joshua Angrist’s book Mastering ‘Metrics: The Path from Cause to Effect (Princeton University Press; December 2014). But it is not a textbook based course and lots of additional teaching material is provided via web-based material.
This course is only available to General Course students with permission of the course convenor. If you wish to take the course, you will need to attend the orientation session for it at the start of the term.
The course aims to present the theory and practice of empirical research in economics. Students will work with the STATA software package in analysing actual data sets. The focus of the course is on causal ‘what-if’ questions (e.g. whether our estimates will deliver answers to questions like: ‘what is the effect of monetary policy
on output?’).
The course content is sequential in nature: each week’s topic builds on the previous one. If you don’t master the ideas and materials covered in the first few weeks, you will not be able to handle the ones that come later. Expect to invest a lot of time and effort on this course!
Topics covered include: randomized experiments; matching, simple, and multiple regression analysis; hypothesis testing; omitted variables bias; functional form; measurement error; instrumental variables; simultaneous equations bias and two stage least squares; regression discontinuity designs; differences-in-differences and panel data. Applications will be discussed throughout the course.
The prerequisites for the course are: a solid background in algebraic equations and functions; at least one semester of intermediate level microeconomics; some multivariate differential calculus; and, most importantly, a rigorous course in statistics including coverage of probability theory and statistical inference. This needs to be equivalent to the material covered in ST102 Elementary Statistical Theory (which is really much more than elementary – make sure you have a look at the details of what is covered in ST102 before thinking about doing EC220!). You should be familiar with the material covered in Chapters 2 and 3 of Stock and Watson.
It is worth General Course students keeping in mind that LSE students taking this course will have taken the full year course in statistics, ST102, and a full year course in maths, MA100.
Do not be fooled by the 100 level listing of these two courses. They are the equivalent of 200 or 300 level courses at most US universities.
It is worth noting that even with the ‘gatekeeping’ of the permission process, the failure rate for General Course students on this course over the last few years is about 15%.
EC221 Principles of Econometrics
In the LSE course guide this is described as an ‘intermediate-level introduction to the theory and practice of econometrics’. As with EC220, this is probably understating the level and degree of difficulty the course operates at. The difference between the two courses is that EC221 places more emphasis on the underlying statistical theory and relies on the use of matrix algebra. So it is more theoretical, stressing mathematical derivations and concentrating on formal proofs and advanced topics such as method of moments estimation and maximum likelihood estimation (non-linear) with applications to binary choice and count data models.
Taught within the Economics Department, it is only available to General Course students with permission of the course convenor.
Textbooks used during the course are: J D Angrist and J S Pischke, Mastering ‘Metrics: The Path from Cause to Effect ((Princeton University Press, 2014) and J M Woolbridge, Introductory Econometrics: A Modern Approach (Thomson, 2012). It also makes use of J Johnston and J Dinardo, Econometric Methods (McGraw-Hill, 1997); G S Maddala, Introduction to Econometrics (John Wiley, 2009); W Greene Econometric Analysis (Pearson); and C Heij et al, Econometric methods with applications in Business and Economics (OUP). The course will also make use of J Stock and M Watson, Introduction to Econometrics 3rded (Peason: 2011)
The course covers: randomised experiments; programme evaluation; matching; simple and multiple regression analysis; omitted variable bias; functional form; heteroskedasticity and weighted least squares; endogeneity (measurement error, simultaneity); instrumental variables and two-stage least squares; and stationary and non-stationary time series analysis.
The prerequisites for the course are: a very solid background in linear algebra (covering matrices and vectors, though abstract vector spaces are not required); a solid background in multivariate calculus (differential calculus is more important than sophisticated integration); a solid background in intermediate level microeconomics,
and a solid background in statistics (as with EC220, equivalent to ST102 Elementary Statistical Theory).
Given the level at which the course operates, each year only a handful of General Course students are equipped to tackle this course.
The failure rate for General Course students over the last few years has averaged about 18%.
Updated July 2016