Level: 300 level. Read more information on levels in our FAQs

Fees:  Please see Fees and payments

Lectures: 36 hours 

Classes: 18 hours

Assessment*: Two written examinations and two computer-based exercises

Typical credit**: 3-4 credits (US) 7.5 ECTS points (EU)

*Assessment is optional

**You will need to check with your home institution

For more information on exams and credit, read Teaching and assessment

Students should have taken EC212 Introduction to Econometrics or an equivalent undergraduate course in econometrics. 

With EC312 being considerably more advanced technically than EC212, a good working knowledge of multivariate calculus and linear algebra will be required as well.

Familiarity with statistical software Stata will be helpful but are not required.

Main Regression

• Principles of Estimation (Ordinary Least Squares, Generalized Least Squares and Maximum Likelihood Estimation with Micro-Econometric applications)

• Principles of Testing (t- and F-test; Wald, Likelihood Ratio, Lagrange Multiplier Testing Principles).

• Time Series: Basic Time Series Processes; Stationarity and Nonstationarity - Unit roots and Cointegration.

Estimation Methodology

• Endogeneity in linear regression models; Instruments; 2SLS estimator and Generalized IV estimator; Simultaneous equations.

• Motivation, definition and asymptotic properties of GMM estimator; Efficient GMM estimation; Over-identifying restrictions.

• Introduction to Panel Data Models: Fixed effect and random effect models.

• Arellano-Bond estimator in dynamic panel data models.

• Introduction to Quantile estimation.

This course is delivered as a combination of lectures, class discussions and practical exercises.

The course is assessed through two examinations: one mid-session examination (45%), one final examination (45%), and two take-home computer-based exercise (5% each). Students will receive formative feedback on two exam type assignments, one before each exam.

*Further details will be provided at the beginning of the course.

Students will gain understanding of advanced, mostly theoretical, treatment of econometric principles for cross-sectional, panel and time-series data sets.

This course will suit you if you are interested in obtaining a more rigorous understanding of the theory behind state-of-the art methods of applied econometric analysis. You should consider taking this course if you are interested in enhancing your ability to understand ongoing research in related areas.  

The LSE Department of Economics is one of the biggest and best in the world, with expertise across the full spectrum of mainstream economics. A long-standing commitment to remaining at the cutting edge of developments in the field has ensured the lasting impact of its work on the discipline as a whole. Almost every major intellectual development within Economics over the past fifty years has had input from members of the department, which counts ten Nobel Prize winners among its current and former staff and students. Alumni are employed in a wide range of national and international organisations, in government, international institutions, business and finance.

The Department of Economics is a leading research department, consistently ranked in the top 20 economics departments worldwide. This is reflected in the 2014 Research Assessment Exercise which recognised the Department's outstanding contribution to the field. According to the REF 2014 results, 56 per cent of the Department’s research output was graded 4 star (the highest category), indicating that it is 'world-leading'. A further 33 per cent was designated 'internationally excellent' (3 star).

On this three week intensive programme, you will engage with and learn from full-time lecturers from the LSE’s economics faculty.

Lecturers:

Dr Tatiana Komarova
Assistant Professor of Economics, Department of Economics

Dr Abhimanyu Gupta
Senior Lecturer, Department of Economics, University of Essex

Though no single textbook covers all methods and applications to be discussed in the course, we will recommend the following textbooks primarily for reference or review:

M. Verbeek, A Guide to Modern Econometrics, (4^th edition), Wiley (2012).

W.H. Greene, Econometric Analysis, (8th edition), Pearson Prentice Hall (2020).

*A more detailed reading list will be supplied prior to the start of the programme

**Course content, faculty and dates may be subject to change without prior notice