London School of Economics

This course introduces students to the study of the dynamic interaction between the pursuit of wealth and the pursuit of power in the global economy. The course presents the key concepts and theories of IPE, and how these can be used to understand pressing empirical and economic policy questions facing policymakers and citizens in the 21st century.

In this course, students develop concepts such as convergence, continuity, completeness, compactness, and convexity in the settings of real numbers, Euclidean spaces, and more general metric spaces.

The course discusses probability, distribution theory, and statistical inference. It covers mathematical statistics as important discrete and continuous probability distributions (such as the Binomial, Poisson, Uniform, Exponential, and Normal distributions) and investigates properties of these distributions, including use of the moment generating function. The course discusses point estimation techniques including method of moments, maximum likelihood, and least squares estimation. Statistical hypothesis testing and confidence interval construction follow, along with non-parametric and goodness-of-fit tests and contingency tables. A treatment of linear regression models, featuring the interpretation of computer-generated regression output and implications for prediction are also covered.

This course explores the origins of modern economic growth through major themes such as life, love, death, place, and inheritance. The focus is on the world's first breakthrough in Britain during the Industrial Revolution. Students are exposed to frontier debates in economic history. Widespread use is made of intuitive econometrics, interdisciplinary insights, and historical context.