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This course explores the impact of the Internet, information technology, and the networked information economy on finance, markets, innovation and invention, intellectual property rights, public finance and taxation, security and cybercrime, media, and social networking. We investigate the implications of the networked information economy for the creation of new economic (and social) relationships. We also examine the continuing struggle over regulation of cyberspace and the definition and enforcement of intellectual property rights.

Drawing on insights from recent scholarship on the "histories of capitalism," this course explores the history of economic life in modern Britain, from the late seventeenth to the early twentieth centuries. Rather than take British economic development as exemplary of modernization we will situate that which was particular about the British case against the pluralities of capitalism that have evolved over the past three centuries.

In the era of “big data,” statistical models are becoming increasingly sophisticated. This course begins with linear regression models and introduces students to a variety of techniques for learning from data, as well as principled methods for assessing and comparing models. Topics include bias-variance trade-off, resampling and cross-validation, linear model selection and regularization, classification and regression trees, bagging, boosting, random forests, support vector machines, generalized additive models, principal component analysis, unsupervised learning and k-means clustering.