About this Fellow
Neil Shephard's broad research interests are in econometrics, finance and statistics, with a particular focus on financial econometrics. He has made significant advances in developing simulation based inference methods for online learning and has contributed methods to allow the mainstream use of high frequency financial data in economics. He joined the Harvard faculty in 2013, holding a professorship joint between the Economics and Statistics Departments. Since 2015 he has also been the chair of the Statistics Department. Professor Shephard is a fellow of the Econometric Society and the British Academy. He is an associated editor of Econometrica. Professor Shephard was a faculty member at the London School of Economics from 1988-1993 and Oxford University and Nuffield College, Oxford from 1991 to 2013.
- Professor of Economics and of Statistics, Harvard University
- Lecturer, London School of Economics and Political Science University of London, 1988 - 1993
- Gatsby Prize Research Fellow, Nuffield College University of Oxford, 1991 - 1993
- Official Fellow in Economics, Nuffield College University of Oxford, 1993 - 2006
- Professorial Fellow, Nuffield College University of Oxford, 2006 - 2013
- Professor of Economics, Nuffield College University of Oxford, 2006 - 2013
- Professor of Economics and of Statistics, Department of Economics, Harvard, 2013
- Director of the Oxford-Man Institute, Nuffield College University of Oxford, 2006 - 2011
Theoretical econometrics and economic statistics; moment condition models, model selection and nonnested tests, specification tests, bias reduction and asymptotic approximations, survey nonresponse, survey-based estimation of expectations and national ac
Game theory and its application to the evolution of social norms, learning and innovation, theories of distributive justice, and the design of legislative systems.
Applied microeconometrics with an emphasis on structural modelling of individual behaviour; intra-household decision making; demand analysis; accounting for heterogeneity; survey design
Nonparametric and semiparametric methods, asymptotic approximations and expansions, financial econometrics, nonlinear time series analysis, survival analysis and missing data