Francis X. Diebold

Francis X. Diebold is Paul F. Miller, Jr. and E. Warren Shafer Miller Professor of Social Sciences, and Professor of Economics, Finance, and Statistics, University of Pennsylvania. He has held visiting appointments at Princeton, Chicago, Johns Hopkins, and NYU.

His research focuses on predictive modeling of financial asset markets, macroeconomic fundamentals, climate change, and the interface. He has made well-known contributions to the measurement and modeling of asset-return volatility, business cycles, yield curves, and network connectedness. He has published more than 150 scientific papers and 8 books, and he is regularly ranked among globally most-cited economists.

He is Founding Fellow and Past President, Society for Financial Econometrics; NBER Faculty Research Associate; Fellow, Econometric Society, American Statistical Association, Guggenheim Foundation, Sloan Foundation, Humboldt Foundation, Journal of Econometrics; Founding Fellow, International Association for Applied Econometrics, Society for Economic Measurement; Honorary Fellow, International Institute of Forecasters; and Past Editorial Board Member, Econometrica, Review of Economics and Statistics, and International Economic Review.

His academic “family” includes more than 75 Ph.D. students.

Francis X. Diebold is Paul F. Miller, Jr. and E. Warren Shafer Miller Professor of Social Sciences, and Professor of Economics, Finance, and Statistics, University of Pennsylvania. He has held visiting appointments at Princeton, Chicago, Johns Hopkins, and NYU.

His research focuses on predictive modeling of financial asset markets, macroeconomic fundamentals, climate change, and the interface. He has made well-known contributions to the measurement and modeling of asset-return volatility, business cycles, yield curves, and network connectedness. He has published more than 150 scientific papers and 8 books, and he is regularly ranked among globally most-cited economists.

He is Founding Fellow and Past President, Society for Financial Econometrics; NBER Faculty Research Associate; Fellow, Econometric Society, American Statistical Association, Guggenheim Foundation, Sloan Foundation, Humboldt Foundation, Journal of Econometrics; Founding Fellow, International Association for Applied Econometrics, Society for Economic Measurement; Honorary Fellow, International Institute of Forecasters; and Past Editorial Board Member, Econometrica, Review of Economics and Statistics, and International Economic Review.

His academic “family” includes more than 75 Ph.D. students.

All Courses

• ECON2310 - Econometric Mthds/Models

  This course focuses on econometric techniques and their application in economic analysis and decision-making, building on ECON 2300 to incorporate the many regression complications that routinely occur in econometric environments. Micro-econometric complications include nonlinearity, non-normality, heteroskedasticity, limited dependent variables of various sorts, endogeneity and instrumental variables, and panel data. Macro-econometric topics include trend, seasonality, serial correlation, lagged dependent variables, structural change, dynamic heteroskedasticity, and optimal prediction. Students are required to perform several econometric analyses in a modern environment such as R.

• ECON4310 - Macro-Econometrics

  This course provides a deeper treatment of time-series econometric methods used in macroeconomc and financial applications, such as nonstationarity, unit roots, and cointegration; structural evolution and breaks; point, interval and density forecasts; forecast evaluation and combination; vector autoregression including impulse-response estimation and analysis; dynamic factor models and dimensionality reduction; univariate and multivariate stochastic volatility models; and prediction markets.

• ECON7310 - Econometrics II: Methods

  Analysis in time and frequency domains, state space representations, Kalman filtering, conditional heteroskedasticity, nonlinear and nonparametric methods for time series, integration, co-integration, numerical and simulation techniques.

• ECON8320 - Econometrics IV: Adv

  Focuses on macro-econometrics. Topics include comparison of Bayesian and frequentist inference in nonstandard settings (e.g. time series models with persistent roots), Bayesian inference in VARS and DSGE models including modern computational tools such as Gibbs sampling, MCMC, Sequential Monte Carlo, particle filtering, etc., and tools for evaluating DSGE models.

Francis X. Diebold is Paul F. Miller, Jr. and E. Warren Shafer Miller Professor of Social Sciences, and Professor of Economics, Finance, and Statistics, University of Pennsylvania. He has held visiting appointments at Princeton, Chicago, Johns Hopkins, and NYU.

His research focuses on predictive modeling of financial asset markets, macroeconomic fundamentals, climate change, and the interface. He has made well-known contributions to the measurement and modeling of asset-return volatility, business cycles, yield curves, and network connectedness. He has published more than 150 scientific papers and 8 books, and he is regularly ranked among globally most-cited economists.

He is Founding Fellow and Past President, Society for Financial Econometrics; NBER Faculty Research Associate; Fellow, Econometric Society, American Statistical Association, Guggenheim Foundation, Sloan Foundation, Humboldt Foundation, Journal of Econometrics; Founding Fellow, International Association for Applied Econometrics, Society for Economic Measurement; Honorary Fellow, International Institute of Forecasters; and Past Editorial Board Member, Econometrica, Review of Economics and Statistics, and International Economic Review.

His academic “family” includes more than 75 Ph.D. students.

Knowledge at Wharton

• Lawrence Klein: Honoring and Remembering a Model Economist, Knowledge at Wharton - 10/25/2013