Matthew Harding

Research: Econometrics, macro-finance, political economics
Current Research: Random matrix theory; high-dimensional data; factor models, nonlinear random coefficients models; finite sample bias; impact of global factors on the US economy; voting behavior in the US congress
Teaching: Econometrics, political economics

Matthew Harding is an economist who conducts research on theoretical and applied econometrics. He is an Assistant Professor in the Department of Economics at Stanford University and a SIEPR Faculty Fellow.

His work is concerned with the estimation of econometric models with latent variables and unobserved heterogeneity. He uses Random Matrix Theory to uncover meaningful economic structures from large panel data. This work focuses on the statistical properties of the spectral decompositions of generalized dependency matrices such as delay correlations, commutators and adjacency matrices in both linear and nonlinear factor models. His research also explores the use of nonparametric Bayesian methods and quantile regression methods in the estimation of nonlinear econometric models with unobserved heterogeneity such as random coefficients models, panel probit, hazard models and stochastic conditional duration models. This research has important implications for the estimation of financial risk, the measurement of consumer preferences from scanner data, predicting the effect of economic news on trading activity, modeling unemployment durations and evaluating the determinants of R&D activity.

Professor Harding believes that solving the current energy and environmental crisis requires an in-depth understanding of both consumer preferences and political economy. His research on energy is primarily concerned with (a) the political economy of the Middle East and its complex connections to world economic factors (b) the measurement of preferences for energy efficiency and the impact of economic policy on consumer choice. His research on energy economics is financed by two major grants from the Presidential Fund for Innovation in International Studies and the Precourt Institute for Energy Efficiency.