Stephen M. Miller (Economics; Center for Business and Economic Research) published “Estimating U.S. housing price network connectedness: Evidence from dynamic Elastic Net, Lasso, and ridge vector autoregressive models" in the International Review of Economics and Finance with David Gabauer, Academy of Data Science in Finance, Vienna, Austria and Institute of Corporate Finance, Johannes Kepler University, Linz, Austria; Rangan Gupta, Department of Economics, University of Pretoria, Pretoria, South Africa; and Hardik A. Marfatia, Department of Economics, Northeastern Illinois University, Chicago.
This paper investigates the dynamic connectedness of random shocks to housing prices between the 50 U.S. states and the District of Columbia, using standard vector autoregressive (VAR) model as well as three VAR models with shrinkage effects. The transmission of real housing return shocks on a regional basis flows from Southern states to the other three regions. The Northeast receives those shocks. The West receives shocks from the South and transmits shocks to the Midwest and the Northeast. Finally, the Midwest transmits shocks to the Northeast and receives shocks from the South and the West. Since the housing market affects the business cycle, the Federal Reserve can monitor housing market movements in the net transmitter states to gather information about the beginnings of the housing market cycle.
