This study analyzes Texas state and metropolitan economic downturn predictability. Publicly available Federal Reserve Bank of Dallas dynamic factor business cycle indices are used in the analysis. Sample data cover Texas and nine of its largest metropolitan economies from January 1991 through May 2018. Dynamic autoregressive profit downturn models are estimated using the United States yield spread plus other regional and macroeconomic variables. Predictive accuracy is analyzed using in-sample model simulations. Results indicate that narrowing yield spreads, real peso appreciation, and oil price declines are generally found to increase recession likelihoods. Varying lag structures and equation specifications indicate that the state and metropolitan economies exhibit distinct timing patterns and follow different paths and each has an individual business cycle. Good predictive properties are also documented for the equations.
Appears in: Regional Statistics, Vol. 13. No. 1. 2023: 55–75; DOI: 10.15196/RS130103