Predicting National and Regional Recessions Using Probit Modeling and Interest-Rate Spreads

Abstract This study extends the work of Estrella and Mishkin (1996 , 1998 ) to show that interest‐rate spreads and probit modeling can be used to predict recessions in many states as well as the nation. State recessions are defined as two or more consecutive quarters of declining real gross state product. The yield spread, SPREAD, is defined as the difference between the 10‐year Treasury bond rate and the three‐month Treasury bill rate. The national results are similar to those obtained by Estrella and Mishkin. Probit models are estimated for all 50 states using SPREAD and unemployment insurance claims, UI, as alternative explanatory variables. For 34 of the 50 states, SPREAD is significant at the 0.01 level as a predictor of state recessions. Much weaker results are obtained using UI. Simulations for the 1979–2001 period are used to compute loss functions for the national and state models at probability screens of 30, 40, 50, and 60 percent. The results demonstrate that probit models based on SPREAD can be useful in improving business and policy decisions in many states.     

DRS. MUTH AND MILLS MEET DR. TIEBOUT: INTEGRATING LOCATION‐SPECIFIC AMENITIES INTO MULTI‐COMMUNITY EQUILIBRIUM MODELS*

ABSTRACT We consider the problem of integrating spatial amenities into locational equilibrium models with multiple jurisdictions. We provide sufficient conditions under which models that assume a single housing price in each community continue to apply in the presence of location‐specific amenities that vary both within and across communities. If these conditions are satisfied, the models, estimation methods, and results in Epple and Sieg (1999) are valid in the presence of (potentially unobserved) location‐specific amenities. We also show how to construct sufficient statistics that capture location specific spatial heterogeneity. We apply these techniques using data from the Pittsburgh metropolitan area. We find that these amenity measures capture proximity to important local employment centers as well as heterogeneity in school quality within a given school district.