LEADING INDICATORS;
MARKOV-SWITCHING MODEL;
MAXIMUM LIKELIHOOD ESTIMATION;
MONTHLY INDUSTRIAL PRODUCTION;
TIME-VARYING TRANSITION PROBABILITY;
D O I:
10.2307/1392086
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
This article examines differences in expansionary and contractionary phases of the business cycle. By extending the nonlinear Markov-switching estimation method of Hamilton to incorporate time-varying probabilities of transitions between the phases, the marginal benefits of the time-varying transition probability Markov-switching model are highlighted. Using this technique, I document the high correlation between the evolution of the phases inferred from the model and traditional reference cycles for monthly output data. Many of the economic variables that determine the time-varying probabilities help to predict turning points. The predictive power of standard leading indicators is evaluated and compared.