We develop a numerical filtering procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-gaussian state-space models. The procedure approximates necessary integrals using continuous or piecewise-continuous approximations of target densities....

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure approximates necessary integrals using continuous approximations of target densities. Construction is achieved via efficient...

We develop a model of GDP growth under which regime changes are triggered stochastically by an observable tension index, constructed as the geometric sum of deviations of actual GDP growth from a corresponding sustainable rate. Within expansionary regimes, the tension index tends to increase,...