Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

This paper surveys recent developments related to the smooth transition autoregressive
(STAR) time series model and several of its variants. We put emphasis on new methods for …

What are the effects of uncertainty shocks on unemployment dynamics? We answer this
question by estimating non-linear (Smooth-Transition) VARs with post-WWII US data. The …

In this course we perform an introduction to Bayesian methods, we show some basic
definitions and properties of the bayesian approach. We have taken the content from the …

We assess the performance of an index of Google job-search intensity as a leading indicator
for predicting the monthly US unemployment rate. We carry out a deep out-of-sample …

The threshold autoregressive (TAR) model developed by Howell Tong has been
enormously influential in economics. A simple illustration of the depth of this influence is to …

We estimate a nonlinear VAR to quantify the impact of US economic policy uncertainty
shocks on the Canadian unemployment rate in booms and busts. We find strong evidence in …

Bayesian Econometric Methods examines principles of Bayesian inference by posing a
series of theoretical and applied questions and providing detailed solutions to those …

This paper evaluates the properties of a joint and sequential estimation procedure for
estimating the parameters of single and multiple threshold models. We initially proceed …

We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best
leading indicator to predict the US unemployment rate. We perform a deep out-of-sample …