This paper corrects some points in the appendix of the paper: George Kapetanios (2003) "Bootstrap Neural Network Cointegration Tests Against Nonlinear Alternative Hypotheses", Studies in Nonlinear Dynamics & Econometrics: Vol. 7: No. 2, Article 2.

Using a new methodology that allows nonlinearities, we find frequent support for external debt sustainability in a number of Latin American countries. Our findings reverse the results for several countries, obtained with traditional unit-root tests and present a richer framework for evaluating...

In the construction of a leading indicator model of economic activity, economists must select among a pool of variables which lead output growth. Usually the pool of variables is large and a selection of a subset must be carried out. This paper proposes an automatic leading indicator model...

We propose a test for neglected nonlinearity that uses an alternative artificial neural network (ANN) specification to the one commonly used in the literature. We use radial basis functions for the "hidden layer" with basis function centres and radii chosen from the sample data set and selected...

This paper presents the theoretical development of a new threshold autoregressive model based on trended time series. The theoretical arguments underlying the model are outlined and a nonlinear economic model is used to derive the specification of the empirical econometric model. Estimation and...

Using a model of deterministic structural change, we revisit several topics in inflation dynamics explored previously using stochastic, time-varying parameter models. We document significant reductions in inflation persistence and predictability. We estimate that changes in the volatility of...

There is a growing literature on the realized volatility (RV) forecasting of asset returns using high-frequency data. We explore the possibility of forecasting RV with factor analysis; once considering the significant jumps. A real high-frequency financial data application suggests that the...

Most macroeconomic data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper...

We consider time series forecasting in the presence of ongoing structural change where both the time series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially...