This chapter summarizes recent literature on asymptotic inference about forecasts. Both
analytical and simulation based methods are discussed. The emphasis is on techniques …

This paper analyses the relationship between real GDP and CO2 emissions for 17
transitional economies based on a series of annual data from 1997 to 2014. The analysis …

In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting
among non-linear forecasting models for economic and financial time series. We review …

This study developed a novel model, HGA-SVR, for type of kernel function and kernel
parameter value optimization in support vector regression (SVR), which is then applied to …

Over the last decade, governments throughout eastern and southern Africa have
increasingly used strategic reserves and/or marketing boards to influence grain market …

This work investigates how the state of credit markets affects the impact of fiscal policies. We
estimate a threshold vector autoregression (TVAR) model on US quarterly data for the …

The study aims to propose a family of Artificial Neural Networks (ANN) model to achieve
improvement in modeling nonlinear cointegration compared to Hansen and Seo (2002) …

Cointegration is studied for a non‐linear autoregressive process characterized by
discontinuous and regime‐dependent equilibrium or error correction. Here the …

This paper proposes a model to predict recessions that accounts for non‐linearity and a
structural break when the spread between long‐and short‐term interest rates is the leading …

This study develops a novel model, GA-SVR, for parameters optimization in support vector
regression and implements this new model in a problem forecasting maximum electrical …