Forecasting GDP growth using mixed-frequency models with switching regimes

Forecasting GDP Growth Using ANN Model with Genetic Algorithm

Applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. Artificial Neural Networks (ANN) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. Most ANN models applied in Economics use the gradient descent method as their learning algorithm. However, t...

forecasting gdp growth using ann model with genetic algorithm

applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. artificial neural networks (ann) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. most ann models applied in economics use the gradient descent method as their learning algorithm. however, t...

Modeling and forecasting China's GDP data with time series models

The gross domestic product (GDP), a basic measure of an economy's economic performance, is the market value of all final goods and services produced within the borders of a nation in a year. In this paper, the features of quarterly data of China’s GDP obtained from aggregated annual data of the National Bureau of Statistics of China starting from 1962 to 2008 are studied. Testing for existing a...

Using Copulas in Statistical Models of Switching Regimes

By a theorem due to Sklar, a multivariate distribution can be represented in terms of its underlying margins by binding them together using a copula function. By exploiting this representation, the “copula approach” to statistical modelling proceeds by specifying distributions for each margin and a copula function. In this paper, a number of families of copula functions are given, with attentio...

Forecasting Corn and Soybean Basis Using Regime-Switching Models by