Forecasting Growth of Australian Industrial Output Using Interest Rate Models
نویسنده
چکیده
We examine the ability of short rates and yield spreads to forecast the growth in Australian industrial output. We find that since 1990, the short rate has a significant increase in its predictive power for forecasting output growth in many industries. We document this increase. The yield spread, on the other hand, is useful in predicting the growth of industries with a `longer' production cycle, such as manufacturing and wholesale trade. Hence, the predictive power of the yield spread on total GDP, is mainly from its ability to forecast these industries. Our out-of-sample forecasts show that yield spread is a good forecasting device for many industries, particular for output growth over longer horizons.
منابع مشابه
A hybrid computational intelligence model for foreign exchange rate forecasting
Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...
متن کاملModeling and forecasting US presidential election using learning algorithms
The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are co...
متن کاملOverview and Comparison of Short-term Interval Models for Financial Time Series Forecasting
In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficien...
متن کاملForecasting 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...
متن کاملInflation Determinants in Low and High Frequencies: An Implication of Spectral Analysis to Iran
There is no evidence that previous studies, available to Iran’s inflation literature, have used spectral methodology to analyze a possible relationship between inflation and its main determinants within a specific period. Accordingly, the present study investigates the effects of money growth, real output growth, output gap and interest rate changes on inflation at low and high frequencies...
متن کامل