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Persistent link: https://www.econbiz.de/10001558168
By employing large panels of survey data for the UK economy, we aim at reviewing linear approaches for regularisation and dimension reduction combined with techniques from the machine learning literature, like Random Forests, Support Vector Regressions and Neural Networks for forecasting GDP...
Persistent link: https://www.econbiz.de/10013226235
This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area economies. The results indicate that the Automatic Leading...
Persistent link: https://www.econbiz.de/10013053184
Persistent link: https://www.econbiz.de/10010516546
This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area economies. The results indicate that the Automatic Leading...
Persistent link: https://www.econbiz.de/10013025082
Persistent link: https://www.econbiz.de/10012795057
Persistent link: https://www.econbiz.de/10012305256
Persistent link: https://www.econbiz.de/10014443196
This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area economies. The results indicate that the Automatic Leading...
Persistent link: https://www.econbiz.de/10015298694
This paper develops a method for producing current-quarter forecasts of GDP growth with a (possibly large) range of available within-the-quarter monthly observations of economic indicators, such as employment and industrial production, and financial indicators, such as stock prices and interest...
Persistent link: https://www.econbiz.de/10013065065