Arbeitspapier
Artificial neural network regression models: Predicting GDP growth
Artificial neural networks have become increasingly popular for statistical model fitting over the last years, mainly due to increasing computational power. In this paper, an introduction to the use of artificial neural network (ANN) regression models is given. The problem of predicting the GDP growth rate of 15 industrialized economies in the time period 1996-2016 serves as an example. It is shown that the ANN model is able to yield much more accurate predictions of GDP growth rates than a corresponding linear model. In particular, ANN models capture time trends very flexibly. This is relevant for forecasting, as demonstrated by out-of-sample predictions for 2017.
- Language
-
Englisch
- Bibliographic citation
-
Series: HWWI Research Paper ; No. 185
- Classification
-
Wirtschaft
Neural Networks and Related Topics
Forecasting Models; Simulation Methods
Optimization Techniques; Programming Models; Dynamic Analysis
Economic Growth and Aggregate Productivity: General
- Subject
-
neural network
forecasting
panel data
- Event
-
Geistige Schöpfung
- (who)
-
Jahn, Malte
- Event
-
Veröffentlichung
- (who)
-
Hamburgisches WeltWirtschaftsInstitut (HWWI)
- (where)
-
Hamburg
- (when)
-
2018
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Jahn, Malte
- Hamburgisches WeltWirtschaftsInstitut (HWWI)
Time of origin
- 2018
Other Objects (12)
Predicting monetary policy using artificial neural networks
Predicting Monetary Policy Using Artificial Neural Networks
Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings
Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties
Artificial neural networks for predicting real estate prices
Artificial neural network in predicting bladder cancer recurrence
Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models
Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke
An artificial neural network approach for predicting hypertension using NHANES data
Inclusive Multiple Model Using Hybrid Artificial Neural Networks for Predicting Evaporation
Predicting Belgium’s GDP using targeted bridge models
Predicting GDP components: do leading indicators increase predictability?
Predicting monetary policy using artificial neural networks
Predicting Monetary Policy Using Artificial Neural Networks
Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings
Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties
Artificial neural networks for predicting real estate prices
Artificial neural network in predicting bladder cancer recurrence
Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models
Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke
An artificial neural network approach for predicting hypertension using NHANES data
Inclusive Multiple Model Using Hybrid Artificial Neural Networks for Predicting Evaporation
Predicting Belgium’s GDP using targeted bridge models
Predicting GDP components: do leading indicators increase predictability?
Predicting monetary policy using artificial neural networks
Predicting Monetary Policy Using Artificial Neural Networks
Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings
Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties
Artificial neural networks for predicting real estate prices
Artificial neural network in predicting bladder cancer recurrence
Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models
Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke
An artificial neural network approach for predicting hypertension using NHANES data
Inclusive Multiple Model Using Hybrid Artificial Neural Networks for Predicting Evaporation
Predicting Belgium’s GDP using targeted bridge models