The accuracy of inflation forecasts has important implications for macroeconomic stability and real interest rates in economies with nominal rigidities. Erroneous forecasts destabilize output, undermine the conduct of monetary policy under inflation targeting and affect the cost of both short and long-term government borrowing. We propose a new method for forecasting inflation that combines individual forecasts using time-varying-coefficient estimation along with an alternative method based on neural nets. Its application to forecast data from the US and the euro area produces superior performance relative to the standard practice of using individual or linear combinations of individual forecasts, especially during periods marked by structu...
This thesis examines the effects of macroeconomic factors on inflation level and volatility in the E...
Proceedings of the International Conference on Science and Science Education August 2015, p. MA.103-...
This paper investigates the impact of both asset and macroeconomic forecast errors on inflation fore...
This paper investigates whether a specific type of a recurrent neural network, in particular Jordan ...
The aim of the article is to analyze inflation factors and their influence on the consumer price ind...
Linear models reach their limitations in applications with nonlinearities in the data. In this paper...
This paper applies linear and neural network-based "thick" models for forecasting inflation based on...
Forecasts are presented for the 12-month ahead US rate of inflation measured by the chain weighted p...
This paper compares the out-of-sample inflation forecasting performance of two non-linear models; a ...
Forecasting methods of the neural network, ARIMA, ARIMA-GARCH, exponential smoothing and others are ...
In this work we use a Neural Network model to forecast Mexican inflation. Related works forecast inf...
We expand Nakamura’s (2005) neural network based inflation forecasting experiment to an alternative ...
In this study the prediction capabilities of Artificial Neural Networks and typical econometric meth...
In times of pronounced nonlinearity of macroeconomic variables and in situations when variables are ...
AbstractOne of the key issues in constructing monetary policy is accurate prediction of the inflatio...
This thesis examines the effects of macroeconomic factors on inflation level and volatility in the E...
Proceedings of the International Conference on Science and Science Education August 2015, p. MA.103-...
This paper investigates the impact of both asset and macroeconomic forecast errors on inflation fore...
This paper investigates whether a specific type of a recurrent neural network, in particular Jordan ...
The aim of the article is to analyze inflation factors and their influence on the consumer price ind...
Linear models reach their limitations in applications with nonlinearities in the data. In this paper...
This paper applies linear and neural network-based "thick" models for forecasting inflation based on...
Forecasts are presented for the 12-month ahead US rate of inflation measured by the chain weighted p...
This paper compares the out-of-sample inflation forecasting performance of two non-linear models; a ...
Forecasting methods of the neural network, ARIMA, ARIMA-GARCH, exponential smoothing and others are ...
In this work we use a Neural Network model to forecast Mexican inflation. Related works forecast inf...
We expand Nakamura’s (2005) neural network based inflation forecasting experiment to an alternative ...
In this study the prediction capabilities of Artificial Neural Networks and typical econometric meth...
In times of pronounced nonlinearity of macroeconomic variables and in situations when variables are ...
AbstractOne of the key issues in constructing monetary policy is accurate prediction of the inflatio...
This thesis examines the effects of macroeconomic factors on inflation level and volatility in the E...
Proceedings of the International Conference on Science and Science Education August 2015, p. MA.103-...
This paper investigates the impact of both asset and macroeconomic forecast errors on inflation fore...