finance; for such tasks as pattern reorganization, and time series forecasting, have dramatically increased. Many central … banks use forecasting models based on ANN methodology for predicting various macroeconomic indicators, like inflation, GDP … ANN model with conventional univariate time series forecasting models such as AR(1) and ARIMA based models and observed …

contribute to anchoring of expectations about nominal variables; its eects on disagreement about real variables are moderate. …

We assess the power of artificial neural network models as forecasting tools for monthly inflation rates for 28 OECD … countries. For short out-of-sample forecasting horizons, we find that, on average, for 45% of the countries the ANN models were … models can also serve as a credible tool for forecasting inflation. …

concept of the guaranteed upper risk of forecasting and the d-admissible distortion level is defined here. In order to make …

This paper uses a panel VAR (PVAR) approach to estimating, analysing and forecasting price dynamics in four different …

finance; for such tasks as pattern reorganization, and time series forecasting, have dramatically increased. Many central … banks use forecasting models based on ANN methodology for predicting various macroeconomic indicators, like inflation, GDP … ANN model with conventional univariate time series forecasting models such as AR(1) and ARIMA based models and observed …

Macroeconomic expectations of various economic agents are characterized by substantial cross-sectional heterogeneity …. In this paper, we focus on expectations heterogeneity among professional forecasters. We first present stylized facts and … discuss theoretical explanations for heterogeneous expectations. We then provide an overview of the empirical evidence …