Much of the US inflation forecasting literature deals with examining the ability of macroeconomic indicators to predict the mean of future inflation, and the overwhelming evidence suggests that the macroeconomic indicators provide little or no predictability. In this paper, we expand the scope...

It is recognised that the understanding and accurate forecasts of key macroeconomic variables are fundamental for the success of any economic policy. In the case of monetary policy, many efforts have been made towards understanding the relationship between past and expected values of inflation,...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

I present evidence that higher frequency measures of inflation expectations outperform lower frequency measures of inflation expectations in tests of accuracy, predictive power, and rationality. For decades, the academic literature has focused on three survey measures of expected inflation: the...

In this paper, we propose a simulation-based method for computing point and density forecasts for univariate noncausal and non-Gaussian autoregressive processes. Numerical methods are needed to forecast such time series because the prediction problem is generally nonlinear and no analytic...

This paper criticises the econometric inflation uncertainty proxies found in the literature, which show an overly optimistic picture about our real ability to forecast, and highlights the sharp contrast between the evidence portrayed by that literature and the evidence conveyed by the literature...

The paper focuses on the comparison of the direct and iterated AR predictors when Xt is a difference stationary process. In particular, it provides some useful results for comparing the efficiency of the two predictors and for extracting the trend from macroeconomic time series using the two...

An artificial neural network (hence after, ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. In previous two decades, ANN applications in economics and finance; for such tasks as pattern reorganization, and...

After two types of inflation uncertainty are derived within a time-varying parameter model with GARCH specification, the relationship between inflation uncertainty and interest rates for safe assets is investigated. The results support the existence of a ‘‘flight to quality’’ effect.

The formation of the European Union (EU) is the one of the biggest political – economic events of the last 50 years. The aim of this study is to develop EU economy functioning system dynamic model. Main research method is system dynamics. General scheme of EU economy system dynamic model is...