In the paper we propose a new methodological approach to core in- flation estimation, based on a frequency domain principal components estimator, suited to estimate systems of fractionally cointegrated processes. The proposed core inflation measure is the scaled common persistent factor in...

Equilibrium correction models of the price level are often used to model inflation. Such models assume that the long-run markup of prices over costs is fixed, but this may not be true for the Euro area economy, which has undergone major structural reforms over the last 25 years. We allow for...

The paper presents an incomplete competition model (ICM), where inflation is determined jointly with unit labour cost growth. The ICM is estimated on data for the Euro area and evaluated against existing models, i.e. the implicit inflation equation of the Area Wide model (AWM) - cf. Fagan, Henry...

This paper carries out another evaluation on a highly debated property of inflation dynamics, namely its persistence. We study inflation dynamics for the United States since 1959 with a time-varying methodology where the intercept, variance and persistence are allowed to vary over time. We...

A key application of long memory time series models concerns inflation. Long memory implies that shocks have a long-lasting effect. It may however be that empirical evidence for long memory is caused by neglecting one or more level shifts. Since such level shifts are not unlikely for inflation,...

The Rational Expectations Permanent Income Hypothesis implies that consumption follows a random walk. However, most empirical tests have rejected the hypothesis. Those empirical tests are based on linear models. If the data generating process is non-linear, conventional tests may not be able to...

The back-propagation neural network (BPN) model has been the most popular form of artificial neural network model used for forecasting, particularly in economics and finance. It is a static (feed-forward) model which has a learning process in both hidden and output layers. In this paper, we...

Artificial neural network modeling has recently attracted much attention as a new technique for estimation and forecasting in economics and finance. The chief advantages of this new approach are that such models can usually find a solution for very complex problems, and that they are free from...

This paper presents tests of the Cagan hyperinflation-money demand model which have several advantages relative to those in the literature. They do not confound specification error and rational bubbles, are implementable with a linear procedure, and are frequently able to detect the periodically...

This paper proposes an inflation forecasting model for Togo through a simple autoregressive (AR) model. Using data on inflation measured by the annual percentage change in the consumer price index (CPI), ranging from 1967 to 2019, we find that a simple AR(1)model can help forecasting inflation...