We propose a test for the evaluation of statistical acceptability of a functional constraint which is imposed on parameters in the mixed data sampling regressions. The asymptotic behavior of the test statistic is characterized and a few other extensions are discussed.

We compare forecasts from different adaptive learning algorithms and calibrations applied to US real-time data on inflation and growth. We find that the Least Squares with constant gains adjusted to match (past) survey forecasts provides the best overall performance both in terms of forecasting...

Notwithstanding high unemployment following the Great Recession, inflation in the United States has been remarkably stable. We find that a traditional Phillips curve describes the behavior of inflation reasonably well since the 1960s. Using a non-linear Kalman filter that allows for time-varying...

A maximal overlap discrete wavelet transform is used to obtain time scale decompositions of economic forecasts and their errors. The generated time scale components can be used in loss measures and tests for comparing forecast accuracy to evaluate whether the forecasts accurately capture the...

This paper suggests using a unit t-value criterion in imposing restrictions on lags to formulate a subset vector autoregressive (VAR) model for the purpose of point forecasts. Among any other alternative models nested to the initial VAR model, this less restrictive modeling strategy produces the...

We develop a simple approach to identify economic news and monetary shocks at a high frequency. The approach is used to examine financial market developments in the United States following the Federal Reserve’s May 22, 2013 taper talk suggesting that it would begin winding down its...

We examine the efficiency of German forecasts for output growth and inflation allowing for an asymmetric loss function of the forecasters. We find the loss of output growth forecasts to be approximately symmetric while there is an asymmetry in the loss of the inflation forecasts. The information...

We test for causality between inflation and its associated uncertainty by means of both in-sample and out-of-sample modelling. Our findings indicate that the impact of inflation on inflation uncertainty is more pronounced than the reverse causal effect.

In this note, we argue that tests of overidentifying restrictions give little information on the validity of the moment conditions implied by the underlying economic model, and therefore are mute about the possibility of identifying the parameters of interest.

We highlight a subtle identification problem that afflicts models for non-negative data in which the conditional expectation is specified as the product of a logit and an exponential function. The results are illustrated with an empirical model for medical expenditures.