Based on a large international panel of surveyed GDP forecasts I analyze the frequency of forecast revisions and the factors that influence the likelihood of forecast revisions. I find that each month on average 40%–50% of forecasters revise their forecasts. In addition, I find that the...

Estimation of the non-linear Constant Elasticity of Scale (CES) function is generally considered problematic due to convergence problems and unstable and/or meaningless results. These problems often arise from a non-smooth objective function with large flat areas, the discontinuity of the CES...

We examine asymmetry in the loss function of Japanese corporate executives in their output growth forecasts and test for rationality of the forecasts under the assumption of a possibly asymmetric loss function. We find evidence of asymmetry and support for rationality under an asymmetric loss...

This paper extends the Markov-switching vector autoregressive models to accommodate both the typical lack of synchronicity that characterizes the real-time daily flow of macroeconomic information and economic indicators sampled at different frequencies. The results of the empirical application...

Recent literature has reported situations in which discretion dominates timeless perspective in the presence of elements that reduce the slope of the New Keynesian Phillips curve. Considering a model-consistent welfare metric inhibits this mechanism in the standard New Keynesian framework.

Housing prices diverge from construction prices after 1997 in four major countries. Besides, total-factor productivity (TFP) differences between construction and the general economy account for the evolution of construction prices in the US and Germany, but not in the UK and Spain.

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.

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...