Macroeconomic forecasts are frequently produced, widely published, intensively discussed and comprehensively used. The formal evaluation of such forecasts has a long research history. Recently, a new angle to the evaluation of forecasts has been addressed, and in this review we analyse some recent developments from that perspective. The literature on forecast evaluation predominantly assumes th...

While the computable general equilibrium (CGE) model is a well established tool used in economic analyses, it is often viewed as a blackbox because of the complexity of the model structure and the many assumptions made regarding the underlying calibration data and model parameters. To characterize the behavior of the CGE model, we perform a large-scale Monte Carlo experiment to examine its sens...

Because of heterogeneity across regions, economic policy measures are increasingly targeted at the regional level. As a result, the need for economic forecasts at a subnational level is rapidly increasing. The data available to compute regional forecasts is usually based on a pseudo-panel that consists of a limited number of observations over time, and a large number of areas (regions) strongly...

This paper compares model-based and reduced-form forecasts of financial volatility when high-frequency return data are available. We derived exact formulas for the forecast errors and analyzed the contribution of the “wrong” data modeling and errors in forecast inputs. The comparison is made for “feasible” forecasts, i.e. we assumed that the true data generating process, latent states and param...

The ubiquity of strange attractors in nature suggests that nonlinear modeling techniques can improve performance in some signal processing applications. We introduce Mixed State Markov Models (MSMMs), a refinement of Hidden Filter HMMs, and apply both to a synthetic Double Scroll time series. Forecasts by HFHMMs diverge after a few steps. Using ad hoc procedures, forecasts by MSMMs, even models...