makes predicting these shifts hard. Hence, this paper asks whether forecasting them is necessary for optimal rotation … forecasting, we suggest a method utilizing Monte-Carlo simulations to obtain a credible upper bound on these losses. We show that …

In this paper, we disentangle tax revenue forecast errors into influences stemming from wrong macroeconomic assumptions … the forecast errors of the energy tax and the sales taxes. For the overall tax sum, more than two-third of the error can … can reduce tax revenue forecast errors …

-switching models, and forecast combination to predict the dynamics in the S&P 500. First, we aggregate the weekly information of 115 …

We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency … for the presence of selective attention offer improved fitting and forecasting results. Specifically, we document a …

We examine forecast accuracy and efficiency of the Social Security Administration’s projections for cost rate, trust …

How does competition affect information acquisition of firms and thus the response of inflation and output to monetary … uncertainty about inflation as a non-targeted moment …

We study how domestic and global output gaps affect CPI inflation. We use a New-Keynesian Phillips curve framework …1-2017Q4 period. We find broadly that both global and domestic output gaps are significant drivers of inflation both in … output gaps on inflation …

aggregates are time-varying, much of the literature on forecasting aggregates considers the case of linear aggregates with fixed … with simulations. Two examples based on European unemployment and inflation series are used to illustrate the virtue of the … theoretical setup and the forecasting results. …

techniques are applied to monthly inflation series of 21 OECD countries and it is found that average forecasting methods in …This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks …