This paper sifts through explanations for the weakness of the out-of-sample evidence on the Phillips curve relative to the in-sample evidence, focusing on the output gap-based models. One explanation could be that, even when the model are stable, out-of-sample metrics are less powerful than...

The welfare costs of inflation and inflation uncertainty are well documented in the literature and empirical evidence on the link between the two is sparse in the case of Egypt. This paper investigates the causal relationship between inflation and inflation uncertainty in Egypt using monthly...

This paper proposes a new method for empirically validate simulation models that generate artificial time series data comparable with real-world data. The approach is based on comparing structures of vector autoregression models which are estimated from both artificial and real-world data by...

We propose a general protocol for calibration and validation of complex simulation models by an approach based on discovery and comparison of causal structures. The key idea is that configurations of parameters of a given theoretical model are selected by minimizing a distance index between two...

We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark model "without oil" against...

The Granger-causal relationship between the size and dispersion of fluctuations in sub-components of the US Consumer Price Index (CPI) is examined using both in-sample and out-of-sample tests and data from January 1968 to December 2008. Strong in-sample evidence is found for feedback between...

This paper reports a study on the causal dynamics between spot oil price, exchange rates, and stock prices in Poland, the Czech Republic, Hungary, Romania, and Serbia. The results are compared with a benchmark analysis in which U.S. monthly data are used, and time periods are selected according...

We propose a modelling approach involving a series of small-scale factor models. They are connected to each other within a cluster, whose linkages are derived from Granger-causality tests. GDP forecasts are established across the production, income and expenditure accounts within a disaggregated...

The forecasting literature has identi ed two important issues: (i) several predictors have substantial and statistically signi cant predictive content, although only sporadically, and it is unclear whether this predictive content can be exploited reliably; (ii) in-sample predictive content does...

Forecast evaluation often compares a parsimonious null model to a larger model that nests the null model. Under the null that the parsimonious model generates the data, the larger model introduces noise into its forecasts by estimating parameters whose population values are zero. We observe that...