This chapter examines the problems of dealing with trending type data when there is uncertainty over whether or not we really have unit roots in the data. This uncertainty is practical – for many macroeconomic and financial variables theory does not imply a unit root in the data however unit...

This paper considers the problem of forecasting real and financial macroeconomic variables across a large number of countries in the global economy. To this end, a global vector autoregressive (GVAR) model previously estimated over the 1979:Q1–2003:Q4 period by Dees, de Mauro, Pesaran, and...

This paper provides a framework for the early assessment of current U.S. nominal GDP growth, which has been considered a potential new monetary policy target. The nowcasts are computed using the exact amount of information that policy-makers have available at the time predictions are made....

We use TVP models and real-time data to describe the evolution of the leading properties of the yield spread for output growth in five European economies and in the US over the last decades and until the third quarter of 2010. We evaluate the predictive performance of benchmark term-structure...

Evidence from a large and growing empirical literature strongly suggests that there have been changes in inflation and output dynamics in the United Kingdom. This is largely based on a class of econometric models that allow for time-variation in coefficients and volatilities of shocks. While...

This paper proposes a model to predict recessions that accounts for non-linearity and a structural break when the spread between long- and short-term interest rates is the leading indicator. Estimation and model selection procedures allow to estimate and to identify time varying non-linearity in...

In this study, we model realized volatility constructed from intraday high-frequency data. We explore the possibility of confusing long memory and structural breaks in the realized volatility of the following spot exchange rates: EUR/USD, EUR/JPY, EUR/CHF, EUR/GBP, and EUR/AUD. The results show...

This paper provides a framework for the early assessment of current U.S. nominal GDP growth, which has been considered a potential new monetary policy target. The nowcasts are computed using the exact amount of information that policy-makers have available at the time predictions are made....

In this paper, we compare the Constant Conditional Correlation (CCC) model to its dynamic counterpart, the Dynamic Conditional Correlation (DCC) model with respect to its accuracy for forecasting the Value-at-Risk of financial portfolios. Additionally, we modify these benchmark models by...

Correlation models, such as Constant Conditional Correlation (CCC) GARCH model or Dynamic Conditional Correlation (DCC) GARCH model, play a crucial role in forecasting Value-at-Risk (VaR) or Expected Shortfall (ES). The additional inclusion of constant correlation tests into correlation models...