A random walk with drift is a good univariate representation of US GDP. This paper shows, however, that US economic downturns have been associated with pre- dictable short-term recoveries and with changes in long-term GDP forecasts that are substantially smaller than the initial drop. To detect these predictable changes, it is important to use a multivariate time series model. We discuss reasons why univariate representations can miss key characteristics of the underlying variable such as predictability, especially during recessions
We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determinati...
The effects of data uncertainty on real-time decision-making can be reduced by predicting data revis...
International audienceIn this paper we re-analyze the nature of the trend (deterministic or stochast...
A random walk with drift is a good univariate representation of US GDP. This paper shows, however, t...
This paper advances beyond the prediction of the probability of a recession by also considering its ...
This paper estimates, using stochastic simulation and a multicountry macroeconometric model, the fra...
The professional forecasters’ inability to anticipate macroeconomic recessions is well documented. T...
This paper documents a new stylized fact of the greater macroeconomic stability of the U.S. economy ...
In this paper, we replicate the main results of Rudebusch and Williams (2009), who show that the use...
Predictive regressions are linear specifications linking a noisy variable such as stock returns to p...
Most representative decision-tree ensemble methods have been used to examine the variable importance...
This paper conducts an empirical analysis of the heterogeneity of recessions in monthly U.S. coincid...
This paper investigates the factors associated with the occurrences of US recessions over the period...
This study uses Markov-switching models to evaluate the informational content of the term structure ...
We re-examine predictability of US stock returns. Theoretically well-founded models predict that sta...
We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determinati...
The effects of data uncertainty on real-time decision-making can be reduced by predicting data revis...
International audienceIn this paper we re-analyze the nature of the trend (deterministic or stochast...
A random walk with drift is a good univariate representation of US GDP. This paper shows, however, t...
This paper advances beyond the prediction of the probability of a recession by also considering its ...
This paper estimates, using stochastic simulation and a multicountry macroeconometric model, the fra...
The professional forecasters’ inability to anticipate macroeconomic recessions is well documented. T...
This paper documents a new stylized fact of the greater macroeconomic stability of the U.S. economy ...
In this paper, we replicate the main results of Rudebusch and Williams (2009), who show that the use...
Predictive regressions are linear specifications linking a noisy variable such as stock returns to p...
Most representative decision-tree ensemble methods have been used to examine the variable importance...
This paper conducts an empirical analysis of the heterogeneity of recessions in monthly U.S. coincid...
This paper investigates the factors associated with the occurrences of US recessions over the period...
This study uses Markov-switching models to evaluate the informational content of the term structure ...
We re-examine predictability of US stock returns. Theoretically well-founded models predict that sta...
We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determinati...
The effects of data uncertainty on real-time decision-making can be reduced by predicting data revis...
International audienceIn this paper we re-analyze the nature of the trend (deterministic or stochast...