Showing 1 - 10 of 19
on particular paths of policy instruments. Even though conditional forecasting is common, there has been little work on …
Persistent link: https://www.econbiz.de/10013046359
subset of variables common to the larger sets of variables included in the competing forecasting models. We consider an out … comparing the predictive content of credit spreads to growth in real stock prices for forecasting U.S. real GDP growth …
Persistent link: https://www.econbiz.de/10014177868
This paper surveys recent developments in the evaluation of point forecasts. Taking West’s (2006) survey as a starting point, we briefly cover the state of the literature as of the time of West’s writing. We then focus on recent developments, including advancements in the evaluation of...
Persistent link: https://www.econbiz.de/10014177872
comparably to quantile regression for estimating and forecasting tail risks, complementing BVARs' established performance for … forecasting and structural analysis …
Persistent link: https://www.econbiz.de/10012843862
. Instead, the cross-equation no-arbitrage restrictions on the factor loadings play a marginal role in producing forecasting …
Persistent link: https://www.econbiz.de/10012822660
This paper shows entropic tilting to be a flexible and powerful tool for combining medium-term forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting systematically improves the accuracy of both point and density forecasts, and...
Persistent link: https://www.econbiz.de/10012972351
Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … instability in a forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to … improve the forecasting performance …
Persistent link: https://www.econbiz.de/10013047531
This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, as well as classical and Bayesian quantile regressions) and also different...
Persistent link: https://www.econbiz.de/10012834306
Recent research has shown that a reliable vector autoregressive model (VAR) for forecasting and structural analysis of … priors. This is important both for reduced form applications, such as forecasting, and for more structural applications, such …
Persistent link: https://www.econbiz.de/10012983057
Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting … apply shrinkage in a classical or Bayesian framework. We focus on forecasting accuracy, using for evaluation both quantile …
Persistent link: https://www.econbiz.de/10014077606