We use several models using classical and Bayesian methods to forecast employment for eight sectors of the US economy. In addition to using standard vector-autoregressive and Bayesian vector autoregressive models, we also augment these models to include the information content of 143 additional...

We use several models using Bayesian and classical methods to forecast employment for eight sectors of the US economy. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of 143 additional monthly series in some models....

We implement several Bayesian and classical models to forecast employment for eight sectors of the US economy. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of 143 additional monthly series in some models. Several...

We implement several Bayesian and classical models to forecast employment for eight sectors of the US economy. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of 143 additional monthly series in some models. Several...

We use monthly data covering a century-long sample period (1915–2021) to study whether geopolitical risk helps to forecast subsequent gold volatility. We account not only for geopolitical threats and acts, but also for 39 country-specific sources of geopolitical risk. The response of...

We examine the time-series relationship between housing prices in Los Angeles, Las Vegas, and Phoenix. First, temporal Granger causality tests reveal that Los Angeles housing prices cause housing prices in Las Vegas (directly) and Phoenix (indirectly). In addition, Las Vegas housing prices cause...

We implement several Bayesian and classical models to forecast housing prices in 20 US states. In addition to standard vector-autoregressive (VAR) and Bayesian vector autoregressive (BVAR) models, we also include the information content of 308 additional quarterly series in some models. Several...

We study the directional accuracy of South African survey data of short-term and longer-term inflation forecasts. Upon applying techniques developed for the study of relative operating characteristic (ROC) curves, we find evidence that forecasts contain information with respect to the subsequent...

Accurate forecasts of home sales can provide valuable information for not only, policy makers, but also financial institutions and real estate professionals. Given this, our analysis compares the ability of two different versions of Singular Spectrum Analysis (SSA) methods, namely Recurrent SSA...

We use South African survey data to study whether short-term inflation forecasts are unbiased. Depending on how we model a forecaster’s information set, we find that forecasts are biased due to forecaster herding. Evidence of forecaster herding is strong when we assume that the information set...