In this paper, an adaptive smoothing forecasting approach based on evolutionary spectra as developed by Rao and Shapiro (1970) is applied to the 3003 time series of various types and lengths used in the M3-Competition (Makridakis and Hibon, 2000). Comparisons of out-of-sample forecasts are made...

In marketing applications, it is common that some key covariates in a regression model, such as marketing mix variables or consumer profiles, are subject to missingness. The convenient method that excludes the consumers with missingness in <i>any</i> covariate can result in a substantial loss of...

There has been recent growth in small area estimation due to the need for more precise estimation of small geographic areas, which has led to groups such as the U.S. Census Bureau, Google, and the RAND corporation utilizing small area-estimation procedures. We develop a novel two-stage...

The authors show that historical property damage losses from US hurricanes contain climate signals. The methodology is based on a statistical model that combines a specification for the number of loss events with a specification for the amount of loss per event. Separate models are developed for...

Compared to the conditional mean or median, conditional quantiles provide a more comprehensive picture of a variable in various scenarios. A semi-parametric quantile estimation method for a double threshold auto-regression with exogenous regressors and heteroskedasticity is considered, allowing...

We derive Bayesian confidence intervals for the probability of default (PD), asset correlation (Rho), and serial dependence (Theta) for low default portfolios (LDPs). The goal is to reduce the probability of underestimating credit risk in LDPs. We adopt a generalized method of moments with...