X-12-ARIMA makes some assumptions about the relationship between trend and seasonality that are not always understood by users. In its simplest form, the observed series Yt can be considered a combination of three components: the trend-cycle Ct, the seasonal component St, and the irregular or random component It. Each of these components can enter the equation by multiplication or addition. Thu...

Agricultural drought is the leading cause for crop failure throughout the world. In the USA, significant impacts of recent droughts on agricultural production indicate the continuing vulnerability of the country to drought. This paper presents a methodology for spatial representation of the agroclimatic component of agricultural drought vulnerability. This methodology was developed as a part of...

We shed light on a class of models that increase the flexibility of the seasonal pattern within a framework of the structural time series model. The basic idea is to drive the seasonal summation model by a moving average process rather than by a white noise or an AR process. Generally, such an approach can be exhaustive in parameters, but the proposed model is parsimonious in the sense that we ...

The potential for climate predictability at seasonal time scales resides in information provided by the ocean initial conditions, in particular the upper thermal structure. Currently, several operational centres issue routine seasonal forecasts produced with coupled ocean-atmosphere models, requiring real-time knowledge of the state of the global ocean. Seasonal forecasting needs the calibratio...

Several model-based seasonal adjustment diagnostics are currently being incorporated into X-13-ARIMASEATS, a new hybrid seasonal adjustment program under development at the U.S. Census Bureau. These diagnostics have been implemented in the Ox programming language, and this paper discusses various aspects of the implementation. The diagnostics are normalized quadratic forms in the data, and roug...

Recent studies suggest that decomposing a series of electricity spot prices into trend-seasonal and stochastic component, modeling them independently, then combining their forecasts can yield more accurate predictions than an approach in which the same parsimonious regression or neural network-based model is calibrated to themselves. Here, we show significant accuracy gains also be achieved cas...

Strong seasonality in demand, a short product life cycle, and the absence of any price competition make the release date of first-run movies one of the main strategic decisions taken by movies’ distributors. These endogenous timing decisions, in turn, generate a strong seasonal pattern of release dates. Therefore, the observed seasonal pattern of sales is a combination of both seasonality in un...

This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested procedure performs well even in small samples, accurately capturing the seasonal properties of the s...