Pierce, Grupe, and Cleveland (1984) introduced a fixed regression approach to the problem of seasonal adjustment for weekly time series. Cleveland (1993) expanded this approach by adding locally-weighted regressions to allow for varying seasonal factors, and the Bureau of Labor Statistics...

This paper examines the distributions of (zero frequency) unit root test statistics for I(1) processes in the presence of noninvertible moving average components. The analysis initially considers a noninvertible MA(1), for which the asymptotic distribution of the ADF test statistic under the...

For benchmarking monthly and quarterly series to annual series and to the Economic Census every five years, the U.S. Census Bureau uses an iterative, nonlinear method known as the Causey-Trager method. However, the Census Bureau's X−12−ARIMA seasonal adjustment program uses a modified Denton...

Benchmarking deals with the problem of combining a series of high-frequency data (e.g., monthly) with a series of low frequency data (e.g., quarterly) into a consistent time series. When discrepancies arise between the two series the latter is usually assumed to provide more reliable...

The paper discusses the main issues arising in the construction of quarterly national accounts estimates, adjusted for seasonality and calendar effects, obtained by disaggregating the original annual actual measurements using related monthly indicators. It proposes and implements an approach...

Government statistical agencies are required to seasonally adjust non-stationary time series resulting from an aggregate of a number of cross-sectional time series. Traditionally, this has been achieved using the X-11 or X12-ARIMA process by us- ing either direct or indirect seasonal adjustment....

Usually, seasonal adjustment is based on time series models which decompose an unadjusted series into the sum or the product of four unobservable components (trend-cycle, seasonal, working-day and irregular components). In the case of clearly weather-dependent output in the west German...

We investigate the effects of the misspecification of cointegrating ranks at other frequencies on the inference of seasonal cointegration at the frequency of interest such as test for cointegrating rank and estimation of cointegrating vector. Earlier studies mostly focused on a single frequency...

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...