In recent years there have been notable advances in the methodology for analyzing seasonal time series.This paper summarizes some recent research on seasonal adjustment problems and procedures.Included are signal-extraction methods based on autoregressive integrated moving average (ARIMA) models, improvements in X.11, revisions in preliminary seasonal factors, regression and other model-based methods, robust methods, seasonal model identification, aggregation, interrelating seasonally adjusted series, and causal approaches to seasonal adjustment.