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A State Space Model‐Based Approach to Intervention Analysis in the Seasonal Adjustment of BLS Series: Some Empirical Results

Raj K. Jain


The Intervention and Explanatory variables are incorporated in the statistical models of seasonal adjustment of BLS series. The State-Space/Kalman Filter methodology is used to estimate these models. EM algorithm and a quasi-Newton algorithm are employed to estimate the hyper-parameters of those models. Two BLS series are seasonally adjusted using these models and the empirical results relating to the effects of intervention analysis and explanatory variables on seasonal adjustment presented.