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Stationary And Non‐Stationary State Space Models

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  • Pidt de Jong
  • Singfat Chu‐Chun‐Lin

Abstract

. The concepts of time invariance, stationarity, non‐stationarity and immemorial time are considered for state space models (SSMs). Necessary and sufficient conditions for stationarity are given and connected with standard conditions. Expressions are given for the unconditional mean and covariance matrix of the state of a time‐immemorial SSM. Application of the results is made to a variety of theoretical and empirical models and the initialization of the Kalman filter in the non‐stationary case and for the ARIMA (p, d, q) model.

Suggested Citation

  • Pidt de Jong & Singfat Chu‐Chun‐Lin, 1994. "Stationary And Non‐Stationary State Space Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(2), pages 151-166, March.
    • Handle: RePEc:bla:jtsera:v:15:y:1994:i:2:p:151-166
    DOI: 10.1111/j.1467-9892.1994.tb00182.x
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    Cited by:

    1. Prakash, Navendu & Srivastava, Bhavya & Singh, Shveta & Sharma, Seema & Jain, Sonali, 2022. "Effectiveness of social distancing interventions in containing COVID-19 incidence: International evidence using Kalman filter," Economics & Human Biology, Elsevier, vol. 44(C).
    2. José Casals Carro & Miguel Jerez Méndez & Sonia Sotoca López, 2006. "Decomposition of state-space Model with inputs: The theory and an application to estimate the ROI of advertising," Documentos de Trabajo del ICAE 0602, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

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