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On parameters estimation of the Seasonal FISSAR Model

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Abstract

In this paper, we discuss the methods of estimating the parameters of the Seasonal FISSAR (Fractionally Integrated Separable Spatial Autoregressive with seasonality) model. First we implement the regression method based on the log-periodogram and the classical Whittle method for estimating memory parameters. To estimate the model's parameters simultaneously - innovation parameters and memory parameters- the maximum likelihood method, and the Whittle method based on the MCMC simulation are considered. We are investigated the consistency and the asymptotic normality of the estimators by simulation

Suggested Citation

  • Papa Ousmane Cissé & Dominique Guégan & Abdou Kâ Diongue, 2018. "On parameters estimation of the Seasonal FISSAR Model," Documents de travail du Centre d'Economie de la Sorbonne 18018, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    • Handle: RePEc:mse:cesdoc:18018
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    1. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    2. Roger J. Marshall, 1991. "A Review of Methods for the Statistical Analysis of Spatial Patterns of Disease," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(3), pages 421-441, May.
    3. Papa Ousmane Cissé & Abdou Kâ Diongue & Dominique Guegan, 2016. "Statistical properties of the seasonal fractionally integrated separable spatial autoregressive model," Post-Print hal-01397357, HAL.
    4. Papa Ousmane Cissé & Abdou Kâ Diongue & Dominique Guegan, 2016. "Note on a new Seasonal Fractionally Integrated Separable Spatial Autoregressive Model," Documents de travail du Centre d'Economie de la Sorbonne 16013, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    5. Diongue, Abdou Kâ & Diop, Aliou & Ndongo, Mor, 2008. "Seasonal fractional ARIMA with stable innovations," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1404-1411, September.
    6. Lambert, Dayton M. & Lowenberg-DeBoer, James & Bongiovanni, Rodolfo, 2003. "Spatial Regression Models For Yield Monitor Data: A Case Study From Argentina," 2003 Annual meeting, July 27-30, Montreal, Canada 22022, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Klüppelberg, Claudia & Mikosch, Thomas, 1993. "Spectral estimates and stable processes," Stochastic Processes and their Applications, Elsevier, vol. 47(2), pages 323-344, September.
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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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