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- handle: 10670/1.dogf5b
- halshs: halshs-01832115
info:eu-repo/semantics/OpenAccess
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Seasonal FISSAR long memory regression method Whittle method MLE method C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C52 - Model Evaluation, Validation, and SelectionCiter ce document
Papa Ousmane Cissé et al., « On the parameters estimation of the Seasonal FISSAR Model », HAL-SHS : économie et finance, ID : 10670/1.dogf5b
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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.