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CWLS and ML estimates in a heteroscedastic RCA(1) model

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  • Janečková Hana
  • Prášková Zuzana

Abstract

The paper concerns with parameter estimation in a heteroscedastic random coefficient autoregressive (RCA) model of the form Xt = btXt−1 + Yt. A conditionally weighted least squares (CWLS) estimator of β = Ebt is studied. Its strong consistency and asymptotic normality are proved. For this purpose theory of near-epoch dependent (NED) processes is used. Consistency results are also obtained in case that variances both of the random parameter and heterogeneous errors are unknown and have to be estimated. Some simulations are presented to support the theory.

Suggested Citation

  • Janečková Hana & Prášková Zuzana, 2004. "CWLS and ML estimates in a heteroscedastic RCA(1) model," Statistics & Risk Modeling, De Gruyter, vol. 22(3), pages 245-259, March.
    • Handle: RePEc:bpj:strimo:v:22:y:2004:i:3/2004:p:245-259:n:6
    DOI: 10.1524/stnd.22.3.245.57064
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    References listed on IDEAS

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    1. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037, Decembrie.
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