Small sample bias reduction of the first-order autoregressive parameter least-squares estimator

1985 ◽  
Vol 30 (9) ◽  
pp. 893-895 ◽  
Author(s):  
Z. Nahorski ◽  
J. Studzinski
1989 ◽  
Vol 5 (2) ◽  
pp. 241-255 ◽  
Author(s):  
Pierre Perron

We tabulate the limiting cumulative distribution and probability density functions of the least-squares estimator in a first-order autoregressive regression when the true model is near-integrated in the sense of Phillips. The results are obtained using an exact numerical method which integrates the appropriate limiting moment generating function. The adequacy of the approximation is examined for various first-order autoregressive processes with a root close to unity.


2003 ◽  
Vol 40 (3) ◽  
pp. 750-765 ◽  
Author(s):  
M. Ispány ◽  
G. Pap ◽  
M. C. A. van Zuijlen

A sequence of first-order integer-valued autoregressive (INAR(1)) processes is investigated, where the autoregressive-type coefficient converges to 1. It is shown that the limiting distribution of the conditional least squares estimator for this coefficient is normal and the rate of convergence is n3/2. Nearly critical Galton–Watson processes with unobservable immigration are also discussed.


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