Abstract. In Nicholls and Quinn (1980) a procedure was proposed for the determination of strongly consistent estimates of random coefficient autoregressive models. These estimates are used here as starting values in a Newton‐Raphson algorithm which is employed to obtain the maximum likelihood estimates of a class of random coefficient autoregressions. The maximum likelihood estimates are shown to be strongly consistent and to satisfy a central limit theorem. The problem of testing for the randomness of the coefficients is also briefly discussed. The results of a number of simulations are reported which illustrate the theoretical results obtained.
|Number of pages||19|
|Journal||Journal of Time Series Analysis|
|Publication status||Published - 1981|
- central limit theorem
- Maximum likelihood
- random coefficient autoregression
- strong consistency