Testing Moving Average Against Autoregressive Disturbances in the Li near-Reg ression Model
研究在线性回归模型中检验MA(1)扰动对AR(1)扰动的方法，比较了近似点最优不变检验、渐近检验和拉格朗日乘子检验的小样本表现，发现近似点最优不变检验在检验水平和功效上更优，并应用于澳大利亚实际利率的随机游走模型。
This paper considers testing for MA(1) against AR(1) disturbances in the linear regression model. Tests investigated include approximate point optimal invariant (POI) tests, an asymptotic test of the second-order residual autocorrelation coefficient and a Lagrange multiplier (LM) test. A Monte Carlo experiment compares their small-sample performances. Of the asymptotic tests, the LM test has the most satisfactory sizes, while its rival has the better overall power. We find the approximate POI tests have superior size and power properties in comparison to the asymptotic tests. An approximate POI test is applied to a random walk model for Australian real interest rates.