Showing 1 - 9 of 9
This paper demonstrates that long memory leads to spurious rejection of the linearity hypothesis, when a STAR specification constitutes the alternative.
Persistent link: https://www.econbiz.de/10005423859
Asymptotic tests for fractional integration are usually badly sized in small samples, even for normally distributed processes. Furthermore, tests that are well-sized under normality may be severely distorted by non-normalities and ARCH errors. This paper demonstrates how the bootstrap can be...
Persistent link: https://www.econbiz.de/10005423891
The LM type linearity test for STAR nonlinearities is severely distorted when the process is governed by conditional heteroskedasticity. In order to correct the test we propose a parametric bootstrap. It is shown, by means of Monte Carlo methods, that the bootstrap test is almost exact.
Persistent link: https://www.econbiz.de/10005207191
This note proposes a tool to investigate and demonstrate the adequacy of the central limit theorem in small samples. The suggested testing procedure provides a method to investigate if the mean estimator is approximately normally distributed, given data and sample size at hand. This is important...
Persistent link: https://www.econbiz.de/10005207190
This paper investigates how fractional cointegration affects the common maximum likelihood cointegration procedure. It is shown that the likelihood ratio test of no cointegration has considerable power against fractional alternatives. In contrast to the case of a cointegrated system, the usual...
Persistent link: https://www.econbiz.de/10005190901
This paper proposes several resampling algorithms suitable for error component models and evaluates them in the context of bootstrap testing. In short, all the algorithms work well and lead to tests with correct or close to correct size. There is thus little or no reason not to use the bootstrap...
Persistent link: https://www.econbiz.de/10005649435
Since the true nature of a time series process is often unknown it is important to understand the effects of model choice. This paper examines how the choice between modelling stationary time series as ARMA or ARFIMA processes affects the accuracy of forecasts. This is done, for first-order...
Persistent link: https://www.econbiz.de/10005423845
This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive...
Persistent link: https://www.econbiz.de/10005190887
Asymptotic tests for fractional integration, such as the Geweke-Porter-Hudak test, the modified rescaled range test and Lagrange multiplier type tests, exhibit size-distortions in small-samples. This paper investigates a parametric bootstrap testing procedure, for size-correction, by means of a...
Persistent link: https://www.econbiz.de/10005649149