In an influential work by Diebold and Inoue (2001), the Markov switching model was shown to exhibit long memory, in terms of the behavior of the second moments of partial sums. The relationship between the Markov switching model and long memory is reexamined here. Common estimators of the long...

We extend Breitung’s (2000) panel data unit root test to the case of fixed time (T) dimension while still allowing for heteroscedastic and serially correlated error terms. The analytic local power function of the new test is derived assuming that only the cross section dimension of the panel...

We consider the use of information criteria (IC) on the basis of a semiparametric seasonal error correction model for selecting seasonal cointegrating ranks. Some limit properties of the IC are considered and, through a small Monte Carlo simulation, we evaluate the performance of the IC.

A Lagrangian multiplier test is proposed for testing market microstructure noise (MMN) in financial asset prices. The test is very simple and is asymptotically chi-squared with 1-degree of freedom. The test is applied to sampling interval determination for realized volatilities (RVs) which...

A novel procedure is applied to test for switches between hysteresis and the natural rate theory over more than a century of UK and USA unemployment data. For both the countries we see a period conforming to hysteresis starting in the early 1920s for the UK and 1930 for USA.

While theory of autoregressive conditional heteroskedasticity (ARCH) models is well understood for strictly stationary processes, some recent interest has focused on the nonstationary case. In the classical model including a positive intercept parameter, the volatility process diverges to...

The asymptotic distributions of the maximum likelihood estimator of the persistence parameter are developed in a linear diffusion model under three sampling schemes, long-span, in-fill and double. Simulations suggest that the in-fill asymptotic distribution gives a more accurate approximation to...