In this paper two techniques, long memory and panel data models, are combined in order to increase the power of unit root tests. The power is shown to be always better against fractional alternatives and usually against autoregressive alternatives. The test is then used to reanalyze data sets...

This paper demonstrates that long memory leads to spurious rejection of the linearity hypothesis, when a STAR specification constitutes the alternative.

This paper shows how a simple univariate stationary nonlinear process has an autocorrelation function suggesting that the underlying process has a long memory, although that is not the case. The conclusion is that just considering linear properties of a process may be misleading.

Estimating a density function over a bounded domain can be very complicated and resulting in an unsatisfactory or unrealistic density estimate. In many cases a one-to-one transformation can be applied to the considered data set, but there are also situations where such a unique transformation...

The price adjustment coefficient model of Amihud and Mendelson (1987) is shown to be suitable for estimation by the Kalman filter. A techique that, under some commonly used conditions, is asymptotically efficient. By Monte Carlo simulations it is shown that both bias and mean squared error are...

A bank that lends money to a household faces two types of risk. Most commonly mentioned is the risk of a default. Hardly ever referred to is the risk of an early redemption of the loan - leading to dormancy. We model consumer loans' transition from an active to a dormant state and estimate a...

The purpose of this paper is to use the bootstrap resampling technique to calculate confidence intervals for efficiency measures and Malmquist productivity indices. The efficiency and productivity measures are obtained from non-parametric linear programming models using primal production data....

This paper shows that the bootstrap algorithm for average technical efficiency by Atkinson and Wilson (1995) should be applied with great care for the Data Envelopment Analysis (DEA) estimator if the production frontier is stochastic. A stochastic frontier implies that the DEA estimator is...

This paper presents and applies different approaches to estimate returns to scale in multiple-input muliple-output technologies. Scale efficiency gives quantitative information of scale characteristics. A primal based approach to estimate the scale elasticity is proposed as an alternative to the...

This paper presents a Monte Carlo simulation study of the bootstrap algorithm proposed by Löthgren and Tambour (1997) for calculation of bootstrap confidence intervals for the firm-specific Data Envelopment Analysis (DEA) Malmquist productivity index. The simulation results indicate that the...