We consider stochastic frontier models in a panel data setting where there is dependence over time. Current methods of modeling time dependence in this setting are either unduly restrictive or computationally infeasible. Some impose restrictive assumptions on the nature of dependence such as the...

Abstract In this paper we consider the robustness to error autocorrelation of four stationarity tests. The size and power properties of these tests are investigated by simulation. Size is improved by using fixed-b critical values to account for the number of lags used in long-run variance...

In this paper we consider the KPSS test. We derive the asymptotic distribution of the statistic under the null of stationarity and under the unit root alternative under the "fixed-b" assumption that the ratio of the number of lags in the long run variance estimate to the sample size is fixed....

In this paper we consider parametric deterministic frontier models. For example, the production frontier may be linear in the inputs, and the error is purely one-sided, with a known distribution such as exponential or half-normal. The literature contains many negative results for this model....

Let u ≥ 0 be technical inefficiency, let z be a set of variables that affect u, and let δ be the parameters of this relationship. The model satisfies the scaling property if u(z, δ) can be written as a scaling function h(z, δ) times a random variable u* that does not depend on z. This...