In theoretical literature on productivity, the disturbance terms of the stochastic frontier model are assumed to be independent random variables. In this paper, we consider a stochastic production frontier model with residuals that are both spatially and time-wise correlated. We introduce...

The estimation of limited dependent variable panel data models usually involves objective functions in which integrals appear without a closed form solution: this is the case of the panel data Tobit model with random effects. Recently, simulation methods have shown to be useful in the inference...

Standard stochastic frontier models estimate log-linear specifications of production technology, represented mostly by production, cost, profit, revenue, and distance frontiers. We develop a methodology for stochastic frontier models of count data allowing for technological and inefficiency...

Survival prediction from a large number of covariates is a current focus of statistical and medical research. In this paper, we study a methodology known as the compound covariate prediction performed under univariate Cox proportional hazard models. We demonstrate via simulations and real data...

This paper studies the sequential sampling scheme as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value. Sequential sampling is analyzed and it is proved that when the sampling ratio is an integral number, the associated spectral...

In this paper, we present a procedure for consistent estimation of the severity and frequency distributions based on incomplete insurance data and demonstrate that ignoring the thresholds leads to a serious underestimation of the ruin probabilities. The event frequency is modelled with a...

In this note I show that a typo in Stata’s help file may have contributed in wrongly estimating marginal changes after truncated and censored regression models. This has significant implications for empirical practice and results from published studies may need to be reconsidered.

The stochastic frontier model was first proposed in the context of production function estimation to account for the effect of technical inefficiency. The inefficiency causes actual output to fall below the potential level (that is, the production frontier) and also raises production cost above...

When the coefficients of a Tobit model are estimated by maximum likelihood their covariance matrix is typically, even if not necessarily, associated with the algorithm employed to maximize the likelihood. Covariance estimators used in practice are derived by: (1) the Hessian (observed...

Estimation of causal eects in regression discontinuity designs relies on a local Wald estimator whose components are estimated via local linear regressions centred at an specic point in the range of a treatment assignment variable. The asymptotic distribution of the estimator depends on the...