A method of evaluating the impact of technical change on productivity in a Farrell-type model is developed here and empirically applied over international airlines data.

A method of measuring the systematic component of dynamic efficiency characterized by Farrell's nonparametric method is developed and empirically applied over airlines data.

Two key element of Schumpeterian dynamics - new innovations in technology and creative destruction - are used here to develop a growth model, which is then applied empirically for two economies: Japan and Korea in their rapid phases of growth.

Two methods of estimating efficiency by cost frontiers are analysed here by way of generalizing Farrell's convex hull method and illustrated by an empirical application.

Empirical estimates of the Lorenz model of chaos are reported here for the conditional variances of returns of selected mutual funds over the period September 1988 to April 1993. These estimates show that chaotic instability may occur with a positive probability.

Two key elements of Schumpeterian dynamics: new innovations and creative destruction are developed here in a stochastic framework to develop a model of stochastic growth. This model explores the diffucion process and the existence of nonlinearities in technological progress.

Dynamic efficiency of firms involves both optimal investments over time and optimal operating costs in the short run. These two stages are separately but sequentially analysed to compare different firms in an industry using a Pareto optimality criterion.

A nonparametric method is empirically applied here to test the efficiency in performance of mutual fund portfolios. It provides a more flexible and robust alternative to the traditional mean variance theory.

Pre- and post-optimality analysis of input-output data is developed here as a practical method of Farrell-type efficiency measurement. Filtering of noise and specifying the optimal output distributions provide the basic tools which are applied to the time series data for international airlines.

A new method of measuring productive efficiency is proposed and empirically applied here, when the input output data are subject to random variations. This method is useful in applications of Farrell efficiency and data envelopment analysis.