Estimating variable returns to scale production frontiers with alternative stochastic assumptions

Two stochastic production frontier models are formulated within the generalized production function framework popularized by Zellner and Revankar (Rev. Econ. Stud. 36 (1969) 241) and Zellner and Ryu (J. Appl. Econometrics 13 (1998) 101). This framework is convenient for parsimonious modeling of a production function with returns to scale specified as a function of output. Two alternatives for introducing the stochastic inefficiency term and the stochastic error are considered. In the first the errors are added to an equation of the form h(log y, theta) = log f (x, beta) where y denotes output, x is a vector of inputs and (theta, beta) are parameters. In the second the equation h(log y,theta) = log f(x, beta) is solved for log y to yield a solution of the form log y = g[theta, log f(x, beta)] and the errors are added to this equation. The latter alternative is novel, but it is needed to preserve the usual definition of firm efficiency. The two alternative stochastic assumptions are considered in conjunction with two returns to scale functions, making a total of four models that are considered. A Bayesian framework for estimating all four models is described. The techniques are applied to USDA state-level data on agricultural output and four inputs. Posterior distributions for all parameters, for firm efficiencies and for the efficiency rankings of firms are obtained. The sensitivity of the results to the returns to scale specification and to the stochastic specification is examined. (c) 2004 Elsevier B.V. All rights reserved.

Electronic commerce investments, the resource-based view of the firm, and firm market value

Firms have embraced electronic commerce as a means of doing business, either because they see it as a way to improve efficiency, grow market share, expand into new markets, or because they view it as essential for survival. Recent research in the United States provides some evidence that the market does value investments in electronic commerce. Following research that suggests that, in certain circumstances, the market values noninnovative investments as well as innovative investments in new products, we partition electronic commerce investment project announcements into innovative and noninnovative to determine whether there are excess returns associated with these types of announcements. Apart from our overall results being consistent with the United States findings that the market values investments in electronic commerce projects, we also find that noninnovative investments are perceived as more valuable to the firm than innovative investments. On average, the market expects innovative investments to earn a return commensurate with their risk. We conclude that innovative electronic commerce projects are most likely seen by the capital market as easily replicable, and consequently have little, if any, competitive advantage period. On the other hand, we conclude from the noninnovative investment results that these types of investments are seen as being compatible with a firm's assets-in-place, in particular, its information technology capabilities, a view consistent with the resource-based view of the firm.