Spiro E. Stefanou

Education, Experience, and Allocative Efficiency: A Dual Approach

A generalization of the dual, non-frontier profit function approach to evaluating allocative efficiency is developed that allows for training (human capital) variables to influence the efficiency level directly. An application to Pennsylvania dairy indicates that education and experience are substitutes and play a significant role in the level of efficiency. While these operators are not allocating their variable inputs in an absolutely efficient manner, relative efficiency can be achieved for four of six possible input combinations for prescribed levels of education and experience. Furthermore, the estimates of the efficiency measures suggest that these operators are maximizing production rather than short-run profits.

Dynamic Measures of Scope and Scale Economies: An Application to German Agriculture

Static concepts of multiproduct economies of scale and scope are extended into a dynamic setting within the cost of adjustment framework. Important properties of the dynamic measures are developed and the foundations of a dynamic theory of the firm generalizing static neoclassical theory are presented. Dynamic measures of scope and scale as well as shadow costs are estimated empirically for multiple-output, multiple-input German dairy farms operating under a production quota. Causes of scope economies are explored and a conceptual model to predict the evolution of the production structure of German farms is formulated.

Productivity Growth in U.S. Agriculture under Dynamic Adjustment

A dynamic measure of productivity growth adjusted for deviations from the long-run equilibrium is established within an adjustment-cost framework. An empirical application to U.S. agriculture is presented which permits identifying the dynamic linkages between technical change and productivity growth in U.S. agriculture. Total factor productivity as dynamically measured grew at 1.50% per annum. The combined effect of scale, quality-adjusted input growth, and long-run disequilibrium input use contributes only 3.44% of the growth, while technical change dominates the growth of total factor productivity.

Nonparametric Dynamic Production Analysis and the Theory of Cost

While the dynamic theory of production provides little insight towards identifying a specific functional form for the firms technology, dynamic production analysis has been explored traditionally in a parametric framework. A nonparametric dynamic dual cost approach to production analysis is developed in this article. Recovering technological information from intertemporal cost minimizing behavior is possible without imposing a parametric functional form on the firms technology. Nonparametric tests to analyze the structure of a dynamic technology are presented from a dynamic cost minimizing perspective. The empirical implementation of these tests is illustrated for a balanced panel data set of Pennsylvania dairy operators during the time period 1986–1992.

Dynamic Efficiency Measurement: Theory and Application

Nonparametric dynamic measures of production efficiency are developed in the context of an adjustment-cost technology and intertemporal cost minimization. Bounds on each efficiency measure are derived for each firm using a nonparametric revealed preference approach. Long-run efficiency measures indicate the relative efficiency of both variable and dynamic factors while short-run measures of efficiency indicate whether variable inputs are employed efficiently in the production process. The efficiency measures are temporal in nature by describing the degree of efficiency of the firm at a particular point along its adjustment path. The empirical implementation is illustrated for a balanced panel of Pennsylvania dairy operators during 1986&-1992. Copyright 2007, Oxford University Press.

Learning-by-doing and the sources of productivity growth: A dynamic model with application to U.S. agriculture

The significance of learning to productivity growth is formulated within a dynamic adjustment-cost framework. Explicitly treating the acquisition of knowledge as a firm-specific capital good entering the production function along with other conventional inputs, the dynamic optimization model integrates the learning-by-doing hypothesis with technical change, scale, and disequilibrium input use effects in the aggregate productivity analysis. The theoretical framework is applied to examining the dynamic components accounting for the growth of U.S. production agriculture over the 1950–82 period. The results imply a less important role for technical change and assign a substantial role to the previously unmeasured contribution of learning-by-doing to the growth of aggregate agriculture industry.

Asymmetric Adjustment of Dynamic Factors at the Firm Level

This study provides a framework for consistent estimation of a dynamic dual model of investment for the case where data reveal zero and nonzero investments. The threshold model that is developed maintains that investments are zero if the shadow value of machinery is between a lower and an upper threshold. Separate equations are estimated for the investment and the disinvestment regime. A significant difference between the parameters of the investment and disinvestment equations is found. The stock of machinery adjusts slower toward the long-run equilibrium target during an investment regime than during a contracting regime. Copyright 1997, Oxford University Press.

Dynamic Efficiency Estimation: An Application to US Electric Utilities

The shadow cost approach is developed in the context of the dynamic duality model of intertemporal decision making to formulate theoretical and econometric models of dynamic efficiency. The dynamic efficiency model is applied to a panel of 72 U.S. major investor-owned electric utilities using fossil fuel–fired steam electric power generation over the period 1986–1999. The major results show that most electric utilities underutilized fuel relative to the aggregated labor and the maintenance input, and overutilized capital in production. States adopting a deregulation plan improve the performance of utilities in terms of the technical efficiency of variable inputs.

Measuring technical efficiency in the presence of pesticide spillovers and production uncertainty: The case of Dutch arable farms

Pesticides’ dynamic effects and production uncertainty play an important role in farmers’ production decisions. Pesticides have a current production impact through reducing crop damage in the current period and a future impact through impacting the farm biodiversity which alters the future production environment. This study presents the difference in inefficiency arising from models that ignore the dynamic effects of pesticides in production decisions and the impact of production uncertainty. A dynamic data envelopment analysis (DEA) model is applied to outputs, inputs, and undesirables of Dutch arable farms over the period 2003–2007. A bootstrap approach is used to explain farmers’ performance, providing empirical representations of the impact of stochastic elements on production. These empirical representations are used to adjust firms’ inefficiency scores to incorporate production uncertainty in efficiency evaluation. We find that efficiency increased dramatically when a production technology representation that considers both pesticides’ dynamic impacts, and production uncertainty is adopted.

A Reduced-Form Model for Dynamic Efficiency Measurement: Application to Dairy Farms in Germany and The Netherlands

The stochastic distance function model is extended to allow for the inefficiency component of the error term to be autocorrelated, as implied by a dynamic model of firm behavior. The autocorrelation parameter can then be interpreted as a measure of the persistence of inefficiency. The model is viewed from a state-space perspective, and Kalman filtering techniques are proposed for estimation. The model is applied to two panels of dairy farms from Germany and the Netherlands. The results suggest a very high degree of persistence of inefficiency through time. Copyright 2010, Oxford University Press.