Technical Efficiency Evaluation: Naturally Dual!

We provide a dual perspective on technical efficiency evaluation, in two respects. First, we build on the price assumptions implicitly associated with the notion of technical efficiency in a general equilibrium framework to characterize a set of appropriate references to be used in the technical efficiency evaluation of an input-output vector. Some existing evaluation methods always select an element of this set, but other methods fail to do so. Second, the above framework leads us to assert that a well-grounded measure of technical efficiency is naturally decomposable. One part refers to technical efficiency as captured by the classical Debreu-Farrell measure. The other part refers to technical efficiency resulting from the “implicit allocative efficiency” or “mix efficiency” of the evaluated vector. We present both a quantity-based distance measure and its price-based equivalent to evaluate this complementary dimension of technical efficiency. This generalized perspective encompasses the standard Debreu-Farrell framework for technical efficiency evaluation, and makes it fully consistent with the well-established Koopmans efficiency notion.

The fixed effects estimator of technical efficiency

Firms and organizations, public or private, often operate on markets characterized by non-competitiveness. For example agricultural activities in the western world are heavily subsidized and electricity is supplied by firms with market power. In general it is probably more difficult to find firms that act on highly competitive markets, than firms that are not. To measure different types of inefficiencies, due to this lack of competitiveness, has been an ongoing issue, since at least the 1950s when several definitions of inefficiency was proposed and since the late 1970s as stochastic frontier analysis. In all three articles presented in this thesis the stochastic frontier analysis approach is considered. Furthermore, in all three articles focus is on technical inefficiency. The ways to estimate technical inefficiency, based on stochastic frontier models, are numerous. However, focus in this thesis is on fixed effects panel data estimators. This is mainly for two reasons. First, the fixed effects analysis does not demand explicit distributional assumptions of the inefficiency and the random error of the model. Secondly, the analysis does not require the random effects assumption of independence between the firm specific inefficiency and the inputs selected by the very same firm. These two properties are exclusive for fixed effects estimation, compared to other stochastic frontier estimators. There are of course flaws attached to fixed effects analysis as well, and the contribution of this thesis is to probe some of these flaws, and to propose improvements and tools to identify the worst case scenarios. For example the fixed effects estimator is seriously upward biased in some cases, i.e. inefficiency is overestimated. This could lead to false conclusions, like e.g. that subsidies in agriculture lead to severely inefficient farmers even if these farmers in reality are quite homogenous. In this thesis estimators to reduce bias as well as mean square error are proposed and statistical diagnostics are designed to identify worst case scenarios for the fixed effects estimator as well as for other estimators. The findings can serve as important tools for the applied researcher, to obtain better approximations of technical inefficiency

TECHNICAL EFFICIENCY IN RUSSIAN AGRICULTURE

For decades, Russian agriculture had had little technological progress and virtually no foreign investment, which resulted in a stable production possibilities frontier and made the sector ideally suited to production function analysis. The production function estimations reported in Chapters 10-13 add to a series of previous studies of the input/output relationship in Russian agriculture (e.g., Clayton, 1980, 1984; Gray, 1981; Johnson and Brooks, 1983), which generally followed the same methodology. In the late 1970s and the 1980s, however, the average response production functions gave way in the economics literature to more sophisticated production analysis techniques that measured not only productivity but technical efficiency as well (Aigner, et al., 1977; Bauer, 1990). Some of the major methodological advances in applying technical efficiency analysis to individual firms were made by a joint Russian-American team in Moscow in the early 1980s (Jondrow, et al., 1982; Danlin et al., 1985), but lack of data for many sectors of the Russian economy precluded the application of this technique until the end of the decade. When the Soviet Union collapsed, the initial optimistic expectation was that many sectors of the new Russian economy could rapidly achieve both higher productivity and higher technical efficiency once market forces prevailed. Our research attempts to understand why this has not happened in Russian agriculture in terms of technical efficiency.Research and Development/Tech Change/Emerging Technologies,

Productivity Growth, Technical Efficiency and Technical Change on Minnesota Farms

Changes and trends in farm productivity have been of intense interest to many involved with agriculture. This study used data envelopment analysis (DEA) to estimate the output-oriented Malmquist total factor productivity (TFP) index from panel data for 1993-2006 for farms in Southern Minnesota. Bootstrap methods were used to estimate confidence intervals for the productivity, efficiency change and technical change indices. The model included three inputs (labor, land and immediate expenditures) and six outputs (corn, soybean, milk, hog, beef, and nonfarm income). Productivity growth was found to be positive during the period, with an average annual productivity growth of 6.6 percent. However, TFP growth has been slowing down in recent years and indeed negative in 2000/01, 2002/03 and 2005/06. In the second stage of the analysis, the significance of various factors that might affect farm performance was estimated. Farm size (as measured by the log of farm income) was correlated with higher productivity which may help explain the increase in farm size in Minnesota farms in recent years. Government subsidies were found to have a negative impact on farm performance supporting the argument that agricultural subsidies may create disincentives for farmers to improve their productivity and efficiency. A higher nonfarm income ratio was positively related with higher productivity growth. A higher proportion of hired labor has a negative effect implying family labor is more crucial than hired labor in improving productivity.total factor productivity, farms, Malmquist index, data envelopment analysis, DEA, bootstrap, government subsidies, Farm Management, Productivity Analysis, Q12, C14,

TECHNICAL EFFICIENCY OF RURAL WATER UTILITIES

Technical efficiency of rural water utilities is determined using frontier production functions. An indirect production function is developed to model the two-step production process of a local government-controlled firm. Data from 26 rural Nevada water utilities are used to estimate inefficiency in terms of firm-specific variables. A multistep estimation procedure is used instead of single-step maximum likelihood estimation. Model selection tests are used to choose the best model. Privately owned utilities are most efficient; self-governing water districts are the least efficient. Municipal governments operate the most and least efficient utilities.Resource /Energy Economics and Policy,

Absorptive Capacity and Efficiency: A Comparative Stochastic Frontier Approach Using Sectoral Data

In this paper, we investigate differences in and determinants of technical efficiency across three groups of OECD, Asian and Latin American countries. As technical efficiency determines the capacity with which countries absorb technology produced abroad, these differences are important to understand differences in growth and productivity across countries, especially for developing countries which depend to a large extend on foreign technology. Using a stochastic frontier framework and data for 22 manufacturing sectors for 1996-2005, we find notable differences in technical efficiency between the three country groups we examine. We then investigate the effect of human capital and domestic R&D, proxied by the stock of patents, on technical efficiency. We find that while human capital has always a strongly positive effect on efficiency, an increase in the stock of patents has positive effects on efficiency in high-tech sectors, but negative effects in low-tech sectors

STOCHASTIC FRONTIER ANALYSIS OF NEW ZEALAND'S MANUFACTURING INDUSTRIES: SOME EMPIRICAL RESULTS

This paper examines the sources of total factor productivity growth (TFP) in New Zealand's manufacturing industries over the period 1978-98 and over various sub-periods. Examination of the data adopts two stages using a stochastic frontier approach. The first stage involves the specification and estimation of the stochastic frontier production function and the prediction of technical efficiency effects. The second stage involves the specification of a regression model for the predicted technical efficiency effects. The sources of TFP growth have been decomposed into four components; i.e. technical progress, changes in technical efficiency, scale effects, and change in allocative efficiency. The empirical results show that productivity has been largely due to changes in technical progress, technical efficiency and resource allocation effect. The changes in technical progress and resource allocation have improved in the post-reform period, i.e. 1984-98, while technical efficiency has declined in the post-reform period. With respect to scale effect its contribution to productivity growth is quite small.New Zealand Manufacturing Sector, Total Productivity Growth, Technical Progress, Technical Efficiency, Scale Components, Allocative Efficiency, Industrial Organization, D24, C23, O47,

The Technical Efficiency of UK Airports

In this paper, the innovative random stochastic frontier model is used to estimate the technical efficiency of UK airports. These airports are ranked according to their total productivity for the period 2000-2005 and homogenous and heterogeneous variables in the cost function are disentangled, which leads us to advise the implementation of common policies as well as policies by segments. Economic implications arising from the study are also considered.Airports; UK; efficiency; random frontier models; policy implications.

Impact of Off-farm Income on Farm Efficiency in Slovenia

The paper investigates the impact of off-farm income on farm technical efficiency for the Slovenian Farm Accountancy Data Network farms in the years 2004-2008. Farm stochastic frontier time-varying decay inefficiency is positively associated with total utilised agricultural areas and total labour input, and vice versa with intermediate consumption and fixed assets. We find a positive association between farm technical efficiency and the off-farm income. Farm technical efficiency has increased steadily over time, the process, which was led by the off-farm spill over effect and most efficient farms. Farm technical efficiency is also positively associated with economic farm size, while association with subsidies is mixed depending on the estimation procedure. Quantile regression confirms the positive and significant associations between farm technical efficiency and off-farm income, and between farm technical efficiency and farm economic size, as well as also the positive association between farm technical efficiency and subsidies, but the results are sensitive by quantiles.Off-farm income, Stochastic frontier analysis, Panel regression, Quantile regression, Slovenia, Farm Management,