Money and production: A stochastic frontier approach

Considerable controversy surrounds the role of money in the production of goods and services. Previous empirical research has appeared to find that the real money stock affects aggregate output, holding other, more conventional inputs constant. However, the theoretical literature offers no convincing explanation for this empirical finding. One interpretation is that real money balances reduce the extent to which labor and capital are diverted into exchange-related activities instead of being used in production defined in a more narrow sense. To investigate this hypothesis, we estimate a production function augmented with real money balances as an input, using time-series data for the aggregate U.S. economy. A stochastic production frontier is then estimated without real money balances. We use these estimates to establish the presence of technical inefficiency. Finally, we show that the extent of technical inefficiency is negatively correlated with the real money stock. Our results provide a reconciliation between the empirical literature, which finds that real money balances affect output in a production function framework, and the theoretical literature, which suggests that real money balances enhance the technical efficiency of the economy.     

Confidence statements for efficiency estimates from stochastic frontier models

This paper is an empirical study of the uncertainty associated with technical efficiency estimates from stochastic frontier models. We show how to construct confidence intervals for estimates of technical efficiency levels under different sets of assumptions ranging from the very strong to the relatively weak. We demonstrate empirically how the degree of uncertainty associated with these estimates relates to the strength of the assumptions made and to various features of the data.     

Water use efficiency and public goods conservation: A spatial stochastic frontier model applied to irrigation in Southern Italy

Water used for irrigation is essential for global food production. Increased water scarcity, due to climate change, is a constraint to agricultural development, especially in arid and semi-arid areas. This increases pressure on agriculture which often manages water inefficiently and competes with other sectors for water use. Enhancing farmers’ production efficiency may lead to substantial water savings and conservation. Public sector is called to play a role in water governance and to introduce appropriate multilevel regulatory and incentive measures for better water management. This work applies a spatial stochastic frontier model to the case of high water-demanding fruit and vegetable crops in the Apulia region of Southern Italy, where water is scarce due to semi-arid climate and erratic rainfall. Using cross-sectional data from the EU Farm Accountancy Data Network, this work incorporates firm specific heterogeneity into technical efficiency analysis and implements an autoregressive specification of the inefficiency component. Results support the hypothesis that spatial heterogeneity exists in on-farm efficiency of irrigated crop production and is adequately captured by the spatial stochastic frontier model approach. Technical efficiency of farms with similar structural and management characteristics greatly varies across crops and geographical areas, because of the different natural resource endowment and agro-climatic factors. Policies providing incentives to on-farm adoption of modern water-saving technologies and measures to promote small family farm activities could effectively contribute to water conservation goal, but they should be well-articulated to account for agriculture spatial diverseness.     

A new approach to estimating the metafrontier production function based on a stochastic frontier framework

This paper proposes a new two-step stochastic frontier approach to estimate technical efficiency (TE) scores for firms in different groups adopting distinct technologies. Analogous to Battese et al. (J Prod Anal 21:91–103, 2004), the metafrontier production function allows for calculating comparable TE measures, which can be decomposed into group specific TE measures and technology gap ratios. The proposed approach differs from Battese et al. (J Prod Anal 21:91–103, 2004) and O’Donnell et al. (Empir Econ 34:231–255, 2008) mainly in the second step, where a stochastic frontier analysis model is formulated and applied to obtain the estimates of the metafrontier, instead of relying on programming techniques. The so-derived estimators have the desirable statistical properties and enable the statistical inferences to be drawn. While the within-group variation in firms’ technical efficiencies is frequently assumed to be associated with firm-specific exogenous variables, the between-group variation in technology gaps can be specified as a function of some exogenous variables to take account of group-specific environmental differences. Two empirical applications are illustrated and the results appear to support the use of our model.     

Socio-institutional determinants of educational resource efficiency according to the capability approach: An endogenous stochastic frontier analysis

We investigate the role of private and public resources in educational attainments and the socio-institutional determinants of educational resource efficiency in Italy. Following the Sen's capability approach, we consider social capital and the quality of government part of the social conversion factors through which resources can be converted into human capabilities, such as education. We analyze the case of Italy by constructing a new longitudinal dataset from 1993 to 2012, using repeated cross sections from the main social survey of the Italian Statistical Institute and a panel stochastic frontier model that takes into account endogeneity. The results show the relative importance of private resources (measured by an ad hoc constructed wealth index), the complementarity between private wealth and public expenditures on education, and the positive impact of social capital and the quality of government on educational resource efficiency.     

Matching in local labor markets: a stochastic frontier approach

This paper investigates the technical efficiency of labor market matching from a stochastic frontier approach. The true fixed-effects model (Greene J Prod Anal 23:7–32, 2005a; J Econom 126:269–303, 2005b) is utilised in order to separate cross-sectional heterogeneity from inefficiency, and inefficiency terms are modelled following Battese and Coelli (Empir Econ 20:325–332, 1995). The data set consists of almost 17,000 observations from Local Labor Offices (LLOs) in Finland. According to the results, there are notable differences in matching efficiency between regions, and these differences contribute significantly to the number of filled vacancies. If all regions were as efficient as the most efficient one, the number of total matches per month would increase by over 23%. The heterogeneity of the job-seeker stock is an important determinant of matching efficiency: the weight of the composition of the job-seeker stock in the inefficiency terms is on average 85%.

A stochastic frontier analysis to estimate the relative efficiency of Spanish airports

There exists a common belief among researchers and regional policy makers that the actual central system of Aeropuertos Españoles y Navegación Aérea (AENA) should be changed to one more decentralized where airport managers could have more autonomy. The main objective of this article is to evaluate the efficiency of the Spanish airports using Markov chain Monte Carlo (MCMC) simulation to estimate a stochastic frontier analysis (SFA) model. Our results show the existence of a significant level of inefficiency in airport operations. Additionally, we provide efficient marginal cost estimates for each airport which also cast some doubts about the current pricing practices.     

Consistent estimation of the fixed effects stochastic frontier model

In this paper we consider a fixed-effects stochastic frontier model. That is, we have panel data, fixed individual (firm) effects, and the usual stochastic frontier analysis (SFA) composed error.     

特许经营商业模式和盈利模式研究

文章认为特许经营这种商业运作模式有初级和高级发展阶段,分别对应着依靠有形商品赚钱的"初级盈利模式"和依靠无形资产赚钱的"高级盈利模式"这两种不同的盈利模式。     

On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components

Analysis of the behavior of technical inefficiency with respect to parameters and variables of a stochastic frontier model is a neglected area of research in frontier literature. An attempt in this direction, however, has recently been made. It has been shown that in a “standard” stochastic frontier model that both the firm level technical inefficiency and the production uncertainty are monotonically decreasing with observational error. In this paper we show, considering a stochastic frontier model whose error components are jointly distributed as truncated bivariate normal, that this property holds if and only if the distribution of observational error is negatively skewed. We also derive a necessary and sufficient condition under which both firm level technical inefficiency and production uncertainty are monotonically increasing with noise-inefficiency correlation. We next propose a new measure of the industry level production uncertainty and establish the necessary and sufficient condition for firm level technical inefficiency and production uncertainty to be monotonically increasing with industry level production uncertainty. We also study the limiting probabilistic behavior of these conditions under different parametric configuration of our model. Finally we carry out Monte Carlo simulations to study the sample behavior of the population monotonic property of the firm level technical inefficiency and production uncertainty in our model.

Model selection in stochastic frontier analysis with an application to maize production in Kenya

This paper shows how to compute the standard errors for partial effects of exogenous firm characteristics influencing firm inefficiency under a range of popular stochastic frontier model specifications. We also develop an R²-type measure to summarize the overall explanatory power of the exogenous factors on firm inefficiency. The paper also applies a recently developed model selection procedure to choose among alternative stochastic frontier specifications using data from household maize production in Kenya. The magnitude of estimated partial effects of exogenous household characteristics on inefficiency turns out to be very sensitive to model specification, and the model selection procedure leads to an unambiguous choice of best model. We propose a bootstrapping procedure to evaluate the size and power of the model selection procedure. The empirical application also provides further evidence on how household characteristics influence technical inefficiency in maize production in developing countries.

Estimators and hypothesis tests for a stochastic frontier function: A Monte Carlo analysis

This paper uses Monte Carlo experimentation to investigate the finite sample properties of the maximum likelihood (ML) and corrected ordinary least squares (COLS) estimators of the half-normal stochastic frontier production function. Results indicate substantial bias in both ML and COLS when the percentage contribution of inefficiency in the composed error (denoted by *) is small, and also that ML should be used in preference to COLS because of large mean square error advantages when * is greater than 50%. The performance of a number of tests of the existence of technical inefficiency is also investigated. The Wald and likelihood ratio (LR) tests are shown to have incorrect size. A one-sided LR test and a test of the significance of the third moment of the OLS residuals are suggested as alternatives, and are shown to have correct size, with the one-sided LR test having the better power of the two.The author would like to thank Bill Griffiths, George Battese, Howard Doran, Bill Greene and two anonymous referees for valuable comments. Any errors which remain are those of the author.     

Determinants of total factor productivity in former Soviet Union economies: A stochastic frontier approach

This paper investigates the process of GDP generation in former Soviet Union (FSU) economies to provide an understanding of the impact of technology channels on countries’ efficiency. We apply a stochastic frontier approach to 15 FSU economies over the period 1995–2008 and find that FDI and human capital improve countries’ technical efficiency. Furthermore, we show that these factors also have a positive impact on total factor productivity (TFP), which, in turn, improves real GDP growth. Hence, our results suggest that FSU countries should promote public policies that provide incentives to attract foreign investment and enhance domestic education in order to improve their economic growth. Additionally, our empirical evidence argues against the resource curse hypothesis. We also show, by computing efficiency change and technological change indices at the country level, that FSU economies benefit more from exploiting technological progress than from catching up to the best practice frontier.     

A generalized procedure to recover the first derivatives of a production function when the firm is a profit maximizer

Partial derivatives of production functions are necessary in many instances to characterize the technology of firms. We present here a general method to recover the first derivatives of the production function of a profit maximizing firm. The method is systematic and applies even when the optimization problem of the firm is subject to additional constraints. It allows researcher to recover returns to scale and technological progress in complex situations.

Cost efficiency of the banking industry and unilateral euroisation: A stochastic frontier approach in Serbia and Montenegro

This paper aims at investigating the differences in cost efficiency of the banking industry in Serbia and Montenegro over the period 2005–2012. These two countries operated under a common monetary regime until 1999 and followed two different monetary regimes thereafter: unilateral euroisation in Montenegro and monetary independence in Serbia. A stochastic frontier approach incorporating bank-specific and country-related variables is used to analyze cost efficiency in the banking sectors of Serbia and Montenegro. The analysis shows that a bank operating at given conditions in terms of ownership, market and other specific characteristics presents significantly higher cost efficiency if it operates in Montenegro rather than in Serbia. We argue that this result may relate to the choice of unilateral euroisation made by Montenegro. It is also shown that foreign-owned banks, higher capitalized banks and banks with lower non-performing loans operate at higher cost efficiency.     

基于前沿生产函数的黑龙江省煤炭城市的技术效率研究

本论文针对黑龙江省经济增长数量很大但经济增长质量不高的现状,采用随机前沿方法,分析了黑龙江省4个煤炭城市10年的技术效率。结果表明,黑龙江省各煤炭城市的技术效率普遍不高,但都呈现稳步上升的趋势。在要素投入不变的情况下,改变经济增长方式,提高技术效率水平,将成为黑龙江省今后经济发展的一个重要方向。     

A semiparametric stochastic input distance frontier model with application to the Indonesian banking industry

This paper proposes a semiparametric smooth-varying coefficient input distance frontier model with multiple outputs and multiple inputs, panel data, and determinants of technical inefficiency for the Indonesian banking industry during the period 2000 to 2015. The technology parameters are unknown functions of a set of environmental factors that shift the input distance frontier non-neutrally. The computationally simple constraint weighted bootstrapping method is employed to impose the regularity constraints on the distance function. As a by-product, total factor productivity (TFP) growth is estimated and decomposed into technical change, scale component, and efficiency change. The distance elasticities, marginal effects of the environmental factors on the distance elasticities, temporal behavior of technical efficiency, and also TFP growth and its components are investigated.

     

Efficiency Gains and Cost Reductions from Individual Transferable Quotas: A Stochastic Cost Frontier for the Australian South East Fishery

In this paper efficiency gains and associated cost reductions from increases in traded quota are estimated with a stochastic cost frontier for the Australian South East Trawl Fishery (SETF). Estimation of this frontier also provides key information on the relative importance of input costs in the SETF, returns to scale, variations in costs as a result of trade in quota and the economic performance of each fishing vessel, year to year. Final estimations indicate that increases in the volume of quota traded have resulted in considerable efficiency gains and cost reductions in the SETF, ranging from 1.8 to 3.5 cents per kilogram for surveyed vessels for every 1% increase in the volume of quota traded, or 1–2.4% of total variable costs, with considerable gains also accruing to crew and skipper in the form of larger share payments. Mean vessel efficiency is relatively high in the SETF, estimated at over 90%, and increases further to 92% over the sample period with increased trades in quota.Jel Classification: Q22, Q28     

A threshold stochastic volatility model with explanatory variables

In this paper, we introduce a threshold stochastic volatility model with explanatory variables. The Bayesian method is considered in estimating the parameters of the proposed model via the Markov chain Monte Carlo (MCMC) algorithm. Gibbs sampling and Metropolis–Hastings sampling methods are used for drawing the posterior samples of the parameters and the latent variables. In the simulation study, the accuracy of the MCMC algorithm, the sensitivity of the algorithm for model assumptions, and the robustness of the posterior distribution under different priors are considered. Simulation results indicate that our MCMC algorithm converges fast and that the posterior distribution is robust under different priors and model assumptions. A real data example was analyzed to explain the asymmetric behavior of stock markets.     

The fundraising efficiency in U.S. non-profit art organizations: an application of a Bayesian estimation approach using the stochastic frontier production model

This article examines how efficient art organizations are in raising funds from private giving. We measure fundraising efficiency using a Bayesian estimation approach using the stochastic frontier production model. We show that fundraising efficiencies are generally quite low for art organizations in the U.S. when private giving is only considered as a fundraising output; however, when the effect of fundraising on ticket sales is considered, fundraising efficiencies improve substantially. We also show that government grants have a negative impact on fundraising efficiency and therefore partially crowd out private giving.