The Brazilian Soccer Championship: an efficiency analysis

This article analyses the top Brazilian football league from 2003 to 2011 by estimating a cost function and using a stochastic frontier model. Among the covariates, the number of fans per club and club remoteness is taken into account. The Brazilian clubs are then ranked according to their technical efficiency during the 2000–2011 period. Based on the results, the policy implication is presented, and the economic implications arising from the study are also considered.     

The efficiency of Mozambique soccer league: the Moçambola

This paper analyses the technical efficiency of the Mozambique football league from 2008 to 2014 using a Bayesian stochastic frontier model with exponential specification. Covariates include contextual characteristics such as location, identification as a Muslim club, and sporting performance. The results uncover that Mozambique sports clubs display varying efficiency, revealing distinct managerial incentives in the Mozambique football league. Policy implications are derived, including efficiency scores deemed to be acceptable to the league and reconsideration of the rationale for national investment in all league’s clubs.     

广东省大中型工业企业研发效率区域差异及其收敛性

基于中间-最终产出效率的视角,运用随机前沿分析和β收敛性检验,利用2002—2010年广东省的统计数据研究了广东省大中型工业企业研发效率的区域差异及其收敛性。结果表明:广东省三大区域(珠三角地区、粤东粤西两翼地区和粤北山区)的大中型工业企业的研发中间产出效率的差异不明显,研发最终产出效率存在显著差异,该差异主要是由环境因素造成;三大区域的大中型工业企业研发中间产出效率不存在绝对收敛,而研发最终产出效率存在明显的"俱乐部收敛",并分化出珠三角地区和粤东粤西两翼地区-粤北山区两大俱乐部。     

Allocative and scale efficiency among maize farmers in Zambia: a zero efficiency stochastic frontier approach

The commonly used stochastic frontier model assumes that all firms are inefficient. In this specification, inefficiency is non-negative, and the probability of inefficiency being exactly zero is also zero. To the extent that efficiency varies widely across farms in under-developed economies, it is important to employ techniques that account for both inefficiency and full efficiency to ensure unbiased efficiency estimates. In this study, we employ a zero-inefficiency stochastic frontier model to examine allocative efficiency and scale economies, as well as key determinants of efficiency among Zambian maize farmers. The results show that, unlike the stochastic frontier model, the zero-inefficiency stochastic frontier model successfully allows for both fully efficient and inefficient firms to be accounted for in the estimation procedure. The estimates also reveal the presence of scale economies, with the zero-inefficiency stochastic frontier model better predicting scale efficiency compared to the stochastic frontier model. The findings also show that inefficiency is explained by the level of education, access to extension services, distance to markets and access to credit.     

Efficiency measurement using a latent class stochastic frontier model

Efficiency estimation in stochastic frontier models typically assumes that the underlying production technology is the same for all firms. There might, however, be unobserved differences in technologies that might be inappropriately labeled as inefficiency if such variations in technology are not taken into account. We address this issue by estimating a latent class stochastic frontier model in a panel data framework. An application of the model is presented using Spanish banking data. Our results show that bank-heterogeneity can be fully controlled when a model with four classes is estimated. This paper was written during Luis Oreas visit to Binghamton University in the summer of 2002. We would like to thank an associate editor of the journal and two anonymous referees for their detailed comments. However, we alone are responsible for any remaining errors.     

创新环境约束下高技术产业区域创新效率及收敛性研究

以各地区高技术产业为样本,应用超越对数随机前沿模型实证测算了创新环境约束下各地高技术产业基础研发和成果转化创新效率,并基于σ收敛、β收敛以及俱乐部收敛3种判别方法,考察了高技术产业基础研发效率和成果转化效率的收敛性特征。研究发现,2000-2014年我国创新环境对区域高技术产业的影响不可小觑,在其约束下高技术产业基础研发效率不断提升,呈现出东西较高、中北较低的分布态势且出现收敛特征;在应用效率方面,各地区成果转化效率大致划分为2000-2007年的缓慢增长期与2008-2014年的缓慢衰退期两个阶段,具有东高西低、南高北低的分布态势且趋于发散。     

Maximum entropy: a stochastic frontier approach for electricity distribution regulation

The literature on incentive-based regulation in the electricity sector indicates that the size of this sector in a country constrains the choice of frontier methods as well as the model specification itself to measure economic efficiency of regulated firms. The aim of this study is to propose a stochastic frontier approach with maximum entropy estimation, which is designed to extract information from limited and noisy data with minimal statements on the data generation process. Stochastic frontier analysis with generalized maximum entropy and data envelopment analysis—the latter one has been widely used by national regulators—are applied to a cross-section data on thirteen European electricity distribution companies. Technical efficiency scores and rankings of the distribution companies generated by both approaches are sensitive to model specification. Nevertheless, the stochastic frontier analysis with generalized maximum entropy results indicate that technical efficiency scores have similar distributional properties and these scores as well as the rankings of the companies are not very sensitive to the prior information. In general, the same electricity distribution companies are found to be in the highest and lowest efficient groups, reflecting weak sensitivity to the prior information considered in the estimation procedure.

     

Sensitivity analysis of efficiency rankings to distributional assumptions: applications to Japanese water utilities

This article examines the robustness of efficiency score rankings across four distributional assumptions for trans-log stochastic production-frontier models, using data from 1221 Japanese water utilities (for 2004 and 2005). One-sided error terms considered include the half-normal, truncated normal, exponential and gamma distributions. Results are compared for homoscedastic and doubly heteroscedastic models, where we also introduce a doubly heteroscedastic variable mean model, and examine the sensitivity of the nested models to a stronger heteroscedasticity correction for the one-sided error component. The results support three conclusions regarding the sensitivity of efficiency rankings to distributional assumptions. When four standard distributional assumptions are applied to a homoscedastic stochastic frontier model, the efficiency rankings are quite consistent. When those assumptions are applied to a doubly heteroscedastic stochastic frontier model, the efficiency rankings are consistent when proper and sufficient arguments for the variance functions are included in the model. When a more general model, like a variable mean model is estimated, efficiency rankings are quite sensitive to heteroscedasticity correction schemes.     

The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: The case of U. S. shipbuilding during WWII

This paper examines the productivity and efficiency experience of World War II Liberty ship builders using two complementary paradigms which can be viewed as alternative specifications of the endogenous growth model introduced by Romer (1986) and the stochastic frontier production model introduced by Aigner, Lovell, and Schmidt (1977). We develop modifications in the endogenous growth model to allow for learning as well as spatial spillovers by relating productivity growth to cumulative productive experience (the ‘learning curve’) and to worker experience as it is transferred and utilized across different geographical regions. We also consider the relative impact of both proximal and distant simultaneous production on productivity growth. We then utilize a framework in which the efficiency component of productivity growth is explicitly considered using a stochastic frontier model wherein contributions to productivity growth introduced in the endogenous growth model are formally modeled as determinants of efficiency change.     

Multi-period mean–variance asset–liability management with uncontrolled cash flow and uncertain time-horizon

This paper considers an asset–liability management problem under a multi-period mean–variance model with uncontrolled cash flow and uncertain time-horizon. The difference from the existing literature is that the liability is assumed to be influenced not only by the stochastic return of the liability but also by some uncontrolled cash flows, which can be explained as, for example, stochastic expenditure of individual investors, or claim processes of insurers. Firstly, the original problem is translated into a standard multi-period stochastic optimal control problem by introducing a Lagrange multiplier, and the corresponding analytical solution is derived by adopting the dynamic programming approach. Secondly, according to Lagrange duality theorem, closed-form expressions for the efficient investment strategy and the mean–variance efficient frontier are obtained. Moreover, a multi-period version of two-fund separation theorem is proved, and some special cases are discussed. Finally, some numerical examples are presented to illustrate our results.     

Cost efficiency of French rugby clubs

This article analyses the cost efficiency of French first-league rugby clubs using a stochastic frontier model. The frontier estimation confirmed that the model fits the data well with all coefficients correctly signed and in line with the theoretical requirements. The results show that one of the clubs is operating efficiently, with the majority of clubs clustered around 20% inefficiency. Policy implications are derived.     

Financial constraints on sport organizations’ cost efficiency: the impact of financial fair play on Italian soccer clubs

We analyze the effect of the introduction of stricter financial constraints on the trade-off between sporting and economic results. We apply a stochastic Cobb-Douglas production frontier model to a sample of Italian Serie A teams, i.e. first division, over the period 2005–2015 to evaluate the variation in soccer clubs’ cost efficiency following the application of the UEFA Financial Fair Play (FFP) principles in 2010. FFP imposes stricter financial regulation as a requirement for a club to be admitted to Union of European Football Associations (UEFA) tournaments. Firstly, we find that FFP does not improve the average efficiency of the Italian first division teams. Secondly, we show that FFP has contributed to leveling the playing field, reducing the gap in terms of efficiency between top teams and lower-tier teams.

Abbreviations: FFP: Financial Fair Play; UEFA: Union of European Football Associations; DEA: Data Envelopment Analysis; SFA: Stochastic Frontier Analysis     

FDI performance: a stochastic frontier analysis of location and variance determinants

The opening up process of the eastern European countries was marked by greater integration of FDI with their western neighbouring countries. Using the single-step ML approach to stochastic frontier analysis, the location and variance determinants of FDI are estimated using the knowledge capital (KK) model framework. The findings, based on a panel of bilateral FDI stocks from 10 western to 10 eastern European countries over the 1996–2007 period, suggest FDI is determined by both horizontal and vertical motives while the process of liberalization and infrastructural developments significantly reduces the variance of FDI. In using a stochastic frontier specification of the KK model, the efficiency of FDI performance is identified relative to maximum levels. The bilateral efficiency scores suggest a mixed performance, indicating scope to improve the efficiency of FDI.     

Estimation of technical inefficiency in manufacturing industry

An extension of the method of estimation of technical ineficiency is presented based on the stochastic production frontier approach. A derivation of the estimation procedure is given and the technique applied at the industry level. The choice of production function is considered and empirical results pertaining to Australia and the UK are presented.     

A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions

Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation‐based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest.     

Estimation of nonparametric inefficiency effects stochastic frontier models with an application to British manufacturing

The purpose of this paper is to propose a simple stochastic frontier model with a non-parametric specification for covariates affecting the mean of technical inefficiency. We derive a simple two-step semiparametric estimation procedure to estimate the frontier parameters as well as the mean of the technical inefficiency. The consistency of the estimator and its asymptotic normality are shown. The proposed method is illustrated using a large panel data set of British manufacturing firms.     

Predicting technical effciency in stochastic production frontier models in the presence of misspecification: a Monte-Carlo analysis

This paper provides a theoretical explanation for the sensitivity of technical efficiency measures to the choice of functional specification in stochastic production frontier models. It is shown that inappropriate functional specifications translate into a misspecification in the conditional mean of the stochastic frontier regression model. This misspecification, in turn, results in estimates of technical efficiency, confidence intervals and production elasticities being biased, even asymptotically. Monte-Carlo simulations reveal that the severity of the bias depends on the functional specification and the percentage contribution of the variance of technical inefficiency to the total variance of the composed errors.     

Path-dependent economic progress and regress: The negative role of subsidies in economic growth

This paper develops a two-stage economic growth model with real options and examines the effects of various subsidy policies. The economic stages are the deterministic and stochastic AK stages, and the economy may shift between the two, depending upon state variables and technological shocks. This model allows for path-dependent economic growth that accounts for both club convergence and divergence across countries. Moreover, it is shown that under certain conditions, a decrease in the subsidy rate facilitates the shift from the deterministic to stochastic AK stages, which is defined as “economic progress”, even in the face of an economic crisis, while more subsidies delay economic progress and promote the shift from the stochastic to deterministic AK stages, which is defined as “economic regress”.     

测度政府技术效率的模型与方法比较研究

技术效率是在产出规模不变,市场价格不变的条件下,按照既定的要素投入比例所能达到的最小生产成本占实际生产成本的百分比。政府技术效率是广义的政府绩效或效率的一个部分,它是政府提供公共服务过程中能够测度的政府投入与政府产出之间的比例关系。测度政府技术效率主要的模型与方法有非参数前沿法和参数前沿法。非参数前沿法主要包括数据包络法分析（DEA）和自由处置包（FDH）,而参数前沿法主要包括随机前沿法（SFA）、模糊边界法（TFA）和确定性前沿法（DFA）。通过建立模型科学对政府技术效率进行评估与测度可提高政府各个方面的科学性和有效性,从而促进政府技术效率的提高。     

Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers

In previous studies, measures of technical inefficiency effects derived from stochastic production frontiers have been estimated from residuals which are sensitive to specification errors. This study corrects for this inaccuracy by extending the doubly heteroscedastic stochastic cost frontier suggested by Hadri (1999) to the model for technical inefficiency effects. This model is a stochastic frontier production function for panel data as proposed by Battese and Coelli (1995). The study uses, for illustration of the techniques, data on 101 mainly cereal farms in England. We find that the correction for heteroscedasticity is supported by the data. Both point estimates and confidence intervals for technical efficiencies are provided. The confidence intervals are constructed by extending the “Battese-Coelli” method reported by Horrace and Schmidt (1996) by allowing the technical inefficiency to be time varying and the disturbance terms to be heteroscedastic. The confidence intervals reveal the precision of technical efficiency estimates and show the deficiencies of making inferences based exclusively on point estimates. First version received: March 2000/Final version received: Oct. 2001 RID="*" ID="*"  The authors are grateful to the Economic and Social Research Council for access to their Data Archive which has provided the data for this research. We are indebted to Badi Baltagi and two anonymous referees for their helpful comments and suggestions. The usual caveat applies.