DEA-based Malmquist productivity indexes for understanding courts reform

Currently there is no clear empirical evidence as to which the most appropriate reform to improve national judicial systems might be, i.e., whether it is better to implement a policy which focuses on judges and their incentives or, alternatively, a policy aimed at reorganizing the courts' structure.The judicial system, like many other sectors of the public administration, is an industry producing a specific good – justice – and, accordingly, it can be studied by using the customary tools of production theory. The paper applies the two-stage analysis by Simar and Wilson (2007) and the Malmquist index to the judiciary, in order to better understand the impact of a specific policy on the productivity of the Italian tax judiciary.The results highlight strong heterogeneity among courts, depending on their geographical location, with North-West and North-East of Italy as the most efficient macro areas. Moreover, by decomposing the index into change in efficiency and change in technology, this work provides a further glimpse into the judiciary's production organization. Interestingly, the evidence shows that a reduction in the number of active sections has had a negative impact on the overall performance of the courts (i.e., a negative change in efficiency of 0.0103, with a p-value < 0.01), although the reorganization of the residual sections has possibly determined a more effective use of the remaining resources (i.e., a positive change in technology of 0.00285, with a p-value < 0.01). Hence, technology does not fully replace the productive role of the judges.The overall results suggest that adjudication is a labor-intensive activity and, although fine-tuning their organization can indeed enhance the productivity of the courts, the role of the judges still remains pivotal. There might indeed be ways to increase the efforts made by judges and a suitable policy should create incentives aimed at boosting their productivity.     

Assessing the Italian tax courts system by weighted three-way log-ratio analysis

Deciding on what should be the most suitable reforms of a national judicial system, whether this means reorganising a courts' structure or offering incetives to judges, requires more empirical evidence. The efficiency of the public judicial system is important to any functioning democracy as it affects several aspects of citizens’ life. As a consequence, new statistical methodologies are required for further valuable insights into the issues that affect the effectiveness of a judicial system.The current study attempts to fill this gap by introducing a new statistical method to investigate the heterogeneity among Italian judicial courts. Here we propose a generalisation of log-ratio analysis for the analysis of the association between the variables of a three-way contingency table. Our focus of this investigation will be on the tax court system of the Italian judicial system.Log-ratio analysis presents many advantages, two of which are the computation and the visual representation of the odds ratios on which the analysis is based. For three-way tables, a conditional odds ratio reflects the likelihood that an event (say tax disputes) will take place in a particular geographical area (say North Italy) instead of an another (say South Italy) given a specific condition (type of justice court).Interestingly, the three-way log-ratio analysis presented in this paper allows one to visually describe these conditional odds-ratios in terms of point distances in a biplot between the types of justice court located in different geographical areas of Italy.     

Efficiency analysis of Norwegian district courts

This paper examines the efficiency of the Norwegian district courts with the aim of suggesting ways of improving this efficiency. Pooling the observations for the period 1983 to 1988 efficiency measures are calculated for each court using the nonparametric data envelopment analysis (DEA) method. The results show estimates of overmanning due to technical inefficiency. Comparisons are made between the specialized city courts and the generalized rural courts. When using the yearly observations Malmquist indices are calculated to estimate the rate of productivity change. Finally the paper addresses the questions of how the information from DEA can be used by the courts to become more efficient.The editor of this paper was Knox Lovell.     

Decomposing multifactor productivity in Italy from 1998 to 2004: evidence from large firms and SMEs using DEA

This paper presents a firm-level analysis of multifactor productivity (MFP) in Italy between 1998 and 2004. Using data envelopment analysis (DEA) technique, MFP change are measured for 31 industries and decomposed into efficiency change and technical change (which in turn is interpreted as the combined effect of technical progress and scale economies). The results highlight the stagnation in many Italian production activities and even a decrease in MFP in some industries. A non-parametric statistical test on the results obtained from DEA reveals that the analysed larger firms have been more likely to perform better in efficiency than the smaller ones. This outcome seems to complement the Schumpeterian view of a relatively high attitude of larger firms towards technological innovation and productivity growth.     

基于环境负产出的能效动态Malmquist模型研究

本文旨在研究环境效率—能源效率—经济效率的"三位一体动态全要素生产率"。首先基于数据包络分析建立了环境约束下的能效动态Malmquist模型,定义了能效效率改变指数、污效效率改变指数和动态进步指数。通过对中国18个行业2000～2007年的数据分析,指出未考虑环境效应、动态效应的Malmquist模型会带来误判,进而揭示出在中国能效全要素生产率改变过程中,能源环境效应起到了不可忽略的作用,而动态效应则是最大的瓶颈,却没得到应有的重视。     

Shadow Price Approach to Total Factor Productivity Measurement: With an Application to Finnish Grass-Silage Production

This paper explores an intermediate route between the Fisher and the Malmquist productivity indexes so as to minimize data requirements and assumptions about economic behavior of production units and their production technology. Assuming quantity data of inputs and outputs and the behavioral hypothesis of allocative efficiency, we calculate the exact value of the Fisher ideal productivity index using implicit shadow prices revealed by the choice of input–output mix. The approach is operationalized by means of a nonparametric data envelopment analysis (DEA) model. Empirical application to Finnish grass silage farms suggests that the Malmquist and the Fisher productivity indices yield similar results when averaged over firms, but there can be major differences in the results of the two approaches at the level of individual firms.     

Measurement of innovation efficiency in logistic enterprises: Evidence from China based on the three-stage DEA-Malmquist index model approach

Continuous improvement of technological innovation ability, adjustment of the development strategy, and enhancement of operational performance are of great theoretical and practical significance for logistics enterprises. This paper aims to analyze and evaluate the innovation efficiency of the logistics industry. The study utilizes the static three-stage DEA model and the dynamic Malmquist index model, considering a total of 12 indicators related to innovation input, output, and environmental variables. A dataset of 2940 entries from 49 listed logistics enterprises from 2017 to 2021 was calculated. The analysis provides insights into the innovation efficiency of logistics enterprises from a static perspective and the innovation total factor productivity from a dynamic perspective and decomposition terms. Based on the analysis of environmental variables by the SFA model, it was found that DEA inefficiency is the combined result of environmental factors and management inefficiency. Environmental variables have both positive and negative effects on innovation. The improvement of the economic development level will lead to excess R&D investment. Increased government simple fund subsidies are not conducive to the efficient allocation of innovation resources within enterprises. The expansion of enterprise scale will increase R&D personnel and investment in fixed assets. A thriving technology market can encourage enterprises to improve their own conversion rate of scientific and technological output and give full play to their innovation ability. The dynamic Malmquist model analysis reveals a recution in the overall innovation efficiency of listed logistics enterprises over 5 years. The changes in total factor productivity and technological progress efficiency of all listed logistics enterprises are synchronized, with most enterprises exhibiting higher technological progress efficiency compared to comprehensive technical efficiency. The total factor productivity of logistics enterprise innovation is mainly affected by comprehensive technical efficiency.     

DEA of financial statements data: The U.S. computer industry

DEA (data envelopment analysis) is a technique for determining the efficiencyfrontier (the envelope) to the inputs and outputs of a collection of individual corporations or other productive units. DEA is here employed to estimate the intertemporal productive efficiency of U.S. computer manufactures, using financial data brought from earnings statements and balance sheets. The results indicate that a few corporations, including Apple Computer Inc., Compaq Computer Corp., and Seagate Technology were able to stay at the productivity efficiency frontier throughout the time period investigated. But not all successful corporations did; sometimes subefficiency (=disequilibrium) actually goes together with very rapid growth. A new Malmquist type productivity index is calculated for each corporation, measuring shifts of the estimated intertemporal efficiency frontier.     

Measuring productivity growth, technical progress, and efficiency changes of CPA firms prior to, and following the Sarbanes–Oxley Act

This paper investigates productivity growth, technical progress, and efficiency change for a group of the 56 largest CPA firms in the US from the period 1996–1999 through the period 2003–2006, where the former preceded, and the latter followed, enactment of the Sarbanes–Oxley Act (SOX). Data envelopment analysis (DEA) is used to calculate Malmquist indices of three measures of interest: productivity growth, technical progress, and efficiency change. Results indicate that CPA firms, on average, experienced a productivity growth of approx. 17% from the pre- to post-SOX period. Consistent with the finding of Banker et al. [Banker RD, Chang H, Natarajan R. Productivity change, technical progress and relative efficiency change in the public accounting industry. Management Science 2005;51:291–304], this productivity gain can be attributed primarily to technical progress rather than a change in relative efficiency. In addition, results indicate that the “Big 4” firms underperformed their non-Big 4 counterparts in both productivity growth and technical progress.     

Sequential Malmquist Indices of Productivity Growth: An Application to OECD Industrial Activities

The paper applies both the standard DEA methodology with contemporaneous frontiers and DEA with sequential frontiers to study changes in productivity and efficiency in manufacturing for a sample of eleven OECD countries over a twenty-year period. It uses a decomposition of the industrial Malmquist productivity indices to locate the sources of productivity growth: 'technical progress' and 'catching up.' The alternative indices are interrelated in a unifying framework that provides an interpretation to their difference. We argue that for manufacturing industries, in which technological regress is unlikely to occur, DEA with sequential frontiers provides a more adequate measure for the contribution of technical changes than standard DEA.     

Measures in DEA with an Application to the Malmquist Index

This paper shows the importance of goal vectors G in measuring and dealing with DEA inefficiencies. It emphasizes the advantages of the family of additive relative to the traditional oriented DEA models and shifts the primary emphasis to measuring inefficiency rather than efficiency. This new (raw) inefficiency measure RIN incorporates both the traditional DEA efficiency and the DEA slacks and provides the background for a new approach to the Malmquist Index. The final section points out some deficiencies in existing computational procedures for selecting G and calls for continued research on the selection process, as well as showing a role for G in returns to scale studies.     

Productivity indexes under Hicks neutral technical change

The Malmquist and Hicks–Moorsteen productivity indexes are the two most widely used theoretical indexes for measuring productivity growth of firms, industries and countries. We indicate that these two indexes coincide under constant returns to scale technology and Hicks neutral technical change. While the conditions on production technology under which two indexes coincide have been examined before, this is the first study on the types of technical change under which they coincide. We shed new insight on the relationship between these popular indexes.     

我国技术效率、技术进步与生产率区域差异的实证研究

本文用非参数Malmquist指数方法研究了我国全要素生产率的增长状况及其区域差异,并将其分解为技术进步和技术效率,同时采用增长回归法对我国地区之间TFP、技术效率、科技进步的差异进行了检验。研究表明:1994-2007年间我国全要素生产率年均增长率达到1%,主要得益于技术进步水平的提高,技术效率总体上呈现下滑趋势;我国各省市区的科技进步、技术效率、TFP变化呈现出较为明显的差异,其中TFP和科技进步变化差异最为明显,而技术效率变化差异不大。     

The productivity of private and social farms: Multilateral Malmquist indices for Slovene dairying enterprises

Applying programming techniques to farm-level panel data for four cooperative and 12 private dairy farms in the Yugoslav Republic of Slovenia gives estimates of technical efficiency, scale efficiency, and technical progress. These are used to construct multilateral Malmquist indices of total factor productivity (TFP). For the cooperatives, TFP growth has been slow and is attributable to technical progress. For the private farms, technical progress was also slow, but TFP growth was faster due to improved efficiency. Scale inefficiency explains the poorer absolute performance of the private farms, indicating the need for land reform as well as technological change.     

Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry

The banking industry in Canada is essentially an oligopoly with five large participants controlling about 90% of the market. To evaluate the industry's performance over time, we need to deal with the problem of a small number of DMU's compared to the number of relevant inputs and outputs. To overcome this problem we use data envelopment analysis (DEA) window analysis, whereby efficiency scores for the 20 year period 1981–2000 are obtained. To measure productivity changes over time, Malmquist indices can be calculated from DEA scores. Using DEA window analysis scores, however, raise the question of how to define the same period frontier in a DEA window analysis. We show that for both the adjacent and the base period Malmquist index and for all suggested definitions of same period frontier, the standard decomposition into frontier shift and catching up effects gives inappropriate results when Malmquist indices are based on DEA window analysis scores.     

A new decomposition and interpretation of Hicks-Moorsteen productivity index for analysis of Stock Exchange companies: Case study on pharmaceutical industry

This paper deals with the productivity index based on Hicks-Moorsteen (HM) productivity index for analysis of Stock Exchange firms. In this paper, a decomposition of Hicks-Moorsteen productivity index is provided that uses data envelopment analysis (DEA) models. On the other hand, it is offered a new interpretation and decomposition for components of HM productivity index that in previous studies were not performed any interpretation of it. These components have named the output production and the input consumption in terms of changing the efficiency frontier. In addition, by comparing the components of HM productivity index and productivity value, the optimal values of output production and input consumption are determined. Also, the analysis is determined how to identify the optimal value of a firm over a period of time. The proposed approach is applied to 26 pharmaceutical manufacturers that are from Tehran Stock Exchange. Data have been collected for six consecutive years (2009–2014) and have been considered financial ratios for evaluating companies. The results show that the Hicks-Moorsteen productivity index is more able to provide managerial aspects than other productivity indexes such as the Malmquist productivity index.     

A superlative index number formula for the Hicks-Moorsteen productivity index

The Malmquist and Hicks-Moorsteen productivity indexes are the two most widely used theoretical indexes for measuring productivity growth. Since these productivity indexes are defined by unknown distance functions, it is necessary to estimate the distance functions to compute them in principle. On the other hand, the Törnqvist productivity index is an empirical index number formula that is directly computable from the prices and quantities of the inputs and outputs alone. Caves et al. (1982) imply that the Malmquist index coincides with the Törnqvist index under profit maximizing behaviour and constant returns to scale technology. The purpose of the present paper is to point out that the Hicks-Moorsteen productivity index coincides with the Törnqvist productivity index under the same condition. We emphasize that the condition of constant returns to scale is indispensable for deriving the equivalence between the two indexes. Moreover, even when this condition is relaxed to the α returns to scale, the equivalence between the Hicks-Moorsteen and Törnqvist productivity indexes is shown to hold true.     

Productivity and efficiency in the US: effects of business cycles and public capital

We add to the literature on the US productivity slowdown and effects of public capital on productivity by employing Malmquist productivity indexes to measure productivity. These indexes allow us to decompose productivity growth into efficiency change and technological innovation. We derive these components for each observation, which we exploit to explore factors which may lead to differences in productivity across regions, including business cycles, both own-state and cross-border public infrastructure investment, and relative sizes of the manufacturing, service and public sector. Our results suggest that the components of total factor productivity change lend important insights into the fairly complex effects of public capital on productivity growth.     

A Huff model with firm heterogeneity and selection. Application to the Italian retail sector

ABSTRACT

In this paper, firm heterogeneity (in terms of productivity, i.e., marginal costs) is incorporated into a Huff model of competition in the Italian retail sector. A higher market potential in the trade area is associated with higher average productivity and lower productivity dispersion through selection of the best stores. The analysis, based on a unique data set encompassing 14,212 Italian retailers, finds support for this relationship in Southern Italy, but not in Northern and Central Italy (where opposite results are obtained in some cases), suggesting the selection dynamics are affected by context factors (other than provincial/regional accessibility) related to an upper geographical scale. The results are robust to controlling for local context factors such as financial risk and floor size restrictions. Floor size restrictions are found to enhance selection.     

Comparing mean efficiency and productivity scores from small samples: A bootstrap methodology

This paper provides a bootstrap methodology for constructing confidence intervals for means of DEA and econometrically estimated efficiency scores, Malmquist productivity indices, and other similar measures in small samples. The procedure is nonparametric since no distributional assumptions are required. An empirical example is provided.This research was performed while Wilson was under contract with the Management Science Group, US Department of Veterans Affairs, Bedford, MA 01730.