Assessing dynamic inefficiency of the Spanish construction sector pre- and post-financial crisis

This paper undertakes the full decomposition of dynamic cost inefficiency into technical, scale and allocative inefficiency based on the dynamic directional distance function. The empirical application estimates dynamic inefficiency in the Spanish construction industry before and during the current financial crisis over the period 2001–2009. Static inefficiency measures are biased in a context of a significant economic crisis with large investments and disinvestments as they do not account for costs in the adjustment of quasi-fixed factors. Allocative inefficiency is smaller, while technical inefficiency is larger when using the dynamic compared to the static framework. Results further indicate that overall dynamic cost inefficiency is very high with technical inefficiency being the largest component, followed by allocative and scale inefficiency. Moreover, overall dynamic cost inefficiency is significantly larger before the beginning of the financial crisis than during the financial crisis. Larger firms are less technically and scale inefficient than smaller firms on average, but have more problems in choosing the mix of inputs that minimizes their long-term costs. Firms that went bankrupt, on average, have a higher overall dynamic cost inefficiency and scale inefficiency than continuing firms.     

Bank productivity and performance groups: A decomposition approach based upon the Luenberger productivity indicator

The purpose of this paper is twofold. First, in the framework of the strategic groups’ literature, it analyZes changes in productivity and efficiency of Spanish private and savings banks over an eight-year period (1998-2006). Second, by adapting the decomposition of the Malmquist productivity indices suggested by Färe et al. (1994), it proposes similar components decomposing the Luenberger productivity indicator. Initially, productivity is decomposed into technological and efficiency changes. Thereafter, this efficiency change is decomposed into pure efficiency, scale and congestion changes. Empirical results demonstrate that productivity improvements are partially due to technological innovation. Furthermore, it is shown how the competition between private and savings banks develops in terms of the analyzed productivity and efficiency components. While private banks enjoy better efficiency change, savings banks contribute more to technological progress. Consequently, the Luenberger components are used as cluster analysis inputs. Thus, economic interpretations of the resulting performance groups are made via key differences in productivity components. Finally, following the strategic groups’ literature, supplementary insights are gained by linking these performance groups with banking ratios.     

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.     

Measuring productivity growth under factor non-substitution: An application to US steam-electric power generation utilities

A theoretical framework is developed for decomposing partial factor productivity and measuring technical inefficiency when the underlying technology is characterized by factor non-substitution. With Farrell’s (1957) radial index of technical inefficiency being inappropriate in this case, Russell non-radial indices are adapted to measure technical inefficiency in a Leontief-type model. A system of factor demand equations with a regime specific technical inefficiency term is proposed and estimated allowing for dependence across inputs using a copula approach. Then the paper presents a complete decomposition of partial factor productivity changes using a dataset of US steam-power electric generation utilities.     

On the inconsistency of the Malmquist–Luenberger index

Apart from the well-known weaknesses of the standard Malmquist productivity index related to infeasibility and not accounting for slacks, already addressed in the literature, we identify a new and significant drawback of the Malmquist–Luenberger index decomposition that questions its validity as an empirical tool for environmental productivity measurement associated with the production of bad outputs. In particular, we show that the usual interpretation of the technical change component in terms of production frontier shifts can be inconsistent with its numerical value, thereby resulting in an erroneous interpretation of this component that passes on to the index itself. We illustrate this issue with a simple numerical example. Finally, we propose a solution for this inconsistency issue based on incorporating a new postulate for the technology related to the production of bad outputs.     

Is there a Trade-Off between Quality and Productivity? The Case of Diagnostic Technologies in Portugal

The purpose of this paper is twofold: first, we compute quality-adjusted measures of productivity change for the three most important diagnostic technologies (i.e., the Computerised Tomography Scan, Electrocardiogram and Echocardiogram) in the major Portuguese hospitals. We use the Malmquist–Luenberger index, which allows to measure productivity growth while controlling for the quality of the production. Second, using non-parametric tests, we analyse whether the implementation of the Prospective Payment System may have had a positive impact on the movements of productivity over time. The results show that the PPS has helped hospitals to use these tools more efficiently and to improve their effectiveness.     

Evolution of bank efficiency in Brazil: A DEA approach

This paper investigates cost, technical and allocative efficiencies for Brazilian banks in the recent period (2000–2007). We use Data Envelopment Analysis (DEA) to compute efficiency scores. Brazilian banks were found to have low levels of economic (cost) efficiency compared to banks in Europe and in the US. For the period with high macroeconomic volatility (2000–2002) the economic inefficiency in Brazilian banks can be attributed mainly to technical inefficiency rather than allocative inefficiency. State-owned banks are significantly more cost efficient than foreign, private domestic and private with foreign participation. There is no evidence of differences in economic efficiency due to type of activity and bank size. These results may provide some useful guidance for financial regulators and bank managers.     

Technological progress and productivity growth in the U.S. mobile telecommunications industry

The fast growing U.S. mobile wireless industry has been experiencing dramatic technological change and substantial competition. As a result of these catalysts, we argue that wireless firms have experienced significant productivity improvement and provide new evidence that technological progress almost exclusively contributed to productivity improvements in the wireless industry by significantly expanding the production possibilities set. We employ nonparametric estimation procedures based on Data Envelopment Analysis (DEA) that utilize input-output data from a representative sample of 16 firms in the mobile wireless industry to estimate productivity change, technological change, and relative efficiency change for the period spanning the years from 2000 to 2002. Our findings show that the industry experienced a significant growth of 13% in productivity, which was primarily due to an average technological progress of 9.9% in the industry. Additionally, we find that national wireless operators experienced significantly higher productivity growth and contributed more to technological progress than regional providers. Firms that were industry pioneers as evidenced by high market share at the beginning of our sample period experienced higher productivity growth and greater technological progress compared to firms with lower initial market share. Moreover, the industry experienced significantly higher productivity growth and technical progress in the later sample period between 2001 and 2002 than in the early period between 2000 and 2001.     

Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms

Recent econometric advances have made it possible to distinguish between persistent and transient technical inefficiency along with allocative inefficiency in stochastic frontier models for panel data. Kumbhakar et al. (2020) and Lai and Kumbhakar (2019) introduce a methodology that allows for the estimation of these inefficiency components and costs therefrom, while including determinants of both components of technical inefficiency. We extend these models to include technical change and determinants of allocative inefficiency (input misallocation). Including a set of variables that influence input misallocation, we are able to determine the effects of these variables on the cost of allocative inefficiency. We provide empirical evidence on the costs of all three types of inefficiency using data on 149 Norwegian electricity distribution firms between 2000 and 2016. We find that the cost of input misallocation is only slightly lower than that of technical inefficiency. Our results reject a commonly imposed modeling assumption that firms are fully allocatively efficient.     

Incentive regulation and the change in productive efficiency in telecommunications in the United States

Incentive regulation has become an important regulatory tool in the telecommunications industry in the United States. The issue explored here is whether incentive regulation has resulted in an increase in productive efficiency. After providing an overview of the nature of incentive regulation, a methodology for measuring technical inefficiency and its change is introduced. This is a stochastic frontier production function approach reflecting technical inefficiency effects. The results of implementing this methodology suggest that in the production of interLATA billed access minutes for interstate calls, there was no change in technical efficiency, something that incentive regulation was specifically designed to enhance. Finally, an assessment of technical efficiency across individual LECs in the United States indicates considerable variability. Published in 2001 by John Wiley & Sons, Ltd.     

Measuring sectoral productivity across time and across countries

This paper examines the problem of measuring the evolution of productivity changes over time and across the 14 countries included in the OECD's International Sectoral Data Base of two sectors considered essential to the economic growth of any nation, namely manufacturing and services. The basic units of analysis are generalized Malmquist productivity indices. These in turn can be decomposed into several components, associated to the various sources of productivity change. Included here are productivity fluctuations due to economies of scale, being constant or variable, to technical change and technical efficiency change. The computational procedure is based upon the concept of distance function, computed through the use of variations of data envelopment analysis.     

劳动生产率增长源泉与收敛研究

在异质性人力资本的条件下,把劳动生产率增长分解为效率的改变、技术改变、人力资本及物质资本.用核密度函数及回归方法分别对劳动生产率增长及收敛性进行了研究.结果表明:(1)劳动生产率分布由单峰变为多峰,其在初级与高级人力资本下的原因分别为技术改变、物质资本与人力资本;(2)全国的劳动生产率是β收敛的,而西部并不存在β收敛;(3)效率改变及技术改变促进了劳动生产率的发散,而人力资本积累及物质资本积累上促进了劳动生产率的收敛.     

A generalized inefficiency model with input and output dependence

In this paper we propose a general inefficiency model, in the sense that technical inefficiency is, simultaneously, a function of all inputs, outputs, and contextual variables. We recognize that change in inefficiency is endogenous or rational, and we propose an adjustment costs model with firm-specific but unknown adjustment cost parameters. When inefficiency depends on inputs and outputs, the firm's optimization problem changes as the first order conditions must take into account the dependence of inefficiency on the endogenous variables of the problem. The new formulation introduces statistical challenges which are successfully resolved. The model is estimated using Maximum Simulated Likelihood and an empirical application to U.S. banking is provided.     

Eco-efficiency and eco-productivity change over time in a multisectoral economic system

We measure eco-efficiency of an economy by means of an augmented Leontief input–output model extended by constraints for primary inputs. Using a multi-objective optimisation model the eco-efficiency frontier of the economy is generated. The results of these multi-objective optimisation problems define eco-efficient virtual decision making units (DMUs). The eco-efficiency is obtained as a solution of a data envelopment analysis (DEA) model with virtual DMUs defining the potential and a DMU describing the actual performance of the economy. This procedure is then extended to an intertemporal approach in the spirit of the Luenberger productivity indicator. This indicator permits decomposing eco-productivity change into eco-efficiency change and eco-technical change. The indicator is then further decompounded in a way that enables us to examine the contributions of individual production factors, undesirable as well as desirable outputs to eco-productivity change over time. For illustration purposes the proposed model is applied to investigate eco-productivity growth of the Austrian economy.     

EMPIRICAL ANALYSIS OF CLIMATE CHANGE IMPACT ON LOBLOLLY PINE PLANTATIONS IN THE SOUTHERN UNITED STATES

Abstract Few studies have empirically examined climate change impacts on managed forests in the southern United States. In this paper, we use the U.S. Forest Service's Forest Inventory and Analysis Database to fit two growth models across the South and apply the four Hadley III climate scenarios developed for the Intergovernmental Panel on Climate Change Fourth Assessment Report to project future growth and site productivity on loblolly pine plantations. The static growth model provides a direct test of whether a significant climate influence on forest growth can be statistically derived, while the dynamic growth model estimates climate effects through site productivity. Results indicate considerable spatial variation in potential future growth and productivity change on loblolly pine plantations due to climate change in the southern United States, while overall regional effects are projected to be marginal. The pattern of climate change impacts is consistent across the growth models and climate scenarios. These findings have several implications for climate change adaptation policies.     

Productivity change using growth accounting and frontier-based approaches – Evidence from a Monte Carlo analysis

This study presents some quantitative evidence from a number of simulation experiments on the accuracy of the productivity growth estimates derived from growth accounting (GA) and frontier-based methods (namely data envelopment analysis-, corrected ordinary least squares-, and stochastic frontier analysis-based malmquist indices) under various conditions. These include the presence of technical inefficiency, measurement error, misspecification of the production function (for the GA and parametric approaches) and increased input and price volatility from one period to the next. The study finds that the frontier-based methods usually outperform GA, but the overall performance varies by experiment. Parametric approaches generally perform best when there is no functional form misspecification, but their accuracy greatly diminishes otherwise. The results also show that the deterministic approaches perform adequately even under conditions of (modest) measurement error and when measurement error becomes larger, the accuracy of all approaches (including stochastic approaches) deteriorates rapidly, to the point that their estimates could be considered unreliable for policy purposes.     

Measuring inefficiency for specific inputs using data envelopment analysis: evidence from construction industry in Spain and Portugal

This article contributes to the efficiency literature by defining, in the context of the data envelopment analysis framework, the directional distance function approach for measuring both technical and scale inefficiencies with regard to the use of individual inputs. The input-specific technical and scale inefficiencies are then aggregated in order to calculate the overall inefficiency measures. Empirical application focuses on a large dataset of Spanish and Portuguese construction companies between 2002 and 2010 and accounts for three inputs: materials, labor and fixed assets. The results show, first, that for both Spanish and Portuguese construction companies, fixed assets are the most technically inefficient input. Second, the most inefficient scale concerns the utilization of material input in both samples; the reason for this inefficiency is that firms tend to operate in the increasing returns to scale portion of technology set. Third, in both samples, large firms have the lowest input-specific technical inefficiencies, but the highest input-specific scale inefficiencies, compared to their small and medium-sized counterparts, and tend to suffer from decreasing returns to scale. Finally, in both samples, input-specific technical inefficiency under constant returns to scale increased during the period of the recent financial crisis, mainly due to the augmentation in scale inefficiency.

     

Subject mix and productivity in Portuguese universities

Recent changes in higher education, especially associated with its massification, have led to calls for more accountability and to an increasing need to evaluate universities’ performance. However, comparing universities with different subject mixes poses some significant problems. In this article, a linear mixed-effect model methodology allowing for random effects at university level is used to measure the productivity of Portuguese public universities, taking into account their subject composition, for a period of five years (1997–2001). The results show that subject mix is an important factor in explaining the variability in productivity between universities. However, even taking account of subject mix, a lot of inefficiency is found in the system, and a significant variability in productivity among universities exists.     

动态视角下我国3E全要素生产率的区域差异研究

基于含有动态效应的全局Malmquist-Luenberger指数和方向性SBM方法,本文以中国30个省份1998~2011年的数据为样本,研究了资本动态效应下3E全要素生产率增长趋势,以及增长模式的省份差异,并引入Bootstrap-DEA方法计算了全要素生产率变化估计值及其置信区间,通过Bootstrap纠偏提高了测度的准确性。我们发现:(1)1998~2011年我国3E全要素生产率呈增长趋势,但增长率却一直维持在1%以下,其原因是3E前沿面追赶效应和移动效应呈现出的互补状态;(2)传统技术进步是当期投入产出质量水平的提升程度,而资本动态效应是资本跨期作用引起的前沿面移动效应,表示资本的滞后效应导致的技术进步,导致资本动态效应滞后于传统技术进步增长率。     

Specification and estimation of multiple output technologies: A primal approach

This paper addresses specification and estimation of multiple-outputs and multiple-inputs production technology in the presence of technical inefficiency. The primary focus is on the primal formulations. Several competing specifications such as production function, input (output) distance function, input requirement function are considered. We show that all these specifications come from the same transformation function and are algebraically identical. We also show that: (i) unless the transformation function is separable (i.e., outputs are separable from inputs), the input (output) ratios in the input (output) distance function can not be treated as exogenous (uncorrelated with technical inefficiency) resulting inconsistent estimates of the input (output) distance function parameters. (ii) Even if input (output) ratios are exogenous, estimation of the input (output) distance function will result in inconsistent parameter estimates if outputs (inputs) are endogenous. We address endogeneity and instrumental variable issues in details in the context of flexible (translog) functional forms. Estimation of several specifications using both single and system approaches are discussed using Norwegian dairy farming data.