Azorean agriculture efficiency by PAR

The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimizing their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study, and, at the same time, to the need of timely and inexpensive information. The “Productivity Analysis with R” (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection and aggregation, and summarization and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez, 2008) and FEAR (Wilson, 2007). The DEA package performs some models of Data Envelopment Analysis presented in (Cooper et al., 2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in (Simar and Wilson, 2000). PAR is a software framework using a portfolio of models for efficiency estimation and providing also results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimization. PER framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self- explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al., 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of “good” practices and cluster of “less good” practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.N/

Data envelopment analysis (DEA) and financial ratios : a pro-stakeholders’ view of performance measurement for sustainable value creation of the wind energy

Purpose: The purpose of the paper is to explore business performance in a rather sensitive sector that equally combines economic, environmental and social dimensions. The paper investigates the efficiency of wind farm companies, in a framework of pursuing more diverse stakeholders’ interests Design/Methodology/Approach: Ratios and DEA approaches are combined to measure economic efficiency among the DMUs of a sample of wind farms, using data from their financial statements. Findings: Productivity and effectiveness comprise the performance measured by the economic efficiency. We show that by choosing inputs and outputs that are closely related in forming an appropriate financial ratio, it helps to design and explain more fully the impact of a policy intervention aiming at improving economic efficiency. DEA supplements ratios to design, implement and assess a strategy of benchmarking towards bolstering performance, that favors a wider range of stakeholders. Originality/Value: The study provides an in-depth insight into using Data Envelopment Analysis and financial ratios to study economic efficiency. The approach combines economic, social and environmental dimensions (indirectly) of performance, and the composite ratio Return on Total Assets (ROTA). The analysis caters the specific features of the sector renewable energy and their diverse stakeholders.peer-reviewe

Measuring the Efficiency of Pesantren Cooperatives: Evidence in Indonesia

The Cooperative (Koperasi) as a non-Bank financial institution has the purpose of improving the welfare of its members as Koperasi Hidmat and the staffs of Latifah Mubarokiyah Koperasi Ponses Suryalaya that have been since decades ago. Over time, the ideal cooperative can show a significant development and increase the welfare of its members. This study aims to determine the efficiency of cooperative as a benchmark, because by known the performance value of a cooperation, it will known the weeknesses and advantages so that it can be improved the weaknesses and maintain the advantages.The method used is apply Data Envelopment Analysis (DEA). Inputs used from principal savings, mandatory savings, and fixed assets while the output used from savings in the cooperative, savings in other cooperative and SHU. As for result of this research indicates there are 9 perfect efficient DMUs (100 %) and inefficient DMU is 11 DMUs, consisting of 7 (IRS conditions) and 4 (DRS condition). The most inefficient cooperative is Koperasi Hidmat (2014) of 30.66% efficiency level.Kopkar IAILM is able to maintain its grade efficiency level from 2009 to 2015 when compared to other DMUs cooperatives in the observation, except in 2014. The calculation of efficiency level in this research is relative and it is not absolute, so that it is possible when the cooperative sample is added or the observation year is expanded, so it will get different result. The necessity of any cooperative or BMT based on Pondok Pesantren to make annual financial statements in order to increase accountability and transparency of fund management

Financial benchmarking of transportation companies in the New York Stock Exchange (NYSE) through data envelopment analysis (DEA) and visualization

In this paper, we present a benchmarking study of industrial transportation companies traded in the New York Stock Exchange (NYSE). There are two distinguishing aspects of our study: First, instead of using operational data for the input and the output items of the developed Data Envelopment Analysis (DEA) model, we use financial data of the companies that are readily available on the Internet. Secondly, we visualize the efficiency scores of the companies in relation to the subsectors and the number of employees. These visualizations enable us to discover interesting insights about the companies within each subsector, and about subsectors in comparison to each other. The visualization approach that we employ can be used in any DEA study that contains subgroups within a group. Thus, our paper also contains a methodological contribution

The Effect of Scale on Productivity of Turkish Banks in the Post-Crises Period: An Application of Data Envelopment Analysis

The purpose of this paper is to investigate the productivity of Turkish Banks according to the effect of scale in the Post-Crises Period. The data used in this study covers the period from 2002:1 to 2004:3. We applied Data Envelopment Analysis (DEA), which is a non-parametric linear programming-based technique for measuring relative performance of decision-making units (DMUs). We calculated DEA as constant & variable return-to-scale based on output oriented Malmquist Index. Although the scale effect can be measured with DEA scale efficiency measurement, we used scale indicators as input variables in order to find out not only scale efficiency but also scale affect directly. We applied DEA by using financial ratios (Athanassopoulos and Ballantine, 1995; Yeh, 1996) and branch & personel number indicators. This study uses five input variables as i) branch numbers, ii) personnel number per branch, iii) share in total assets, iv) share in total loans, v) share in total deposits; and five output variables as i) net profit-losses/total assets (ROA), ii) net profit-losses/total shareholders equity (ROE), iii) net interest income/total assets, iv) net interest income/ total operating income, and v) noninterest income/total assets. We find that difference in efficiency is mainly from technical efficiency rather than scale efficiency in the post-crises period. The other finding reveals that efficiency approximate between selected banks and supporting that advantage of scale economies can be lost in Turkish banking. Overall, the results confirm that Turkish banking has U shaped Scale Efficiency on selected profitability ratios. The application of this paper based on other financial ratios with decreasing and increasing return-to-scale DEA is left to future research.Turkish Banks; Return to Scale; Scale Efficiency; Profit Efficiency; Data Envelopment Analysis

Explaining bank failures: deposit insurance, regulation, and efficiency

This paper uses micro-level historical data to examine the causes of bank failure. For state charactered Kansas banks during 19 10-28, time-to-failure is explicitly modeled using a proportional hazards framework. In addition to standard financial ratios, this study includes membership in the voluntary state deposit insurance system and measures of technical efficiency to explain bank failure. The results indicate that deposit insurance system membership increased theprobability of failure and banks which were technically inefficient were more likely to fail than technically efficient banks.Bank failures

Efficiency of Economic Regions in Finland 1988-1999: Application of the DEA method

The economic efficiency of the private sector in the 83 Finnish labour market areas is investigated by using the Data Envelopment Analysis method. This method is often used for assessing efficiency in public service production, but it can also be applied to regional economies. Compared with ordinary production function analysis, one of its advantages is the possibility to handle several output variables at the same time. For the study, private sector capital stock was first estimated. Other inputs included the number of employed by education level, years of schooling of the population and the local volume of public sector activity. As outputs, regional value added and personal real income were used. The study period 1988-1999 is interesting, because it includes years of rapid growth (1988-1990), falling into a deep recession (1990-94) as well as a time of recovery (1994-1999).

Could Society’s willingness to reduce pesticide use be aligned with Farmers’ economic self-interest?

agricultural intensification (AI), agricultural extensification (AE), pesticide reduction, environmental performance, non parametric cost-functions

Demutualization, outsider ownership and stock exchange performance - empirical evidence

Academic contributions on the demutualization of stock exchanges so far have been predominantly devoted to social welfare issues, whereas there is scarce empirical literature referring to the impact of a governance change on the exchange itself. While there is consensus that the case for demutualization is predominantly driven by the need to improve the exchange's competitiveness in a changing business environment, it remains unclear how different governance regimes actually affect stock exchange performance. Some authors propose that a public listing is the best suited governance arrangement to improve an exchange's competitiveness. By employing a panel data set of 28 stock exchanges for the years 1999-2003 we seek to shed light on this topic by comparing the efficiency and productivity of exchanges with differing governance arrangements. For this purpose we calculate in a first step individual efficiency and productivity values via DEA. In a second step we regress the derived values against variables that - amongst others - map the institutional arrangement of the exchanges in order to determine efficiency and productivity differences between (1) mutuals (2) demutualized but customer-owned exchanges and (3) publicly listed and thus at least partly outsider-owned exchanges. We find evidence that demutualized exchanges exhibit higher technical efficiency than mutuals. However, they perform relatively poor as far as productivity growth is concerned. Furthermore, we find no evidence that publicly listed exchanges possess higher efficiency and productivity values than demutualized exchanges with a customer-dominated structure. We conclude that the merits of outside ownership lie possibly in other areas such as solving conflicts of interest between too heterogeneous members

Efficiency of French football clubs and its dynamics

In the paper we evaluate the efficiency of French football clubs (Ligue 1) from 2004 to 2007 using Data Envelopment Analysis (DEA) with « Assurance Region ». Then, we study the dynamics of clubs’ performances. Contrary to previous works on other championships, best teams in competition or most profitable clubs are not the most efficient units in our sample. High average scores show that French First League is efficient. The first source of inefficiency in the Ligue 1 is linked to size problems and over-investments. Despite an average club performance stable over the period, we exhibit a deterioration of conditions in which clubs operate.Ligue 1, efficiency scores, Data Envelopment Analysis (DEA), Malmquist index, over-investment