Highlighting the Drivers of Italian Diversified Farms Efficiency: A Two-Stage DEA-Panel Tobit Analysis

Farm diversification is an important phenomenon in agricultural systems and rural development in Europe, pursuing economic, social and environmental goals. For the sustainability of diversified farms, it is important to analyse some drivers affecting farm efficiency, for instance, socio-economic, technical and policy drivers. The efficiency performance of a panel of Italian farms practising other gainful activities in the period 2012–2017 was investigated and regressed against the drivers that mostly affects farm performances. FADN data and a two-step approach were used. An output-oriented Data Envelopment Analysis was applied; in the second step, efficiency scores were used as a dependent variable in a panel Tobit regression analysis used to determine differences in the significance of drivers. Social, economic, technical and policy drivers were considered as explanatory variables. Results show margins for improving farms performances. The incidence of the output from other gainful activities has been proven to positively affect farms efficiencies, while intermediate costs are the most negatively impacting factor. As regards policy variables and implications, the significance of localization in mountain disadvantaged territories further supports the relevance of EU subsidies in less-favoured areas. Managerial implications in terms of technical, structural and economic indicators can be drawn from study findings.

Appraising healthcare systems’ efficiency in facing COVID-19 through data envelopment analysis

The healthcare system is a vital element for any community, as it extremely affects the socio-economic development of any country. The current study aims to assess the performance of the healthcare systems of the countries above fifty million citizens in facing the spread of the COVID-19 pandemic since late December 2019. For this purpose, seven scenarios were adopted via the DEA methodology with six variables, which are the number of medical practitioners (doctors and nurses), hospital beds, Conducted Covid-19 tests, affected cases, recovered cases, and death cases. To shed light on the relative efficiency of drivers, the Tobit analysis was used. Besides, the study carried out various statistical tests for the DEA models' findings to validate the choice of the variables and the obtained scores. The DEA results reveal that less than half of the considered countries are relatively efficient. Moreover, the Tobit regression analysis showed that the main impact on the efficiency scores was due to the number of affected and recovered cases. Finally, the results of the tests of Spearman, Mann-Whitney U, and Kruskal-Wallis H indicate the internal validity and robustness of the chosen DEA models. The current study findings raise important implications, which can be helpful for decision makers regarding continuous improvement of performance, in which the findings assert the importance of achieving the best practices regarding relative efficiency through the linkage between the healthcare systems’ resources, and the needed outputs.

Research on financing efficiency of China's strategic emerging industries based on super efficiency DEA and tobit model

PurposeThe purpose of this research is to explain the financing dilemma of China's strategic emerging industries and improve their financing efficiency, seize the commanding heights of economic science and technology to provide theoretical support.Design/methodology/approachThis paper selects the companies listed under strategic emerging industry during the period of 2010–2017 as the research object and used the data envelopment analysis method (DEA) to evaluate the financing efficiency of China's strategic emerging industries and selects the tobit analysis method to find out the factors affecting its financing efficiency.FindingsThe results show that the average financing efficiency of listed companies in strategic emerging industries between 2010 and 2017 is 0.7792, and the level of financing efficiency of strategic emerging industries is still at a low level. Among them, the bio-pharmaceutical industry and the energy-saving and environmental protection industry have the highest comprehensive level, and the high-end equipment manufacturing industry and the new energy industry have the lowest level of financing efficiency. Among the factors affecting the financing efficiency of strategic emerging industries, the asset-liability ratio, financial expenses and cash ratio and financing efficiency are negatively correlated, and the net asset income is positively correlated with the growth rate of the main business income.Originality/valueThis paper measures the financing efficiency of China's strategic emerging industries, then explores the influencing factors of the financing efficiency of strategic emerging industries and tries to provide important reference values for the improvement of the financing efficiency of China's strategic emerging industries at a practical level.

Sign-constrained linear regression for prediction of microbe concentration based on water quality datasets

This study presents a novel methodology for estimating the concentration of environmental pollutants in water, such as pathogens, based on environmental parameters. The scientific uniqueness of this study is the prevention of excess conformity in the model fitting by applying domain knowledge, which is the accumulated scientific knowledge regarding the correlations between response and explanatory variables. Sign constraints were used to express domain knowledge, and the effect of the sign constraints on the prediction performance using censored datasets was investigated. As a result, we confirmed that sign constraints made prediction more accurate compared to conventional sign-free approaches. The most remarkable technical contribution of this study is the finding that the sign constraints can be incorporated in the estimation of the correlation coefficient in Tobit analysis. We developed effective and numerically stable algorithms for fitting a model to datasets under the sign constraints. This novel algorithm is applicable to a wide variety of the prediction of pollutant contamination level, including the pathogen concentrations in water. This article has been made Open Access thanks to the generous support of a global network of libraries as part of the Knowledge Unlatched Select initiative.

Technical Efficiency Analysis of Terubok Fisheries in Malaysia

Terubok fish is an estuarine fish that is significant among local fishermen because of high commercial value and it also constitutes to source of income for Terubok fishermen during its catching season. Therefore, due to high commercial value, Terubok fish has been subject to overfished and the population has been declining throughout the years. This study is carried out to analyse the efficiency performance of Terubok fisheries in Malaysia. A sample of actively Terubok fishermen was selected through stratified random sampling and the field survey has conducted at three different places in Sarawak. Data Envelopment Analysis (DEA) and Tobit Analysis were employed to determine the technical efficiency level and factors influencing technical efficiency among Terubok fishermen. The results of the study show that, most fishing units exhibit a low level of technical efficiency. This implies that either fishing inputs were used inefficiently, or insufficient inputs were used in fishing operations. The mean technical efficiency of the sample was estimated to be 0.304 using CRS Model, 0.406 using VRS Model and Scale Efficiency is 0.805. The determinant factors of efficiency among Terubok fishermen was among all, hours in a day, days spent in fishing per month, engine horsepower and fisherman association show positive sign towards efficiency contradictorily other determinant such as age, education, distance and length of vessels possess negative sign towards efficiency. These findings suggest that there’s urgent need to the efficiency level of the fishermen as this will indicate the impact of their living standard. With appropriate training and using more advanced technologies by the fishermen, the level of technical efficiency can be raised, segmented for inshore fisheries.

Investment Expenditure Behavior of Remittance Receiving Households: An Analysis Using Reserve Bank of India Data

Although it is the world’s largest recipient of remittances, India lacks information about the investment behavior of its remittance receiving households. Using data from Reserve Bank of India and the Tobit analysis, this paper examines how remittances, different household and migrant characteristics have affected both the propensity to invest and the amount of investment by the remittance receiving households. The findings have significant implications for policy purposes. For example, government programs can create incentives for older migrants to have more remittance transfers. Remittance money used for children’s education could be matched to create robust flow of educational investments.