Directional scale elasticity considering the management preference of decision-makers

Most data envelopment analysis (DEA) studies on scale elasticity (SE) and returns to scale (RTS) of efficient units arise from the traditional definitions of them in economics, which is based on measuring radial changes in outputs caused by the simultaneous change in all inputs. In actual multiple inputs/outputs activities, the goals of expanding inputs are not only to obtain increases in outputs, but also to expect the proportions of such increases consistent with the management preference of decision-makers. However, the management preference is usually not radial changes in outputs. With the latter goal into consideration, this paper proposes the directional SE and RTS in a general formula for multi-output activities, and offers a DEA-based model for the formula of directional SE at any point on the DEA frontier, which is straightforward and requires no simplifying assumptions. Finally, the empirical part employs the data of 16 basic research institutions in Chinese Academy of Sciences (CAS) to illustrate the superiority of the proposed theories and methods.

HOW DO ADAPTATION OPTIONS TO CLIMATE CHANGE, RISK PREFERENCES AND SOCIAL CAPITAL AFFECT TECHNICAL EFFICIENCY OF SMALL VINEYARD FARMERS IN CENTRAL CHILE?

Climate change can be seen as a shock that decreases the value of economic activities and production functions. Therefore, this study estimates technical efficiency as an integrated approach with risk preferences and social capital for small vineyard farmers who have adapted to climate change, because empirical evidence shows the key role of adaptation, risk preferences and social capital related to technical efficiency on a one-to-one basis, but not as overarching analysis. This study took place in the O’Higgins and Maule regions of central Chile, data were collected through a field experiment and an exit survey from September to December 2016. Specifically, we conducted an artefactual field experiment to elicit risk preferences from 175 small vineyard farmers; we used the midpoint method to estimate the Cumulative Prospect Theory (CPT) parameters, which indicate vineyard farmers are risk averse, sensitive to losses, and tend to distort probabilities. Then we applied a stochastic frontier analysis on the main variety area of vineyards. Results showed that the influence of capital (0.55) and number of vines (0.32) is higher enough; whereas, labor (0.13) and intermediate inputs (0.11) are also important but relatively low. The scale elasticity is 1.11, showing a Constant Returns to Scale (CRS). On average, technical efficiency was 0.73, which means that farmers could improve their performance by 27%. Additionally, results suggest that experience and education positively influence the technical efficiency, contrary to age, gender, region and density; whereas, access to extension services and irrigation increases efficiency. Also, general trust and membership in farmer organizations increases efficiency; and, as we expected, risk aversion and probability weighting decreases efficiency. In this regard, it is necessary to design policies and strategies focused on facilitate accessibility to exchangeable inputs; in the promotion of extension services with greater action area; facilitate access to irrigation through subsidies and credits; improve trust in programs and networks; develop cooperative enterprises or local and horizontal organizations to share information and services from farmer to farmer; and also generate action plans to promote a better risk and loss behavior in order to seize technological and economic opportunities and not overestimate extreme events.

Scale elasticity in the presence of integer data: An application to electricity distribution companies

Returns to scale and scale elasticity are two important issues in the field of economics and operations research. Recently, estimating returns to scale and scale elasticity using tools such as data envelopment analysis (DEA) has attracted considerable attention among researchers. The existing approaches to calculate scale elasticity in DEA context, assume all inputs and outputs are real-valued and in this sense, the underlying technology is a continuous set. In many real cases, however, we face input/output measures that are restricted to be integer-valued. Scale properties of frontier points in such cases are interesting and important. In this paper, this problem in integer-valued DEA is studied. The Lagrangian dual formulation of a mixed integer linear programming problem is used to calculate the scale elasticity of a frontier point. To illustrate the real applicability of the theoretical framework, a real case on electricity distribution companies is given.

Scale elasticity in the presence of integer data: An application to electricity distribution companies

Returns to scale and scale elasticity are two important issues in the field of economics and operations research. Recently, estimating returns to scale and scale elasticity using tools such as data envelopment analysis (DEA) has attracted considerable attention among researchers. The existing approaches to calculate scale elasticity in DEA context, assume all inputs and outputs are real-valued and in this sense, the underlying technology is a continuous set. In many real cases, however, we face input/output measures that are restricted to be integer-valued. Scale properties of frontier points in such cases are interesting and important. In this paper, this problem in integer-valued DEA is studied. The Lagrangian dual formulation of a mixed integer linear programming problem is used to calculate the scale elasticity of a frontier point. To illustrate the real applicability of the theoretical framework, a real case on electricity distribution companies is given.

Social Welfare Analysis of China’s High-Speed Rail Industry: Based on the Perspective of Enterprises’ Entry in Upstream Market

Based on the analysis of the high-speed rail industry chain, first, this paper divides the high-speed rail industry chain into infrastructure construction market and manufacturing market of mobile equipment and, second, this paper uses the empirical method of new experience industry organization to measure the market power premium of the high-speed rail upstream market. The study shows that the market power premium of the high-speed rail upstream market is 0.551, and the scale elasticity is 0.314, indicating that there is no systematic market power in the high-speed rail upstream market and there is significant scale diseconomy. The vertical market structure where “private enterprises dominate the upstream competition market and state-owned enterprises dominate the downstream oligopoly market” is further established. Based on the perspective of enterprises’ entry in upstream markets, the social welfare of the high-speed rail industry market structure is analyzed. It is found in the study that the upstream market of the high-speed rail industry has a tendency of insufficient enterprise entry, and the total social welfare increases with the increase in the number of upstream enterprises entry. What is more, the profit of enterprises in the upstream market of high-speed rail decreases with the increase in the number of enterprises in the upstream. This paper believes that policies such as stimulating upstream high-speed rail enterprises entry, providing subsidies to upstream enterprises, reducing upstream enterprises’ entry barriers, and expanding international markets can effectively improve the overall social welfare of the high-speed railway industry.

Performance of Smallholder Soybean Farmers in Ghana; Evidence from Upper West Region of Ghana

The economic importance of soybean towards poverty alleviation and food security is gaining wider popularity and common acceptance among smallholder farmers in sub-Sahara Africa, especially in Ghana. Commercial soybean cultivation is relatively new in Ghana; hence it has recently benefited from several productivities enhancing innovation/technologies. However, despite these efforts, productivity has remained low. This paper investigates factors affecting production efficiency among commercial soybean farmers, across the three commercial districts of the Upper West region of Ghana. A cross-sectional data collected from 271 soybean farmers were used to investigate technical efficiency of soybean production. The overall mean technical efficiency estimate is 59% with a scale elasticity of 0.89-indicating a huge scope for efficiency improvement. The result shows that, factors affecting technical efficiency are dependent on the farmer’s socioeconomic status. With the existing technology and production recourses, soybean farmers can improve their current levels of soybean production by 41% through the adoption of best production practices.

Closed form of the response function in FDH technologies: Theory, computation and application

Response function (RF), which gives the value of maximum feasible outputs in response to changing the inputs, has a crucial role in performance analysis and scale elasticity measurement. In this paper, a polynomial-time algorithm is provided which is able to obtain the closed form of the RF under (nonconvex) FDH productions technologies. Finite convergence of the presented algorithm is proved; and it is established that the algorithm is polynomial-time from a complexity standpoint. Moreover, an application of the proposed procedure with real-world data accompanying some experiment-based computational discussions are given.

Scale and quality in Nordic hospitals

Empirical analysis of hospitals in production economics often find little or no evidence of scale economies and quite small optimal sizes. Medical literature on the other hand provides evidence of better results for hospitals with a large volume of similar procedures. Based on a sample of Nordic hospitals and patients, we have examined whether the inclusion of quality variables in the production models changes estimates of scale elasticity. A sample of 58 million patient records from 2008 and 2009 in 149 hospitals in Denmark, Finland, Norway and Sweden were collected. Patient data DRG-points were aggregated into 3 outputs (medical inpatients, surgical inpatients and outpatients) and linked to operating costs for 292 observations. The patient data were used to calculate quality indicators on emergency readmissions and mortality within 30 days, adjusted for age, gender, comorbidities, hospital transfers and DRG using DRG-specific logistic regressions.The hypothesis that the elasticity of scale increases when quality variables are included was tested against the null hypothesis of no change in the scale elasticity. The observations were used to estimate a cost function using Stochastic Frontier Analysis (SFA). Country dummies as well as dummies for University hospitals, capital city hospitals and the average travelling time for the patients were included as environmental variables. The estimated scale elasticities did not change with the inclusion of quality indicators in any of the tested models. This may be because medical volume effects are confined to few patient groups or possibly even offset by effects on other groups, where quality is reduced by volume. In one model, the scale elasticity was significantly larger than 1.0, a result that contradicts previous studies which have found decreasing returns. Published: Online October 2018. In print Janury 2019.