Semiparametric Stochastic Frontier Model Research Articles

Labor differentiation and cotton productivity in Burkina Faso

AbstractAgriculture is a very important sector in Africa's economic development, particularly in Burkina Faso, as it employs a large proportion of the population. Given the importance of labor in this sector, a good allocation of the different types of labor could help increase agricultural productivity in Burkina Faso. This research contributes to the literature by determining the specific contributions of each type of labor in enhancing cotton productivity. The sample of this research is 477 cotton farms, and a semiparametric stochastic frontier model has been used in the analysis. The results show that the proportion of wage labor has a nonlinear effect and contributes to improving cotton productivity when the number of educated people in the household increases. But family labor decreases cotton productivity when the number of educated people in the household increase. The comparison between the findings of the semiparametric and parametric frontier shows that technical efficiency is 72.44% when education is used as the channel through which production factors affect cotton productivity. However, this technical efficiency is 54.96% when production factors directly affect cotton productivity in the parametric frontier model. Promoting education in rural areas will help to increase the number of people educated and consequently improve cotton productivity.

Analyzing technical efficiency in Vietnamese seafood processing firms: A semi-parametric stochastic frontier approach

This research aims to estimate and analyze the technical efficiency of Vietnamese seafood processing firms by applying the semi-parametric stochastic frontier model and Tobit regression. The data used in this study is a panel sample of 170 Vietnamese seafood processing firms in the period from 2013 to 2018. It is collected from enterprise census data of the General Statistics Office of Vietnam and provincial competitiveness index data of the Vietnam Chamber of Commerce and Industry. The estimated results show that: The scores of technical efficiency of firms averaged 0.712 and there was a decline during the study period. There is still plenty of room for technical efficiency in firms; The gap in technical efficiency in firms is still large and there is a strong difference in efficiency between firm’s ownerships and firm sizes; Firms with export activities, large scale, foreign direct investment capital, and low equity restrictions will have a positive impact on technical efficiency; However, there is no evidence to show the impact of the firm’s age and firm located in industrial zones factors on the efficiency of firms. In addition, the institutional quality and business environment also have an impact on the performance of firms.

Measuring the long run technical efficiency of offshore wind farms

Offshore wind energy has emerged as an attractive alternative to conventional resources to meet the Paris agreement commitment. The present paper studies the long run capacity of offshore wind farms to transform kinetic energy into electricity. We start estimating the technical efficiency of twenty-six farms over a thirteen years interval using a fully parametric and a semiparametric stochastic frontier model. The latter allows the factors of production to impact non-linearly on the quantity of electricity produced, those reducing the possibility of committing a functional misspecification error. Our results suggest that fully parametric specifications fails to identify the non-linear effect of labour cost on volumes of electricity produced. Then, we regress the estimated technical efficiency over the farm age, while controlling for the technological change of the wind power industry, to single out the resilience of the technical efficiency to aging. According to our calculations, technical efficiency ranges from 83% to 98% and it does not decline with age. This result shades light on the capacity of offshore wind farms to be a long term solution of the energy transition.

Financial Performance Evaluation

We propose a different methodology to assess the financial performance of banks: Multiple Indicator, Multiple Cause (MIMIC) Variable model. We also consider other existing methodologies in the literature for estimation of bank performance. The result shows that the influence of funds in affecting the performance of banks, which have been considered a latent construct here, has been increasing over the years. The latent performance score of the public-sector banks is always higher than the private-sector banks. The same is obtained even if we use the semi-parametric stochastic frontier model: The public-sector (nationalised) banks perform better than the Indian private banks (domestic) in terms of advancing loans only. We justify the use of MIMIC model as an alternative by comparing rank correlation between the MIMIC and semi-parametric stochastic frontier model. Our results demonstrate that financial market development through deregulation creates a competitive and efficient banking sector. JEL Classification: C58, G21, G28

Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks

In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.

Efficient Semiparametric Estimation in a Stochastic Frontier Model

This paper considers the semiparametric stochastic frontier model with panel data which arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual firm-specific effects is considered unknown. We construct an efficient estimator of the slope parameters in the frontier function . We also give an estimator of the level of the frontier function and its asymptotic properties are investigated. Furthermore, we provide a predictor of the individual effects which can be directly translated to firm-specific technical inefficiencies. Finally, we illustrate our methods through a real data example.

Efficient Semiparametric Estimation in a Stochastic Frontier Model

This article considers the semiparametric stochastic frontier model with panel data that arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual firm-specific effects is considered to be unknown. We construct an efficient estimator of the slope parameters in the frontier function. We also give an estimator of the level of the frontier function and investigate its asymptotic properties. Furthermore, we provide a predictor of the individual effects that can be directly translated to firm-specific technical inefficiencies. Finally, we illustrate our methods through a real data example.