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Blood lipid and lipoprotein abnormalities are common among patients with diabetes. The study aimed to assess dietary fat intake and its association with blood lipids among patients with Type 2 diabetes mellitus (T2DM) considering sex differences.

A cross-sectional observational study was conducted with patients (207 males and 197 females) with T2DM. The daily food intake and its contents of fat and fat types were assessed through face-to-face interview. Anthropometric measurements, glycated hemoglobin (HbA1c), triglyceride, total cholesterol (TC), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol were initially recorded.

The results revealed that TC, LDL and HDL cholesterol levels were significantly higher in females than in males. However, the TC: HDL ratio was significantly higher in males than in females. The results also showed that the daily intake of saturated fatty acid (SFA) slightly exceeded the daily recommended allowance. However, the monounsaturated fatty acid + polyunsaturated fatty acid/SFA (MUFA + PUFA/SFA) ratio was within the recommended ratio. In addition, this study found that the main sources of SFA and cholesterol intake were milk and milk products. A significant association between high fat intake and HbA1c levels was observed (r = 0.234, p < 0.001).

As it is a cross-sectional observational study, this study has the natural limitation where it can only demonstrate an association.

The types of dietary fat intake may contribute to blood lipid abnormalities and differences effects may exist among male and female. Studies on the effect of daily fat intake and its types on blood lipids in patients with diabetes, in particular Saudi patients with diabetes are limited. This study focused on the amount and type of the consumed fat among male and female Saudi patients with T2DM and studied the relationship between the type of consumed fat and blood lipid profiles.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

The literature argues on ambiguous impacts of different types of the common agricultural policy (CAP) subsidies on farm technical efficiency (TE). The purpose of this paper is to estimate and analyse the TE and the impact of the CAP subsidies on the TE of wine farms in Hungary using the farm accountancy data network data set in the period 2013–2019.

The authors use stochastic frontiers analysis (SFA) models to estimate the TE scores for the Hungarian wine farms with four wine farm-level inputs in terms of agricultural land, labour, capital and intermediate consumption. The TE scores are explained by the CAP subsidies and economic wine farm size. The different SFA models were applied with robustness tests to investigate the drivers of the TE values of wineries.

Like for Hungarian farms in general, the distribution of the wine farm structure is a dual with a greater number of smaller wine farms and a smaller number of bigger wine farms. The agricultural land, capital and intermediate consumption are significantly positively associated with the wine farm TE. With higher capital intensity wine farm TE increase. The results imply that the CAP subsidies decrease the TE of the Hungarian wine farms, whereas economic farm size increase.

To the best of the authors’ knowledge, this is one of the first specific efficiency studies on the wine sector in the Central and Eastern European region and the first one for Hungary to evaluate the TE at wine farm level and to assess the impact of CAP subsidies and economic farm size on wine farm (in)efficiency to apply production technologies and use farm resources. This study is among the first that applied the fixed-effects stochastic frontier model at the wine farm level to measure the drivers of the TE scores.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

Total factor productivity (TFP) change is an important driver of long-run economic growth in the construction sector. However, examining TFP alone is insufficient to identify the cause of TFP changes. Therefore, this paper employs the infrequently used Geometric Young Index (GYI) and stochastic frontier analysis (SFA) to measure and decompose the TFP Index (TFPI) at the firm-level from 2009 to 2018 based on Malaysian construction firms' data.

To improve the TFPI estimation, normally unobserved environmental variables were included in the GYI-TFPI model. These are the physical operation of the firm (inland versus marine operation) and regional locality (West Malaysia versus East Malaysia). Consequently, the complete components of TFPI (i.e. technological, environmental, managerial, and statistical noise) can be accurately decomposed.

The results reveal that TFP change is affected by technological stagnation and improvements in technical efficiency but a decline in scale-mix efficiency. Moreover, the effect of environmental efficiency on TFP is most profound. In this case, being a marine construction firm and operating in East Malaysia can reduce TFPI by up to 38%. The result, therefore, indicates the need for progressive policies to improve long-term productivity.

Monitoring and evaluating productivity change allows an informed decision to be made by managers/policy makers to improve firms' competitiveness. Incentives and policies to improve innovation, competition, training, removing unnecessary taxes and regulation on outputs (inputs) could enhance the technological, technical and scale-mix of resources. Furthermore, improving public infrastructure, particularly in East Malaysia could improve regionality locality in relation to the environmental index.

This study contributes to knowledge by demonstrating how TFP components can be completely modelled using an aggregator index with good axiomatic properties and SFA. In addition, this paper is the first to apply and include the GYI and environmental variables in modelling construction productivity, which is of crucial importance in formulating appropriate policies.

This study aims to analyse the efficiency effects of institutional distance on Chinese outward foreign direct investment (FDI) in Africa.

The study utilised the true fixed-effect stochastic frontier analysis (SFA) model. Data from 2003 to 2016 (14 years) were acquired from 42 targeted African countries, which are included in the analysis.

The results reveal that FDI flow efficiency can be maximised with a high institutional distance between China and African countries. Contrariwise, comparable institutional distance, measured by the rule of law, regulatory quality and government effectiveness between the host and home countries, reflected a significant positive impact for Chinese outward foreign direct investment (OFDIs), indicating Chinese MNEs can invest directly in a country with comparable institutional characteristics.

There have been limited exceptional studies that assessed the effect of institutional distance between emerging countries. However, none of these studies investigated the effect of institutional distance between China and Africa at a national level. Using the advantage of the SFA model, this study assesses the efficiency effects of institutional distance between the host and home country.

This study aims to investigate the influence of the financial system (financial development and financial structure) on firms' innovation efficiency in China.

This study employs country level data of capital markets and financial institutions along with innovation data from 18 high-tech industries in China spanning the 2009–2016 period, and the stochastic frontier analysis (SFA) is applied to explore how financial development and financial structure affect the innovation efficiency of these industries.

Results show that financial development influences firms' innovation efficiency positively and the capital-market-based financial structure has a positive impact on innovation efficiency of high-tech industries. Furthermore, when the high-tech industries are grouped into five sub-industries, the results show that financial structure had different effects on the innovation efficiency in each sub-industry.

This work contributes to the empirical research on considering the influential factors of innovation efficiency from the perspective of financial system. This paper also extends the existing literature by the different influences of financial system on innovation efficiency in each sub-industry of Chinese high-tech industries.

African countries are endowed with both human and natural resources. These resources constitute integral components for any economic development due to the long-lasting relationship with all sectors in an economy, yet there is an obvious disagreement between growing economy and employment generation in Africa. Though there has been a growing pattern of economic size, particularly the gross domestic product (GDP) among African countries, most of these economies are low in human development. The disagreement between economic growth and employment generation in Africa despite abundant natural resources located on the continent calls for public discourse among scholars. Therefore, the purpose of the study is to examine the peculiar drivers of unemployment intensity in a region characterized by endowed resources.

The paper adopts two approaches; the authors employed the pooled mean group (PMG) estimator and utilised stochastic frontier analysis (SFA) to generate a government efficiency index between the period 1991 and 2017 among sub-Saharan Africa (SSA) countries.

The empirical results through the single output-multiple inputs framework indicate that on average, there is a low level of government efficiency towards increasing the objective of human development in Africa. However, in the long run, natural resource endowment has a positive and significant relationship with employment generation for SSA. Hence, the study established that a low level of government efficiency has a long-lasting effect on low human development experienced in Africa.

The need to improve the level of government efficiency towards economic development by making both human and physical capital more effective will spur the exploration of natural resources.

The paper provides an empirical study of the effectiveness and efficiency of government through PMG and SFA in establishing the relationship between government approaches and employment level in selected SSA countries.

This paper aims to study the underpricing phenomenon of initial public offerings (IPOs) of 355 Indian companies issued from 2007 to 2019. The research question this paper empirically examines is whether Indian corporate executives deliberately underprice IPOs from its fair value to attract investors, thereby causing an abnormal spike in the prices on the listing day. The findings of this study challenge a commonly held notion of leaving money on the table by IPO issuing companies. Of the overall average listing day returns of 17%, the deliberate premarket underpricing component is found to be mere 5.3%, while the remaining price fluctuation is, inter alia, a result of market momentum along with the unmet demands of impatient investors.

Following Koop and Li (2001), this study uses Stochastic frontier model (SFM) to study a routine anomaly of disparity between the primary market price (i.e. IPO issue price) and the secondary market price (listing price). The jump in the issue price observed on a listing day is decomposed into deliberate premarket underpricing component that reflects the extent of managerial manipulation and the after-market misvaluation component attributable to information asymmetry and prevailing market volatility.

This paper uses SFM to bifurcate initial returns into deliberate underpricing by managers and after-market mispricing by noise traders. This study finds that a significant part of the initial return is explained through after-market mispricing. This study finds that average initial returns are 17%, deliberate premarket underpricing is 5.3% and after-market mispricing averages 11.9%.

This study can isolate underpricing done at the premarket by estimating a systematic one-sided error term that measures the maximum predicted issue price deviation from the offered price. Consequentially, the disaggregation of initial returns may be especially informative for retail investors in planning their exit strategy from an IPO by separating the strength of the firm's fundamentals and its causal relationship with the initial returns. Substantial proportion of after-market mispricing implies that future research should focus on factors causing after-market mispricing. As underlying causes are identified, tailor-made policy responses can be formulated to benefit investors.

This paper has empirically validated that initial return is a mix of both components, i.e. deliberate underpricing and aftermarket mispricing. This disaggregation of initial returns can prove helpful for investors in planning their exit strategy. This study can help investors to become more aware of the importance of the fundamentals of the firm and its causal relation with the initial returns. This information in turn can help reduce the information asymmetry amongst investors and help them lessen the costs of adverse selection.

A large number of research studies on IPO pricing find overwhelming evidence of underpricing in public issues. This research attempts to decompose the extent of underpricing into deliberate underpricing and after-market mispricing, thereby supplementing the existing literature on the IPO pricing puzzle. To the best of the authors’ knowledge, this study is the first contribution to the literature on initial return decomposition for the Indian capital markets.

This study examines the impact of agricultural credit on rice farmers' technical efficiency (TE) in Côte d'Ivoire by considering the heterogeneity among credit sources.

A multistage sampling technique was used to collect data from 588 randomly sampled rice farmers in seven rice areas of the country. The authors use the endogenous stochastic frontier production (ESFP) model to account for the endogeneity of access to agricultural credit.

On the one hand, agricultural credit has a significant and positive impact on rice farmers' TE. Rice farmers receiving agricultural credit have an average of 5% increase in their TE, confirming the positive impact of agricultural credit on TE. On the other hand, the study provides evidence that the impact of credit on rice production efficiency differs depending on the source of credit. Borrowing from agricultural cooperatives and paddy rice buyers/processors positively and significantly influences the TE, while borrowing from microfinance institutions (MFIs) negatively and significantly influences the TE. Moreover, borrowing from relatives/friends does not significantly influence TE.

Future research can further explore the contribution of agricultural credit by including several agricultural productions and using panel data.

The study provides evidence that the impact of agricultural credit on agricultural production efficiency depends on the source of credit. This study contributes to the literature on the impact of agricultural credit and enlightens policymakers in the design of agricultural credit models in developing countries, particularly Côte d'Ivoire.