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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 study estimates total factor productivity growth (TFPG) and its components of the 4-digit manufacturing industries of chemical and chemical products in India from 1998–1999 to 2017–2018, pre-economic crises period (from 1998–1999 to 2007–2008) and post-economic crises period (from 2008–2009 to 2017–2018) using frontier approaches, that is, data envelope analysis DEA and stochastic frontier approach (SFA). The components of TFPG are technological progress (TP), technical efficiency change (TEC) and economic scale change (SC). It is found that the growth rates of total factor productivity (TFP) in most of the 4-digit industries of chemical and chemical products in India increased during the post-economic crises period (from 2008–2009 to 2017–2018) and the increase in TFPG of them during that period is mainly accounted for by the increase in TP of the same during that period. The TEC of almost all the industries remains the same, however, declined during the post-economic crises (from 2008–2009 to 2017–2018) and SC of them remains very low or even negative during the aforementioned study periods.

The fact that Mexican immigrants are healthier than their US-born co-ethnics has been well established. The subsequent observation that this health advantage diminishes over time and with increased acculturation is confirmed by only limited research and is severely compromised by several methodological shortcomings. Our analysis directly tests the acculturation hypothesis by investigating childhood health at an early age; specifically, we explore the relationships between birth-weight, primary language spoken, maternal nativity, and stature for age (SFA) among a sample of respondents to the NHANES III Youth survey data. Results indicate that a substantially large portion of the health advantages transferred from mother to child among the Mexican-born are due to birth-weight advantages. After controlling for health advantages conferred at birth among the foreign-born, language differences fully account for nativity differences between Mexican- and US-born mothers, suggesting an additional protective effect of Spanish-language maintenance and lending evidence to the hypothesis that language-based acculturation erodes health among Mexican Americans.

This chapter draws from Structuration theory (Giddens, 1979, 1984) and Schema theory (Niesser, U. (1967). Cognitive psychology. New York, NY: Appleton-Crofts.) to examine how words reflect changing frames of reference (Orlikowski & Gash, 1994) that affect adaptation to strategic technological change. The method of recursive dialogue analysis we use provides evidence of how expectations about a new technology introduced to a sales force changed over time. Individuals had expectations based on past experiences, made initial decisions about using the new technology, juxtaposed new concepts against previous ones, interacted with team-mates, and built further concepts around previously expressed phrases. The results we exhibit here allow us to visualize complex interactions under conditions of uncertainty, contributing a detailed view of the recursive and cognitive process of developing a frame of reference about technology in an organization.

There were 4,919 registered, short-term, community hospitals in the 2004 American Hospital Association (AHA) Annual Survey of Hospitals; 60 percent of those hospitals were non-profit (NP), 23 percent of them were public (non-federal government owned and operated), and 17 percent were for-profit (FP). In general, while the absolute number of hospitals in the United States has decreased in recent years, the share of hospitals that are FP has increased. For example, in 1997, the AHA reported 5,057 registered, short-term, community hospitals, of which 59 percent were NP, 25 percent were public, and 16 percent were FP.

We present empirical evidence on the productive efficiency of electric utilities in the United States from 1990 to 2004. This period is marked by major attempts to introduce deregulation with an expectation that it will lead to improved operating efficiency and ultimately to lower consumer prices. However, relying on improved techniques of estimating productive efficiency, we find that firms in jurisdictions that adopted deregulation have in fact lower productive efficiency, and have also experienced decreases in efficiency over time. In particular, the vertical separation of generation, a hallmark of an effort to deregulate the industry, is associated with an adverse impact on productive efficiency.

This study aims to empirically verify that gender equality, one of the indicators of equitable development in countries, has a positive effect on reducing CO₂ emissions per capita in emerging markets economies. It also aims to determine and rank the countries that are inefficient in terms of CO₂ emissions per capita (metric tons). For this purpose, the panel data stochastic frontier model is estimated. The Global Gender Gap Index, which measures gender equality, primary energy consumption per capita (gigajoule), and GDP per capita (constant 2010 US$) are used as independent variables of 24 countries from 2006 to 2018. The authors test the negative impact of gender equity on CO₂ emissions. The results of the model support this hypothesis. This study indicates that gender equity can be suggested both as a driving force for economic development and sustainable environmental efficiency in which growth can be linked to lower emissions of CO₂.

Purpose – The purpose of this paper is to examine the relationship between banking sector efficiency and economic growth in Africa.

Methodology/approach – The paper used the stochastic frontier approach stating the banking sector cost function as a Fourier flexible to estimate bank efficiency. We then used the Arellano–Bond GMM estimator to investigate the relationship between banking sector efficiency and economic growth. Annual data for banking sector financial statements were used in estimating efficiency scores.

Findings – The study found banking sector efficiency in the sample to be 69%. We also found a positive relationship between banking sector efficiency and economic growth, confirming the critical role banks play in the economy.

Practical implications – Banking sector efficiency score of 69% implies banks in Africa could save up to 31% of their total cost if they were to operate efficiently. Policy direction should therefore focus on policies and incentives that will improve the efficiency of the banking sector and hence economic growth. The study brings to the fore the importance of the qualitative aspect of the banking sector in allocating financial resources in the real economy. Focus in the real economy should not be only on the size of the banking system but also on the quality with which resources are allocated.

Originality/value of paper – This study is among the first dedicated solely to African countries. It does set the pace for future research in the area and also confirms in Africa the Schumpeterian hypothesis that the banking sector is key in allocating resources in the real economy.

This chapter proposes a new technique based on the data envelopment analysis (DEA) method to evaluate the scale efficiency with considering the environmental influences. Using this method, we can get the pure scale efficiency which has eliminated the environmental factors and random errors that might influence the production process. Our approach extends the three-stage-DEA model by Fried, Lovell, Schmidt, and Yaisawarng (2002) to the five-stage DEA model. Afterward, in order to measure the scale efficiency of the China’s universities more accurately, this chapter gives an empirical study on the scale efficiency of the top universities in China by applying the five-stage DEA model. The results show that the efficiency levels of many universities are indeed affected by external environmental variables and random factors. According to the levels of pure technical efficiency and scale efficiency, we divide China’s universities into four types, and we also propose some suggestions for the inefficient universities to improve their scale efficiency.

John Antonakis: To SFA, AFA, AFA, BFA, MFA, RFA and the unnamed bunnies.