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This paper aims to evaluate the technical efficiency of the health-care systems in 21 selected middle-income countries during the period (2000–2017) and determine the source of inefficiency whether it is transient (short run) or persistent (long run).

The study uses the stochastic frontier analysis technique through employing the generalized true random effects model which overcomes the drawbacks of the previously introduced stochastic frontier models and allows for the separation between unobserved heterogeneity, persistent inefficiency and transient inefficiency.

Persistent efficiency is lower than the transient efficiency; hence, there are more efficiency gains that can be made by the selected countries by adopting long-term policies that aim at reforming the structure of the health-care system in the less efficient countries such as South Africa and Russia. The most efficient countries are Vietnam, Mexico and China which adopted a social health insurance that covers almost the whole population with the aim of increasing access to health-care services. Also, decentralization in health-care has assisted in adopting health-care policies that are suitable for both the rural and urban areas based on their specific conditions and health-care needs. A key success in the implementation of the adopted long-term policies by those countries is the continuous monitoring and evaluation of their outcomes and comparing them with the predefined targets and conducting any necessary modifications to ensure their movement in the right path to achieve their goals.

Although several studies have evaluated the technical efficiency both across and within countries using non-parametric (data envelopment analysis) and parametric (stochastic frontier analysis) approaches, to the best of the authors’ knowledge, this is the first attempt to evaluate the technical efficiency of selected middle-income countries during the period (2000–2017) using the generalized true random effects stochastic frontier analysis model.

Recent advances in stochastic frontier analysis (SFA) suggest two alternative approaches to account for unobserved heterogeneity and to distinguish between persistent and transient inefficiency. The first approach is the generalized true random effects (GTRE) model, and the second approach is an autoregressive inefficiency (ARI) model. This study compares them to highlight whether they capture similar inefficiency aspects.

Using recent methodological advances in SFA, the authors estimate the GTRE and the ARI models using a Monte Carlo experiment and two real datasets from two industries (banking and agriculture).

The authors find that the two models provide quite different results in terms of inefficiency persistence and overall inefficiency (combination of transient and persistent inefficiency), regardless of the dataset considered.

The study findings suggest that researchers should be careful when referring to these two models because they do not capture the same inefficiency aspects, even though they have the same conceptual basis. This work is a warning about the empirical aspects of the persistent and transient efficiency framework, in order to convey a consistent story to the reader on firms' performance.

Even though they are used in a large number of studies, the present paper contributes to the productivity and efficiency literature by providing the first comparison of the GTRE and the ARI models.

The purpose of this paper is to measure technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from actual inefficiency using comprehensive household-level panel data.

This paper estimates technical efficiency based on the true random-effects stochastic production frontier estimator with a Mundlak adjustment. By utilising comprehensive panel data with 4,694 observations from 39 districts of four major maize-producing regions in Ethiopia, the author measures technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from technical inefficiency. By using competing stochastic production frontier estimators, the author provides insights into the influence of farm heterogeneity on measuring farm efficiency and the subsequent impact on the ranking of farmers based on their efficiency scores.

The study results indicate that ignoring unobservable farmer heterogeneity leads to a downwards bias of technical efficiency estimates with a consequent effect on the ranking of farmers based on their efficiency scores. The mean technical efficiency score implied that about a 34% increase in maize productivity can be achieved with the current input use and technology in Ethiopia. The key determinants of the technical inefficiency of maize farmers are the age, gender and formal education level of the household head, household size, income, livestock ownership, and participation in off-farm activities.

While the findings of this study are critical for informing policy on improving agricultural production and productivity, a few important things are worth considering in terms of the generalisability of the findings. First, the study relied on secondary data, so only a snapshot of environmental factors was accounted for in the empirical estimations. Second, there could be other sources of unmeasured potential sources of heterogeneity caused by persistent technical inefficiency and endogeneity of inputs. Third, the study is limited to one country. Therefore, future research should extend the analysis to ensure the generalisability of the empirical findings regarding the extent to which unmeasured potential sources of heterogeneity caused by persistent technical inefficiency, endogeneity of inputs and other unobservable country-specific features – such as geographical differences.

This paper contributes to the literature on agricultural productivity and efficiency by providing new evidence on the influence of unobservable heterogeneity in a farm efficiency analysis. While agricultural production is characterised by heterogeneous production conditions, the influence of unobservable farm heterogeneity has generally been ignored in technical efficiency estimations, particularly in the context of smallholder farming. The value of this paper comes from disentailing producer-specific random heterogeneity from the actual inefficiency.

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 purpose of this paper is to investigate whether firm efficiency can explain the investment anomaly. The investment anomaly refers to the persistent negative relation between firm growth and future risk-adjusted returns. When firms grow by investing heavily, the market often takes the growth as positive news initially but will correct prices downward subsequently if the firms lack skills to materialize value from the investments.

The author conducts portfolio sorting and Fama–Macbeth regression analyses with three different measures of efficiency and four variables for firm investment: net stock issuance (NSI), total asset growth (dAA), fixed asset and inventory growth (IA) and net operating assets (NOA).

The author finds that the NSI, dAA and IA anomalies are concentrated in firms with low overall efficiency. In addition, there is strong evidence that manager-driven efficiency is closely related to the NSI anomaly and limited evidence that NOA efficiency plays a role in the NSI, IA and NOA anomalies.

The research contributes to the literature by employing advanced efficiency measures developed by Demerjian et al. (2012) to resolve extant asset pricing puzzles. Also, the findings offer important implications for corporate managers and investors by demonstrating the effect of firm investments and efficiency on future profitability of stocks.

The purpose of this paper is to seek ways to improve energy efficiency in the residential building sector of Nigeria. This is necessary so as to promote a wider scope of energy efficiency practice in order to reduce energy demand on the central power supply of the nation and as well-attain reasonable level of energy security.

However, the objective of the study is to propose a strategic plan (scheme) of energy efficiency practice for the housing sector of the Nigerian economy. To accomplish this task, a review of the main issues of energy efficiency; the current energy situation in Nigeria; and the challenges to implementing energy efficiency in the country was undertaken.

Finally, remedial measures to achieving energy efficiency in the Nigerian households were proffered by the provision of a “strategic scheme” to be accomplished by the government and the housing stakeholders.

It is evident that a strategic plan or framework must be put in place in order to overcome the challenges of energy efficiency in the residential building sector. And this framework is to adequately address the issues of design practice, the efficiency of appliances in use and the housing occupant behaviour.

The main goal is the attainment of energy-efficient households in Nigeria through the application of EE practice strategies.

The study highlights on the energy development level of the country. It has also identified the numerous barriers as well as the principal actors to achieving energy-efficient households in Nigeria. After all, the suggested “plan of action” as provided in the scheme is to serve as a benchmark and reference point to the government, the housing stakeholders as well as the housing occupant for the attainment of energy efficiency.

The purpose of this paper is to discuss the relevance and evolution of adaptive markets hypothesis (AMH) that has gained traction in the recent years, as it provides a dynamic perspective to the concept of informational efficiency.

This paper discusses several issues related to the concept of informationally efficient markets that have indicated efficient market hypothesis to be an incomplete portrayal of stock market behavior.

The authors find that a strict and perpetual adherence to informational efficiency is highly unlikely, and AMH provides a much more plausible description of the behavior of stock markets.

The authors provide a description of studies that examine the testable implications of AMH.

This paper aims to assess whether incubation affects the technical efficiency of innovative firms after entering the market. The study of efficiency allows firms to understand how well resources have been used in production processes. The research intends to contribute to the literature on the performance of incubated firms.

This study estimates the relative efficiency of innovative firms adopting a DEA-based two-stage semi-parametric method. Incubation, firm age and initial capital are used for explaining the relative performance of previously incubated firms compared to non-incubated ones over a six-year period of activity. This research focuses on Italian innovative firms using a large sample of companies.

Results show that incubators have a positive and significant effect on efficiency for firms that have been in the market for more than two years. Efficiency also improves with age and with the level of initial capital of the firm.

This analysis is limited to the quantitative dimension of inputs as reported in the balance sheets, without qualitative considerations.

Findings enhance firms' understanding of the role of incubators as neutral places to develop a business culture of efficiency. From an empirical standpoint, this study provides useful insights to start-uppers who intend to attend incubation programs. Overall, incubators matter to the extent that they enable new firms, net of those that fail to survive in the first two years of activity, to improve their efficiency in the use of inputs. This research also suggests incubators consider the start-ups’ potential of being efficient.

Findings provide tips to policymakers when they are called upon to propose funding programs to support prominent firms entering the business scalability.

This study contributes to the literature on the relative performance of post-incubated firms, highlighting the efficiency frontier analysis. This methodological approach is relatively new in this field. It allows researchers to study the innovative firms' performance in relative terms, that is with respect to the input level. It integrates the performance-based with efficiency frontier analysis. Also, this study reinforces the idea that incubators prepare start-ups to develop capacities and managerial skills, which will be useful in post-incubation life to improve their cost competitiveness.

A number of studies have investigated the relationship between energy performance certificates (EPCs) and house prices. A majority of studies have tended to model energy performance pricing effects within a traditional hedonic conditional mean estimate model. There has been limited analysis that has accounted for the relationship between EPCs and the effects across the pricing distribution. Moreover, there has been limited research examining the “standard cost improvements EPC score”, or “potential score”. Therefore, this paper aims to quantify and measure the dynamic effects of EPCs on house prices across the price spectrum and account for standardised cost-effective retrofit improvements.

Existing EPC studies produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price effect. The approach within this study applies a quantile regression approach to empirically estimate how quantiles of house prices respond differently to unitary changes in the proximal effects of EPCs and structural property characteristics across the conditional distribution of house prices. Using a data set of 1,476 achieved transaction prices, the quantile regression models apply both assessed EPC score and bands and further examine the potential EPC rating for improved energy performance based on an average energy cost improvement.

The findings show that EPCs are valued differently across the quantiles and that conditional quantiles are asymmetrical. Only property prices in the upper quantiles of the price distribution show significant capitalisation effects with energy performance, and only properties with higher EPC scores display positive significant effects at the higher end of the price distribution. There are also brown discount effects evident for lower-rated properties within F- and G-rated EPC properties at the higher end of the pricing distribution. Moreover, the potential energy efficiency rating (score) also shows increased effects with sales prices and appears to minimise any brown discount effects. The findings imply that energy performance is a complex feature that is not easily “averaged” for valuation effect purposes.

While numerous studies have investigated the pricing effects of EPCs, they have tended to provide a single estimate to determine the relationship with price. This paper extends the traditional analytical insights beyond the conditional mean estimate by examining the quantiles of the relationship between EPCs and house prices to enhance the understanding of this esoteric and complex issue. In addition, this research applies the assessed energy efficiency potential to establish whether effective cost improvements enhance the relationship with sales price and capitalisation effects.

Advancements in digital technologies have provided significant opportunities to improve the Architecture, Engineering, Construction and Owner-operated (AECO) sector’s performance through superior data management, streamlined processes and cooperative working practices. However, whilst academic literature widely espouses these benefits during the design and construction phases of development, research suggests that the operational phase of a building’s lifecycle has yet to fully realise performance improvements available through the application of digital modelling technology. The purpose of this paper is to synthesise extant digital modelling, asset management and emergent digital asset management literature, to report upon the beneficial implications of digitalised asset management and identify obstacles hampering its adoption in industry.

A componential synthesis of future work reported upon in extant literature is organised into thematic categories that indicate potential research avenues and a trajectory for digital asset management research and practice.

Themes identified include: imprecise Building Information Modelling definitions; isolated software development; data interoperability; intellectual property and virtual property rights; and skills and training requirements. Notably, increased environmental performance also arose as a theme requiring further research but received considerably less academic coverage than the other obstacles identified.

The work presents a comprehensive review of digital technologies utilised within the AECO sector and as such provides utility to researchers, policy makers and practitioners to enhance their knowledge capabilities.