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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.

In the backdrop of an increase in market-based banking activities, this paper aims to study operational efficiency of Indian banking sector during 2009–2010 through 2017–2018 considering Capital Gain and Gain from Forex Market (as desirable outputs) and Slippage (as undesirable byproducts) simultaneously, along with Advances – a desirable output considered in the traditional banking performance assessment literature. This enables to have an assessment of performance (as captured by the measured efficiency scores) of Indian Banks following an alternative viewpoint about the banking activities. The authors also explain such efficiency scores in terms of bank-specific factors, banking industry competition scenario and interest rate channel.

Using data envelopment analysis (DEA) method, the authors estimate six alternatives but interlinked operational efficiency scores (TES) of the Indian domestic commercial banks. In the second stage, they explain such TES in terms of bank-specific factors, banking industry competition scenario and interest rate channel.

The authors observe that the private sector banks as a group outperform those under public ownership. Moreover, although the private sector banks could maintain somewhat consistency in their operational efficiency performance over the sample period, public sector banks clearly show a declining tendency. The second stage econometric estimation results show that the priority sector lending has a negative effect on efficiency. Interestingly, the authors get varying results for the relationship between maturity and efficiency score depending on banks’ strategies on stressed assets management. Furthermore, the analyses result that banks are not so efficient in managing relatively larger-volume loans. It is also observed that banks’ efficiency positively depends on the Credit-to-Deposit (CD) ratio. It is found that the overall operational efficiency of the banks to manage their credit risk portfolio improves with a reduction in the lending rate (LR). However, the interaction of lending activities and capital market shows that with the increase in LR, corporate borrowers may switch to capital market to explore for desired funds, which may induce the banking sector to investment in capital markets and create a positive market sentiment.

Literature, although scanty, is there dealing stressed assets of a bank as some undesirable byproducts of its operational and business activities. However, such literature mostly done within the traditional framework of banking business activities and modern market-based business activities are almost absent in the literature. The authors have done it in the present study.

Purpose: This study analyses how investments and specific financial factors affect the financial performance of businesses in Kosovo. Exploring the relationship between investments and financial performance and their impact on performance volatility, performance is assessed using return on assets (ROA) and return on equity (ROE) investments.

Methodology: Quantitative methods using secondary data from audited financial statements of Kosova manufacturing and commercial enterprises cover a 3-year period (2019–2021), involving 40 enterprises with 120 observations. Statistical tests such as descriptive statistics, correlation analysis, linear regression, Hausman–Taylor regression, fixed effects, random effects, and generalised estimating equations (GEE) model are applied. The study also utilises ARCH–GARCH analysis to assess the relationship between investments and performance volatility.

Findings: Investments positively impact the financial performance of Kosova businesses and significantly reduce performance volatility. Long-term liabilities, retained earnings, and short-term liabilities also play a role in reducing asset return volatility, while cash flow from financial activities increases it. Investments, cash flows from financial activities, long-term liabilities, short-term liabilities, retained earnings, and solvency affect equity return volatility.

Practical Implications: The study sheds light on how investments and financial factors influence the financial performance and volatility of Kosova businesses. Policymakers can use these insights to create policies that foster the development of commercial and manufacturing enterprises, given their importance in Kosovo’s economy.

Significance: This research provides valuable insights for business managers to enhance investment strategies and improve financial performance. Policymakers can rely on this academic study to enhance the economic environment and promote the growth of businesses in Kosovo.

The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

The purpose of this study is to assess the influence of institutional quality (IQ), fossil fuel efficiency, structural change and renewable energy (RE) consumption on carbon efficiency.

This research uses an econometric approach, more specifically the Autoregressive Distributed Lag model, to examine the relationship between structural change, RE consumption, IQ, fossil fuel efficiency and carbon efficiency in India from 1996 to 2019.

This study finds the positive contributions of variables like fossil fuel efficiency, technological advancement, structural transformation, IQ and increased RE consumption in fostering environmental development through enhanced carbon efficiency. Conversely, this study emphasises the negative contribution of trade openness on carbon efficiency. These findings provide concise insights into the dynamics of factors impacting carbon efficiency in India.

This study's exclusive focus on India limits the generalizability of findings. Future studies should include a broader range of variables impacting various nations' carbon efficiency. Furthermore, it is worth noting that this study examines renewable and fossil fuel efficiency aggregated. Future research endeavours could yield more specific policy insights by conducting analyses at a disaggregated level, considering individual energy sources such as wind, solar, coal and oil. Understanding how the efficiency of each energy source influences carbon efficiency could lead to more targeted and practical policy recommendations.

To the best of the authors’ knowledge, this study addresses a significant gap in the existing literature by being the first empirical investigation into the effects of IQ, fossil fuel efficiency, structural change and RE consumption on carbon efficiency. Unlike prior research, the authors consider a comprehensive IQ index, providing a more holistic perspective. The use of a comprehensive composite index for IQ, coupled with the focus on fossil fuel efficiency and structural change, distinguishes this study from previous research, contributing valuable insights into the intricate dynamics shaping India's path towards enhanced carbon efficiency, an area relatively underexplored in the existing literature.

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

Higher economic growth accompanied by rising energy demand poses severe challenges to the long-term environmental sustainability of E7 economies, including Brazil, China, India, Indonesia, Mexico, Russia and Turkey. Thus, this paper explores the influence of foreign direct investment (FDI) inflows on energy diversification for E7 economies.

The dataset is panel data for emerging seven (E7) economies, covering the period 1992–2017. The empirical investigation relies on econometric techniques: panel cointegration test and panel autoregressive distributed lag model.

The findings reveal that energy diversification and FDI inflows are cointegrated. In the long run, higher FDI inflows encourage energy diversification, but energy efficiency improvements discourage energy diversification. In the short run, the effects of FDI inflows on energy diversification vary across E7 economies, highlighting the role of country-specific factors in determining the short-run influence of FDI inflows on energy diversification.

The findings suggested that FDI policies should encourage the adoption of nonconventional energy resources to stimulate energy diversification in E7 economies. Besides, better coordination between energy diversification and energy efficiency policies is required in the long run for a successful transition towards low-carbon economy goals.

This study is a unique empirical exercise that uncovers a cointegrating relationship between energy diversification and FDI inflows for E7 economies. Moreover, the analysis provides homogenous long-run and heterogeneous (country-specific) short-run coefficient estimates for the effect of FDI inflows on energy diversification.

The paper aims to compare the efficiency of alternative municipal solid waste (MSW) management business models: a single provider against multiple providers.

In this paper the drivers of MSW management costs are analysed to test the impact of the scale and scope of MSW management services on the average cost. While the business-as-usual scenario foresees a single provider, the alternative scenario foresees multiple providers.

Based on the empirical data on municipal waste management costs, on average, the size and the average cost of the service are inversely related. This trend is supported using sub-sets defined by the quantity of waste managed. Multiple factors aid in explaining this result, and among others, due to scale and scope, factors such as transition costs increase with the number of players running different services.

The provision of public services of economic interest should favour the participation of more companies wherever possible to the extent that social surplus is produced. However, pursuing this principle to the detriment of efficient service delivery is not ideal. This paper demonstrated that a single-provider waste management business model is efficient under specific conditions, as in this article.

This paper presents an original research methodology for comparatively analysing waste management service efficiency in urban areas and provides adequate evidence using alternative measures of costs according to the phase of the waste management chain, the scale and ultimately the scope of MSW management services.

本學術論文擬比較另類的都市固體廢物管理模式的效率, 比較的對像是:單一服務提供者和多個提供服務者。

研究人員分析都市固體廢物管理成本和價格的動因, 以測試有關的管理服務之規模和範圍對平均成本的影響。若在一切照常的情況下, 我們會預見單一服務提供者, 唯在不尋常的情況下, 我們則會預見多個提供服務者。

根據都市廢物管理價格和成本上的實證數據, 平均而言, 服務的規模與其平均成本是成反比的。我們使用了以所處理之廢物量來界定的子集來支持這趨勢。多重因素會幫助解釋和說明這研究結果, 其中包括:因規模和範圍的關係, 諸如過度成本等的因素, 會按著提供各種不同服務的主要參與者的數目而增加。

在能達創造社會剩餘的前題下, 會帶來經濟效益之公共服務的提供, 應有利於在可行範圍內有更多公司的參與; 但如果實行這原則而因此有損於服務提供的效率的話, 則這是不理想的。本文展示了在特定的情況下, 單一服務提供者的廢物管理商業模式是高效率的, 本文已說明這些特定情況。

本文為以比較分析法去探討城市地區廢物管理服務的效率、提出了一個新穎的研究方法, 並根據廢物管理鏈的階段、都市固體廢物管理服務的規模、以及最終其範圍, 考慮了成本和價格的另類測量方法, 繼而提供充分的證據, 以支持這些測量方法。

Although India is seen as a key player in the global economy, it is still below its potential level of growth. In this age of globalism, integration with the global economy through trade and foreign investments fosters domestic growth. For India, although this integration has strengthened over the years, there are certain gaps that remain to be addressed. Though numerous studies in the literature have tried to find answers to these questions, an important aspect that has not been considered by these studies relates to India’s federal structure and the role of states in determining the aggregate economic outcome. As Foreign Direct Investment (FDI) inflows to India are concentrated in a few states, this paper aims to provide an assessment of the reasons behind this trend.

This paper aims to investigate the reasons behind the interstate differences with respect to FDI inflows in India. The analytical work undertaken for this paper is based on secondary data, collected and collated from various sources. The approach adopted for this paper includes a heat graph analysis to examine whether there is a clear pattern in terms of the state-specific factors for high FDI states versus the low FDI states. This data analysis is followed by an econometric estimation to gauge the impact of state-specific factors in determining the FDI inflows.

As per the secondary data–driven heat graph and econometric analysis, factors like industrial output, social sector expenditure, judicial quality, connectivity indicators, labor cost and availability of credit, act as differentiators between high and low FDI-receiving states. It then becomes imperative to bridge the gap between the two sets of states in terms of these specific factors. Implementation and success of policy interventions can only be derived at the state level and therefore needs more decentralized approach.

This paper tries to identify the reasons that are responsible for FDI inflows being concentrated in a few Indian states. This involves a comprehensive analysis of several variables to understand whether there is a clear pattern where high-FDI states are also in a better position with respect to these attributes. This effort to factor in the federal aspect of a macroeconomic indicator like FDI provides new dynamic to this area of work.