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The purpose of this paper is to provide new empirical evidence on the impact of credit risk on China banks' total factor productivity.

The paper employs the Malmquist Productivity Index (MPI) which allows for the examination of five different indices: total factor productivity change (TFPCH); technological change (TECHCH); efficiency change (EFFCH); pure technical efficiency change (PEFFCH); and scale efficiency change (SECH) indices.

The empirical findings indicate that the State Owned Commercial Banks (SOCB), Joint Stock Commercial Banks (JSCB), and City Commercial Banks (CCB) have exhibited lower TFPCH levels with the inclusion of risk factor. It was found that the JSCB and CCB have exhibited lower TFPCH due to TECHCH, while the SOCB have exhibited lower TFPCH due to EFFCH. The empirical findings suggest that the inclusion of credit risk factor has resulted in a higher JSCB EFFCH levels. On the other hand, the SOCB and CCB have exhibited a lower EFFCH levels due to SECH and PEFFCH, respectively.

The results clearly highlight the importance of credit risk and lending quality in determining the total factor productivity change of banks operating in the China banking sector. The author demonstrates that the inclusion of credit risk factor has resulted in a lower TFPCH level of all banks operating in the China banking sector. Thus, excluding the credit risk factor from the analysis on the China banking sector may potentially bias the result upwards.

In an environment of heavy government influence over the lending process, a large proportion of loans extended by Chinese banks over the years have gone bad. Policymakers should prevent the flow of new non‐performing loans by separating bad clients from banks that are being restructured and recapitalized in the reform of the banking sector.

By employing the Malmquist Productivity Index (MPI), the present paper contributes to the existing literature by examining, for the first time, the impact of credit risk on China banks' total factor productivity. To the best of the author's knowledge, this type of analysis is completely missing from the literature in regard to the China banking sector.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

The purpose of this paper is to measure the Malmquist Productivity Index and its different components such as technological change, technical efficiency change and the change in scale efficiency in the Indian food industry during the period spanning 1988‐1989 to 2004‐2005. Further, it examines the variation in productivity and its components with respect to the factors internal to the firms.

The technique of data envelopment analysis has been used to measure productivity index and its different components under the assumption of variable returns to scale. Further, log‐linear regression model has been used to explain the variation in productivity and its components with respect to certain factors internal to the firms.

In spite of a strong agricultural base and being the third largest producer of food products in the world, India's food processing industry is far from tapping its full potential as a result of a low rate of technological progress/regress on the one hand and increasing inefficiencies of the firms on the other hand. It is necessary to encourage imports along with R&D to ensure faster technological progress in the Indian food industry. However, the technological possibilities depend on the mode of organization and various economic and institutional factors. Therefore, bold institutional changes are to be made side‐by‐side in order that inefficiency is substantially reduced.

The present study evaluates the contribution of technological change, technical efficiency change and scale efficiency change to total factor productivity growth in the Indian food processing industry by using the firm‐level data, collected from the Centre for Monitoring Indian Economy (CMIE). It further examines the impact of some common factors internal to the firms on their performance.

The nature and extent of productivity change of ten commercial banks in Malaysia is analysed over the period 2000‐2001. Utilising non‐parametric methodology, Data Envelopment Analysis (DEA) and Malmquist total factor productivity index (MPI), individual bank efficiency and productivity changes which took place within this period is estimated. The MPI calculated within the framework of DEA further decompose productivity growth into technical efficiency change and technological change. The results from this analysis indicate that total factor productivity increased in all eight banks except for EON, which remain the same while PBB, recorded a decrease in productivity. AFB recorded the highest growth in total factor productivity. The growth in productivity is attributed to technological change rather than technical efficiency change.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

This research identifies the level of misallocation in Vietnamese manufacturing sector for the period 2000–2015. Meltiz and Polanec dynamic productivity decomposition is used to compare the relative productivity contributions from surviving, entering and exiting firms to aggregate productivity change by the type of ownership. Heckman's two-step model is used to examine the effect of misallocation and industry- and firm-level factors on entry or exit decision and market share of firms in Vietnamese manufacturing sector.

The level of misallocation and efficiency gains in total factor productivity (TFP) are assessed using Hsieh and Klenow (2009) productivity decomposition framework for the period 2000–2015. The dynamic productivity decomposition of Meltiz and Polanec (2015) is used to compare the relative contributions from surviving, entering and exiting firms to aggregate productivity change. The effects of misallocation and other factors on entry or exit decisions and market share of firms are determined by using Heckman choice model.

The results indicate three main points. Firstly, resource misallocation is found to be highest among state-owned enterprise (SOEs) and low technology industries. TFP is found to 81.2% greater if there is no resource misallocation among firms. Secondly, the aggregate productivity change for the entering, exiting and surviving firms is 35% due to productivity reallocation among three groups. Finally, the decision of entry or exit as well as the market share of firms are influenced by misallocation and industry- and firm-level factors such as Vietnam's WTO entry, tax policy, financial frictions, industrial concentration, technology gap, capital intensity, human capital, scale of firm, time entry and FDI spillovers. The result finds the higher misallocation level is, the lower the probability and market share for a new firm to enter in the industry is.

The main limitation of the study is that the market is assumed perfectly competitive and the method has only decomposed misallocation of resources to those arising from output and capital distortions. The results of Heckman choice model only clarify on the sub-sample of state-owned enterprises and low technology firms.

The focus of many previous research papers on resource misallocation was generally to look at the level of misallocation in developed countries. However, knowledge about the effect of misallocation and other factors on entry or exit decisions and market share of firms is limited, particularly in the context of developing countries. This paper clarifies the level of misallocation in Vietnamese manufacturing sector and the effect of misallocation and other factors on entry or exit decisions and market share of firms.

This study aims to undertake the evaluation and examination of the productivity change of the Egyptian banking sector. Using a novel data set covering 14 banks operating in the Egyptian market from 1997 to 2013. We use a nonparametric approach (based on data envelopment analysis (DEA)) to investigate the productivity change in the Egyptian banking sector. Input-oriented Malmquist indices of productivity change are estimated with DEA to measure total factor productivity (TFP) change. The TFP changes are decomposed into the product of technological change and technical efficiency change (catch-up). In the second stage, we study potential determinants of productivity change using a regression model. We find that the Egyptian banking sector as a whole shows a productivity regress of 0.9% per year, mainly due to the technological improvements. The estimated regression model identifies some variables that significantly influence the productivity of banks in Egypt. The banks with higher loan to deposit ratio and higher returns on equity have higher productivity growth reflecting on their strong strategic and managerial skills. The size of a bank seems to be associated with an increase in productivity. The maturity of a bank (measured by age) is associated with higher productivity. The NIM and NIETA variables do not seem to be affecting the productivity of banks. Surprisingly, our results reveal that the financial crisis was negatively and statistically insignificant, hence it had no effect on the Egyptian banks.

This paper aims to explore the level of productivity of Islamic banks specifically in selected Southeast Asian Countries from the period 2006 to 2014. Besides, this study also investigates the potential determinants of bank-specific characteristics and macroeconomic conditions that may influence the productivity of banking sector.

The present study gathers data on the 29 Islamic banks from Southeast Asian countries, namely, Brunei, Indonesia and Malaysia. The productivity level of the Islamic banks is evaluated using the data envelopment analysis-based Malmquist productivity index method. The authors then used a panel regression analysis framework based on the ordinary least square to identify potential determinants.

The domestic and foreign Islamic banks have exhibited progress in total factor productivity change solely attributed to the increase in efficiency change (EFFCH) which were mainly managerial rather than scale related. Foreign-owned banks have been slightly more productive compared to their domestic-owned bank counterparts, attributed to a higher EFFCH but insignificantly different. Furthermore, capitalisation, liquidity and world financial crisis determinants have significantly influenced productivity level of Islamic banks.

The study on the productivity of Islamic banking is still in its formative stage. To date, very limited study has been conducted to examine the productivity level in Southeast Asian, which is a strong regional hub for Islamic banking. This study intends to fill the gaps with a specific focus on the productivity level, specifically narrowing down to Southeast Asian countries in the domestic and foreign Islamic banking sector.

This study aims to investigate the productivity level of family takaful in Malaysia and Indonesia from 2014 to 2019. Productivity can support corporate sustainability, which is one of the company’s goals.

The measurement of the productivity level in this study involved applying the Malmquist Productivity Index (MPI) method. The input variables used consisted of equity, total expenses and total investment. The output variables consisted of total profit and investment income. In addition, this research used the orientation of the output and intermediation.

Throughout the study period, the Indonesian family takaful had an average total factor productivity change (TFPCH) of about 0.945. In other words, it did not reach optimal productivity. It is more due to the low value of technological change (TECHCH). On the contrary, family takaful companies in Malaysia had called productivity, showing a TFPCH of about 1.041. Again, this is mainly due to an increase in TECHCH and efficiency change, but it is still low in pure technical efficiency change.

This study focuses on factors that exist in internal takaful companies. Neither micro- nor macroeconomic variables that can affect productivity levels have been measured. In addition, this study only analyzed two countries out of the 11 countries in the Southeast Asian region.

Family takaful companies can use the productivity index as one of the bases of evaluation in managing their resources to enhance optimal output. Furthermore, the management of family takaful companies in Indonesia needs to focus more on technological innovation and delivery of services to increase productivity. Meanwhile, family takaful companies in Malaysia can maintain their technology usage and efficiency to operate productively. The government in both countries is expected to actively accelerate the growth of family takaful companies by producing regulatory products that strengthen the industry. Specifically, the government in Indonesia needs to make regulations that support technology improvement.

There is still not much research that examines family takaful’s productivity level using the MPI. The MPI is an appropriate tool to evaluate the productivity of family takaful companies. Thus, family takaful companies can improve their quality by assessing the productivity index value.