Efficiency and productivity gains of robotic surgery: The case of the English National Health Service

This paper examines the effect of new medical technology (robotic surgery) on efficiency gains and productivity changes for surgical treatment in patients with prostate cancer from the perspective of a public health sector organization. In particular, we consider three interrelated surgical technologies within the English National Health System: robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar clinical benefits. While the clinical benefits in adopting robotic surgery over laparoscopic intervention are unproven, it requires a high initial investment cost and carries high on-going maintenance costs. Using data from Hospital Episode Statistics for the period 2000-2018, we observe growing volumes of prostatectomies over time, mostly driven by an increase in robotic-assisted surgeries, and further analyze whether hospital providers that adopted a robot see improved measures of throughput. We then quantify changes in total factor and labor productivity arising from the use of this technology. We examine the impact of robotic adoption on efficiency gains employing a staggered difference-in-difference estimator and find evidence of a 50% reduction in length of stay (LoS), 49% decrease in post-LoS and 44% and 46% decrease in postoperative visits after 1 year and 2 years, respectively. Productivity analysis shows the growth in radical prostatectomy volume is sustained with a relatively stable number of urology surgeons. The robotic technique increases total production at the hospital level between 21% and 26%, coupled with a 29% improvement in labor productivity. These benefits lend some, but not overwhelming support for the large-scale hospital investments in such costly technology.

Do VIP medical services damage efficiency? New evidence of medical institutions' total factor productivity using Chinese panel data

This study examines the causal impact of very important person (VIP) medical services on hospital total factor productivity in Deyang, a prefectural-level city in western China, spanning the years 2015-2020. This aims to offer empirical evidence and policy recommendations for the implementation of VIP practices in the medical field. A secondary unbalanced panel dataset of 416 observations was collected from the annual reports of the Health Commission and 92 eligible medical institutions were included. This study utilized a two-stage strategy. First, the Global Malmquist index was used to calculate the total factor productivity and its decomposition terms for hospitals from 2015 to 2020. In the second stage, two-way fixed effects models and Tobit models were used to identify the relationship between VIP medical services and hospital efficiency; instrumental variables were used to solve potential endogeneity problems in the model. The results showed that VIP medical services had a significantly negative impact on medical institutions' efficiency. The technological advances and pure technical efficiency related to VIP medical care may help explain these negative impacts, which were heterogeneous across groups divided by the nature of the hospital and the outside environment. It is imperative to prioritize the standardized provision of VIP medical services for medical institutions, optimize management and service process, enhance the training of clinical and scientific research capabilities of medical personnel, and scientifically allocate resources for both VIP and general medical services. This will help mitigate health inequality while improving the overall quality of medical services.

How Does the Digital Economy Drive High-Quality Regional Development? New Evidence From China

The digital economy, which boasts general technology, intense penetration, platform ecology, and low marginal cost, is a product of advanced digital technology. This new engine has become a driving force for high-quality economic development. From the three aspects of development momentum, efficiency, and structure, this paper profoundly explores internal mechanisms to lead the high-quality growth of the regional economy. By constructing an econometric model, the influence effect and means of the digital economy on the high-quality development of the regional economy are empirically tested. The digital economy and its three sub-dimensions can significantly promote the high-quality development of the regional economy. However, industrial digitalization has the most vital role in promoting it. The digital economy has shown a more vital promotion role in the central and western regions and provinces with low total factor productivity, and it can indirectly impact high-quality economic development by promoting dynamic, efficient, and structural changes.

Evaluating the resource recovery efficiency of garbage removal and disposal in Taiwan

All countries recognize the importance of enhancing circular resource utilization and promoting zero waste in order to achieve a circular economy. This study focuses on 22 counties (cities) in Taiwan and analyses the relationship between changes in resource recovery efficiency and productivity over an 8-year period (2011-2018) using the super efficiency directional distance function and total factor productivity. The results indicate that the average total efficiency of resource recovery in the 22 counties (cities) is 1.3951, with 17 counties (cities) exceeding 1. The average gross productivity of resource recovery is 1.0417, and only four counties have a gross productivity of less than 1. Despite having more administrative resources, municipalities directly under the central government have a slightly lower average total efficiency of resource recovery (1.1464) than non-municipalities (1.4885). To improve efficiency, the government should allocate resources rationally and upgrade technology. The study's findings can serve as a reference for the 22 counties (cities) in Taiwan and provide guidance for municipal governments worldwide in developing policies related to resource recovery.

How does the air pollution prevention and control action plan affect sulfur dioxide intensity in China?

As a part of China's efforts to mitigate and control air pollution in key areas, the Air Pollution Prevention and Control Action Plan was implemented in 2013, and several regulatory measures were introduced. Based on the data from 271 prefecture-level cities between 2008 and 2018, the difference-in-differences model is used to explore the effect of it on sulfur dioxide intensity in our study, and several significant results are as follows: (1) The baseline results suggest a 23% reduction in sulfur dioxide intensity in pilot cities compared to non-pilot cities. (2) The total factor productivity fails to play a partial mediating role in reducing the sulfur dioxide intensity under the implementation of the policy. (3) The results of the triple differences model suggest that the policy still exerts significant adverse effects on sulfur dioxide intensity in the pilot areas of the carbon emission trading scheme.

Environmental Regulation, Resource Misallocation, and Total Factor Productivity: An Empirical Analysis Based on 284 Cities at the Prefecture-Level and Above in China

We investigated the impact of environmental regulation on total factor productivity (TFP) based on a panel dataset of 284 cities at the prefecture-level and above in mainland China from 2006 to 2020 and examined whether environmental regulation had a resource reallocation effect and thus affected TFP. The results showed that there was an "inverted U-shaped" pattern in the impact of environmental regulation on TFP in China and a moderate strengthening of environmental regulation helped to increase TFP, which still held after endogeneity treatment and robustness tests. The "inverted U-shaped" relationship between environmental regulation and TFP in eastern, central, and western cities still held, while environmental regulation did not produce significant effects on TFP in the northeast. The effect of environmental regulation on TFP in large, medium, and small cities tested in groups by city size was consistent with the full sample findings, but the effects decreased in a gradient with city size. The analysis of the impact mechanism showed that environmental regulation had a suppressive effect on resource misallocation and could generate a positive resource reallocation effect and enhance city TFP. The labor reallocation effect of environmental regulation for TFP was stronger than the capital reallocation effect. The findings of our study are of policy reference value for optimizing resource allocation through environmental regulation and thus promoting high-quality city development in China.

The impact of digital transformation on corporate total factor productivity

Introduction

Corporates need to break through the dilemma of system and efficiency with the help of digital transformation in the digital economy era. This paper aims to examine the influence of digital transformation on corporate total factor productivity by investigating whether and how corporate technical cooperation and ESG performance mediate and moderate the relationship between them.

Methods

This study choose Chinese A-share listed manufacturing firms from 2016-2020 as the research sample and use the FGLS regression model to test the proposed hypotheses.

Results

Results show that digital transformation has a positive effect on corporate total factor productivity, and this positive impact is more pronounced when corporates have higher ESG performance. Corporate technical cooperation plays a mediating role between digital transformation and total factor productivity. ESG performance also plays a positive moderating role in the relationship between digital transformation and corporate technical cooperation.

Discussion

Our results contribute to the literature on digital transformation and corporate total factor productivity at the micro-corporate level. Further, our findings offer insights to decision-makers and regulatory bodies regarding the current practices of digital transformation and its potential economic impact.

The Impact of Digital Transformation on Corporate Environment Performance: Evidence from China

In recent years, the rate of climate change appears to have accelerated, and digital transformation and environmental performance have become increasingly important in the field of corporate social responsibility. Previous studies have mainly focused on the economic consequences of digital transformation. However, research on the effect of digital transformation on reducing firms' emissions is relatively rare. This study focused on two kinds of typical environmental pollutants: waste gas emissions and wastewater emissions. Using data on Chinese listed firms from 2010 to 2018 and adopting the fixed effect model to investigate the emission reduction effect and mechanism of digital transformation on waste gas emissions and wastewater emissions of firms, we found the following: (1) digital transformation significantly reduces pollution emissions; (2) the relationship is more pronounced in state-owned enterprises (SOEs), high-polluting enterprises, and economically developed regions; (3) to gain a more in-depth understanding of how digital transformation affects the pollution emission behavior of firms, we further conducted mechanism tests and found that digital transformation reduces pollution by increasing total factor productivity and green innovation and improving firms' internal controls. The above conclusions still hold after a series of robustness tests, including alternative econometric specifications and overcoming potential endogeneity with an instrumental variable. Overall, our findings provide new insights into the effect of digital transformation on environmental pollution emissions. Hence, all governments should pay more attention to digital transformation for sustainable development and improved environmental quality.

Levels, trends, and determinants of effectiveness on the hierarchical medical system in China: Data envelopment analysis and bootstrapping truncated regression analysis

Background

The hierarchical medical system (HMS) refers to the classification of treatment according to disease priorities based on severity and difficulty to promote the fairness of medical services for residents, which is regarded as the key to the success of medical reform in China.

Methods

In the past decade of "New Medical Reform," the efficiency of HMS, including secondary and tertiary hospitals and primary healthcare centers (PHCs), was measured horizontally and vertically by employing the combination of an output-oriented superefficiency slack-based model-data envelopment analysis (SE-SBM-DEA) model with the Malmquist total factor productivity index (MTFP). In the second stage, the overall technical efficiency (OTE) scores were regressed against a set of environmental characteristics and several managerial factors through bootstrapping truncated regression.

Results

On average, the OTE score in tertiary hospitals was 0.93, which was higher than that in secondary hospitals and PHCs (0.9 and 0.92, respectively). In terms of trend, the OTE of tertiary hospitals declined at first and then increased. The opposite was true of secondary hospitals, in which the APC of the OTE was 10.82 and -3.11% in early and late 2012, respectively. The PHCs generally showed a fluctuating downward trend. In the aspects of productivity, all institutions showed a downturn by an annual average rate of 2.73, 0.51, and 2.70%, respectively. There was a significant negative relationship between the ratio of outpatients to inpatients and tertiary hospitals. Additionally, the medical technical personnel per 1,000 population negatively affected PHCs. In contrast, the GDP per capita had a significantly positive effect on tertiary hospitals, and the number of beds per 1,000 population positively influenced PHCs.

Conclusion

The efficiency of medical institutions at various levels in HMS was unbalanced and took the form of an "inverted pyramid." Multilateral factors influence the efficiency of HMS, and to address it, multi-intervention packages focusing on sinking high-quality medical resources and improving healthcare capacity, and guiding hierarchical medical practice should be adopted.

The Impact of Environmental Regulation on Agricultural Productivity: From the Perspective of Digital Transformation

China's goal of becoming a strong agricultural country cannot be achieved without the modernization and digital transformation of the agricultural sector. Presently, China's agriculture has ushered in the era of digital economy transformation. The digital transformation of agriculture has played a huge role in improving agricultural productivity, promoting sustainable development of China's agricultural economy, and achieving sustainable development goals. The deep integration of digital economy and agricultural economy has become an important issue of The Times. This study uses a two-way fixed-effects model and an instrumental variable method to examine the impact of environmental regulation on agricultural total factor productivity. Using the method of mechanism analysis, the conduction path of improving agricultural productivity under the means of environmental regulation is discussed. Therefore, the visualization analysis results based on the panel data of Chinese agricultural enterprises from 2011 to 2019 show that the distribution of digital transformation and productivity level of enterprises is uneven and tends to be stable in space. The empirical analysis results show that there is a direct and significant positive relationship between voluntary environmental regulation and agricultural total factor productivity. The results of mechanism analysis show that, under the means of environmental regulation, digital transformation plays an indirect role in improving agricultural productivity. On the basis of enriching and deepening the theoretical extension of the "Porter Hypothesis", this study subtly incorporates environmental regulation, digital transformation, and agricultural productivity into a unified framework, expanding existing research.

Environmental Information Disclosure, Digital Transformation, and Total Factor Productivity: Evidence from Chinese Heavy Polluting Listed Companies

Environmental information disclosure, as a new environmental regulatory model, is important for achieving collaborative environmental pollution management and sustainable socioeconomic development. Based on the data of listed firms in China's A-share heavy pollution industry from 2009 to 2019, this paper empirically tested the impact of environmental information disclosure on the total factor productivity of enterprises and the contribution of digital transformation to this impact. An increase in the level of environmental information disclosure had a significant positive effect on the total factor productivity of enterprises. However, with the increase in digital transformation among enterprises, the effect of environmental information disclosure on total factor productivity improvement is gradually being replaced. The heterogeneity test results showed that the positive effect of environmental information disclosure on total factor productivity changed depending on property rights, firm size, and geographical location. The effect of environmental information disclosure was stronger for non-state firms, large firms, and firms located in the east-central region. Further mechanism tests showed that the effect was induced through innovation incentives and facilitated financing. The above results provide a valuable reference for a comprehensive understanding of the effect of environmental information disclosure on productivity and adjustment by the digital transformation of enterprises.

The productivity growth of euro area banks

We study the performance of the banking system in the Eurozone over the period 2006-2017 as measured by total factor productivity growth (TFPG) and its components. We find that Total Factor Productivity growth for the median euro area bank decreased from around 2.6% in 2007 to below 1.7% in 2017, driven mainly by a decline in technical efficiency. In addition, we control for unobserved heterogeneity across banks and disentangle persistent and time-varying inefficiency in the banking sector. This modelling choice is important to avoid distorted and biased inefficiency estimates. We find that cost efficiency in the euro area banking sector amounted to around 84% on average over the 2006 to 2017 period. The largest part of bank inefficiency is persistent, suggesting that structural long-term factors (such as location, client structure, macroeconomic environment, regulation, etc.) play a bigger role than time-varying factors.

Does Environmental Regulation Help Mitigate Factor Misallocation?-Theoretical Simulations Based on a Dynamic General Equilibrium Model and the Perspective of TFP

How environmental regulation affects factor allocation is becoming an emerging hot topic in academia. In this paper, we construct a dynamic general equilibrium model accommodating environmental regulatory shock based on the H-K framework to explain the impact of environmental regulation on factor misallocation from the perspective of aggregate total factor productivity loss changes, and numerical simulation results are provided for several representative scenarios. The results show that environmental regulation has a significant effect on factor market misallocation, but this effect is not simply positive or negative, and it mainly depends on the firms’ initial factor allocation status and the intensity of the shock. Reducing the intensity of environmental regulation for firms that face stronger distortion helps mitigate factor misallocation and, on the contrary, the same policy could exacerbate factor market misallocation. Under the environmental regulatory shock condition, firms’ overhead labor input has a moderating effect on the factor allocation mitigation of environmental regulation. Distorted firms’ higher overhead labor share inhibits the correction of factor misallocation by environmental regulation. And reducing firms’ overhead labor share amplifies the correcting effect of environmental regulation on factor misallocation.

Research on China Cities' Total Factor Productivity of Carbon Emission: Based on Decoupling Effect

Economic development depends on energy consumption, which is a major source of carbon emission. How to achieve economic decarbonization has become one of the key questions urgently needing to be solved on the road of carbon peak and carbon neutral development in China. Advancing total factor productivity (TFP) of carbon emission is an important way to promote economic decarbonization. For the carbon emission TFP, current research is mainly conducted from province level or an industry perspective, and studies its deference with various geographical locations, economic development levels, urbanization levels, etc., lacking the research that combines the decoupling effect to carbon emission TFP. The carbon emission TFP of Chinese cities and how to improve it remain unclear. Therefore, based on Tapio decoupling theory, this paper firstly analyzed the decoupling effect of China’s 284 cities from 2005 to 2019, and aggregated the cities into four groups according to the decoupling effect. Then, using the DEA–Malmquist index, this paper researched the carbon emission TFP and its driving factors based on the aggregation. The result shows that weak decoupling is the main decoupling status in China. As a whole, carbon emission TFP of Chinese cities does not perform well, but it shows a growth trend over time. Strong decoupling cities outperform expansive negative decoupling cities on carbon emission TFP. Technical change and pure technical efficiency change have inhibiting effect and promoting effect on carbon emission TFP, respectively, which are the main factors for the difference of carbon emission TFP between strong decoupling cities and expansive negative decoupling cities. Based on these findings, some common but differentiated recommendations are provided for improving Chinese cities’ carbon emission TFP.

Does Low-Carbon City Construction Improve Total Factor Productivity? Evidence from a Quasi-Natural Experiment in China

Low-carbon city construction (LCC) is an important strategy for countries desiring to improve environmental quality, realize cleaner production, and achieve sustainable development. Low-carbon cities have attracted widespread attention for their attempts to coordinate the relationship between environmental protection and economic development. Using the panel data from 2006 to 2017 of prefecture-level cities in China, this study applied the difference-in-differences (DID) method to analyze the effects of LCC on the total factor productivity (TFP) of the cities and its possible transmission mechanism. The results show significantly positive effects on TFP, but the effects on each component of TFP are different. Although the LCC has promoted technical progress and scale efficiency, it has inhibited technical efficiency. The accuracy of the results has been confirmed by several robustness tests. Mechanism analysis showed that the pilot policy of low-carbon cities has promoted technical progress and scale efficiency by technological innovation and the upgrading of industrial structure, but resource mismatches among enterprises have been the main reason for reduced technical efficiency. Regional heterogeneity analysis showed that the effects on TFP in the eastern region have been more significant than in the central and western regions. In the eastern region, they have promoted technical progress, while in the central and western regions, they have promoted technical progress and scale efficiency but hindered technical efficiency. This paper presents our findings for the effects of LCC on economic development and provides insightful policy implications for the improvement of technical efficiency in low-carbon cities.

Research on Total Factor Productivity and Influential Factors of the Regional Water-Energy-Food Nexus: A Case Study on Inner Mongolia, China

With the supply of water, energy and food facing severe challenges, there has been an increased recognition of the importance of studying the regional water–energy–food nexus. In this paper, Inner Mongolia, including 12 cities in China, was selected as a research case. A super-efficiency slack based measure (SBM) model that considered the undesirable outputs was adopted to calculate the regional total factor productivity (TFP) and the Malmquist–Luenberger index was used to investigate the change trend of the TFP from 2007 to 2016 based on understanding the water–energy–food nexus. Finally, influential factors of the TFP were explored by Tobit regression. The results show that the 12 Inner Mongolia cities are divided into higher, moderate and lower efficiency zones. The higher efficiency zone includes Ordos, Hohhot, Xing’an, and Tongliao, and the lower efficiency zone includes Chifeng, Xilin Gol, Baynnur, Wuhai and Alxa. There is a serious difference in TFP between Inner Mongolia cities. During the study period, the TFP of the water–energy–food nexus in Inner Mongolia cities shows a rising trend, which is mainly driven by the growth of technical progress change. However, the average ML values of the lower and moderate efficiency zones were inferior to the higher efficiency zone in six of the ten years, so the difference between Inner Mongolia cities is growing. According to the Tobit regression, the mechanization level and degree of opening up have positive effects on the TFP, while enterprise scale and the output of the third industry have negative effects on the TFP. Government support does not have any significant impact on the TFP. Finally, suggestions were put forward to improve the TFP of the water–energy–food nexus in Inner Mongolia cities.

Productivity Growth in the English National Health Service from 1998/1999 to 2013/2014

Productivity growth is a key measure against which National Health Service (NHS) achievements are judged. We measure NHS productivity growth as a set of paired year-on-year comparisons from 1998/1999-1999/2000 through 2012/2013-2013/2014, which are converted into a chained index that summarises productivity growth over the entire period. Our measure is as comprehensive as data permit and accounts for the multitude of diverse outputs and inputs involved in the production process and for regular revisions to the data used to quantify outputs and inputs. Over the full-time period, NHS output increased by 88.96% and inputs by 81.58%, delivering overall total factor productivity growth of 4.07%. Productivity growth was negative during the first two terms of Blair's government, with average yearly growth rate of -1.01% per annum (pa) during the first term (to 2000/2001) and -1.49% pa during the second term (2000/2001-2004/2005). Productivity growth was positive under Blair's third term (2004/2005-2007/2008) at 1.41% pa and under the Brown government (2007/2008-2010/2011), averaging 1.13% pa. Productivity growth remained positive under the Coalition (2010/2011-2013/2014), averaging 1.56% pa. © 2016 The Authors Health Economics Published by John Wiley & Sons Ltd.

Determining climate effects on US total agricultural productivity

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures such as crop yields and economic returns, but these measures cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regression model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain ∼70% of variations in TFP growth during 1981-2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. As a result, TFP could fall to pre-1980 levels by 2050 even when accounting for present rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective resource for policy making.