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This research aims to explore how environmental pollution events affect total factor productivity in related industries in China. The results of the research found that (1) Cadmium-contaminated rice cases had negative impacts on the related industry after a time delay by reducing the production scale and investment in R&D to improve productive efficiency, therefore decreasing the total factor productivity. Rising public awareness significantly expanded the negative impact of environmental pollution events. (2) The more sophisticated environmental regulations at the provincial level, the more obvious the total factor productivity decreased after cadmium-contaminated rice cases. The effect of existing environmental regulations at the municipal and county levels was not satisfactory. (3) Cadmium-contaminated rice cases had a greater negative impact on East and Central China than other regions. The result also indicates cross-regional pollution transfer for the purpose of regulation evasion. [ABSTRACT FROM AUTHOR]

After the 2008 financial crisis, companies in China begun paying more attention to sustainable development. This article attempts to examine whether and how digital transformation affects total factor productivity (TFP) at the firm-level. Using 2913 listed companies in China from 2012 to 2018, this study finds that digital transformation is positively associated with corporate TFP in China. Our explanatory variable of firm-level digitalization index is constructed via text analysis methods. After a series of robustness checks and different attempts that mitigate endogeneity concerns, our findings remain valid. However, traditional information and communication technologies (ICT) cannot improve corporate TFP. Further analyses of three plausible channels indicate that digital technologies improve TFP primarily through cost reduction and human substitution rather than supervision advantage. The results indicate that firms achieve actual benefits from the digital transformation, and how digital transformation improve the sustainable development. This study could serve as a policy inspiration for other developing countries. [ABSTRACT FROM AUTHOR]

It is beyond doubt that Solow's proposal for "an elementary way of segregating variations in output per head due to technical change from those due to the availability of capital per head" (Solow, 1957, p. 312) leading to the 'residual', and hence, TFP growth, has been a crucial development of Neoclassical economics. This notwithstanding, the critique of (and alternative to) Solow's proposal advanced by Pasinetti (1959) has not been equally acknowledged. The debate re-emerged when a posthumous note by Richard Stone (1998[1960]) triggered a further exchange between the authors. This paper aims at retracing the key conceptual aspects of the discussion, pointing to some limitations of Pasinetti's original implementation of his measure of productivity changes, and providing an Input–Output generalisation based on Pasinetti's notion of hyper-integrated labour. Seen in this light, Pasinetti's computable measure of technical change provides a theoretically sound alternative to perform productivity analyses from a Classical perspective. • Review of debate between Solow and Pasinetti on productivity measurement. • Pasinetti's 1959 index of technical change co-moves with K/W, rather than with K/Q. • Input–Output reformulation validates Pasinetti's original intuition. • Novel indicator of direction of technical change at aggregate and sectoral levels. • Illustrative empirical application to the case of Italy. [ABSTRACT FROM AUTHOR]

Prior to 2018, Chinese enterprises registered for Value Added Tax (VAT) were required to carry forward excess input tax credits indefinitely. Following the 2018 VAT Credit Refund Reform, enterprises became entitled to refunds on excess input tax credits, as is standard in a conventional VAT system. The reform significantly enhanced tax neutrality, which might have been expected to have impacted production efficiency. This study employs a difference-in-differences (DID) method of analysis, using the commencement of the 2018 reform as the focal point, to highlight how from 2014 to 2020 certain Chinese enterprises received fiscal benefits from the reform while others did not. The conclusion is striking; enterprises that were able to obtain VAT refunds increased their total factor productivity by 6.96% compared to those that received no fiscal benefit from the reform. The outcome reflects the impact of the VAT credit refund as a source of financing for these firms, leading directly to increased investment, or, in the case of high-tech enterprises, increased R&D. The impact of this change is particularly pronounced in private enterprises and growing businesses. Our study provides evidence of the benefits of VAT reform in the direction of neutrality by providing swift and full refunds for excess input tax credits. [ABSTRACT FROM AUTHOR]

Intangible capital stock is an important variable of current concern for all sectors, which is a new driving force of innovation-driven economic growth. However, there is still room for improvement in the estimation method of China's intangible capital stock, and the analysis of the estimation results is not yet sufficient. For this purpose, this paper firstly re-estimates China's intangible capital stock using the CHS classification framework, especially in the estimation methods of software capital and scientific R&D capital, and makes a lot of improvements. Then, this paper uses not only the growth model but also the mediating effect model to classify the intangible capital in the CHS framework into explanatory and mediating variables of economic growth, and proposes that the explanatory variables are what drive new driving force of China's economic growth and the intangible capital stock estimated in this paper. Finally, this paper provides a detailed analysis of the changes, structure, and distribution of the explanatory variables. The results find that (1) software capital and scientific R&D capital are the new driving forces of China's economic growth; (2) China's national stock of current-valued intangible capital rose from 0.4 trillion yuan to 16.4 trillion yuan from 2001–2017, with software capital stock growing faster than scientific R&D capital stock; (3) Intangible capital stock is mainly distributed in a few regions such as Beijing, Guangdong, Jiangsu and Shanghai; (4) The structure of intangible capital in most regions is not reasonable, and there is a bias towards software capital or scientific R&D capital; (5) The rapid growth of intangible capital stock in Jiangsu and other regions is one of the reasons for their fast economic growth rate, while the slow growth of intangible capital stock in Heilongjiang and Liaoning has led to a decline in their economic growth rate. [ABSTRACT FROM AUTHOR]

In this study, the DEA–Malmquist index method was used to measure the total factor productivity of citrus in seven major mandarin-producing provinces and seven major tangerine-producing provinces in China from 2006 to 2020. Moran's I index was used to test the spatial correlation of total factor productivity of mandarin and tangerine, and its σ convergence and β convergence characteristics were explored using coefficient of variation and spatial panel models. The results show that from the perspective of time series evolution, the growth rate of total factor productivity of mandarin and tangerine in China slowed down year by year after reaching the maximum value in 2008. Technological progress was the main factor affecting the total factor productivity of citrus. The total factor productivity growth of tangerine was more stable than that of mandarin, and the pure technical efficiency index and scale efficiency change index of mandarin and tangerine were not stable. From the perspective of regional differences, the total factor productivity of China's main citrus-producing provinces all indicated positive growth, showing an increasing trend from east to west. The drivers of growth were mainly technological progress and scale efficiency. The regional differences in total factor productivity growth for mandarin were more obvious than for tangerine. The total factor productivity of mandarin and tangerine showed obvious spatial correlation characteristics; the positive spatial spillover effect was significant; and there were σ convergence, absolute β convergence, and conditional β convergence. Regional disparities in citrus industry development can be more objectively reflected by convergence analysis that takes spatial factors, economic and social factors, and other factors into account. [ABSTRACT FROM AUTHOR]

Nearly 40 percent of worldwide energy and process-related CO2 emissions are produced by the construction sector. China's construction industry is the largest in the world, with Chinese construction enterprises completing a total output value of RMB 26.39 trillion in 2020; these buildings contribute to about 20 percent of China's overall carbon emissions and 20 percent of the global total emissions. There is an urgent need to prove whether construction enterprises are benefiting from the carbon trading policy. Compared to the traditional method, a double difference model can be used to highlight the consequences of different states of construction enterprises' responses to carbon trading regimes. In this study, we examine the following results based on cross-sectional data collected from 2006 to 2021, from listed construction enterprises: (1) Existing carbon emission policies have had a significant impact on the improvement of construction enterprises' total factor productivity. This improvement is more pronounced in large state-owned enterprises in particular. (2) Construction enterprises' greater involvement in carbon trading income is most strongly influenced by their green innovation level. (3) Construction enterprises located in eastern and central China benefit significantly from carbon trading, but construction enterprises based in the west do not. The research result indicates that future incentive initiatives should pay more attention to western regions and privately owned building enterprises. The leading role of large state-owned building enterprises should be reinforced. [ABSTRACT FROM AUTHOR]

National income calculations may not include knowledge that directly concerns the socioeconomic stance in an economy. Knowledge plays a significant role in promoting the economic growth of a country; however, its socio-economic role has received little attention in the literature. Total factor productivity, which is the main source of long-term economic prosperity, expresses the increase in productivity in all production factors. This paper attempts to quantify the effects of total factor productivity growth on economic prosperity. The analysis is conducted for the 2007-2020 period and 18 Central Eastern Europe countries. The "Legatum Prosperity Index" is utilized in the econometric analysis, in line with the purpose of the study. Results of the study with panel ordinary least squares, panel fixed-effects, panel random effects, panel-corrected standard errors (robustness check), and system-generalized method of moments (robustness check) confirm that total factor productivity growth positively correlated with economic prosperity. [ABSTRACT FROM AUTHOR]

The impacts of shocks generated by macroeconomic growth scenarios (2 percent, 5 percent, and 10%) on the overall welfare index in Iran were explored in this study. The essential data were gathered from the social accounting matrix of 1390, the central bank, and the data-output table of 1395, and the new recursive dynamic computable general equilibrium (RDCGE) model was employed for data analysis. The findings revealed that real GDP shocks of up to 2.66 percent result in an increase in Iran's social welfare index. Because growing real GDP through boosting economic capacity raises individual income in society and creates the circumstances for household well-being to improve. Furthermore, productivity shocks of total inputs of production of up to 1.55 percent raise the social welfare index. Because improving total factor productivity has resulted in a rise in output, which has a direct influence on household consumption owing to greater income and promotes economic well-being. Furthermore, the short-term reaction of the social welfare index to oil income shocks is a maximum of 0.81 percent. Because, on the one hand, more oil revenues contribute to increased economic growth, but on the other hand, they lead to the establishment of the Dutch illness. Finally, the data revealed that among the factors analysed, shock due to real GDP growth, shock due to total productivity growth, and shock due to oil revenue increase had the greatest influence on overall well-being. [ABSTRACT FROM AUTHOR]

Artificial intelligence is profoundly influencing various facets of our lives, indicating its potential to significantly impact sustainability. Nevertheless, capturing the productivity gains stemming from artificial intelligence in macro-level data poses challenges, leading to the question of whether artificial intelligence is reminiscent of the "Solow paradox". This study employs micro-level manufacturing data to investigate the impact of artificial intelligence on firms' productivity. The study finds that every 1% increase in artificial intelligence penetration can lead to a 14.2% increase in total factor productivity. This conclusion remains robust even after conducting endogeneity analysis and a series of robustness tests. The study identifies that the positive impact of artificial intelligence on productivity is primarily achieved through the value-added enhancement effect, skill-biased enhancement effect, and technology upgrading effect. Furthermore, the study reveals that the effects of artificial intelligence on productivity vary across different property rights and industry concentration contexts. Additionally, the structure of factor endowments within firms can also influence the productivity gains from artificial intelligence. Our study presents compelling evidence demonstrating the role of artificial intelligence in fostering economic sustainability within the framework of Industry 4.0. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, digital transformation has become an important strategic choice in driving enterprise development. However, there are few studies on how digital transformation affects the total factor productivity of enterprises. In order to fill this theoretical gap, this study explored the impact of digital transformation on total factor productivity from the perspective of information transmission that analysts focus on. Based on data from Chinese A-share listed companies from 2012 to 2021, this work constructed a fixed effects model and a mesomeric effect model. The experimental results show the following: (1) the digital transformation of enterprises significantly improves total factor productivity; (2) the attention of analysts has significantly improved the total factor productivity of enterprises; (3) enterprise digital transformation can significantly improve analysts' attention, which plays an intermediary role between enterprise digital transformation and total factor productivity; (4) the heterogeneity analysis showed that digital transformation has a more significant promoting effect on the total factor productivity of tertiary industry enterprises and enterprises with lower competitiveness in their respective industries. For the first time, this study explored the mechanism by which digital transformation impacts total factor productivity from the perspective of analysts. It is necessary to encourage enterprises to attach importance to the role of analysts in information transmission in the process of digital transformation. It is suggested that enterprises formulate strategies according to the characteristics of their industries in digital transformation, and the government should formulate differentiation strategies according to the different industries and the different levels of competition between industries in the national economy. [ABSTRACT FROM AUTHOR]

Using the panel data of the manufacturing industry in 30 provinces of China from 2005 to 2021, this research takes the establishment of a Chinese national-level comprehensive big data pilot zone as a quasi-natural experiment, empirically analyzes the processing effect of digital economy development on the green transformation and upgrading of manufacturing industry by using a time-varying DID model. The results show that the development of the digital economy can significantly promote the green transformation and upgrading of the manufacturing industry. Further analysis reveals that the development of the digital economy has a significant effect on the green transformation and upgrading of the manufacturing industry in regions with low economic development levels and regions with high network development levels. The development of the digital economy can significantly stimulate the green technology innovation of enterprises and promote the upgrading of industrial structures so as to promote the green transformation and upgrading of the manufacturing industry. Manufacturing agglomeration and environmental regulation intensity have moderating effects and threshold effects, respectively, on the impact of digital economy development on the green transformation and upgrading of the manufacturing industry. [ABSTRACT FROM AUTHOR]

With a persistent global economic slump, governments encourage economic growth by expansionary fiscal policies through tax cuts. Total factor productivity (TFP) is an important determinant of corporate development and economic growth. Taking China's 2008 Corporate Income Tax Reform as a quasi‐natural experiment, this paper uses data from China's A‐share listed companies from 2003 to 2018 and difference‐in‐differences analyses to identify the impact of corporate income tax (CIT) rate changes on TFP. The findings indicate that reducing the CIT rate positively impacts corporate TFP through two available channels: corporate investment and human capital investment. Additionally, the effects of reducing the CIT rate on TFP are primarily significant in non‐state‐owned, smaller and more financing‐constrained enterprises. [ABSTRACT FROM AUTHOR]

Un-incorporated firms are usually found less productive than their incorporated counterparts. However, little is known about the misallocation conditional on firms' incorporation status and their productivity. This paper investigates the resource misallocation across un-incorporated firms and gauges the consequent aggregate productivity loss in comparison with their incorporated counterparts. We examine the question by using firm-level survey data from Sri Lanka's manufacturing sector for 2005–2017 that provide unique information about firms' corporation status. Our findings suggest that misallocation is more severe in unincorporated firms than in incorporated ones, leading to extra 42 % aggregate TFP loss to the former. By comparing the sources of misallocation between the two types of firms, we find capital is more misallocated relative to output and there is a stronger positive correlation between firm-specific distortion and productivity across the unincorporated firms. Our findings suggest that the un-incorporated firms suffer additional productivity loss at the aggregate level due to misallocation. [ABSTRACT FROM AUTHOR]

Unreliable electricity supply is a widespread problem in developing countries. This paper examines the impact of power outages on firm productivity in East Africa, considering the effect of generator ownership in general and during blackouts. The results show large negative effects of power outages on productivity and a mitigating effect of self-generating during power outages of approximately the same size. However, self-generation is also found to generally reduce productivity due to the idle capital effect of unused generators during blackout-free times. This finding highlights that self-generation is only profitable for firms if the experienced power outages are severe enough. [ABSTRACT FROM AUTHOR]

This study provides a vital understanding of how local government capacity affects total factor productivity (TFP) growth in the context of an emerging economy. The sample of the study is a panel dataset of 63 Vietnamese provinces over the period of 2006-2017. We find that provinces that are high in self-financing have a positive effect on TFP growth, while low self-financing provinces have a negative effect on TFP growth. More interestingly, the impact of public governance is negative on TFP growth for high self-financing provinces, but is positive for low self-financing provinces. Our findings imply that the Vietnamese decentralisation regime drives high self-financing and low self-financing provinces to pursue different paths. High self-financing provinces defy governance reforms, leading to a race to the bottom. [ABSTRACT FROM AUTHOR]

This study investigates whether an increase in wages of foreign firms generates the total factor of productivity (TFP) growth of Indonesian manufacturing firms by considering different job characteristics and geographical boundaries. Using system GMM, the result shows that on average the wage spillover in production jobs within an industry positively affects the TFP, while the wage spillover in non-production jobs contributes negatively. Moreover, the wage spillover in production jobs and non-production jobs within a province do not affect the TFP of Indonesian manufacturing firms. These results indicate that employees in production jobs have larger contributions to increasing TFP than those in non-production jobs when foreign firms increase their wages. Such contributions occur within an industry, not within a province. For the Government, the different contributions to the TFP of firms from wage spillovers in production and non-production jobs indicate the importance of skill mobility to the national economy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Technology Economics is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forestry is the underpinning of economic and environmental civilization for sustainable economic development. Forestry benefits ecosystems and local dwellings; thus, transforming and advancing forest products in a civilized society is critical to building a progressive community. This research aims to analyze the merits of forest products based on static, dynamic, and scale efficiency. It employed the super-efficient data envelopment analysis—Charnes, Cooper and Rhodes, and Malmquist index methods with an enhanced robustness check by applying the Stochastic Frontier Analysis. The results show that, first, from the perspective of static efficiency, the forestry industry's operating performance is maintained at a relatively high level, with a minimal fluctuation range; however, the scale efficiency is observed at a deficient level. Limited by the scale efficiency results, the aggregate comprehensive technical efficiency was at a low standard. The average total factor productivity of dynamic efficiency for each company reached 1.029, indicating that the resource allocation of listed companies is relatively reasonable, operating efficiency is on the rise, and technical level changes are a substantial source of total factor productivity growth. Furthermore, the super efficiency DEA findings indicated that 11 of the most high-performance companies attained an efficiency value above criterion value one after re-ranking. The comprehensive efficiency value of Sun Paper reached 1.438 in 2019, Sophia 1.393, Hexing Packaging 1.383, Fujian Jinsen 1.326, Bunny 1.271, Meike Home Furnishing 1.235, Jingxing Paper 1.222, Zhongshun Jiezou 1.116, Meiying Sen 1.099, Chenming Paper 1.064, Da Ya Dekor 1.015. Second, the comprehensive efficiency value of Fujian Jinsen's company has a more significant impact on the overall average efficiency of the forestry listed companies. After excluding Fujian Jinsen, the average comprehensive efficiency of 2018–2019 indicated an upward trend for the listed companies. This study suggests that policymakers should strengthen the forestry industry development plan and policy implementation regulations to focus on the forward-looking and guiding principles of industrial and technological innovation policies. [ABSTRACT FROM AUTHOR]

This paper shows that, when parents can endow their offspring with bequests and human capital, markets cannot deliver (generically under laissez-faire) the planner's choice, if educational investments affect total factor productivity—as empirical evidence establishes. Moreover, for a human capital production function close enough to affine (around market and planner steady states with similar fertilities), the market steady state wage is higher than the marginal productivity of labor at the planner's steady state, so that the market steady state human capital is too low. In other words, the market misses the planner's allocation by leading households to transfer to their offspring more in bequests and less in education than would be optimal. These results obtain in spite of parents perfectly internalising (1) the value for their children of their bequests and educational investment, but not (2) the externality on total factor productivity—nor hence on factor prices. The planner's allocation can, nonetheless, be decentralised subsidising labor income through a lump-sum tax on saving returns that reduces bequests. An estimate of the subsidy needed—for standard functional forms and parameter values estimated from US data—suggests a sizeable market inefficiency. [ABSTRACT FROM AUTHOR]

The sports industry, an emerging industry with low pollution and low emissions, plays an important role in the sustainable development of human society. Using 489 observations from a panel of 128 sports firms listed on the New Third Board in China from 2015 to 2020, this study investigated the effects of three different innovation-driven policies on the total factor productivity of sports firms and the moderating role of governance structure on this relationship. The results showed that high-tech enterprise tax relief was an important policy tool to promote the total factor productivity of sports enterprises, but the direct effects of government subsidies and pre-tax deduction of R&D expenses were not significant. In addition, governance structure had a positive moderating effect on the relationship between innovation-driven policies and the total factor productivity of sports firms. The positive effect of the pre-tax deduction of R&D expenses policy was more significant for sports firms with larger and more independent boards of directors. This study provides new insight into innovation policy development for the sports industry by showing that corporate governance has a significant impact on the effectiveness of innovation-driven policies. Furthermore, the findings provide practical guidance for both managers and government–industry policymakers in the sports industry. [ABSTRACT FROM AUTHOR]

This paper studied the total factor productivity (TFP) of agriculture in the Bohai Rim region. The agricultural TFP showed the dependence of agricultural development on chemical fertilizers, pesticides, labor, science, technology, etc. By coordinating the inputs of various production factors, production efficiency can be improved, reducing the over-reliance on chemical fertilizers and pesticides and achieving the development and sustainability of agriculture. In this study, the sectional data of three provinces (Shandong, Hebei, and Liaoning) and two cities (Beijing and Tianjin) in the Bohai Rim region of China from 2011 to 2020 were collected, and the envelope analysis was performed on the collected data using the Malmquist index model. The results showed that the TFP of agriculture in the Bohai Rim region was greater than one, and agriculture was generally well-developed. Regionally, the agricultural productivity in Shandong Province was generally lower than in other provinces and cities. In addition, the scale efficiency was the most important factor restricting agricultural TFP in the Bohai Rim region, indicating that there was still room to improve investment in the agricultural production scale. Based on the analysis results, suggestions were made for sustainable and high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

Balancing water environmental protection and economic growth is a priority for the local governments. Many literature analyses found that the reform of the River Chief System (RCS) had a significant effect on water quality improvement in China; however, it is important and necessary to comprehensively assess the impact of the RCS on the total factor productivity (TFP) of industrial enterprises, which provides a realistic basis for the decisions of local governments. This paper uses the quasi-natural experiment of the RCS in China and data from Chinese industrial enterprises to analyze the impact of the policy reform on the total factor productivity (TFP) of enterprises and the influence mechanism. The empirical analysis finds that the TFP of industrial enterprises in the reformed areas of the RCS is significantly lower than that in the non-reformed areas. This indicates that the implementation of the RCS is not conducive to the improvement of TFP of industrial enterprises. And this effect is mainly generated by reducing the output level and capital allocation efficiency of industrial enterprises. Meanwhile, the impact of the RCS on the TFP of industrial enterprises exists heterogeneity. [ABSTRACT FROM AUTHOR]

It is typical in the modern world that most economic growth is explained by an increase in total factor productivity, commonly accompanied by the rise of real capital. After the last financial crisis, Slovenia was specific in the growth of total factor productivity between 2009 and 2019 in that the 44 analyzed industries substituted the decline of net real values of fixed capital, associated with a large contraction in bank loans to non-financial corporations. During this period, Slovenia's total factor productivity strengthened due to increases in innovative potential, human capital (employees with higher education), and the share of foreign trade in Slovenia's GDP. The public sector played an important role in this, as the increase in innovation potential and human capital was the result of the increase in the real level of Slovenian Export and Development Bank loans to enterprises and from extensive EU Structural and Cohesion Funds placements. The growth of innovation potential was influenced by the rise in the number of full-time researchers, and the increase in human capital was influenced by the economic climate in the EU. [ABSTRACT FROM AUTHOR]

Based on China's supply-side structural economic reforms, this paper examines the impact of the Belt and Road Initiative (BRI) on the formation of zombie firms. We find that the BRI significantly inhibits the formation of zombie firms by easing financial constraints and optimizing investment efficiency. Our findings are robust to different model specifications and samples. Further investigations find that the impact of the BRI is pronounced for private enterprises, manufacturing enterprises and enterprises with more intense market competition. Overall, our results provide clear policy implications by shedding light on the role of the BRI in optimizing the allocation of resources. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Higher Education & Science / Yüksekögretim ve Bilim Dergisi is the property of Zonguldak Bulent Ecevit Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Industrial agglomeration (IA), a common industrial phenomenon, has been verified to have a significant impact on total factor productivity (TFP) in many industries. However, the impact of IA on TFP is seldom investigated in the construction industry, despite the existence of the industrial agglomeration phenomenon in the construction industry. As such, this study aims to probe into the impact of IA on TFP in the construction industry, so as to provide new insights into the industry development and improvement of TFP in the construction industry. Based on the competing results of the agglomeration effect and congestion effect caused by IA, this study proposed three hypotheses on the impact mechanism of IA on TFP in the construction industry. Then, the non-linear regression model and linear regression model were developed to test the hypotheses based on the provincial panel data from 2002 to 2017 in China. The empirical results reveal that IA has a positive linear impact on TFP in the construction industry, and the impact of IA on TFP in the Chinese construction industry during the observed period is in the embryonic stage. Besides, both the firm scale and economic development level have positive impacts on TFP, whereas the specialization structure has a negative impact. Hence, the government can encourage industrial agglomeration in the construction industry to enhance TFP, in order to leverage the knowledge spillovers, labor pool, and other benefits from IA. [ABSTRACT FROM AUTHOR]

Copyright of Environmental Science & Technology (10036504) is the property of Editorial Board of Environmental Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since at least the mid-2000s, many advanced economies have experienced low productivity growth. This development is often related to declining productivity gains at the technology frontier, which is largely determined by the US. We challenge this explanation by studying the effects of US technology shocks on productivity levels in advanced economies. We find positive but small spillovers of US technology shocks. For many countries, the elasticity of their productivity with respect to a 1% increase in the US technology level is significantly lower than 1. Thus, the recent US productivity slowdown must have had a limited effect on productivity developments in advanced economies. Nevertheless, after 5 years, the degree of productivity spillovers varies across countries. Therefore, we analyze the role of institutions in shaping these results. Our findings suggest that isolated institutional characteristics are not able to explain the observed various spillover degrees. [ABSTRACT FROM AUTHOR]

This study examines agricultural total factor productivity (TFP) from theoretical and empirical perspectives. Specifically, the measures, relevant data, and major sources of the TFP growth are discussed. Using the sector-level growth and productivity data from the EU KLEMS, EUROSTAT, FAOSTAT, and USDA databases, the TFP growth in the EU countries over 1996–2019 is considered. The sources of the TFP growth are analyzed. The results suggest that agricultural TFP increased in almost all EU countries over the period covered. TFP growth appears as an important component of labour productivity and value-added growth in the EU agriculture. The differences among the databases considered are noted in the sense of input and output levels and TFP growth rates. [ABSTRACT FROM AUTHOR]

This paper analyzes the granularity hypothesis in a large emerging economy, Kazakhstan. We use a new longitudinal dataset at the firm level and at quarterly frequency between 2012 and 2018 to document the size distribution of firms and to provide evidence that it follows a power law. We find that the largest 30 firms explain nearly 80 percent of the growth in aggregate total factor productivity. This confirms earlier research for the U.S. and other developed countries. However, the granular nature of the Kazakh economy is even more outspoken than in other countries. Thus idiosyncratic shocks and the way they ripple through the production network matter to understand changes in aggregate productivity growth. Moreover, since these granular firms are concentrated in the oil industry it exposes the vulnerability of the economy more to unexpected shocks in one industry in particular. [ABSTRACT FROM AUTHOR]

IntroductionWith the rapid development of digital technology and its deep integration with the engineering and construction field, digital construction has become an effective way for low-carbon transformation in the construction industry. However, there is a gap of empirical research between digital construction and carbon emissions. MethodsThis paper empirically investigates the impact of digital construction level on carbon emission intensity and the mechanism of action by using the two-way fixed effects model and mechanism testing based on the panel data of 52 Shanghai and Shenzhen A-share listed companies in China’s construction industry from 2015 to 2021. ResultsThe findings indicate that the improvement of digital construction level can significantly decrease the carbon emission intensity of construction enterprises, and the conclusions still hold after robustness tests and discussions on endogeneity issues such as replacing core explanatory variables, replacing models, using instrumental variables method, system GMM model and difference in differences model. According to a mechanism analysis, digital construction can curb carbon emission intensity by enhancing the R&D innovation capacity and total factor productivity of enterprises. Furthermore, the heterogeneity analysis shows that the improvement of digital construction level in state-owned enterprises as well as civil engineering construction enterprises can better contribute to reducing carbon emission intensity. DiscussionThis paper will provide a reference for the synergistic optimization of digital construction development and carbon emissions reduction in construction enterprises. The research conclusions are going to promote the digital transformation of the construction industry to accelerate the achievement of the carbon peaking and carbon neutrality goals.

China introduced the ''agricultural water conversion policy'' in 2012 to efficiently utilize agricultural water resources and improve production technology in different regions of the Country to increase sustainable agriculture production. To this end, for Policy impact evaluation, our study employed slack-based measure data envelopment analysis, Meta frontier Analysis, and the Malmquist productivity index to measure the agriculture water usage efficiency, agriculture Production technology heterogeneity, and total factor productivity change in pre- and post-agriculture water policy (2012) implementation in different regions of China. Data for 31 provinces and cities were taken for efficiency and productivity estimation from 2000 to 2020. Results revealed that agriculture water usage efficiency significantly increased after the policy implementation. The average agricultural water usage efficiency score for the 2000–2012pre–policy period is 0.6763, whereas the average AWUE score for the 2013–2020 post–policy period is 0.7522, showing an increase of 11.22%. Further results show that the eastern region maintains superior agriculture production technology compared to the western and central regions, with an average technology gap ratio of 0.8941 during the study period. The average total factor productivity change for the study period is 1.0769. Technological change is the primary determinant of productivity growth. There was a marginal decline in average Productivity change after policy implementation. Mann-Whitney and Kruskal Wallis test strengthens the study's results by providing statistically significant differences among different periods and regions.

This paper analyzes the impact of reducing output tariffs (i.e., domestic tariffs on import of final goods) and input tariffs (i.e., domestic tariffs on imports of intermediate goods) on total factor productivity growth of Peruvian manufacturing firms. Peru’s annual survey of manufacturing data from 2003–2017 is used to explore the reduction of tariffs during three preferential trade agreements: United States, China, and the European Union. Lower output tari˙s could decrease productivity by reducing firm’s market share or could increase productivity by inducing tougher import competition, while cheaper imported inputs can raise productivity via learning, variety, and quality effects. The results show that a decrease in output tariffs decreases Peruvian firms’ productivity growth for non-exporters (i.e., domestic firms producing goods that are also imported) while increasing productivity growth for exporters (i.e., domestic firms producing export goods). In contrast, a reduction in input tariffs increases firm productivity for all firms.

The textile sector is a significant exporting sector of Pakistan. This study examines the determinants of the export performance of Pakistani textile firms using firm-level panel data from 2008 to 2018. Under the framework of the dynamic System Generalized Method of Moment (SGMM) methodology, our findings suggest that both sunk costs and firm-specific characteristics like productivity, age, and size are important determinants of textile exports. Further, the study also observes that firms with a high number of export destinations and greater product diversification tend to export more. The year-specific dummies reveal that textile export performance is adversely affected by the energy crisis in 2012. We recommend that Pakistan should support large, experienced, and productive textile exporter firms to boost textile exports. Besides, more assistance should be provided regarding potential overseas markets to the existing and new export firms.

Government green investment (GGI) is one of the effective tools for reducing carbon emissions (CEs). This is of great significance for the realization of “carbon peaking and carbon neutrality.” This study innovatively considers the multidimensional CE reduction (CER) process indexes to explore the impact mechanism of GGI on China’s CER process. At the same time, CER is particularly critical in resource-dependent regions. This study incorporates this perspective to explore the CER effect of GGI in these regions. This paper developed a multidimensional evaluation system for China’s CER process, using panel data of 269 prefecture-level cities from 2008 to 2019 to explore the impact of GGI on China’s CER process. The results indicated that 1) GGI promotes CER in China as a whole and effectively inhibits CEs, per capita CEs, and CE intensity; 2) GGI promotes CER to some extent by enhancing the energy efficiency and total factor productivity; 3) it plays a larger role in CER in regions with a high energy endowment; and 4) the impact of GGI on CER is heterogeneous in geographical regions, city sizes, and economic development levels. This study makes policy recommendations for reducing CEs, including intensifying GGI and playing its investment-pulling role, thereby increasing the investment related to improving energy efficiency and total factor productivity and promoting government intervention in areas with high energy endowments.

The trade-off between environment and economy has been one of the hot topics discussed in academia, but there are many disputes among them. Based on the micro data of Chinese listed companies from 2016 to 2020, this paper uses the shock of the Environmental Protection Tax Law (EPTL) in 2018 as a quasi-natural experiment. Our Differences-in-Differences (DID) method is used to study the impact of the environmental governance pressure caused by the EPTL on firms’ total factor productivity (TFP). The conclusions suggest that: 1) The EPTL has significantly improved heavily polluting enterprises’ TFP, and this finding remains stable after a range of robustness checks. 2) The subgroup analysis shows that. The smaller the size of the administrative expenses paid by the enterprises, the larger the effect of the EPTL on firms’ TFP; the positive effect of the EPTL on the TFP of heavily polluting enterprises is not pronounced in the sample of small-scale enterprises; when the degree of financial slack is small, the effect of the EPTL on firms’ TFP is greater; the effect of the EPTL is greater when the enterprises are located in provincial capital and municipalities. 3) Meanwhile, we also find that promoting firm value and stimulating green innovation may be the potential mechanisms of the EPTL affecting firms’ TFP. This paper provides experience summary for the firms’ high-quality development under the background of government environmental governance.

In recent years, Chinese manufacturing enterprises have competed to chase the wave of the "digital revolution"; digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises' export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region, and industry. Furthermore, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises and form a "masking effect" on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences and provides certain guidance for enterprises to implement the strategy of digital transformation. [ABSTRACT FROM AUTHOR]

As the world's most populous developing country and the world's largest carbon emitter, China has already completed its 2020 Intended National Determined Contribution set out in the Paris Agreement. It achieved this result by adopting a dual-goal strategy of economic growth and reducing carbon emission, that is, low-carbon economic growth. Based on both parametric and nonparametric methods, quantitative and qualitative conclusions about China's low-carbon economic growth are presented. It is found that since the beginning of this century, China has maintained an annual growth efficiency of 1% in low-carbon total factor productivity (TFP) and low-carbon technological progress rate. The Eastern region has leading advantages in low-carbon TFP, low-carbon technology advancement, low-carbon efficiency, and low-carbon technology revolution. It has the potential to be the first to reach its CO2 turning point. The inefficiency ratio of labor and CO2 is higher at the national level and in the Eastern region, with the two accounting for about seven tenths and eight to nine tenths, respectively. The difference is that at the national level, the input–output inefficiency is similar, and the inefficiency in the Eastern region is more from the input side, about eight tenths. At the present stage, China is still lenient in the implementation of low-carbon environmental regulations. In the future, the adjustment of low-carbon policy should pay attention to regional heterogeneity, focus on reducing labor and CO2 inefficiency, and be more stringent in policy implementation. [ABSTRACT FROM AUTHOR]

This article estimates the total factor productivity (TFP) growth of Chinese manufacturing firms and quantifies how international sourcing and trade liberalization affect TFP growth. To this end, we estimate stochastic frontier production that decomposes TFP growth into technical changes, returns to scale, and technical efficiency changes. Furthermore, we consider two channels through which external factors affect TFP growth: technical change and technical efficiency change components. We measure international sourcing and trade liberalization by foreign value-added shares and input tariffs, respectively. Several novel findings emerge. First, international sourcing and import tariff reduction positively impact TFP growth by improving technical changes and technical efficiency. Second, international sourcing has a negative effect on the technical changes of processing importers, while it has positive effects on the technical change and technical efficiency change of ordinary importers. Third, input tariff reduction has a substantial and positive impact on the technical efficiency change of processing importers and the technical change of ordinary importers. [ABSTRACT FROM AUTHOR]

It is well established that improving livestock productivity has the potential to boost food security, income, and employment for rural communities. While the technical efficiency of the livestock sector has been extensively studied in both developing and developed countries, few studies have analysed total factor productivity (TFP) and its components (technical change, technical, scale, and mix efficiency changes). To fill this gap this study specifically analyses the TFP growth of 26 beef cattle producing districts in Botswana using the Färe-Primont index. This index does not only allow us to understand how TFP varies amongst the districts but also how it has changed over time (between 2007 and 2014) as well as examining what has been driving that change. We also employ a feasible generalised least squares estimator for panel data to identify sources of productivity and efficiency growth. Results show that livestock TFP increased during the study period, and that this was driven by technological change, whilst efficiency change (TFPE) decreased. Further, we found that the decline in scale-and mix efficiency change (OSME) was largely responsible for the slowdown of TFPE, with a relatively smaller decline in technical efficiency change (OTE) also contributing. Districts with foot and mouth disease (FMD) outbreaks and restricted access to export markets had lower TFP growth whilst proximity to livestock advisory centres (LAC), off-farm income, education and herd size were shown to enhance productivity and efficiency growth. [ABSTRACT FROM AUTHOR]

Recent high dropout and low graduation rates in the South African higher education institutions as well as government funding cuts and the economic uncertainty due to COVID-19 pandemic have heightened the urgency for the higher education sector to improve its productivity. However, empirical evidence on the productivity growth of the sector remains unexplored. To address this gap, we applied a Färe-Primont index approach to a panel data of 22 public universities over an 8-year period to measure total factor productivity (TFP) and its components—technological change, technical, scale and mix efficiency changes. We also used a feasible generalised least squares model to assess the determinants of productivity and efficiency growth. The results show that the average TFP of the sector for the study period was 0.631, led by historically advantaged universities (0.894), whilst historically disadvantaged universities had lower average TFP (0.823). During the period, TFP increased by 3.43%, largely driven by scale and mix efficiency changes (5.32%) and technical efficiency change (0.83%), whilst technical change declined by 1.80%. In terms of university types, the comprehensive universities achieved the largest TFP growth (6.13%) followed by traditional universities (4.85%), and technology universities by 1.41%. TFP growth was positively influenced by student graduation rates, quality of academics and academic-student ratios. Therefore, policy considerations to improve the sector's productivity and efficiency should consider investment on research and development, adoption of teaching and research innovations, re-skilling through training and education and aligning admission policies with staffing. [ABSTRACT FROM AUTHOR]

This paper examines the effects of trade sanctions on the relative demand for skilled labor and wages by using Iranian industrial manufacturing data covering 7 years before and 7 years after the sanction year. The decomposition of the change in the aggregate demand for skilled labor sheds light on the fact that it comes from labor reallocation within industries, not from across industries. The trade sanctions adversely affected both exporters' and non-exporters' total factor productivity; however, non-exporters endured a larger negative impact. As a result of the significant reduction in industries' total factor productivity, the relative demand for skilled labor decreases which results in a decrease in the real wage per-worker as well. Furthermore, exporters, compared to non-exporters, are responsible for more changes in the relative demand for skilled labor, are faster in changing skills, and their change in skills have a greater impact on the real wage per-worker. [ABSTRACT FROM AUTHOR]

This study investigates the effects of market concentration and diversification on firms' performance in the case of the Indian chemical industry. The findings indicate a positive relationship between market concentration and performance measured in terms productivity and profitability. However, firm diversification shows a negative impact on a firm's productivity and but positive impact on its profitability. The study also reveals that market concentration outperformed in comparison to the diversification strategy for the Indian chemical industry. [ABSTRACT FROM AUTHOR]