Total Factor Productivity Growth Research Articles

Differentials in Countries’ Total Factor Productivity and the Factors Influencing Them

The diminishing potential for enhancing productive resources in order to sustain economic growth demands greater emphasis on how efficiently they are used as measured by total factor productivity (TFP). Long-term trends, differences between countries, and macro-level factors were assessed using qualitative and quantitative analysis of economic and financial indicators for a sample of 74 countries from 1978 to 2022. The article confirms that Russia and most other countries have been experiencing a steady downturn in total factor productivity. In some cases, productivity has been falling since the 2008 global financial crisis because key factors changed in the post-crisis period. In particular, growth of TFP has become correlated with increasing fixed investment, a high level of domestic financial development and protection of property rights, and limitation of state intervention in the economy, as well as with following a model of capitalism that allows for a moderate level of state ownership. Those developing countries of Central and Eastern Europe that have consistently implemented market-oriented reforms have also been able to sustain growth. The increasing importance of highly country-specific variables suggests that countries are trying to make greater use of domestic economic policies to support TFP growth and thus counteract the global productivity decline observed by many economists. Although individual countries may succeed in maintaining their growth, such measures are not sufficient to prevent a global slowdown.

External shocks and dynamics of resource use patterns: empirical evidence from the Indian manufacturing sector

While promoting manufacturing growth is imperative to boost economic growth, potential adverse consequences on natural resources and ecology have created sustainability-related concerns and challenges. In India, with the reform processes deepening further and the business environment becoming more market-oriented over the years, the adoption of appropriate measures for sustainable manufacturing growth under such conditions would require a deeper investigation of the underlying dynamics, particularly to address the impacts of external shocks. This is especially true when external shocks alter market dynamics and, hence, input is used significantly in the manufacturing sector. Given this backdrop, the present paper examines how the major external shocks to the Indian economy during in the post-reform era have altered the resource use patterns in selected manufacturing industries. The paper uses secondary data collected from the KLEMS database of the Reserve Bank of India for the period from 1980–81 to 2019–20 and applies descriptive statistics and econometric techniques to address the research objective. It is found that energy intensity, vertical integration, capital intensity, and rate of growth of total factor productivity decreased over the decades, whereas labour productivity experienced an increasing trend in most industries. However, the trends are mixed in the case of material intensity. Further, the regression results indicate significant effects of external shocks on resource use, factor productivity, and structural changes. There are also industry-specific differences in the nature and extent of such changes. Hence, a deeper investigation of the underlying factors and impacts at a disaggregate industry level is necessary to draw more robust insights.

Research on the Impact of Digital Green Finance on Agricultural Green Total Factor Productivity: Evidence from China

Green development has become one of the important concepts leading China’s economic developments, and it is extremely meaningful to boost the continuous growth of agricultural green total factor productivity (AGTFP) to achieve the construction of a powerful agricultural country. Using China’s provincial data from 2011 to 2020, this manuscript calculates AGTFP through the SBM–GML model, and the digital green finance (DGF) through a comprehensive indicator system. The double fixed-effect model, quantile model and spatial Durbin model are used for in-depth study of the benchmark influence, the nonlinear effect and spatial spillover effect of DGF on AGTFP. The main research conclusions of the article are as follows: (1) DGF is significantly conducive to the improvement of AGTFP. Along with the continuous growth of AGTFP, the promoting effect of DGF has gradually increased. (2) In terms of impact path, green finance can properly promote the growth of AGTFP, while the role of the degree of digitization is not very significant. Meanwhile, the main channel for DGF to promote AGTFP is through green technology efficiency. (3) The impact of DGF on AGTFP varies spatially, while the role is more effective in regions with a higher degree of economic development and well-developed modernization. (4) There is a spatial spillover effect of DGF’s impact on AGTFP, which means that DGF can simultaneously promote the growth of AGTFP in local regions and neighboring regions.

Mitigating excessive financialization or promoting innovation? Productivity effects of China's carbon emission trading scheme

AbstractThe success of the carbon emissions trading scheme (ETS) in fostering a mutually beneficial outcome for both the economy and the environment depends on its ability to enhance total factor productivity (TFP). We investigate the diverse implementation of this market‐based environmental policy across Chinese provinces using a staggered Difference‐in‐Differences model. Our study delves into the mechanisms of the ETS, particularly focusing on financialization and innovation, utilizing listed companies in Chinese stock markets as our research sample spanning from 2009 to 2022. Our analysis shows several key findings: (1) ETS facilitates the growth of TFP in micro‐firms, positively influencing other listed companies within the same sector and city. However, its impact on TFP is notably weaker in regions with robust environmental information disclosure and stringent environmental regulations. (2) The ETS helps alleviate resource misallocation stemming from excessive financialization of firms, prompting them to reallocate investments from financing activities to production and operation activities, thus enhancing TFP. (3) Contrary to expectations, the ETS does not directly influence TFP through enhancing firm innovation ability; instead, it encourages directed technical innovation toward green technology over digital technology. This study highlights the effectiveness of the ETS in promoting firm development and sheds light on resource management practices within firms.

World Productivity: 1996–2014

We use a new growth accounting method to quantify the drivers of world total factor productivity (TFP) growth during 1996–2014 and uncover four main results. World productivity growth is volatile from year to year. This mainly reflects reallocation of labor across country-industries. The contribution of country-industry level productivity growth to world productivity is relatively constant over time. This constancy masks that the increased importance of emerging economies offsets a productivity slowdown in advanced economies. After 2008, this offsetting effect dissipated and world TFP growth declined. These conclusions are robust to the inclusion of markups in the analysis. (JEL E23, E32, O30, O47)

Digital transformation and its effect on resource allocation efficiency and productivity in Chinese corporations

Digital technology improves the capacity for collecting, processing, and sharing information, enabling corporations to optimize resource allocation. Based on data from Chinese A-share listed corporations between 2008 and 2020, the study investigates the relationship between digital transformation and resource reallocation. The findings indicate that digital transformation significantly enhances the allocation efficiency of capital and labor. Specifically, doubling the frequency of digital transformation terms can correct capital input deviation by approximately 9.5 % and labor input deviation by around 7.3 %. The enhancement primarily stems from mitigating excessive input inefficiencies, while demonstrating insignificant effects on underinvestment scenarios. Moreover, these results are consistent across an array of robustness tests, including Bartik IV and difference-in-differences strategy using the “Broadband China” policy as a quasi-natural experiment. Mechanism analysis reveals that alleviating external information frictions and enhancing internal information utilization constitute the primary channels through which digital transformation fosters resource allocation efficiency. Furthermore, digital transformation not only raises the overall total factor productivity (TFP) through resource reallocation but also directly fosters the growth of corporate TFP.

Rising Tides of Knowledge: Exploring China’s Higher Education Landscape and Human Capital Growth

AbstractThis study examines the status of human capital in China’s higher education system by analyzing the quantity of higher education institutions as a metric. The results show a general enhancement in human capital in all regions, along with an optimized structure. This is demonstrated by a decline in the primary education demographic, a consistent growth in secondary education, and a rapid surge in the higher education demographic. The percentage of junior college students has remained steady, whereas the ratios of undergraduate and graduate students have been consistently increasing. The Malmquist index method is used to analyze changes in total factor productivity (TFP) among provinces and regions by breaking it down into technical level and efficiency changes. From 2005 to 2010, there was a general increase in total factor productivity (TFP) and technical proficiency, although technical efficiency showed only slight enhancement. TFP and technical level growth decelerated from 2011 to 2020, while technical efficiency stayed above 1. These findings indicate that China’s total factor productivity (TFP) growth is mainly driven by technological advancements, with minimal improvements in technical efficiency.

Complexity and FDI in market-dependent economies: The hidden effect of industrial offshoring

AbstractThis study examines the complexity in the Eastern European economies, with a focus on the role of foreign direct investment (FDI). Despite transitioning to market economies, these countries remain economically fragile and dependent. Their lower technological complexity and reliance on foreign capacity make them vulnerable. However, some countries like Austria and Poland demonstrate successful integration of production and innovation. The analysis shows FDI has a limited impact on developing complex knowledge but contributes positively to economic complexity. Results also indicate that in the long-term, economic and technological complexity does not lead to accelerated total factor productivity growth, contrary to complexity literature. Combining labour with innovation, safeguarding local industries, and prioritizing education and research are more effective approaches. The study clearly shows how Hungary is stuck in an “assembler trap.” It also finds that the gap between economic and technological complexity negatively affects liberal democracies.

The impact of new digital infrastructure on green total factor productivity

As a new engine driving economic development, new digital infrastructure plays a significant role in enhancing green total factor productivity. Based on 2011–2020 panel data covering 30 Chinese provinces, this study empirically investigates the effects and mechanisms of new digital infrastructure on green total factor productivity. The results show that new digital infrastructure can significantly improve regional green total factor productivity, and this conclusion remains valid after a series of robustness tests and regressions of instrumental variables. Further mechanism research shows that new digital infrastructure indirectly promotes the growth of green total factor productivity by improving capital misallocation and driving technological innovation, while there is no mediating mechanism of labor misallocation. In addition, there is significant heterogeneity in the impact of new digital infrastructure on green total factor productivity. Especially during periods of high government attention, in the eastern regions, and in areas with higher levels of human capital, the positive incentive effect of new digital infrastructure is more significant. This study provides empirical evidence and policy references for promoting and amplifying the green growth effects of new digital infrastructure.

An evaluation of the regional heterogeneity of museums' operational efficiency and productivity changes across Chinese provinces

Museums are critical in safeguarding cultural heritage and cultivating community educational opportunities. This research aims to evaluate operational efficiency (OE), the impact of technological change on total factor productivity change (TFPC), and the regional heterogeneity of museum performance in three regions and 31 provinces across China. To this end, the study employed DEA-SBM and the Malmquist Productivity Index to gauge OE, TFPC, and determinants of TFPC (efficiency change or emerging technologies change) across 31 provinces for 2012–2021. Results reveal that the average OE of the Chinese Museum is 0.8394. It shows a 16.06 % growth potential in the operational efficiency of Chinese Museums. Further, the OE of Chinese Museums declined over the study period from 0.8965 in 2012 to 0.8088 in 2021. Beijing, Fujian, and Hunan are ranked top with a Museum's OE Score of 1. The average MI score of Chinese Museums is 0.9744, and technology change is the main determinant of Decline in productivity change as EC = 0.9992 is greater than TC = 0.9846. The MI of Liaoning, Shanghai, Ningxia, Jiangxi, Chongqing, Sichuan, Guangdong, and Tianjin is over 1, indicating growth in total factor productivity over the study period. The eastern region of China shows higher operational efficiency and total factor productivity scores of museums than the central and western regions. The results of the Kruskal-Wallis test proved that a statistically significant difference exists among different regions of China for the OE, MI, EC, and TC of museums.

Exploring the Role of Digital Economy in Enhanced Green Productivity in China’s Manufacturing Sector: Fresh Evidence for Achieving Sustainable Development Goals

Confronted with challenges such as escalating demand, expanding energy consumption, and emissions, China’s manufacturing sector stands at a pivotal juncture on its path towards sustainable development. Against the backdrop of a new wave of technological revolution and industrial transformation, exploring how the digital economy can foster growth in green total factor productivity (GTFP), particularly amidst technological diversification, holds significant importance for realizing sustainable development objectives. This study employs the system generalized method of moments (System GMM), encompassing 30 provinces in China, to delve deeply into the notable and dynamic correlation between the development index of the digital economy and GTFP. The findings reveal that the advancement of the digital economy significantly influences GTFP, underscoring its direct and enduring impact on green productivity. Key mechanisms through which the digital economy promotes green productivity are identified, including resource optimization, green technological innovation, data-driven decision making, and the transformation of environmentally sustainable behaviors. By bridging gaps in existing literature, this study integrates economic and environmental perspectives, emphasizing the necessity for formulating digital innovation policies aligned with environmental objectives. It provides richer insights into the role of the digital economy in enhancing GTFP, accentuating the potential of digital technologies in driving green transformation. With its holistic approach, this study combines economic efficiency with environmental sustainability, offering crucial guidance for policymakers and industry stakeholders in crafting sustainable development strategies.

Digitalization as a Factor of Production in China and the Impact on Total Factor Productivity (TFP)

In the digital transformation era, digitalization integrates deeply into production, bolstering output efficiency and economic value. Through stochastic frontier analysis (SFA), this research positions digitalization as an input in the production function, dissecting its elasticity impact on capital, labor, and output. The effect of digitalization on total factor productivity change (TFPC) is explained by comparing TFPC with and without digitalization. Findings reveal that digitalization’s integration into economic growth displays a U-shaped trajectory, with initial productivity setbacks transitioning to long-term benefits as industries adapt. The periodic complementarity and substitution between digitalization and labor, along with a weak substitution relationship with capital, illustrate that, as a production factor, digitalization dynamically interacts with other factors, both complementing and substituting them. This dynamic interplay highlights the intricate role that digitalization plays within the production function. Furthermore, digitalization has played a crucial role in China’s TFP growth, which also highlights the lack of other technological progress. Meanwhile, the pace of digital transformation presents scalability challenges, evident in the fluctuating scale efficiency change (SEC). Policymakers are advised to address these early stage challenges through supportive measures, ensuring smoother digital transitions. Concurrently, industries should embrace this non-linear transformation, emphasizing adaptability to maximize digitalization’s long-term advantages.

Carbon productivity growth in China’s transportation industry: empirical analysis using a global Malmquist-Luenberger productivity index based on an endogenous directional distance function

In China, transportation is one of the fastest-growing industries for CO2 emissions, so scientifically measuring the carbon total factor productivity growth of this industry could provide accurate guidance to achieve sustainable development. To this end, this study proposes an endogenous directional distance function (DDF) approach using a common directional vector based on satisfaction degree, and then integrates it with the global Malmquist-Luenberger productivity index (GMLPI) to measure the carbon total factor productivity growth. We employ this novel endogenous DDF-based GMLPI approach to evaluate and decompose the carbon total factor productivity growth of China’s 30 provincial-level transportation industries from 2010 to 2020. The empirical results show that the carbon total factor productivity of 14 provinces improved during 2010–2020, and 28 provinces from 2015 to 2020. Efficiency improvement and technological progress have become the joint drivers for the carbon total factor productivity growth. Targeted policy implications are provided.

Does e‐commerce infrastructure increase enterprise productivity? Evidence from China's e‐commerce demonstration city

AbstractThis study leverages the National E‐commerce Demonstration City Pilot (NEDC) as a quasi‐natural experiment in e‐commerce infrastructure development. Utilising panel data from non‐financial firms listed on China's A‐share market from 2005 to 2022, we pioneered employ a multi‐period difference‐in‐differences (DID) approach to explore the direct and indirect effects of e‐commerce infrastructure on total factor productivity (TFP). Our findings reveal that: (1) The NEDC initiative significantly enhances firm‐level TFP. This result remains robust after addressing endogeneity issues through IV‐2SLS and propensity score matching and difference in differences methods and undergoing a series of robustness tests. (2) Channels tests indicate that the NEDC policy indirectly boosts firm TFP primarily by fostering technological innovation and augmenting human capital. (3) Heterogeneity analysis demonstrates that the NEDC policy effectively stimulates TFP growth in state‐owned enterprises, firms with high equity concentration, manufacturing and low‐tech industry firms. The policy's impact is more pronounced in cities with high administrative levels, in the eastern and central cities, and in cities with superior traditional infrastructure. The empirical evidence provided by this study not only supports the role of e‐commerce infrastructure in driving economic growth but also offers valuable insights for bridging the income disparity between developing and developed nations, and mitigating income inequality.

The Productivity Slowdown in Advanced Economies: Common Shocks or Common Trends?

This paper reviews advanced‐economy productivity developments in recent decades. We focus primarily on the facts about, and explanations for, the mid‐2000s labor‐productivity slowdown in large European countries and the United States. Slower total factor productivity (TFP) growth was the proximate cause of the slowdown. This conclusion is robust to measurement challenges including the role of intangible assets, rankings of productivity levels, and data revisions. We contrast two main narratives for the stagnating TFP frontier: The shock of the Global Financial Crisis; and a common slowdown in TFP trends. Distinguishing these two empirically is hard, but the pre‐recession timing of the U.S. slowdown suggests an important role for the common‐trend explanation. We also discuss the unusual pattern of labor productivity growth since the start of the Covid‐19 pandemic. Although it is early, there is little evidence so far that the large pandemic shock has changed the slow pre‐pandemic trajectory of labor‐productivity growth.

Artificial intelligence and outward foreign direct investment: Evidence from China

We investigate the impacts of robot adoption (a representative form of artificial intelligence) on outward foreign direct investment (OFDI) by firms in China. First, we construct a unique firm-level dataset of A-share listed firms and conduct empirical analysis by adopting a staggered difference-in-differences (DID) strategy. Second, we find that changes in robot adoption on both the extensive and intensive margins encourage firms to conduct more OFDIs. Specifically, robot adoption has positive effects on multidimensional categories of OFDI but has no significant impact on buying OFDI. Third, we explore the underlying mechanism to show that the rise in output and growth of total factor productivity (TFP) matter. Fourth, we conduct a series of empirical tests to check robustness and obtain consistent results. Finally, we analyze the heterogeneous effects and find that adoption firms with state-owned ownership or higher profit tend to send more OFDI projects, especially to the Organization for Economic Co-operation and Development (OECD)-rich countries. Our findings elucidate the impact of robot adoption on OFDI at the firm level in developing and transition countries.

The role of inefficiency in a productivity puzzle: Regional evidence for Great Britain

AbstractFrom around the 2008 crisis there has been a marked slowdown in UK productivity. This has been referred to as a productivity puzzle as there is no consensus on the key explanations for this slowdown. Using data for all the 168 International Territorial Level 3 areas in Great Britain (2004–2020), we make two empirical contributions to the literature on this puzzle. First, we are the first to analyze this productivity puzzle using a stochastic frontier model to account for technical inefficiency. Second, to aid policymakers we uncover the areas that represent spatial total factor productivity (TFP) growth hubs, spokes, leaders and followers. Of the components of TFP growth (growth rates of technical change, returns to scale and efficiency), we find that Britain's productivity slowdown can be more specifically described as a rise in inefficiency.

Growth Models and Influencing Mechanisms of Total Factor Productivity in China’s National High-Tech Zones

Total factor productivity (TFP) serves as a crucial indicator of high-quality development, showcasing a region’s utilization of technological advancements and innovative strategies to enhance production efficiency. With China’s regions experiencing varying levels of development, the paths to high-quality development in NHTZs also exhibit significant disparities. Analyzing data from 88 NHTZs between 2011 and 2018, this research aims to explore differences in TFP growth models and the mechanisms influencing these models. Employing stochastic frontier analysis (SFA) and the Tobit model, the study identifies three TFP growth models: technology-led, multi-efficiency improvement, and scale efficiency compensation. While factors such as capital accumulation, overseas market participation, and patent output moderately hinder TFP growth, innovation platforms, R&D investment, and overseas talent acquisition significantly contribute to TFP enhancement. Distinguishing itself from existing TFP studies, this paper focuses on NHTZs, highlighting their role in regional high-tech industry development. It introduces three TFP growth models and their characteristics while also uncovering influencing factors for each model. This research offers valuable insights into regional disparities in high-quality development and contributes to understanding TFP growth dynamics in NHTZs.

Canadian productivity growth: Stuck in the oil sands

AbstractWe study the behaviour of Canadian Total Factor Productivity (TFP) growth over the past 60 years. We find that the observed stagnation during the last 20 years is accounted for entirely by the oil sector. Higher oil prices made capital‐intensive sources of oil like the oil sands viable to extract on a commercial scale. However, the greater input required per barrel of oil slowed TFP growth. Comparing Canadian TFP growth with that of the United States and Norway reinforces these results. However, our result should not be interpreted to carry any welfare implications.

Digitalization as a determinant of economic policy choice: Russian realities and world experience

The article considers digitalization as a new general purpose technology and its impact on economic growth and economic policy in the world and Russia against the background of the so-called “productivity paradoxes” and economic shocks of 2020—2023. The importance of accelerating the growth of total factor productivity in Russia through the introduction of advanced digital technologies is shown. The world experience in assessing the impact of digital information and communication technologies on economic growth is briefly described, and an adapted methodology for assessing macroeconomic effects of economic policy, previously used by experts from the OECD and the Ministry of Economic Development of Russia at the level of country groups, is proposed and tested on a panel of Russian regions. The authors calculated the original series of contributions of labor, capital and total factor productivity to the GRP growth of Russian regions for the period 2011—2020. This makes possible to compare the benefits of digitalization and the rate of accumulation of digital capital in Russia and in other countries . The article discusses the desirable parameters of short-term macroeconomic stabilization tools and some aspects of developing the national innovation system.