Total Factor Productivity Growth Research Articles

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.

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.

Decomposition and Driving Factors of Total Factor Productivity of Food Crops in the Yellow River Basin, China

The urgency of enhancing agricultural productivity within the Yellow River Basin cannot be overstated, given its critical role in ensuring food security amidst the challenges posed by climate change, natural disasters, and the increasing demand for food crops. Utilizing panel data from nine provinces within the Yellow River Basin for the period 2001 to 2020, this study examines the temporal characteristics and spatial distribution of Total Factor Productivity (TFP) for key grain crops—namely wheat, corn, and soybean—through the application of the Malmquist index which can be decomposed through the DEA-Malmquist index methodology. The empirical results demonstrate that TFP growth rates for these crops have exhibited significant phase variations, with soybean recording the highest TFP growth rate in the basin. Additionally, this study underscores marked regional disparities in soybean productivity. TFP decomposition reveals that the primary drivers of TFP improvement across these crops are attributed to technical progress, with gains in overall technical efficiency largely due to scale efficiency enhancements, whereas pure technical efficiency has shown limited progress. Regional analysis indicates that Inner Mongolia leads in TFP growth for all crops, while Ningxia, Sichuan, and Shaanxi lag behind in wheat, corn, and soybean. Additionally, our analysis delineates natural disasters as a significant barrier to Total Factor Productivity (TFP), notably obstructing technological advancements in wheat cultivation. The investigation further reveals a positive relationship between regional per capita income and the growth of wheat TFP, in contrast to a negative relationship with the TFP growth of corn and soybeans. Moreover, investing in agriculture, forestry, water management, and road infrastructure supports the growth of wheat TFP, while urbanization levels pose constraints. Conclusively, an uptick in annual rural electricity usage, along with improved per capita postal and telecommunication services, exerts a favorable influence on TFP for corn and soybeans.

How Important is Mobile Broadband Latency for Total Factor Productivity Growth?

This paper investigates the relationship between the log change in mobile broadband latency and total factor productivity (TFP) growth based on data for 130 countries. It finds that there is a strong negative correlation between TFP growth and one year lag of latency growth in OECD countries. The interpretation of the findings is that a 10 percentage points decrease in the growth of latency in period t-1 is associated with an increase of 0.3 percentage points in TFP growth. The findings are in accordance with the framework of General Purpose Technologies that suggests that the impact of new technologies often appear with a lag. Moreover, no relationship is found for the total sample or for non-OECD countries. One possible explanation could be that OECD countries have reached a higher maturity in digitalisation and automation in production processes and thus are able to take advantage of the benefits of lower latency.  

Can Technological Advancements be Effective for the Economic Value of the Companies? Insights from the DSE Listed Food and Allied Companies

Purposes: Adopting technology in the production process increases the overall efficiency of inputs used in the production, and enhances a firm's economic value. Methodology: This study tries to explore the impact of technology on firm performance from 8 listed Food and Allied companies spanning 2015-2021 listed on DSE. Total factor productivity (TFP) is an inclusive measure that apprehends the contribution of all aspects that improve the efficiency of production including technology. Therefore, the contribution of technical advancement to the firm is captured by TFP, applying the Solow residual method. TFP is the main study variable and some other control variables, such as tangibility, liquidity, firm size, and growth; long-term leverage ratio and net debt tax shield are used as exogenous variables to increase the robustness of the model and improve the value of both the firm performance ROA and ROE. Results: Finally, this study concluded that investment in technology in the food and allied sectors has a notable impact on a firm’s performance. Therefore, the study indicates that economists, policymakers, and business management can use TFP growth as an indicator for making their long-term decision policy and increase the overall sustainable economic productivity, growth and efficiency of the firm and can contribute to accelerating the economic growth of the country.

Factors Influencing Economic Growth in Nigeria: A Growth Accounting Framework Analysis

This research examines the drivers of economic expansion in Nigeria from 1960 to 2017, employing the growth accounting methodology based on the classical neoclassical production function. The focus is on assessing the contributions of capital, labor, and total factor productivity (TFP) to Nigeria's economic growth. Furthermore, to determine the interrelations among capital, labor, TFP, and economic growth, correlation coefficients among these variables were calculated. The correlation analysis indicated positive associations between the growths of capital, labor, TFP, and economic growth. Moreover, findings from the growth accounting analysis highlighted capital as the primary contributor to economic growth in Nigeria throughout 1961-2017. In specific sub-periods, capital remained the dominant growth driver in the initial phase (1961-1980), while labor took precedence in the 1981-2000 period, with capital following and TFP growth showing a decline, as evidenced by its negative contribution. Nonetheless, TFP emerged as the critical factor driving economic growth from 2001-2017. Consequently, the study suggests the implementation, maintenance, and enhancement of policies that promote physical capital, human capital, and technological advancements through both domestic and foreign investments, recognizing their essential roles in fostering economic growth and development.

Total Factor Productivity Growth in the Indian Food Processing Industry: A Non-parametric Investigation

This study analysed total factor productivity growth (TFPG) in the Indian food processing industry in the organised sector. The results showed that TFPG in this industry resulted from technical progress and that the role of change in technical efficiency was insignificant. Therefore, for sustainable output growth, the application of new technologies must be followed by adaptation. In this context, policymakers should consider sub-sectoral heterogeneity when designing policies for the Indian food processing industry so that the rates of applying technology and its adaptability can be matched for each industry sub-sector. Thus, the study offers a strong note of caution about investments in technological improvements.

Sources of Algeria's economic growth, 1979–2019: Augmented growth accounting framework and growth regression method

This paper examines the sources of economic growth in Algeria, studying the key drivers of their slow and weak economic performance, during the period of 1979–2019 from the perspective of the augmented growth accounting framework and the growth regression method. More specifically, the paper uses the augmented growth accounting framework to decompose the aggregate growth of an individual economy to determine the contribution of various inputs and the total factor productivity. The growth regression method, then, links the growth performance of a given country to a set of economic, social, and institutional variables to identify the deep drivers of its economic growth. Results of the accounting framework show that Algeria's growth performance has been weak and modest for decades. This is due, mainly, to labor growth with weak gain in capital accumulation and to sharp losses in the total factor productivity growth. Furthermore, results of the econometrics study stress the importance of the political, institutional, and economic variables and the macroeconomic stability as potential factors that may affect growth in Algeria. These findings highlight the need for policymakers to identify and to target these determinants to improve the long‐run economic growth in Algeria.

The regional pervasiveness of local productivity shocks on macroeconomic output in Europe

ABSTRACT This paper studies inter-regional technology spillover in EU-28 countries and shows how regional total factor productivity (TFP) shocks shape aggregate productivity in Europe. This paper provides evidence that several regions play a significant role as common factors in the production function of almost every other region. We provide a procedure to identify and test these regions through inter-regional trade flows. In our estimations, the ten most pervasive regions out of 272 NUTS 2 regions explain about 12% of the total factor productivity growth in the EU-28 countries. Significant heterogeneity exists in the region’s ability to absorb imported knowledge among these countries. Local knowledge stock’s contribution is limited compared to imported knowledge due to a regional disparity in R&D distribution. Our work contributes to understanding the granular features of spatial macroeconomics, with a particular focus on inter-regional trade flows and knowledge spillovers.

The Impact of Port Total Factor Productivity on Carbon Dioxide Emissions in Port Cities: Evidence from the Yangtze River Ports

This paper investigates the relationship between port productivity and carbon dioxide (CO2) emissions in port cities. The study initially employs the global Malmquist productivity index (MPI) to measure productivity growth in 16 major inland ports along the Yangtze River, obtaining data on the ports’ total factor productivity (TFP). Through an analysis using the panel data model with two-way fixed effects, we find a positive correlation between the improvement of port TFP and the increase in CO2 emissions in port cities. Further panel quantile regression analysis reveals the heterogeneity of this impact, especially in cities with medium and higher CO2 emissions, where the positive effects of TFP on carbon emissions are particularly significant. The study also indicates a threshold effect of port size in the relationship between TFP and CO2 emissions: in smaller ports, the impact of TFP improvement on CO2 emissions is less significant; however, once the port size exceeds a certain threshold, the growth in TFP significantly promotes an increase in CO2 emissions. These findings provide theoretical justification and decision-making references for policymakers to adopt effective measures to mitigate the growth of CO2 emissions while promoting the efficiency of port production.

UNCERTAINTY, LONG‐RUN, AND MONETARY POLICY RISKS IN A TWO‐COUNTRY MACRO MODEL

AbstractWe study the currency risk premium and the forward premium bias in a two‐country New Keynesian model with production, no physical capital, and recursive utility. Monetary policy follows an interest rate feedback rule and exogenous total factor productivity (TFP) growth follows a long‐run risk process with stochastic volatility, which we estimate from data. With cross‐country heterogeneity in TFP and monetary policy, reasonable currency risk premia emerge under complete and incomplete markets but the forward premium bias is trivial. We diagnose the challenge faced by this fairly standard production model to explain the forward premium bias.

Natural resources utilization efficiency evaluation, determinant of productivity change, and production technology heterogeneity across developed and developing G20 economies

Efficiently utilizing natural resources (NRs) and enhancing their productivity growth are crucial factors for sustainable economic growth in major global economies. Further production technologies heterogeneity among developed and developed G20 countries is vital to natural resource utilization efficiency (NRUE). To this end, the estimation of NRUE, natural resources total factor productivity, and technological gap ratio (TGR) is worth investigating. This study employed Data Envelopment Analysis (DEA) Super-SBM, Meta-frontier analysis, and the Malmquist productivity index to evaluate NRUE, TGR, and productivity changes among G20 countries from 1995 to 2020. The average Natural Resource utilization Efficiency (NRUE) among G20 countries is 0.7071, indicating an improvement potential of around 29.29% in natural resource conversion. Developed G20 economies have a natural resource utilization efficiency (NRUE) of 0.9528, higher than that of the NRUE (0.506) of developing G20 countries. Developed countries have a TGR of 0.9962, which is significantly higher than the TGR of developing countries at 0.6746, indicating a significant gap in production technology. Total factor productivity growth of 0.8 % was witnessed in developed countries while developing countries demonstrated a decline of 0.6 percent in Total Factor Productivity Change (TFPC) over the study period. Analyzing the decomposition of TFPC reveals technological change as the predominant factor influencing productivity change in G20 economies instead of efficiency changes. A Mann-Whitney U test has proved the existence of significant statistical differences in average NRUE, TGR, and technological change (TC) levels between developed and developing G20 countries.

Structural change, labour reallocation, and productivity growth in post-reform China

Abstract Why has the structural bonus been so small during China’s post-reform era? This article explains the puzzle by exploiting the heterogeneity in structural-change patterns across Chinese provinces. Using an original database covering production and factor inputs in 8 sectors and 31 provinces over 1993–2016, I show only those provinces where labour was reallocated from agriculture to manufacturing and services benefited from a structural bonus on labour productivity growth. In the other provinces, this structural-change effect was minimal or negative. Regarding the structural-change effect on total factor productivity (TFP) growth, I find both labour and capital reallocation played a limited role. Labour reallocation has little potential in boosting aggregate TFP growth, as marginal labour returns are similar across sectors. Capital reallocation has a far greater potential but remains restrained, suggesting substantial reallocation frictions. China’s TFP growth is mostly explained by within-sector technological progress, which has been dissipating since 2008, leading to declining TFP growth.

New evidence of the driving forces behind Brazil's agricultural TFP growth—A stochastic frontier analysis with climatic variables and land suitability index

AbstractUsing panel data from 510 Brazilian micro‐regions in three census years (1995, 2006 and 2017), this study presents a productivity decomposition for the Brazilian agricultural sector using stochastic production frontier methods that account for the effects of rainfall, temperature and the land suitability index. We also calculated the total factor productivity (TFP) index and decomposed it into technical efficiency, technological change, scale efficiency and environmental efficiency. This article thus provides a new and more realistic assessment of recent Brazilian agricultural productivity growth. In recent decades, Brazilian agriculture has become widely known for presenting fast productivity growth; however, our results suggest that a lower TFP growth rate than previous estimates (1.96% per annum) and the overall effects of climate change could potentially compromise Brazilian agricultural TFP growth in the long run. Our findings might thus generate insights for agricultural and regional policies to increase efficiency in the sector and promote sustainable agricultural development in Brazil, which will contribute to the sector's competitiveness in international markets, the country's social and economic welfare, and environmental conservancy.

Banking sector reforms in a challenging environment: An emerging financial market experience

The long-lasting impact of reforms on financial institutions in the presence of country level risks and uncertainties may be unclear but has been rarely investigated. By using more than two decades of Pakistani banking industry data covering a period of uncertain policies and volatile political and economic environment alongside severe security threats due to terrorism, this study examines technical change, scale effect, and total factor productivity growth. Our estimates show that despite deep economic and regulatory reforms spreading over a decade, country level risks and uncertainties led to no longer run technological progress and productivity growth. This made the long-run outcome of broader reforms in the presence of a number of uncertainties less satisfactory and did not help materialize the true benefits of reforms. Change of ownership through privatization contributed positively in achieving technological progress and productivity growth, but this limited positive effect faded subsequently. Interestingly, the negative impact of risks and uncertainties is more severe for domestic privately owned and foreign-owned banking firms with parent institutions based in other than Western and developed countries. More specific analysis of the individual uncertainties and related risks shows that although economic, legal, and security-related risks and uncertainties are important for all firms in determining the outcome of reforms, increased uncertainty with corruption perception, law & order conditions, and investment climate in particular impacts more domestically owned firms.

Financial resources utilization efficiency in sports infrastructure development, determinant of total factor productivity growth and regional production technology heterogeneity in China

Despite China's heavy investment in sports infrastructure development in the last decades, the financial resources utilization efficiency (FRUE), regional technological gap (TGR), and total factor productivity change (TFPC) in sports infrastructure development are undiscovered and worth investigating. To this end, this study employed DEA-SBM, Meta-frontier analysis, and Malmquist productivity index on the data set of 31 Chinese provinces and 3 regions for the years 2014–2021 to gauge the FRUE, TGR, and TFPC in sports infrastructure development. The results indicate that the average FRUE is 0.4859, with a growth potential of 51.41% in financial resource utilization efficiency for sports infrastructure development. Further Eastern region is more efficient as compared to the Central and western regions. Beijing, Shanghai, Tibet, Hainan, and Guangdong are top performers in FRUE. Further, the value of TGR in the East is 0.9787 which is higher than in Central (0.4977), and Western (0.5821) regions. It indicates that the eastern region contains superior production technology in the development of the sports infrastructure in China. Moreover, the average TFPC value is 1.035 witnessed a 3.5% growth, primarily determined by technological change (TC). As TC = 1.0273 is higher than efficiency change EC = 0.997. The eastern region has a higher average TFPC of 1.048, indicating higher total factor productivity growth in sports infrastructure development. Beijing, Liaoning, Tianjin, Shanghai, and Zhejiang are the top performers in the TFP growth over the study period. Finally, the Kruskal-Wallis test proved the statistically significant difference in three regions of China for FRUE, TGR, and TFPC in sports infrastructure development.