nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2021‒09‒27
fourteen papers chosen by



  1. Intangible Capital and Labor Productivity Growth: Revisiting the Evidence By Roth, Felix; Sen, Ali
  2. State-Level Electricity Generation Efficiency: Do Restructuring and Regulatory Institutions Matter in the US? By Ajayi, V.; Weyman-Jones, T.; ;
  3. Misallocation, Selection and Productivity: A Quantitative Analysis with Panel Data from China By Tasso Adamopoulos; Loren Brandt; Jessica Leight; Diego Restuccia
  4. Mind the financing gap: Enhancing the contribution of intangible assets to productivity By Lilas Demmou; Guido Franco
  5. Do export transitions differently affect firm productivity? Evidence across Vietnamese manufacturing sectors By Ngo, Thanh; Nguyen, Canh
  6. Are Farmers “Efficient but Poor”? The Impact of Crop Choices on Agricultural Productivity and Poverty in Nigeria By Chisom Ubabukoh; Katsushi S. Imai
  7. Are Industrial Robots a new GPT? A Panel Study of Nine European Countries with Capital and Quality-adjusted Industrial Robots as Drivers of Labour Productivity Growth By Kariem Soliman
  8. Key factors behind productivity trends in EU countries By Modery, Wolfgang; Valderrama, Maria Teresa; Lopez-Garcia, Paloma; Albani, Maria; Anyfantaki, Sofia; Baccianti, Claudio; Barrela, Rodrigo; Bodnár, Katalin; Bun, Maurice; De Mulder, Jan; Falck, Elisabeth; Fenz, Gerhard; Lopez, Beatriz Gonzalez; Labhard, Vincent; Le Roux, Julien; Linarello, Andrea; Meinen, Philipp; Moder, Isabella; Oja, Kaspar; Ragacs, Christian; Oke, Roehe; Schulte, Patrick; Justo, Ana Seco; Serafini, Roberta; Setzer, Ralph; Lopez, Irune Solera; Vanhala, Juuso
  9. The Plant-Level View of an Industrial Policy: The Korean Heavy Industry Drive of 1973 By Minho Kim; Munseob Lee; Yongseok Shin
  10. How do environmental regulations affect carbon emission and energy efficiency patterns? A provincial-level analysis of Chinese energy-intensive industries By Ngo, Thanh Quang
  11. An Industrial Organization Perspective on Productivity By Jan De Loecker; Chad Syverson
  12. House prices and misallocation: The impact of the collateral channel on productivity By Sergi Basco; David López-Rodríguez; Enrique Moral-Benito
  13. Zoom in, zoom out: A shift-share analysis of productivity in Switzerland based on micro data By Jean-Marie Grether; Benjamin Tissot-Daguette
  14. The impact of institutional pressures and top management regulations on firm performance By Khai, Dinh Cong; Thanh, Ngo Quang

  1. By: Roth, Felix; Sen, Ali
    Abstract: This contribution analyzes the impact of intangible capital on labor productivity growth across countries at the aggregate and sectoral levels by employing an econometric growth-accounting approach. First, our results show that intangible capital deepening accounts for around 40 percent of labor productivity growth at both the aggregate and sectoral level. Second, we find that this positive impact of intangible capital on productivity growth at both levels of aggregation is driven by investments in economic competencies, the only intangible group not covered in the national accounts. Third, our results reveal deep sectoral heterogeneities regarding investments and productivity effects of different intangible types. These findings have important implications for future EU industrial policies and are directly relevant to the EU's efforts to close its productivity gap with the US.
    Keywords: intangible capital,labor productivity growth,cross-country sectoral panel analysis,manufacturing,market services,EU
    JEL: C23 E22 L16 L60 L80 O47 O52
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:zbw:uhhhdp:10&r=
  2. By: Ajayi, V.; Weyman-Jones, T.; ;
    Abstract: This paper examines the impact of deregulation and the political support for it on the electric power industry using a consistent state-level electricity generation dataset for the US contiguous states from 1997-2014. Recent analyses of productivity growth suggests that institutional factors are important and we wish to study the role of deregulation as a statelevel institutional change through two measures: (a) restructuring and (b) the political support for it, measured by the majority political affiliation of public utility commissions. We find evidence of positive impacts of deregulation (both restructuring and the political support for it) on technical efficiency across the models estimated. Our preferred model which allows for the control for deregulation variables on the mean and variance of the inefficiency shows an average technical efficiency of 73.1 percent. The results of the marginal effects reveal that the impact of deregulation including its political support on inefficiency is negative and monotonic, with the potential reduction of 8.4 percent in the mean of technical inefficiency, thereby suggesting a compelling evidence for generation efficiency improvement via deregulation.
    Keywords: Electricity generation, technical efficiency, marginal effect, restructuring, regulatory institutions
    JEL: C23 D24 L51 L94
    Date: 2021–09–22
    URL: http://d.repec.org/n?u=RePEc:cam:camdae:2166&r=
  3. By: Tasso Adamopoulos; Loren Brandt; Jessica Leight; Diego Restuccia
    Abstract: We use household-level panel data from China and a quantitative framework to document the extent and consequences of factor misallocation in agriculture. We find that there are substantial within-village frictions in both the land and capital markets linked to land institutions in rural China that disproportionately constrain the more productive farmers. These frictions reduce aggregate agricultural productivity by affecting two key margins: (1) the allocation of resources across farmers (misallocation) and (2) the allocation of workers across sectors, in particular the type of farmers who operate in agriculture (selection). Selection substantially amplifies the productivity effect of distortionary policies by affecting occupational choices that worsen average ability in agriculture.
    Keywords: agriculture, misallocation, selection, productivity, China
    JEL: O11 O14 O4 E02 Q1
    Date: 2021–09–16
    URL: http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-707&r=
  4. By: Lilas Demmou; Guido Franco
    Abstract: Intangible assets are an important driver of productivity and ultimately output growth. Yet, despite their aggregate rise in the past decades, productivity has continued to grow modestly in the majority of OECD countries. This is in part because many firms – particularly young and small ones - are often held back from building up intangible assets, as financing their production or acquisition is more difficult than for tangibles. Building on the analytical framework recently developed by the OECD (Demmou, Stefanescu and Arquié, 2019; Demmou, Franco and Stefanescu, 2019) and extending the empirical analysis, the paper provides evidence that easing financing restrictions is particularly beneficial for productivity in sectors that rely more intensively on intangible assets, indirectly pointing to the existence of a “financing gap” due to financial frictions. This aggregate productivity impact reflects both increases in the productivity of each firm and better allocation of labour across firms. Recognizing cross-country differences in the structure of financial systems, the policy discussion focuses on how to make the three main sources of external finance available to firms -- bank lending, equity financing, and direct government support -- more suited to fit the needs of an intangible-based economy. Finally, the paper briefly discusses the extent to which the COVID-19 crisis may have created specific challenges for intangible investment, making policy interventions in these areas more relevant and urgent.
    Keywords: finance, Intangible assets, productivity
    JEL: D24 G30 O30 O47
    Date: 2021–09–28
    URL: http://d.repec.org/n?u=RePEc:oec:ecoaaa:1681-en&r=
  5. By: Ngo, Thanh; Nguyen, Canh
    Abstract: This paper, by exploring the enriched information in annual Vietnamese enterprise surveys from 2010 to 2015, tries to shed light on the causal effect of the various statuses of export transitions on total factor productivity occurring across 20 manufacturing sectors and during various phases of export transition. The empirical results derived from the system GMM estimation provide evidence of causal direction from export transitions to total factor productivity, after controlling for endogenous variables and taking firm heterogeneity into account. Our results indicate that export effects on productivity are highly dependent on specific manufacturing sectors, and on type of export transition. From the perspective of trade and industrial policies, while supporting the creation of new exporters, some issues related to a high level of subsidy and tax incentives by the government to every exporting firm and export-oriented unit in every manufacturing sector seem to be questionable.
    Keywords: Learning-by-exporting; total factor productivity; export persistence; export fluctuation; export striving; manufacturing sectors
    JEL: C23 D21 F14 L60
    Date: 2019–10–06
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:98386&r=
  6. By: Chisom Ubabukoh (Economics School of Social Science, The University of Manchester, UK and Jindal Global Law School, O. P. Jindal Global University, India); Katsushi S. Imai (Department of Economics, The University of Manchester, UK, Research Institute for Economics and Business Administration, Kobe University, Japan)
    Abstract: This paper aims to test the “efficient-but-poor” hypothesis” by estimating the determinants of smallholders’ crop choices and whether their crop choices affect productivity and poverty using the national household panel data in Nigeria. As crop choices are endogenous in the sense that the farmers’ crop choice is also influenced by resulting revenue from the crop, we carry out stochastic frontier analyses with the Greene (2010) correction for sample selection about farmers’ crop choices and find that smallholders are generally efficient in their resource allocations. However, they are not necessarily rational in making their crop choices - defined in terms of the degree of crop’s exportability or commercialization. This is because, even when some crops are found to be more productive than others, the “less productive” crop is often chosen for production. To figure out why, a treatment effects model is employed to estimate farmers’ selection into the choice of a type of crop in the first stage and the impact of their choices on productivity and poverty outcomes in the second. The results show that farmers’ access to free inputs, non-farm income and the use of seeds from the previous growing season are important determinants of crop choice. The choice of tuber and root crops is found to improve productivity and reduce poverty, while choosing highly commercialised crops reduces poverty but does not improve productivity.
    Keywords: Agricultural productivity; Poverty; Crop choice; Stochastic frontier analysis; Treatment effects model; Nigeria
    JEL: D24 I32 N57 O13 O33
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:kob:dpaper:dp2021-17&r=
  7. By: Kariem Soliman (Europäisches Institut für Internationale Wirtschaftsbeziehungen (EIIW))
    Abstract: In recent years, the interest in the field of economic research in studying the effect of robots on economic outcomes, i.e., labour productivity, labour demand and wages, has increased from an individual country perspective as well as for country groups. By using a fixed effects panel modeling approach, this study of nine robot intensive European countries shows that the core characteristics of a general purpose technology (GPT) are already satisfied by industrial robots. In 2019, seven countries in the panel, i.e. Germany, Italy, France, Spain and the UK (top 5), Sweden (7th) and Austria (10th) - in terms of operational stocks - were among the top 10 of robot using European countries (excl. Turkey). Following the understanding of a GPT of Bresnahan/Trajtenberg (1995), six panel regression models were estimated and linked to the four main characteristics of a GPT. Accordingly, two new measures are proposed in this paper; the first one is named the Division of Labour (or DoL) and is constructed by building the ratio of labour productivity inside the manufacturing industry to labour productivity across all industries. The second one is the Robot Task Intensity Index (RTII), which accounts for the number of tasks that a robot was used for in different production processes across the nine European countries. A high level of fulfilled tasks implies a higher quality of robot as the number of potential tasks, which the robot can perform, is an important criterion for the quality of that robot. In accordance with the GPT literature, both measures showed the expected (in) significances. At the bottom line, all six models underlined the economic relevance of industrial robots for the nine European countries included in the analysis and give a strong indication that robots can indeed be seen as a new general purpose technology.
    Keywords: Industrial Robots, General Purpose Technology, Labour Productivity Growth, Robot Task Intensity Index (RTII), Fixed Effects Model, EU KLEMS
    JEL: D24 J24 O11 O14 O33
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:bwu:eiiwdp:disbei307&r=
  8. By: Modery, Wolfgang; Valderrama, Maria Teresa; Lopez-Garcia, Paloma; Albani, Maria; Anyfantaki, Sofia; Baccianti, Claudio; Barrela, Rodrigo; Bodnár, Katalin; Bun, Maurice; De Mulder, Jan; Falck, Elisabeth; Fenz, Gerhard; Lopez, Beatriz Gonzalez; Labhard, Vincent; Le Roux, Julien; Linarello, Andrea; Meinen, Philipp; Moder, Isabella; Oja, Kaspar; Ragacs, Christian; Oke, Roehe; Schulte, Patrick; Justo, Ana Seco; Serafini, Roberta; Setzer, Ralph; Lopez, Irune Solera; Vanhala, Juuso
    Abstract: The aim of this report is to foster a better understanding of past trends in, and drivers of, productivity growth in the countries of the European Union (EU) and of the interplay between productivity and monetary policy. To this end, a group of experts from 15 national central banks and the European Central Bank (ECB) joined forces and pooled data and expertise for more than 18 months to produce the report. Group members drew on the extensive research already conducted on productivity growth, including within the European System of Central Banks and in the context of the review of the ECB’s monetary policy strategy, and worked together to conduct new analyses.After recalling the key facts and figures, the report looks into the predominant drivers of productivity growth in firms, with a focus on technology as a key determinant of aggregate productivity dynamics. It then discusses the main factors behind resource reallocation both across incumbent firms and as a result of the entry and exit of firms. Although productivity is a real-economy phenomenon and its evolution predominantly hinges on the structural features of the economy and national policies, the report also raises the question of the extent to which, and under what circumstances, monetary policy may affect productivity. In addition, it places productivity in a broader perspective by taking into account other important structural trends that are expected to have an impact on productivity in the medium-to-long run, such as globalisation, population ageing, climate change and digitalisation. Finally, the report considers the possible impacts of the coronavirus (COVID-19) pandemic on productivity in EU countries. ... JEL Classification: D22, D24, D61, O33, O47, O52
    Keywords: drivers and policy implications, European Union, Productivity growth
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbops:2021268&r=
  9. By: Minho Kim; Munseob Lee; Yongseok Shin
    Abstract: Does industrial policy work? This is a subject of long-standing debates among economists and policymakers. Using newly digitized microdata, we evaluate the Korean government's policy that promoted heavy and chemical industries between 1973 and 1979 by cutting taxes and building new industrial complexes for them. We show that output, input use, and labor productivity of the targeted industries and regions grew significantly faster than those of non-targeted ones. While the plant-level total factor productivity also grew faster in targeted industries and regions, the misallocation of resources within them got significantly worse, especially among the entrants, so that the total factor productivity at the industry-region level did not increase relative to the non-targeted industries and regions. In addition, we provide new evidence on how industrial policy reshapes the economy: (i) The establishment size distribution of targeted industries and regions shifted to the right with thicker tails due to the entry of large establishments and (ii) the targeted industries became more important in the economy's input-output structure in the sense that their output multipliers increased significantly more.
    JEL: E24 O14 O25 O53
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29252&r=
  10. By: Ngo, Thanh Quang
    Abstract: This study measures the environmental regulation effect and pattern of carbon emission and energy efficiency through data envelopment analysis and econometric estimation. One of the most important ways to achieve a green transition is promoting technical progress through environmental regulation. Though China has witnessed rapid economic growth over the last two decades, the country can improve it further through adopting sustainable green energy and establishing more energy-efficient industries to strike a good balance between economic and social developments. The oil and carbon dioxide emission performances form the most important metrics. This study uses panel data from 30 Chinese provinces from 2008 to 2017 to assess the effect of environmental regulation on energy production. The nonradial directional distance function (NDDF) is used to measure the total factor energy efficiency index (TFEEI). The panel system GMM model, which can effectively address endogenous problems and regional variability, is utilized to research the nonlinear relationship between environmental regulations and EEI under various environmental regulations to study it. The findings reveal a considerably modest total average EEI amount for energy-intensive industries, averaging between 0.55 and 0.58, which is way below the ideal value (i.e., 1). Furthermore, the results of the dynamic panel data model revealed a significant U-shaped relationship between China’s EEI and environmental regulation. The results show that as the values of market-based environmental regulations (MERs) and command and control environmental regulations (CCERs) exceed the corresponding levels, the impact of environmental regulation on the TFEEI increases gradually. This study will aid policymakers in better understanding the efficacy of different levels of environmental regulations to make more educated decisions.
    Keywords: Total factor energy efficiency; High energy-intensive industries; Environmental regulation; Nonradial directional distance function
    JEL: E0
    Date: 2021–08–02
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:109674&r=
  11. By: Jan De Loecker; Chad Syverson
    Abstract: This chapter overviews productivity research from an industrial organization perspective. We focus on what is known and what still needs to be learned about the productivity levels and dynamics of individual producers, but also how these interact through markets and industries to influence productivity aggregates. We overview productivity concepts, facts, data, measurement, analysis, and open questions.
    JEL: D2 L1 L2 L6
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29229&r=
  12. By: Sergi Basco (Universitat de Barcelona); David López-Rodríguez (Banco de España); Enrique Moral-Benito (Banco de España)
    Abstract: This paper empirically investigates the impact of local house price booms on capital misallocation within manufacturing industries. Using the geographic variation provided by the salient Spanish housing boom (2003-2007), we show that manufacturing firms exposed to positive local house price shocks received more credit from banks and their investment grew more intensively when they had a larger proportion of collateralizable real estate assets. We exploit the geographical variation in both house prices and pre-boom urban land supply at municipality level to document that this collateral channel was exacerbated for firms located in urban land-constrained geographical areas where real estate appreciation was larger. The interaction of geographical conditions, that led to heterogeneous housing booms, with the collateral channel on investment resulted in an increasing dispersion of the capital-labor ratio within industries. A simple counterfactual calculation suggests that the misallocation generated by the collateral channel on investment could account for between one-quarter and half of the fall in TFP experienced in the Spanish manufacturing sector over the housing boom.
    Keywords: housing boom, misallocation, collateral channel, productivity
    JEL: E22 E44 O16
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:bde:wpaper:2135&r=
  13. By: Jean-Marie Grether; Benjamin Tissot-Daguette
    Abstract: Using novel data on value added in Switzerland we propose to use a growth rate decomposition technique, in the spirit of shift-share analysis, to analyze the patterns of regional competitiveness over the 2011-2015 period. The growth differential of a region (or canton) depends on four terms, three structural effects and one competitive effect. The competitive effect turns out to be the dominant force at a high level of aggregation. An interesting pattern of structural effects unveils when working at a lower level of aggregation, allowing for identification of the leaders and laggers across regions and sectors.
    Keywords: firm-level, productivity, shift-share, structural and competitive effects, Switzerland.
    JEL: R11 R32
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:irn:wpaper:21-10&r=
  14. By: Khai, Dinh Cong; Thanh, Ngo Quang
    Abstract: The manufacturing industry performance in Vietnam has become a significant issue due to covid-19 and other economic factors and needs to examine frequently. Thus, the present research aims to investigate the impact of institutional pressures, such as human resource pressure, resources management pressure and operations management pressures, on the firm performance of the manufacturing industry in Vietnam. This research also examines the mediating impact of top management regulations among the relations of human resource pressure, resources management pressure, operations management pressures and firm performance of the manufacturing industry in Vietnam. The researchers followed the quantitative methods of data collection and used the questionnaires to obtain the data from respondents. A total of 610 questionnaires were sent to them, but only 380 were returned after three weeks and represented approximately 62.29 percent rate of response. This study also used the smart-PLS to examine the relations among the variables. The results indicated that human resource pressure, resources management pressure and operations management pressures positively associate with a firm performance of the manufacturing industry in Vietnam. The results also revealed that top management regulations positively mediate among the links of human resource pressure, resources management pressure, operations management pressures, and firm performance in Vietnam's manufacturing industry. This research has guided the regulators to increase their focus on managing institutional pressures that could enhance the firm performance.
    Keywords: institutional pressure; human resource pressure; resources management pressure; firm performance
    JEL: E0
    Date: 2021–04–14
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:109673&r=

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