nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2022‒12‒12
sixteen papers chosen by

  1. R&D and Productivity in Finnish Firms By Valmari, Nelli
  2. A Measure of Well-Being Efficiency Based on the World Happiness Report By Sarracino, Francesco; O'Connor, Kelsey J.
  3. The Identification of Time-Invariant Variables in Panel Data Model: Exploring the Role of Science in Firms’ Productivity By Amoroso, Sara; Bruno, Randolph Luca; Magazzini, Laura
  4. Agglomeration Transport and Productivity: Evidence from Toulouse Metropolitan Area By Ivaldi, Marc; Quinet, Emile; Ruiz Mejia, Celia
  5. Environmentally-adjusted productivity measures for the UK By Matthew Agarwala; Josh Martin
  6. Economic Efficiency By Cranier, Louis
  7. What Do R&D Spillovers from Universities and Firms Contribute to Productivity? Plant level productivity and technological and geographic proximity in Japan By René BELDERBOS; IKEUCHI Kenta; FUKAO Kyoji; KIM Young Gak; KWON Hyeog Ug
  8. Automation and the Workforce: A Firm-Level View from the 2019 Annual Business Survey By Daron Acemoglu; Gary W. Anderson; David N. Beede; Cathy Buffington; Eric E. Childress; Emin Dinlersoz; Lucia S. Foster; Nathan Goldschlag; John C. Haltiwanger; Zachary Kroff; Pascual Restrepo; Nikolas Zolas
  9. Measuring data as an asset: Framework, methods and preliminary estimates By Carol Corrado; Jonathan Haskel; Massimiliano Iommi; Cecilia Jona-Lasinio
  10. Management and Performance in the Public Sector: Evidence from German Municipalities By Florian Englmaier; Gerd Muehlheusser; Andreas Roider; Niklas Wallmeier
  11. Environmental social efficiency By Khuc, Quy Van
  12. AI, Skill, and Productivity: The Case of Taxi Drivers By Kanazawa, Kyogo; Kawaguchi, Daiji; Shigeoka, Hitoshi; Watanabe, Yasutora
  13. The impact of access to credit on energy efficiency By Jun Zhou; Zhichao Yin; Pengpeng Yue
  14. Small and Medium Sized European Firms and Energy Efficiency Measures: A Probit Analysis By Guglielmo Maria Caporale; Cristiana Donati; Nicola Spagnolo
  15. Are Working Hours Complements in Production? By Lin Shao; Faisal Sohail; Emircan Yurdagul
  16. Does Industry Agglomeration Attract Productive Firms? The role of product markets in adverse selection By René BELDERBOS; FUKAO Kyoji; IKEUCHI Kenta; KIM Young Gak; KWON Hyeog Ug

  1. By: Valmari, Nelli
    Abstract: Abstract Productivity of the Finnish private sector decreased during the financial crisis of 2008–2009 and, since then, productivity growth has not reached the level preceding the crisis. A key factor underlying productivity growth is R&D. The population of Finnish firms, excluding Nokia, have increased their R&D inputs since the financial crisis. Therefore, it is worthwhile considering whether changes in productivity effects of R&D, instead of changes in volumes of R&D inputs, may explain the slowdown in productivity growth. This paper estimates productivity effects of Finnish firms’ R&D inputs in several industries for the years 2001–2009 and 2010–2018. The estimates are used to find out whether the productivity effects of R&D have decreased after the financial crisis. The empirical strategy (Doraszelski and Jaumandreu, 2013) allows for productivity effects that are nonlinear and heterogeneous across firms. For most of the industries studied, there is no statistical evidence that the productivity effects of R&D are lower for the years 2010–2018 than for the years 2001–2009. Instead, there is evidence that, in some industries, the productivity effects of R&D increased after the financial crisis. In other words, low productivity growth after the financial crisis does not seem to be caused by a decrease in the productivity effects of R&D.
    Keywords: R&D, Productivity, Production function estimation
    JEL: D24 L60 O30
    Date: 2022–11–28
  2. By: Sarracino, Francesco (STATEC Research – National Institute of Statistics and Economic Studies); O'Connor, Kelsey J. (STATEC Research – National Institute of Statistics and Economic Studies)
    Abstract: We estimate a measure of well-being efficiency that assesses countries' ability to transform inputs into subjective well-being (Cantril ladder). We use the six inputs (real GDP per capita, healthy life expectancy, social support, freedom of choice, absence of corruption, and generosity) identified in the World Happiness Reports and apply Data Envelopment Analysis to a sample of 126 countries. Efficiency scores reveal that high ranking subjective well-being countries, such as the Nordics, are not strictly the most efficient ones. Also, the scores are uncorrelated with economic efficiency. This suggests that the implicit assumption that economic efficiency promotes well-being is not supported. Subjective well-being efficiency can be improved by changing the amount (scale) or composition of inputs and their use (technical efficiency). For instance countries with lower unemployment, and greater healthy life expectancy and optimism are more efficient.
    Keywords: subjective well-being, World Happiness Report, efficiency, Data Envelopment Analysis
    JEL: I31 E23 D60 O47 O15
    Date: 2022–10
  3. By: Amoroso, Sara (European Commission, Joint Research Centre); Bruno, Randolph Luca (University College London); Magazzini, Laura (Sant'Anna School of Advanced Studies)
    Abstract: Recent literature has raised the attention on the estimation of time-invariant variables both in a static and a dynmamic framework. In this context, Hausman-Taylor type estimators have been applied, relying crucially on the distinction between exogenous and endogenous variables (in terms of correlation with the time-invariant error component). We show that this provision can be relaxed, and identification can be achieved by relying on the milder assumption that the correlation between the individual effect and the time-varying regressors is homogenous over time. The methodology is applied to identify the role of inputs from "Science" (firm-level publications' stock) on firms' labour productivity, showing that the effect is larger for those firms with higher level of R&D investments. The results further support the dual – direct and indirect – role of R&D.
    Keywords: panel data, time-invariant variables, science, productivity, R&D
    JEL: C23 O32 L20
    Date: 2022–11
  4. By: Ivaldi, Marc; Quinet, Emile; Ruiz Mejia, Celia
    Abstract: The objective of this paper is to estimate the extent of agglomeration externalities taking into account the direct and indirect impacts of transport exposure on productivity. To do so, we take advantage of a rich data infrastructure that combines very fine georeferenced infra-municipality data on more than one million employees with detailed data on the public-transport and road networks of a typical European metropolitan area, namely the Toulouse Metropolitan Area (TMA). We recover the productivity effects of agglomeration and transport measures by the implementation and estimation of a wage determination model in two stages. The first stage assesses the importance of industrial concentration and employees’ characteristics against true productivity differences across zones on the average of local industrial wages. The second stage explains local productivity differences on our local factors of interest: agglomeration and transport. Finally, and to have a full representation of transport impacts, we investigate the size of the indirect effect of transport exposure on productivity by its impact on the distribution of metropolitan employment. We exploit the panel nature of our data and apply instrumentation techniques to cope with the endogeneity of agglomeration and transport measures. Our results suggest that both agglomeration and transport exposure measures have a substantial and significant effect on local productivity. Indeed, when density of employment doubles, productivity increases by 1.6%. Further, the effects of transport exposure measures differ for the two modes considered, private vehicle and public transport. In both cases, a higher exposure to transport supply implies higher levels of employment an productivity.
    Keywords: agglomeration economies; accessibility; transport exposure; public transport network; road network; productivity; transport infrastructure; density; cities; commuting costs; urban economics; transport economics.
    Date: 2022–06
  5. By: Matthew Agarwala (Bennett Institute for Public Policy, Unviersity of Cambridge); Josh Martin (The Bank of England, and ESCoE)
    Keywords: productivity, environmental accounting, national accounting, greenhouse gas emissions
    Date: 2022–11
  6. By: Cranier, Louis
    Abstract: In microeconomics, economic efficiency, depending on the context, is usually one of the following two related concepts: Allocative or Pareto efficiency: any changes made to assist one person would harm another. Productive efficiency: no additional output of one good can be obtained without decreasing the output of another good, and production proceeds at the lowest possible average total cost.
    Date: 2022–07–29
  7. By: René BELDERBOS; IKEUCHI Kenta; FUKAO Kyoji; KIM Young Gak; KWON Hyeog Ug
    Abstract: We examine the simultaneous effects of spillovers due to R&D by universities and by firms on total factor productivity in a panel of over 20,000 Japanese manufacturing plants. Estimating geographic decay functions based on the location of the universe of manufacturing plants run by R&D conducting firms and public research institutions in Japan, we find a positive influence of both private and public technologically proximate-R&D stocks, which decay in distance and become negligible at around 500 kilometers. Decomposition analyses show that declining R&D spillovers are responsible for a substantial part of the decline in the rate of TFP growth in Japanese manufacturing. The exit of geographically proximate plants operated by R&D intensive firms, which may be associated with a relocation of manufacturing activity overseas, plays a notable role in this process and is an important phenomenon in major industrial agglomerations such as Tokyo and Osaka.
    Date: 2022–11
  8. By: Daron Acemoglu; Gary W. Anderson; David N. Beede; Cathy Buffington; Eric E. Childress; Emin Dinlersoz; Lucia S. Foster; Nathan Goldschlag; John C. Haltiwanger; Zachary Kroff; Pascual Restrepo; Nikolas Zolas
    Abstract: This paper describes the adoption of automation technologies by US firms across all economic sectors by leveraging a new module introduced in the 2019 Annual Business Survey, conducted by the US Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES). The module collects data from over 300,000 firms on the use of five advanced technologies: AI, robotics, dedicated equipment, specialized software, and cloud computing. The adoption of these technologies remains low (especially for AI and robotics), varies substantially across industries, and concentrates on large and young firms. However, because larger firms are much more likely to adopt them, 12-64% of US workers and 22-72% of manufacturing workers are exposed to these technologies. Firms report a variety of motivations for adoption, including automating tasks previously performed by labor. Consistent with the use of these technologies for automation, adopters have higher labor productivity and lower labor shares. In particular, the use of these technologies is associated with a 11.4% higher labor productivity, which accounts for 20-30% of the difference in labor productivity between large firms and the median firm in an industry. Adopters report that these technologies raised skill requirements and led to greater demand for skilled labor but brought limited or ambiguous effects to their employment levels.
    JEL: E22 J20 J24
    Date: 2022–11
  9. By: Carol Corrado; Jonathan Haskel; Massimiliano Iommi; Cecilia Jona-Lasinio
    Abstract: Data are shown to generate efficiency gains but to have been unevenly shared across firms and households, and the subpar economic performance of most advanced economies (prior to the pandemic) has been attributed to increased market power originating, at least in part, from the increased use of data. To sharpen our understanding of these divergent perceptions of the modern digital age, this paper puts the recent increase in use of digitised information, i.e., data, into an economic framework amenable to measurement and analysis. Data are conceptualised as an intangible asset: a storable factor input that is only partially captured in existing macroeconomic and financial statistics. Our proposed framework treats data as an intangible asset that contributes to final production in an economy. This paper provides the conceptual groundwork that is needed for defining and measuring data investments. We also provide a review of methods that are used to measure data, and we offer an experimental implementation of our framework. We also develop preliminary estimates of data assets intended to fully encompass the “intelligence” or “knowledge” generated by the use of data that are coherent with national accounts data at the industry-level of analysis as well as with measures of intangibles developed by EUKLEMS-INTANProd.
    Keywords: data, innovation, intangible capital, productivity growth
    JEL: E22 O47 E01
    Date: 2022–11–21
  10. By: Florian Englmaier; Gerd Muehlheusser; Andreas Roider; Niklas Wallmeier
    Abstract: We study management practices and performance of public sector organizations in Germany. For a representative sample of municipalities, we provide survey evidence for substantial het-erogeneity in the use of structured management practices. This heterogeneity is not driven by differences across states, regional types, or population size. Moreover, we document a system-atic positive relationship between the degree of structured management and a diverse set of performance measures capturing municipalities’ attractiveness for citizens and firms. Topic modelling (LDA) of survey responses suggests that management styles differ indeed in the extent of structured management, with many municipalities displaying relatively little of it.
    Keywords: management practices, public sector organizations, local government, municipal performance, World Management Survey (WMS)
    JEL: D20 D73 H11 H73 R50
    Date: 2022
  11. By: Khuc, Quy Van
    Abstract: I propose and adopt the environmental social efficiency framework that uses mindspongeEdu, MindspongeTech, MindspongeAI to achieve our environment-related goals/objectives for tackling climate change and environmental problems that humans face today.
    Date: 2022–09–14
  12. By: Kanazawa, Kyogo (University of Tokyo); Kawaguchi, Daiji (University of Tokyo); Shigeoka, Hitoshi (Simon Fraser University); Watanabe, Yasutora (University of Tokyo)
    Abstract: We examine the impact of Articial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers' productivity by shortening the cruising time, and such gain is accrued only to low-skilled drivers, narrowing the productivity gap between high- and low-skilled drivers by 14%. The result indicates that AI's impact on human labor is more nuanced and complex than a job displacement story, which was the primary focus of existing studies.
    Keywords: artificial intelligence, skill, productivity, taxi-drivers, prediction, demand forecasting, machine learning
    JEL: J22 J24 L92 R41
    Date: 2022–10
  13. By: Jun Zhou; Zhichao Yin; Pengpeng Yue
    Abstract: This paper proposes a brand-new measure of energy efficiency at household level and explores how it is affected by access to credit. We calculate the energy and carbon intensity of the related sectors, which experience a substantial decline from 2005 to 2019. Although there is still high inequality in energy use and carbon emissions among Chinese households, the energy efficiency appears to be improved in long run. Our research further maps the relationship between financial market and energy. The results suggest that broadened access to credit encourages households to improve energy efficiency, with higher energy use and carbon emission.
    Date: 2022–11
  14. By: Guglielmo Maria Caporale; Cristiana Donati; Nicola Spagnolo
    Abstract: This paper investigates the factors (such as different sources of financing, energy audits and internal monitoring activities) affecting the propensity of European small and medium sized enterprises (SMEs) to adopt energy efficiency measures (EEMs). For this purpose, a Probit model is estimated using data from the 2017 Flash Eurobarometer survey covering a large sample of European firms. The analysis is carried out for the full sample as well as for clusters based on an environmental performance index (EPI) and on the level of economic development in turn. The results indicate that internal financing always has a positive effect on a firm’s propensity to adopt EEMs. Private external sources of financing appear to be more important for Western European firms as well as for those located in countries with a greater level of environmental awareness; in the latter, when firms combine private financing with energy audits or internal monitoring activities the propensity to adopt EEMs increases further. By contrast, in the Eastern Countries this occurs when firms simultaneously rely on public funds and monitoring activities.
    Keywords: energy efficiency measures, EPI, financing, SMEs
    JEL: G32 O16 Q40
    Date: 2022
  15. By: Lin Shao; Faisal Sohail; Emircan Yurdagul
    Abstract: This paper uses Canadian matched employer-employee data to show that working hours are gross complements in production rather than perfect substitutes, as is typically assumed. We exploit within-establishment and individual-level variation in hours and wages to document novel evidence consistent with complementarities in hours worked. Next, we estimate an elasticity of substitution in working hours of 0.69 in the aggregate and between 0.52 and 1.04 at the industry level. We validate our estimates by showing that industries with higher elasticities exhibit greater flexibility in hours. Our findings have important implications for research on labor supply and the efficacy of policies that aim to influence it.
    Keywords: Economic models; Labour markets
    JEL: E23 J23 J31
    Date: 2022–11
  16. By: René BELDERBOS; FUKAO Kyoji; IKEUCHI Kenta; KIM Young Gak; KWON Hyeog Ug
    Abstract: Do high or low productivity firms self-select into locations characterized by high industry agglomeration? On the one hand, productive firms may benefit more from the availability of specialized (labour) inputs and they are also more likely to survive heightened competition. On the other hand, productive firms face greater risks of knowledge dissipation to collocated rival firms, as they may contribute more than they receive in terms of knowledge spillovers. We examine location decisions for new plant establishments by firms in Japan with established productivity records (multi-plant firms) at the fine-grained level of towns, wards, and cities where knowledge spillovers are most likely to occur. We find that the adverse selection effects of industry agglomeration–the process of agglomerated areas attracting weaker rather than stronger firms–dominate if knowledge spillovers are most harmful to productive entrants when the focal firm and local incumbent establishments target the same (domestic) product market. We conclude that negative sorting processes do occur, but that these can only be uncovered in a more fine-grained analysis that takes into account ex ante measures of firm heterogeneity and the nature of product markets.
    Date: 2022–11

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