nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2026–05–04
nine papers chosen by
Angelo Zago, Universitàà degli Studi di Verona


  1. Emotional stability and firm productivity. Evidence from German matched employer-employee data By Giorgio Brunello; Caroline Neuber-Pohl
  2. Unions in Developing Countries By Alex Bryson; Mari Tanaka
  3. Does generative AI narrow education-based productivity gaps? Evidence from a randomized experiment By Guillermo Cruces; Diego Fernández Meijide; Sebastian Galiani; Ramiro H. Gálvez; María Lombardi
  4. Allocative Efficiency in the Manufacturing Sector: A Firm-Level Analysis for Costa Rica By Melissa Vega-Monge; Claudio Mora-García
  5. Hive of activity: what would it take to raise skills and productivity in Greater Manchester? By Aadya Bahl; Henry G. Overman
  6. Mind the Gap: AI Adoption in Europe and the US By Alexander Bick; Adam Blandin; David Deming; Nicola Fuchs-Schündeln; Jonas Jessen
  7. Urban Sprawl in Shrinking Cities: Causal Evidence from Brazil By Gustavo Castro; Carlos Azzoni; André Chagas
  8. The Virtuous Cycle Between Skills and Technology By Sascha O. Becker; Christian Dustmann; Hyejin Ku
  9. The mediating role of ESG on the interaction between green banking and financial performance of commercial banks in Kenya By Maru, Lucy

  1. By: Giorgio Brunello; Caroline Neuber-Pohl
    Abstract: Using matched employer-employee data for Germany, we estimate firm production functions augmented with workers' personality traits. We find that emotional stability is the only trait that positively affects firm productivity. Its effect shows up mainly in large firms operating with a higher than median share of educated workers.
    Keywords: personality traits, firm productivity
    JEL: J24
    Date: 2026–01
    URL: https://d.repec.org/n?u=RePEc:crm:wpaper:26025
  2. By: Alex Bryson; Mari Tanaka
    Abstract: The effects of trade unions on firm performance are theoretically ambiguous. The sizable empirical literature on their effects is almost exclusively confined to developed countries, particularly those in North America and Europe. We contribute to the literature by estimating union effects on firm performance in about 40, 000 firms in 77 developing countries between 2002 and 2011. In doing so, we exploit standardized firm level data collected by the World Bank. We find positive partial correlations between unionization and firm labor productivity and wages, especially in lower-income countries. These positive effects persist when we instrument for union presence, consistent with recent evidence of union positive effects on productivity and wages in western industrialized countries.
    Keywords: trade unions; productivity; wages; developing countries; enterprise data; union formation
    JEL: J51
    Date: 2025–09
    URL: https://d.repec.org/n?u=RePEc:crm:wpaper:2569
  3. By: Guillermo Cruces; Diego Fernández Meijide; Sebastian Galiani; Ramiro H. Gálvez; María Lombardi
    Abstract: Does generative artificial intelligence (AI) reinforce or reduce productivity differences across workers? Existing evidence largely studies AI within firms and occupations, where organizationalselectioncompresseseducationalheterogeneity, leavingunclearwhetherAI narrows productivity gaps across individuals with substantially different levels of formal education. Weaddressthisquestionusingarandomizedonlineexperimentconductedoutside firms, in which1, 174 adults aged 25–45 with heterogeneous educational backgrounds complete an incentivized, workplace-style business problem-solving task. The task is a general (not domain-specific) exercise, and participants perform it either with or without access to a generative-AI assistant. Unlike prior work that studies heterogeneity within relatively homogeneous worker samples, our designtargets the between–education-group productivity gap as the primary estimand. We find that AI increases productivity for all participants, with substantially larger gains for lower-education individuals. In the absence of AIaccess, higher-education participants outperform lower-education participants by0.548standarddeviations; withAIaccess, thisgapfallsto0.139standarddeviations, implying that generative AI closes three-quarters of the initial productivity gap. We interpret this pattern as evidence that generative AI narrows effective productivity differences in task execution by relaxing constraints that are more binding for lower-education individuals, even though underlying skill differences remain, as reflected in persistent education gaps in task performance and in a follow-up exercise without AI assistance.
    Keywords: Productivity, artificial intelligence, education, human capital, inequality
    JEL: J24 O33
    Date: 2026–03
    URL: https://d.repec.org/n?u=RePEc:udt:wpgobi:wp_gob_2026_03
  4. By: Melissa Vega-Monge (Department of Economic Research, Central Bank of Costa Rica); Claudio Mora-García (Department of Economic Research, Central Bank of Costa Rica)
    Abstract: This paper studies the evolution of allocative efficiency (AE) in Costa Rica’s manufacturing sector between 2005 and 2022, using comprehensive administrative firm-level data. Building on the structural framework of Blackwood et al. (2021), we estimate productivity and AE under both constant and non-constant returns to scale, explicitly accounting for the role of markups, demand elasticity, and firm-level fundamentals. Our results show that while AE in manufacturing remains relatively low, it exhibits an upward trend over time. Nonetheless, the potential gains from eliminating misallocation are large: moving to an efficient allocation of resources would raise manufacturing productivity by an estimated 61% – 89%. ***Resumen: Este documento analiza la evolución de la asignación eficiente de recursos (i.e., eficiencia asignativa) en el sector manufacturero de Costa Rica con datos administrativos a nivel de la firma entre 2005 y 2022. Con base en el marco estructural de Blackwood et al. (2021), estimamos la productividad y la eficiencia asignativa bajo los supuestos de retornos constantes y no constantes a escala. Además, consideramos explícitamente el papel de los márgenes, la elasticidad de la demanda y los fundamentos de la firma. Nuestros resultados muestran que, si bien la eficiencia asignativa en la manufactura se mantiene relativamente baja, presenta una tendencia creciente a lo largo del tiempo. No obstante, las ganancias potenciales de eliminar la mala asignación son significativas: transitar hacia una asignación eficiente de los recursos productivos incrementaría la productividad del sector manufacturero entre un 61% y un 89%.
    Keywords: Allocative Efficiency; Productivity; Administrative Data; Costa Rica, Eficiencia asignativa, Productividad, Datos administrativos, Costa Rica
    JEL: G21 G28 C63
    Date: 2026–03
    URL: https://d.repec.org/n?u=RePEc:apk:doctra:2602
  5. By: Aadya Bahl; Henry G. Overman
    Abstract: Finding enough highly-skilled workers to enable Greater Manchester to make a serious dent in its productivity gap with London will require action that goes beyond skills policy alone, a new report from the Centre for Economic Performance (CEP) shows.
    Keywords: Manchester, UK Economy, Productivity, Economic geography, skills, living standards, education, growth
    Date: 2026–04–29
    URL: https://d.repec.org/n?u=RePEc:cep:cepsps:55
  6. By: Alexander Bick; Adam Blandin; David Deming; Nicola Fuchs-Schündeln; Jonas Jessen
    Abstract: This paper combines international evidence from worker and firm surveys conducted in 2025 and 2026 to document large gaps in AI adoption, both between the US and Europe and across European countries. Cross-country differences in worker demographics and firm composition account for an important share of these gaps. AI adoption, within and across countries, is also closely linked to firm personnel management practices and whether firms actively encourage AI use by workers. Micro-level evidence suggests that AI generates meaningful time savings for many workers. At the macro level, in recent years industries with higher AI adoption rates have experienced faster productivity growth. While we do not establish causality, this relationship is statistically significant and similar in magnitude in Europe and the US. We do not find clear evidence that industry-level AI adoption is associated with employment changes. We discuss limitations of existing data and outline priorities for future data collection to better assess the productivity and labor market effects of AI.
    Keywords: artificial intelligence, management practices, productivity
    JEL: E23 M51
    Date: 2026–04
    URL: https://d.repec.org/n?u=RePEc:crm:wpaper:26102
  7. By: Gustavo Castro (Departament of Economics, University of S˜ao Paulo, Brazil); Carlos Azzoni (Departament of Economics, University of S˜ao Paulo, Brazil); André Chagas (Departament of Economics, University of S˜ao Paulo, Brazil)
    Abstract: Across many urban systems, cities continue to expand physically even as their populations decline. This spatial-demographic mismatch, which we refer to as shrinking but sprawling cities, raises important questions about the economic consequences of urban expansion under demographic contraction. Using data for more than 5, 500 Brazilian municipalities between 2010 and 2022, we estimate the causal impact of urban sprawl on labor productivity in municipalities experiencing population decline. To address endogeneity, we implement a two-stage least squares strategy that instruments population shrinkage using a SPEI-based shift-share design and urban sprawl using spatial diffusion in urban expansion across neighboring municipalities. We find that urban sprawl significantly reduces labor productivity growth in municipalities experiencing population decline. The negative interaction between shrinkage and sprawl is robust across sectors and to multiple robustness checks. These findings suggest that spatial expansion under demographic contraction weakens agglomeration forces and generates significant productivity losses in urban systems.
    Keywords: Urban Shrinkage; Urban Sprawl; Labor Productivity
    JEL: R11 O18 C26
    Date: 2026
    URL: https://d.repec.org/n?u=RePEc:ris:nereus:022452
  8. By: Sascha O. Becker; Christian Dustmann; Hyejin Ku
    Abstract: We examine the long-term labor market impact of the steam engine, an early general-purpose technology, by linking newly digitized 19th-century records from Prussia to modern German labor market data (1975-2019). Regions with a higher concentration of steam engines per worker in 1875 exhibit higher wages today, primarily because of higher firm productivity and a more skilled workforce. These regions also exhibited greater skill diversity in 1939 and generated more innovations between 1877 and 1918, a pattern that persists to this day. Our findings highlight a lasting, self-reinforcing cycle between technology and skills, set in motion by the steam engine, offering a novel explanation for regional income disparities and their persistence.
    Keywords: steam engine, technology adoption, diversity, innovation, human capital, productivity
    JEL: I24 J24 O14 O33
    Date: 2026–01
    URL: https://d.repec.org/n?u=RePEc:crm:wpaper:26013
  9. By: Maru, Lucy
    Abstract: Green banking practice involves the bank's internal operations, external operations and lending decisions which are environmentally, socially and governance (ESG) compliant and sustainable. In Kenya, green banking practice is influenced internally and externally and is context based. Adverse weather patterns such as drought and floods have recently influenced income in sectors such as agriculture, transport and manufacturing. The adverse effects have affected GDP and livelihoods and as a trickle down influenced savings and investments. From the year 2012, conversation on sustainable financial institution was tabled through a CEO round table targeting players in the banking sector. The aim was to transform the banking industry to be more resilient and sustainable. One way of greening the banking sector was by embracing green banking practices and incorporating ESG in banks' processes and products. This paper aims to investigate how green banking interacts with ESG performance to shape the financial outcomes of commercial banks in Kenya. The paper looks at profitability assessed through ROA and credit risk assessed through NPLs. Anchored on the stakeholder theory, the resource-based view theory and the institutional theory, the paper goes further to test the role of ESG as a mediator on the interaction between green banking and financial performance of commercial banks in Kenya. The paper uses panel data collected from commercial banks in Kenya. Secondary data on GBI, ESG and financial performance was collected for a period of 13 years. ESG and GBI measures were obtained, measured and scored using existing literature. The study analysed a total of 25 commercial banks applying balanced panel data regression with firm fixed effects and controls per year. Mediation analysis was used to test the indirect effect of green banking (independent variable) on financial performance (dependent variable) through the mediating variable (ESG). The findings of the study indicate that green banking positively influences financial performance The findings also indicate that green banking reduces credit risk. As a mediator, ESG shows a statistically strong association with green banking. However, from the mediator, there is a limited mediating effect on performance and risk. The findings indicate that as commercial banks embrace ESG practices, they become greener and this has a positive and statistically significant relationship with financial performance. Therefore, this paper aims at proposing measures that policy makers and banks as heads of the supply chain can adopt in driving climate risk mitigation and adaptation, and incorporating ESG in banking practice, while safeguarding financial performance. The paper encourages commercial banks to embrace green banking and ESG practices in order to draw short term, medium term and long-term benefits that accrue.
    Keywords: Green Banking Practice, ESG (Environmental Social and Governance), Financial performance
    Date: 2026
    URL: https://d.repec.org/n?u=RePEc:zbw:kbawps:340180

This nep-eff issue is ©2026 by Angelo Zago. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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