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on Efficiency and Productivity |
| By: | Lavinia Piemontese; Andrea Tulli |
| Abstract: | We study how variation in the allocation mechanism of public demand shapes firm performance and aggregate productivity. Exploiting the quasi-random implementation of an efficient or lottery-like auction format in the Italian construction sector, we find that when the same amount of public resources is allocated through the efficient mechanism, recipient firms experience about 8% higher revenue growth within three years. The effect is strongest where contracting authorities exhibit greater screening capacity and in less competitive markets. Efficient allocation targets more productive firms, which subsequently secure a larger amount of future public resources. Simulations suggest that replacing lottery-like mechanisms with efficient ones could raise sectoral productivity by about 4%. |
| JEL: | H57 D22 D61 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:bol:bodewp:wp1218 |
| By: | Antonin Bergeaud; Ruveyda Nur Gozen; John Van Reenen |
| Abstract: | We introduce a methodology to measure cross-country trends in innovation capability - “technological trajectories” and implement this on a new rich dataset covering patents between 1836 and 2016 across multiple countries. Intuitively, trajectories are revealed by a country’s sustained increases in patenting across multiple patent offices. We first describe the data patterns, showing the relative decline of the UK, and the rise first of the US and Germany, and then later of Japan and China. We then econometrically estimate trajectories on (i) the post-1902 period for France, Germany, Japan, the UK and US, and (ii) the post-1960 period for a wider sample of 40 countries. Our trajectories are strongly positively correlated with Total Factor Productivity growth, and also (but less strongly) associated with the growth of labour productivity and capital intensity. We show that future trajectories are predicted by a country’s initial levels of R&D, education and defence spending, classic drivers of innovation in modern growth theory. |
| JEL: | O31 O33 O34 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34760 |
| By: | Nour Nsiri (UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement, CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes); Georgios Kleftodimos (CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes, UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Sophie Drogué (UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement) |
| Abstract: | Context To improve agricultural productivity and water sustainability in water-scarce regions, it is essential to understand the efficiency and diversity of farming practices Objective This study aims to assess the diversity and efficiency of farming systems in Morocco's Chtouka-Massa plain. It focuses on resource management, agricultural intensification, and water use, identifying inefficiencies and proposing sustainable solutions. Methods Using Principal Component Analysis and Hierarchical Clustering, we classify 40 farm households into three distinct typologies: (i) extensive cereal-arboriculture systems, (ii) semi-intensive mixed cereal-vegetable systems, and (iii) intensive vegetable farming systems. A meta-frontier approach combined with Data Envelopment Analysis (DEA) is then applied to assess disparities in resource efficiency, technological performance, and environmental sustainability among these typologies. Results and conclusions Our results show that extensive cereal-arboriculture systems exhibit the highest resource efficiency—particularly in water, nitrogen, and labor—but achieve the lowest gross margins due to limited agricultural intensification. Semi-intensive mixed systems demonstrate moderate efficiency but consume the largest amounts of water, largely sourced from subsidized private wells. Intensive vegetable farming systems, while generating the highest gross margins, are the least efficient due to high input costs, reliance on desalinated water, and labor-intensive practices. Targeted policy interventions are needed to optimize resource use and promote sustainable practices adapted to each farming typology. Significance This study provides actionable insights for policymakers aiming to enhance the sustainability of agricultural systems and groundwater resources in arid and semi-arid regions. The findings support the need for targeted policies to enhance groundwater management. |
| Keywords: | Farm household typology, Efficiency, DEA Model, Meta-Frontier, Farm household typology Efficiency DEA Model Meta-Frontier |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05398998 |
| By: | Marc Aliana (Department of Finance and Accounting, Universitat Jaume I, Castellón, Spain); Maria Teresa Balaguer-Coll (Department of Finance and Accounting, Universitat Jaume I, Castellón, Spain); Diego Prior (Department of Business, Universitat Autònoma de Barcelona, Spain); Emili Tortosa-Ausina (IVIE, Valencia and IIDL and Department of Economics, Universitat Jaume I, Castellón, Spain) |
| Abstract: | This paper examines eco-productivity convergence across European Union regions while explicitly incorporating institutional quality within a multilevel governance framework. Using a panel of 216 NUTS-2 regions over the period 2010–2023, we analyse whether regions converge in their ability to generate economic output while limiting environmental pressures, and how this process is shaped by both national and regional Quality of Government (QoG). Ecoproductivity is measured using a nonparametric frontier approach based on Data Envelopment Analysis, with labour and capital as inputs, GDP as a desirable output, and Greenhouse Gas (GHG) emissions, transformed into an outputoriented ‘GHG savings’ indicator. The results show that average eco-productivity levels are around 8% higher when QoG is accounted for, cross-regional dispersion is considerably lower, and β-convergence is consistently stronger and statistically significant across all subperiods. Overall, eco-productivity convergence is associated with QoG, suggesting that sustainable regional catch-up is more likely where green investment is matched by improvements in institutional quality. |
| Keywords: | Cohesion Policy; Eco-productivity convergence; Multilevel governance; Quality of Government. |
| JEL: | C14 C61 O18 Q56 R11 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:jau:wpaper:2026/05 |
| By: | Giorgio Brunello (University of Padova); Désirée Rückert (European Investment Bank); Christoph T. Weiss (European Investment Bank); Patricia Wruuck (German Federal Ministry of Economic Affairs and Climate Action) |
| Abstract: | Using firm-level data covering 25 EU countries, the UK and the US and a difference-in-differences approach, we show that employers adopting advanced digital technologies reduce their investment in training per employee. Compared to non-adapting firms, this reduction is negligible on impact but increases to -11.3 and -13.8 percent of the pre-treatment mean two and three years after adoption. It can be decomposed into two contrasting effects: the increase in the probability of investing in training and the reduction in investment by firms with positive training. We argue that a candidate reason for the decline in investment in training per employee is that the use of advanced digital technologies and employee training are substitutes in production, implying that an increase in the former negatively affects the marginal productivity of the latter. Our findings point to challenges in realizing high levels of firm-sponsored training for employees in increasingly digital economies. |
| Keywords: | Digital Technologies, Investment in Employee Training. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:pad:wpaper:0315 |
| By: | Simon Deakin; Kamelia Pourkermani |
| Abstract: | We report the results of an econometric analysis of the effects of labour laws in the UK and China. For data on labour laws we draw on the 2023 update of the CBR-LRI index, part of the Cambridge Leximetric Database, which codes for labour laws around the world between 1970 and 2022. The longitudinal coverage of the CBR-LRI enables us to use time-series techniques which model dynamic changes in an economy over time. We employ impulse response function analysis to estimate the effects of labour laws on indicators of efficiency (productivity, employment and unemployment) and distribution (labour’s share of national income). We find that stronger labour laws in the UK are associated with rising employment and falling unemployment, while those in China are associated with rising productivity. We also observe positive impacts of labour laws on the labour share in both countries. Breaking down our results according to particular types of labour law, the positive employment effect we see in the UK is associated with stronger working time protections, while the positive productivity effect in China is associated with more protective laws regulating flexible forms of employment and with stronger dismissal laws. Assessing our results, we suggest that they speak to the importance of labour laws for avoiding regression, in the British case, to a low-cost, low productivity economy, and, in China’s case, for helping bridge the ‘middle income gap’ to sustainable development. More generally, our findings imply the need for adjustment to standard models of the role of labour laws in the economy and to the policy advice which they generate, to the following effect: labour laws, by disciplining capital, contribute to its more productive use. |
| Keywords: | Labour law, employment, unemployment, productivity, labour share, leximetrics, UK, China |
| JEL: | K31 J83 O57 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:cbr:cbrwps:wp547 |
| By: | Natalia Emanuel; Emma Harrington |
| Abstract: | What are the returns to firms of paying more? We study a Fortune 500 firm’s voluntary firm-wide $15/hour minimum wage, which affected some warehouses more than others. Using a continuous difference-in-differences design, we find that a $1/hour pay increase (5.5 percent) halves worker departures, reduces absenteeism by 18.6 percent, and increases productivity (boxes moved per hour) by 5.7 percent. These productivity gains fully defrayed increased labor costs, offsetting the firm’s incentive to mark down wages. We develop a simple model that connects efficiency-wage incentives and monopsony power, showing how these forces can counterbalance each other to keep wages closer to workers’ marginal revenues. |
| Keywords: | voluntary firm minimum wage; Efficiency wages; monopsony; labor market frictions |
| JEL: | M52 J31 J42 |
| Date: | 2026–02–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednsr:102436 |
| By: | Thomas Jacquet |
| Abstract: | This article assesses the short- and medium-term effects of extreme heat on agricultural productivity across French departments during 1980-2023. Using high-resolution ERA5-Land temperature data and CORINE Land Cover, we construct a sector-specific Extreme Degree Days (EDD) index, weighted by cropland and pasture shares to capture sector-specific thermal stress. We estimate department-specific impulse responses via local projections and find significant and persistent productivity losses following heat shocks above 29 °C, with effects intensifying over a four-year horizon and attenuating only modestly thereafter. A Wald test confirms substantial regional heterogeneity in sensitivity to extreme temperatures. The negative impacts are particularly pronounced in lower-productivity, livestock-oriented departments clustered between 44.5° and 46° north latitude. These findings underscore the macroeconomic relevance of a spatially disaggregated measure of exposure to extreme temperatures and highlight the urgency of region-specific adaptation strategies as these episodes intensify. |
| Keywords: | Agriculture; Climate change; Extreme heat; France; Productivity |
| JEL: | O13 Q19 Q54 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:drm:wpaper:2026-4 |
| By: | Dr Chinnasamy Agamudai Malarvizhi (Multimedia University, Cyberjaya, 63100, Selangor, Malaysia Author-2-Name: Theshmah Janarthanan Nambiar Author-2-Workplace-Name: Multimedia University, Cyberjaya, 63100, Selangor, Malaysia Author-3-Name: Author-3-Workplace-Name: Author-4-Name: Author-4-Workplace-Name: Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:) |
| Abstract: | "Objective - The human resources (HR) teams in information technology (IT) organizations have begun adopting AI solutions to enhance workforce management, improve communication, and increase productivity, given the emergence of remote and hybrid working models. Methodology/Technique - These calls for further research into the effects of artificial intelligence (AI) tools on employee performance in IT firms in Malaysia, particularly in the context of remote and hybrid work. Hence, this study aims to examine how AI-based platforms, such as automated performance appraisals, employee engagement tools, and virtual collaboration services, affect work productivity, job satisfaction, and overall morale. Findings - The independent variables of work-life balance, communication satisfaction, and organizational support are examined via convenience sampling. The three exogenous variables are linked to a single endogenous variable, employee performance. Moreover, the research investigates the limitations and potential of these resources in remote or hybrid settings by assessing their impact on organizational culture, employee relations, and well-being. Novelty - This empirical work aims to aggregate and analysis empirical information on the risks involved in AI-driven hybrid working environments. The elicited data could be used to develop an AI-driven tool to assist workers and employers in recognizing, assessing, and mitigating risks. Existing legislation should be analyzed to determine how HR technology can reinforce guidelines to safeguard remote workers. Type of Paper - Empirical" |
| Keywords: | Remote and hybrid working, AI tools, Work-life balance, Organizational support, Communication Satisfaction, Employee performance |
| JEL: | M1 M15 |
| Date: | 2026–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:gtr:gatrjs:jmmr357 |
| By: | Ajay K. Agrawal; John McHale; Alexander Oettl |
| Abstract: | The task-based approach has become the dominant framework for studying the labor-market effects of artificial intelligence (AI), typically emphasizing the replacement of human workers by machines. Motivated by growing empirical evidence that contemporary AI is more often used as a tool that augments workers, this paper develops two related task-based models in which AI enhances worker productivity without automating tasks. Abstracting from capital, we develop a pair of related task-based models that examine how technological progress in AI that provides new tools to augment workers affects aggregate productivity and wage inequality. Both models emphasize the role of human capital in intermediating the effects of AI-related technological shocks. In the first model, AI use requires specialized expertise, and technological progress expands the set of tasks for which such expertise is effective. We show that a larger supply of AI expertise amplifies the productivity gains from improvements in AI technology while attenuating its adverse effects on wage inequality. The second model focuses on non-AI skills, allowing AI tools to alter the set of tasks that workers can perform given their skills. In equilibrium, workers allocate across tasks in response to wages, generating an endogenous distribution of skills across the task space. A central result is that aggregate productivity and wage inequality depend on different global properties of this equilibrium distribution: productivity is particularly sensitive to thinly staffed tasks that create bottlenecks, while wage inequality is driven by the concentration of workers in a narrow set of tasks. As a result, improvements in AI tools can induce non-monotonic co-movement between productivity and inequality. By linking these mechanisms to multidimensional human capital---including AI expertise and higher-order non-AI skills---the paper highlights the role of education and training policies in shaping the economic consequences of AI-driven technological change. |
| JEL: | J24 O33 O41 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34781 |
| By: | Robin Fischer; Anton Pichler |
| Abstract: | Mobilising private capital is a critical bottleneck of the energy transition, yet recent crisis-driven windfall profits for fossil power firms suggest that market signals may still favour carbon-intensive assets. Here we analyse a panel of 900 European power firms (2001-2023) to resolve whether these profits reflect a durable profitability advantage or a crisis-driven anomaly. Using machine-learning clustering and Bayesian model averaging, we identify a structural divergence: wind and solar portfolios exhibit rising profitability, with return on assets among wind-dominated firms increasing by over 6% between 2014 and 2023. Conversely, higher fossil portfolio shares are increasingly associated with lower profitability, with marginal effects reaching -4% by 2023, while renewable-dominated firms match or outperform their fossil-heavy counterparts across most European regions. These findings suggest that the record profits of fossil incumbents were distinct outliers, masking an ongoing decline in the profitability of carbon-intensive business models. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.22167 |
| By: | Seong-Young Kim (Rennes SB - Rennes School of Business); Phillip H Kim |
| Abstract: | We study how and why firms shift their interfirm network positions during the routinized regime of a mature high-technology industry. Firms seek benefits from network positions (structural holes or centrality) by forming alliances that move them into these positions and increase their innovation performance. However, during the routinized technology regime, inertia impedes such movements, leading firms a dilemma: whether to continue shifting between two network positions and determine if such shifts yield better outcomes. We analyzed firm network positioning behavior in the semiconductor industry from 1991-2007. Our findings indicate that firms shift toward more central positions, which, in turn, improves innovation performance. These results explain how firms actively shape their network strategy when external conditions discourage such shifts. |
| Keywords: | semiconductor industry, routinized technology regime, high-technology industries, innovation performance, interfirm network positioning |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05410602 |