Efficiency and Productivity http://lists.repec.org/mailman/listinfo/nep-eff Efficiency and Productivity 2026-03-02 Nonparametric Spatial Frontier Models for Productivity Analysis: Evidence from EU Regions https://d.repec.org/n?u=RePEc:aiz:louvad:2025020&r=&r=eff This paper proposes a novel nonparametric panel data framework for estimating conditional production frontiers and efficiency measures that explicitly accounts for spatial interdependencies. By integrating recent advances in nonparametric frontier estimation with spatial panel data analysis, the proposed approach offers a flexible and robust framework for assessing productivity and efficiency in the presence of spatial interactions, explicitly accounting for both global and local spatial effects. By extending recently developed tools for estimating Malmquist productivity indices to conditional nonparametric frontier efficiency models, we provide a refined decomposition of productivity growth into technological change, efficiency change, and scale effects within a fully nonparametric framework. Applying this framework to a comprehensive dataset on European regions, we provide new evidence on spatial patterns of productivity growth and efficiency dynamics across the EU. The results reveal marked heterogeneity in regional performance and highlight the crucial role of spatial spillovers in shaping productivity outcomes. Ignoring these interdependencies can lead to mismeasurement of productivity trends, reinforcing the value of our proposed spatial nonparametric frontier approach for policy and performance analysis. Mastromarco, Camilla Simar, Léopold Nonparametric Conditional Frontier ; Panel Data Model ; Spatial Dependence ; Productivity Analysis ; Malmquist Productivity Index ; EU Regional Performance 2025-11-13 Cycle, productivity, and efficiency: Evidence from the European regions https://d.repec.org/n?u=RePEc:ahy:wpaper:wp66&r=&r=eff Most economists believe that cyclical factors do not impact on long-run total factor productivity. However, the Kaldorian approach maintains the existence of a significant positive relationship, while the opposite view is held by some economists, sometimes defined as Schumpeterian. In this paper we shed light on this issue disentangling the impact of the cycle on the change of technical efficiency («catch-up») from the impact on technical progress. We carry out this empirical exercise for 267 NUTS2 European regions, computing a Malmquist index of total factor productivity throughout 1995-2016. We find that the Great Recession elicits catch-up, while decisively lowering technical progress. Overall, long-run TFP growth significantly falls during the slump. We also report evidence for region groups selected across various sample cuts. In the samples dominated by regions belonging to new Member States, there is little catch-up due to the slump, and the Great Recession strongly reduces long-run TFP growth. There is also a group of low growth regions whose TFP growth is relatively insensitive to demand fluctuations. Gianluigi Coppola Sergio Destefanis Giulia Nunziante catch-up, technical progress, Malmquist index, creative destruction 2026-02 Balassa-Samuelson Effect in Emerging Market Economies- An Empirical Examination https://d.repec.org/n?u=RePEc:pra:mprapa:127546&r=&r=eff This study revisits the Balassa-Samuelson (B-S) hypothesis for 16 inflation-targeting emerging market and developing economies (EMDEs) to test whether their inflation differential with the advanced economies (AEs) could be explained through the productivity channel. The study finds positive and significant impact of total factor productivity (TFP) and labour productivity (LP) growth differentials on inflation differentials between AEs and inflation targeting EMDEs. The B-S effect is estimated in the range 1.6-2.5 percentage points for India. The average B-S effect for the inflation targeting EMDEs, however, is found at a lower level at 0.5-0.8 percentage points. This difference in the B-S effect between India and EMDEs arises from India’s higher TFP growth (vis-à-vis AEs) compared to the EMDEs. The sectoral level analysis also corroborates these findings. Our findings provide an empirical support to the role of productivity growth differential in explaining the inflation differential between AEs and major EMDEs in the medium term. Verma, Radheshyam Nath, Siddhartha Bhowmick, Chaitali Yadav, Swastik TFP, Inflation targeting, Balassa-Samuelson, productivity differential, traded-non-traded sector 2025 Reconciling Engineers and Economists: the Case of a Cost Function for the Distribution of Gas https://d.repec.org/n?u=RePEc:aiz:louvad:2025013&r=&r=eff The analysis of cost functions is an important topic in econometrics both for scientific studies and for industrial applications. The object of interest may be the cost of a firm or the cost of a specific production, in particular in case of a proposal to a procurement. Engineer methods evaluate the technical cost given the main characteristics of the output using the decomposition of the production process in elementary tasks and are based on physical laws. The error terms in these models may be viewed as idiosyncratic chocs. The economist usually observes ex post the cost and the characteristics of the product. The difference between theoretical cost and the observed one may be modeled by the inefficiency of the production process. In this case, econometric models are cost frontier models. In this paper we propose to take advantage of the situation where we have information from both approaches. We consider a system of two equations, one being a standard regression model (for the technical cost function) and one being a stochastic frontier model for the economic cost function where inefficiencies are explicitly introduced. We derive estimators of this joint model and derive its asymptotic properties. The models are presented in classical parametric approach, with few assumptions on the stochastic properties of the joint error terms. We suggest also a way to extend the model to a nonparametric approach, the latter provides an original way to model and estimate nonparametric stochastic frontier models. The techniques are illustrated in the case of the cost function for the distribution of gas in France. Fève, Frédérique Florens, Jean-Pierre Simar, Léopold Cost efficiency ; Stochastic frontier models ; Location-Scale efficiencies ; Nonparametric stochastic frontier models 2025-05-01 Gender Effects on Microfinance Social Efficiency: A Robust Approach Incorporating Undesirable Outputs https://d.repec.org/n?u=RePEc:aiz:louvad:2025019&r=&r=eff This study investigates the impact of gender diversity at both the strategic and operational levels on the social efficiency of microfinance institutions (MFIs). Specifically, we assess how the presence of women on boards and among loan officers influences MFIs’ ability to deliver social outcomes, particularly in serving female borrowers, considering the portion of the loan portfolio that is delinquent or overdue as an undesirable output. Using a novel robust nonparametric frontier estimation method developed by Daraio and Simar (2024), we estimate both efficiency scores and their derivatives, allowing for a more nuanced evaluation of marginal effects and returns to scale. Our analysis draws on a cross-sectional dataset of 346 MFIs worldwide, incorporating directional distance functions and conditional efficiency frontiers based on external gender-related variables. The findings reveal that while the direct effect of gender composition on inputs and outputs is limited, there is a significant joint and non-linear impact of female board and loan officer representation on mitigating the negative effects of portfolio delinquency. These results underscore the importance of integrated gender diversity across strategic and field levels in enhancing the social performance of MFIs and provide actionable insights for policymakers aiming to promote inclusive financial practices. Daraio, Cinzia Fall, François Seck Simar, Léopold Vanhems, Anne OR in developing countries ; Microfinance performance and gender effect ; undesirable output ; nonparametric frontier estimation ; marginal effects 2025-10-23 Artificial Intelligence and Productivity in Europe https://d.repec.org/n?u=RePEc:ces:ceswps:_12401&r=&r=eff The discussion on Artificial Intelligence (AI) often centers around its impact on productivity, but macroeconomic evidence for Europe remains scarce. Using the Acemoglu (2024) approach we simulate the medium-term impact of AI adoption on total factor productivity for 31 European countries. We compile many scenarios by pooling evidence on which tasks will be automatable in the near term, using reduced-form regressions to predict AI adoption across Europe, and considering relevant regulation that restricts AI use heterogeneously across tasks, occupations and sectors. We find that the medium-term productivity gains for Europe as a whole are likely to be modest, at around 1 percent cumulatively over five years. While economically still moderate, these gains are still larger than estimates by Acemoglu (2024) for the US. They vary widely across scenarios and countries and are substantially larger in countries with higher incomes. Furthermore, we show that national and EU regulations around occupation-level requirements, AI safety, and data privacy combined could reduce Europe’s productivity gains by over 30 percent if AI exposure were 50 percent lower in tasks, occupations and sectors affected by regulation. Florian Misch Ben Park Carlo Pizzinelli Galen Sher artificial intelligence, productivity, technology, regulation 2026 Do R&D Spillovers Support Low-carbon Transition? Firm-level Evidence from Finnish Energy-intensive Manufacturing https://d.repec.org/n?u=RePEc:rif:wpaper:136&r=&r=eff Abstract A structural shift from fossil fuel-based energy systems to renewable, sustainable energy sources critically depends on research and development (R&D) activities at the firm-level. This study examines the contribution of R&D spillovers from other firms to greenhouse gas (GHG) emissions in Finnish energy-intensive manufacturing industries. We link firm-level GHG emissions to financial and innovation data for 230 firms in the pulp and paper, chemicals, non-metallic minerals, and basic metals industries over 2000–2019. We derive emissions-generating functions based on a directional distance function framework, and estimate them using shape-constrained semiparametric regression. Our key result is that R&D spillovers have a strong statistically significant association with the firm-level GHG emissions. However, the signs and magnitudes of the spillovers differ across industries. In the chemical industry, intra-industry R&D spillover is associated with lower emissions, whereas in the pulp and paper and the basic metals industries, intra-industry R&D spillover is associated with higher emissions. These results demonstrate that R&D spillovers do not self-evidently lower emissions, but can also contribute to higher emissions. Our findings also reveal an important channel of inter-industry R&D spillovers through material flows, highlighting the pivotal role of the chemical industry for the GHG abatement in the pulp and paper production and non-metallic minerals industry. Kuosmanen, Natalia Kuosmanen, Timo Zhou, Xun Carbon dioxide emissions, Environmental performance, Green productivity, Sustainability, Technology spillovers 2026-02-23 The Costs of Fleet Variety https://d.repec.org/n?u=RePEc:mos:moswps:2026-01&r=&r=eff We study how heterogeneity in capital inputs affects firm performance. Drawing on detailed data on municipal bus fleets in Poland, we exploit plausibly exogenous variation generated by public procurement and nationally coordinated sales behavior of bus manufacturers to identify the causal effects of variety in fleet composition across brands and other technical dimensions. More heterogeneous fleets exhibit lower vehicle utilization and, for a fixed level of output, require more units of capital and generate higher costs. Our results emphasize that the pro- ductive capacity of capital depends on its internal structure, not only on its aggregate quantity or value. Filip Premik Dan Yu Productivity, hetergeneous capital , capital utilization , fleet composition , organization of production 2026-02 Regional outlook on labor productivity in Spain, 2000–2022 https://d.repec.org/n?u=RePEc:bde:opaper:2605e&r=&r=eff This paper analyzes the evolution of labor productivity in Spanish regions during 2000–2022, with attention to their sectoral structure and productive specialization. Using data from the National Statistics Institute and the Fundación de Estudios de Economía Aplicada, we compute labor productivity as the ratio of gross value added at constant prices to effective hours worked. Through cluster analysis, we group the regions into five clusters based on their relative productive specialization. The results highlight the sustained leadership of the cluster formed by Madrid, the Balearic Islands, and the Canary Islands, marked by strong tertiarization. They also show greater resilience of industrially oriented clusters during economic crises. At the same time, differences in labor productivity dynamics do not always match the groupings suggested by cluster analysis, due to the heterogeneous role of service subsectors. Carles Manera Ferran Navinés Javier Franconetti Miquel Quetglas José A. Pérez-Montiel productivity, labor productivity, Spanish regions, economic diversification, Spanish economy 2026-02 Legacy of apartheid: misallocation of labour and firm productivity https://d.repec.org/n?u=RePEc:unu:wpaper:wp-2026-15&r=&r=eff This paper investigates the extent to which the historical legacy of apartheid laws explains contemporary misallocation and firm productivity in South Africa. During the apartheid era (1948-1994), job reservations, closed-shop agreements, and minimum-wage policies were implemented to restrict occupational mobility for Black workers and to insulate White employees from competition. Talent Nesongano Carol Newman John Rand Marvin Suesse South Africa, Apartheid, Discrimination, Misallocation, Labour, Firm productivity 2026 Do R&D Spillovers Support Emission Abatement Targets? https://d.repec.org/n?u=RePEc:rif:briefs:175&r=&r=eff Abstract This brief examines how R&D spillovers are associated with firm-level greenhouse gas emissions in Finnish energy-intensive manufacturing. The results show that R&D spillovers from other firms within the same industry are more strongly associated with lower emissions than the firm’s own R&D activity. This result highlights the role of innovation spillovers and knowledge diffusion in emissions abatement. However, the direction and magnitude of R&D spillovers differ across industries depending on their R&D intensity. In the chemical industry that has high R&D intensity, inter-industry R&D spillovers are associated with lower emissions, whereas in the pulp and paper and basic metals industries, inter-industry R&D spillovers are associated with higher emissions. These results demonstrate that technology spillovers do not automatically lower emissions, but can also contribute to higher emissions. Our findings reveal an important channel of inter-industry R&D spillovers through material flows, highlighting the pivotal role of the chemical industry for the GHG abatement in the pulp and paper production and non-metallic minerals industry. Kuosmanen, Natalia Kuosmanen, Timo Carbon dioxide emissions, Environmental performance, Green productivity, Sustainability, Technology spillovers 2026-02-23 The Price of Productivity https://d.repec.org/n?u=RePEc:rco:dpaper:563&r=&r=eff We construct a new micro-geographic commercial rent index for Germany to study the capitalization of agglomeration economies into floor space prices. In large local labor markets, commercial rents decline by -17% per kilometer from the central business district, compared to 13% for residential rents, reflecting stronger agglomeration benefits at the center. Commercial rents in central business districts increase with local labor market size at an elasticity of 15%, implying that wage responses capture only about half of the agglomeration effect on total factor productivity. Gabriel Ahlfeldt Stephan Heblich Tobias Seidel Fan Yin floor space; rents; spatial equilibrium; total factor productivity; 2026-02-09 Does Generative AI Narrow Education-Based Productivity Gaps? Evidence from a Randomized Experiment https://d.repec.org/n?u=RePEc:nbr:nberwo:34851&r=&r=eff Does generative artificial intelligence (AI) reinforce or reduce productivity differences across workers? Existing evidence largely studies AI within firms and occupations, where organizational selection compresses educational heterogeneity, leaving unclear whether AI narrows productivity gaps across individuals with substantially different levels of formal education. We address this question using a randomized online experiment conducted outside firms, in which 1, 174 adults ages 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 design targets 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 AI access, higher-education participants outperform lower-education participants by 0.548 standard deviations; with AI access, this gap falls to 0.139 standard deviations, implying that generative AI closes about 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 cognitive 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. Guillermo Cruces Diego Fernández Meijide Sebastian Galiani Ramiro H. Gálvez María Lombardi 2026-02 Technology and Economic Development https://d.repec.org/n?u=RePEc:ces:ceswps:_12404&r=&r=eff This chapter presents a tractable framework for the study of technology adoption and diffusion in the context of economic development. Firms in countries behind the world technology frontier can rapidly adopt new techniques from the world frontier. Lower absorptive capacity (because of weak education systems, poor management practices, or barriers to technology adoption), institutional distortions, mismatch between frontier technologies and the needs of firms in the country (i.e., “inappropriate technology”), and credit market frictions slow down technology adoption and cause the economy in question to have a greater distance to the frontier and thus lower income per capita — although the long-run growth rate of the country still remains equal to that of the frontier. This framework is extended to study the choice between innovation and imitation, as well as the role of selection for higher-productivity and higher-absorptive capacity firms during the process of economic development. We illustrate the main comparative statics of our framework with a number of correlations based on cross-country and firm-level data. The tractability of the framework makes it amenable to a range of additional extensions. Daron Acemoglu Ufuk Akcigit Simon Johnson technology adoption, innovation, income gap, institutions, economic growth, development, productivity 2026 Low barriers, high stakes: Formal and informal diffusion of AI in the workplace https://d.repec.org/n?u=RePEc:zbw:zewdip:336765&r=&r=eff Artificial intelligence (AI) is diffusing rapidly in the workplace, yet aggregate productivity gains remain limited. This paper examines the dual diffusion of AI - through both formal, employer-led and informal, employee-initiated adoption - as potential explanation. Using a representative survey of nearly 10, 000 employees in Germany, we document a high extensive but low intensive margin of usage: while 64 percent use AI tools, only 20 percent use them frequently. This diffusion is strongly skill-biased and depends less on establishment and regional characteristics. While formality is associated with more frequent usage, training, AI-based supervision, and higher perceived productivity gains, it does not broaden access. These patterns suggest that widespread informal usage can coexist with limited productivity effects when complementary investments and organizational integration lag behind. Arntz, Melanie Baum, Myriam Brüll, Eduard Dorau, Ralf Hartwig, Matthias Matthes, Britta Meyer, Sophie-Charlotte Schlenker, Oliver Tisch, Anita Wischniewski, Sascha artificial intelligence, AI, technology diffusion, formal and informal adoption, training, algorithmic management, productivity, inequality 2026