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on Efficiency and Productivity |
| By: | Hennessy, Hugh; Lawless, Martina; O'Connor, Ciara |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:esr:wpaper:wp817 |
| By: | Enghin Atalay; Ali Hortacsu; Nicole Kimmel; Chad Syverson |
| Abstract: | We examine the recent slow growth in manufacturing productivity. We show that nearly all measured TFP growth since 1987 — and its post-2000s decline — comes from a few computer-related industries. We argue conventional measures understate manufacturing productivity growth by failing to fully capture quality improvements. We compare consumer to producer and import price indices. In rapidly changing industries, consumer price indices indicate less inflation, suggesting mismeasurement in standard industry deflators. Using an input-output framework, we estimate that TFP growth is understated by 1.4 percentage points in durable manufacturing and 0.3 percentage points in nondurable manufacturing and is slightly overstated in nonmanufacturing industries. |
| Keywords: | manufacturing; productivity measurement; ICT |
| JEL: | C67 D24 E01 E31 |
| Date: | 2026–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedpwp:103003 |
| By: | Vladislav Morozov; Andrea Sy |
| Abstract: | Firms in denser areas are more productive, a pattern attributed to agglomeration economies and firm selection. To disentangle these two channels, the popular approach of Combes et al. (2012, ECTA) critically assumes that total factor productivity (TFP) distributions between denser and less dense areas are the same up to mean, variance, and left-tail truncation. We empirically validate this assumption using Spanish administrative firm-level data and recent econometric methods adapted to noisy TFP estimates. Our results find that TFP distributions are indeed statistically identical up to these parameters, validating the use of such productivity decompositions. Furthermore, using only the mean and variance is sufficient to capture differences for all sectors. Accordingly, the productivity advantage of cities may be entirely due to agglomeration rather than stronger selection, suggesting that policymakers should focus on policies targeting agglomeration. Finally, our approach extends to related contexts like differences in worker skill distributions. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.13188 |
| By: | Michele Battisti (University of Palermo); Antonio Francesco Gravina (University of Messina); Matteo Lanzafame (Asian Development Bank) |
| Abstract: | Structural transformation is a central driver of economic development, yet recent challenges such as premature deindustrialization have raised critical questions about whether low-income economies can still follow traditional growth paths that rely on manufacturing expansion to drive productivity gains. Building on a theoretical model that incorporates learning-by-doing mechanisms, sectoral employment reallocation, and factor accumulation, we examine labor productivity growth trajectories using a panel of 31 developing and emerging economies over 1960–2019, detecting a data-driven structural break in 1982 that fundamentally altered productivity growth dynamics. To account for the potential heterogeneity in how structural transformation affects different types of economies, we employ quantile-based techniques to examine effects across different segments of the productivity growth distribution, moving beyond conventional approaches that focus on average effects and may obscure important distributional patterns. The unconditional quantile regression results identify manufacturing expansion as a key driver of productivity growth, with employment reallocation in this sector delivering twice the productivity benefits for slower-growing economies compared to high performers. The quantile decomposition further shows that observable characteristics and unobservable factors became increasingly important determinants of productivity performance following the structural break, with substantial heterogeneity across the distribution. Moreover, we construct counterfactual scenarios to investigate what outcomes low-performing economies could have attained had they adopted the characteristics, returns to factors, and unobservable capabilities of top performers. These scenarios unveil substantial untapped growth potential, with bottom-quartile economies potentially achieving average productivity growth improvements of up to 2.7 percentage points |
| Keywords: | structural transformation;quantile analysis;decomposition;counterfactual scenarios |
| JEL: | O11 O14 O25 |
| Date: | 2026–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:022426 |
| By: | Daouia, Abdelaati; Laurent, Thibault |
| Abstract: | This chapter discusses the current state of development of robust measures for evaluating firms’ production performance, focusing on two prominent approaches: (i) partial order-m frontiers and related efficiency scores based on probability-weighted moments, and (ii) their competing order-α counterparts, which rely on quantiles. It provides a structured overview of the original concepts and their recently introduced robustified versions, analyzing their strengths and weaknesses in terms of axiomatic properties, estimation methods, and robustness. The frontiles package offers various functions for computing both order-α and order-m frontiers and efficiency scores, including their robustified analogs, in the general setting with multiple inputs and outputs. It supports different performance measurement directions, namely input, output and hyperbolic orientations. Additionally, frontiles includes procedures for inference and robustness assessment, notably through confidence intervals, gross-error sensitivity and breakdown points. It also provides diagnostic checks to assess the presence of outliers in the data and, accordingly, to guide the choice of suitable trimming levels. It further enables the visualization of robust surface estimators in three-dimensional settings involving two inputs and one output. The use of this package is illustrated with a number of empirical applications. |
| Date: | 2026–04–02 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:131658 |
| By: | Vygintas Gontis; Lesya Kolinets |
| Abstract: | The long-run convergence of developing economies toward advanced countries exhibits robust empirical regularities, yet the mechanisms underlying technological diffusion remain insufficiently specified in standard growth models. In this paper, we extend the neoclassical framework by introducing a micro-founded mechanism of technological transfer as a driver of total factor productivity. Rather than treating technological progress as exogenous or purely innovation-driven, we model productivity growth as a process of adopting existing technologies from the global frontier. The diffusion process is described using a herding-type interaction mechanism, in which agents transition from non-adopters to adopters under the combined influence of individual incentives and peer effects. This approach yields a tractable aggregate representation of TFP dynamics characterized by nonlinear convergence toward a moving technological frontier. We derive an explicit analytical solution and provide an interpretation of model parameters in terms of initial productivity, convergence limits, and diffusion speed. The model is evaluated using OECD productivity data for Central and Eastern European economies. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.11413 |
| By: | Serdar Ozkan; Nicholas Sullivan |
| Abstract: | An analysis suggests changes in workforce composition—particularly foreign-born employment share—have had little effect on U.S. productivity growth since 2023. |
| Keywords: | immigration; workforce composition; foreign-born workers; productivity growth; Current Population Survey (CPS); Annual Social and Economic Supplement (ASEC) |
| Date: | 2026–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:fip:l00001:102986 |
| By: | Miguel León-Ledesma (University of Exeter) |
| Abstract: | This paper reviews the process of structural transformation (ST) across a wide range of Asian economies. After outlining key theories of ST, it documents Asia’s transformation and compares it with patterns observed elsewhere, using standard indicators and broader dimensions of structural change. It then examines the contribution of ST to productivity growth, drawing on disaggregated data. Finally, it assesses whether Asian economies exhibit signs of premature deindustrialization. The findings show that Asia’s ST broadly mirrors global experience but features a steeper decline in agriculture and faster expansion of services as income rises. Structural transformation has contributed positively to productivity growth, largely through labor reallocation out of agriculture. Agriculture shows the largest productivity gaps relative to the United States, while services show the smallest, suggesting substantial productivity gains from labor shifts toward services. There is no evidence of premature deindustrialization; industrial shares of output and inputs have not declined with higher incomes. |
| Keywords: | structural transformation;productivity growth;Asia |
| JEL: | O11 O14 |
| Date: | 2026–04–13 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:022435 |
| By: | Elvis Korku Avenyo (South African Research Chair in Industrial Development, University of Johannesburg); Danilo Spinola (College of Accounting, Finance and Economics, Researcher at UNU-Merit.); Fiona Tregenna (South African Research Chair in Industrial Development, University of Johannesburg) |
| Abstract: | This paper examines the firm-level effects of Chinese manufacturing import penetration on the performance of manufacturing firms in Belt and Road Initiative (BRI) countries. We construct a dataset of 59 BRI member countries by combining firm-level data from the World Bank's Enterprise Survey with industry-level data from the United Nations Commodity Trade (Comtrade) database from 2011 to 2020. Employing a multi-level modelling approach, our findings reveal that Chinese manufacturing imports exert a considerable adverse effect on productivity growth and employment, and a robust and significant positive effect on the export capabilities of manufacturing firms. The adverse effects on performance are significantly moderated by firms that pursue innovation and engage in foreign licensing. These findings are significant in middle-income countries and small and medium-sized enterprises (SMEs) within BRI countries. Based on these findings, we argue that the importation of manufactured goods from China results in a crowding-out effect on the productive capacities of firms within the Belt and Road Initiative (BRI) countries on the one hand and a catalytic effect on the internationalisation of firms on the other hand. These dual outcomes may underscore China's global value chains (GVCs) position-seeking strategy. |
| Keywords: | Chinese manufacturing import penetration; Multi-level modelling; Firm-level effects; Belt and Road Initiative. |
| JEL: | F14 F15 F61 O14 P33 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:adz:wpaper:2024-06 |
| By: | David Benatia; R\'emy Molini\'e; Pierre-Olivier Pineau |
| Abstract: | What drives cross-state differences in U.S. energy consumption? We combine LMDI decomposition, stochastic frontier analysis, and variable-importance methods on a panel of 50 states plus DC over the 2006--2022 period. The observed 12.8% decline in per capita energy use is driven almost entirely by intensity improvements. A variance decomposition attributes 63% of cross-state variation in log energy use to the demand frontier, 34\% to inefficiency above it, and 3% to noise. Within the frontier, energy prices account for roughly 26% of cross-state variation and state efficiency policies for about 13%, while GDP and climate together explain only around 10\%. Efficiency policies also operate through a second channel by reducing inefficiency, adding a further 6 percentage points to their total contribution. The results suggest that pricing and regulation are the primary drivers of cross-state energy use differences. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.12112 |
| By: | Ali Béjaoui; René Morissette |
| Abstract: | Measuring labour productivity is difficult. This is in part why recent studies on the productivity impact of telework focus on occupations where productivity is easily measured, such as call centers. One would think that matched employer-employee panel survey data on telework and self-reported productivity collected for stayers who experience an exogenous change in their number of telework days might provide an alternative. Since these data allow researchers to analyze changes in employees’ self-reported productivity while controlling for firm fixed effects and ruling out reverse causality, they might identify the impact of telework on stayers’ true productivity. We show that even with such data, the impact of telework on productivity is not identified if telework affects self-reported productivity by affecting not only true productivity but also other factors—such as satisfaction with one’s work arrangement—that likely depend on true productivity. Under these conditions, not controlling for these other factors leaves the other factors-to-self-reported productivity channel open but controlling for them leads to collider bias (Pearl and Mackenzie, 2018; Imbens, 2020), i.e. generates a spurious correlation between telework and self-reported productivity. Mesurer la productivité du travail est difficile. C’est en partie pour cette raison que les études récentes sur l’impact du télétravail sur la productivité se concentrent sur des professions où la productivité est facile à mesurer, comme les centres d’appels. On pourrait penser que des données d’enquête en panel appariées employeur-employé portant sur le télétravail et la productivité auto-déclarée, recueillies auprès de travailleurs restant dans la même entreprise mais connaissant un changement exogène du nombre de jours de télétravail, pourraient offrir une alternative. Comme ces données permettent aux chercheurs d’analyser les variations de la productivité auto-déclarée des employés tout en contrôlant les effets fixes liés à l’entreprise et en excluant la causalité inverse, elles pourraient permettre d’identifier l’impact du télétravail sur la productivité réelle des travailleurs restants. Nous montrons que même avec ce type de données, l’impact du télétravail sur la productivité n’est pas identifiable si le télétravail influence la productivité auto-déclarée en affectant non seulement la productivité réelle, mais aussi d’autres facteurs tels que la satisfaction à l’égard de l’organisation du travail, qui dépendent probablement eux-mêmes de la productivité réelle. Dans ces conditions, ne pas contrôler ces autres facteurs laisse ouvert le canal reliant ces facteurs à la productivité auto-déclarée, mais les contrôler entraîne un biais de collision (collider bias) (Pearl et Mackenzie, 2018 ; Imbens, 2020), c’est-à-dire génère une corrélation fallacieuse entre le télétravail et la productivité auto-déclarée. |
| Keywords: | telework, work from home, productivity, collider bias, télétravail, travail à domicile, productivité, biais de collision |
| Date: | 2026–04–10 |
| URL: | https://d.repec.org/n?u=RePEc:cir:cirwor:2026s-05 |
| By: | Tetsuji OKAZAKI |
| Abstract: | Immediately after World War II, under the occupation by the United States, the Japanese government implemented various policies aimed at initiating economic recovery through restoring production and suppressing inflation. Reflecting the policy of the U.S. government, Japanese policy regimes evolved through three phases: First, naïve economic controls were implemented that prioritized increasing production but disregarded productivity, second, economic controls aiming at increasing productivity, and finally a transition to a market economy. In this paper, we explored implications of this sequence of policy regime change, focusing on the coal mining industry. Analyzing mine-level panel data, we found that naive economic controls prioritizing increasing production, and particularly price control policies, distorted coal mining firms’ incentives for increasing productivity. Specifically, the firms whose productivity was higher in the initial year lacked incentives to increase productivity, and consequently, productivity of those firms stagnated. Additionally, despite policy changes aiming at productivity increase implemented in 1948, the changes had no significant effect on productivity growth. In contrast, the transition to a market economy had a positive impact on productivity growth; however, this impact was heterogeneous, and only firms whose initial productivity was higher and whose incentives had been distorted under the system of economic control saw positive effects. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:26030 |
| By: | Tsiboe, Francis; Njuki, Eric |
| Abstract: | This paper addresses divergent interpretations of agricultural insurance's association with on-farm production variability by conducting an exhaustive analysis of the U.S. Federal Crop Insurance Program and its effect on farm technology levels and efficiency. We utilize a meta-stochastic frontier approach and employ nearest-neighbor matching of insured and uninsured farms to minimize the self-selection issue in insurance participation. Analyzing 106, 551 farm-level observations from the Agricultural Resource Management Survey spanning 2001–2023, we find that insured farms exhibit an 8.50% higher technology level and a 6.36% greater efficiency in resource usage compared to uninsured farms. This technology level gap associated with insurance is weakly linked to its ability to strengthen producers' financial positions, making them more reliable candidates for credit and potentially promoting the use of technologies that yield relatively higher output. Additionally, significant variations in the benefits of insurance across different farm types and operator demographics are documented, underscoring the necessity for agricultural policy to be responsive to the heterogeneous needs of the farming community to optimize the impact of insurance programs. |
| Keywords: | Agricultural and Food Policy, Agricultural Finance, Risk and Uncertainty |
| Date: | 2026–04–06 |
| URL: | https://d.repec.org/n?u=RePEc:ags:arpcwo:396438 |
| By: | Nuriye Melisa Bilgin; Gianmarco Ottaviano |
| Abstract: | We study how digital infrastructure relaxes constraints on the diffusion and economic impact of artificial intelligence (AI). Using administrative data and a nationally representative enterprise survey from Turkey (2021-2024), we document significant disparities in AI adoption. Adoption is concentrated among large firms and in regions with high-speed broadband and proximity to data centers, particularly for software-intensive and cloud-based applications. To identify causal effects, we exploit the staggered expansion of Turkey's national natural gas pipeline network, which serves as a conduit for fiber-optic deployment. Because pipeline routing is determined by energy distribution priorities rather than digital demand, it provides plausibly exogenous variation in connectivity. Difference-in-differences estimates show that improved connectivity significantly increases AI adoption, particularly for software-intensive technologies and among small and medium-sized enterprises. Instrumental-variable estimates indicate that infrastructure-driven AI adoption raises labor productivity and export intensity while shifting labor composition toward ICT-related roles. These findings highlight digital infrastructure as a primary determinant of both the pace of AI diffusion and its resulting economic returns. |
| Keywords: | artificial intelligence, digital infrastructure, broadband, technology diffusion, firm productivity, cloud computing |
| Date: | 2026–04–15 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2172 |
| By: | Ruben Gaetani; Gustavo de Souza; Martí Mestieri Ferrer |
| Abstract: | Long-run economic growth depends on the international diffusion of frontier technologies. Using Brazilian data, we identify a channel through which tariff cuts slow this diffusion: they weaken foreign firms' incentives to transfer technology to domestic producers. Exploiting variation in import tariffs across origin countries within narrowly defined industries, we find that tariff reductions lead to fewer technology transfers and fewer citations to foreign technology, with the largest declines occurring among firms located near previous technology recipients. To interpret these findings, we develop a growth model in which foreign firms choose between exporting goods and transferring technology, with learning from exports being less efficient than learning from transferred technologies, as informed by the empirical evidence. Trade liberalization shifts learning from transferred technologies to imported goods, raising welfare in the short run but slowing diffusion and productivity growth. An optimal subsidy to technology transfers substantially amplifies the welfare gains from trade liberalization. |
| Keywords: | growth, international trade, technology diffusion, technology transfer |
| JEL: | O33 O40 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1572 |
| By: | Yukiko SAITO; Xinyi TONG; Kongphop WONGKAEW |
| Abstract: | This paper examines the dynamics of the Japanese production network during the COVID-19 pandemic. We utilize a panel dataset of approximately 1.8 million firms spanning from 2015 to 2023 and document that firms largely maintained existing inter-firm relationships during the early stages of the pandemic, often before severing ties in subsequent periods. Moreover, new link formation did not recover at a commensurate pace, resulting a net contraction of the production network. Furthermore, we identify a shift in the geographical distance between transacted firms. Firms increasingly dropped local partners but added distant partners. Notably, changes in network dynamics and geographical distance were driven by firms with high ICT intensity and those located in core prefectures. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:26027 |