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on Efficiency and Productivity |
| By: | Rentaro Utamaru |
| Abstract: | Production function estimates underpin the measurement of firm-level markups, allocative efficiency, and the productivity effects of policy interventions. Since Olley and Pakes (1996), every major proxy variable estimator has identified the production function through a first-order Markov assumption on unobserved productivity; I show that misspecification of this assumption generates persistent upward bias in the materials elasticity that propagates into overestimated markups and inflated treatment effects. I replace the Markov restriction with conditional independence across three intermediate input demands, a static condition grounded in input market segmentation, and establish nonparametric identification from a single cross-section. I develop a GMM estimator and establish consistency and asymptotic normality. Monte Carlo simulations confirm that the proposed estimator is unbiased across Markov and non-Markov environments, while the standard estimator exhibits persistent bias of up to 63 percent of the true materials elasticity. In 502 Japanese manufacturing industries, the proposed method yields systematically lower markups than the standard method across the entire distribution (median 0.93 vs. 1.03), reducing the share of industries with markups above unity from 54 to 37 percent. In a difference-in-differences analysis of the 2011 Tohoku earthquake, the standard method overstates the productivity loss by 0.40 percentage points, roughly $3.6 billion (400 billion yen) per year. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.04458 |
| By: | Theunissen, Anne |
| Abstract: | While the relation between gender and productivity has been predominantly explored in management and organization studies literature along the rigid boundaries of the gender binary, the perspectives of transgender and gender non-conforming (TGNC) workers have received little attention. Moreover, whereas studies have illustrated how productivity is a gendered construct that favours cis-gender men over cis-gender women at work, alternative conceptualisations of productivity have rarely been explored. Aiming to come to a more flexible and gender-minority-inclusive conceptualisation of the gender/productivity relation, this study analyses 19 interviews with TGNC workers in the UK and develops an alternative notion of productivity based on Queer Theory. The findings illustrate how TGNC workers produce narratives in which they portray the lack of queer productivity in the workplace as requiring emotional and queer labour. They engage in discourses that present these forms of gendered labour as draining them from resources they could otherwise invest in their individual hegemonic productivity. Simultaneously, they portray workplaces where they are not engaging in gendered labour as environments where their individual hegemonic productivity is facilitated. This paper contributes to the literature by reconceptualising productivity as a multiplicity, and by reframing the gender/productivity relation beyond its binary frameworks of reference. It also highlights the significance of social-identity-sensitive notions of productivity, and it illuminates forms of minoritised gender inequality tied to productivity dynamics in the workplace. |
| JEL: | R14 J01 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:137894 |
| By: | Wagner, Joachim (Leuphana University Lüneburg) |
| Abstract: | The use of advanced technologies like artificial intelligence, robotics, or smart devices will go hand in hand with higher productivity, higher product quality, and lower trade costs. Therefore, it can be expected to be positively related to export activities. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union collected in 2025 to shed further light on this issue by investigating the link between the use of advanced technologies and extensive margins of exports. Applying a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), which does not impose any restrictive assumptions for the functional form of the relation between margins of exports, use of advanced technologies, and any control variables, we find that firms which use more advanced technologies do more often export and do export to more different destinations. |
| Keywords: | advanced technologies, exports, firm level data, Flash Eurobarometer 559, kernel-regularized least squares (KRLS) |
| JEL: | D22 F14 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18496 |
| By: | SHIMIZU, Chihiro |
| Abstract: | We develop a vintage-accounts framework for real estate capital measurement . The Mutual Determination Lemma, formalises the equivalence among vintage prices, user costs, and depreciation rates a constraint routinely violated in applied work. The MaintenanceDepreciation Theorem shows that linearly increasing maintenance costs produce a strictly accelerating depreciation profile, rationalising geometric-type patterns. The Geometric PIM Decomposition Theorem proves that geometrically distributed retirement ages are necessary and sufficient for a geometric population PIM, establishing Diewert (2004) 's δ * = |
| Keywords: | Vintage capital, depreciation, user cost, TFP, Builder's Model, land structure decomposition |
| JEL: | C43 D24 D92 E22 R33 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:hit:rcesrs:dp26-9 |
| By: | Allan Hsiao; Jacob Moscona; Benjamin A. Olken; Karthik A. Sastry |
| Abstract: | This paper studies how global warming affects deforestation and agricultural land use. Using high-resolution satellite data on global temperature, deforestation, and land cover from 2001 to 2019, we find that extreme heat shocks to agricultural productivity cause large and persistent forest loss on the world’s agricultural frontier. This effect is strongest in the tropics, in areas growing the most temperature-sensitive crops, and in regions with the most inelastic demand for agricultural products, and it does not seem to be offset by international spillovers. Moreover, we show that deforestation in response to extreme heat can be explained almost entirely by cropland expansion. We corroborate these findings using agricultural census data from Brazil, where we find evidence for a mechanism whereby heat reduces yields and raises local agricultural prices, driving cropland expansion but little land use or input adjustment along other margins. Our estimates imply that extreme heat has driven substantial forest loss and that projected warming through 2100 could lead to an additional 28 million hectares of deforestation. Our findings challenge the view that reallocation will soften the environmental consequences of climate change, suggesting instead that farmers double down and expand cropland locally when productivity falls. |
| JEL: | O13 Q15 Q23 Q24 Q54 Q56 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35029 |
| By: | Wagner, Joachim (Leuphana University Lüneburg) |
| Abstract: | The use of advanced technologies like artificial intelligence, robotics, or smart devices will go hand in hand with, among others, higher productivity, higher product quality, more exports and better chances to survive any crisis. Better firms tend to use advanced technologies. Information on firm level determinants of adoption of these technologies, therefore, is important to inform industrial policies. This paper uses firm level data for manufacturing enterprises from 38 countries collected in 2025 to shed further light on this issue by investigating the link between the use of advanced technologies and firm characteristics. Applying a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), which does not impose any restrictive assumptions for the functional form of the relation between use of advanced technologies, firm characteristics and any control variables, we find that firms which use advanced technologies tend to be larger and more innovation orientated, while firm age does not matter. |
| Keywords: | advanced technologies, firm characteristics, Flash Eurobarometer 559, kernel-regularized least squares (KRLS) |
| JEL: | D22 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18499 |
| By: | Pulito, Giuseppe (ROCKWOOL Foundation Berlin); Pytlikova, Mariola (CERGE-EI Prague); Schroeder, Sarah (Aarhus University and Ratio Institute); Lodefalk, Magnus (Orebro University, Ratio Institute, GLO) |
| Abstract: | Using surveys of Danish firms and individuals linked to employer–employee administrative data, we analyze AI adoption across technologies, business functions, and workers. We show that AI adoption is driven primarily by firm capacities rather than performance. Adoption is strongly associated with firm size, digital infrastructure, and workforce composition, particularly education and STEM intensity, while productivity and capital intensity explain little of the variation. Conditional on AI adoption, larger and more digitally mature firms deploy advanced technologies more broadly. Moreover, AI technologies diffuse across multiple business functions while other advanced technologies remain function-specific. Individual-level evidence mirrors these patterns and points towards workforce readiness as a key determinant of AI adoption. Finally, commonly used occupational AI exposure measures vary substantially in their ability to predict actual adoption, with benchmark-based measures outperforming patent-based and LLM-focused alternatives. These findings show that treating AI as a monolithic category obscures economically meaningful variation in who adopts, what they deploy, and how well existing measures capture it. |
| Keywords: | Artificial Intelligence, technology adoption, digitalisation, human capital, AI exposure measures |
| JEL: | D24 J23 J62 O33 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18515 |
| By: | Sailendra Pattanayak; Lorena Rivero del Paso; Herve Tourpe; Chloe Cho |
| Abstract: | This note offers insights into harnessing emerging technologies to enhance efficiency, decision making, and accountability in public financial management (PFM). Acknowledging the speculative enthusiasm around certain technologies and the diversity of country contexts, traditions, and PFM frameworks, it advocates for a structured, objective-driven approach for adopting emerging technologies, which involves assessing the potential gains and feasibility. The note also outlines key practices for sustainable adoption and for navigating the complexities of digital transformation in PFM. It is accompanied by Technology Cards, which illustrate key technologies and their relevance for PFM, providing a practical resource for policymakers and practitioners. |
| Keywords: | digitalization; digital transformation; GovTech; emerging technologies; public financial management; financial management information systems; Open Data; artificial intelligence |
| Date: | 2026–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imftnm:2026/006 |
| By: | Wei Cai; Andrea Prat; Jiehang Yu |
| Abstract: | Prior research has pointed to differences in organizational capital as a reason for the persistent performance discrepancies among otherwise similar firms. In this paper, we develop and validate a new measure of organizational capital. Based on over a million crowd-sourced employee reviews scraped from Glassdoor, we construct the measure of organizational capital at the firm-year level using the word embedding model and ChatGPT-generated synthetic reviews. Our measure varies over time in accordance with macro trends, and differs both across and within firms, reflecting firm heterogeneity and major internal changes. We validate our measure by testing empirical predictions of the properties of organizational capital discussed in prior literature. Our findings suggest that this measure captures a slowly evolving intangible asset that is significantly associated with firm performance and top management’s influence, aligning with the conceptualization of organizational capital by Dessein and Prat (2022). We further showcase applications of our measure in accounting, economics, finance, and management literature. Taken together, the paper provides implications for various stakeholders who are interested in assessing and managing firms’ organizational capital. |
| JEL: | D22 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35039 |
| By: | Wagner, Joachim (Leuphana University Lüneburg) |
| Abstract: | In a paper published in the Journal of Information Economics in 2024 I reported evidence that firms which use cloud computing do more often export, do more often export to various destinations all over the world, and do export to more different destinations. Results are based on data for manufacturing firms from the 27 member countries of the European Union taken from the Flash Eurobarometer 486 survey conducted in 2020. This note uses strictly comparable data from the Flash Eurobarometer 559 conducted in 2025 and the identical empirical strategy to document that the big picture found for 2020 did not change over the last five years. Extensive margins of exports and the use of cloud computing are still positively related. |
| Keywords: | cloud computing, exports, firm level data, Flash Eurobarometer 559, kernel-regularized least squares (KRLS) |
| JEL: | F14 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18498 |
| By: | Nils M. Gornemann; Eugenio Rojas; Felipe Saffie |
| Abstract: | Does global financial risk affect long-run growth? Using a panel state-space model for emerging and advanced small open economies, we measure the effects of U.S. monetary policy uncertainty shocks. A one-standard-deviation shock lowers the level of the stochastic trend in emerging markets by at least 25 basis points after three years, with little effect in advanced economies. A small open economy model with growth through innovation and occasionally binding borrowing constraints explains this heterogeneity: higher interest-rate volatility depresses valuations, tightens collateral constraints, and slows innovation in equilibrium. A novel interaction between the occasionally binding constraint and stochastic volatility is key for our results. |
| Keywords: | Emerging market economies (EME); Dynamic stochastic general equilibrium (DSGE) models; Monetary policy; Productivity; Volatility |
| JEL: | F32 F41 G15 O16 |
| Date: | 2026–03–20 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgif:102989 |
| By: | Borjas, George (Harvard University) |
| Abstract: | The H-1B program lets firms hire high-skill foreign workers for a six-year term. The annual number of visas allocated to for-profit firms is capped at 85, 000 and there is excess demand for those visas. The analysis merges administrative data, including the I-129 petitions that report the wage offer made to specific H-1B beneficiaries, with the American Community Surveys. On average, H-1B workers earn 15 percent less than comparable natives, suggesting that firms may be willing to pay a one-time fee to obtain the visas. The data are examined using a labor demand model to simulate how a fee alters the hiring decision. For moderate levels of excess demand, the revenue maximizing fee ranges from $97, 000 to $154, 000 after allowing for unobserved productivity gains or costs associated with an H-1B hire, and for wage growth and job turnover in the H-1B workforce. The fee also changes the skill composition of that workforce, making it more skilled. |
| Keywords: | high-skill immigration, H-1B program, visa fees |
| JEL: | J08 J18 J69 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18487 |
| By: | Manuel Arellano; Orazio Attanasio; Margherita Borella; Mariacristina De Nardi; Gonzalo Paz-Pardo |
| Abstract: | We develop a new approach to estimating earnings, job, and employment dynamics using subjective expectations data from the NY Fed Survey of Consumer Expectations. These data provide beliefs about future earnings offers and acceptance probabilities, offering direct information on counterfactual outcomes and enabling identification under weaker assumptions. Our framework avoids biases from selection and unobserved heterogeneity that affect models using realized outcomes. First-step fixed-effects regressions identify risk, persistence, and transition effects; second-step GMM recovers the covariance structure of unobserved heterogeneities such as ability, mobility, and match quality. We find lower risk and persistence of the individual productivity component than in prior work, but greater heterogeneity in ability and match quality. Simulations show that reduced-form estimates overstate persistence and volatility on individual-level productivity due to job transitions and sorting. After accounting for heterogeneity, volatility declines and becomes flat across the earnings distribution. These results underscore the value of expectations data. |
| JEL: | C23 C8 D15 J01 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35027 |
| By: | Holden, Stein T. (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Makate, Clifton (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Tione, Sarah E. (Centre for Land Tenure Studies, Norwegian University of Life Sciences) |
| Abstract: | Reliable measurement of farm size is central to empirical research on agricultural structure, land inequality, and land use efficiency in developing countries. Most studies rely on single-round household survey data and implicitly assume that reported farm size is stable and accurately measured. This paper questions that assumption using balanced panel data from Ethiopia and Malawi. <p> We exploit within-household variation over time by comparing reported owned farm size in each survey round to the household-specific maximum observed across rounds, interpreted as an upper-envelope benchmark. We document large and widespread shortfalls from this benchmark that are frequently reversed across survey rounds, indicating episodic instability rather than monotonic landholding change. Instability is strongly associated with parcel attrition – captured by deviations from maximum plot counts and unmeasured parcels – while indicators of real landholding change explain little of the observed variation. <p> These findings imply that instability in reported owned farm size can materially affect measured farm size distributions, land inequality, and inferences about land markets and allocative efficiency. |
| Keywords: | farm size measurement; land ownership; panel survey data; land inequality; Sub-Saharan Africa |
| JEL: | C23 D31 Q12 Q15 |
| Date: | 2026–03–30 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nlsclt:2026_001 |
| By: | Khadija Moumtaz (UH2C - Université Hassan II de Casablanca = University of Hassan II Casablanca = جامعة الحسن الثاني (ar)) |
| Abstract: | Impact de l'IA sur la performance organisationnelle : le rôle médiateur du burnout et modérateur de l'IE |
| Date: | 2025–12–18 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05557734 |
| By: | Mr. Alberto Behar |
| Abstract: | Skilled wage premia in Latin American countries have continued declining, albeit more slowly and unevenly. Is the decline driven by demand or supply? This paper proposes a novel adaptation to the demand-supply decomposition framework by incorporating directed technical change (DTC), specifically supply-induced skill-biased technical change that acts to increase the wage premium. DTC counters the traditional substitution effect through which higher education wage attainment reduces the skill premium. Therefore, DTC makes adjusted inferred demand changes less skill biased than the standard framework’s traditional inferred demand changes. We apply the framework to ten Latin American countries over three periods, namely the length of the sample, the period between maximum wage premia and 2015, and since 2015. In our baseline results, DTC is quantitatively significant while the substitution effects remain important. Traditional demand shifts were skill biased over the length of the sample including since 2015 but our novel adjusted demand shifts were skill neutral. During the period between maximum premia and 2015, unadjusted demand shifts were skill-neutral and adjusted demand shifts favored unskilled workers. Equivalently, sizeable DTC effects imply wages would have fallen significantly faster in the absence of DTC. For an alternative elasticity of 1.25, DTC effects are smaller, supply effects are bigger, and adjustments to demand effects are smaller. For alternative supply measures, the results are relatively robust. |
| Keywords: | Skill-biased technical change; directed technical change; elasticity of substitution; schooling premium; wage premium; wage inequality. |
| Date: | 2026–03–27 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2026/054 |