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on Macroeconomics |
| By: | Alexander Meléndez (Banco Central de Reserva del Perú) |
| Abstract: | This paper examines the influence of monetary policy and the zero lower bound (ZLB) on government consumption and investment multipliers in Peru from 1996Q1 to 2023Q3. Using a hybrid Time-Varying Parameter Vector Autoregression with Stochastic Volatility (TVP-VAR-SV), the study estimates impulse response functions, fiscal multipliers, forecast error variance decompositions, and historical decompositions for each quarter of the sample. The results indicate that a tighter monetary policy stance is associated with lower estimated government consumption and investment multipliers, consistent with standard monetary-fiscal interaction mechanisms documented in the literature. Moreover, following the adoption of an explicit policy rate framework, estimated fiscal multipliers exhibit greater sensitivity to interest rate conditions. In this context, the COVID-19 period provides a natural episode of historically low policy rates, approximating a ZLB-type environment from an analytical perspective, under which estimated government investment multipliers increase significantly, in line with the international literature. These findings contribute to the literature on monetary–fiscal policy interactions in emerging market economies operating under inflation targeting and a managed floating exchange rate regime. |
| Keywords: | fiscal multipliers, monetary policy, zero lower bound, emerging country |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:rbp:wpaper:dt-2026-016 |
| By: | Luca Fornaro; Martin Wolf |
| Abstract: | We provide a macroeconomic framework to study monetary and fiscal policies for AI. Advances in AI expand firms’ ability to automate production. While higher automation boosts productivity and potential output, it also reduces workers’ share of income. Since workers have a high propensity to consume, advances in AI may depress aggregate demand and lead to a slump. Expansionary monetary policy can convert an AI slump into an AI boom, but in doing so it faces two challenges. In the short run, AI worsens the inflation-employment trade off faced by the central bank. In the medium run, monetary policy may be constrained by the zero lower bound, since weak demand lowers the natural rate. Employment subsidies and cuts in labor taxes can usefully complement monetary policy, by reducing firms’ cost of labor and inflation, as well as supporting workers’ income and aggregate demand. |
| Keywords: | monetary policy, automation, AI, inflation, liquidity traps, endogenous productivity, wages, artificial intelligence |
| JEL: | E32 E43 E52 O31 O42 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:upf:upfgen:1943 |
| By: | Michael Pfarrhofer (Vienna University of Economics and Business); Anna Stelzer (Oesterreichische Nationalbank) |
| Abstract: | We assess asymmetries, nonlinearities and state dependencies in dynamic responses of the euro area to monetary policy shocks. The dataset includes macroeconomic, financial, and survey-based variables measuring credit conditions and bank lending transmission channels. These data are observed at different frequencies. We propose a multivariate nonparametric mixed-frequency model, and discuss how to compute dynamic causal effects in a nonlinear context. The results suggest limited effects of expansionary policy shocks whereas contractionary shocks yield responses in line with theory. There is little variation over the business cycle and in distinct periods such as at the effective lower bound. |
| Keywords: | nonlinear structural inference, mixed frequency data, Bayesian nonparametrics, credit channel |
| JEL: | C32 E32 E52 |
| Date: | 2026–03–16 |
| URL: | https://d.repec.org/n?u=RePEc:onb:oenbwp:276 |
| By: | Francesco Vidoli (Department of Economics, Society & Politics, Università di Urbino Carlo Bo); ; |
| Abstract: | Standard policy evaluation methods typically assume that treatment effects are homogeneous within fixed administrative units. However, the true policy relevant boundaries are typically unknown to the researcher, as latent territorial characteristics, such as institutional quality or local economic structure, generate unobserved spatial heterogeneity that does not align with administrative borders. To address this challenge, we propose a novel unsupervised learning algorithm that endogenously identifies geographic regimes heterogeneous in terms of causal impact. Unlike existing clustering methods that group units based on geometric density or outcome similarity, our approach partitions spatial units specifically on the basis of their causal response to treatment. By explicitly maximizing treatment effect variance subject to spatial coherence, we identify where policies have differential impacts, recovering latent economic boundaries while maintaining identification requirements. We validate the estimator through Monte Carlo simulations, demonstrating its robustness in recovering latent economic structures even in high-noise environments. Finally, we apply the method to analyse the local labour market effects of the 2001 Chinese import competition shock in the United States, revealing distinct latent spatial regimes of industrial resilience that cut across state lines. |
| Keywords: | Difference-in-Differences, Spatial Heterogeneity, Treatment Effect Heterogeneity, Clustering Algorithms, Place-Based Policies, Causal Inference |
| JEL: | C21 C23 H40 R10 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:urb:wpaper:26_01 |
| By: | Hendrickx, Stef (RS: GSBE other - not theme-related research, ROA / Human capital in the region); Huijgen, Timo (RS: GSBE other - not theme-related research, ROA / Health, skills and inequality); van Wetten, Sanne (RS: GSBE other - not theme-related research, ROA / Education and transition to work) |
| Abstract: | In dit rapport worden de mogelijkheden beschreven voor het uitbreiden van de NCO-data (Nationaal Cohortonderzoek Onderwijs) naar het mbo. In het eerste deel van het rapport wordt verkend hoe het NCO uitgebreid kan worden met CBS-data en met informatie uit de schoolverlatersonderzoeken. Allereerst is het nodig om de NCO-populatie aan te passen zodat de data ook dekkend worden voor het mbo-onderwijsveld. Omdat het huidige NCO zich richt op de cohorten in het po en vo zijn de data op dit moment alleen dekkend voor het mbo voor zover leerlingen van het vo naar het mbo zijn doorgestroomd. De populatie die aan de basis staat van de NCO-bestanden zal dus uitgebreid moeten worden zodat ook de indirecte instroom in het mbo vanuit onder andere de arbeidsmarkt meegenomen kan worden. Ook zal er een uitbreiding van de in het NCO opgenomen variabelen nodig zijn omdat er een aantal belangrijke variabelen voor het mbo nu nog niet in de data opgenomen zijn. Hierbij gaat het met name om variabelen die iets zeggen over de gevolgde opleiding in het mbo en afgeleide classificaties van deze gevolgde opleiding. Daarnaast is er soms een aanpassing van de inhoud van al in de NCO-data aanwezige variabelen nodig. Zo verdient het aanbeveling om de volledige versie van de variabele over de examenuitslag in het vo op te nemen behalve de nu, voor NCO aangepaste, beperkte versie. Voor sommige variabelen geldt dat de reikwijdte in jaren uitgebreid moet worden zoals de variabele over de sociaaleconomische status van de onderwijsdeelnemers. Verder wordt ook de relevantie van de microdata van de schoolverlatersonderzoeken (SVO) toegelicht. Deze data zijn al opgenomen in de registerdata van het CBS en kunnen voor onderzoeken naar het mbo van toegevoegde waarde zijn. In het tweede deel van dit rapport wordt een factsheet gepresenteerd. In dit factsheet worden een (niet uitputtend) aantal figuren gepresenteerd die met de voor mbo aangepaste dataset mogelijk zouden zijn |
| Date: | 2026–04–21 |
| URL: | https://d.repec.org/n?u=RePEc:unm:umarot:2026003 |
| By: | Ahmet Gulek |
| Abstract: | I study how local immigration shocks impact labor markets and firms across the economy through production networks. Using Turkey's Syrian refugee crisis and firm-level trade network data, I show that firms buying from host regions demand more labor, while those selling to host regions increase sales. These spillovers depend critically on network centrality: a 1% labor supply increase in Istanbul decreases local real wages by 0.56% while increasing non-host wages by 0.38%. For non-central regions, identical shocks reduce local wages by 1% with negligible spillovers. Network position thus determines whether immigration only lowers local wages or also generates economy-wide gains. |
| Keywords: | Immigration, trade, production network |
| JEL: | F16 F22 J15 J23 J61 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:25109 |
| By: | Juan Manuel Campana; Eckhard Hein |
| Abstract: | This paper investigates the drivers of economic growth by focusing on macroeconomic policy regimes (MPRs) as a key dimension of demand and growth regime (DGR) and growth model (GM) analysis. Building on Campana and Hein’s (2026) results on demand-led growth decomposition based on the national income and financial accounting (NIFA) and the Sraffian supermultiplier (SSM) approaches for seven economies—Germany, Spain, Argentina, Brazil, India, South Africa, and Turkey—across the periods 2000–2007 and 2011–2019, this paper applies the MPR approach to understand the differences in DGRs and their respective changes. The paper thus contributes to post-Keynesian and comparative political economy literature. The analysis shows that the configuration and coordination of monetary, wage, fiscal, and external policies play a central role in shaping dominant sources of autonomous demand and explaining regime shifts over time. While some countries, such as Germany and India, display stability in their MPRs, DGRs, and dominant autonomous demand components, others—Spain, Brazil, South Africa, and Turkey—have undergone significant transformations driven by policy changes and external conditions. Overall, the findings highlight the explanatory power of MPR analysis in understanding growth trajectories and provide foundations for the examination of the political economy dimension of these trajectories. |
| Keywords: | macroeconomic policy regimes, growth decomposition, post-Keynesian macroeconomics, growth drivers, growth models, demand and growth regimes |
| JEL: | E11 E12 E60 F43 O57 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:pke:wpaper:pkwp2611 |
| 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 |
| By: | Mario Huarancca (Banco Central de Reserva del Perú); Maria Rita Huarancca (Banco Central de Reserva del Perú) |
| Abstract: | Este estudio evalúa el impacto del terremoto de Pisco de 2007 sobre la acumulación de capital humano en el Perú, medido en años de educación. Utilizando microdatos del Censo de Población y Vivienda 2017 e información geoespacial de intensidad sísmica (MMI), se implementa una estrategia de diferencias en diferencias por cohorte y distrito de residencia, la cual explota la variación del año de nacimiento y la exposición geográfica al terremoto. Los resultados muestran que la población más expuesta al terremoto acumuló, en promedio, menos años de educación (-0, 67 años) respecto aquella población que residió en distritos alejados del epicentro. Asimismo, la exposición al terremoto de 2007 redujo significativamente la probabilidad de completar la educación primaria (-0, 06 puntos) y secundaria (-0, 07 puntos) entre las cohortes jóvenes en las zonas afectadas, sugiriendo así que, el impacto negativo del terremoto sobre el capital humano no solo se traduce en interrupciones temporales de la etapa escolar, sino también en potenciales abandonos del sistema educativo. Estos resultados son persistentes bajo diversos ejercicios de robustez y sugieren que el principal canal de transmisión es la destrucción de infraestructura educativa. El estudio concluye que los efectos del terremoto no se limitaron a pérdidas humanas y daños materiales inmediatos, sino que generaron pérdidas, de largo plazo, en el capital humano y evidenciaron la necesidad de incorporar la dimensión educativa en las estrategias de gestión del riesgo y respuesta post-desastre. |
| Keywords: | Terremoto, Educación, Infraestructura, Perú |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:rbp:wpaper:dt-2026-014 |
| By: | Alena Gorbuntsova; Gaurav Khanna; Sultan Mehmood |
| Abstract: | Wars are often framed as responses to external threats or shifts in the regional balance of power. Yet they can also serve domestic political ends. This paper studies how Russia’s escalations against Ukraine reshaped support for the regime and redistributed the burdens of war across the population. Combining ethnic Russian shares with election and independent polling data, we exploit two sharp geopolitical shocks, the 2014 annexation of Crimea and the 2022 full-scale invasion, in a difference-in-differences event-study design. We find that provinces with larger ethnic Russian populations exhibit sharp increases in support for President Putin following both episodes. At the same time, battlefield casualties fall disproportionately on regions with lower ethnic Russian shares, and attitudes toward the US and EU deteriorate sharply. On the Ukrainian side, Russian attacks are concentrated in areas with higher ethnic Russian shares rather than in resource-rich provinces. Explanations based on material extraction, Soviet symbolism, or differential exposure to external threats do not account for these patterns. Instead, the evidence is more consistent with ethnic identity playing a central role in the domestic political economy of the war. Our conclusions remain similar in fraud-adjusted electoral outcomes, with alternative ethnicity measures, under bounded departures from parallel trends, and after accounting for several baseline regional differences. |
| JEL: | F50 O43 P50 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35107 |
| By: | Bouzahzah, Mohamed |
| Abstract: | This paper addresses a persistent and consequential puzzle in climate econometrics: the recurring observation of null climate effects in panel fixed-effects models for African agriculture, despite overwhelming agronomic and micro-level evidence of climate vulnerability. This identification failure has led to confusion regarding climate risk assessment among policymakers. Recent studies by Gebreslassie (2024) and Affoh et al. Robustness checks confirm null findings are stable across alternative standard error specifications, ruling out error misspecification as an explanation. (2024) continue to document these statistically insignificant effects once year fixed effects are included. Using cereal yields from ten African countries (2000-2023), we deliberately replicate this "null results paradox" -our baseline specification with year fixed effects produces no significant climate coefficients (p > 0.28) for temperature and precipitation). Through variance decomposition, we provide the first empirical quantification of this identification failure: we demonstrate that the annual fixed effects alone absorb 15 percentage points of the explanatory power for within-country yield variation (R2 reduction from 0.380 to 0.230). Crucially, we demonstrate that the annual fixed effects act as a statistical absorber, masking economically significant relationships. When year dummies are removed, the strong and theoretically sound signal of fertilizer use (coefficient = 0.202, p |
| Keywords: | Climate econometrics; Panel data; Fixed effects; Identification; Agricultural productivity; Africa; Year dummies; Spatial correlation |
| JEL: | C23 O13 Q15 Q54 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:128054 |
| By: | Kaja, Fatjon |
| Abstract: | This article advances a new perspective on corporate purpose, grounded in the institutional conditions under which corporate privileges are granted. Using a novel dataset of historical UK royal charters and a mixed-methods empirical strategy, the study shows that early corporations articulated specific, enforceable, and public-facing purpose clauses because incorporation was a scarce privilege that allowed the Crown to impose obligations as a "asking price" for the benefits of the corporate form. Machine-learning evidence demonstrates that clauses reflecting Crown leverage cluster systematically and decline over time as incorporation becomes more accessible. The findings reframe corporate purpose not merely as a normative contest among stakeholders but as the product of institutional bargaining at the point of corporate formation, offering a historical lens for contemporary purpose debates. |
| Keywords: | corporate purpose, UK royal charters, text as data, shareholder primacy, historical perspective |
| JEL: | K00 K2 K22 N80 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:safewp:340163 |
| By: | Ihsaan Bassier; Joshua Budlender |
| Abstract: | When firm productivity or product demand rises, workers typically share in the gains through higher wages or expanded employment. We show that for firms under monopsony with a binding minimum wage, this link from firm gains to worker outcomes breaks sharply. Revenue-productivity improvements raise revenues but not wages or employment: firms simply maintain the minimum wage and absorb the gains into higher wage markdowns. We find compelling evidence for these predictions using South African administrative data, based on a cross-sectional kink design as well as within-firm responses to internal and shift-share trade shocks. These results reveal a previously overlooked monopsonistic margin---productivity-induced markdown adjustment---and we show using a structural model that this substantially diminishes the intended returns of policies such as employment subsidies. |
| Keywords: | Monopsony, Rent-sharing, Minimum wage, Firm productivity |
| JEL: | D22 J31 J38 J42 O33 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:25122 |
| By: | Seema Jayachandran; Lea Nassal; Matthew J. Notowidigdo; Marie Paul; Heather Sarsons; Elin Sundberg |
| Abstract: | Many couples face a trade-off between advancing one spouse's career or the other's. We study this trade-off using administrative data from Germany and Sweden. Using an event study approach, we find that when couples move across commuting zones, men's earnings increase more than women's. To distinguish between two leading explanations - men's greater potential earnings and a gender norm of prioritizing men's careers - we examine how the patterns differ when the woman has the higher potential earnings. We then estimate a model of household decision-making in which households can (and do) place more weight on the man's earnings. |
| Keywords: | Labor migration, tied movers, gender gap in earnings |
| JEL: | J61 J16 R23 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26017 |
| By: | Alexander Ahammer; Martin Halla; Pia Heckl; Rudolf Winter-Ebmer |
| Abstract: | Long-term unemployment among older workers is particularly difficult to overcome. We study the impacts of a large-scale job guarantee program that offered up to two years of fully subsidized employment to long-term unemployed individuals aged 50 and above. Using a sharp age-based discontinuity in eligibility, we find that participation increased regular, unsubsidized employment by 43 percentage points two years after the program ended. The gains are driven by transitions into new firms and industries, rather than continued subsidized employment, and we find no evidence of displacement effects for non-participants or spillovers to family members. The program had no measurable short-run health effects. |
| Keywords: | Long-term unemployment, temporary job guarantee, subsidized employment, health status. |
| JEL: | J64 J08 J78 I14 H51 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:25160 |
| By: | André L. S. Chagas (Department of Economics, University of São Paulo) |
| Abstract: | This paper develops specification tests for irregular network panels with time-varying and asymmetric interaction matrices. We decompose each matrix into symmetric and antisymmetric components and show that standard residual quadratic diagnostics, including Moran’s I and the LM-error statistic, are exactly invariant to the antisymmetric component. In contrast, lag-type bilinear diagnostics retain directional information. Building on this dichotomy, we derive a joint score limit for the decomposed lag alternative and propose conditional score tests for directional and contextual relevance. The directional statistic LM tests whether the antisymmetric component contributes information beyond symmetric exposure, while LM provides the corresponding contextual test. The tests have standard chi-square limits under primitive conditions for irregular panels. Monte Carlo evidence shows that the decomposed tests control size and correctly attribute network propagation across contextual and directional channels, whereas conventional quadratic diagnostics are exactly direction-blind and conventional lag diagnostics conflate the two channels. |
| Keywords: | spatial econometrics; network panels; specification testing; asymmetric weight matrix; directed propagation; contextual dependence |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ris:nereus:022454 |
| By: | Victor Lavy; Assaf Yancu |
| Abstract: | This paper examines the impact of classroom exposure to peers with a history of violent behavior on academic achievement and the underlying mechanisms. This measure of peer violence departs significantly from earlier studies that measured potential peer violence based on the background characteristics of students. We exploit idiosyncratic treatment variations during the transition from primary to middle school for causal identification. We find that a higher proportion of violent peers negatively affects cognitive performance in tests in various subjects, particularly pronounced in mathematics and English, compared to Hebrew and science. These effects are more pronounced in girls than in boys. While boys' performance is negatively influenced only by the presence of violent male peers, girls are adversely affected by both violent male and female peers. As for mechanisms, violent peers disrupt learning environments and lower teachers' productivity, reflected in lower job satisfaction and perception of higher workloads. Violent peers also significantly increase the likelihood of other students engaging in physical fights, and reduce their homework time, especially for girls and students from low SES. |
| Keywords: | violent peers, classroom environment, cognitive performance, mechanisms |
| JEL: | J10 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:25127 |
| By: | Christopher J. Waller |
| Date: | 2026–04–17 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgsq:103056 |
| By: | Reiter, Renate; Riese, Dorothee; Ewert, Benjamin; Klenk, Tanja; Lückenbach, Caspar; Kurrek, Dennis |
| Abstract: | Die Corona-Pandemie hat den Öffentlichen Gesundheitsdienst als dritte Säule des Gesundheitswesens in den Fokus öffentlicher und politischer Debatten gerückt, auch durch den milliardenschweren "Pakt für den Öffentlichen Gesundheitsdienst" von 2020. Die damit und auch über den Pakt hinaus angestoßenen Modernisierungsprozesse sind jedoch noch weitgehend unerforscht. Auf der Grundlage einer Befragung der kommunalen Gesundheitsbehörden in Deutschland präsentiert dieses Working Paper Befunde zur Modernisierung des Öffentlichen Gesundheitsdienstes in den Bereichen Personal, Organisation, Digitalisierung und Governance. Es finden sich Ansatzpunkte für eine programmatische Modernisierung, während Bestehendes an vielen Stellen pfadabhängig weiterentwickelt wird. |
| Keywords: | Gesundheit, Behörden, Modernisierung, Verwaltung, Personal |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:hbsfof:340161 |
| By: | Du, Zaichuan |
| Abstract: | By integrating Discrete Exterior Calculus (DEC) with upwind stabilization, I develop a structure-preserving numerical scheme that guarantees absolute mass conservation in heterogeneous agent models. Standard finite difference methods rely on algebraic approximations that entangle state dimensions. DEC, instead, natively isolates economic forces: exogenous income diffusion operates strictly on vertices, while endogenous savings advection flows across edges. This topological modularity rigorously justifies finite volume techniques on non-uniform grids and perfectly unifies the mechanism of different numerical methods used in continuous and discrete time, revealing the Endogenous Grid Method and Young’s projection as exact geometric Pullback and Pushforward operators. Crucially, DEC’s strict operator separation unlocks Strang splitting for transition dynamics. By safely decoupling income uncertainty from wealth accumulation, this fractional step method avoids dynamic multidimensional matrix inversions. Resolving advection via independent one-dimensional sweeps and pre-factorizing the static diffusion operator achieves more than a 2x computational speedup over purely finite difference iteration. |
| Keywords: | heterogeneous agent, incomplete market, discrete exterior calculus, mean field game |
| JEL: | C61 C63 E21 |
| Date: | 2026–04–03 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:128565 |
| By: | Giuseppe Pulito; Mariola Pytlikova; Sarah Schroeder; Magnus Lodefalk |
| Abstract: | Using two waves of nationally representative Danish firm surveys linked to employer– employee administrative registers, we study how adoption varies across artificial intelligence (AI) and related advanced technologies. We show that AI adoption is highly technologyspecific. While firm size and digital infrastructure predict adoption broadly, workforce composition operates through distinct channels: STEM-educated workforces predict core AI adoption, whereas non-STEM university-educated workforces are associated with generative AI adoption, indicating different human capital complementarities. The factors associated with adoption differ from those predicting deployment breadth: firm size and digital maturity matter for both, whereas workforce composition primarily predicts adoption alone. Machine learning and natural language processing are deployed across multiple business functions, whereas other advanced technologies remain concentrated in specific operational domains. Individual-level evidence provides a foundation for these patterns, with awareness of workplace AI usage concentrated among managers and high-skilled workers. Self-reported AI knowledge is higher among younger and more educated individuals. Finally, commonly used occupational AI exposure measures vary substantially in their ability to predict observed 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:cer:papers:wp818 |
| By: | Alessandro Fabbri; Michele Pellizzari |
| Abstract: | This paper examines earnings differences between first-generation and continuing generation college graduates across 24 OECD countries using data from the OECD Survey of Adult Skills (PIAAC). In all but two of the countries analysed, first-generation graduates earn less than their peers from college-educated families, with an average gap across all countries of approximately 8%. We investigate potential mechanisms behind this result and find that first-generation graduates are less likely to pursue postgraduate education, more likely to hold vocational degrees, and tend to have lower cognitive skills. These findings highlight the need for policy interventions to enhance educational mobility and promote equality of opportunity. |
| Keywords: | Inequality, Tertiary education, Intergenerational mobility |
| JEL: | I23 I24 J62 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:2597 |
| By: | Matías Gutman (ZS Associates. Buenos Aires, Argentina.); Juan Carlos Hallak (Universidad de Buenos Aires. Facultad de Ciencias Económicas. Instituto Interdisciplinario de Economía Política (IIEP UBA–CONICET). Buenos Aires, Argentina.) |
| Abstract: | Este trabajo examina el Plan Calidad Argentina (PCA), lanzado en 2016 como un experimento de política pública para abordar la infraestructura de la calidad fragmentada del país y fortalecer la competitividad exportadora. El PCA representó el primer alineamiento explícito del Sistema Nacional de la Calidad con una estrategia de desarrollo exportador, fomentando la coordinación entre los actores del sistema, particularmente sus tres pilares —metrología (INTI), normalización (IRAM) y acreditación (OAA)—, y promoviendo iniciativas sectoriales de mejora de la calidad. Utilizando un enfoque histórico-institucional, el artículo describe la creación y consolidación del PCA, así como su continuidad a través de gobiernos sucesivos. El PCA mejoró la coordinación, amplió las capacidades de acreditación y certificación, y posicionó la política de calidad como una herramienta para la inserción internacional. Sin embargo, el recambio político, las restricciones fiscales y el débil apoyo de alto nivel limitaron su sostenibilidad. La experiencia argentina destaca la importancia del diseño de políticas "de abajo hacia arriba", la construcción de confianza entre los actores y mecanismos de gobernanza resilientes para fortalecer la política nacional de calidad. En términos más amplios, ilustra cómo los sistemas de calidad coordinados pueden convertirse en un impulsor de competitividad en países en desarrollo. |
| Keywords: | Infraestructura de calidad; Política de calidad; Coordinación; Plan Calidad Argentina |
| JEL: | F13 F63 H11 H41 H83 L15 L52 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:ake:iiepdt:2025-108 |