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Working Paper. No 310: Crowding out or Knowledge Spillovers: The Wind Power Industry´s Effect on Related Energy Machinery

Abstract

There is a risk that if a government adopts a R&D spending policy directed towards wind power technology crowding out of other technologies might occur due to fiscal constraints and changes in relative prices. The purpose of this paper is to provide a backward-looking analysis of how the accumulation of wind energy patents and public R&D spending affected the domestic and neighboring country output of granted patents in the “related energy machinery field”. The econometric analysis, a Poisson fixed-effects estimator based on the Hausman, Hall and Griliches (1984) method, relies on a data set consisting of eight countries in Western Europe with the highest rates of patent production in the field of wind power between 1978 and 2008. The results show that an accumulation of a national wind power stock is a statistically significant negative determinant of a country’s related energy machinery patenting outcomes. However, no crowding out effects of public R&D spending were found.

Grafström, J. (2018). Crowding out or Knowledge Spillovers: The Wind Power Industry´s Effect on Related Energy Machinery. (Ratio Working Paper No. 310)

Similar content

Article (with peer review)

Barriers to circularity in the metals industry: an analytical framework of feedback and lock-in effects

Grafström, J., Poelzer, G., & Pettersson, J.

Publication year

2025

Published in

Mineral Economics.

Abstract

The metals sector faces multiple and interconnected barriers to achieving circularity. This study examines steel, aluminum, and copper to illustrate how challenges vary between metals. While copper can often be recycled without quality loss, steel and aluminum face alloy-related limitations that drive downcycling and quality degradation. Using a matrix-based analytical framework, the study maps the interactions between economic, technological, institutional, and social constraints, distinguishing between primary drivers, secondary effects, feedback loops, and lock-in mechanisms. The results show strong reinforcing links between economic, technological, and institutional domains, with social factors playing a more indirect role. These findings align with observed industry patterns while adding a structured, quantitative perspective. By clarifying how different barriers combine and reinforce one another, the analysis identifies priority areas for intervention to advance metals recycling and support the transition toward a more circular economy.

Working Paper No. 387 Time as a Structural Barrier for a Circular Economy

Jonas Grafström

Publication year

2025

Published in

Ratio Working Paper Series.

Abstract

Circular economy debates often acknowledge material lifespans and delays, but time is usually treated as a contextual issue rather than a structural barrier. The contribution is to reframe circular economy transitions as intertemporal processes by treating time as an endogenous structural barrier. A framework is developed that classifies goods into short-, medium-, and long-lived categories, demonstrating how lagged inflows and valuation biases suppress aggregate circularity even when technology improves. By making temporal mechanisms explicit, the analysis explains why indicators remain stagnant despite policy and efficiency gains. The contribution is to introduce time as an endogenous barrier, integrating insights from environmental and resource economics into circular economy theory and showing how delayed substitution shapes both firm investment and policy outcomes.

Working Paper No. 385 The workload paradox: Will AIreduce academic labor?

Jonas Grafström

Publication year

2025

Published in

Ratio Working Paper Series.

Abstract

Artificial intelligence is reshaping academia, but instead of liberating scholars, AI might keep them running faster just to stay in place. This paper theoretically explores how AI increases institutional expectations rather than reducing workload. Using a formal workload model, the study examines how automation affects academic tasks, revealing that while AI streamlines some processes, it also creates new responsibilities in research, publishing, and administration. A case study illustrates how scholars experience rising pressures to verify AI-generated work, adapt to changing publication norms, and meet intensifying institutional demands. The findings suggest that AI’s role in academia is not one only of simplification, but acceleration—a race where efficiency gains are quickly absorbed, where the pursuit of academic excellence becomes ever more demanding, and where scholars must continuously push forward, not to advance, but merely to avoid falling behind.

Details

Author: Grafström, J.
Publication year: 2018
Published in: Ratio Working Paper

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Ph.D. and vice CEO
Jonas Grafström
+46703475854jonas.grafstrom@ratio.se