Vietnam, a lower-middle-income economy, faces severe climate risks from heat waves, sea-level rise, and tropical cyclones, which are expected to intensify under ongoing global warming. Using a dynamic general equilibrium model, we analyze economic transition dynamics from 2015 to 2100, incorporating heat-induced labor productivity losses, agricultural land loss, and cyclone-related property damage. We compare a Paris-compatible scenario limiting warming to below 2 °C with a high-emission scenario reaching 4–5 °C. While output and investment impacts remain highly uncertain and statistically indistinguishable across scenarios until 2100, consumption losses are significantly larger under high emissions, mainly driven by heat-related productivity declines, with cyclones contributing most to uncertainty. These findings underscore the importance of considering multiple impact channels beyond output damages in climate-development research.

Lowering carbon intensity in manufacturing is necessary to transform current production technologies. We test if local agents’ preferences, revealed by vote shares for the Green party during local elections in Germany, relate to the carbon intensity of investments in production technologies. Our sample comprises all investment choices made by manufacturing establishments from 2005-2017. Our results suggest that ecological preferences correlate with significantly fewer carbon-intensive investment projects while investments stimulating growth and reducing carbon emissions increase by 14 percentage points. Both results are more distinct in federal states where the Green Party enjoys political power and local ecological preferences are high.

Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.

Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.

We propose a novel mechanism through which established firms contribute to the startup ecosystem: the allocation of R&D tax credits to startups via the M&A channel. We show that when established firms become eligible for R&D tax credits, they increase their R&D and M&A activity. In particular, they acquire more venture capital (VC)-backed startups, but not non-VC-backed firms. Moreover, the impact of R&D tax credits on firms’ R&D is increasing with their acquisition of VC-backed startups. The results suggest that established firms respond to R&D tax credits by acquiring startups rather than solely focusing on increasing their R&D intensity in-house. We also highlight evidence that startups do not appear to benefit from R&D tax credits directly, perhaps because they typically lack the taxable income necessary to directly benefit from the tax credits. In this context, established firms can play an intermediary role by acquiring startups and reallocating R&D tax credits, effectively relaxing the financial constraints faced by startups.