Conference Agenda

This paper presents a quantitative analysis of the European Union labor market and the green skills requirements along the transition towards a net-zero economy. Our study employs a Dynamic Stochastic General Equilibrium (DSGE) model that is enhanced to capture key labor market features, including: (i) skilled and unskilled workers; (ii) green and traditional skills employable in two different productive sectors, i.e., clean and dirty; (iii) green and conventional vocational education programs; (iv) clean technology adoption from pollutant firms. This model enables the analysis of the labor market implication and skills requirements of a gradual increase in the emission tax. Three main findings emerge from our study. First, skills heterogeneity and the ability of unskilled workers to invest in education generate mild positive long-run effects on consumption, output, and hours. Second, an increase in green education programs (about 7.54% ) is essential for acquiring the necessary skills to meet climate goals. Third, skills heterogeneity, green educational programs, and relative employment frictions are accompanied by gradual gains in dirty output, investment, and labor, along the transition. In conclusion, abstracting from job skills and education heterogeneity in this framework entails that the same policy has misleading effects, revealing the importance of these channels for a complete analysis of the macroeconomic consequences of the green transition.

To reduce greenhouse gas emissions, a growing number of countries are resorting to carbon taxes. They pursue various approaches to cushion social hardships and ensure democratic support. The aim of this study is to investigate public acceptance of a carbon tax in Austria (n=1216). Our findings show that specifying the use of tax revenues significantly improves acceptance rates. Accordingly, if tax revenues will be spent on public transport or climate protection measures, public acceptance is maximized and tax increases of up to 50€-cents per liter fuel are majority capable. On the other hand, all the other tested earmarking strategies are unacceptable to a majority of respondents, independent of the tax rate and annual repayment. Tax rates of 75€-cents or higher are shown to be too high and thus prohibitive for majority support. Annual lump-sum payments between €50 and €100 lead to the highest acceptance rates, while €200 and €300 reduce the likelihood of majority support across our sample. Finally, earmarking strategies in general are found to be more important to our experiment participants than lump-sum payments.

We estimate an EASI demand system with nonlinear Engel curves, a labour supply schedule, and an income tax schedule from German household data. We combine this with a model of households’ and firms’ carbon emissions to obtain a micro-based simulation model of the German economy. The policy of pricing carbon and rebating the revenue as lump-sum climate dividends curbs emissions and offsets some of the adverse effects on the equity of regressive carbon taxes. If the government is permitted to also reform the income tax system, it never lowers income tax revenue, but makes the tax slightly less progressive in a budgetary-neutral fashion while simultaneously increasing the optimal carbon tax and climate dividend. Carbon tax and climate dividends rise with inequality aversion and carbon is priced consistently below the Pigouvian rate except if inequality aversion is high enough. We decompose the effects on welfare into efficiency, equity, and emission components for different degrees of inequality coefficient and climate damages. Income tax reform is preferred over climate dividends when raising carbon taxes if inequality aversion is low and vice versa.

This research investigates the influence of extreme climate events on income distribution at the municipality level in Italy by leveraging on a novel dataset spanning from 2000 to 2021. To assess the occurrence of climate events, two distinct datasets are employed. The first dataset, ERA5 from Copernicus datastore, offers daily precipitation and temperature data across Europe at a 5.5km x 5.5km grid resolution. The second dataset is specifically designed on disasters event, the European Severe Weather Database (ESWD), which provides geo-referenced information concerning catastrophic events.

To establish the relationship between extreme climate events and income distribution, this study, spatially matches each catastrophic event, temperature, and precipitation to the corresponding municipality where it transpired. Econometric techniques are then employed to estimate the impact of these extreme events on the average income growth for several segment of the income distribution.

Our estimates indicate that extreme climate events lead to decreased income growth for the lower-income group within each municipality, while having no impact on the top income earners.

By shedding light on the socioeconomic consequences of extreme climate events, this research contributes to a better understanding of the complex relationship between climate change and income inequality, offering valuable insights for policymakers in devising targeted mitigation and adaptation strategies.