Research

This paper investigates the macro-financial risks of the energy transition using an extended MATRIX model, a multi-agent, multi-sector integrated assessment framework for the Euro Area. The model features endogenous, directed technical change in the energy sector and a decentralized electricity market operating under a merit-order rule. Energy firms switch technologies based on relative profitability, creating feedback loops between R&D, productivity, and competitiveness, that can lead to either a brown lock-in or a green energy transition. We compare conventional environmental policies, such as a brown tax on polluting firms’ profits, a carbon tax on emissions, and green subsidies — both unconditional and R&D-based — with alternative policy mixes, including coordinated monetary policy, green finance, and green industrial policy. Results show that conventional policies modestly increase the likelihood of a green transition, but entail significant GDP losses due to production and financial constraints. Green finance and industrial policy mitigate these costs by easing sectoral bottlenecks and fostering a more effective transition. Finally, the brown tax proves more effective than carbon tax, as polluting firms tend to pass carbon costs onto consumers, reducing its impact.

Green preferences are often seen as crucial for mitigating climate change. Yet, it remains unclear whether they alone can drive the shift toward a low-carbon economy and what the distributional consequences might be. This paper studies the macroeconomic, environmental, and distributional effects of green preferences among consumers and producers using the agent-based integrated assessment MATRIX model. We compare scenarios with varying pro-environmental attitudes to conventional supply-side climate policies like carbon taxes and cap-and-trade mechanisms, with and without abatement investment subsidies and alternative redistribution strategies. Without an active policy, achieving a low-carbon transition requires unrealistically high values of green preferences among consumers and producers. Conversely, carbon taxes and cap-and-trade mechanisms can reach that objective, but at the cost of increased instability and inequality. Moderate abatement subsidies can balance those effects, reducing emissions while mitigating both economic and distributional challenges, especially when environmental revenues fund social transfers instead of tax cuts. 

This paper explores the potential impacts of climate change and mitigation policies in the Euro Area, considering the uncertainty and heterogeneity in both climate and economic systems. Using the MATRIX model, a multi-sector and multi-agent macroeconomic model, we simulate various climate scenarios by employing different carbon cycle models, damage functions, and marginal abatement curves found in the literature. We find that heterogeneous climate damages amplify both the magnitude and the volatility of GDP losses associated with global warming. By the end of the century, we estimate that assuming homogeneous shocks may underestimate the effects of climate change on aggregate output by up to one-third. Moreover, we find that the speed and feasibility of a low-carbon transition crucially depend on (i) the ambition in emission reduction targets set by the policymaker, which determine the level of a carbon tax, and (ii) the rate of technological progress, which influences the shape of the abatement cost curve.

We employ a new version of the ABC macro-epidemiological agent based model presented in Delli Gatti and Reissl (2020) to evaluate the effects of vaccinations and variants on the epidemic and macroeconomic outlook. Vaccination plays the role of a mitigating factor, reducing the frequency and the amplitude of contagion waves, while also significantly improving macroeconomic performance. The emergence of a variant, on the other hand, plays the role of an accelerating factor, increasing the volatility of epidemic curves and worsening the macroeconomic outlook. If a more contagious variant emerges after vaccination becomes available, therefore, the mitigating factor of the latter is at least partially offset by the former. A new and improved vaccine in turn can redress the situation. Vaccinations and variants, therefore, can be conceived of as drivers of an intertwined cycle impacting both epidemiological and macroeconomic developments.

The recent surge in energy prices in Europe has prompted governments to introduce policy measures to support households and businesses. This paper uses the MATRIX model, a multi-sector and multi-agent macroeconomic model calibrated on the Euro Area, to analyse the economic and distributional effects of different macro-stabilization policies in response to energy price shocks. We find that, without policies, a surge in fossil fuel prices leads to higher inflation, lower GDP, and slow recovery. Generalized tax cuts and household subsidies have no significant effects, while firm subsidies promote a faster recovery at the expense of financial instability in the medium term, leading to a second slump. However, this second-round effect can be mitigated with proper fiscal-monetary policy coordination. If timely adopted, a government-funded energy tariff reduction is the most effective policy in mitigating GDP losses at relatively low public costs, particularly when coupled with an extra-profit tax on energy firms. Energy entrepreneurs benefit from rising fuel prices in all scenarios, but workers and downstream firms’ owners benefit more from energy tariff cuts and windfall profits tax.

The global energy crisis that began in fall 2021 and the subsequent spike in energy prices constitute a significant challenge for the world economy that risks undermining the post-COVID-19 recovery. In this paper, we develop and calibrate a new Multi-Agent model for Transition Risks (MATRIX) to analyze the role of energy in the functioning of a complex adaptive system and the economic and distributional effects of energy shocks. The economic system is populated by heterogeneous agents, i.e., households, firms and banks, which take optimal decision rules and interact in decentralized markets characterized by limited information. After calibrating the model on US quarterly macroeconomic data, we assess the economic and distributional impacts of different types of energy shocks, namely: (i) an exogenous increase in the price of fossil fuels (e.g., oil or gas); (ii) a decrease in energy firms’ productivity; (iii) a reduction in the available quantity of fossil fuels. We find that the energy shocks entail similar effects at the aggregate level in terms of higher inflation and lower real GDP. Nevertheless, the distribution of gains and losses across sectors and agents varies significantly depending on the type of shock. Our findings suggest that policymakers should carefully consider the nature of energy shocks and the resulting distributional effects to design effective measures in response to energy crises.

The response of governments to the COVID-19 outbreak was foremost oriented to two objectives: saving lives and limiting economic losses. However, the effectiveness and success factors of interventions were unknown ex-ante. This study aims to shed light on the drivers of countries’ performances during the first year of the COVID-19 pandemic. We measure performances by excess mortality and GDP growth adjusted for additional fiscal stimulus. We conduct an empirical analysis in two stages: first, using hierarchical clustering, we partition countries based on their similarity in health and economic outcomes. Second, we identify the key drivers of outcomes in each country cluster by regression analysis, which include linear, least absolute shrinkage and selection operator (LASSO), and logit models. We argue that differences in countries’ performances can be traced back both to policy responses to COVID-19 and structural conditions, the latter being immutable over the pandemic. Three relevant structural conditions emerge from the results: trade reliance on services, corruption, and the size of the vulnerable population (elderly, low-income, smoking, or cardiovascular-failing). Policies such as large-scale open public testing and additional fiscal stimulus in non-health could help reduce excess mortality, which might lead to lower economic losses.

This paper presents a macroeconomic agent based model with endogenous innovation-driven growth and knowledge accumulation which aims to analyze the underlying causes of the recent increase in market concentration, by focusing on the interplay of technical change and market power, and the resulting macroeconomic consequences in terms of higher inequality and lower growth. The source of concentration lies in the fact that heterogeneous firms do not have equal access to capital-embodied innovations, as we assume that this depends on the “knowledge gap”, i.e., the difference between the degree of capital good’s technical advancement and the firm’s accumulated technological knowledge. The analysis shows that, in the absence of consistent knowledge spillovers and as long as capital goods remain considerably different from each other, technical progress generates systematic differences in productivity across firms, leading to a reallocation of market shares towards more productive firms. Consequently, as the newly-emerging large firms seek to translate the enhanced market power into higher mark-ups, the resulting shift in the income distribution from wages to profits eventually undermines aggregate demand and growth. Yet, simulation experiments reveal that the evolution of market concentration over time as well as its macroeconomic effects crucially depend on the presence (or lack thereof) of legal entry barriers, which, by influencing the process of diffusion of technological innovations, reinforce (or attenuate) the large firms’ ability to consolidate their dominant position and thus exploit their market power.