This paper analyzes the implications of different designs of policies, which aim to contain the diffusion of the SARS-CoV-2 virus, with respect to induced economic loss and virus mortality. An agent-based simulation model is implemented and calibrated with German data, which combines the representation of a simple multi-sectoral closed economy with the explicit incorporation of virus transmission channels at the workplace, during shopping activities and other social contacts. It is demonstrated that under a policy resembling German containment measures the model closely reproduces the dynamics of pandemic and economic variables in the aftermath of the COVID-19 outbreak in Germany. Exploring alternative policy designs shows that any efficient policy should impose a low threshold of newly infected for moving from the lock-down to the opening-up stage and in the opening-up stage all restrictions on economic activity should be lifted. With respect to the reduction of consumption activities during the lock-down a trade-off between the induced GDP loss and the resulting mortality emerges. Regardless of the chosen design of the containment measures, the introduction of complementary economic support measures substantially reduces the induced GDP loss and leads to a reduction of the public debt accumulated during the considered time interval. The efficient design of containment policies changes substantially if lifting economic restrictions during the opening-up stage also results in reduced effectiveness of the individual prevention measures by agents.

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In this paper, we study the effect of different types of technological regime changes on the evolution of industry concentration and wage inequality. Using a calibrated agent-based macroeconomic framework, the Eurace@Unibi model, we consider scenarios where the new regime is characterized by a finite time period of more frequent respectively more substantial changes in the frontier technology compared to the old regime. We show that under both scenarios, the regime change leads to an increase in the heterogeneity of productivity in the firm population and to increased market concentration, where effects are much less pronounced if the new regime differs from the old one with respect to the frequency of innovations. If the new regime is characterized by an increase of the size of the frontier jumps along the technological trajectory, the evolution of the wage inequality has an inverted U-shape with a large fraction of workers profiting in the very long run from high wages offered by dominant high-tech firms. Finally, it is shown that (observable) heterogeneity of worker skills plays an important role in generating these dynamic effects of technological regime changes.

We analyze the impact of different designs of COVID-19-related lockdown policies on economic loss and mortality using a micro-level simulation model, which combines a multi-sectoral closed economy with an epidemic transmission model. In particular, the model captures explicitly the (stochastic) effect of interactions between heterogeneous agents during different economic activities on virus transmissions. The empirical validity of the model is established using data on economic and pandemic dynamics in Germany in the first 6 months after the COVID-19 outbreak. We show that a policy-inducing switch between a strict lockdown and a full opening-up of economic activity based on a high incidence threshold is strictly dominated by alternative policies, which are based on a low incidence threshold combined with a light lockdown with weak restrictions of economic activity or even a continuous weak lockdown. Furthermore, also the ex ante variance of the economic loss suffered during the pandemic is substantially lower under these policies. Keeping the other policy parameters fixed, a variation of the consumption restrictions during the lockdown induces a trade-off between GDP loss and mortality. Furthermore, we study the robustness of these findings with respect to alternative pandemic scenarios and examine the optimal timing of lifting containment measures in light of a vaccination rollout in the population.

This paper explores the impact of technological change on industry concentration and the underlying firm dynamics. In the agent-based model EURACE@Unibi I implement a paradigm shift in the technological frontier -a shift from a slow to a fast growing regime.The analysis shows that the acceleration in technological change causes a strong increase in market concentration. The reallocation of market shares towards a few large firms is driven by diverging productivities and skills across firms. An ex-post analysis reveals that after the paradigm shift small, but undervalued firms become the large dominating ones in the long-run. Their success gets initiated by a fortunate outcome on the labor market, which increases their skill level. With the faster technological change, their high skilled workforce incentivizes them to invest at the frontier and to build up the most productive capital stock.A virtuous cycle between their decisions on the labor and capital market further increases the productivity gap towards competitors enabling their rise.