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With data from the World Bank Enterprise Survey, this paper examines how firm-level resilience capabilities interact with government support in the reduction of lay-offs among formal firms in Central America. We estimate two latent variables to approximate resilience-related capabilities before (static) and after (dynamic) the COVID-19 pandemic. We create four counterfactual groups using a Markov chain Monte Carlo simulation to assess which resilience capabilities help firms cope better, with and without government support. We find that support policies play a marginal role among most groups, except in the dynamic resilient group, where receiving government support does shrink the probability of lay-offs.

In order to slow the spread of the CoViD-19 pandemic, governments around the world have enacted a wide set of policies limiting the transmission of the disease. Initially, these focused on non-pharmaceutical interventions; more recently, vaccinations and large-scale rapid testing have started to play a major role. The objective of this study is to explain the quantitative effects of these policies on determining the course of the pandemic, allowing for factors like seasonality or virus strains with different transmission profiles. To do so, the study develops an agent-based simulation model, which is estimated using data for the second and the third wave of the CoViD-19 pandemic in Germany. The paper finds that during a period where vaccination rates rose from 5% to 40%, rapid testing had the largest effect on reducing infection numbers. Frequent large-scale rapid testing should remain part of strategies to contain CoViD-19; it can substitute for many non-pharmaceutical interventions that come at a much larger cost to individuals, society, and the economy.

For monetary policy guiding inflation expectations provides an instrument to achieve price stability. However, expectation uncertainty may undermine monetary policy's ability to stabilise the economy. This study examines the effects of inflation expectation uncertainty on inflation, inflation expectations and the output gap by means of a structural VAR with stochastic volatility in mean. Inflation expectation uncertainty negatively affects the inflation rate and the output gap, without having a distinct effect on the level of expectations. This result is replicable with a model in which uncertainty is approximated by a cross-sectional survey measure. Furthermore, simulating an uncertainty shock in a DSGE model shows that the demand channel dominates the supply channel of an inflation expectation uncertainty shock. ; Die Steuerung der Inflationserwartungen ist ein geldpolitisches Instrument zur Erreichung von Preisstabilität. Allerdings kann Erwartungsunsicherheit die Fähigkeit der Geldpolitik zur Stabilisierung der Wirtschaft untergraben. In dieser Studie werden die Auswirkungen der Unsicherheit der Inflationserwartungen auf die Inflation, die Inflationserwartungen und die Produktionslücke mit Hilfe eines strukturellen VAR mit stochastischer Volatilität untersucht. Es zeigt sich, dass sich Unsicherheit der Inflationserwartungen negativ auf die Inflationsrate und die Produktionslücke auswirkt, ohne einen deutlichen Effekt auf das Niveau der Erwartungen zu haben. Dieses Ergebnis ist mit einem Modell reproduzierbar, bei dem die Unsicherheit durch ein Querschnittserhebungsmaß approximiert wird. Darüber hinaus zeigt die Simulation eines Unsicherheitsschocks in einem DSGE-Modell, dass der Nachfragekanal den Angebotskanal eines Unsicherheitsschocks der Inflationserwartung dominiert.

In Switzerland, transportation represents 41% of CO2 emissions from energy combustion (2016), a much higher share than in the European Union (EU) (28%) or even the USA (34%). While total Swiss CO2 emissions decreased by 10% between 1990 and 2016, CO2 emissions from transport increased by 4.5% over the same period (all data from UNFCCC database). Our projections (Vielle and Thalmann, Updated emissions scenarios without measures, 1990-2025, Tech. rep., 2017) show that the contribution of the transport sector would remain constant in a scenario taking into account climate and energy policy measures already implemented or adopted in 2016. In the EU, several initiatives have already been introduced to limit the use of petroleum products in transportation. This paper presents deep decarbonization pathways for Switzerland that demand a strong contribution from the transport sector. We find that a preferential treatment of transportation fuels raises the welfare cost of decarbonization by about 18% relative to a uniform tax on all fossil fuels. This is of similar magnitude as the preferential treatment of large CO2 emitters through an emissions trading system. We also find that the preferential treatment leads to a share of fossil fuels in total energy for road transportation in 2050 which is approximately twice as high as in the uniform treatment.

Increasing the realism with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society since actors, decision-making, and institutions are the defining elements of transition pathways. In this paper, we explore how this can be done by conducting a model-based scenario analysis. The increasing focus on implementation and transition dynamics towards long-term objectives requires a better comprehension of what drives change and how those changes can be accelerated. We explore opportunities that arise from a deeper engagement of quantitative systems modeling with socio-technical transitions studies, initiative-based learning, and applied economics. We argue that a number of opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches.

In recent years, a number of Western industrialized nations have experienced a notable polarization of political ideologies, and growing numbers of individuals seemingly support extreme positions. As a result, established political parties have moved to the left or right and new parties have appeared on the fringes. But why are people with extreme political views this visible in the public debate, and how are they able to move party positions further to the margins when they should be outnumbered by a moderate majority? Contradictory to the classic literature that focuses on collective action problems, this paper studies emerging effects from informational asymmetries. It extends a spatial voting model to include incompletely informed candidates and knowledgeable voters. Agent-based simulations suggest that only fringe voters benefit from distorting their opinions and dominating political discourse. At the same time, better informed candidates have a competitive advantage in elections no matter how strongly voters distort their positions.

This paper shows that a modified real business cycle (RBC) model, one that includes home production and fiscal spending shocks, can solve one of the RBC puzzles and generates zero correlation between wages and hours. In addition, the micro-founded model presented here provides a sound theoretical model to analyze fiscal policy in a neoclassical framework and is able to capture many aspects of the data that the benchmark RBC model was missing.

This paper shows that a modified real business cycle (RBC) model, one that includes home production and fiscal spending shocks, can solve one of the RBC puzzles and generates zero correlation between wages and hours. In addition, the micro-founded model presented here provides a sound theoretical model to analyze fiscal policy in a neoclassical framework and is able to capture many aspects of the data that the benchmark RBC model was missing.

Electricity generation from renewable energy sources (RES-E) is supposed to increase signi ficantly within the coming decades. However, uncertainty about the progress of necessary infrastructure investments, public acceptance and cost developments of renewable energies renders the achievement of political plans uncertain. Implementation risks of renewable energy targets are challenging for investment planning, because different RES-E shares fundamentally change the optimal mix of dispatchable power plants. Speci cally, uncertain future RES-E deployment paths induce uncertainty about the steepness of the residual load duration curve and the hourly residual load structure. In this paper, we show how uncertain future RES-E penetrations impact the electricity system and try to quantify effects for the Central European power market. We use a multi-stage stochastic investment and dispatch model to analyze effects on investment choices, electricity generation and system costs. Our main findings include that the uncertain achievement of RES-E targets significantly effects optimal investment decisions. First, a higher share of technologies with a medium capital/operating cost ratio is cost-efficient. Second, the value of storage units in systems with high RES-E penetrations might decrease. Third, in the case of the Central European power market, costs induced by the implementation risk of renewable energies seem to be rather small compared to total system costs.

Whether observed differences in redistributive policies across countries are the result of differences in social preferences or efficiency constraints is an important question that paves the debate about the optimality of welfare regimes. To shed new light on this question, we estimate labor supply elasticities on microdata and adopt an inverted optimal tax approach to characterize the redistributive preferences embodied in the welfare systems of 17 EU countries and the US. Implicit social welfare functions are broadly compatible with the fiction of an optimizing Paretian social planner. Some exceptions due to generous demogrant transfers are consistent with the ignorance of behavioral responses by some European governments and are partly corrected by recent policy developments. Heterogeneity in leisure-consumption preferences somewhat affect the international comparison in degrees of revealed inequality aversion, but differences in social preferences are significant only between broad groups of countries.

We present electronic structure calculations based on a single-parameter plane wave expansion method for basic graphene building blocks, namely n-oligophenylenes and n-oligoacenes, revealing excellent agreement with density-functional theory. When oligophenylene molecules are joined through meta (zigzag) or ortho (chevron) junctions, the resulting molecular dimers and polymers exhibit a semiconducting character. While zigzag dimers of oligoacenes also exhibit gapped electronic structures, their chevron-phase features a sharp metallic band at the Fermi energy. This zero-point-energy state, which transforms into Dirac-like band in chevron polymers, survives at the outer elbows of the dimer irrespective of the molecular length, and has the same origin as reported for the polyacetylene and topologically induced edge states at edge-decorated graphene nanoribbons. These findings assist the engineering of topological electronic states at the molecular level and complement the toolbox of quantum phases in carbon-based nanostructures. ; JEO acknowledges financial support from the Spanish Ministry of Science and Innovation (Grants PID2019-107338RB-C63) and the Basque Government (Grant IT-1255-19). ; Peer reviewed

JEL Classification Codes: C63, C68, D58ing ; Multiplier analysis based upon the information contained in Leontief's inverse is undoubtedly part of the core of the input-output methodology and numerous applications an extensions have been developed that exploit its informational content. Nonetheless there are some implicit theoretical assumptions whose implications have perhaps not been fully assessed. This is the case of the 'excess capacity' assumption. Because of this assumption resources are available as needed to adjust production to new equilibrium states. In real world applications, however, new resources are scarce and costly. Supply constraints kick in and hence resource allocation needs to take them into account to really assess the effect of government policies. Using a closed general equilibrium model that incorporates supply constraints, we perform some simple numerical exercises and proceed to derive a 'constrained' multiplier matrix that can be compared with the standard 'unrestricted' multiplier matrix. Results show that the effectiveness of expenditure policies hinges critically on whether or not supply constraints are considered.

In order to slow the spread of the CoViD-19 pandemic, governments around the world have enacted a wide set of policies limiting the transmission of the disease. Initially, these focused on non-pharmaceutical interventions; more recently, vaccinations and large-scale rapid testing have started to play a major role. The objective of this study is to explain the quantitative effects of these policies on determining the course of the pandemic, allowing for factors like seasonality or virus strains with different transmission profiles. To do so, the study develops an agent-based simulation model, which is estimated using data for the second and the third wave of the CoViD-19 pandemic in Germany. The paper finds that during a period where vaccination rates rose from 5% to 40%, rapid testing had the largest effect on reducing infection numbers. Frequent large-scale rapid testing should remain part of strategies to contain CoViD-19; it can substitute for many non-pharmaceutical interventions that come at a much larger cost to individuals, society, and the economy.