The paper deals with the pattern of asset price dynamics as sequence of "bull markets" and "bear markets" and with stabilising these" long swings" through replacing continuous asset trading with electronic auctions. First, the paper sketches the channels through which the "overshooting" of exchange rates, commodities prices, and stock prices but also of EU carbon prices dampens the real economy and hampers fighting global heating. Second, a theoretical alternative to the still dominating "efficient market hypothesis" is presented, the "bull-bear-hypothesis". Third, the paper discusses the role of "technical" or "algorithmic" trading strategies in exploiting short-term asset price trends and strengthening them at the same time. Fourth, it is shown that bulls (bear) markets result from (verry) short-term trends ("runs") in line with the prevailing (bullish or bearish) market sentiment lasting longer than counter-movements. Fifth, to mitigate the extent of the "long swings" of asset prices one needs to restrict (super) fast speculation unrelated to market fundamentals thereby dampening the short-term trending of asset prices. Instead of implementing a financial transactions tax, one could achieve this objective also through replacing continuous trading with electronic auctions, e.g., every three hours. This approach is theoretically more appealing, technically easy to implement and has so far not seriously been discussed.

This article presents a novel explanation why demand for redistribution on average does not respond to information on low intergenerational mobility. Building on insights from behavioural economics, we expect that incentives to update perceptions of intergenerational mobility change along the income distribution. Empirically, we conduct a survey experiment in Austria and show that the average treatment effect of information on perceptions is mostly driven by higher income individuals while low-income respondents hardly react. We replicate this result for the United States and Germany using data from two closely related survey experiments (Alesina et al., 2018; Fehr et al., 2022). Thus, the frequently observed unresponsiveness of demand for redistribution may result because the group which drives the effect on beliefs does not increase demand for redistribution and may even decrease it. Indeed, despite the strong perception shift in the high-income group, the treatment effects on its preferences are mostly zero and even negative for certain policies. At the same time, the group with the clearest incentives to change its redistributive preferences, the low-income group, is systematically less inclined to update its perceptions and thus their redistributive preferences are mostly unaffected and only partially increased in response to the treatment. We suggest that different responses to information could be due to motivated beliefs, since high social mobility implies for low-income earners that effort is more likely to pay off.

We assess the role that nontradable goods play as a determinant of fiscal spending multipliers, making use of a two-sector model. While fiscal multipliers increase with the share of nontradable goods, an inverted U-shaped relationship exists between multiplier size and the import share. Employing an interacted panel VAR model for EU countries, we estimate the effect of the share of nontradable goods on fiscal spending multipliers. Our empirical results provide strong evidence for the predictions of the theoretical model. They imply that the drag of fiscal consolidations is on average smaller in countries with a low share of nontradable goods.

Cross-demand creates links between goods which cause demand-driven cross-price dependencies. We construct a theoretical model to analyze their role in propagating microeconomic price shocks to the CPI inflation rate and examine their empirical relevance using spatial econometric techniques. The results highlight the importance of complementarity and substitution properties between goods in exacerbating or mitigating price shocks. This contrasts with the propagation through the production network. Most importantly, demand-driven cross-price dependencies determine the impact of producer prices on the CPI inflation rate.

This paper advances a dynamic rationale for competitiveness policy that focuses on an economy's ability to evolve in order to achieve high real incomes along with desired qualitative changes in the socio-economic system. It highlights that the ubiquitous "rationalities of failure", either of markets, governments, or systems, are rooted in a peculiar habit of accepting hypothetical perfect states as normative benchmarks. In contrast, competitiveness policy starts from the objectives that the system wants to achieve. By combining the structuralist ontology of the micro, meso and macro levels of development with the basic system functions of evolutionary change, a general typology is developed that differentiates, organizes, and integrates various economic policies according to their respective contributions to the evolvability of the system. Among other advantages, the proposed concept of competitiveness policy allows (i) to replace the negative "logic of failure" with the active pursuit of dynamic development goals, (ii) to break the ideologically afflicted dichotomy between "vertical" and "horizontal" policies and (iii) to better align the theoretical rationale with the actual perception of the societal purpose of public interventions by most policy agents.

For the project "Social Aspects of Market-Based Instruments for Greenhouse Gas Emission Reductions – SoMBI" Austria and Poland were chosen as case study countries to compare the impacts of an EU-wide carbon price combined with different revenue recycling policies. The detailed analysis will focus on the macroeconomic and greenhouse gas emission effects of the introduction of the carbon pricing and revenue recycling schemes as well as the distributional effects of such price mechanisms for different household types. The two countries were chosen as they differ considerably in terms of their energy systems and economic conditions. Further differences regard the level of ambition of the respective domestic climate policies as well as the priorities set in energy policies. The aim of this paper is to provide indications of the sectors that are emission-intensive and/or labour-intensive and are likely to gain or lose from the chosen revenue recycling mechanisms. Moreover, the findings will provide background information for the interpretation of modelling results for the various carbon pricing and recycling options.

We examine the role of intangible capital as a production factor using Austrian firm-level register data. Descriptive statistics show that intangible investment has increased over time. The intensive and extensive margins of firms' investments are highly skewed. They differ across sectors. A series of sample splits show that the components of intangible capital play different roles as inputs in the production function. Software and especially licenses are important for SMEs and exporters. Research and development play an important role in production in all specifications. For firms that continuously invest in intangible capital, all components of intangible capital gain importance in the production functions. These patterns differ from those found in previous studies and have implications for the strategic orientation of industrial and innovation policy.

This paper analyses the direct and indirect trade volume and trade cost effects of uncertainty on international trade and economic welfare using a structural gravity framework for a panel of 97 developed and developing countries from 2000 to 2018. Our results suggest that an increase in unilateral uncertainty affects average trade costs in a heterogeneous manner, depending on whether the uncertainty originates from the importing or exporting country. Moreover, using a cross-sectional gravity approach, we show that an uncertainty shock directly reduces cross-border trade flows. The paper illustrates the suitability of the proposed modelling approach by means of two counterfactual scenario analyses in which we calculate the general equilibrium trade and welfare effects of uncertainty induced by the unexpected outcome of the Brexit referendum in 2016 and the outbreak of the COVID-19 pandemic in 2020.

We analyse the (techno- and macro-)economic and distributive effects of a transformation to a renewable electricity system in Austria by 2030, as stipulated by the Austrian government. For the analysis, the macroeconomic model DYNK and ATLANTIS, a partial model of the electricity market, were expanded and linked. Four transformation scenarios conforming with the 100 percent renewable electricity target in Austria on a national balance are examined, integrated into a consistent scenario for the development of the European electricity system. Additionally, sensitivity analyses with respect to the gas price are performed. Although all scenarios achieve 100 percent RES-E on a national balance, the analysis shows that electricity from gas-fired power plants will still be needed in 2030 to balance variable renewable generation, to avoid grid congestion, and for heat generation from combined heat and power plants in winter months. Another main conclusion from the simulations is that the transition towards a renewable electricity sector is almost neutral from a socio-economic perspective. It does neither reveal harmful impacts nor lead to high multiplier effects from additional investment. With high natural gas prices in the sensitivity scenarios a decrease in GDP and household income, which might motivate redistributive policies, can be observed.

In this paper, we present a novel approach of linking the technical model of the continental European electricity system ATLANTIS with the macroeconomic model DYNK to provide comprehensive integrated power and socio-economic analyses. We thoroughly describe both models and explain the work that has been done to interlink the models. Further, we take Austria's generation expansion plans to transform the electricity sector to 100 percent renewable energy sources (national balance) by 2030 and analyse the effects of different CO₂ prices on the electricity demand that couples the two models via a feedback loop. As the electricity price and demand are interlaced and influence each other, the linked models are solved iteratively until convergence, i.e., until the change of the electricity demand from the DYNK model does not affect the electricity price in the ATLANTIS model anymore. The results show that coupling a technical and macroeconomic model is possible and convergence is achieved after just a few iterations.