With ever-increasing political tensions between China and Russia on one side and the EU and the USA on the other, it only seems a matter of time until protectionist policies cause a decoupling of global value chains. This paper uses a computable general equilibrium trade model calibrated with the latest version of the GTAP database to simulate the effect of such a decoupling – implemented by doubling non-tariff barriers – between the two blocks on trade and welfare. Imposing import barriers almost completely eliminates bilateral imports. In addition, changes in price levels lead to higher imports and lower exports of the imposing country group from and to the rest of the world. The targeted country group increases exports to the rest of the world and reduces imports. Welfare falls in all countries involved, suggesting that governments should strive to cooperate rather than turn away from each other. By imposing a trade war on Russia, the political West could inflict severe damage on the Russian economy because of the latter's smaller relative economic size.

What are the socio-economic effects of the widespread introduction of robots, algorithms and digital technologies like artificial intelligence and machine learning? Following Frey and Osborne (London futures agiletown: the relentless march of technology and London's response. Deloitte, 2014, Technol Forecast Social Change 114(C), 254-280, 2017) we apply the computerisation probabilities to occupations in Austria. We conclude that about 40 percent of the Austrian workforce is active in occupations that are very likely to undergo substantial changes regarding task structure, skill requirement and working environment in the future, causing challenges and opportunities. We also provide evidence that compared to men, women in Austria seem more likely to be affected by technological changes, with sectoral orientation playing a role. Following EBRD (Skills, employment and automation. Chapter 2 in: EBRD (2018): Transition Report 2018-19, European Bank for Reconstruction and Development, London, 2018), we see a broader move towards job polarisation. We see this as distributive consequences of technological change and argue that the consequences of technology refashioning socio-economic development are influencing market processes, actors and inequalities. As in previous technological advances, coping with these changes will require efforts on the individual as well as on the political level.

This study explores productivity growth of 65 Austrian biogas plants from 2006 to 2014 using Data Envelopment Analysis. Productivity growth is measured by calculating the Malmquist productivity index, and the contributions of technical change, efficiency change, and scale change to productivity growth are isolated. The results reveal that the average annual productivity growth between 2006 and 2014 is 1.1 percent. The decomposition of the Malmquist productivity index shows that the annual scale change, technical change, and efficiency change for the average plant is 0.6 percent, 0.3 percent, and 0.3 percent, respectively. These results indicate that the exploitation of returns to scale is a major driver of productivity growth and technical change is rather low. A second-stage regression analysis reveals that rising feedstock prices incentivised efficiency improvements but initial capital subsidies did not have an impact on technical change and productivity growth.

The paper employs surveys among Austrian households to study ownership and purchase intentions of crypto-assets. About 1.6 percent of Austrians own crypto-assets and about 5 percent can be viewed as potential adopters. Owners, on average, have higher financial knowledge and are more risk-tolerant than non-owners. Distrust in banks or in conventional currencies is not found to be an important driver of ownership. Intentions to adopt are strongly affected by profit expectations and by beliefs that crypto-assets offer advantages for payments – most adopters or potential adopters hold both beliefs. Perceptions of high volatility or the risk of fraud and online theft dampen the demand for crypto-assets.

This study attempts to identify the short- and long-run components of the Kaldor-Verdoorn law (KV law). The law claims that demand dynamics drive productivity dynamics. The claim is tested with a panel of ten Central and Eastern European countries, where productivity and demand growth have been slowing since 2004-2006 and where fears of an end of convergent growth are spreading. Meanwhile, the gradual slowing of output and productivity growth applies not only to the region considered, but it is also a global phenomenon that is occurring despite remarkable technical progress and that is referred to as the productivity puzzle. However, this puzzle would be solved in light of the KV law. To test for its long-term properties, panel cointegration models with autoregressive distributed lags are applied. Our results confirm the law for the region; slower productivity growth is not due to "adverse technological progress" but to weakening external and domestic demand, which might block the implementation of product and process innovations.