This study explores how artificial intelligence (AI) and robotics drive innovation in European SMEs, analyzing key factors influencing their adoption and their impact on product, process, organizational, and marketing innovation. he study uses data from Flash Eurobarometer 486 and employs a two-stage residual inclusion strategy to analyze the relationship between the adoption of new digital technologies and the innovative potential of European SMEs, controlling for endogeneity and multicollinearity.

The main findings are as follows. First, start-ups and scale-ups lead in the adoption of AI and robotics. Both types of companies stand out as the most innovative SMEs. Second, internationalization, company size, and access to digital talent significantly influence digitalization. Third, digital skills and infrastructure at the national level are key factors that incentivize digitalization. Fourth, the simultaneous adoption of both technologies is confirmed. Finally, in manufacturing, AI and robots have more specialized applications in the development of innovations, while in services, their use is broader.

This article examines the impact of the massive and unexpected inflow of Ukrainians that resulted from Russia's aggression in 2014 on local migration patterns in Poland. For identification, I use an instrumental variable approach drawing on unique historical data on the forced resettlement of Ukrainians in Poland after World War II. The results show that the regional inflow of immigrants, while crowding out internal in-migration, decreases both internal and international out-migration of the local population. I provide supportive evidence that the decrease in out-migration is due to an enlargement of local labor markets.

This paper examines the impact of sanctuary policies on the financial inclusion of Hispanics in the U.S. mortgage market. By reducing local cooperation with federal immigration authorities, sanctuary policies reduce the risk of deportation and signal local acceptance of irregular immigrants and their families. This reduction in uncertainty for Hispanic borrowers and profit-maximizing lenders influences decision-making in financial markets.

Aviation is becoming a major contributor to greenhouse gas emissions and generates local pollution with harmful health effects. This paper studies the effects of airport charges by means of a theoretical setup and an empirical application. The equilibrium analysis identifies how airport charges affect fares, frequencies, and aircraft emissions. The welfare analysis concludes that frequencies are excessive when the damage caused by emissions is severe. Finally, our model explores mechanisms for revenue-neutral airports to compensate rises in emission charges by lowering non-emission charges to generate incentives for airlines to renew their fleets. The empirical analysis concludes that NOx-emission charges have a modest effect on fares and frequencies as compared to per-passenger and per-flight charges. Although only emission charges spur the use of newer aircraft, they should be much higher than their actual values to play a relevant role in contributing to a more sustainable aviation.

This study empirically documents that inflation is significantly more persistent when it is below the Central Bank's target than otherwise, in five inflation targeting countries (Australia, New Zealand, Sweden, United States and the Euro-Area). We use a threshold autoregressive model to test for this asymmetry in inflation persistence; above and below some estimated threshold. We find that the threshold estimates are reasonable in light of a central bank's announced inflation target. Theoretically, we postulate that this phenomenon occurs because while forming their expectations, agents pay attention to recent observations asymmetrically along the business cycle. It is shown that a New Keynesian model with adaptive learning and an adaptive gain can explain the asymmetry in inflation persistence. Due to relatively larger forecasting errors, agents tend to put more weight on recent events in periods of high inflation, forcing inflation persistence to deteriorate. Our empirical evidence supports the theoretical findings that inflationary periods are associated with larger forecasting errors.