Finding the proper balance between state and market is challenging. Especially in banking (Stiglitz, 1993). Banks in their function as financial intermediaries are risky and inherently prone to failure (Diamond and Dybvig, 1983; Diamond, 1984). But they provide services of vital importance to the economy in the form of payment services, credit supply for investments, inter-temporal liquidity transformation, or management of savings accounts. Consequently, the stability of the banking and financial sector is of public interest. In the least, the financial crisis was an unpleasant reminder to the industrialized world about the severe repercussions of unstable banking systems.

Economic growth is the core topic for both economic researchers and economic policy makers. Thereby two questions are regarded as central: What are the factors that establish high growth? And how can sustainable growth, i.e. the avoidance of severe fluctuations, be achieved? Indeed, basically all areas of economics, from finance to labor economics, from development economics to industrial organization, from competition economics to environmental economics aim to achieve knowledge that directly (or indirectly) helps to understand and create growth that is both sufficient and sustainable.

Firm training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.

A distinctive aspect of the recent financial crises is that they emerged primarily in the industrial world. Since the 2008-2009 global financial crisis emerging countries have been therefore confronted with financial shocks triggered at the core of the international financial system, affecting the volatility of capital flows worldwide. Emerging countries’ dependence on capital and trade flows, combined with a large presence of foreign-owned banks, has been identified as a central driver of the cross-border transmission of these crises (see IMF, 2009). While historical events such as the Latin American debt crisis or the 1997 Asian financial crisis highlighted the importance of sound balance of payments and inflation targeting policies at the macroeconomic level, the global financial crisis has revealed the importance of weighing the costs and benefits of banking globalization. This is foremost important from a policy perspective, since emerging countries faced for the first time in decades an external shock in a context free of large local macroeconomic imbalances, having to adapt their traditional policy framework to new challenges. This has been emphasized, among others, by the former Chairman of the U.S. Federal Reserve Ben Bernanke. In particular, this changing scenario implied that microeconomic aspects involved in the cross-border transmission of shocks gained increasing momentum in the international policy debate (see for instance Freixas et al., 2015).

The contribution of this thesis is to widen the focus of the literature on related variety. So far, this line of research has a strong focus on technological relatedness and cognitive proximity (Boschma et al. 2015). This thesis puts emphasis on three dimensions of relatedness that not yet been at the heart of research: input-output linkages and vertically related variety, the occupational dimensions of relatedness as well as insights from a project level R&D efforts and their relevance for the analysis of technological relatedness. We contribute to the understanding of how the specific composition and the degree of relatedness of economic agents in space shape their ability to generate variety in terms of entry of new occupational specialisations in regions. We enhance the understanding of how related variety affects different regional outcomes such employment growth and innovation and offer insights into the structure of inter-industry relations from a technological perspective and explains how the rise of certain technologies shapes inter-industry relatedness patterns.

This study employs bilateral data on external assets to examine the impact of climate policies on the reallocation of international capital. We find that the stringency of climate policy in the destination country is significantly and positively associated with an increase in the allocation of portfolio equity and banking investment to that country. However, it does not show significant effects on the allocation of foreign direct investment and portfolio debt. Our findings are not driven by valuation effects, and we present evidence that suggests diversification, suasion, and uncertainty mitigation as possible underlying mechanisms.

Firm training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.