Does generative AI raise productivity, expand employment, or both? I provide cross-country evidence by comparing industry-level responses in the United States and Norway, two economies with comparable technological access but sharply different labor market institutions. Using a long-difference design with a pre-COVID baseline and a post-adoption measurement window, I find a mirror-image pattern: high-exposure industries in the US show strong productivity gains with no employment response, while the same industries in Norway expand employment with no significant productivity effect. Crucially, AI-exposed industries generate comparable value-added growth in both countries, establishing that the technology creates value regardless of institutional setting. The divergence lies in the adjustment margin, US firms absorb gains through higher output per worker, Norwegian firms through workforce expansion. Despite these different paths, hourly compensation does not rise in either country. In the US hourly compensation is flat, while in Norway it falls as employment expands. This suggests that at this early stage, workers do not capture the AI surplus through higher wages.

Does a floating exchange rate stabilise or destabilise a small open economy? We address this question using structural VAR models estimated for Iceland and Sweden under three complementary identification schemes. The two countries share the same broad monetary framework but differ sharply in exchange-rate pass-through and financial openness, making the comparison informative about the conditions under which the optimum currency area shock-absorber prediction holds. We find that it holds for Sweden but fails for Iceland: the króna amplifies rather than absorbs external shocks, domestic monetary policy is constrained by ECB co-movement, and idiosyncratic exchange-rate disturbances dominate króna fluctuations. A variance-decomposition welfare metric suggests that the output variance costs of exchange-rate flexibility exceed its monetary autonomy benefits for Iceland, while the reverse holds for Sweden.

After decades of low and stable inflation, advanced economies experienced a sharp and persistent surge in inflation following the COVID-19 pandemic. While many studies have examined the sources of this inflation, less attention has been paid to how domestic inflation expectations amplify global shocks. This paper makes a novel contribution by quantifying that amplification mechanism across six advanced, inflation-targeting economies: the United States, Canada, New Zealand, the Euro Area, the United Kingdom, and Norway. Using a structural Bayesian vector autoregression model, we jointly identify global demand and supply shocks, including various oil market shocks and global supply chain disruptions, as well as domestic shocks to inflation and inflation expectations. We show that these global shocks were key drivers of the post-pandemic inflation surge in all countries studied. Importantly, our counterfactual analysis reveals that inflation expectations have significantly amplified the transmission of global shocks, particularly in Canada, New Zealand, and the US. These findings demonstrate that the interaction between global forces and country-specific expectations is central to understanding inflation dynamics, and underscore the importance of managing inflation expectations as a tool to mitigate persistent inflation.

We search for leading determinants of financial instability in Norway using a signaling approach, and examine how these respond to a monetary policy shock with the use of structural VAR models. We find that the wholesale funding ratio and gap, credit-to-GDP gap, house price-to-income ratio and gap, and credit growth provide good signals of future financial instability. Following a contractionary monetary policy shock, the credit-to-GDP gap and house price-to-income ratio decrease significantly. The implication of our findings is that the central bank can respond to an increase in these indicators by increasing the interest rate, which in turn will decrease the indicators and thereby the probability of financial distress.

Constructs a daily financial conditions index combining market prices and spreads to track short-run changes in Norwegian financial tightness and its co-movement with macro indicators.