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This paper examines how market-perceived AI exposure is associated with extreme financial-sector gains and losses across five markets, using Expected Shortfall and skewness decompositions to distinguish AI-sector, macroeconomic, systemic and financial scenarios.

Using a controlled macroeconomic experiment, we compare monetary policy rules that differ in how much they look through inflation: a Lean-Against policy with strong response to inflation and a Look-Through policy with less strong response. We combine each rule with communication protocols that vary the information the central bank releases about its policy response.

Positive commodity price shocks reduce labor income inequality in commodity-exporting economies by compressing the skill premium, as unskilled-labor-intensive sectors such as construction expand faster than skill-intensive services. A multisector small-open-economy model shows how saving or spending commodity windfalls can reinforce or moderate this decline in inequality.

This paper studies the impact of offshoring by US firms on voting patterns for incumbents in the US.

Using Canadian firm-level market shares and an oligopolistic model, the paper shows that a 25% counter-tariff on U.S. imports raises Canada's aggregate price index by 0.66%, far below direct cost pass-through predictions due to consumer substitution and markup adjustments.

We develop a framework to quantify how tariff changes on imported goods affect sectoral and aggregate consumption prices through direct and production-network channels. Using Canada's input-output matrix and administrative firm-good import data for the universe of Canadian firms, we estimate price elasticities for tariffs on U.S.-imported goods.

This paper examines the direct effects of industrial robot adoption on workers and owners within Canadian private corporations. Adoption increases firm scale and per-worker payroll but does not decrease the labor share of value added. Conventional accounting of labor income earned by owners masks the impact on non-owner workers.

Portfolio-balance models of the yield curve are notoriously hard to estimate. This paper offers a simple, two-step estimation approach that can be implemented with standard term structure estimation methods. In our application to U.S. Treasury data, our method recovers economically interpretable drivers of the yield curve.

Building on our earlier quantum algorithm, this paper shows that reordering queued payments can significantly reduce liquidity needs. The algorithm performs well on smaller payment batches, while traditional algorithms can process larger batches and deliver greater savings. Machine learning also helps identify which payment patterns offer the greatest potential for improvement.

We document the macroeconomic patterns that characterize labor market recovery from financial crises. Using a sample of postwar recession episodes from around the world, we show that financial crises are typically followed by jobless recoveries, with a sluggish recovery in employment relative to output.