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Privacy-enhancing technologies (PETs) could offer solutions to safeguard end-user privacy and meet rigorous data protection standards for central bank digital currencies. We consider how PETs can transform privacy design in financial systems and the implications of their broader adoption.

We propose a new strength measure of the global financial cycle by estimating a regime-switching factor model on cross-border equity flows for 61 countries. We then assess how the strength of the global financial cycle affects monetary policy independence, which is defined as the response of central banks' policy interest rates to exogenous changes in inflation.

Using two complementary approaches, we investigate the importance of U.S. macroeconomic news in driving low-frequency fluctuations in the term structure of interest rates in Canada, Sweden and the United Kingdom. We find that U.S. macroeconomic news is particularly important to explain changes in the expectation components of the nominal, real and break-even inflation rates of small open economies.

In this paper we study the impact of immigration to the United States on the vote for the Republican Party by analyzing county-level data on election outcomes between 1990 and 2010. Our main contribution is to separate the effect of high-skilled and low-skilled immigrants, by exploiting the different geography and timing of the inflows of these two groups of immigrants.

Central bankers argue that programmable digital currencies may compromise the uniformity of money. We develop a stylized model to examine this argument and the trade-offs involved in circulating programmable money.

This equilibrium model explains the trend in long-term yields and business-cycle movements in short-term yields and yield spreads. The less-frequent inverted yield curves (and less-frequent recessions) after the 1990s are due to recent secular stagnation and procyclical inflation expectations.

There is an old saying, “Knowledge is gained from experience, and experience is gained from mistakes.” In Canada, we made our mistakes early and often in the 1970s and 1980s. Our fiscal situation deteriorated sharply, inflation surged to double-digit levels, and a few small regional banks collapsed.

We study the trading of an asset with bankruptcy risk. The traded price of the asset is, on average, 40% of the expected total dividend payments. We investigate which economic models can explain the low traded price.

Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.