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We model the asset-opacity choice of an intermediary subject to rollover risk in wholesale funding markets. Greater opacity means investors form more dispersed beliefs about an intermediary’s profitability.

Information about the role of emergency lending assistance in recovery and resolution, and about its terms and conditions, eligibility criteria, management, and relationship to the standing liquidity facility.

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.

G-20 representatives, academics, market participants, and members of international financial institutions were brought together in Ottawa to explore the connection between robust financial markets and economic growth and development, share experiences, and to develop policy recommendations, where possible. Participants identified several areas they deemed critical for fostering strong domestic financial markets and reducing external vulnerability: sound macroeconomics policies, strengthened financial infrastructures and banking systems, and exchange rate flexibility for countries with widely open capital accounts. Papers presented in the six sessions and keynote address highlighted a number of issues, including currency mismatches, the sequence of financial liberalization and supervisory reforms, the development of local financial markets, infrastructure building and governance, and appropriate incentives.

As the title of the conference suggests, we have seen many boom-and-bust cycles in the commodity sector. This raises one obvious and central question: How can we avoid them in the future?

How do firms change their employment decisions when tax benefits for low-earning workers are expanded? Some firms increase employment overall, whereas others replace high-earning workers with low-earning workers, according to German linked employer-employee data.

When countries are hit by supply shocks, central banks often face the dilemma of either looking through such shocks or reacting to them to ensure that inflation expectations remain anchored. In this paper, we propose a tractable framework to capture this dilemma and then explore optimal policy under a range of assumptions about how expectations are formed.

Economists in the nineteenth century spent considerable time discussing the merits of a free-banking system, in which each commercial bank would be able to issue its own notes and deposits, subject to a convertibility requirement backed by its own gold reserves. Such a system, the proponents argued, would be able to deliver price-level stability yet be flexible enough to withstand the vicissitudes of the business cycle. Moreover, there would be no need for central banks. While this idea has received less attention in recent years, some economists still put it forward as a practical alternative to the current system. Laidler suggests that the centralizing tendencies in banking would inevitably undermine competition within a free-banking system, and lead to the natural emergence of one dominant bank. Other developments in the twentieth century, most notably the demise of the gold standard and widespread agreement that governments should play a determining role in setting monetary policy goals, have also limited the practicality of such a system. Laidler examines the Bank of Canada's history from the free-banking perspective and concludes that the current system of inflation targeting provides a much better anchor for orderly price-level behaviour than the free-banking system's convertibility could ever guarantee.

Digital currencies have attracted strong interest in recent years and have the potential to become widely adopted for use in making payments. Public authorities and central banks around the world are closely monitoring developments in digital currencies and studying their implications for the economy, the financial system and central banks.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.