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265 Results

Trading on Long-term Information

Staff working paper 2020-20 Corey Garriott, Ryan Riordan
Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading.

Markups and Inflation in Oligopolistic Markets: Evidence from Wholesale Price Data

Staff working paper 2024-20 Patrick Alexander, Lu Han, Oleksiy Kryvtsov, Ben Tomlin
We study how the interaction of market power and nominal price rigidity influences inflation dynamics. We find that pass-through declines with price stickiness when markets are concentrated, which implies a lower slope of the New Keynesian Phillips curve.
January 31, 2020

Terry Fox is bank NOTE-able

Terry Fox was selected from a short list of eight iconic Canadians to be on the next $5 bank note.

On the Wedge Between the PPI and CPI Inflation Indicators

Staff working paper 2022-5 Shang-Jin Wei, Yinxi Xie
We find that the CPI and PPI inflation indexes co-moved strongly throughout the late 20th century, but their correlation has fallen substantially since the early 2000s. We offer a structural explanation for this divergence based on the growth of global supply chains since 2000. This finding offers a unique perspective for the future design of optimal monetary policy.

Outside Investor Access to Top Management: Market Monitoring versus Stock Price Manipulation

Staff working paper 2020-43 Josef Schroth
Should managers be paid in stock options if they provide stock-market participants with information about the firm? This paper studies how firm owners trade off the benefit of stock-price incentives and better-informed market participants against the cost of potential stock-price manipulation.

Optimal Taxation in Asset Markets with Adverse Selection

Staff working paper 2020-11 Mohammad Davoodalhosseini
What is the optimal tax schedule in over-the-counter markets, e.g., those for corporate bonds? I find that an optimal tax schedule is often non-monotonic. For example, trading of some high-price assets should be subsidized, and trading of some low-price assets should be taxed.

Understanding Post-COVID Inflation Dynamics

Staff working paper 2022-50 Martin Harding, Jesper Lindé, Mathias Trabandt
We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. Our model can generate more sizable inflation surges due to cost-push and demand shocks than a standard linearized model when inflation is high.

The Central Bank Strikes Back! Credibility of Monetary Policy under Fiscal Influence

Staff working paper 2022-11 Antoine Camous, Dmitry Matveev
Central banks in many advanced economies enjoy a high degree of independence, which protects monetary policy decisions from political influence. But how should independent central banks react if pressured by fiscal policy-makers? We examine whether a central bank should design a monetary policy framework that prescribes acting conditionally on how fiscal policy behaves.

The Interplay of Financial Education, Financial Literacy, Financial Inclusion and Financial Stability: Any Lessons for the Current Big Tech Era?

Staff working paper 2020-32 Nicole Jonker, Anneke Kosse
The objective of this paper is twofold. First, we assess whether financial education might be a suitable tool to promote the financial inclusion opportunities that big techs provide. Second, we study how this potential financial inclusion could impact financial stability.

Predictive Density Combination Using a Tree-Based Synthesis Function

This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability.
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