Federal Reserve System

About: Federal Reserve System is a other organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Monetary policy & Inflation. The organization has 2373 authors who have published 10301 publications receiving 511979 citations.

What Accounts for the Variation in Retirement Wealth Among U.S. Households

Abstract: Even among households with similar socioeconomic characteristics, saving and wealth vary considerably. Life-cycle models attribute this variation to differences in time preference rates, risk tolerance, exposure to uncertainty, relative tastes for work and leisure at advanced ages, and income replacement rates. These factors have testable implications concerning the relation between accumulated wealth and the shape of the consumption profile. Using the Panel Study of Income Dynamics and the Consumer Expenditure Survey, we find little support for these implications. The data are instead consistent with "rule of thumb," "mental accounting," or hyperbolic discounting theories of wealth accumulation. (JEL DI, D91, E21)

An Arbitrage-Free Three-Factor Term Structure Model and the Recent Behavior of Long- Term Yields and Distant-Horizon Forward Rates

Abstract: This paper reviews a simple three-factor arbitrage-free term structure model estimated by Federal Reserve Board staff and reports results obtained from fitting this model to U.S. Treasury yields since 1990. The model ascribes a large portion of the decline in long-term yields and distant-horizon forward rates since the middle of 2004 to a fall in term premiums. A variant of the model that incorporates inflation data indicates that about two-thirds of the decline in nominal term premiums owes to a fall in real term premiums, but estimated compensation for inflation risk has diminished as well.

The Macroeconomic Effects of Inflation Targeting

Abstract: We find evidence that inflation targeting (IT) plays a role in anchoring long-run inflation expectations and in reducing the intrinsic persistence of inflation. Over the period since 1994, private-sector long-run inflation forecasts for the United States and the euro area exhibit significant correlation with lagged inflation, whereas this correlation is largely absent for Australia, Canada, New Zealand, Sweden, and the United Kingdom, indicating that these five inflation targeters have been quite successful in delinking expectations from realized inflation. Furthermore, we show that the null hypothesis of a random walk in core CPI inflation can be clearly rejected for four of these five countries, but not for either the U.S. or the euro area. Finally, we provide some evidence concerning the initial effects of the adoption of IT in a number of emerging-market economies.

Corporate governance and bank performance : a joint analysis of the static, selection, and dynamic effects of domestic, foreign, and state ownership

Abstract: We jointly analyze the static, selection, and dynamic effects of domestic, foreign, and state ownership on bank performance. We argue that it is important to include indicators of all the relevant governance effects in the same model. “Nonrobustness” checks (which purposely exclude some indicators) support this argument. Using data from Argentina in the 1990s, our strongest and most robust results concern state ownership. State-owned banks have poor long-term performance (static effect), those undergoing privatization had particularly poor performance beforehand (selection effect), and these banks dramatically improved following privatization (dynamic effect). However, much of the measured improvement is likely due to placing nonperforming loans into residual entities, leaving “good” privatized banks.

Pitfalls in Tests for Changes in Correlations

Abstract: Correlations are crucial for pricing and hedging derivatives whose payoff depends on more than one asset. Typically, correlations computed separately for ordinary and stressful market conditions differ considerably, a pattern widely termed "correlation breakdown." As a result, risk managers worry that their hedges will be useless when they are most needed, namely during "stressful" market situations. We show that such worries may not be justified since "correlation breakdowns" can easily be generated by data whose distribution is stationary and, in particular, whose correlation coefficient is constant. We make this point analytically, by way of several numerical examples, and via an empirical illustration. But, risk managers should not necessarily relax. Although "correlation breakdown" can be an artifact of poor data analysis, other evidence suggests that correlations do in fact change over time, though not in a way that is correlated with "stressful" market conditions.