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We develop a model of the market for federal funds that explicitly accounts for its two distinctive features: banks have to search for a suitable counterparty, and once they meet, both parties negotiate the size of the loan and the repayment. The theory is used to answer a number of positive and normative questions: What are the determinants of the fed funds rate? How does the market reallocate funds? Is the market able to achieve an efficient reallocation of funds? We also use the model for theoretical and quantitative analyses of policy issues facing modern central banks.

We examine the importance of liquidity hoarding and counterparty risk in the U.S. overnight interbank market during the financial crisis of 2008. Our findings suggest that counterparty risk plays a larger role than does liquidity hoarding: the day after Lehman Brothers' bankruptcy, loan terms become more sensitive to borrower characteristics. In particular, poorly performing large banks see an increase in spreads of 25 basis points, but are borrowing 1% less, on average. Worse performing banks do not hoard liquidity. While the interbank market does not freeze entirely, it does not seem to expand to meet latent demand.

Extreme disruptions in the interbank market severely hampered the broader financial system during the 2007-08 financial crisis. We use Fedwire data to estimate fed funds trades and track banks' intraday balances. We show empirical evidence of banks' precautionary holding of reserves and reluctance to lend linked to documented extreme fed funds rate volatility, including the fed funds rate spiking above the discount rate and crashing to zero. We develop a model of constrained banks that makes new predictions and provides a unified explanation for the stark anomalies during the crisis, our empirical findings, and previous stylized facts from normal times.

A number of recent articles have used different financial market instruments to measure near-term expectations of the federal funds rate and the high-frequency changes in these instruments around Federal Open Market Committee announcements to measure monetary policy shocks. This article evaluates the empirical success of a variety of financial market instruments in predicting the future path of monetary policy. All of the instruments we consider provide forecasts that are clearly superior to those of standard time series models at all of the horizons considered. Among financial market instruments, we find that federal funds futures dominate all the other securities in forecasting monetary policy at horizons out to six months. For longer horizons, the predictive power of many of the instruments we consider is very similar. In addition, we present evidence that monetary policy shocks computed using the current-month federal funds futures contract are influenced by changes in the timing of policy actions that do not influence the expected course of policy beyond a horizon of about six weeks. We propose an alternative shock measure that captures changes in market expectations of policy over slightly longer horizons.

In February 2005 Federal Reserve Chairman Alan Greenspan noticed that the 10-year Treasury yields failed to increase despite a 150-basis-point increase in the federal funds rate and called it a \"conundrum.\" This paper investigates the historical relationship between the 10-year Treasury yield and the federal funds rate and finds that the relationship changed dramatically in the late 1980s, well in advance of Greenspan's observation. The paper evaluates three competing hypotheses for the change. The evidence from a variety of sources supports the conclusion that the most plausible explanation is that the change occurred because the FOMC began using the federal funds rate as a policy instrument.

We examine the relationship between gold prices and the U.S. dollar exchange rate, arguing that their interactions are state-dependent and asymmetric under different market conditions. State dependency hinges on different short-term interest rate zones. To prove this point, we determine three distinct levels or zones of the effective federal funds rate using SETAR(2,p) tests. Subsequently, we perform conditional least square estimations of log changes in gold prices as a function of log changes in the nominal broad U.S. dollar exchange rate index for each of the obtained zones. Their relationship is consistently inverse, suggesting that gold and the U.S. dollar are risk-hedging substitutes for normal market periods. This also implies that gold is a safe-haven asset against the U.S. dollar exchange rate risk against a broad range of currencies. The substitution is weaker in the low-interest rate zone, more robust in the intermediate zone, and very pronounced in the high zone. We also perform a Markov switching test on the double-log function of gold prices and the exchange rate. The tests show a pronounced inverse relationship, i.e., substitution between assets, at normal market conditions. The relationship becomes significantly positive during episodes of financial distress, indicating complementarity between gold and U.S. dollar assets.

This article investigates the relationship between representation in legislatures and the geographic distribution of federal funds. In a legislative bargaining model, we demonstrate that funds are concentrated in high representation areas, and two channels underlie this result. The proposal power channel reflects the role of representation in committee assignments, and the vote cost channel reflects the role of representation in coalition formation. In our empirical analysis, we find that small states, relative to large states, receive more funding in the US Senate, relative to the House. We also find empirical support for the two channels underlying this relationship.

We present a dynamic over-the-counter model of the fed funds market and use it to study the determination of the fed funds rate, the volume of loans traded, and the intraday evolution of the distribution of reserve balances across banks. We also investigate the implications of changes in the market structure, as well as the effects of central bank policy instruments such as open market operations, the discount window lending rate, and the interest rate on bank reserves.

This article develops a new identification procedure to estimate the contemporaneous relation between monetary policy and the stock market within a vector autoregression (VAR) framework. The approach combines high-frequency data from the futures market with the VAR methodology to circumvent exclusion restrictions and achieve identification. Our analysis casts doubt on VAR models imposing a recursive structure between innovations in policy rates and stock returns. We find that a tightening in policy rates has a negative impact on stock prices and that the Federal Reserve (Fed) has responded significantly to movements in the stock market. Estimates are robust to various model specifications.