Does the Federal Reserve Follow a Non-Linear Taylor Rule?

The Taylor rule has become one of the most studied strategies for monetary policy. Yet, little is known whether the Federal Reserve follows a non-linear Taylor rule. This paper employs the smooth transition regression model and asks the question: does the Federal Reserve change its policy-rule according to the level of inflation and/or the output gap? I find that the Federal Reserve does follow a non-linear Taylor rule and, more importantly, that the Federal Reserve followed a non-linear Taylor rule during the golden era of monetary policy, 1985-2005, and a linear Taylor rule throughout the dark age of monetary policy, 1960-1979. Thus, good monetary policy is associated with a non-linear Taylor rule: once inflation approaches a certain threshold, the Federal Reserve adjusts its policy-rule and begins to respond more forcefully to inflation.

Deregulation and Structural Change in the U.S. Commercial Banking Industry

Regulatory change not seen since the Great Depression swept the U.S. banking industry beginning in the early 1980s and culminated with the Interstate Banking and Branching Efficiency Act of 1994. Banking analysts anticipated dramatic consolidation with large numbers of mergers and acquisitions. Some expressed concern about the long-term health of the smaller community banks. This paper describes and discusses the actual evolution of the U.S. banking industry over the past two decades, using the 1976 to 1998 Report of Condition and Income (Call Report) and merger data recently posted on the web site of the Federal Reserve Bank of Chicago. Among several results, more permissive interstate banking and branching regulation significantly associates with higher merger rates, with lower net entry rates, and with higher concentration within states. Interestingly, more permissive intrastate banking and branching regulation only associates with higher concentration.

Predicting the Fed

Predicting the federal funds rate and beating the federal funds futures market: mission impossible? Not so. We employ a Markov transition process and show that this model outperforms the federal funds futures market in predicting the target federal funds rate. Thus, by using purely historical data we are able to better explain future monetary policy than a forward looking measure like the federal funds futures rate. The fact that the federal funds futures market can be beaten by a statistical model, suggests that the federal funds futures market lacks eciency. The mar- ket allocates too much weight to current Federal Reserve communication and other real-time macro events, and allocates too little weight to past monetary policy behavior.