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Some banks are quite simple, while others are part of complex multi-layered organizations with affiliates in many industries scattered all around the world. The latter organizations are formally called bank holding companies (BHCs). In this post, we investigate changes in BHC geography, especially the rising share of BHC affiliates in tax havens and financial secrecy jurisdictions. We examine what has happened since 2000, including the period after the 2010 Dodd-Frank Act, which focused attention on the size and complexity of large BHCs. Our analysis complements a growing body of work on large and complex BHCs and their global affiliates, including this blog series based on papers from the Economic Policy Review.
The Federal Reserve has kept interest rates at historic lows for the last six years, but eventually rates will return to their long-term averages. That means both policymakers and the public will once again be asking one of the classic questions in monetary economics: What are the impacts of rising interest rates on the real economy? Our recent New York Fed staff report “Interest Rates and the Market for New Light Vehicles,” considers this question for the U.S. market for new cars and light trucks. We find strong evidence that rising rates will dampen activity: Our model predicts that in the short-run a 100-basis-point increase in interest rates will cause light vehicle production to fall at an annual rate of 12 percent and sales to fall at an annual rate of 3.25 percent.
When the U.S. Civil War broke out in 1861, cotton was king. The southern United States produced and exported much of the world’s cotton, England was a major textile producer, and cotton textiles were exported from England around the world. At the time, many around the world depended on cotton for their livelihood. The South believed this so deeply that when the North blocked Southern ports to cut off the South’s primary means of financing war—cotton sales—Southern leaders were sure that Britain would enter the war on their side. That never happened. So when cotton supplies dried up in late 1862, thousands in Manchester and Lancashire who either directly or indirectly depended on cotton for a living found themselves without work. In this post, we describe the British cotton famine of 1862-63 and the stoic British national response. We draw primarily from a fascinating BBC Radio broadcast on the subject and John Watts’ matter-of-factly named Facts of the Cotton Famine, published in 1866.
By Andrew Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw
Update (12.11.15): We added a link to the data used in our charts. See “Chart Data” below.
Today, the New York Fed announced that household debt increased by a robust $212 billion in the third quarter of 2015. Both mortgage and auto loan originations increased, as auto originations reached a ten-year high and new mortgage lending appears to have finally recovered from the very low levels seen in the past year. This quarter, we’re introducing an improved estimate of auto loan originations, some new charts, and some fresh data on the auto loan market. The Quarterly Report on Household Debt and Credit and this analysis use our Consumer Credit Panel data, which is itself based on Equifax credit data.
The dollar rose sharply against both the euro and yen in 2014 and 2015 and non-oil import prices subsequently fell. An explanation for this relationship is that a stronger dollar reduces the dollar-denominated cost of producing something in Germany or Japan, giving firms room to lower their dollar prices in order to gain sales against their U.S. competitors. A breakdown by type of good, however, shows that import prices for autos, consumer goods, and capital goods tend not to move much with changes in the dollar as foreign firms choose to keep the prices of their goods stable in the U.S. market. Instead, the connection between import prices and the dollar largely reflects the tendency for commodity prices to fall in dollar terms when the dollar strengthens. As a consequence, the dampening effect of a stronger dollar on U.S. inflation is transmitted much more through falling commodity prices than through cheaper imported cars and consumer goods.
There’s an ongoing debate about whether policymakers should respond to financial conditions when setting monetary policy. An argument is often made that financial stability concerns are more appropriately dealt with by using regulatory and macroprudential tools. This post offers a theoretical justification for policymakers to monitor and possibly respond to financial conditions not because this would lessen concerns about financial stability but because this information helps reveal the state of the economy and the appropriate stance of monetary policy.
Which of the following statements is true (you may choose more than one): (a) you are more likely to get a job at the Fed if you look like a Barbie doll, (b) you are less likely to get a job at the Fed if you look like a Barbie doll, (c) the inventor of the Barbie doll sat on the Board of Directors of a Federal Reserve Bank, (d) a key cleaner/restorer of the Federal Reserve Bank of New York building has strong ties to Architect Barbie, (e) a Federal Reserve Bank has used Barbie in its economic education program.
Marco Cipriani, Julia Gouny, Matthew Kessler, and Adam Spiegel
The Federal Reserve Bank of New York will begin publishing the overnight bank funding rate (OBFR) sometime in the first few months of 2016. The OBFR will be a broad measure of U.S. dollar funding costs for U.S.-based banks as it will be calculated using both fed funds and Eurodollar transactions, as reported in a new data collection—the FR 2420 Report of Selected Money Market Rates. In a recent post, “The Eurodollar Market in the United States,” we described the Eurodollar activity of U.S.-based banks and compared recent fed funds and Eurodollar rates. Here, we look at the historical relationship between overnight fed funds and Eurodollars and compare the new OBFR rate to the fed funds rate.
However important income inequality is, it is only a partial representation of the inequality in well-being among individuals, households, counties, and other communities. At a minimum, we need to consider other crucial measures such as consumption, leisure, and health. The reason for looking at other measures is that the inequality in income per se might not translate directly into a deeper and more important concept of inequality in welfare terms. For example, Jones and Klenow state that if we were to look at GDP only, France’s living standards would be only about 60 percent those of the United States. However, once we factor in leisure and life expectancy, that figure gets closer to 85 percent, a substantial change. In essence, monetary income, and therefore income inequality, is only a part of what individuals and countries value. We apply exactly this concept to highlight the substantial amount of health inequality across counties in the United States.
Income, or wealth, inequality is not something that central bankers generally worry about when setting monetary policy, the goals of which are to maintain price stability and promote full employment. Nevertheless, it is important to understand whether and how monetary policy affects inequality, and this topic has recently generated quite a bit of discussion and academic research, with some arguing that the Federal Reserve’s expansionary policy of recent years has exacerbated inequality (see, for instance, here or here), while others reach the opposite conclusion (see here or here). This disagreement can be attributed in part to the different channels through which expansionary monetary policy can affect inequality: its effect on asset prices would tend to increase inequality, while its effect on labor incomes and employment would likely decrease inequality. In this post, I study one particular channel through which Fed policies may have disparate effects—namely, mortgage refinancing—and I focus on dispersion across locations in the United States.
Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.
The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Asani Sarkar, all economists in the Bank’s Research Group.
The views expressed are those of the authors, and do not necessarily reflect the position of the New York Fed or the Federal Reserve System.
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