The Federal Reserve Bank of New York works to promote sound and well-functioning financial systems and markets through its provision of industry and payment services, advancement of infrastructure reform in key markets and training and educational support to international institutions.
The New York Fed engages with individuals, households and businesses in the Second District and maintains an active dialogue in the region. The Bank gathers and shares regional economic intelligence to inform our community and policy makers, and promotes sound financial and economic decisions through community development and education programs.
Oil prices plunged 65 percent between July 2014 and December of the following year. During this period, the yield spread—the yield of a corporate bond minus the yield of a Treasury bond of the same maturity—of energy companies shot up, indicating increased credit risk. Surprisingly, the yield spread of non‑energy firms also rose even though many non‑energy firms might be expected to benefit from lower energy‑related costs. In this blog post, we examine this counterintuitive result. We find evidence of a liquidity spillover, whereby the bonds of more liquid non‑energy firms had to be sold to satisfy investors who withdrew from bond funds in response to falling energy prices.
In Monday’s post, we described the estimation of real wage growth rates for different cohorts of U.S. workers. We showed that the life-cycle pattern of real wage growth is characterized by high growth early in a worker’s career, little to no growth in mid-career, and negative growth as workers near retirement. We also documented that a growing fraction of the U.S. adult population is transitioning into the flat to negative real wage growth phases of their careers. Here, we turn our attention to estimating the effect of this demographic shift on the economy-wide average real wage growth rate. Our analysis shows that this economy-wide average real wage growth rate has declined by a third since the mid-1980s.
Jaison R. Abel, Giacomo De Giorgi, Richard Deitz, and Harry Wheeler
Given Puerto Rico’s long-term economic malaise and ongoing fiscal crisis, it is no wonder that out-migration of the Island’s residents has picked up. Over the past five years alone, migration has resulted in a net outflow of almost 300,000 people, a staggering loss. It would make matters worse, however, if Puerto Rico were losing an outsized share of its highest-paid workers. But we find that, if anything, Puerto Rico’s migrants are actually tilted somewhat toward the lower end of the skills and earnings spectrum. Still, such a large outflow of potentially productive workers and taxpayers is an alarming trend that is likely to have profound consequences for the Island for years to come.
Estimates from the Current Population Survey show that the probability of finding a job declines the longer one is unemployed. Is this due to a loss of skills from being unemployed, employer discrimination against the long-term unemployed, or are there characteristics of workers in this segment of the workforce that lower their probability of finding a job? Studies that send out fictitious resumes find that employers do consider the length of unemployment in deciding whom to interview. Our recent work examines how such employer screening based on unemployment duration ultimately affects job-finding rates and long-term unemployment.
The May Indexes of Coincident Economic Indicators (CEIs) for New Jersey, New York State, and New York City, released today, show some slowing in economic growth across the region—in part reflecting the Verizon strike (which has since been settled), as well as somewhat weaker economic fundamentals. As shown in the chart below, New York City continues to be the strongest engine of growth in the region, by far, though there too, we have seen some deceleration.
Olivier Armantier, Giorgio Topa, Wilbert van der Klaauw, and Basit Zafar
Today, the New York Fed is introducing a number of new data series and interactive charts reporting findings from its Survey of Consumer Expectations (SCE). Since January 2014, we have been reporting findings from this monthly survey on U.S. households’ views on inflation, commodity prices, the labor market and household finances. In addition to interactive charts showing national trends (going back to June 2013), as well as trends by demographic groups (age, income, education, numeracy and geography), we also make the underlying micro data (with a nine-month lag) available for download for research purposes.
It always seemed to come down to railroads in the 1800s. Railroads fueled much of the economic growth in the United States at that time, but they required that a great deal of upfront capital be devoted to risky projects. The panics of 1837 and 1857 can both be pinned on railroad investments that went awry, creating enough doubt about the banking system to cause pervasive bank runs. The fatal spark for the Panic of 1873 was also tied to railroad investments—a major bank financing a railroad venture announced that it would suspend withdrawals. As other banks started failing, consumers and businesses pulled back and America entered what is recorded as the country’s longest depression.
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.
How much someone earns is an important determinant of many significant decisions over the course of a lifetime. Therefore, understanding how and why earnings are dispersed across individuals is central to understanding dispersion in a wide range of areas such as durable and non-durable consumption expenditures, debt, hours worked, and even health. Drawing on a recent New York Fed staff report "What Do Data on Millions of U.S. Workers Reveal about Life-Cycle Earnings Risks?", this blog post investigates the nature of earnings inequality over a lifetime. It finds that earnings are subject to significant downside risk and that such risk contributes substantially to overall earnings dispersion.
The Federal Reserve’s statutory mission from Congress is to achieve maximum employment and price stability for the country as a whole. In line with this dual mandate, economists at the New York Fed monitor conditions in the “aggregate” economy on a day-to-day basis. But in addition, they have been doing a substantial amount of work to understand the differences in economic experiences across individuals, households, and regions. This blog series will examine our economists’ findings on how labor, housing, and health outcomes vary for different groups. A brief summary of the posts in the series follows:
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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