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Gizem Kosar, Kyle Smith, and Wilbert van der Klaauw
Today, we are releasing new data on individuals’ expectations for future changes in a wide range of public policies. These data have been collected every four months since November 2015 as part of our Survey of Consumer Expectations (SCE). The goal of this post is to introduce the SCE Public Policy Survey and highlight some of its features.
Given momentum in house prices over business cycles, research on consumer beliefs since the financial crisis has honed in on the potential importance of extrapolative beliefs—myopically assuming trends in asset prices will continue. Extrapolation is frequently cited as a central reason for excessively optimistic expectations about future asset prices, featuring prominently, for example, in the irrational exuberance narrative of Shiller. Other influential work since the Great Recession has emphasized the outsized role that extrapolative optimists can have in bubble formation. In this post, we look at how much dispersion there is in the amount of house price extrapolation and how consequential extrapolative beliefs could be for house price dynamics.
Health is an integral part of well-being. The United Nations Human Development Index uses life expectancy (together with GDP per capita and literacy) as one of three key indicators of human welfare across the world. In this post, I discuss the state of life expectancy inequality in the United States and examine some of the underlying factors in its evolution over the past several decades.
Michael J. Fleming, Peter Johansson, Frank M. Keane, and Justin Meyer
Five years ago today, U.S. Treasury yields plunged and then quickly rebounded for no apparent reason amid high volatility, strained liquidity conditions, and record trading volume in the market. Federal Reserve Chair Jerome Powell, then a Board governor, noted that such episodes, “threaten to erode investor confidence” and that investors need “to have full faith in the structure and functioning of Treasury markets themselves.” The October 15, 2014, “flash rally” led to an interagency staff report on the events of that day, an annual series of Treasury market conferences, additional study of clearing and settlement practices, and the introduction of a new transactions reporting scheme. Many of these developments are discussed in posts (see, for example, here and here) in the Liberty Street Economics archive.
Rajashri Chakrabarti, William Nober, and Wilbert van der Klaauw
The rising cost of a college education has become an important topic of discussion among both policymakers and practitioners. At least eleven states have recently introduced programs to make public two-year education tuition free, including New York, which is rolling out its Excelsior Scholarship to provide tuition-free four-year college education to low-income students across the SUNY and CUNY systems. Prior to these new initiatives, New York, had already instituted merit scholarship programs that subsidize the cost of college conditional on academic performance and in-state attendance. Given the rising cost of college and the increased prevalence of tuition-subsidy programs, it’s important for us to understand the effects of such programs on students, and whether these effects vary by income and race. While a rich body of work has studied the effects of merit scholarship programs on educational attainment, the same is not true for the effects on financial outcomes of students, such as debt and repayment. This blog post reports preliminary findings from ongoing work, which is one of the first research initiatives to understand such effects.
Andrew F. Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw
Student loans are increasingly a focus of discourseamongpoliticians, policymakers, and the news media, resulting in a range of new ideas to address the swelling aggregate debt. Evaluating student loan policy proposals requires understanding the challenges faced by student borrowers. In this post, we explore the substantial variation in the experiences of borrowers and consider the distributional effects of various policy options.
Workers in the United States experience vast differences in lifetime earnings. Individuals in the 90th percentile earn around seven times more than those in the 10th percentile, and those in the top percentile earn almost twenty times more. A large share of these differences arise over the course of people’s careers. What accounts for these vastly different outcomes in the labor market? Why do some individuals experience much steeper earnings profiles than others? Previous research has shown that the “job ladder”—in which workers obtain large pay increases when they switch to better jobs or when firms want to poach them—is important for wage growth. In this post, we investigate how job ladders differ across workers.
Economic inequality in the United States is much more pronounced in some parts of the country than others. In this post, we examine the geography of wage inequality, drawing on our recent Economic Policy Review article. We find that the most unequal places tend to be large urban areas with strong economies where wage growth has been particularly strong for those at the top of the wage distribution. The least unequal places, on the other hand, tend to have relatively sluggish economies that deliver slower wage growth for high, middle, and lower wage earners alike. Many of the least unequal places are concentrated in the Rust Belt. These differences in the degree of wage inequality are tied to powerful economic forces arising from technological change and globalization, which have pushed up wages strongly for high-skilled workers in locations that have become the most unequal. Yet those same forces have kept wage growth compressed within a fairly narrow range for workers in places that are the least unequal.
Economic analysis is often geared toward understanding the average effects of a given policy or program. Likewise, economic policies frequently target the average person or firm. While averages are undoubtedly useful reference points for researchers and policymakers, they don’t tell the whole story: it is vital to understand how the effects of economic trends and government policies vary across geographic, demographic, and socioeconomic boundaries. It is also important to assess the underlying causes of the various inequalities we observe around us, whether they are related to income, health, or any other set of indicators. Starting today, we are running a series of six blog posts (apart from this introductory post), each of which focuses on an interesting case of heterogeneity in the United States.
Two years after hurricanes Irma and Maria wreaked havoc on Puerto Rico and the U.S. Virgin Islands, the two territories’ economies have moved in very different directions. When the hurricanes struck, both were already in long economic slumps and had significant fiscal problems. As of the summer of 2019, however, Puerto Rico’s economy was showing considerable signs of improvement since the hurricanes, while the Virgin Islands’ economy remained mired in a deep slump through the end of 2018, though signs of a nascent recovery have emerged in 2019. In this post, we assess the contrasting trends of these two economies since the hurricanes and attempt to explain the forces driving these trends.
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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