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.
Rajashri Chakrabarti, Michael Lovenheim, and Kevin Morris
The higher education landscape changed drastically over the last decade and a half. This evolution was largely characterized by the unprecedented growth of the private for-profit sector. In this post, we examine whether the evolution of the higher education market was associated with changes in the types of students who attended the institutions in various sectors of the market. Was the growth in enrollment spurred by an increased entry of traditional students? Or was it driven by an inflow of nontraditional students? Has student composition in higher education changed differentially between sectors? It is important for us to understand not only the growth in the higher education market but also which types of students contributed to this growth, because any changes in the composition of students may have implications for the composition of skilled workers in the labor market, for student loans, for loan repayment, and for the labor market returns to education investments.
Rajashri Chakrabarti, Michael Lovenheim, and Kevin Morris
The past decade and a half has seen dramatic changes in the higher education landscape, characterized by significant growth in enrollment. This growth has been concentrated mostly in for-profit schools, where enrollment skyrocketed in the first decade of the period, nearly quadrupling between 2000 and 2011. The post-2011 period has been marked by an abatement of this growth. These patterns have strong implications not only for the higher education market but also for the labor force and the economy more broadly. Therefore, it is essential to understand the evolution of the different sectors of higher education over the last sixteen years; in this post we aim to do just that. How have the different sectors of higher education changed during this period, in particular the for-profit sector? Is the story here more about enrollment in existing schools, or were there differential entries and exits of for-profit schools? This post is the first in a four-part series looking at different aspects of the changing higher education market, including enrollment growth and its composition, student loans, and student loan defaults.
Rajashri Chakrabarti, Giacomo De Giorgi, and Rachel Schuh
Educational attainment is an important element of human capital; however a series of recent papers highlights the crucial role of the quality of education—which determines the skills actually learned, rather than the number of years spent in a classroom—as a main driver of growth. In fact, Hanushek and Woessmann argue that the importance of more appropriately measuring skills is seen in the very tight relationship between quality of skills, or knowledge capital, and growth. Moreover, the researchers state, “The knowledge capital–growth relationship suggests little mystery for East Asia, Latin America, or other regions: Growth rates are accounted for by cognitive skills.” Similarly, “Considering knowledge capital dramatically increases our ability to account for differences in growth.”
This morning, the Federal Reserve Bank of New York released a set of interactive visuals that present data on school spending and its various components—such as instructional spending, instructional support, leadership support, and building services spending—across all thirty-two community school districts (CSD) in New York City and map their progression over time. A key feature of these interactive visuals is that they present the data in two forms: as adjusted data, which control for student categories that receive differential funding from the City based on their needs, and as raw data that do not include this adjustment. The interactive features allow the user to easily view (and compare) the adjusted and raw data, to observe trends for different spending categories, and to compare spending profiles across community school districts for each form of data. Demographic and socioeconomic characteristics of each CSD can be viewed by clicking on the district of interest. Our purpose is to make data on education finance and education indicators more accessible to a broader audience, including education researchers.
Many newly minted college graduates entering the labor market in the wake of the Great Recession have had a tough time finding good jobs. But just how difficult has it been, and are things getting better? And for which graduates? These questions can be difficult to answer because timely information on the employment prospects of college graduates has been hard to come by. To address this gap, today we are launching a new interactive web feature to provide data on a wide range of job market metrics for recent college graduates, including trends in unemployment rates, underemployment rates, and wages. We also provide data on the demand for college-educated workers, as well as differences in labor market outcomes across college majors. These data will be updated regularly and are available for download.
With the college graduation season well under way, a new crop of freshly minted graduates is entering the job market and many bright young minds are hoping to land a good first job. It’s no wonder if they are approaching the job hunt with some trepidation. For a number of years now, recent college graduates have been struggling to find good jobs. However, the labor market for college graduates is improving. After declining for nearly two years, openings for jobs requiring a college degree have picked up since last summer. Not only has this increase in the demand for educated workers continued to push down the unemployment rate for recent graduates, but it has also finally started to help reduce underemployment, though the underemployment rate remains high. While successfully navigating the job market will likely remain a challenge, it appears that finding a good job has become just a little bit easier for the class of 2015.
This morning, the Federal Reserve Bank of New York released a set of interactive visuals that present school spending and its various components—such as instructional spending, instructional support, leadership support, and building services spending—across all thirty-two Community School Districts (CSD) in New York City and map their progression over time. The interactive features allow the user to easily view the data and observe spending trends. Our purpose is to make data on education finance more accessible to a broader audience.
Uncertainty is of considerable interest for understanding the behavior of individuals as well as the movements in key macroeconomic and financial variables. Despite its importance, direct measures of uncertainty aren’t widely available. Because of this data limitation, a common practice is to use survey-based measures of forecast dispersion—reflecting disagreement among respondents—to proxy for uncertainty. Is this a reliable practice? Here, we review the distinction between disagreement and uncertainty as concepts, and show that this conceptual distinction carries over to their empirical counterparts, suggesting that disagreement is not generally a good proxy for uncertainty.
In the first of this two post series, we investigated the relationship between state aid and local funding before and after the Great Recession. We presented robust evidence that sharp changes in state aid brought about by the prolonged downturn influenced local budget decision-making. More specifically, we found that relative to the pre-recession relationship, a dollar decline in state aid resulted in a $0.19 increase in local revenue and a $0.14 increase in property tax revenue in New York school districts. In this post, we dive deeper to consider whether there were variations in this compensatory response across school districts, using an approach described in our recent study. For example, one might expect that there would be differences in willingness and ability to offset cuts in state aid across districts with varying levels of property wealth, which in turn might lead to differences in responses. Was this really the case?
Correction: Earlier, we inadvertently posted the content of the second post in this two-part series under today’s headline. We have updated the blog with the correct content and will post part two on November 12. We apologize for the error.
It’s well known that the Great Recession led to a massive reduction in state government revenues, in spite of the federal government’s attempt to ease budget tightening through American Recovery and Reinvestment Act aid to states. School districts rely heavily on aid from higher levels of government for their funding, and, even with the federal stimulus, total aid to school districts declined sharply in the post-recession years. But the local school budget process gives local residents and school districts a powerful tool to influence school spending. In this post, we summarize our recent study in which we investigate how New York school districts reacted when state aid declined sharply following the recession.
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.
Economic Research Tracker
Liberty Street Economics is now available on the iPhone® and iPad® and can be customized by economic research topic or economist.
We encourage your comments and queries on our posts and will publish them (below the post) subject to the following guidelines:
Please be brief: Comments are limited to 1500 characters.
Please be quick: Comments submitted after COB on Friday will not be published until Monday morning.
Please be aware: Comments submitted shortly before or during the FOMC blackout may not be published until after the blackout.
Please be on-topic and patient: Comments are moderated and will not appear until they have been reviewed to ensure that they are substantive and clearly related to the topic of the post. We reserve the right not to post any comment, and will not post comments that are abusive, harassing, obscene, or commercial in nature. No notice will be given regarding whether a submission will or will not be posted.
The LSE editors ask authors submitting a post to the blog to confirm that they have no conflicts of interest as defined by the American Economic Association in its Disclosure Policy. If an author has sources of financial support or other interests that could be perceived as influencing the research presented in the post, we disclose that fact in a statement prepared by the author and appended to the author information at the end of the post. If the author has no such interests to disclose, no statement is provided. Note, however, that we do indicate in all cases if a data vendor or other party has a right to review a post.