New York, NY…Good morning. I am very pleased to speak at the 6th Annual Community Development Conference. I would like to give a special thanks to the Association for Neighborhood and Housing Development for organizing this conference about issues of importance to the community development industry and to the future of New York City.
At the Federal Reserve Bank of New York, we develop a wide variety of research and data products to gain a deeper understanding of regional economic conditions. We track the health of household balance sheets at the state and local level using data from the New York Fed’s Consumer Credit Panel. We also conduct an annual poll of small businesses to understand their credit needs and credit availability. My meeting with you today is part of our continuing efforts to understand what is going on at the grassroots level of our economy and to share insights from the New York Fed.
The Federal Reserve has dual objectives, set by Congress, with respect to monetary policy—maximum sustainable employment and price stability. I would like to focus my remarks today on the first of these objectives. As always, what I have to say today reflects my own views and not necessarily those of the Federal Open Market Committee or the Federal Reserve System.1
The Federal Reserve’s employment objective can be viewed both narrowly and broadly. Narrowly, we focus on the degree of slack or tightness in the labor market. This leads to discussion of many measures of the labor market such as the unemployment rate, the participation rate and the growth of wages. Broadly, the economy’s potential growth rate depends on effectively investing in and taking advantage of all of the resources in the economy—in particular, we need to achieve the full potential of the human capital of all Americans. For the United States to reach its maximum economic potential, all Americans must have the opportunity to reach their potential.
The United States has always prided itself on being “the land of opportunity.” Parents hope that their children can achieve more than they did. Over the course of our history, immigrants have journeyed to America in search of a better life, a chance to live the “American Dream.”
What defines the American Dream? President Reagan thought that one element of the American dream is “the opportunity to grow, create wealth, and build a better life for those who follow,” while President Obama has described it as follows: “A child’s course in life should be determined not by the zip code she’s born in, but by the strength of her work ethic and the scope of her dreams.” One’s destination in life should not depend on where the journey begins.
Equal opportunity does not imply equal outcomes—some people may work harder, be more fortunate in terms of their disposition and endowments, or just be luckier in how their lives evolve. But it does require that income mobility—in particular, upward mobility—be widely evident and remain part of the fabric of the nation.
It is important to keep in mind the distinction between income mobility and income inequality. Income mobility is a dynamic concept—the degree to which individuals or families can move up or down in the income distribution over time. Income inequality is a static concept—how unequal are individual or family incomes at a particular point in time.
Recognizing that rising income inequality in the United States is an important issue, my focus today will be mainly on income mobility. I don’t think the issue of income mobility receives the attention it deserves. It is a foundational element for a well-functioning democratic society and provides evidence about the ability of an economy to provide opportunities for its citizens.
A standard approach to measuring income mobility is to compare where a child is in the income distribution relative to where the parents were in the income distribution. A striking result is that intergenerational income mobility in the U.S.—a child’s chances of moving up in the income distribution relative to her parents—has remained stable over the past half century. However, because of the increase in income inequality, the consequences of being born to low-versus high-income parents are larger today than in the past. One explanation for the lack of a correlation between income inequality and income mobility in the U.S. is that income inequality is strongly influenced by the top one percent of the income distribution, but there is little correlation between income mobility and this top income percentile.2
While income mobility in the United States has been relatively unchanged, it remains well below several other nations. According to Stanford economist Raj Chetty, the probability of moving from the bottom quintile to the top quintile is 7.5 percent in the United States, as compared to 11.7 percent in Denmark and 13.5 percent in Canada—two countries with relatively high levels of intergenerational mobility.3 So effectively the chance of achieving the American Dream is not the highest for children born in America.
Importantly, Chetty finds even more significant variation in intergenerational mobility across different metro and rural areas within the United States.4 While some regions in the U.S. match the highest mobility levels among developed countries, others persistently offer less mobility than in most other developed countries. Relative income mobility is highest in the Mountain West and the rural Midwest and lowest in the Southeast. Now these differences could be caused by the experience of living in different neighborhoods, but they may also simply reflect differences in the people living in these neighborhoods. In an effort to distinguish between these two possible explanations, Chetty and fellow economists study children from families who changed their neighborhood during childhood and provide evidence that much of the variation in upward mobility reflects the experience of living in particular neighborhoods. Their findings imply that upward mobility depends strongly on where you grow up as a child.
This research indicates that it is the places themselves, rather than the families who live there, that affect the outcomes for children. An important question is what specific features of neighborhoods are associated with greater upward mobility. Chetty and co-authors find that higher upward mobility is associated with areas that are less residentially segregated by race or income, have lower income inequality (i.e. a bigger middle class), higher quality schools, 5 stronger social networks, higher community involvement and stable family structures.
The finding that intergenerational mobility is primarily a local problem has two broad policy implications. The first is the need for place-based policies to invest more in at-risk communities to improve their childhood environments. The second is to facilitate families to be able to move into areas with better childhood environments.
With respect to the first, I would initially like to talk about the importance of schools―and in particular, strong public education. Consistent with the findings by Chetty, there exists a large literature that has established the importance of high-quality education as a key determinant of economic mobility. While there are differences of opinions on the most relevant measures of school quality, there is ample evidence that children who attend better schools on average end up with better outcomes later in life—such as higher levels of educational attainment and higher earnings. It is also well known that there exist large disparities in the quality of education by geography and socioeconomic background. Compared to children born to low-income parents, those born to higher-income families can better afford to move and live in areas with high-quality schools.
The sorting of families by income and their desire for better educational opportunities leads to enclaves of higher-quality and higher-spending schools that are separated from areas of economically less-advantaged populations and lower-quality schools. To a degree, this residential segregation has been perpetuated by our system of school financing that relies heavily on local property tax funding. Local financing of public schools leads to a bundling of two distinct choices—residential choice and school choice—and increases the degree of socioeconomic segregation across school districts.
We can promote greater income mobility by unbundling the residential and school choices. This can be done in one of two ways. The first is to work to equalize school quality across location, while the second is to allow parents more choice of schools from a given location. Along the lines of the first approach, New York Fed research has shown that school finance reforms that seek to equalize funding across school districts by reducing the role of local property taxes can go a long way in decreasing residential segregation and equalizing quality of education.6 The key mechanism is that such reforms make underperforming neighborhoods more attractive, thus reducing socioeconomic segregation and leading to consequent gains in peer quality in previously-challenged enclaves. This in turn reduces disparities in school quality stemming from reduced socioeconomic segregation.
On the second approach, there exists research indicating that school vouchers that enable students to move to private schools or better-quality public schools can lead to improvements in public school quality and student performance by increasing competition among schools.7 It is important to note, though, that not all voucher programs are created equally, and the design of the program matters in how vouchers impact school quality. Charter schools have provided another source of school choice in education. More research into evaluating the effectiveness of voucher programs and charter schools at raising student achievement would be desirable in terms of informing public policy choices.8
The importance of education is not limited to elementary and secondary levels. In fact, there exists convincing evidence from the child development literature that suggests that educational investments early in childhood have especially large rates of returns in terms of lifetime earnings and other outcomes. Take, for example, the Perry Preschool program for low-income African-American children, a two-year preschool program experiment in the mid-1960s. Recent research shows that this program had very large beneficial long-term effects, with participants experiencing higher rates of high school graduation, higher salaries, higher homeownership, more stable family structures, fewer arrests and lower welfare dependence. The large positive economic externalities from these investments in children imply that such programs more than pay for themselves over the long term. Estimates indicate that the aggregate benefits over the life of a child exceeded by eightfold the program’s per-pupil cost.9 Almost equally-large gains were reported for children who enrolled in Head Start, a federally-funded nationwide preschool program for low-income children.10
Related literature on neighborhood effects has found that labor market outcomes for adults are also significantly affected by the type of neighborhoods where people reside. The role of labor market networks and referrals has been amply-demonstrated as affecting the likelihood of finding a job, the quality of matches between employers and workers, and the earnings associated with these jobs. Several studies show that many of these networks have a significant local neighborhood component. Further, workers who live in neighborhoods with higher-quality networks are more likely to move to jobs with higher wages.11
Let me now turn to policies aimed at improving upward income mobility through increased residential mobility. There is some striking evidence that shows providing more opportunities for families to move to wealthier areas may improve upward mobility while also being cost-effective.12 In the mid-1990s, as part of a lottery-based housing mobility experiment sponsored by HUD—called the Moving to Opportunity (MTO) experiment—families in high-poverty housing projects were given housing vouchers to move to lower-poverty mixed-income neighborhoods. While this project appears to have had little impact on the economic outcomes of the adults and older children, the program appears to have had remarkable long-term impacts on children who moved to such neighborhoods at a young age, with the impacts increasing by the number of childhood years they ended up living in the better environment.
Analysis of the data from the experiment shows that those who moved to lower-poverty areas when they were 12 or younger were found to earn about 30 percent more, on average, in their early- to mid-twenties compared to those who did not move, were 27 percent more likely to have entered college, and 30 percent less likely to be a single parent. The MTO experiment again illustrates the importance of neighborhood effects on child development early in childhood. It also demonstrates that grants to move families to lower-poverty neighborhoods may reduce the intergenerational persistence of poverty.
Of course, mobility of the sort that Chetty and other researchers have emphasized interacts in a very important way with the availability of affordable housing. Making high quality neighborhoods accessible to families from all socioeconomic backgrounds is a major challenge for public policy. Of course, illegal racial and other discrimination has played a role in preventing access to high-quality neighborhoods. However, part of the challenge arises from the fact that in a free-market economy, the quality of the environment is reflected in the price of land—and thus housing—in that place. This means that the neighborhoods with the best schools, the best access to jobs, shopping, recreation and other amenities will be the most desirable and will have the highest cost of land and housing. Simply put, families seeking the upward mobility that better neighborhoods can promote may well find that housing in these neighborhoods is unaffordable.
Some kinds of public policies may exacerbate, rather than lessen, the tendency of the housing market to price some families out of good neighborhoods. Zoning and other land use regulations are sometimes enacted to artificially reduce the supply of housing, thus driving its price up even further. Take, for example, minimum lot size zoning which specifies a minimum amount of land per housing unit. When this regulation is binding, it reduces the number of housing units that can be built in a given area, and thus introduces artificial scarcity into the housing market, thereby raising prices.
Zoning can also be used to promote affordable housing—to include, rather than exclude low-and moderate-income families by setting aside space for those families in exchange for the right to develop market-rate units. This is a strategy that New York and other large cities have pursued for many years, and in these cities it is easy to point to units that were developed under the program. Nonetheless, these programs are often controversial—some economists and others argue by increasing the cost of development they restrict supply. Thus, while some percentage of new units developed will be affordable, fewer new units will be developed with uncertain effects on affordability overall.
It’s perhaps informative to contrast this kind of program with one that has historically been the main mechanism by which the supply of affordable housing has increased. The program I have in mind here isn’t a housing program, but, in my view, it has extremely important effects on the housing market. I’m talking about intra-urban transportation, which can serve to dramatically increase the locations available for development, and thus promote the availability of affordable housing.13 I believe that safe, reliable, affordable and efficient transportation to job locations should be a crucial element in an effective housing policy. Such a program indisputably increases the supply of sites available for development, which is a key way to get the benefits of lower prices to a broader set of families. Indeed, it is clear that cities’ ability to grow and attract new residents requires them to either increase density—essentially meaning taller buildings—or to expand outwards by increasing transportation access.
Access to affordable credit is yet another pillar of a policy program that promotes housing affordability. We at the Federal Reserve have long worked to ensure that credit flows equitably and that financial services are available to all U.S. citizens. The Fed’s research on these subjects ranges from the pioneering study of redlining by a team of Boston Fed economists, to a very recent New York Fed study on “banking deserts” that appeared in our Liberty Street Economics blog just last month, as well as ongoing community credit work. We understand the importance of credit in allowing communities to grow, and the importance of the Community Reinvestment Act in requiring financial institutions to make investments in their communities. But, as my remarks here have indicated, credit is only one factor—and perhaps not the most important one—that affects the affordability of housing in our cities.
I’ve addressed the importance of geographic mobility in supporting income mobility from the perspective of providing parents options for better neighborhoods in which to raise their children. Geographic mobility is also important in terms of individuals receiving the highest return to their human capital. Local economic shocks can depress employment and wages in some labor markets. This creates a strong incentive for individuals to move to an alternative labor market in order to more fully utilize their skills. Financial frictions to geographic mobility can reduce this movement of individuals across labor markets leading to less-efficient outcomes for the economy. Income mobility can be enhanced through policies that attempt to limit these financial frictions. This argues for avoiding, where possible, policies that create “in-place” subsidies where the household can access the benefits only while remaining in a specific location.
The Federal Reserve has the twin objectives of maximum sustainable employment and price stability. Achieving the first of our objectives requires that every individual has the opportunity to achieve her full potential in life. Where you happen to be born should not determine your chance of living the American Dream. Research is highlighting possible key determinants of economic opportunity and income mobility. More research is necessary to inform future policy choices in this critical area.
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Chakrabarti, Rajashri. 2008.”Can Increasing Private School Participation and Monetary Loss in a Voucher Program Affect Public School Performance? Evidence from Milwaukee,” Journal of Public Economics, 92(5-6), 1371-1393.
Chakrabarti, Rajashri. 2013. “Impact of Voucher Design on Public School Performance: Evidence from Florida and Milwaukee Voucher Programs,” B.E. Journal of Economic Analysis and Policy: Contributions, 14(1): 349-394.
Chetty, Raj, Nathaniel Hendren, Patrick Kline, Emmanuel Saez and Nicholas Turner. 2014. “Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility,” American Economic Review: Papers and Proceedings, 104(5): 141-147.
Chetty, Raj and Nathaniel Hendren. 2015. “The Impacts of Neighborhoods on Intergenerational Mobility: Childhood Exposure Effects and County-Level Estimates,” Harvard University and NBER.
Chetty, Raj, Nathaniel Hendren, Patrick Kline and Emmanuel Saez. 2014. “Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States,” Quarterly Journal of Economics, 129(4): 1553-1623.
Chetty, Raj, Nathaniel Hendren, and Lawrence F. Katz. 2015. “The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment,” Harvard University and NBER.
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1 Rajashri Chakrabarti, Andrew Haughwout, Giorgio Topa, Joseph Tracy and Wilbert van der Klaauw assisted in preparing these remarks.
2 Piketty and Saez (2003) and Chetty, et al. (2014).
3 Chetty, et al. (2014).
4 Chetty and Hendren (2015), Chetty, et al. (2014).
5 Measured by income-adjusted test scores, drop-out rates, average class size and per-pupil spending.
6 Chakrabarti and Roy (2015).
7 Hoxby (2003), Chakrabarti (2008) and Chakrabarti (2013).
8 Dobbie and Fryer (2011), Dobbie and Fryer (2015), Angrist, et al. (2016).
9 Heckman (2006)
10 Deming (2009).
11 See Bayer et al. (2008), Schmutte (2015), Hellerstein et al. (2011), Aslund et al. (2011).
12 Chetty et al. (2015)
13 See Baum-Snow (2007) and Jackson (1987).