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The Oxford Handbook of Urban Economics and Planning

The Oxford Handbook of Urban Economics and Planning

The Oxford Handbook of Urban Economics and Planning

Nancy Brooks is Visiting Associate Professor at Cornell University in the Department of City and Regional Planning, and has also been on the economics department faculty at the University of Vermont. She earned her Ph.D. in economics from the University of Pennsylvania in 1995. Her research interests are in applied urban and environmental economics. She has published in the Journal of Environmental Economics and Management and the Journal of Economic Behavior and Organization.

Kieran Donaghy is Professor and Chair of the Department of City and Regional Planning at Cornell University. He holds a Ph.D. in regional science from Cornell University. He has studied issues in transportation, land use, housing, labor markets, and the environment. Much of his recent research concerns the impacts of globalization and climate change on regions and how resource-rich regions can avoid the "resource curse."

Gerrit-Jan Knaap is Professor of Urban Studies and Planning and Director of the National Center for Smart Growth Research and Education at the University of Maryland. Knaap's research interests include the economics and politics of land use planning, the efficacy of economic development instruments, and the impacts of environmental policy. He serves on the State of Maryland's Smart Growth Subcabinet and Sustainable Growth Commission and the Science and Technical Advisory Committee to the Chesapeake Bay Commission. Knaap earned his B.S. from Willamette University, his M.S. and Ph.D. from the University of Oregon, and received post-doctoral training at the University of Wisconsin-Madison, all in economics.

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The Oxford Handbook of Urban Economics and Planning embodies a problem-driven and theoretically informed approach to bridging frontier research in urban economics and urban/regional planning. The articles focus on the interface between these two subdisciplines that have historically had an uneasy relationship. Although economists were among the early contributors to the literature on urban planning, many economists have been dismissive of a discipline whose leading scholars frequently favor regulations over market institutions, equity over efficiency, and normative prescriptions over positive analysis. Planners, meanwhile, even as they draw upon economic principles, often view the work of economists as abstract, not sensitive to institutional contexts, and communicated in a formal language spoken by few with decision making authority. Not surprisingly, papers in the leading economic journals rarely cite clearly pertinent papers in planning journals, and vice versa. Despite the historical divergence in perspectives and methods, urban economics and urban planning share an intense interest in many topic areas: the nature of cities, the prosperity of urban economies, the efficient provision of urban services, efficient systems of transportation, and the proper allocation of land between urban and environmental uses. In bridging this gap, the book highlights the best scholarship in planning and economics that address the most pressing urban problems of our day and stimulates further dialog between scholars in urban planning and urban economics.

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research topics in urban economics

Research Projects

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Publications

 Current research Projects

research topics in urban economics

Immigration, Social Outcomes, and Housing Markets

research topics in urban economics

Housing Policy

research topics in urban economics

Economics of Zoning

research topics in urban economics

Amenities and Housing Prices

research topics in urban economics

The Economics of Urban Form

Rasha Ahmed

Rasha Ahmed

Econ 431-37: Topics in Urban Economics

Class time: T/Th  9:25 am -10:40 pm

Email: [email protected]

Class Room:

Office Phone: 860-297-2446

Office Hours:  MWF  *** or by appointment

Course Description and objectives

Urban economics is the study of the location choices of firms and consumers and how these choices affect different urban phenomenon. The course will explore four urban topics:

1. Cities around the world: The rise of cities in developed and developing countries and the challenges currently faced by each.

2. Technology: Technological advances in production, transportation and communication and how they shape urban landscapes in terms of size and function.

3. Segregation:  The economic analysis of racial segregation and the impact it had on the functioning of markets, e.g. housing and labor markets, and opportunities for reform.

4. Education: The impact of space on education opportunities and achievement.  An analysis of the education gap at the local and international level and strategies for reform.

A prior background in urban economics is not required although interest in the subject matter is.  I will start each topic with a brief overview of the economic approach to the particular urban issue.  Students research each topic through reading the required articles, choosing a question of interest to research,  prepare a presentation to the class. By the end of each topic I will give you a writing assignment that tests your ability to synthesize the material covered in a meaningful way.

The Grade for class will be calculated as follows:

Writing assignments                  60%

Participation/ in class writing     20%

Presentations                            20%

1. I expect you to attend every class and to be there on time and not to leave till the end.  I understand that this is your last semester and that many of you will be interviewing for jobs.  I expect you to schedule your job interviews so you do not miss class.

2. I expect you to be engaged in the class at all times.

3. I expect you to check your email regularly.

4. If you accumulate more than two absences, 1 % will be deducted from your final grade for every class missed.

5. Papers submitted within a week after the due date will get graded and discounted by 30%.  There are no makeups for missed presentations.

6. There are no “extra credit” assignments. Your grade will be determined as outlined in the grading section above.

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Glaeser, Edward (2011). “Triumph of the City” the Penguin Press.

Glaeser, Edward and David Cutler (2021). “ Survival of the City: Living and Thriving in an Age of Isolation, ” the Penguin Press.

Arnott, Richard and Dan McMillen.2006. A Companion to Urban Economics. Blackwell Publishers

Bluestone, Barry, Mary Huff Stevenson, and Russell Williams. 2008. The urban experience: economics, society, and public policy. Oxford: Oxford University Press

DeSoto, Hernando. 2000. The Mystery of Capital: Why Capitalism Triumphs in the West and Fails Everywhere Else. Basic Books.

Inman, Robert. 2009. Making Cities Work: Prospects and Policies for Urban America. Princeton University Press

O’Sullivan, Arthur. 2008. Urban Economics. McGraw-Hill/Irwin 7e

Course Outline

The following is an outline of the topics that will be covered each week. The outline and dates may be changed during the semester.

Week 1, 2, 3, 4 (Feb 9 – March 9): Overview of Urban Economics     Urbanization and growth of cities , cities in developed and developing countries ,

Overview: The benefits and costs of cities, Urbanization and development, The modern city, Urban policies

First Writing Assignment Due

Book Chapters:

  • O’Sullivan, chapters 2-5
  • Bluestone, chapters  1 , 2
  • Inman, chapters 1 and 2
  • De Soto chapters 2-4
  • Glaeser chapters 0, 1, 2, 3, 4
  •   America’s Ten Dead Cities: From Detroit to New Orleans . 24/7 Wall Street, August 2010
  • See: The Industrial Revolution Overview
  • See: The BBC documentary on the industrial revolution
  • Assessing Urban Development After the Arab Spring: Illusions and Evidence of Change , Built Environment, Vol 40 (1)
  •   UNFPA State of World Population 2007 : Unleashing the Potential of Urban Growth
  • Hamer, Andrew and Johannes Linn (1987). “ Urbanization in the developing World: Patterns Issues and Policies ,” available in Edwin S. Mills Handbook of Urban and Regional Economics, Vol 2, 1255-1284
  • United Nations Population Report 2019
  • 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 ,”  NBER working paper
  • World Bank (2009). Reshaping Economic Geography.  Report
  • World Bank (2009). Reshaping Economic Geography. Documentary
  • Marx, Benjamin, Thomas Stoker and Tavneet Suri (2013).  “ The Economics of Slums in the Developing World ,” Journal of Economic Perspectives 27(4): 187- 210

Week 5, 6, 7 : Technology (March 11- March 30)

Technology of Production, Communication and Transportation

Inman, chapter 3

Bluestone, chapter 10

Glaeser, chapter 7

Reading Articles:

  • Glaeser, Edward (1998). Are Cities Dying? Journal of Economic Perspectives 12(2):139- 160
  • Gasper, Jess and Edward Glaeser (1998). “ Information Technology and the Future of Cities ,” Urban Economics, 43(1): 136-156
  • Goldin, Claudia and Lawrence (1988). “ The Origins of Technology – skill complementarity ,” Quarterly Journal of Economics
  • Piketty, Thomas and Emmanuel Saez. 2003. “Income Inequality in the United States, 1913-1998.” Quarterly Journal of Economics 118(1): 1-39.
  • Autor, David H. 2014. “Skills, education, and the rise of earnings inequality among the ‘other 99 percent.’” Science 344(6186): 843-85.
  • Goldin, Claudia and Lawrence Katz. 2010. The Race Between Education and Technology Belknap Press of Harvard University Press, Cambridge, Mass.
  • Leamer E.E., Storper M. (2014) “ The Economic Geography of the Internet Age ,” In: Cantwell J. (eds) Location of International Business Activities. Palgrave Macmillan, London
  • Bell, Alex, Raj Chetty, Xavier Jaravel, Neviana Petkova, and John Van Reenen. 2019. “Who Becomes an Inventor in America? The Importance of Exposure to Innovation.” Quarterly Journal of Economics
  • Ahmed, Rasha, Mark Stater and Michael S. Visser (2017). “ Market and Welfare Effects of Big Box Retail Entry in a Linear City Model with Oligopolistic Competition ,”  Annals of Economics and Statistics , 127.
  • Ahmed, Rasha and Mark Stater (2017). “ Is energy efficiency under provided? An analysis of the provision of energy efficiency in multi-attribute products ,” Resource and Energy Economics, 49: 132-149
  • Glaeser, Edward L. and Matthew E. Kahn (2004). “ Sprawl and Urban Growth ,” Handbook of Regional and Urban Economics, 4: 2481-2527
  • Glaeser, Edward L., Matthew E. Kahn and Jordan Rappaport. (2008). “ Why do the poor live in cities? The role of public transportation .” Journal of Urban Economics 63(1): 1-24
  • Helfand, Gloria, and Ann Wolverton. “ Evaluating the Consumer Response to Fuel Economy: A Review of the Literature .” International Review of Environmental and Resource Economics 5.2 (2011): 103-146
  • Kenworthy,Jeffrey R. and Felix B. Laube. (1996) “ Automobile dependence in cities: An international comparison of urban transport and land use patterns with implications for sustainability ,” Environmental Impact Assessment Review 16(4–6): 279–308
  • Litman, Todd (2006). “ London Congestion Pricing Implications for Other Cities .” Victoria Transport Policy Institute, Jan 10
  • Mahaparta, Lisa (2013). “ Gas Prices At The Pump: Europeans Pay Almost Twice As Much As US Residents ” International Business Times
  • Ford, Peter (2005). “ Gas prices too high? Try Europe .” The Christian Science Monitor  
  • “ FACTBOX: Auto emission standards around the world .” Reuters 2009
  • Snavely, Brent (2012). “ U.S. announces tough new 54.5-mpg CAFE standard for vehicle fuel economy ” Detroit Free Press
  • End of Suburbia documentary

Week 8, 9, 10: (April 1-20)  Segregation and Housing

Rise of the suburb

Housing segregation

Housing assistance and promoting home ownership

Third Writing Assignment due

Inman, chapter 5

Bluestone, chapter 12

Edwards, chapter 13

O’Sullivan, chapter 8

Reading Articles :

Fischel, William A. “ An Economic History of Zoning and a Cure for its Exclusionary Effects ,” Urban Studies , 41(2): 317–340, February 2004

“ Social Benefits of Homeownership and Stable Housing ,” National Association of Realtors Research Division , August 2010

Dietz, Robert D. and Donald R. Haurin (2003). “ The social and private micro-level consequences of homeownership ,” Journal of Urban Economics , 54 (3): 401–450

Collins, Michael (2003). “ Towards a Strategic Federal Policy Promoting Homeownership ,” Federal Homeownership Policy.

Ross, Stephen (2008). “ Understanding Racial Segregation: What is known about the Effect of Housing Discrimination ,” UConn Working Paper

Seitles, Marc (1996). “ The Perpetuation of Residential Racial Segregation in America: Historical Discrimination, Modern Forms of Exclusion, and Inclusionary Remedies ,” Journal of Land Use and Environmental Law

Ladd, Helen (1998). “ Evidence on Discrimination in Mortgage Lending ,” The Journal of Economic Perspectives ,12(2): 41- 62

Been,Vicki,  Ingrid Ellen, and Josiah Madar (2008). “ The High Cost of Segregation: Exploring Racial Disparities in High Cost Lending ,”  Fordham Urban Law Journal , 36(3)

US Census Bureau. Residential Segregation of Blacks or African Americans: 1980- 2000 , Chapter 5, page 59

Suresh, Geetha and Gennaro f. Vito (2009). “ Homicide Patterns and Public Housing : The Case of Louisville, KY (1989- 2007)” Homicide Studies

Popkin, Susan J., Michael J. Rich, Leah Hendey, Chris Hayes, and Joe Parilla, “ Public Housing Transformation and Crime: Making the Case for  Responsible relocation” The Urban Institute

Denvir, Daniel (2011). “ The Ten Most Segregated Urban Areas in America ,” Salon, March 29

David M. Cutler, Edward L. Glaeser, and Jacob L. Vigdor (1999). “ The Rise and Decline of the American Ghetto ,” Journal of Political Economy , 107(3): 455- 506

Chetty, Raj, Nathaniel Hendren, and Lawrence F. Katz. 2016. “The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment.” American Economic Review 106 (4): 855–902. Non-technical summary

Chetty, Raj, and Nathaniel Hendren. 2018. “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects.” Quarterly Journal of Economics 133(3): 1107-1162. Non-technical summary.

Week 11, 12, 13 April (April 22 – May 11): Education

Education and Market failure

Education crisis, segregation and empirical evidence

presentations

O’Sullivan, chapter 12

Bluestone, chapter 8

Inman, chapter 9

Brown v. Board at Fifty: “With an Even Hand” A century of Racial segregation , Library of Congress

  • Hoxby, Caroline Minter (1996). “ Are Efficiency and Equity in School Finance Substitutes or Complements? ”  The Journal of Economic Perspectives,  10(4): 51-73
  • Tulip, Peter and Gregory Wurzburg (2007). “ Primary and Secondary Education in the United States ,”  OECD Economics Department working Paper No. 585
  • Taylor, Lori (1999) “ Government’s Role in Primary and Secondary Education ,” Economic Review — Dallas, 15 – 23
  • The Cities, Suburbs and Schools Project website .  (read the report titled: Visual Guide to Sheff vs. O’Neill School Desegregation)
  • Bifulco, Robert, Helen Ladd and Stephen Ross (2009). “ The Effects of Public School Choice on Those Left Behind: Evidence from Durham, North Carolina ,” Peabody Journal of Education, 84:130- 149
  • Ross, Stephen, John Clapp and Anupam Nanda (2008). “ Which school attributes matter? The influence of school district performance and demographic composition on property values ,”  Journal of Urban Economics  63, 451-466
  • Chetty, Raj, John N. Friedman, and Jonah E. Rockoff. 2011. “Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood.” American Economic Review 104 (9): 2633–79.
  • Fredriksson, Peter, Björn Öckert, and Hessel Oosterbeek. 2013. “Long-Term Effects of Class Size.” Quarterly Journal of Economics 128 (1): 249–85.
  • Reardon, Sean. 2016. “School Segregation and Racial Academic Achievement Gaps.” Russell Sage Foundation Journal of the Social Sciences 2 (5): 34–57.
  • Reardon, Sean, Demetra Kalagrides, and Kenneth Shores. 2016. “The Geography of Racial/ Ethnic Test Score Gaps.” CEPA Working Paper , no. 16.
  • Bifulco, Robert, Jason Fletcher, Sun Jung Oh and Stephen Ross (2009). “ Do High School Peers Have Persistent Effects on College Attainment and Other Life Outcomes? ” Labour Economics 29: 83- 90
  • Dobbie, Will, and Roland G. Fryer. 2011. “Are High-Quality Schools Enough to Increase Achievement among the Poor? Evidence from the Harlem Children’s Zone.” American Economic Journal: Applied Economics 3 (3): 158–87.
  • Baker, Bruce (2012). “ Does Money Matter in Education? ” The Albert Shanker Institute
  • Hoxby, Caroline, and Sarah Turner. 2013. “Expanding College Opportunities for High-Achieving, Low Income Students.” Stanford Institute for Economic Policy Research Discussion Paper , no. 12-014: 1–57
  • Zimmerman, Seth D. 2014. “The Returns to College Admission for Academically Marginal Students.” Journal of Labor Economics 32(4): 711-754.
  • Chetty, Raj, John N. Friedman, Nathaniel Hilger, Emmanuel Saez, Diane Whitmore Schanzenbach, and Danny Yagan. 2011. “How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project STAR.” Quarterly Journal of Economics 126 (4): 1593–1660.
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Urban Aging

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Urban aging is an emerging research topic that focuses on the study of senior citizens from an urban health perspective of aging. The scientific assumptions postulated are that the shift toward urbanized lifestyles, combined with an aging population and emerging threats such as climate change, has promoted an increased burden of a range of non-communicable human diseases. Moreover, the context of aging and the use of age-related health services can vary greatly between urban and rural settings. Of course, the aging of society is a positive but challenging phenomenon, as population aging and urbanization are linked to the success of human development. However, whether the urban environment is a better place to age and live in later life than rural areas is still a question without solid evidence, and the rise of chronic non-communicable diseases opens a window for research on investigating the link between the urban environment and chronic disease risk. This Research Topic will explore all the evidence related to the impact of the urban environment and urban pollutants on the prevalence and exposure to the risk of developing chronic diseases in the aging population, including approaches implemented to create age-friendly cities and all concerns related to urban aging. Original article, systematic review, review, mini-review, and opinion paper providing additional knowledge on the topic "Urban Aging" will be welcome.

Keywords : Urban population, Cities, Age-friendly, Urban Health, Pollution, Air Pollutants, Elderly, Disability, Healthy Aging, Multimorbidity, Geriatrics, Older Population, Epidemiology, Public Health, Geriatric Assessment, Aging Research

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Economics for Disaster Prevention and Preparedness in Europe

Europe is facing overwhelming losses and destruction from climate-related disasters. From 1980 to 2022, weather and climate-related events across the EU caused total losses of about €650 billion , or around €15.5 billion per year. Recent disasters, such as floods in 2022 and wildfires in 2023, have highlighted the vulnerabilities of critical infrastructure, including emergency response buildings such as fire stations, but also roads and power lines.

To guide priority investments in disaster and climate resilience and strengthen financial resilience, the report series  Economics for Disaster Prevention and Preparedness —developed by the World Bank and the European Commission—offers evidence and tools to help countries take a more strategic approach to boost their climate resilience. These approaches are also being promoted and operationalized through the ongoing Technical Assistance Financing Facility for Disaster Prevention and Preparedness (TAFF) ,  funded by the European Commission, and implemented by the World Bank and the Global Facility for Disaster Reduction and Recovery ( GFDRR ).

From Data to Decisions: Tools for making smart investments in prevention and preparedness in Europe

Half of EU Member States have fire stations located in areas with high levels of multiple hazards including wildfires, landslides, floods, or earthquakes. Investing in disaster resilience makes economic sense , and there is an urgency to scale up investments in disaster and climate resilience in a cost-effective and smart manner. This report provides guidance and examples on how to make focused and smart investments to increase the disaster and climate resilience of critical sectors, including those that provide emergency-response services. Risk data, analytical tools, and examples can guide decision-making toward high-priority areas and enable a strategic approach that maximizes benefits of investing in resilience.

Investing in Resilience: Climate adaptation costing in a changing world

The report provides new insights into the costs for a country to adapt to the impacts of climate change, new costing approaches, and best practices with estimated ranges for various sectors and multiple risks. While the estimated cost of climate adaptation varies significantly, in the EU, climate change adaptation costs up to the 2030s are estimated(based on extrapolation from national studies) to be between €15 billion to €64 billion. As Europe grapples with the escalating risks of climate change , the urgency to develop 'adaptation pathways' is paramount. These decision-making approaches enable countries to prepare and act amidst uncertainty, informed by current and future climate risks.

Financially Prepared: The case for pre-positioned finance

Floods, earthquakes, landslides and storms, wildfires and droughts, extreme heat risks create additional pressure on already constrained response and recovery budgets. The size of a potential funding gap due to major earthquakes and floods varies between €13 billion to €50 billion . Should a drought or a wildfire happen in a year where a major earthquake or flood has already occurred, there would be no funding available at the EU level to respond to a wildfire or drought event. Countries in Europe need to enhance their financial resilience through better data utilization and innovative financial instruments, including risk transfer to the private sector.

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70 years after brown v. board of education, new research shows rise in school segregation.

Kids getting onto a school bus

As the nation prepares to mark the 70th anniversary of the landmark U.S. Supreme Court ruling in Brown v. Board of Education , a new report from researchers at Stanford and USC shows that racial and economic segregation among schools has grown steadily in large school districts over the past three decades — an increase that appears to be driven in part by policies favoring school choice over integration.

Analyzing data from U.S. public schools going back to 1967, the researchers found that segregation between white and Black students has increased by 64 percent since 1988 in the 100 largest districts, and segregation by economic status has increased by about 50 percent since 1991.

The report also provides new evidence about the forces driving recent trends in school segregation, showing that the expansion of charter schools has played a major role.  

The findings were released on May 6 with the launch of the Segregation Explorer , a new interactive website from the Educational Opportunity Project at Stanford University. The website provides searchable data on racial and economic school segregation in U.S. states, counties, metropolitan areas, and school districts from 1991 to 2022. 

“School segregation levels are not at pre- Brown levels, but they are high and have been rising steadily since the late 1980s,” said Sean Reardon , the Professor of Poverty and Inequality in Education at Stanford Graduate School of Education and faculty director of the Educational Opportunity Project. “In most large districts, school segregation has increased while residential segregation and racial economic inequality have declined, and our findings indicate that policy choices – not demographic changes – are driving the increase.” 

“There’s a tendency to attribute segregation in schools to segregation in neighborhoods,” said Ann Owens , a professor of sociology and public policy at USC. “But we’re finding that the story is more complicated than that.”

Assessing the rise

In the Brown v. Board decision issued on May 17, 1954, the U.S. Supreme Court ruled that racially segregated public schools violated the Equal Protection Clause of the Fourteenth Amendment and established that “separate but equal” schools were not only inherently unequal but unconstitutional. The ruling paved the way for future decisions that led to rapid school desegregation in many school districts in the late 1960s and early 1970s.

Though segregation in most school districts is much lower than it was 60 years ago, the researchers found that over the past three decades, both racial and economic segregation in large districts increased. Much of the increase in economic segregation since 1991, measured by segregation between students eligible and ineligible for free lunch, occurred in the last 15 years.

White-Hispanic and white-Asian segregation, while lower on average than white-Black segregation, have both more than doubled in large school districts since the 1980s. 

Racial-economic segregation – specifically the difference in the proportion of free-lunch-eligible students between the average white and Black or Hispanic student’s schools – has increased by 70 percent since 1991. 

School segregation is strongly associated with achievement gaps between racial and ethnic groups, especially the rate at which achievement gaps widen during school, the researchers said.  

“Segregation appears to shape educational outcomes because it concentrates Black and Hispanic students in higher-poverty schools, which results in unequal learning opportunities,” said Reardon, who is also a senior fellow at the Stanford Institute for Economic Policy Research and a faculty affiliate of the Stanford Accelerator for Learning . 

Policies shaping recent trends 

The recent rise in school segregation appears to be the direct result of educational policy and legal decisions, the researchers said. 

Both residential segregation and racial disparities in income declined between 1990 and 2020 in most large school districts. “Had nothing else changed, that trend would have led to lower school segregation,” said Owens. 

But since 1991, roughly two-thirds of districts that were under court-ordered desegregation have been released from court oversight. Meanwhile, since 1998, the charter sector – a form of expanded school choice – has grown.

Expanding school choice could influence segregation levels in different ways: If families sought schools that were more diverse than the ones available in their neighborhood, it could reduce segregation. But the researchers found that in districts where the charter sector expanded most rapidly in the 2000s and 2010s, segregation grew the most. 

The researchers’ analysis also quantified the extent to which the release from court orders accounted for the rise in school segregation. They found that, together, the release from court oversight and the expansion of choice accounted entirely for the rise in school segregation from 2000 to 2019.

The researchers noted enrollment policies that school districts can implement to mitigate segregation, such as voluntary integration programs, socioeconomic-based student assignment policies, and school choice policies that affirmatively promote integration. 

“School segregation levels are high, troubling, and rising in large districts,” said Reardon. “These findings should sound an alarm for educators and policymakers.”

Additional collaborators on the project include Demetra Kalogrides, Thalia Tom, and Heewon Jang. This research, including the development of the Segregation Explorer data and website, was supported by the Russell Sage Foundation, the Robert Wood Johnson Foundation, and the Bill and Melinda Gates Foundation.   

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  • Half of Latinas Say Hispanic Women’s Situation Has Improved in the Past Decade and Expect More Gains

3. Educational and economic differences among Latinas today

Table of contents.

  • Assessing the progress of Hispanic women in the last 10 years
  • Views of Hispanic women’s situation in the next 10 years
  • Views on the gender pay gap
  • Latinas’ educational attainment
  • Latinas’ labor force participation
  • Latinas’ earnings
  • Latinas as breadwinners in their relationships
  • Bachelor’s degrees among Latinas
  • Labor force participation rates among Latinas
  • Occupations among working Latinas
  • Earnings among Latinas
  • Latinas as breadwinners in 2022
  • Appendix: Supplemental charts and tables
  • Acknowledgments
  • The American Trends Panel survey methodology
  • Methodology for the analysis of the Current Population Survey

Though Latinas have collectively seen socioeconomic gains, their educational and economic circumstances are varied. Younger Latinas and U.S.-born Latinas, for instance, are more likely to report having a bachelor’s degree than older and immigrant Latinas, respectively. This chapter explores how other characteristics such as spouse or partner ethnicity and presence of their children at home are associated with differences in educational and economic outcomes.

A bar chart showing younger and U.S.-born Latinas are more likely to have a bachelor’s degree. In 2023, 30% of Latinas ages 25-29 had a bachelor’s compared with just 14% of Latinas 65 or older.

Some Latinas are more likely than others to have a bachelor’s degree.

  • Age: Younger Latinas (ages 25 to 29) are about twice as likely as older Latinas (ages 65 or older) to hold a bachelor’s degree (30% vs. 14%).
  • Nativity: U.S.-born Latinas are more likely than those born outside the U.S. to hold a bachelor’s degree (30% vs. 19%).

A bar chart showing that among Latinas, those with more education, non-Hispanic partners, are more likely to work or seek work. In 2023, 82% of Latinas with a bachelor’s and 77% of Latinas living with a non-Hispanic spouse or partner participated in the labor force.

Though labor force participation rates have increased in the last two decades for Latinas overall, some are more likely to be employed or seeking work. Among civilians ages 25 to 64:

  • Education: Latinas with a bachelor’s degree or higher are more likely than those with a high school education or less to participate in the labor force (82% vs. 60%).
  • Nativity: U.S.-born Latinas are more likely than Latinas born outside the U.S. to participate in the labor force (75% vs. 64%).
  • Spouse or partner: Latinas who are living with a Hispanic spouse or partner are less likely to work or seek work than those living with a non-Hispanic partner (63% vs. 77%).
  • Children at home: Latinas with children in the home are less likely to work or seek work than Latinas without (67% vs. 73%).

A bar chart showing that about a quarter of Latinas with a bachelor’s degree work in education, legal, community service, arts, and media jobs. Latinas with bachelor’s degrees were much more likely than Latinas with some college or less education to work in education, management, or health care occupations.

Among civilian Latinas ages 25 to 64 who were employed or looking for work in 2023, 15% work in office and administrative support occupations. Similar shares work in management, business and financial occupations (13%) and education, legal, community service, arts and media occupations (12%).

The kinds of occupations Latinas most recently worked in are also associated with whether they have a bachelor’s degree. Among civilian Latinas ages 25 to 64 who were employed or looking for work in 2023:

  • Those with a bachelor’s are most likely to have education, legal, community service, arts and media jobs (27%) or management, business and financial jobs (24%).
  • For those without a bachelor’s, the most common occupational groups are office and administrative support (17%) and health care support, protective service, and personal care and service (15%).
  • Those with a bachelor’s degree are less likely than those without one to work in health care support, protective service, and personal care and service occupations (6% vs. 15%, respectively) and building and grounds cleaning and maintenance occupations (3% vs. 12%).

A bar chart showing earnings for Hispanic women rise with educational attainment. Latinas with a bachelor’s degree make $28.85 per hour (at the median) while those with a high school education or less earn $16.67 per hour.

Though wages have increased for Latinas overall in the last two decades, some earn more than others. Among Latinas ages 25 to 64 who are not self-employed:

  • Education: Latinas with a bachelor’s degree make $28.85 per hour (at the median) while those with a high school education or less earn $16.67 per hour.
  • Nativity: U.S.-born Latinas make more per hour than immigrant Latinas ($21.25 vs. $17.90).
  • Spouse or partner: Hispanic women who live with a spouse or partner earn roughly the same as those without a spouse or partner. However, Hispanic women living with a non- Hispanic spouse or partner make significantly more at the median than those living with a Hispanic spouse or partner ($25.00 vs. $19.00).
  • Children at home: Latinas living with their children earn about the same as Latinas not living with their children ($18.50 vs. $20.00).

A bar chart showing Latinas with more education or living with non-Hispanic partners more likely to be breadwinners in their relationships. Latinas with a bachelor’s degree or higher were more likely than those with a high school education or less to be breadwinners (16% vs. 9%, respectively) or in financially egalitarian relationships (35% vs. 24%).

Overall, 13% of Hispanic women living with their spouse or partner are the breadwinners of their couples. Another 28% of Latinas are in financially egalitarian relationships, while the remaining 59% are living with a breadwinner spouse or partner.

Some Latinas are more likely than others to be either their relationships’ breadwinners or in financially egalitarian relationships with their spouse or partner.

  • Education: Latinas with a bachelor’s degree or higher were more likely than those with a high school education or less to be breadwinners (16% vs. 9%, respectively) or in financially egalitarian relationships (35% vs. 24%).
  • Spouse or partner: Hispanic women living with a partner or spouse who is not Hispanic were more likely than those with a Hispanic spouse or partner to be the breadwinner of their relationship (16% vs. 12%, respectively). They were also less likely than their Hispanic-partnered counterparts to say their spouse or partner was the breadwinner (54% vs. 61%).

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Key facts about U.S. Latinos with graduate degrees

Hispanic enrollment reaches new high at four-year colleges in the u.s., but affordability remains an obstacle, u.s. public school students often go to schools where at least half of their peers are the same race or ethnicity, what’s behind the growing gap between men and women in college completion, for u.s. latinos, covid-19 has taken a personal and financial toll, most popular, report materials.

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The Streetlight Effect in Data-Driven Exploration

We examine innovative contexts like scientific research or technical R&D where agents must search across many potential projects of varying and uncertain returns. Is it better to possess incomplete but accurate data on the value of some projects, or might there be cases where it is better to explore on a blank slate? While more data usually improves welfare, we present a theoretical framework to understand how it can unexpectedly decrease it. In our model of the streetlight effect, we predict that when data shines a light on attractive but not optimal projects, it can severely narrow the breadth of exploration and lower individual and group payoffs. We test our predictions in an online lab experiment and show that the availability of data on the true value of one project can lower individual payoffs by 17% and reduce the likelihood of discovering the optimal outcome by 54% compared to cases where no data is provided. Suggestive empirical evidence from genetics research illustrates our framework in a real-world setting: data on moderately promising genetic targets delays valuable discoveries by 1.6 years on average. Our paper provides the first systematic examination of the streetlight effect, outlining the conditions under which data leads agents to look under the lamppost rather than engage in socially beneficial exploration.

The first part of the experiment was conducted online via the Toronto Experimental Economics Laboratory in September 2021 and March 2022. The second part of the experiment was conducted online via the Vienna Center for Experimental Economics in July, August, and October 2023. The experiment received approval from the University of Toronto Research Ethics Board (approval #00038482) and was pre-registered at https://osf.io/zs2mu/. We are grateful to Gary Biglaiser, Kevin Bryan, Emeric Henry, Ryan Hill, Riitta Katila, Ramana Nanda, Jean-Robert Tyran and participants at the SIE workshop, the MOM workshop at HBS, the MAD conference at Columbia, the SMS Special Conference at Bocconi, the Strategy Science conference, as well as seminars at BU, GeorgiaTech, Michigan, NBER, Purdue, UC Berkeley, UCLA, and Wharton for their suggestions. We thank Adit Jain for his outstanding help in designing the experimental platform. Eva Chang and Cecil-Francis Brenninkmeijer provided excellent research assistance. All authors contributed equally and are listed in alphabetical order. Corresponding author: [email protected]. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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