How States Can Direct Economic Development to Places and People in Need

Overview

Data from an array of sources has shown that Americans who grow up in economically distressed areas experience lower-performing schools, higher crime rates, a variety of health and environmental hazards, and less upward mobility. The consequences of these disadvantages have been on stark display during the coronavirus pandemic as low-income neighborhoods and racial and ethnic minority communities have disproportionately borne the virus’s toll.

To address local disparities and help struggling areas thrive, governments at all levels have spent hundreds of billions of dollars over the past 40 years on a range of geographically targeted, or “place-based,” economic development programs—mostly in the form of financial incentives—designed to boost job creation and business investment, incentivize real estate development, or increase property values in specific places.

However, previous research has shown that place-based programs often fail to benefit the places and people they are intended to aid. To better understand the reasons for this lack of effectiveness, The Pew Charitable Trusts performed a literature review of more than 100 studies from research organizations, academics, and governments, including more than 40 produced by states. Pew staff also conducted more than 30 interviews with national experts, government officials, and researchers. The analysis focused on state governments because they play a central role in place-based development efforts, helping to administer major federal economic and community development programs, designing their own initiatives, and writing laws that dictate how local government programs may operate.

Pew’s analysis found that the criteria that states use to geographically target their programs are often ill-conceived or out-of-date, with the result that initiatives end up serving wealthy locations instead of disadvantaged ones. And even when programs do reach the intended communities, they often are not well-suited to help residents.

Pew’s research indicates that to begin solving these problems, states should:

• Target programs using quantitative measures. To ensure that benefits accrue to communities in need, policymakers should use carefully selected objective measures of distress to determine eligible areas.
• Systematically assess geographic targeting. States should regularly examine where businesses using programs are located in order to identify and correct instances in which wealthier areas unintentionally benefit.
• Regularly update the set of eligible locations. Because local economic conditions change over time, policymakers should regularly review where programs are available to ensure that those places still need assistance.
• Tailor economic development strategies to local needs. Financial incentives alone may be insufficient to encourage private investment in areas that lack trained workers or necessary infrastructure, so policymakers should address these prerequisites to growth.
• Create job opportunities for low-income residents. Even programs that successfully encourage investment in distressed areas may not provide benefits to the local population, so states should embrace strategies—such as prioritizing industries that offer good jobs to people without college degrees—that can help direct economic gains to community members.

Some states are demonstrating that progress is possible. For instance, in response to assessments that revealed flawed targeting, New Jersey and North Carolina changed their approaches to more effectively direct the benefits to the intended locations. Through similar reforms, policymakers in other states could ensure that place-based economic development programs help combat poverty, joblessness, and disinvestment in some of America’s poorest communities.

How place-based programs work, and why they disappoint

For decades, local, state, and federal policymakers have pursued initiatives to strengthen the economies of distressed areas. Geographically targeted tax breaks and other financial incentives for businesses, developers, and investors emerged as governments’ predominant approach in the 1970s and 1980s as policymakers tried to reverse population loss and economic decline in many of the nation’s largest cities. By the 1990s, most states were authorizing tax increment financing (TIF) and enterprise zones, programs that still are in widespread use around the nation.² (See Table 1 and the appendix for descriptions of the types of place-based programs.)

Today, place-based programs remain governments’ primary strategy for bolstering struggling local economies, at an annual cost to taxpayers in the tens of billions of dollars. For example, tax credits for companies that create jobs are by far the most expensive category of state business incentives.³ And states often make those credits more generous or offer relaxed qualification standards for companies that locate or expand in economically distressed areas.

Table 1

Geographically Targeted Initiatives Use Varied Economic Development Strategies

Major types of place-based programs

© 2021 The Pew Charitable Trusts

Although local, state, and federal policymakers share responsibility for designing and administering place-based initiatives, states play the crucial role of determining which locations are eligible for many of the largest programs. In addition to creating and targeting state incentives, such as job creation tax credits, state lawmakers write the statutes that authorize local governments to use key tools such as TIF, “the most widely used local government program for financing economic development in the United States.”⁴ And in doing so, they decide whether and how local programs will be targeted to distressed areas.

State governments also make eligibility decisions for key federal programs. For instance, state housing officials create the scoring systems that help determine where projects will be built using the $8 billion-a-year low-income housing tax credit (LIHTC), “the nation’s largest source of funding for the construction of affordable rental housing.”⁵ Similarly, although populous cities and counties automatically receive benefits under the Community Development Block Grant (CDBG) program—which has provided a total of $150 billion in aid for localities since the 1970s—states are responsible for dividing up dollars to smaller jurisdictions.⁶ And governors, not federal officials, made the final decisions about which neighborhoods qualify for the opportunity zones program, which Congress created in 2017 and which former U.S. Treasury Secretary Steven Mnuchin predicted would lead to $100 billion in new investment spurred by capital gains tax breaks.⁷

Flawed targeting

Decades of research have shown that governments have struggled to effectively target programs geographically. TIF, enterprise zones, CDBG, and other programs designed to direct economic activity to struggling areas frequently end up benefiting wealthier communities.⁸ For instance, studies in Colorado, Maine, Maryland, and Minnesota have found that these states did a poor job targeting their enterprise zone programs to distressed areas.⁹ And early signs indicate that many states may have had similar difficulties with the newer federal opportunity zones program.¹⁰

Part of the problem with targeting is that eligibility for place-based programs often extends to locations with varying degrees of economic hardship, and if businesses and developers can receive the same tax or other incentives for investing in an area that is doing well versus one that is struggling, they usually prefer the former. As a result, benefits tend to flow to the least-distressed eligible locations, and areas that are struggling the most often receive little investment.

Poor targeting also reflects two oft-competing pressures that policymakers face: the need to improve economic conditions in distressed areas and the broader imperative to attract businesses to locate and hire statewide. When those aims conflict, statewide economic development usually wins. Over time, lawmakers often dilute the geographic emphasis of place-based programs to accommodate businesses that want maximum flexibility regarding where to locate.¹¹

Further, even when states effectively direct place-based interventions to the appropriate locations, they often do not successfully achieve their ultimate goal: to assist the people who live in struggling communities. For example, a program that creates jobs in a distressed area usually offers no guarantee that local residents will fill those jobs.

These failures represent a missed opportunity not only to boost prosperity broadly, but also to combat racial inequities. Low-income Black and Hispanic Americans are about five and three times as likely, respectively, as economically similar White people to live in an extremely poor census tract—areas in which at least 40% of residents live below the federal poverty threshold.¹² As a result, people of color more often confront “the double burden of being poor in a very poor place.”¹³

Of course, better targeting of place-based programs will not end racial inequities on its own. But if policymakers are going to spend billions of dollars on programs to aid predominantly Black and Hispanic neighborhoods, they should ensure that the initiatives they choose benefit those neighborhoods and their residents.

Strategies to improve targeting of place-based programs

Target programs using quantitative measures

Former Chicago Mayor Richard M. Daley (D) once declared that tax increment financing was “the only game in town” for promoting development in his city.¹⁴ Although the program is intended to redevelop struggling areas, Chicago’s leaders have created TIF districts not only in distressed communities, but also in some of the city’s most prosperous neighborhoods in order to fund prominent development projects. In Daley’s time, TIF was used to build luxury office developments in Chicago’s downtown and to create Millennium Park, and his successor, Rahm Emanuel (D), spent TIF dollars to renovate the Navy Pier, one of the city’s top tourist attractions.¹⁵ In 2019, TIF diverted $900 million in property tax revenue from Chicago’s city government, public schools, and other local taxing authorities, primarily for development projects in wealthier areas, potentially leaving less money for citywide services. Of the nine TIF districts that generated the most revenue that year, eight were downtown or nearby.¹⁶

Chicago’s leaders have been able to use TIF so expansively in part because Illinois’ statute establishing the program is ambiguous on key points. Local officials can declare an area “blighted” and eligible for TIF if it meets any five of 13 criteria, including highly subjective metrics such as “obsolescence” and “deleterious land use or layout.”¹⁷ Many TIF programs—as well as other place-based initiatives—around the country rely on similarly vague criteria.¹⁸

States can address this challenge by adopting objective statistical measures such as poverty and unemployment rates and per capita income. But not all metrics can meaningfully measure distress in all jurisdictions, so policymakers must take care when they select quantitative criteria or risk unintended consequences. For instance, under federal law, governors could designate census tracts with high poverty rates or low median family incomes as opportunity zones. And because full-time students often have little or no income, these criteria extended program eligibility to many elite public and private college campuses or adjoining areas, including ones without other signs of distress such as abandoned buildings or a lack of private investment. In California, for example, two tracts at the University of Southern California qualified as opportunity zones. One of the tracts has an official poverty rate of 88%, but 99% of residents are enrolled in the university, where undergraduate tuition is nearly $60,000 a year.¹⁹

By contrast, New Jersey has had success improving its use of quantitative criteria to measure distress and accurately target interventions. In 2017, the state’s Department of Community Affairs set out to update the Municipal Revitalization Index (MRI)—a ranking of the state’s 565 municipalities based on economic hardship—which state officials use to target several programs. The department began by calculating the rankings using the indicators included in the most recent (2008) version of the MRI, but with more current data.

That analysis yielded several surprising outcomes. For instance, Winfield Township, a middle-class bedroom community with a low poverty rate, placed as the second-most-distressed municipality in New Jersey—ahead of much poorer cities such as Camden, Newark, and Atlantic City.²⁰ A close examination revealed that two indicators—both housing related—were largely responsible for the idiosyncratic results. First, to reflect the infrastructure needs of older communities, the MRI rated municipalities with a larger share of pre-1960 housing as more distressed, but in practice, the measure caused the MRI to lump together places with high-quality older housing and much more troubled locales. This contributed to the rating for Winfield Township, which was built during World War II to house workers at a nearby shipyard.

Second, the MRI considered the percentage of occupied homes with incomplete plumbing, such as a lack of flush toilets. Although this indicator might have been helpful for measuring distress when the MRI was introduced in 1979, by 2017 it was largely obsolete because fewer than 1 in 500 homes in most municipalities lacked complete plumbing.²¹ As a result, very small differences on this indicator, such as whether zero or 1% of homes lacked complete plumbing, could significantly shift the ratings.

In light of these findings, the department launched a study of similar indexes across the country to identify better criteria, selected 15 promising candidates, and conducted empirical analyses on those indicators. For example, the department studied the extent to which the criteria correlated with one another, based on research suggesting that although each indicator should add something distinct to the index, a criterion that was wholly unrelated to the others probably was not measuring distress.

In the end, the department settled on 10 indicators, including a range of economic, social, demographic, and fiscal measures. For instance, it selected the share of residents with a high school diploma, instead of the proportion with at least a bachelor’s degree, because the latter tended to “obscure distress within communities with high concentrations of college-educated residents, but also large pockets of poverty.”²² With these new indicators in place, the 2017 index ranked Camden as the most distressed municipality in New Jersey.²³ And today, the state is using the updated MRI to target a range of initiatives, including a financial and technical assistance program designed to help municipalities turn around struggling neighborhoods, and tax credits to support low-income housing and neighborhood revitalization.²⁴

Assess geographic targeting systematically

In 2016, the staff of Maryland’s Department of Legislative Services (DLS)—which conducts regular evaluations of place-based programs that offer insights on targeting—studied a tax credit for rehabilitating historic buildings and determined that the program’s targeting rules were only partially achieving the intended goals.²⁵ In the years preceding the DLS review, Maryland lawmakers had added provisions to direct benefits toward localities that historically had been underrepresented in the program and to limit the share of credit-funded projects that could be located in any one jurisdiction, a stipulation intended to reduce Baltimore’s dominance of the program.²⁶ The review found that although the changes did effectively limit the number of approved projects in Baltimore, they also had caused a backlog of otherwise worthy applications from the city.²⁷

Further, the analysis showed that the effort to reach underrepresented jurisdictions was mostly irrelevant because the volume of applications from outside Baltimore was so small that the state usually approved them all anyway, regardless of whether the location was historically underrepresented.²⁸ Based on these findings, when lawmakers revised the program again in 2016, they eliminated the requirement that officials consider whether jurisdictions were historically underrepresented.²⁹

As the Maryland example shows, well-intentioned efforts to direct place-based programs can yield unexpected outcomes, so states need to regularly assess targeting to identify problems and improve results. To date, states have not consistently conducted the necessary assessments, and when they do, they typically focus on only one program at a time rather than evaluating their full portfolio of place-based economic development programs. One reason for this is that responsibility for place-based programs is spread across the various levels of governments and multiple agencies.

To ensure that they have more comprehensive information, state policymakers should task a single agency with conducting regular analyses of their state’s targeting strategies. In states that already have processes for evaluating economic development tax incentives, such as Maryland—where DLS evaluates tax credits on a regular schedule—lawmakers can require that those studies include examinations of targeting provisions.³⁰

Policymakers can also act to ensure that analysts studying the program have the data to reach meaningful conclusions. The lack of such data has often been a significant barrier to effective assessments. Information—such as what types of locations are eligible, where investments are being made under the program, which businesses are receiving incentives, and what economic activities those businesses engage in—has frequently been scarce and sometimes virtually nonexistent. For instance, after Congress created opportunity zones in 2017, researchers and even government officials lacked data about the program’s performance. As one journalist put it, “State and local leaders, unable to track projects any other way, are relying on self-reporting, gossip and local news.”³¹ Although tax forms introduced in 2019 included some reporting requirements, a range of stakeholders—including members of Congress from both parties, critics of the program, and the organization that originally conceived the idea—continue to call for additional reporting rules.³²

Beyond programmatic data, states rely on economic, demographic, and social indicators to identify and examine the areas where programs are offered and in which of those places businesses and developers are actually using the incentives—and to determine whether those places are distressed. Unlike program-specific information, much data of this type is widely available from sources such as the U.S. Census Bureau. However, researchers and policymakers can still face challenges finding data that is reliable and up-to-date, especially if they are focusing on small areas such as neighborhoods or census tracts.³³

When governments or other stakeholders lack the data to answer important questions about local areas, they can collect new information. In this regard, Detroit’s 2013-14 effort to track blight provides a particularly ambitious example. Guided and supported by a mix of nonprofit organizations, government officials, private funders, researchers, and local businesses, the initiative deployed about 150 local residents to assess and photograph the city’s 380,000 parcels and look for fire damage, broken windows, litter-filled yards, and other signs of troubled properties.³⁴ The research helped to identify neighborhoods that were at a tipping point between stabilization and greater blight and abandonment, and, acting on the findings, a city task force recommended specific neighborhoods to receive property remediation dollars.³⁵

Regularly update the set of eligible locations

In 2008, the transformation of Washington, D.C.’s NoMa neighborhood was national news. The New York Times declared NoMa, short for “north of Massachusetts Avenue,” to be “Washington's newest and hottest commercial neighborhood, with residential development expected to follow.” The construction of a subway station, the Times reported, had helped set off a building boom in a neighborhood that had “formerly held mainly parking lots, warehouses and light industry.”³⁶ Federal government agencies were moving to NoMa—just blocks from the U.S. Capitol—and National Public Radio had announced plans to move its headquarters there.³⁷

However, when the Great Recession slowed the neighborhood’s development, D.C. Council members became concerned that the transformation would stall without an extra boost and in 2009 authorized residential property tax abatements in NoMa.³⁸ A decade later, by almost any measure, NoMa is thriving. Roughly three-quarters of residents are college graduates, and the median household income tops $100,000.³⁹ But a decade after the council enacted them, the property tax abatements continued to cost the city $5 million a year.⁴⁰ As the NoMa abatements demonstrate, place-based programs may continue to target formerly distressed areas long after they have turned the economic corner, directing scarce resources to well-to-do locations at the expense of development in areas that continue to struggle. To help avoid these outcomes, policymakers should regularly update their lists of eligible locations.

Some programs, such as many job creation and investment tax credits, include requirements to routinely revise targeting. Kentucky, for example, annually updates the list of counties where businesses can receive more generous incentives under the Kentucky Business Investment Program (KBI)—one of the state’s largest economic development programs—using a formula that accounts for factors such as unemployment rates and educational attainment.⁴¹ State officials report that the updates are valuable because they allow counties to qualify promptly when they face serious economic setbacks, such as the departure of a major employer.⁴² And, although poor counties usually remain poor, conditions do occasionally improve to the point where a county no longer qualifies for enhanced KBI incentives: The state has removed one county from the list in the past three years.⁴³

However, KBI and other job creation incentives are the exception; most place-based programs, including enterprise zones and TIF, revise their lists of eligible locations far less often. Areas often retain enterprise zone status for 10 years or more before officials revisit the zones, and TIF designations can remain in place for 20 years or longer. Other programs do not include any mechanism for updating eligible areas. Opportunity zones are one such case, and in this program the designations simply expire after a decade and are not replaced.⁴⁴

The lack of frequent revisions for TIF, enterprise zones, and opportunity zones is particularly worrisome because these programs target smaller geographic areas, such as neighborhoods or census tracts, where conditions can change rapidly. For instance, many of the census tracts that governors selected as opportunity zones—although poor in comparison to much of the country—already were enjoying substantial economic gains before the program launched.⁴⁵ If those improvements continue in the years ahead, billions of dollars in taxpayer-subsidized investment may be directed to areas that have already experienced a turnaround rather than the struggling places that policymakers said the program was intended to help. In response to this concern, some members of Congress are discussing removing high-income zones from the program before the original 10-year expiration date and allowing states to nominate replacements.⁴⁶

Tailor economic development strategies to local needs

North Carolina uses a ranking system to determine localities’ eligibility for place-based initiatives, grouping counties into three tiers based on their level of distress. As of 2015, the state used those classifications to target 15 programs, ranging from CDBG and LIHTC to a state spay-and-neuter program.⁴⁷ However, an evaluation by legislative staff found that the system did not effectively direct resources to the counties most in need: Only 24% of the $71.4 million the state committed using the system went to the most distressed counties.⁴⁸ (See Figure 1.) A primary reason for that outcome, the study noted, was that many counties lacked the prerequisites for business investment, such as infrastructure and a skilled workforce.⁴⁹

As North Carolina’s experience shows, even generous incentives may not be enough to persuade businesses to locate in places that lack the workers, broadband internet service, transportation networks, or other resources they require. Those shortcomings typically must be overcome before a city, county, or neighborhood will be attractive to private investment. Additionally, some place-based initiatives require local governments to apply for funding or provide staff to administer the programs— requirements that can present significant barriers to participation, especially for poor, rural municipalities.⁵⁰

Some of the most successful place-based programs have included funding to address such obstacles rather than simply offering financial incentives to businesses, developers, and investors. For example, the Tennessee Valley Authority (TVA) brought electricity and infrastructure to one of the most impoverished parts of the country during the Great Depression, improvements that, in turn, attracted better jobs and substantially increased wages in the region, producing benefits that lasted for decades.⁵¹ Likewise, Empowerment Zones, a federal version of enterprise zones that Congress created in 1993, provided each zone $100 million in block grants for purposes such as worker training. Research shows that the program increased employment and decreased poverty in the first designated zones while leading to only modest rent increases.⁵²

Recent economic research points to a range of strategies that states can use to replicate these encouraging results, including workforce training, infrastructure investments, customized business services, and streamlined land-use regulations.⁵³ But even when governments use these approaches, they rarely target them specifically to distressed areas—the CDBG program is one exception—or commit comparable financial resources to them as to incentives.⁵⁴

Policymakers also should consider which programs are a good fit for the size of the areas they are trying to help. Generally, job-creation and business-attraction programs are better suited for larger places, such as metropolitan areas.⁵⁵ When governments target job creation programs by neighborhood, those efforts often face practical challenges, such as zoning rules that preclude commercial development in residential neighborhoods or worker commuting that prevents benefits from being realized within the neighborhood where the jobs are created. For example, a 2020 evaluation from Colorado found that in urban enterprise zones, most workers hired by participating businesses—in one case, 86%—did not live in the zones.⁵⁶

Create job opportunities for low-income residents

Today’s place-based programs emerged in the 1970s and 1980s, but they were not the United States’ first foray into geographically targeted economic development. Although some early place-based programs, such as the TVA, achieved notable successes, others are remembered mostly as cautionary tales—perhaps none more so than urban renewal.

Created by Congress in 1949, urban renewal provided federal funding for cities to demolish “slums” to make way for new development. However, as a result of the program, hundreds of thousands of residents in areas targeted for redevelopment were displaced from their homes via eminent domain and insufficiently compensated—with these harms disproportionally affecting Black families.⁵⁷ For example, in Lubbock, Texas, a city where only 8% of the population was people of color, the program displaced approximately 1,281 households by the late 1960s, none of them White.⁵⁸ Across the country, many racial and ethnic minority neighborhoods were simply bulldozed off the map.⁵⁹

The history of urban renewal is a reminder that place-based programs must do more than improve the economy or physical structures in the places they target; to be truly successful, they must benefit the residents of those areas. Congress replaced urban renewal with CDBG in 1974, but the new generation of place-based programs has continued to struggle to serve local populations.

States sometimes create requirements designed to ensure that target populations benefit, but they don’t always succeed. For example, California in 2013 created a tax credit for businesses located in distressed areas and required participating companies to hire from groups such as people who were previously convicted of felonies and the long-term unemployed. However, the program has been underutilized. Businesses claimed $2.5 million in credits in 2017, just a small fraction of the $172 million in claims that state officials projected for that year when they conceived the program.⁶⁰ Reviews by the state have shown that the incentives are too small and the administrative hurdles too great to persuade companies to hire from target groups.⁶¹

And although governments could try to address this problem by simply making incentives more generous, doing so may not be affordable or cost-effective. Instead, they may have more success embracing strategies to ensure that prospective employees have in-demand skills. “First-source” hiring policies, for example, require that certain businesses or real estate developments consider applicants from target groups but also allow those companies to look elsewhere if they cannot find qualified candidates. Some research indicates that first-source requirements tend to be most effective when government officials take an active role in identifying candidates and connect the policies to workforce training initiatives.⁶²

For instance, San Francisco prescreens candidates, sets up interviews, and connects workforce training graduates with employers via an online portal.⁶³ This approach may allow businesses to more easily fill vacancies, while also helping target populations find jobs. However, the value of first-source systems depends on governments’ ability to effectively administer and implement the policies—by training a pool of qualified candidates, identifying companies or real estate projects that need to participate, and tracking firms’ compliance.⁶⁴

Another option is to direct place-based incentives to industries that are most likely to offer good jobs to the residents of distressed areas. Identifying the right industries requires careful evaluation, however. Creating jobs that require advanced degrees may do little in areas where few residents have college educations or even high school diplomas. But subsidizing many industries that hire less-educated workers—such as hospitality and food service—also may not be the best option, given the low wages and limited benefits they offer. A 2018 Brookings Institution study showed that industries that require specialized skills are more likely to provide jobs that offer “stable middle-class wages and benefits” to people who lack bachelor’s degrees.⁶⁵ Beyond traditional sources of working-class jobs such as manufacturing and construction, the report found that industries such as engineering and information technology also offer good jobs for people without bachelor’s degrees.⁶⁶

In most instances, policymakers have not prioritized better job opportunities for residents when selecting industries to receive place-based program incentives. And many major place-based programs are not directed to specific industries in any way. For instance, states typically make job creation tax credits available to a range of businesses so long as they sell their products nationally or internationally and thereby bring in dollars from out of state. And many state enterprise zone programs do not have even that limitation. A study of Florida’s enterprise zone program found that it achieved weaker results than other incentives in part because it did not include any industry targeting. The program was so broad that even companies that already had to locate in the state because their business depended on Florida’s natural resources or economy could qualify.⁶⁷

Regardless of which strategies governments adopt, they should measure the results of their efforts. Unfortunately, although states and localities have not consistently assessed whether place-based programs are aiding the intended locations, they have done even less to collect and analyze data on whether the programs are serving residents. However, a few states, including Colorado and Maryland, have examined certain programs to determine who benefits, and some cities that have prioritized low-income residents and people of color in their place-based initiatives, such as Portland, Oregon, are starting the hard work of gathering better data.⁶⁸

Conclusion

Local, state, and federal policymakers have committed billions of dollars to economic development programs designed to strengthen distressed areas. Too often, however, these programs have been poorly targeted so that benefits accrue to wealthier communities instead.

And although all levels of government have a role to play in place-based economic development, state policymakers are uniquely empowered to start to solve this problem because states have primary responsibility for determining where programs are available. To do so, however, government officials first need better data and analysis. Clear information about where place-based programs are used and who benefits from them is essential to efforts to regularly update and reform the programs.

But place-based programs also have deeper problems than inadequate geographic targeting. Frequently, the strategies they use do not address many of the obstacles that can prevent struggling areas from attracting investment or residents from filling available jobs. Ultimately, to effectively fight concentrated unemployment and poverty, states must undertake a broad reconsideration of the role and nature of place-based financial incentives that prioritizes expanding economic opportunity for families that live in struggling locations.

Appendix: Descriptions of major place-based programs

Community Development Block Grant

The U.S. Department of Housing and Urban Development (HUD) offers billions of dollars to city and county governments each year through the Community Development Block Grant program. Local governments must use the program in service of three primary goals: fighting blight, helping low- and moderate-income people, and meeting urgent public health and welfare needs in the community. However, those goals are general enough that localities can use CDBG funds for a wide range of purposes, such as helping homeowners renovate their homes, constructing homeless shelters, or offering loans to businesses.

HUD distributes CDBG funds in two tranches. About 70% of total program spending goes directly to larger cities and urban counties. For the “entitlement communities,” so called because they automatically qualify for the program, funds are allocated based on formulas that assess “community need” according to indicators such as poverty rate, population size and growth rate, and housing overcrowding.

The remaining 30% of CDBG spending is directed to state governments, which serve as intermediaries, distributing funds to smaller cities and counties that do not automatically qualify. The federal government gives states broad discretion to decide which localities will receive funding and for what purposes. States generally use competitive application processes, awarding CDBG funds to the highest-scoring submissions from local governments.

For more information, see:

• Congressional Research Service, “Community Development Block Grants and Related Programs: A Primer,” updated April 30, 2014, https://crsreports.congress.gov/product/pdf/R/R43520/3.
• Brett Theodos, Christina Plerhoples Stacy, and Helen Ho, “Taking Stock of the Community Development Block Grant,” Urban Institute (2017), https://www.urban.org/sites/default/files/publication/89551/cdbg_ brief_finalized_1.pdf.
• Michael J. Rich, “Community Development Block Grants at 40: Time for a Makeover,” Housing Policy Debate 24, no. 1 (2014): 46-90. https://www.tandfonline.com/doi/full/10.1080/10511482.2013.865656

Enterprise zones

Most states have created programs that offer tax breaks to companies that locate or expand in designated areas. How these “enterprise zone” programs function differs across states, but many follow roughly the same framework.

Generally, state laws set standards designed to limit the zones to distressed areas. These standards frequently involve quantitative criteria, including unemployment and poverty rates, per capita income, and population growth and sometimes more subjective measures, such as “general distress.” Often, local governments must submit applications to have areas that meet the standards designated as enterprise zones. State officials review the applications and may have discretion to choose which applications to approve. The size of each zone varies widely from state to state, with state laws often stipulating a minimum or maximum.

Once an area is designated as an enterprise zone, businesses that locate or hire in the zone can receive breaks on various state and local taxes, often including income, property, and sales taxes. These benefits may be limited to businesses in specific industries, and the size of the breaks is often tied to companies’ activities. For instance, a company may receive a tax credit for each worker it hires. Some programs offer extra benefits to companies that hire from specific populations, including zone residents or groups that struggle to gain employment, such as people who have previously been incarcerated.

State laws usually dictate that an area’s enterprise zone status expires after a set number of years, but local officials often have the option to apply for extensions.

For more information, see:

• Don Hirasuna and Joel Michael, “Enterprise Zones: A Review of the Economic Theory and Empirical Evidence,” Minnesota House of Representatives Research Department (2005), https://www.house.leg.state.mn.us/hrd/pubs/entzones.pdf.
• Alan H. Peters and Peter S. Fisher, “State Enterprise Zone Programs: Have They Worked?” W.E. Upjohn Institute for Employment Research (2002), https://research.upjohn.org/cgi/viewcontent. cgi?article=1057&context=up_press.
• Daphne A. Kenyon, Adam H. Langley, and Bethany P. Paquin, “Rethinking Property Tax Incentives for Business,” Lincoln Institute of Land Policy (2012), https://www.lincolninst.edu/publications/policy-focusreports/rethinking-property-tax-incentives-business.

Job creation and investment tax credits

Most states offer tax credits to select businesses in exchange for creating jobs or making capital investments such as building a new facility. The details of how the credits work vary from state to state, but many of the programs share some commonalities. They often involve multiyear performance agreements between companies and the state, with the credits’ value linked to the number of jobs added or the cost of capital investments made. Generally, the programs seek to encourage businesses to create high-quality jobs. For example, businesses may receive larger credits for creating higher-wage jobs, or they may not receive credits for jobs that pay less than a certain amount.

States often make these programs available only to companies that sell their products nationally or internationally, such as manufacturers, or only for activities that can help the state economy to grow, such as locating a corporate headquarters.

Often, businesses can receive tax credits for investments anywhere in the state, but many programs include provisions to try to direct more activity to struggling places. This geographic targeting takes various forms. Some programs relax eligibility requirements for firms that locate in distressed areas by, for instance, allowing businesses to create fewer jobs than they would have to elsewhere. Others offer more generous benefits in struggling areas, such as increasing the credits that companies receive for each job created. Other job creation and investment tax credits do not focus on distressed areas and have no geographic targeting provisions. Instead, these incentives seek to encourage economic development statewide.

For more information, see:

• Luke Martel, “Jump-Starting Jobs,” National Conference of State Legislatures, January 2011, https://www.ncsl.org/research/fiscal-policy/jump-starting-jobs.aspx.
• Maryland Department of Legislative Services Office of Policy Analysis, “Evaluation of the Job Creation Tax Credit” (2016), http://dls.maryland.gov/pubs/prod/TaxFiscalPlan/Draft-Evaluation-of-the-Job-CreationTax-Credit.pdf.
• Robert S. Chirinko and Daniel J. Wilson, “Job Creation Tax Credits, Fiscal Foresight, and Job Growth: Evidence From U.S. States,” (working paper, Federal Reserve Bank of San Francisco, 2016), http://www.frbsf.org/economic-research/files/wp10-25bk.pdf.

Low-income housing tax credits

The federal low-income housing tax credit offers incentives to developers to build or renovate affordable rental housing. Credits are available nationwide to properties that meet affordability standards based on the rent charged and the tenants’ income levels. The federal government provides each state with a formula-determined amount of money, which state housing agencies then allocate to developers according to their own rules, typically via a competitive selection process. Some properties, such as those funded by government-issued bonds, automatically qualify for less generous credits that do not require state allocations.

The program offers enhanced benefits in two types of geographic areas: Qualified Census Tracts (QCTs) and Difficult Development Areas (DDAs). QCTs are census tracts that have high poverty rates or many residents with incomes below the regional median, and DDAs are places where construction costs are high relative to median incomes, which may make housing expensive for many residents. In non-metropolitan areas, DDAs typically encompass entire counties, while in metropolitan areas their borders follow the lines of smaller geographic designations, known as ZIP code tabulation areas. The federal government defines QCTs and DDAs, but states have discretion to determine the extent to which they prioritize those areas when allocating credits. States can also supplement the QCTs and DDAs with additional geographic targeting, such as offering preference to developers who build in areas with high-quality schools.

More than a dozen states have also created their own affordable housing tax credits. These programs generally piggyback on the federal credit, offering additional state tax breaks to projects that qualify for the federal program.

For more information, see:

• Corianne Payton Scally, Amanda Gold, and Nicole DuBois, “The Low-Income Housing Tax Credit: How It Works and Who It Serves,” Urban Institute (2018), https://www.urban.org/sites/default/files/publication/98758/lithc_how_it_works_and_who_it_serves_final_2.pdf.
• Kirk McClure, “What Should Be the Future of the Low-Income Housing Tax Credit Program?” Housing Policy Debate 29, no 1 (2019): 65-81, https://doi.org/10.1080/10511482.2018.1469526.
• Ingrid Gould Ellen and Keren Mertens Horn, “Points for Place: Can State Governments Shape Siting Patterns of Low-Income Housing Tax Credit Developments?” Housing Policy Debate 28: no 5 (2018): 727-745, https://doi.org/10.1080/10511482.2018.1443487.

New markets tax credits

Congress in 2000 created the new markets tax credit (NMTC) to encourage business and real estate investments in struggling census tracts. Each year, the Community Development Financial Institutions Fund, an agency within the U.S. Department of the Treasury, uses a competitive application process to allocate tax credits to Community Development Entities (CDEs), which are corporations and partnerships formed specifically to take advantage of the program. The CDEs then sell the credits to investors in exchange for dollars that the CDEs use to invest in businesses and nonprofits in qualifying tracts. Federal lawmakers conceived the CDE system as a way to allow market forces to dictate which investments the program would support.

Unlike several other federal place-based initiatives, state governments play no role in targeting the NMTC. Instead, the program uses quantitative measures of distress, such as high poverty or low family income, to identify eligible tracts. The law also includes provisions to allow more rural areas to qualify. For instance, tracts with low populations enjoy more permissive eligibility standards. Finally, wealthier tracts can qualify if CDEs direct their investments to businesses and nonprofits that serve or employ low-income individuals or groups.

The combination of these various standards potentially allows NMTC projects to locate in much of the country. However, in assessing applications for credits, federal officials promote geographic targeting by awarding bonus points to CDEs that plan to invest in severely distressed tracts, such as those with poverty rates above 30%.

About a dozen states have established their own new markets incentives, and many link their programs to the federal initiative by, for instance, offering credits to organizations that qualify as CDEs under federal law.

For more information, see:

• Congressional Research Service, “New Markets Tax Credit: An Introduction,” updated June 27, 2019, https://fas.org/sgp/crs/misc/RL34402.pdf.
• Martin D. Abravanel et al., “New Markets Tax Credit (NMTC) Program Evaluation: Final Report,” Urban Institute (2013), https://www.urban.org/sites/default/files/publication/24211/412958-new-markets-tax-credit-nmtc-program-evaluation.pdf.
• Tax Foundation, “An Overview of the New Markets Tax Credit,” July 8, 2019, https://taxfoundation.org/new-markets-tax-credit-nmtc/.

Opportunity zones

Congress created the opportunity zones program as part of the Tax Cuts and Jobs Act, the major 2017 federal tax overhaul. Under the program, individuals and businesses can receive breaks on capital gains taxes if they invest in census tracts that states designated as opportunity zones. To receive these benefits, investors must place profits from the sale of stocks or other capital assets in “qualified opportunity funds,” a new category of investment vehicle created as part of the program, which, in turn, can invest those resources in almost any business or real estate project in one of the zones.

The federal law provided a starting point for determining which census tracts could qualify but allowed state and territorial governors to make the final decisions. Under the law, governors could select tracts with high poverty rates or low median incomes as well as some areas that were contiguous with those tracts. Governors had until March 2018 to designate up to 25% of tracts that met the eligibility standards as zones (or up to 25 tracts in states with fewer than 100 qualified tracts). To make these decisions, states often solicited input from businesses and business groups, the public, and local government officials, and many gathered and analyzed data on the tracts’ level of distress, appeal to investors, or both.

For more information, see:

• Congressional Research Service, “Tax Incentives for Opportunity Zones,” updated Dec. 7, 2020, https://fas.org/sgp/crs/misc/R45152.pdf.
• Hilary Gelfond and Adam Looney, “Learning From Opportunity Zones: How to Improve Place-Based Policies,” Brookings Institution (2018), https://www.brookings.edu/wpcontent/uploads/2018/10/Looney_ Opportunity-Zones_final.pdf.
• Brett Theodos, Brady Meixell, and Carl Hedman, “Did States Maximize Their Opportunity Zone Selections?” Urban Institute (2018), https://www.urban.org/sites/default/files/publication/98445/did_states_ maximize_their_opportunity_zone_selections_7.pdf.

Tax increment financing

One of the primary development tools used by municipalities is tax increment financing. TIF programs allow local governments to use revenue generated in designated geographic areas—usually from property taxes, but sometimes sales or other taxes—to pay for development costs in those areas.

Local governments designate areas within jurisdictions—ranging from individual real estate developments to a few blocks or even an entire neighborhood—as TIF districts, with eligibility determined by state statute. Most states require that the TIF area be “blighted,” but they differ on how that is measured. Many state laws define blight based at least partially on qualitative criteria such as the presence of dilapidated buildings.

After a local government has designated an area as a TIF district, the district’s tax revenue continues to flow to government coffers for general use, as it usually would, until it reaches the level of the area’s pre-TIF revenue. But once that threshold is reached, revenue in excess of that figure is directed for use within the district, typically for development costs and public improvements. For example, if the municipality collected $10 million a year in property tax revenue from an area before that area became a TIF district, then after it becomes a district, the first $10 million in property tax revenue collected from the area each year continues to be allocated for general use, but any additional revenue is reinvested back into the district. Depending on state law, areas may retain their TIF status for a set number of years or until they collect a predetermined amount of revenue.

In many cases, governments borrow money against future TIF revenue so they can start making improvements in the district promptly after its designation as a TIF district. These loans are taken with the expectation that those initial improvements will foster further development in the district, which in turn should lead to the increased revenue needed to pay off the borrowing costs.

For more information, see:

• David Merriman, “Improving Tax Increment Financing (TIF) for Economic Development,” Lincoln Institute of Land Policy (2018), https://www.lincolninst.edu/publications/policy-focus-reports/improving-tax-increment-financing-tif-economic-development.
• Richard Briffault, "The Most Popular Tool: Tax Increment Financing and the Political Economy of Local Government," The University of Chicago Law Review 77, no. 1 (2010): 65-95, https://www.jstor.org/stable/40663026.
• Robert T. Greenbaum and Jim Landers, “The Tiff Over TIF: A Review of the Literature Examining the Effectiveness of the Tax Increment Financing,” National Tax Journal 67, no. 3 (2014): 655-674, http://www.ntanet.org/NTJ/67/3/ntj-v67n03p655-674-tiff-tif-tax-increment-financing.html.

Endnotes

1. A. von Hoffman, “The Past, Present, and Future of Community Development in the United States,” in Investing in What Works for America’s Communities (Federal Reserve Bank of San Francisco, 2012), https://www.frbsf.org/community-development/files/vonhoffman.pdf.
2. D.A. Kenyon, A.H. Langley, and B.P. Paquin, “Rethinking Property Tax Incentives for Business” (Lincoln Institute of Land Policy, 2012), 5, https://www.lincolninst.edu/publications/policy-focus-reports/rethinking-property-tax-incentives-business; D. Hirasuna and J. Michael, “Enterprise Zones: A Review of the Economic Theory and Empirical Evidence” (Minnesota House of Representatives Research Department, 2005), https://www.leg.state.mn.us/docs/2005/other/050167.pdf.
3. T.J. Bartik, “A New Panel Database on Business Incentives for Economic Development Offered by State and Local Governments in the United States” (W.E. Upjohn Institute for Employment Research, 2017), 89, http://research.upjohn.org/cgi/viewcontent.cgi?article=1228&context=reports.
4. R. Briffault, “The Most Popular Tool: Tax Increment Financing and the Political Economy of Local Government,” University of Chicago Law Review 77, no. 1 (2010): 65, https://chicagounbound.uchicago.edu/uclrev/vol77/iss1/4/.
5. I.G. Ellen, K.M. Horn, and K.M. O’Regan, “Poverty Concentration and the Low-Income Housing Tax Credit Program: Effects of Siting and Tenant Composition,” Journal of Housing Economics 34 (2016): 49-59, https://www.prrac.org/pdf/EllenHornORegan_JHE2016_LIHTCPovConc.pdf; E. Stamm and T. LaJoie, “An Overview of the Low-Income Housing Tax Credit” (Tax Foundation, 2020), https://taxfoundation.org/low-income-housing-tax-credit-lihtc/.
6. B. Theodos, C.P. Stacy, and H. Ho, “Taking Stock of the Community Development Block Grant” (Urban Institute, 2017), https://www.urban.org/sites/default/files/publication/89551/cdbg_brief_finalized_1.pdf; S. Malanga, “Anti-Poverty Community Development Block Grants Are a Total Failure,” Investor’s Business Daily, Nov. 30, 2017, https://www.manhattan-institute.org/html/anti-poverty-community-development-block-grants-are-total-failure-10801.html.
7. J. Manchester, “Mnuchin Predicts $100B in Cap Investment From New Opportunity Zones,” The Hill, Sept. 28, 2018, https://thehill.com/hilltv/rising/408980-mnuchin-predicts-100b-in-cap-investment-from-new-opportunity-zones.
8. A. Talanker, K. Davis, and G. LeRoy, “Straying From Good Intentions: How States Are Weakening Enterprise Zone and Tax Increment Financing Programs” (Good Jobs First, 2003), https://www.goodjobsfirst.org/publications/straying-good-intentions-how-states-are-weakening-enterprise-zone-and-tax-increment-fin; Theodos, Stacy, and Ho, “Taking Stock of the Community Development Block Grant,” 5-6.
9. Colorado Office of the State Auditor, “Enterprise Zones Tax Expenditures” (2020), 49, https://leg.colorado.gov/sites/default/files/2020-te9_enterprise_zones_tax_expenditures_0.pdf; Maryland Department of Legislative Services Office of Policy Analysis, “Evaluation of the Enterprise Zone Tax Credit” (2013), 34, 79, http://www.dat.state.md.us/Documents/DLS_EvaluationEnterpriseZone_Taxcredit.pdf; Office of the Legislative Auditor State of Minnesota, “Evaluation Report: Jobz Program” (2008), 31-46, https://www.auditor.leg.state.mn.us/ped/pedrep/jobz.pdf; Office of Program Evaluation & Government Accountability of the Maine State Legislature, “Tax Expenditure Review Final Report: Pine Tree Development Zones” (2017), 28, https://legislature.maine.gov/doc/1809.
10. B. Theodos, B. Meixell, and C. Hedman, “Did States Maximize Their Opportunity Zone Selections?” (Urban Institute, 2018), https://www.urban.org/research/publication/did-states-maximize-their-opportunity-zone-selections; J. Elliott, J. Ernsthausen, and K. Edwards, “A Trump Tax Break to Help the Poor Went to a Rich GOP Donor’s Superyacht Marina,” ProPublica, Nov. 14, 2019, https://www.propublica.org/article/superyacht-marina-west-palm-beach-opportunity-zone-trump-tax-break-to-help-the-poor-went-to-a-rich-gop-donor; E. Lipton and J. Drucker, “Symbol of ’80s Greed Stands to Profit from Trump Tax Break for Poor Areas,” The New York Times, Oct. 26, 2019, https://www.nytimes.com/2019/10/26/business/michael-milken-trump-opportunity-zones.html; J. Drucker and E. Lipton, “How a Trump Tax Break to Help Poor Communities Became a Windfall for the Rich,” The New York Times, Aug. 31, 2019, https://www.nytimes.com/2019/08/31/business/tax-opportunity-zones.html; H. Gelfond and A. Looney, “Learning From Opportunity Zones: How to Improve Place-Based Policies” (The Brookings Institution, 2018), https://www.brookings.edu/wp-content/uploads/2018/10/Looney_Opportunity-Zones_final.pdf.
11. Talanker, Davis, and LeRoy, “Straying from Good Intentions.”
12. E. Kneebone and N. Holmes, “U.S. Concentrated Poverty in the Wake of the Great Recession” (The Brookings Institution, 2016), https://www.brookings.edu/research/u-s-concentrated-poverty-in-the-wake-of-the-great-recession/.
13. Ibid.
14. R. Briffault, “The Most Popular Tool: Tax Increment Financing and the Political Economy of Local Government,” The University of Chicago Law Review 77, no. 1 (2010): 65-95, https://www.jstor.org/stable/40663026.
15. J. Chase and D. Ecker, “How City Power Players Diverted Millions in Blight-Fighting Tif Cash to Navy Pier,” Crain’s Chicago Business, 2017, https://www.chicagobusiness.com/article/20170721/ISSUE01/170729970/how-chicago-power-players-diverted-tif-funds-to-navy-pier.
16. Office of Cook County Clerk Karen A. Yarbrough, “Cook County TIFs to Generate Over $1.3 Billion: TIF Revenue up 11.5% Compared to Last Year” (2019), https://www.cookcountyclerk.com/publications/2019-tif-release-executive-summary.
17. Illinois 65 ILCS 5 (1977), http://www.ilga.gov/legislation/ilcs/ilcs4.asp?DocName=006500050HArt%2E+11+Div%2E+74%2E4&ActID=802&ChapterID=14&SeqStart=213100000&SeqEnd=215400000.
18. C. Gordon, “Blighting the Way: Urban Renewal, Economic Development, and the Elusive Definition of Blight,” Fordham Urban Law Journal 31, no. 2 (2004): 305-37.
19. Gelfond and Looney, “Learning From Opportunity Zones,” 8-9; University of Southern California, “Financial Aid at USC,” accessed Dec. 3, 2020, https://admission.usc.edu/learn/cost-financial-aid/.
20. New Jersey Department of Community Affairs Office of Policy and Regulatory Affairs, “Measuring Distress in New Jersey: The 2017 Municipal Revitalization Index” (2017), 11-14, https://www.nj.gov/dca/home/NJ_MRI_Report.pdf.
21. Ibid., 14-16.
22. Ibid., 28.
23. Ibid., 32-33.
24. C. Wheeler (Chief Data Officer, State of New Jersey Department of Community Affairs), interview with The Pew Charitable Trusts, July 31, 2019.
25. Maryland Department of Legislative Services Office of Policy Analysis, “Evaluation of the Sustainable Communities Tax Credit” (2016), 82-84, http://dls.maryland.gov/pubs/prod/TaxFiscalPlan/Evaluation-of-the-Sustainable-Communities-Tax-Credit.pdf.
26. Ibid., 33-34.
27. Ibid., 58-60.
28. Ibid., 58.
29. Heritage Structure Rehabilitation Tax Credit—Alteration and Extension, S.B. 0759, Maryland General Assembly (2016), http://mgaleg.maryland.gov/mgawebsite/legislation/details/sb0759?ys=2016rs.
30. The Pew Charitable Trusts, “Maryland Tax Incentive Evaluation Ratings” (2017), https://www.pewtrusts.org/en/research-and-analysis/fact-sheets/2017/05/state-tax-incentive-evaluation-ratings-maryland.
31. S. Quinton, “Luxury Apartments Get the Tax Breaks Meant to Boost Low-Income Areas,” Stateline, Sept. 25, 2019, https://www.pewtrusts.org/en/research-and-analysis/blogs/stateline/2019/09/25/luxury-apartments-get-the-tax-breaks-meant-to-boost-low-income-areas.
32. E. Lipton and J. Drucker, “Lawmakers Increase Criticism of ‘Opportunity Zone’ Tax Break,” The New York Times, Nov. 6, 2019, https://www.nytimes.com/2019/11/06/business/opportunity-zones-congress-criticism.html; Economic Innovation Group, “Unpacking the Impact Act,” accessed May 27, 2020, https://eig.org/news/unpacking-the-impact-act.
33. Center for Community Progress, “Neighborhoods by Numbers: An Introduction to Finding and Using Small Area Data” (2017), 15-16, https://www.communityprogress.net/download-neighborhoods-by-numbers--2017--pages-552.php.
34. Detroit Blight Removal Task Force, “Every Neighborhood Has a Future ... and It Doesn’t Include Blight” (2014), 3943, https://www.documentcloud.org/documents/1173946-detroit-blight-removal-task-force-plan-may-2014.html?embed=true&responsive=false&sidebar=true.
35. Ibid., 92-94.
36. E.L. Meyer, “In Washington’s NoMa, a Trendy Name and High Hopes,” The New York Times, Sept. 23, 2008, https://www.nytimes.com/2008/09/24/business/24noma.html.
37. Ibid.
38. District of Columbia Code of the District of Columbia, §§ 47-859.01 through 47-859.05 (2009), https://code.dccouncil.us/dc/council/code/sections/47-859.01.html; Council of the District of Columbia Committee on Finance and Revenue, “Report on Bill 18-18, the ‘NoMa Residential Development Tax Abatement Act of 2009,’” (2009).
39. Washington D.C. Economic Partnership, “Neighborhood Profiles” (2020), https://14x1z243z988315lc25fjqzl-wpengine.netdna-ssl.com/wp-content/uploads/2017/10/2020-WDCEP-NP-final.pdf.
40. Government of the District of Columbia Office of Revenue Analysis, “District of Columbia Tax Expenditure Report” (2018), 257, https://cfo.dc.gov/sites/default/files/dc/sites/ocfo/publication/attachments/2017%20Tax%20Expenditure%20Report.pdf.
41. Kentucky Cabinet for Economic Development, “Just the Facts: Kentucky Business Investment Program” (2020), http://www.thinkkentucky.com/kyedc/pdfs/KBIFactSheet.pdf.
42. K. Smith and J. Mazurak (Commissioner of the Department for Financial Services, Executive Director of the Office of Marketing and Public Affairs, Kentucky Cabinet for Economic Development), interview with The Pew Charitable Trusts, Sept. 4, 2019.
43. Kentucky Cabinet for Economic Development, “Just the Facts.”
44. U.S. Department of the Treasury, “Treasury Releases Proposed Regulations on Opportunity Zones Designed to Incentivize Investment in American Communities,” news release, Oct. 19, 2018, https://home.treasury.gov/news/press-releases/sm530.
45. Gelfond and Looney, “Learning from Opportunity Zones,” 6-7.
46. United States Senate Committee on Finance, “Opportunity Zone Reporting & Reform Act Detailed Summary” (2019), https://www.finance.senate.gov/download/opportunity-zone-reporting-and-reform-act-of-2019-summary.
47. North Carolina General Assembly Program Evaluation Division, “North Carolina Should Discontinue the Economic Development Tiers System and Reexamine Strategies to Assist Communities With Chronic Economic Distress” (2015), 10, https://www.ncleg.net/PED/Reports/documents/EDTiers/ED_Tiers_Report.pdf.
48. Ibid., 11.
49. Ibid., 23.
50. S. Nienow (Principal Program Evaluator, North Carolina General Assembly), interview with The Pew Charitable Trusts, Oct. 12, 2019.
51. P. Kline and E. Moretti, “Local Economic Development, Agglomeration Economies, and the Big Push: 100 Years of Evidence From the Tennessee Valley Authority,” The Quarterly Journal of Economics 129, no. 1 (2014): 275-331, https://www.nber.org/papers/w19293.
52. M. Busso and P. Kline, “Do Local Economic Development Programs Work? Evidence From the Federal Empowerment Zone Program” (working paper, 2008), http://economics.yale.edu/sites/default/files/files/Working-Papers/wp000/ddp0036.pdf; M. Busso, J. Gregory, and P. Kline, “Assessing the Incidence and Efficiency of a Prominent Place Based Policy” (working paper, National Bureau of Economic Research, 2010), http://www.nber.org/papers/w16096.
53. T. Bartik, “Should Place-Based Jobs Policies Be Used to Help Distressed Communities?” (W.E. Upjohn Institute for Employment Research, 2019), 21-25, https://research.upjohn.org/cgi/viewcontent.cgi?article=1326&context=up_workingpapers.
54. A.K. Chatterji, “The Main Street Fund: Investing in an Entrepreneurial Economy” (The Hamilton Project, 2018), 5-6, https://www.brookings.edu/wp-content/uploads/2018/06/ES_THP_20180611_Chatterji.pdf; Bartik, “Should Place-Based Jobs Policies Be Used to Help Distressed Communities?” 57.
55. T.J. Bartik, “Making Sense of Incentives: Taming Business Incentives to Promote Prosperity” (W.E. Upjohn Institute for Employment Research, 2019), 2, https://www.upjohn.org/research-highlights/making-sense-incentives-taming-business-incentives-promote-prosperity.
56. Colorado Office of the State Auditor, “Enterprise Zones Tax Expenditures,” 24-25, 49.
57. Digital Scholarship Lab, “Renewing Inequality: Urban Renewal, Family Displacements, and Race 1955-1966,” University of Richmond, accessed May 29, 2020, https://dsl.richmond.edu/panorama/renewal/#view=0/0/1&viz=cartogram&text=about&city=lubbockTX&loc=15/33.5700/-101.8250.
58. Ibid.
59. J.C. Teaford, “Urban Renewal and Its Aftermath,” Housing Policy Debate 11, no. 2 (2010): 443-65, https://doi.org/10.1080/10511482.2000.9521373.
60. State of California Franchise Tax Board, “New Employment Credit Report” (2020), 5, https://www.ftb.ca.gov/about-ftb/data-reports-plans/new-employment-credit.pdf.
61. M. Taylor, “California Hiring Tax Credits” (California Legislative Analyst’s Office, 2018), 3-4, https://lao.ca.gov/reports/2018/3784/hiring-credits-031518.pdf; State of California Franchise Tax Board, “New Employment Credit Report.”
62. K. Liu and R. Damewood, “Local Hiring and First Source Hiring Policies” (Regional Housing Legal Services, 2013), 13, https://rhls.org/wp-content/uploads/First-Source-Hiring-Overview-RHLS.pdf.
63. City and County of San Francisco Office of Economic and Workforce Development, “First Source Hiring Fact Sheet,” https://oewd.org/sites/default/files/Workforce/Workforce-Docs/First-Source-Fact-Sheet-NonConstr_08072019_0.pdf.
64. M. Jacobson and L. Perry, “Less Than One-Fifth of First Source Provisions Have Been Effectively Implemented and the District Has Not Demonstrated Success in Hiring and Retaining District Employees” (Office of the District of Columbia Auditor, 2018), https://dcauditor.org/report/less-than-one-fifth-of-first-source-provisions-have-been-effectively-implemented-and-the-district-has-not-demonstrated-success-in-hiring-and-retaining-district-employees/.
65. C. Shearer and I. Shah, “Opportunity Industries: Exploring the Industries That Concentrate Good and Promising Jobs in Metropolitan America” (Brookings Institution, 2018), 5, 8, https://www.brookings.edu/wp-content/uploads/2018/12/2018.12_BrookingsMetro_Opportunity-Industries_Report_Shearer-Shah.pdf.
66. Ibid., 8-9.
67. Florida Office of Economic and Demographic Research, “Analysis of the Enterprise Zone Program” (2015), 16, http://edr.state.fl.us/content/special-research-projects/economic/enterprisezone_2014.pdf.
68. Maryland Department of Legislative Services Office of Policy Analysis, “Evaluation of the Enterprise Zone Tax Credit”; Colorado Office of the State Auditor, “Enterprise Zones Tax Expenditures”; T. Adrian (Business and Industry Team Manager, Prosper Portland), interview with The Pew Charitable Trusts, Aug. 28, 2019.