Thursday, August 8, 2019

Place-based economic policies (pt. 2 of 3): How effective are tax incentives for investments in low-income communities

In this post, I discuss tax incentives for investments in low-income communities. In the U.S., these incentives often have bipartisan support. Democratic presidential contender and Senator Cory Booker and Republican Senator Tim Scott were the primary architects of the provision in the recent Trump tax bill (Tax Cuts and Jobs Act or TCJA) that allows investors to forego capital gains taxes on long-term investments made in low-income Census tracts that they designate as "opportunity zones". These incentives are by no means recent or unique. This policy paper from the Minnesota House of Representatives provides a concise summary of the history and implementation of enterprise zones in the U.S. and evidence from the literature - through 2005 - on their effectiveness.

In theory, economic barriers prevent qualifying low-income communities from reaching their full potential (lack of transportation, lack of access to capital, lack of skilled labor, social problems, environmental problems) however tax incentives can outweigh the costs to investors of investing in these areas. As stated aptly in the paper: "In the language of economics, the first, best solution is to find a subsidy that equates the marginal social benefits with the marginal social costs to doing business within the zone. Deciding upon the value of the social benefits is a difficult task, let alone determining how much of a subsidy is needed to attract the needed number of businesses."

These decisions are made by our elected officials (and therefore indirectly by us). For example, elected officials determine which social benefits matter, the way in which these social benefits are to be quantified (e.g. unemployment rate, job growth rate, quality of jobs created, poverty rate), and they determine the price tag associated with these social benefits (e.g. the capital gains tax that the federal or state government foregoes by incentivizing investments in these communities and any administrative costs).

The TCJA, for example, indicates that investors will be allowed to delay paying a capital gains tax on any investments that are moved into an opportunity zone fund, will have to pay the capital gains on a smaller proportion of that initial investment depending on the number of years that the investment is held, and will not have to pay any capital gains on the proceeds from the opportunity zone investment. This is aptly summarized in a CNN article: "Here's how it works. Someone who reinvests a capital gain worth $100 in an Opportunity Zone in 2019 gets a 15% step up in basis," which means she has to pay the federal capital gains tax on only $85 of that original income. At a tax rate of 23.8%, that comes to $20 - and she doesn't have to pay it for another 10 years. On top of that, if she holds the investment for at least 10 years, she pays no capital gains taxes on the proceeds from the Opportunity Zone investment."

Governors were allowed to nominate Census tracts to become opportunity zones so long as they met one of the following criteria: (1) poverty rate of at least 20 percent; (2) median family income of the tract is 80 percent or less of the median family income at the metropolitan or state level; (3) contiguous to a low-income tract and does not exceed 125 percent of the median family income of the neighboring tract. Any tracts selected based on criteria (3) were to make up only 5 percent of the total opportunity zones in a state. There are no restrictions on the types of investments that can be made within opportunity zones other than "sin businesses" that include "liquor stores, gambling facilities, golf courses, country clubs, tanning facilities, and massage parlors".

But the effectiveness of these policies and whether they even produce the social benefits that we as a society care about is unclear. The decisions are made by elected officials but the degree to which they have been informed by the empirical economic literature is circumspect. Even Jared Bernstein, economist behind this TCJA provision and former chief economist to another Democratic presidential contender, Vice President Joe Biden, wrote: "If OZs [opportunity zones] turn out to largely subsidize gentrification, if their funds just go to places where investments would have flowed even without the tax break, or if their benefits fail to reach struggling families and workers in the zones, they will be a failure."

It is therefore unsurprising that these tax incentives in the Trump tax bill have received significant backlash (see here, here, and here for examples) if these incentives place a hefty cost to the federal government in foregone capital gains taxes - these capital gains benefits accruing to the wealthy, i.e. the 9.2 percent of taxpayers that report realizing any long-term capital gains at all - while their social benefits are reduced to these big "ifs". The California Budget and Policy Center estimates the cost to the federal government as follows: "These lost revenues - mostly benefiting high-income investors - could instead help pay for other services that may have a greater impact on vulnerable communities in California and across the nation. The official cost estimate for the tax incentives is small relative to the total cost of the TCJA - $1.6 billion over 10 years in a package of nearly $2 trillion in tax cuts. However, the long-run costs could be much greater given that this estimate does not include revenue losses from the complete exclusion of gains on QOF investments held for 10 years, which fall outside the 10-year period for which budget estimates were made." These costs and distributional implications are difficult to ignore.

To inform this debate from an economist's perspective, I focus on the evaluation of an existing tax incentive program for investments in low-income communities. The New Markets Tax Credit (NMTC) has been ongoing since it was legislated in 2000. Like the TCJA it provides incentives for investing in low-income communities but it places more stringent requirements on the ways in which investments are made.

Freedman (2012)

The NMTC program is distinct from opportunity zones in the TCJA because it provides tax credits to investors who make equity investments in Community Development Entities (CDEs). According to the federal government, any "domestic corporation or partnership that is an intermediary vehicle for the provision of loans, investments, or financial counseling in Low-Income Communities (LICs)" can qualify to be a CDE. However, in order to qualify these organizations need to have a primary mission of serving LICs and must maintain accountability to the residents of the LICs that they serve. Qualified CDEs can then take the equity investments and make Qualified Low Income Community Investments (QLICs). These requirements are stated very clearly in this presentation.

The NMTC program places more stringent requirements on qualifying investments than does TCJA. Not only does it require the investments to be made through CDEs (organizations must qualify to become a CDE) but it requires that the investments are made by the CDE to qualified active low income community businesses (QALICBs). NMTC does not allow these funds to be invested in businesses that build or rehabilitate residential rental property. This is a notable omission from the TCJA opportunity zone provision given the role that real estate development - particularly for rental property - plays in gentrification. It is discussed in part in this article on gentrification in NYC.

Freedman (2012) uses quasi-experimental variation to study the effects of NMTC. Because Census tracts at or below 80 percent of median family income of the metropolitan or state median family income qualify for NMTC-subsidized investments and tracts above 80 percent (even if they are 81 percent of the median family income) do not, Freedman uses a regression discontinuity (RD) identification strategy. His RD strategy allows him to estimate the causal effect of NMTC on community economic outcomes (poverty rate, median home value, median household income, unemployment rate, and household turnover) by comparing Census tracts around the 80 percent cutoff. In other words, the RD identification strategy assumes that Census tracts immediately above and immediately below the 80 percent cutoff do not differ based on any observable or unobservable characteristics other than the fact that those below the cutoff are eligible to receive NMTC-subsidized investments.

Freedman finds that most estimates are statistically indistinguishable from zero. In certain specifications he finds that: from OLS estimates $1 million NMTC-subsidized investment is associated with (1) .01-.03 percent decrease in median home values; (2) .02 percent increase in median household income; from IV estimates $1 million investment is associated with (1) reduction in poverty rates by one percent off a base of 13 percent; (2) reduction in unemployment rate by .33 percent off a base of 6 percent; and (3) increase in household turnover rates by .75 percent off a base of 16 percent. These select estimates are significant but very modest. He states: "Indeed, the results suggest that to the extent that there are benefits associated with subsidizing investment in poor areas, those benefits are limited, and for many outcomes we cannot rule out that there is no effect at all." The issue with Freedman's analysis is that it is conducted at the Census tract-level indicating that the results may be due to a change in the composition of the Census tract rather than an improvement in the economic outcomes of the existing residents. This is hinted at by the statistically significant and positive effect of investment on household turnover (i.e. there is more migration in and out of the tract).

The questions remain: (1) how does the value for money provided by this program - in terms of poverty reduction or one of its other goals - compare to value for money of other dedicated social programs? (2) how much of these results are driven by changes in the composition of neighborhoods (i.e. gentrification) as opposed to economic improvements seen by existing residents? The latter question is best answered with panel data at the individual or household-level rather than the Census tract-level. The former data would allow researchers to follow the same individuals or households between the pre- and post-investment periods and track the in and outflows from these communities.

Freedman (2014)

Question (1) above is arguably more difficult to answer but Freedman (2014) has another more recent paper that provides a partial answer to whether improvements in economic outcomes due to NMTC investments accrue to existing residents of these communities. While he does not use individual or household-level data to study the changing composition of the residents of a given Census tract, he uses administrative data to study the changing proportion of residents who work outside the tract and non-residents who work inside the tract. Given that policymakers would prefer that social benefits of these investments accrue to the residents of these zones rather than non-residents, this addresses an important dimension to the puzzle.

Freedman states in this paper: "a common feature of these programs is that, while restricting where businesses may locate or invest in order to receive subsidies or tax breaks, they place few constraints on whom subsidized businesses must hire... Further, to the extent that any new jobs subsidized under these programs fall into the hands of residents of distant communities, the local economic benefits of these programs may be diluted and any imbalances between the locations of jobs and housing exacerbated." He notes that only 30 percent of the state enterprise zone programs that he reviewed included an incentive for participating businesses to hire residents of those zones. This is not an incentive included in the NMTC or TCJA either.

The identification strategy in this paper is the same as in Freedman (2012). While Freedman (2014) does not use individual or household-level data he has data from the OnTheMap database constructed and maintained by the Longitudinal Employer-Household Dynamics (LEHD) program at the Census Bureau that enables him to study the proportion of workers in a tract who live in the same tract. These proportions are further broken down by different earnings categories and industries. This disaggregated data allows the author to connect changes in the number of composition of jobs to change in the proportion of jobs held by residents of the Census tract. He finds a small and - only in some specifications statistically significant - impact of NMTC investment on overall workplace employment. He specifically finds a statistically significant increase in employment in goods-producing industries with no impact on trade, transportation, utilities, or services employment which he indicates is consistent with previous findings (Harger and Ross, 2014) suggesting that NMTC attracted firms in capital-intensive rather than labor-intensive industries. This is suggestive that more limited skills in low-income communities may be deterring labor-intensive industries from locating in these communities.

Taken in conjunction with the effect on resident employment - a small decline in low-wage resident employment significant at the 10 percent level - these findings suggest that any positive effect of NMTC investments on employment accrue to residents outside of the Census tract. To explore this finding, the author further finds that observed changes in the commuting times of LICs were driven by an increase in commuters who were traveling at least 20 or more miles. As he states in his paper: "Households in these neighborhoods turn out to be not only physically distant, but also socioeconomically distant from households in LICs that receive investment. Indeed... there is a marked gradient in income levels and poverty rates as one moves away from tracts that received NMTC-subsidized investment. The figure shows median family income and poverty rates averaged across treated tracts and tracts at distances up to 30 miles away from treated tracts in the RD sample."

Taken together, this indicates that any modest benefits in job growth resulting from NMTC investment accrued to non-residents of the tract who were less-likely to be low-income. It should be noted - even acknowledging the positives of an Amazon HQ2 deal in Queens - that concerns like this were made by opponents of this deal. As stated in this Tech Crunch article on the issue: "Amazon's promise of 25,000 jobs (high-paying jobs) may have reduced that number [NYC unemployment rate], but there's no guarantee that those jobs would be filled by New Yorkers or Queens residents more specifically - and every indication that they would have gone to Amazon employees coming from somewhere else."

Policy implications

These are only two papers on the subject (notably both by the same author and employing the same identification strategy). However, the results from these papers are consistent with broader findings from the literature in that the evidence is very mixed and much of it is insignificant. This is similarly stated in the Minnesota House report: "Considering all the studies using regression analysis, the economic effect of enterprise zones remains unclear. Most studies find no significant increase in employment, while a few do. Moreover, the prospect for success seems greatest in already economically viable areas, rather than traditional zone locations - areas with stagnant or declining economies."

Ultimately, evidence of positive effects is inconclusive and, more importantly, there is at least some evidence of negative effects that would warrant a better investigation into the impact of investments on gentrification and displacement. Individual and household-level panel data can allow for such an investigation because they can provide greater visibility into the trajectory of existing residents of these communities. While the sum spent on this initiative is small relative to the cost of the broader TCJA, it is a large sum to be spent on a set of policies that has had mixed empirical support - and importantly, some of it negative - for several decades. These negative effects may also be exacerbated by the allowance of investments in residential rental property in this bill. Given the mixed evidence, these programs should collect data and evaluate the effectiveness of their program on social benefits but this is perhaps one of the most notable concerns about TCJA opportunity zones: there are limited reporting requirements and guidelines to ensure that investments are socially impactful. A bill on these requirements has been introduced in the House and should be followed closely.

  1. Freedman, M. (2012). Teaching new markets old tricks: The effects of subsidized investment on low-income neighborhoods. Journal of Public Economics
  2. Freedman, M. (2014). Place-based programs and the geographic dispersion of employment. Regional Science and Urban Economics
  3. Harger, K., Ross, A. (2014). Do capital tax incentives attract new businesses? Evidence from across industries from the New Markets Tax Credit. West Virginia University Working Paper. 
  4. Hirasuna, D., Michael, J. (2005). Enterprise Zones: A Review of the Economic Theory and Empirical Evidence. Policy Brief: Minnesota House of Representatives Research Department. 


  1. Chandni, I'd love to read the last part (third) of this blog series. I quite enjoyed reading both the write-ups. Thank you.

  2. Dear sir, your blog contents are really helpful for all users.I do believe that especially helpful for bankers, researchers, students and financial analysts.