Do Capital Tax Incentives Attract New Businesses?
Evidence across Industries from the New Markets Tax Credit
West Virginia University
Department of Economics
Morgantown, WV 26506
West Virginia University
Department of Economics
Morgantown, WV 26506
May 6, 2014
We use the New Markets Tax Credit (NMTC) to determine the effect of a capital tax credit on where different types of firms choose to locate. All levels of government pursue policies to attract new businesses with the hope that these establishments will become drivers of future growth. Businesses select their location based on unobservable characteristics and if these attributes are correlated with the policy, then OLS estimates will be biased. To obtain causal estimates, we draw upon an eligibility cutoff in the NMTC to determine the effect of the tax credit on where new businesses locate. We compare census tracts just eligible for the tax credit to those that are just ineligible for the credit to determine the impact of the tax credit on business location decisions. Using data from the Dun and Bradstreet MarketPlace Files, we find t hat in Metropolitan Statistical Areas, the NMTC incentivized businesses to locate in lower income tracts that were eligible for the tax credit in 2002 and 2004. However, we find that in 2006 the tax credit had a deterrent effect. When we stratify the sample by industry, we find that the tax credit attracted more capital intensive industries, such as manufacturing, while deterring more labor intensive industries, such as services. This finding is consistent with previous research which has found that the type of tax credit offered, capital versus labor, causes different industries to sort into different locations.
Policy makers at all levels of government in the United States believe that a key driver of local economic growth is new businesses. Therefore, government designs policy through various tax credits and subsidies to attract new businesses with the hope that these enterprises will create growth within their jurisdiction (Neumark et al., 2007). These tax credit programs are typically place-based policies, where a business will be eligible to receive the tax credit if they locate in a specific area. In general, research that has estimated the impact of tax credits on where businesses locate has been mixed, with some papers finding positive effects while others find the tax credit has no effect. 
One explanation for the discrepancies across papers regarding the effect of tax credits on where businesses locate is that there are heterogenous effects across different industries (Hanson & Rohlin, 2011b; Patrick, 2014). For example, a tax credit may be offered to firms who locate in a specific area and hire workers from that area. A program such as this effectively creates a labor subsidy for businesses that locate in the area, so we would expect industries that are more labor-intensive will outbid those industries that are more capital intensive to locate in areas eligible for the credit. Sorting of this type is consistent with the predictions of a standard urban economics model, which predicts firms or households that value locating in a given area the most will outbid others for the land in that area.
In this paper, we use a capital investment tax to determine the effect of government tax credits on the location decisions of new enterprises. We look not only at the effect of the program on all new businesses, but also how the effect of the policy varies across firms in capital intensive industries versus labor intensive industries. To determine the effect of a capital investment tax credit on business location decisions, we use the New Markets Tax Credit (NMTC). The NMTC, which was passed in 2000, offered a tax credit to businesses to make capital investments in low-income communities.
One of the issues when estimating the effect of place-based tax credits on business location decisions is that there is likely to be non-random selection of communities both by businesses and the government program. First, businesses choose which neighborhood to locate in based on various attributes of the local area, such the poverty rate, local crime rates, and agglomeration economies. Therefore, looking at the impact of a tax incentive on all areas is likely to produce biased estimates, as many of these attributes that affect business location decisions are likely to be unobservable. Second, there is a selection process regarding which businesses receive the tax credit. With the NMTC, not all applicants for the tax credit were selected to receive the credit. Therefore, to compare those businesses that received the tax credit to those that did not is problematic, since the firms that were selected may have been selected based on expected growth.
To obtain causal estimates, we use whether a tract is just eligible for the NMTC as exogenous variation to determine whether or not the tax credit successfully attracted new establishments. More specifically, eligibility for the NMTC program is based on a cutoff that creates a ratio of the median income in a given census tract to the state median income, which we refer to as the income eligibility ratio. To be eligible to receive the NMTC, the income eligibility ratio must be less than 0.80. We use whether or not a census tract falls just above or just below this cutoff as plausibly exogenous variation in where a business chooses to locate. Note that we do not know whether or not a specific business was allocated the tax credit, only that the business opened in a tract that was eligible to receive the credit. By comparing tracts that just qualify to receive the NMTC to those that just fail to qualify to receive the credit based on the eligibility ratio cutoff, we are able to control for unobserved local attributes that could potentially bias our results.
To conduct our analysis, we use data from the Dunn and Bradstreet (D&B) MarketPlace files from the second quarter of 1994, 2002, 2004, and 2006. The D&B data contains a wealth of information on establishments at the ZIP code level, including the SIC code of each business. In addition, the D&B data has information on how long an establishment has been open, which allows us to focus on only those businesses that have been open for less than one year, which is what we define as a new business.
When we estimate the effect of the NMTC on businesses across all census tracts in the U.S., we find that businesses are less likely to locate in those tracts that are eligible to receive the NMTC. However, businesses are likely to prefer to locate in lower poverty, higher income areas which are not eligible for the NMTC and are likely to be very different from those tracts that are eligible. To address the selection issue, we restrict the sample to those census tracts that are just above and just below the 0.80 income eligibility ratio. We focus first on those tracts that have an income eligibility ratio between 0.70 and 0.90, and then further restrict the sample to those with an eligibility ratio between 0.79 and 0.81. With both of these restrictions, we estimate a positive impact of the NMTC on business location decisions, but this effect is not statistically significant.
Next, we restrict our sample to only those tracts located in metropolitan areas. Previous research has found that rural growth and development is fundamentally different from urban growth and development, suggesting that rural and urban areas should be examined separately (Stephens & Partridge, 2011; Rupasingha & Goetz, 2013; Stephens, Partridge, & Faggian, 2013). When we focus on just those census tracts located in MSAs that are near the income eligibility ratio, we find that a new business is more likely to locate in the census tract that is eligible for the NMTC in 2002 and 2004. However, we find a negative and statistically significant effect of the tax credit in 2006.
The NMTC is a capital subsidy, so it is likely that the credit will create a sorting across industries, where firms that are more capital intensive will locate in the eligible tracts and those that are more labor intensive will locate in other areas. When we stratify our results by industry, we find that in 2006 the NMTC had a positive effect on manufacturing, which is consistent with the program goal to stimulate capital investment. We also find that in 2006 there is a negative and statistically effect in the service industry, a labor intensive industry. This finding supports the existing work on capital subsidies and tax credits which has found that the impact of government tax and subsidy programs varies based on whether the program is designed to stimulate investment in capital or labor (Hanson & Rohlin, 2011b; Patrick, 2013). Given that the NMTC was allocated for capital investments, the credit is likely to have increased the value of locating in these areas for capital intensive industries, causing these establishments to bid more for land in areas that are eligible for the credit.
The rest of the paper proceeds as follows. Section II describes in detail the specifics of the NMTC program. Existing research on government based business incentive programs and the NMTC in particular are discussed in Section III. Our empirical strategy is outlined in Section IV and in Section V we discuss our data set. Section VI contains our results. We conclude and discuss policy implications in Section VII.
- The New Markets Tax Credit
The Community Renewal Tax Relief Act of 2000 created the NMTC program, which allocated the first set of tax credits in 2002 and has been renewed annually since its implementation (Freedman, 2012; Abravanel et al., 2013). The NMTC program aims to combine government funds with private market investment in order to increase private investment in targeted communities where investment may otherwise not take place (Rubin & Stankiewicz, 2005; Gurley-Calvez et al., 2009; Freedman, 2012; U.S. Department of the Treasury, CDFI Fund, 2013). The NMTC’s goal was to increase investment in low-income communities between 2002 and 2007 by $15 billion (Groves 2006). If awarded a NMTC allocation, investors receive a federal income tax credit totaling 39% of the initial investment over seven years. Although the NMTC program is similar to other location-based tax incentives, it is somewhat unique in that it aims to increase investment in ‘risky’ communities by using tax credits to mitigate some of the risk of loss. However, the tax credit is not large enough to mitigate all of the risks and thus is likely to avoid overinvestment (Freedman 2012).
The NMTC is allocated through a division of the U.S. Treasury department known as the Community Development Financial Institutions (CDFI) Fund. The goal of the CDFI is to increase community development and economic opportunities for distressed areas within the United States. The CDFI administers tax credit allocations to qualified Community Development Entities (CDEs) which then disperse the funds to private investments in target areas (Freedman 2012, Abravanel et al. 2013, Freedman 2013). Since the inception of the NMTC, the CDFI fund has awarded roughly $36.5 billion in tax credits through the program. Table 1 provides information on the total amount allocated through the NMTC program from 2001 to 2012. According to Abravanel et al. (2013), 46% of the projects funded by the NMTC were used for office, retail, mixed use, or hotel development. The remaining projects were split up as follows: 22% to social services, educational, or cultural/arts use, 18% to manufacturing, industrial, or agricultural uses, 9% to health facilities, and 5% to housing.
CDEs consist of domestic corporations or partnerships that serve as intermediaries between investors and Low-Income Communities (LICs). In order to qualify as a CDE, a corporation or partnership must apply for certification through the U.S. Treasury’s CDFI fund. Only businesses listed as corporations or partnerships for Federal tax purposes are eligible for CDE certification. Limited liability companies and sole proprietorships are not eligible for CDE status. Government entities listed as partnerships or corporations for Federal income tax purposes are eligible to apply for CDE certification. Once certified as a CDE by the CDFI fund, the certification remains valid for the lifetime of the business provided it continues to comply with the requirements listed above. The certification requirements listed above detail only what is required to quality as a CDE. Additional requirements and reports may be obligatory depending on the type and amount of investment a CDE receives.
The primary focus of a CDE must be to increase the amount of capital investment available to the LICs. More specifically, at least 60 percent of the firm’s financial activity is required to be directed to LICs. In addition, qualification as a CDE is contingent upon community-resident representation on any advisory board present within the organization (Freedman 2012). The goal of the advisory board requirement is to ensure accountability to the residents of the LICs. CDEs accept qualified equity investments for use in low-income communities from private investors and in turn supply those investors with the tax credit funds.
In the initial creation of the NMTC program, a census tract could qualify as a LIC in the NMTC designation if it met one of two criteria. The first criteria is based on the median income of the census tract. More specifically, there is an income eligibility ratio that compares the median family income (MFI) in each tract to the median family income in the state. Non-MSA census tracts are eligible for LIC designation if the ratio of tract MFI to state MFI is less than or equal to 80%. Census tracts located within a MSA qualify for LIC status if the ratio of tract MFI to the larger of state or MSA MFI, is less than or equal to 80%. The second way a census tract could qualify is based on the poverty rate of the tract. In this case, tracts with poverty rates of 20% or higher are designated as LICs.
A 2004 revision to the NMTC program added two additional qualification criteria – the low-population criteria and the out-migration criteria. Tracts may qualify on low-population status if the tract contained less than 2,000 people, is located within an empowerment zone, and is contiguous to at least one other LIC (Freedman, 2012; Abravanel et al., 2013). The migration classification applies only to rural tracts. A tract could qualify on the migration criteria if it was located in a county with high out-migration, where high rural out-migration is said to occur if in the twenty years previous to the most recent census, the net out-migration from the county is at least 10% of the county’s population at the beginning of the twenty year period. This change allowed CDEs to invest in businesses not located in LICs if these businesses serve targeted populations, where targeted populations are defined as individuals who lack adequate access to loans or credit opportunities. Freedman (2012) notes that LICs have thus far received 95% of the investment dollars allocated to CDEs. Of the U.S. census tracts qualifying as LICs, 98% qualify on the first two criteria listed above, and the remaining 2% qualify as either low-population or high out-migration tracts.
Local Economic Development Policy and Business Location
State and local policy makers strive to attract new businesses, as these establishments are crucial components to the U.S. economy. In 2005, approximately 3.5 million new jobs were created by new businesses, dramatically more than any other firm-age category (Haltiwanger et al., 2013). In order to help lagging areas within a jurisdiction, policy makers at all levels of government enact legislation that encourages new businesses to open in these struggling areas. This idea, known as “economic gardening,” is emphasized by Neumark et al. (2007) who stated that “new firms contribute substantially to job creation.”
However, there are questions regarding the best way to set up incentives to attract new businesses to an area. Some argue that location-based tax incentives are the optimal policy. Glaeser (2001) argues that attracting new businesses to an area will generate economic surplus for current residents in the targeted area. Furthermore, he suggests that offering location-based tax incentives may be justified as it compensates new businesses for future tax payments that will be made to the locality. This research is likely to be one of the reasons why policy makers at all levels of government offer location based tax incentives to attract new establishments to their jurisdiction.
Numerous papers have looked at the various types of government policy that affect where businesses locate. Kolko and Neumark (2008) use the National Establishment Time Series database to track the movement of both businesses and employment into and out of California as a result of differences in state policy. Other researchers have used establishment level data to determine the impact of state tax policy on business location (Gabe & Bell, 2004; Rathelot & Sillard, 2008; Duranton, Gobillon, & Overman, 2011; Bruce & Deskins, 2012; Rohlin, Rosenthal, & Ross, 2014). Patrick (2014) created an index to capture the degree to which state constitutions are constructed in a manner that allows state governments to offer non-tax incentives to attract new businesses. For a recent review of the methods used in this literature, see Arauzo-Carod et al. (2010).