Place-Based Tax Incentives and Minority 

Employment: Evidence from the New Market 

Tax Credit (NMTC) Program

Anil Rupasingha (USDA-ERS)

Alex Marre (NTIA) and Jose Josemari Feliciano (USDA-RD)

Presented at the Federal Committee on Statistical Methodology Research & Policy 

Conference, October 25-27, 2022, Washington, DC.

The findings and conclusions in this presentation are those of the authors and should not be construed 

to represent any official USDA, NTIA, or U.S. Government determination or policy. 
2

Motivation

• Advancing equity has become a major policy priority for the current 

administration (Executive order 13985)

• Consideration of place-based economic incentives for low-income 

communities (LICs) continues to be relevant given this policy priority

– LICs generally have a high representation of racial and ethnic minorities 

– LICs are known to experience spatial mismatch in labor market and 

discrimination in credit market 

• Place-based tax incentives have been featured notably as a solution to 

rectifying spatial mismatch and addressing access to capital issues in LICs

• One of the popular place-based programs is the New Market Tax Credit 

(NMTC) program

• The objective of this research is to study the effectiveness of the NMTC 

program on minority and rural populations
3

New Market Tax Credit (NMTC) Program 

• A federal program designed to attract private investment to 

low-income communities (LICs)

• Created as part of the Community Renewal Tax Relief Act of 

2000

• Administered by the Community Development Financial 

Institutions (CDFI) Fund at the Treasury

• Encourages capital investment in businesses located in 

qualified LICs (QLICs)
4

Qualified Low-Income Communities (QLICs)

• Median family income (MFI) threshold:

– Census tracts in MSAs with MFI that does not exceed 80% of the greater of 

MSA MFI or statewide MFI 

– Tracts outside MSAs (rural) with MFI that does not exceed 80% of their 

state's MFI 

• Tracts with poverty rates of at least 20%

• “Low-population” tracts: populations less than 2000, are located in 

Empowerment Zones, and are contiguous with another QLIC 

• “Rural, high out-migration”: rural tracts, have MFI less than or equal 

to 85% of statewide MFI, and have net out-migration of at least 10%
5

What does the NMTC program do?

• Offers tax incentives to investors who make qualified equity investments 

(QEIs) in Community Development Entities (CDEs)

• CDEs: intermediary domestic corporations or partnerships that offer financial 

intermediation in QLICs

• CDEs must apply for certification from the CDFI Fund to qualify as a CDE

• The program starts when the CDFI Fund awards tax credit allocation 

authority to CDEs

• Investors investing in CDEs are granted a tax credit equal to 39 percent over a 

period of seven years

• In turn, the CDEs provide loans or equity investments to businesses in QLICs 

with better terms
6

NMTC Annual Investments

Source: ERS Calculations using CDFI data

Year number of

projects

Amount

(million $)

Year number of

projects

Amount

(million $)

2001 1 1.1 2011 462 5637.5

2002 3 11.4 2012 426 4962.0

2003 11 34.6 2013 385 4102.0

2004 197 1069.9 2014 394 3361.9

2005 380 2194.8 2015 400 3104.6

2006 464 2882.8 2016 383 2759.4

2007 562 3275.6 2017 460 4277.6

2008 479 3215.3 2018 591 3999.7

2009 411 3295.8 2019 403 2983.6

2010 410 4825.9 Total 6822 55995.5

These projects were located in 2,751 tracts
7

Literature

• Freedman (2012) studies the impact on home values, 

household income, poverty rate, unemployment, and 

household turnover 

• Freedman (2015) studies the impact on local labor markets 

through employment gains 

• Harger and Ross (2016) study how the NMTC program affects 

the sorting of industries across census tracts
8

Research Objectives

• Study the impact of NMTC program on tract-level employment

– Total employment

• Employment by place-based and residence-based 

• Impacts on rural tracts

– Employment by race and ethnicity

• Employment by place-based and residence-based 

• Impacts on rural tracts

• We focus on the time-period between 2010 and 2018 

– data on minority employment is not available for prior years
9

Identification Issues

• Identification issues mainly due to two reasons

– Reverse causality: program receipt of a census tract may depend 

on its employment conditions 

– Selection bias: the receipt of the program and employment 

outcomes could be driven by common characteristics that may not 

be observable

– OLS is not suitable and there are no appropriate instruments
10

Identification Strategy

• We use matching techniques

– Potentially include all the NMTC recipient tracts and can recover the 

average treatment effect on the treated (ATET)

• Not without problems: strong assumption of no unobserved 

differences. To minimize this, we include:

– Pre-treatment demographic and housing controls and employment 

outcomes

• Conduct further robustness checks for existence of unobserved 

differences
11

Data

• Information on NMTC eligibility tracts (31,680) and NMTC 

investment was obtained from the CDFI Fund

– NMTC projects were located in 2,751 tracts

• Demographic and housing information was from the ACS (2006-10)

• All tract-level employment data were compiled from the Census 

LODES (Longitudinal Employer-Household Dynamics Local Origin- Destination Employment Statistics) dataset

– LODES data are available for the years 2002–2018, but employment data 

based on race and ethnicity are available from 2009 onward only

• Employment outcomes are measured as the difference between 

2010 and 2018
12

Matching Estimation 

• Use kernel matching based on Mahalanobis distance - more efficient than k

pairs matching (Heckman, et al.,1998)

– Considers all tracts from the control group weighted by the inverse of the 

covariates’ variance–covariance matrix

• Also use one-to-one (nn=1) and one-to-two matching (nn=2) based on 

Mahalanobis distance

• Use bias-corrected version of the Mahalanobis matching estimator (Abadie 

and Imbens, 2011) 

• Exclude Gulf Opportunity (GO) Zones tracts and all the tracts that received 

NMTC investments prior to 2010

• Limit the control tracts sample to QLIC tracts designated by the CDFI Fund 

(approach suggested by Neumark and Simpson, 2015)
13

Matching

• Matched on pre-treatment total workplace- and residence-based 

employment change between 2007 and 2009

• Matched demographic and housing variables from ACS

• Exact-matched census tracts based on RUCA codes for 2010

• Balancing statistics show matching procedure ensures balance 

across these covariates

– Mean difference within the matched pairs is closer to zero and the 

variance ratio remains around 1

– The equality of immediate pre-treatment employment outcomes ensures 

parallel trends
14

Matching Results

• Estimated coefficients show 

number of jobs

• NMTC investments increased 

both total place-based and 

residence-based employment 

• Individuals live outside the 

treated tract hold many of 

these jobs

• Increased place-based 

employment for all racial and 

ethnic categories 

• Resident-based employment 

growth is significantly positive 

only for Whites

Employment change

Kernel Nearest Neighbor

(nn=1)

Nearest Neighbor

(nn=2)

Panel A

Chg. workplace jobs 

(2010-18) 239.66*** 237.78*** 243.04***

(57.15) (72.65) (68.58)

White 110.30*** 102.99** 106.37**

(37.85) (51.93) (47.58)

Black 66.93*** 66.28*** 69.62***

(14.49) (16.63) (16.52)

Hispanic 86.59*** 103.29*** 104.50***

(12.26) (14.37) (13.62)

Panel B

Chg. resident jobs (2010-

18) 34.28*** 47.82*** 39.13***

(9.54) (11.79) (10.73)

White 31.43*** 37.17*** 30.61***

(6.86) (8.54) (7.81)

Black -1.43 4.37 3.57

(3.53) (4.59) (3.99)

Hispanic -6.09** 1.66 -2.04

(2.79) (3.50) (3.18)
15

Matching Results – Rural Tracts

Employment change

Kernel Nearest Neighbor

(nn=1)

Nearest Neighbor

(nn=2)

Panel A - Workplace

Chg. workplace jobs (2010-18) 50.23 75.41 32.99

(53.84) (66.60) (64.81)

White 16.83 47.10 8.58

(47.33) (59.39) (54.86)

Black 18.82** 23.59** 15.33

(7.81) (9.18) (12.01)

Hispanic 11.20 13.64 10.54

Pane B - Resident (8.47) (10.91) (10.72)

Chg. resident jobs (2010-18) -14.22 -11.69 -6.45

(21.31) (27.96) (25.63)

White -6.31 0.95 3.96

(14.90) (19.45) (17.85)

Black -8.23 -12.67 -9.36

(7.85) (10.93) (10.13)

Hispanic -6.62* -5.90 -6.21

(3.95) (5.25) (4.90)

• Overall, the 

program had no 

impact on job 

growth in rural 

treated tracts

• Place-based 

employment for 

Blacks shows 

some positive 

impacts
16

Placebo Analysis (1)

Employment change

Kernel Nearest Neighbor

(nn=1)

Nearest Neighbor

(nn=2)

Panel A

Chg. workplace jobs (2002-05) -43.12 -40.17 -39.54

(26.40) (30.29) (32.38)

Chg. resident jobs (2002-05) -2.33 -6.65 -4.09

(8.36) (11.53) (9.97)

• Move the NMTC 

investment period prior to 

2002, which is earlier than 

the true intervention 

period considered in the 

analysis

• Looked for treatment 

effect for 2002-2005 

period

• The expectation is that the 

estimated mean 

differences in outcomes 

between treated and 

control tracts should not 

be statistically significantly 

different from zero
17

Placebo Analysis (2)

• Randomly assign treated 

tracts to all tracts in QLICs 

and conduct matching 

(kernel) for 500 random 

draws for each outcome 

variable

• Each chart for each 

outcome studied compares 

the distribution of 

estimated placebo effects 

to the estimated program 

effects

• Distribution of estimates 

from random appointments 

is centered around zero, 

and the actual estimates 

are located at the far-right 

tail, indicating no significant 

effect of the randomly 

selected treatment
18

Spatial Spillover Effects

Kernel Nearest Neighbor

(nn=1)

Nearest Neighbor

(nn=2)

Panel A

Chg. workplace jobs (2010-18) 229.79*** 230.91*** 233.27***

(57.71) (72.97) (69.42)

White 102.98*** 98.40* 99.27**

(38.19) (52.19) (48.08)

Black 65.78*** 65.23*** 68.84***

(14.59) (16.64) (16.53)

Hispanic 86.54*** 103.11*** 103.52***

(12.22) (14.31) (13.62)

Panel B

Chg. resident jobs (2010-18) 33.44*** 44.06*** 39.23***

(9.56) (11.73) (10.71)

White 30.69*** 34.55*** 30.56***

(6.87) (8.51) (7.79)

Black -1.45 3.19 3.56

(3.53) (4.59) (3.99)

Hispanic -6.74** 0.46 -2.59

(2.80) (3.49) (3.18)

• Some of the matched 

control tracts could 

be bordering treated 

tracts and may be 

subject to spillover 

effects of the 

treatment

• Excluded control 

census tracts within 

less than 10 miles of 

a treated tract before 

matching

• New results align 

very closely with the 

base results 
19

Conclusion

• There is clear evidence that the NMTC program increased placebased employment in treated tracts

• Individuals live out-side the program recipient tracts are holding 

many of these jobs

• Minority and rural populations living in the treated tracts did not 

seem to benefit from the program

• Caveats: 

– Possibility of additional financial capital flowing into treated tracts

– Cannot rule out some degree of crowd-out of unsubsidized investments 

from recipient communities

– Cannot fully rule out the effects of unobserved factors in the research design
20

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21

Anil Rupasingha, Ph.D.

USDA Economic Research Service

anil.rupasingha@usda.gov
22

Balance Table before and after Mahalanobis Distance 

Kernel Matching 

Raw Matched

Means Treated Untreated Std.Diff. Treated Untreated Std.Diff.

Log of total population 8.122 8.193 -0.144 8.130 8.130 0

Share Black 0.311 0.210 0.334 0.311 0.311 5.52E-16

Share Hispanic 0.200 0.226 -0.100 0.199 0.199 -8.42E-16

Share population under age 5 0.072 0.072 0.000 0.072 0.072 0

Share population over age 64 0.114 0.125 -0.170 0.114 0.114 2.06E-16

Share enrolled in school 0.292 0.280 0.119 0.291 0.291 0

Share HS degree 0.320 0.331 -0.117 0.321 0.321 0

Share some college degree 0.257 0.268 -0.139 0.257 0.257 7.04E-16

Share college or more degree 0.167 0.167 0.002 0.166 0.166 2.24E-16

Labor force participation rate 0.600 0.620 -0.192 0.601 0.601 0

Unemployment rate 0.076 0.066 0.260 0.076 0.076 3.68E-16

Log of total housing units 7.336 7.357 -0.046 7.343 7.343 0

Log of median home values 11.720 11.819 -0.147 11.720 11.720 0

Share move in population 0.216 0.202 0.104 0.213 0.213 2.03E-16

Chg. workplace jobs (2007-09) -148.235 -73.747 -0.050 -126.555 -126.555 3.82E-17

Chg. resident jobs (2007-09) -57.321 -53.355 -0.014 -54.949 -54.949 -4.89E-17