Supply of immigrant entrepreneurs and native entrepreneurship

Sample	All	Natives	Immigrants
Outcome variables
Self-employed	0.0961	0.0950	0.101
Incorporated self-employed	0.0342	0.0345	0.0330
Unincorporated self-employed	0.0619	0.0606	0.0684
Control variables
Age	41.28	41.41	40.66
Female	0.471	0.481	0.422
Less than high school	0.0815	0.0494	0.239
High school	0.295	0.300	0.271
Some college	0.285	0.306	0.179
College degree	0.224	0.231	0.192
Advanced degree	0.114	0.113	0.119
White	0.677	0.776	0.197
Black	0.108	0.113	0.0838
Other race	0.214	0.111	0.719
Hispanic	0.147	0.0817	0.468
Number of family members under 18	0.807	0.765	1.011
Lives in a metropolitan	0.852	0.832	0.947
State population (millions)	7.661	7.124	1.029
Observations	1,361,196	1,111,850	249,346

[i] Note: Data span 1994–2016 from the ASEC of the CPS. All foreign-born individuals are categorized as immigrants. CPS sample weights applied.

[ii] ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey.

Table 2

Summary statistics: incorporated vs. unincorporated

Sample	Natives		Immigrants
Sample	Incorp.	Unincorp.	Incorp.	Unincorp.
Age	46.33	44.91	45.39	43.73
Female	0.278	0.402	0.285	0.358
Less than high school	0.0265	0.0633	0.0787	0.243
High school	0.229	0.301	0.247	0.303
Some college	0.274	0.301	0.179	0.175
College degree	0.290	0.210	0.285	0.182
Advanced degree	0.181	0.125	0.210	0.0978
White	0.902	0.854	0.374	0.253
Black	0.0402	0.0614	0.0560	0.0591
Hispanic	0.0358	0.0567	0.238	0.450
Number of family members under 18	0.851	0.803	1.021	1.028
Lives in a metropolitan city	0.853	0.772	0.962	0.943
Observations	39,007	67,829	7,846	16,518

[i] Note: Data span 1994–2016 from the ASEC of the CPS. All foreign-born individuals are categorized as immigrants. CPS sample weights applied.

[ii] ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey.

Table 3

Impact of immigrant entrepreneurs on entrepreneurial propensities of natives: LPM

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives:	0.0950	0.0345	0.0606
Immigrant entrepreneurs	0.0035^** (0.0014)	0.0064^*** (0.0017)	0.0025^* (0.0014)
Observations	1,111,863	1,111,863	1,111,863

Note: Data span 1994–2016 from the ASEC of the CPS. Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; LPM, linear probability model.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Pre and Post Policy Trends in the Supply of Immigrant Entrepreneurs.
*Notes*: Data span 1994–2016 from the ASEC of the CPS. Trends are for the supply of immigrant entrepreneurs immediately prior to and after the implementation of SCHIP. Only 4 years prior to and after the policy implementation are shown in figure. See text for further details. ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; SCHIP, State Children's Health Insurance Program.

Pre- and Post-Policy Trends in the Supply of Immigrant Entrepreneurs with Various Attributes.
*Notes*: Data span 1994–2016 from the ASEC of the CPS. Trends are for the supply of immigrant entrepreneurs immediately prior to and after the implementation of SCHIP. Only 4 years prior to and after the policy implementation are shown in figure. See text for further details. ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; SCHIP, State Children's Health Insurance Program.

Table 4

First-stage regressions: impact of generous SCHIP on supply of immigrant entrepreneurs

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Average supply of immigrant entrepreneurs:	144,200	41,800	102,400
Generous SCHIP	0.1160^*** (0.0025)	0.0493^*** (0.0009)	0.0668^*** (0.0018)
First stage F-stat	2,101.30	2,697.76	1,374.92
Observations	609,365	609,365	609,365

Note: Data span 1997–2008 from the ASEC of the CPS. Dependent variable is supply of immigrant entrepreneur (in 100,000s). All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Event Study to Test Policy Endogeneity.
*Notes*: Data span 1994–2016 from the ASEC of the CPS. Observations before 5 years of SCHIP are added to “−5” bin and those beyond 5 years post SCHIP are included in the “+5” bin. Then “−5” is dropped as the omitted category. All additional controls included in the baseline regression are retained. Estimates with 95% confidential interval are for the effect of generous SCHIP on the supply of immigrant entrepreneurs. See text for further detail. ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; SCHIP, State Children's Health Insurance Program.

Table 5

Impact of immigrant entrepreneurs on entrepreneurial propensities of natives: TSLS Model

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives	0.0950	0.0345	0.0606
Immigrant entrepreneurs	0.0109 (0.0470)	−0.0491 (0.0426)	0.1268 (0.1161)
Observations	609,365	609,365	609,365

Note: Data span 1997–2008 from the ASEC of the CPS. Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; TSLS, two stage least squares.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table 6

Sensitivity to modeling and sampling choices: TSLS estimates

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives:	0.0950	0.0345	0.0606
State specific linear trends
Immigrant entrepreneurs	0.0080 (0.0161)	0.0875 (0.0993)	−0.0005 (0.0150)
Observations	609,352	609,352	609,352
Weighted least squares
Immigrant entrepreneurs	0.0130 (0.0667)	−0.0320 (0.0407)	1.2307 (1.9806)
Observations	609,365	609,365	609,365
Clustered standard errors
Immigrant entrepreneurs	0.0109 (0.0611)	–0.0491 (0.1231)	0.1268 (0.3590)
Observations	609,365	609,365	609,365
Logged explanatory variable
Immigrant entrepreneurs	−0.0057 (0.1044)	0.0128 (0.0098)	−0.0588 (0.0634)
Observations	605,156	605,156	605,156
Extended sample
Immigrant entrepreneurs	−0.0014 (0.0984)	−0.0537 (0.0479)	−0.2859 (0.3718)
Observations	806,462	806,462	806,462

Note: Data span 1997–2008 from the ASEC of the CPS. Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Except explicitly stated, robust standard errors are reported in parentheses.

ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; TSLS, two stage least squares.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table 7

Heterogeneity in the impact of immigrant entrepreneurs across races of natives: TSLS estimates

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Blacks
Entrepreneurial propensity of natives:	0.0469	0.0126	0.0343
Immigrant entrepreneurs	0.0924^* (0.0519)	0.0217 (0.0843)	0.1260^* (0.0662)
First stage F stat	442.68	157.00	369.79
Observations	64,163	64,163	64,163
Whites
Entrepreneurial propensity of natives:	0.1121	0.0414	0.0706
Immigrant entrepreneurs	0.0434 (0.1014)	−0.0432 (0.0729)	0.5106 (0.5606)
First stage F stat	280.89	731.16	12.25
Observations	461,397	461,397	461,397

ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; TSLS, two stage least squares.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A1

SCHIP Implementation and Immigrant Coverage by State

State	Date of SCHIP implementation	Coverage for new immigrants
Alaska (AK)	March 1999	Yes
Alabama (AL)	February 1998	No
Arkansas (AR)	October 1998	No
Arizona (AZ)	October 1997	No
California (CA)	July 1998	Yes
Colorado (CO)	April 1998	No
Connecticut (CT)	October 1997	No
District of Columbia (DC)	September 1997	Yes
Delaware (DE)	October 1998	Yes
Florida (FL)	April 1998	No
Georgia (GA)	September 1998	No
Hawaii (HI)	January 2000	Yes
Iowa (IA)	July 1998	No
Idaho (ID)	October 1997	No
Illinois (IL)	January 1998	Yes
Indiana (IN)	October 1997	No
Kansas (KS)	July 1998	No
Kentucky (KY)	July 1998	No
Louisiana (LA)	November 1998	No
Massachusetts (MA)	October 1997	Yes
Maryland (MD)	July 1998	No
Maine (ME)	July 1998	No
Michigan (MI)	May 1998	No
Minnesota (MN)	September 1998	Yes
Missouri (MO)	October 1997	No
Mississippi (MS)	July 1998	No
Montana (MT)	January 1998	No
North Carolina (NC)	October 1998	No
North Dakota (ND)	October 1998	No
Nebraska (NE)	May 1998	Yes
New Hampshire (NH)	May 1998	No
New Jersey (NJ)	February 1998	Yes
New Mexico (NM)	May 1998	Yes
Nevada (NV)	October 1998	No
New York (NY)	April 1998	Yes
Ohio (OH)	January 1998	No
Oklahoma (OK)	December 1997	No
Oregon (OR)	July 1998	No
Pennsylvania (PA)	June 1998	Yes
Rhode Island (RI)	October 1997	No
South Carolina (SC)	October 1997	No
South Dakota (SD)	July 1998	No
Tennessee (TN)	October 1997	No
Texas (TX)	July 1998	No
Utah (UT)	August 1998	No
Virginia (VA)	October 1998	Yes
Vermont (VT)	October 1998	No
Washington (WA)	January 2000	Yes
Wisconsin (WI)	April 1999	No
West Virginia (WV)	July 1998	No
Wyoming (WY)	April 1999	No

[i] Source: Rosenbach et al. (2001) and Ghimire (2018). All states covered new immigrants starting 2009.

[ii] SCHIP, State Children's Health Insurance Program.

Table A2

Impact of Supply of Immigrant Entrepreneurs on Entrepreneurial Propensities of Natives: LPM

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives:	0.0950	0.0345	0.0606
Immigrant entrepreneurs	0.0035^** (0.0014)	0.0064^*** (0.0017)	0.0025^* (0.0014)
Age	0.00310^*** (0.00003)	0.00139^*** (0.00002)	0.00171^*** (0.00002)
Female	−0.04504^*** (0.00055)	−0.02901^*** (0.00034)	−0.01603^*** (0.00045)
High school	−0.00688^*** (0.00135)	0.00903^*** (0.00064)	−0.01591^*** (0.00122)
Some college	−0.00141 (0.00135)	0.01478^*** (0.00065)	−0.01619^*** (0.00122)
College degree	0.00642^*** (0.00141)	0.02653^*** (0.00072)	−0.02011^*** (0.00125)
Advanced degree	0.01341^*** (0.00156)	0.03144^*** (0.00087)	−0.01804^*** (0.00135)
White	0.02559^*** (0.00148)	0.01142^*** (0.00085)	0.01416^*** (0.00126)
Black	−0.02389^*** (0.00159)	−0.01070^*** (0.00091)	−0.01320^*** (0.00135)
Hispanic	−0.01709^*** (0.00161)	−0.00484^*** (0.00091)	−0.01226^*** (0.00137)
Number of children	0.01181^*** (0.00026)	0.00626^*** (0.00016)	0.00555^*** (0.00021)
Lives in a city	0.01484^*** (0.00085)	−0.00430^*** (0.00048)	0.01914^*** (0.00072)
State population	0.00027 (0.00087)	0.00080^** (0.00037)	−0.00043 (0.00071)
Observations	1,111,863	1,111,863	1,111,863

Note: Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, ethnicity, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

LPM, linear probability model.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A3

First-stage Regressions: Association between Generous SCHIP and Supply of Immigrant Entrepreneurs

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Average supply of immigrant entrepreneurs:	144,200	41,800	102,400
Generous SCHIP	0.1160^*** (0.0025)	0.0493^*** (0.0009)	0.0668^*** (0.0018)
Age	−0.00002 (0.00002)	0.00000 (0.00001)	−0.00002 (0.00002)
Female	0.00024 (0.00046)	0.00011 (0.00022)	0.00013 (0.00038)
High school	−0.00079 (0.00110)	0.00056 (0.00053)	−0.00136 (0.00091)
Some college	−0.00158 (0.00111)	0.00069 (0.00054)	−0.00227^** (0.00092)
College degree	0.00114 (0.00115)	0.00131^** (0.00056)	−0.00017 (0.00095)
Advanced degree	0.00139 (0.00125)	0.00140^** (0.00061)	−0.00001 (0.00104)
White	−0.00704^*** (0.00149)	−0.00147^** (0.00064)	−0.00557^*** (0.00122)
Black	−0.00916^*** (0.00166)	−0.00249^*** (0.00074)	−0.00667^*** (0.00136)
Hispanic	−0.00353^* (0.00182)	0.00009 (0.00079)	−0.00362^** (0.00150)
Number of children	−0.00030 (0.00021)	−0.00007 (0.00010)	−0.00023 (0.00017)
Lives in a city	0.00456^*** (0.00046)	0.00206^*** (0.00024)	0.00250^*** (0.00038)
State population	0.66179^*** (0.00115)	0.17862^*** (0.00049)	0.48317^*** (0.00097)
Observations	609,365	609,365	609,365

Note: Dependent variable is supply of immigrant entrepreneur (in 100,000s). All models control for demographic characteristics (age, marital status, education, race, ethnicity, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A4

Impact of Supply of Immigrant Entrepreneurs on Entrepreneurial Propensities of Natives: Second Stage Estimates

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives:	0.0950	0.0345	0.0606
Immigrant entrepreneurs	0.0109 (0.0470)	−0.0491 (0.0426)	0.1268 (0.1161)
Age	0.00311^*** (0.00004)	0.00134^*** (0.00002)	0.00178^*** (0.00003)
Female	−0.04720^*** (0.00075)	−0.03003^*** (0.00046)	−0.01718^*** (0.00062)
High school	−0.00528^*** (0.00177)	0.00888^*** (0.00083)	−0.01397^*** (0.00163)
Some college	−0.00005 (0.00178)	0.01482^*** (0.00085)	−0.01457^*** (0.00164)
College degree	0.00885^*** (0.00186)	0.02726^*** (0.00096)	−0.01832^*** (0.00166)
Advanced degree	0.01802^*** (0.00211)	0.03320^*** (0.00118)	−0.01510^*** (0.00183)
White	0.02627^*** (0.00213)	0.01184^*** (0.00118)	0.01499^*** (0.00193)
Black	−0.02582^*** (0.00230)	−0.01105^*** (0.00126)	−0.01415^*** (0.00210)
Hispanic	−0.01754^*** (0.00229)	−0.00482^*** (0.00126)	−0.01230^*** (0.00203)
Number of children	0.01279^*** (0.00035)	0.00661^*** (0.00022)	0.00620^*** (0.00029)
Lives in a city	0.01795^*** (0.00117)	−0.00446^*** (0.00065)	0.02224^*** (0.00103)
State population	−0.00482 (0.03122)	0.01032 (0.00772)	−0.06039 (0.05612)
Observations	609,365	609,365	609,365

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A5

Heterogeneity in the Impact of Immigrant Entrepreneurs across Races of Natives: First Stage Estimates for Blacks

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Generous SCHIP	0.09265^*** (0.00440)	0.02986^*** (0.00238)	0.06280^*** (0.00327)
Age	0.00001 (0.00007)	0.00004 (0.00003)	−0.00004 (0.00006)
Female	0.00017 (0.00142)	0.00013 (0.00071)	0.00005 (0.00116)
High school	−0.00049 (0.00242)	0.00229^* (0.00133)	−0.00278 (0.00201)
Some college	−0.00507^** (0.00252)	0.00230^* (0.00137)	−0.00737^*** (0.00210)
College degree	0.00107 (0.00287)	0.00467^*** (0.00152)	−0.00360 (0.00238)
Advanced degree	0.00084 (0.00344)	0.00235 (0.00180)	−0.00151 (0.00283)
Number of children	0.00112^* (0.00062)	0.00009 (0.00031)	0.00103^** (0.00051)
Lives in a city	0.00309 (0.00213)	0.00175 (0.00121)	0.00134 (0.00174)
State population	0.61485^*** (0.00343)	0.16403^*** (0.00149)	0.45081^*** (0.00284)
Observations	64,163	64,163	64,163

Note: Dependent variable is supply of immigrant entrepreneur (in 100,000s). All models control for demographic characteristics (age, marital status, education, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A6

Heterogeneity in the Impact of Immigrant Entrepreneurs across Races of Natives: Second Stage Estimates for Blacks

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Immigrant entrepreneurs	0.09242^* (0.05191)	0.02171 (0.08435)	0.12605^* (0.06622)
Age	0.00142^*** (0.00008)	0.00038^*** (0.00004)	0.00105^*** (0.00007)
Female	−0.02960^*** (0.00177)	−0.01345^*** (0.00098)	−0.01614^*** (0.00150)
High school	−0.00514 (0.00342)	0.00246^* (0.00132)	−0.00735^** (0.00320)
Some college	−0.00147 (0.00351)	0.00613^*** (0.00139)	−0.00719^** (0.00327)
College	0.00754^* (0.00391)	0.01698^*** (0.00191)	−0.00899^*** (0.00348)
Advanced degree	0.01911^*** (0.00493)	0.02570^*** (0.00285)	−0.00637 (0.00413)
Number of children	0.00388^*** (0.00074)	0.00233^*** (0.00042)	0.00152^** (0.00063)
Lives in a city	−0.00109 (0.00353)	−0.00188 (0.00159)	0.00087 (0.00318)
State population	−0.05595^* (0.03182)	−0.00293 (0.01364)	−0.05658^* (0.02985)
Observations	64,163	64,163	64,163

Note: Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A7

Heterogeneity in the Impact of Immigrant Entrepreneurs across Races of Natives: First Stage Estimates for Whites

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Generous SCHIP	0.02622^*** (0.00156)	0.02212^*** (0.00082)	0.00410^*** (0.00117)
Age	−0.00001 (0.00002)	−0.00000 (0.00001)	−0.00000 (0.00002)
Female	−0.00009 (0.00049)	0.00002 (0.00024)	−0.00010 (0.00040)
High school	0.00018 (0.00123)	0.00033 (0.00063)	−0.00015 (0.00102)
Some college	−0.00002 (0.00124)	0.00042 (0.00063)	−0.00044 (0.00104)
College degree	0.00166 (0.00127)	0.00066 (0.00065)	0.00100 (0.00106)
Advanced degree	0.00149 (0.00138)	0.00086 (0.00070)	0.00063 (0.00115)
Number of children	−0.00028 (0.00022)	−0.00014 (0.00011)	−0.00015 (0.00018)
Lives in a city	0.00393^*** (0.00049)	0.00184^*** (0.00025)	0.00209^***s (0.00040)
State population	0.65092^*** (0.00144)	0.17584^*** (0.00062)	0.47509^*** (0.00122)
Observations	461,397	461,397	461,397

SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A8

Heterogeneity in the Impact of Immigrant Entrepreneurs across Races of Natives: Second Stage Estimates for Whites

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Immigrant entrepreneurs	−0.04320 (0.10143)	0.02171 (0.07292)	0.51066 (0.56062)
Age	0.00349^*** (0.00004)	0.00157^*** (0.00003)	0.00192^*** (0.00004)
Female	−0.05136^*** (0.00091)	−0.03497^*** (0.00057)	−0.01634^*** (0.00078)
High school	−0.00803^*** (0.00258)	0.01112^*** (0.00126)	−0.01905^*** (0.00239)
Some college	−0.00276 (0.00258)	0.01721^*** (0.00128)	−0.01973^*** (0.00240)
College degree	0.00565^** (0.00263)	0.03003^*** (0.00135)	−0.02478^*** (0.00246)
Advanced degree	0.01165^*** (0.00284)	0.03379^*** (0.00155)	−0.02236^*** (0.00257)
Number of children	0.01590^*** (0.00044)	0.00799^*** (0.00028)	0.00797^*** (0.00038)
Lives in a city	0.02021^*** (0.00136)	−0.00470^*** (0.00076)	0.02409^*** (0.00163)
State population	−0.02639 (0.06614)	0.00969 (0.01300)	−0.24279 (0.26639)
Observations	461,397	461,397	461,397

Note: Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A9

Heterogeneity in the Impact of Immigrant Entrepreneurs across Skill Levels of Natives: First Stage Estimates for Low Skilled

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Generous SCHIP	0.04620^*** (0.00167)	0.03038^*** (0.00087)	0.01582^*** (0.00124)
Age	−0.00003 (0.00003)	0.00001 (0.00001)	−0.00003 (0.00002)
Female	−0.00007 (0.00056)	0.00021 (0.00027)	−0.00028 (0.00046)
High school	−0.00047 (0.00110)	0.00064 (0.00054)	−0.00111 (0.00091)
Some college	−0.00085 (0.00111)	0.00082 (0.00054)	−0.00167^* (0.00092)
White	−0.00437^*** (0.00165)	−0.00060 (0.00072)	−0.00376^*** (0.00134)
Black	−0.00721^*** (0.00187)	−0.00213^** (0.00084)	−0.00508^*** (0.00152)
Hispanic	−0.00117 (0.00203)	0.00056 (0.00088)	−0.00173 (0.00165)
Number of children	−0.00000 (0.00025)	0.00012 (0.00012)	−0.00012 (0.00021)
Lives in a city	0.00375^*** (0.00054)	0.00168^*** (0.00028)	0.00207^*** (0.00045)
State population	0.65169^*** (0.00139)	0.17641^*** (0.00060)	0.47528^*** (0.00117)
Observations	406,090	406,090	406,090

Note: Dependent variable is supply of immigrant entrepreneur (in 100,000s). All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A10

Heterogeneity in the Impact of Immigrant Entrepreneurs across Skill Levels of Natives: Second Stage Estimates for Low Skilled

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Immigrant entrepreneurs	0.03144 (0.05516)	−0.04661 (0.04708)	0.18127 (0.13897)
Age	0.00264^*** (0.00004)	0.00102^*** (0.00002)	0.00162^*** (0.00004)
Female	−0.04654^*** (0.00090)	−0.02342^*** (0.00052)	−0.02307^*** (0.00077)
High school	−0.00584^*** (0.00178)	0.00813^*** (0.00083)	−0.01376^*** (0.00163)
Some college	−0.00080 (0.00179)	0.01370^*** (0.00086)	−0.01419^*** (0.00164)
White	0.03208^*** (0.00253)	0.01239^*** (0.00129)	0.02021^*** (0.00230)
Black	−0.02104^*** (0.00272)	−0.01112^*** (0.00137)	−0.00932^*** (0.00250)
Hispanic	−0.01388^*** (0.00270)	−0.00498^*** (0.00136)	−0.00859^*** (0.00242)
Number of children	0.01184^*** (0.00042)	0.00497^*** (0.00024)	0.00690^*** (0.00036)
Lives in a city	0.02034^*** (0.00132)	−0.00425^*** (0.00070)	0.02441^*** (0.00119)
State population	−0.01453 (0.03602)	0.00996 (0.00842)	−0.08193 (0.06607)
Observations	406,090	406,090	406,090

Note: Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A11

Heterogeneity in the Impact of Immigrant Entrepreneurs across Skill Levels of Natives: First Stage Estimates for High Skilled

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Generous SCHIP	0.04370^*** (0.00251)	0.02993^*** (0.00130)	0.01377^*** (0.00185)
Age	0.00000 (0.00004)	−0.00001 (0.00002)	0.00001 (0.00003)
Female	0.00047 (0.00082)	−0.00023 (0.00039)	0.00070 (0.00067)
College degree	−0.00021 (0.00088)	−0.00019 (0.00042)	−0.00002 (0.00072)
White	−0.00965^*** (0.00298)	−0.00237^* (0.00128)	−0.00728^*** (0.00247)
Black	−0.01125^*** (0.00336)	−0.00238 (0.00148)	−0.00887^*** (0.00277)
Hispanic	0.00012 (0.00385)	0.00142 (0.00164)	−0.00130 (0.00320)
Number of children	−0.00093^** (0.00036)	−0.00049^*** (0.00017)	−0.00044 (0.00030)
Lives in a city	0.00487^*** (0.00090)	0.00240^*** (0.00045)	0.00247^*** (0.00074)
State population	0.68288^*** (0.00205)	0.18323^*** (0.00087)	0.49965^*** (0.00176)
Observations	203,275	203,275	203,275

SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A12

Heterogeneity in the Impact of Immigrant Entrepreneurs across Skill Levels of Natives: Second Stage Estimates for High Skilled

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Immigrant entrepreneurs	0.03144 (0.05516)	−0.04661 (0.04708)	0.18127 (0.13897)
Age	0.00412^*** (0.00007)	0.00189^*** (0.00004)	0.00223^*** (0.00005)
Female	−0.04593^*** (0.00138)	−0.04148^*** (0.00093)	−0.00449^*** (0.00109)
College degree	−0.00477^*** (0.00155)	−0.00353^*** (0.00108)	−0.00125 (0.00119)
White	0.01376^*** (0.00394)	0.00908^*** (0.00245)	0.00503 (0.00359)
Black	−0.03556^*** (0.00437)	−0.01289^*** (0.00273)	−0.02224^*** (0.00404)
Hispanic	−0.02256^*** (0.00446)	−0.00520^* (0.00289)	−0.01726^*** (0.00361)
Number of children	0.01358^*** (0.00068)	0.00855^*** (0.00048)	0.00504^*** (0.00052)
Lives in a city	0.00794^*** (0.00244)	−0.00501^*** (0.00159)	0.01288^*** (0.00202)
State population	0.01691 (0.06453)	0.01176 (0.01675)	−0.01816 (0.12021)
Observations	203,275	203,275	203,275

Note: Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A13

Heterogeneity in the Impact of Immigrant Entrepreneurs across Natives by Parents’ Origin: TSLS Estimates

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
At least one foreign born parent
Entrepreneurial propensity of natives:	0.0935	0.0357	0.0578
Immigrant entrepreneurs	−0.1659 (0.1109)	−0.1791 (0.1286)	−0.1510 (0.1945)
First stage F stat	139.94	144.049	369.79
Observations	64,475	64,475	64,475
No foreign born parents
Entrepreneurial propensity of natives:	0.0997	0.0350	0.0647
Immigrant entrepreneurs	0.0369 (0.0514)	−0.0349 (0.0454)	0.1834 (0.1321)
First stage F stat	984.07	1622.47	194.04
Observations	544,890	544,890	544,890

ASEC, Annual Social and Economic Supplement; CPS, Current Population Survey; TSLS, two stage least squares.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A14

Results from Nonlinear Models

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives:	0.0950	0.0345	0.0606
Probit
Immigrant entrepreneurs	0.0064^*** (0.0019)	0.0068^*** (0.0023)	0.0035^* (0.0019)
Observations	609,365	609,365	609,365
IV probit
Second stage:
Immigrant entrepreneurs	0.0067 (0.0475)	0.0083 (0.0459)	0.0037 (0.1116)
First stage F-stat	2101.30	2697.76	1374.92
Observations	609,365	609,365	609,365

Note: Estimates are marginal effects calculated at means. Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A15

Results using Immigrant Entrepreneurship Rate as the Key Explanatory Variable

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Entrepreneurial propensity of natives	0.0950	0.0345	0.0606
LPM
Immigrant entrepreneurship rate	0.00042^** (0.00020)	0.00027 (0.00027)	0.00018 (0.00019)
Observations	609,365	609,365	609,365
TSLS
Second stage
Immigrant entrepreneurship rate	0.0029 (0.0125)	0.0299 (0.0266)	0.0089 (0.0082)
First stage F-stat	92.93	25.20	174.76
Observations	609,365	609,365	609,365

Note: Dependent variable is binary indicator for being an entrepreneur. Immigrant entrepreneurship rate is the percentage of immigrants that report as being self-employed. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects.

LPM, linear probability model; TSLS, two stage least squares.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A16

Effect of SCHIP on Entry of Immigrants into Entrepreneurship

	Entry into entrepreneurship (measured as a proportion)	Entry into entrepreneurship (measured as count)
Sample mean/proportion	0.007	1,324.39
SCHIP	0.0090^*** (0.0001)	0.0156^*** (0.0012)
Observations	609,365	609,365

Note: Estimates represent the effect of generous SCHIP on annual entry of immigrants into entrepreneurship. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

SCHIP, State Children's Health Insurance Program.

* p < 0.10.

** p < 0.05.

*** p < 0.01.

Table A17

Results with Separate Controls for Immigrant and Native Population

Outcome	Any self-employment	Incorporated self-employment	Unincorporated self-employment
Immigrant entrepreneurs	0.01247 (0.0258)	0.5644 (0.3684)	−0.0130 (0.0225)
First stage F-stat	7,012.38	72.25	8,873.64
Observations	609,365	609,365	609,365

Note: Dependent variable is binary indicator for being an entrepreneur. The supply of immigrant entrepreneurs is expressed in 100,000s. All models control for demographic characteristics (age, marital status, education, race, number of children, and city residence status), state immigrant population (millions), state native population (millions), state fixed effects, and year fixed effects. Robust standard errors are reported in parentheses.

* p < 0.10.

** p < 0.05.

*** p < 0.01.