reg.dat <- read.csv("~/Dropbox (ASU)/Political Economy of NP Startups/data-and-analysis/data-prepped/RegressionData.csv")
pander(head(reg.dat))
Table continues below
| 1 |
111667771 |
Religion |
0.02291 |
0.03907 |
140221 |
0.8599 |
| 2 |
111667771 |
Religion |
0.02291 |
0.03907 |
140221 |
0.8599 |
| 3 |
112405741 |
Sports |
0.1316 |
0.2773 |
47835 |
0.4931 |
| 4 |
112405741 |
Sports |
0.1316 |
0.2773 |
47835 |
0.4931 |
| 5 |
112411617 |
Human Services |
0.08865 |
0.04206 |
85714 |
0.8557 |
| 6 |
112411617 |
Human Services |
0.08865 |
0.04206 |
85714 |
0.8557 |
Table continues below
| 0.003371 |
268 |
0.9846 |
-0.7308 |
-0.5122 |
-1.23 |
-0.4577 |
| 0.003371 |
268 |
0.9846 |
-0.6698 |
-0.4209 |
-1.23 |
-0.4577 |
| 0.5219 |
1919 |
0.6683 |
0.6721 |
0.5889 |
1.564 |
-0.04123 |
| 0.5219 |
1919 |
0.6683 |
0.6721 |
0.5889 |
1.564 |
-0.04123 |
| 0.9141 |
2396 |
0.8813 |
-0.6054 |
-0.6911 |
-0.101 |
-1.003 |
| 0.9141 |
2396 |
0.8813 |
-0.729 |
-0.7828 |
-0.101 |
-1.003 |
| New York-Newark-Jersey City, NY-NJ-PA |
2.612 |
0.7237 |
| New York-Newark-Jersey City, NY-NJ-PA |
2.612 |
0.7237 |
| New York-Newark-Jersey City, NY-NJ-PA |
0.5226 |
0.837 |
| New York-Newark-Jersey City, NY-NJ-PA |
0.5226 |
0.837 |
| New York-Newark-Jersey City, NY-NJ-PA |
391.7 |
778.7 |
| New York-Newark-Jersey City, NY-NJ-PA |
391.7 |
778.7 |
- unemp - unemployment for NPO census tract
- poverty - poverty rate for NPO census tract
- medinc - median income for NPO census tract
- ownerocc - Owner Occupancy for NPO census tract
- black - percentage black for NPO census tract
- h.density - housing density for NPO census tract
- hs - High School graduation rate for NPO census tract
- BMS1 - Vulneravility factor for Board Member census tract
- BMS2 - Urbanity factor for Board Member census tract
- NPO1 - Urbanity factor for Nonprofit census tract
- NPO2 - Urbanity factor for Nonprofit census tract
- cbsaname - MSA for Nonprofit
- dist.to.npo - Average distance for board members to Nonprofit
- ave.dist - Average distance between board members
reg1a <- (lm(BMS1~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) ,data=reg.dat))
reg1b <- (lm(BMS1~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) +factor(labels),data=reg.dat))
reg1c <- (lm(BMS1~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) +factor(cbsaname),data=reg.dat))
reg1d <- (lm(BMS1~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) +factor(labels)+factor(cbsaname),data=reg.dat))
stargazer(reg1a, reg1b, reg1c, reg1d,type="text",title ="Board Member Community Vulnerability",
keep.stat=c("n", "adj.rsq"),
omit=c("labels", "cbsaname"),
covariate.labels=c("Nonprofit Neighborhood Vulneraility",
"Nonprofit Neighborhood Urbanity",
"Average Distance of Board Members to NPO (log)",
"Average Distance Between Board Members (log)"),
add.lines=list(c("NTEE Code","", "Yes", "","Yes"), c("MSA?", "", "", "Yes", "Yes")))
##
## Board Member Community Vulnerability
## ======================================================================================
## Dependent variable:
## ---------------------------------------
## BMS1
## (1) (2) (3) (4)
## --------------------------------------------------------------------------------------
## Nonprofit Neighborhood Vulneraility 0.341*** 0.326*** 0.290*** 0.275***
## (0.003) (0.003) (0.003) (0.003)
##
## Nonprofit Neighborhood Urbanity -0.050*** -0.051*** -0.015*** -0.016***
## (0.003) (0.003) (0.003) (0.003)
##
## Average Distance of Board Members to NPO (log) -0.030*** -0.031*** -0.034*** -0.035***
## (0.004) (0.004) (0.004) (0.004)
##
## Average Distance Between Board Members (log) 0.017*** 0.016*** 0.019*** 0.018***
## (0.004) (0.004) (0.004) (0.004)
##
## Constant -0.026*** -0.012 0.120*** 0.133***
## (0.005) (0.020) (0.016) (0.025)
##
## --------------------------------------------------------------------------------------
## NTEE Code Yes Yes
## MSA? Yes Yes
## Observations 104,483 104,483 104,483 104,483
## Adjusted R2 0.137 0.146 0.164 0.172
## ======================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
reg2a <- (lm(BMS2~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) ,data=reg.dat))
reg2b <- (lm(BMS2~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) +factor(labels),data=reg.dat))
reg2c <- (lm(BMS2~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) +factor(cbsaname),data=reg.dat))
reg2d <- (lm(BMS2~NPO1+NPO2+log(dist.to.npo)+log(ave.dist+1) +factor(labels)+factor(cbsaname),data=reg.dat))
stargazer(reg2a, reg2b, reg2c, reg2d,type="text",title ="Board Member Community Urbanity",
keep.stat=c("n", "adj.rsq"),
omit=c("labels", "cbsaname"),
covariate.labels=c("Nonprofit Neighborhood Vulneraility",
"Nonprofit Neighborhood Urbanity",
"Average Distance of Board Members to NPO (log)",
"Average Distance Between Board Members (log)"),
add.lines=list(c("NTEE Code","", "Yes", "","Yes"), c("MSA?", "", "", "Yes", "Yes")))
##
## Board Member Community Urbanity
## ======================================================================================
## Dependent variable:
## ---------------------------------------
## BMS2
## (1) (2) (3) (4)
## --------------------------------------------------------------------------------------
## Nonprofit Neighborhood Vulneraility -0.038*** -0.043*** 0.021*** 0.016***
## (0.003) (0.003) (0.003) (0.003)
##
## Nonprofit Neighborhood Urbanity 0.250*** 0.240*** 0.173*** 0.166***
## (0.003) (0.003) (0.003) (0.003)
##
## Average Distance of Board Members to NPO (log) -0.007 -0.008* 0.001 0.0002
## (0.004) (0.004) (0.004) (0.004)
##
## Average Distance Between Board Members (log) 0.031*** 0.028*** 0.024*** 0.022***
## (0.004) (0.004) (0.004) (0.004)
##
## Constant -0.099*** -0.202*** -0.463*** -0.524***
## (0.005) (0.022) (0.017) (0.027)
##
## --------------------------------------------------------------------------------------
## NTEE Code Yes Yes
## MSA? Yes Yes
## Observations 104,483 104,483 104,483 104,483
## Adjusted R2 0.067 0.074 0.110 0.115
## ======================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01