Open ndavis4904 opened 2 years ago
The variables for mhv are in the code supplied for Lab 5 (see the code chunk below). We want to know about change so we are using both 00 and 10.
Note how we are creating mhv.00 and mhv.10:
mhv.00 <- d$mhmval00 * 1.28855
mhv.10 <- d$mhmval12
d <- select( d, tractid,
mhmval00, mhmval12,
hinc00,
hu00, vac00, own00, rent00, h30old00,
empclf00, clf00, unemp00, prof00,
dpov00, npov00,
ag25up00, hs00, col00,
pop00.x, nhwht00, nhblk00, hisp00, asian00,
cbsa, cbsaname )
d <-
d %>%
mutate( # percent white in 2000
p.white = 100 * nhwht00 / pop00.x,
# percent black in 2000
p.black = 100 * nhblk00 / pop00.x,
# percent hispanic in 2000
p.hisp = 100 * hisp00 / pop00.x,
# percent asian in 2000
p.asian = 100 * asian00 / pop00.x,
# percent high school grads by age 25 in 2000
p.hs = 100 * (hs00+col00) / ag25up00,
# percent pop with college degree in 2000
p.col = 100 * col00 / ag25up00,
# percent employed in professional fields in 2000
p.prof = 100 * prof00 / empclf00,
# percent unemployment in 2000
p.unemp = 100 * unemp00 / clf00,
# percent of housing lots in tract that are vacant in 2000
p.vacant = 100 * vac00 / hu00,
# dollar change in median home value 2000 to 2010
pov.rate = 100 * npov00 / dpov00,
## percent 25 and up in population
p.25andUp = 100 * ag25up00 / pop00.x)
adjust 2000 home values for inflation
mhv.00 <- d$mhmval00 * 1.28855
mhv.10 <- d$mhmval12
# change in MHV in dollars
mhv.change <- mhv.10 - mhv.00
# drop low 2000 median home values
# to avoid unrealistic growth rates.
#
# tracts with homes that cost less than
# $1,000 are outliers
mhv.00[ mhv.00 < 1000 ] <- NA
# change in MHV in percent
mhv.growth <- 100 * ( mhv.change / mhv.00 )
d$mhv.00 <- mhv.00
d$mhv.10 <- mhv.10
d$mhv.change <- mhv.change
d$mhv.growth <- mhv.growth
Also note that a five-year ACS variable pulled from 2012 is centered at 2010, (years 2008-2012), so it can be thought of conceptually as a 2010 variable.
What variable do we use for median home value for 2010? I had this problem in lab 5 and found what I felt was the workaround by using the 2012 ACS data for 2008 to 2012, but now am questioning whether that is the most appropriate choice. I have been using the variable
mhmval00
(andmhmval12
previously). Is there a better option that I have passed over? Or would this be the reason for the creation ofpov.rate
? Thanks