Case Study:

Impact of new housing projects in New York State Municipalities.

VARIABLES:

     State  Code
     County  Code
     Expenditure per person
     Wealth per person
     Population
     Percent intergovernmental
     Density
     Mean Income per person
     id #  (for matching)
     Growth rate

Dataset : NYM http://www.rci.rutgers.edu/~cabrera/586/nym VARIABLE NAMES:

"ST" "CO" "EXPEN" "WEALTH" "POP"  "PINTERG" "DENS"
"INCOME"  "ID"      "GROWR"

NY Municipalities data

     TOWNS OF INTEREST:

        ST CO EXPEN WEALTH  POP PINTERG DENS INCOME ID GROWR
WARWICK 36 33   237  78908 16225  24.7  170  19044 8730 30.3
MONROE  36 33   159  55067  9338   8.8  599  16726 5420 30.0
TUXEDO  36 33   926 155034  2328   6.1   52  30610 8400  2.5

QUESTION : PREDICT EXPENDITURE FOR YEARS 2005 and 2025

     Year  POP WEALTH PINTERG DENS INCOME

     2000 16225   78908  24.7  170 19044
     2025 31033   89000  26.0  325 20000

     2000  7750   55067   8.8  599 16726
     2025 12413   60000  10.1  959 18000

     2000  2317  155034   6.1   52 30610
     2025 29246  115000   7.0  656 25000

GRAPH OF EXPENDITURES VS POPULATION IN THE LOG SCALE

plot(log(EXPEN)~log(POP),data=nym,axes=F,xlab="POP",ylab="EXPEN")

axis(1, log(c(1000,10000,30000,100000)),c("1K","10K","30K","100K"))

axis(2,log(c(100,300,1000)),c(100,300,1000))

box()

lines(smooth.spline(log(nym$POP),log(nym$EXPEN)),col=2,lwd=3)