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Source: City of El Paso Planning Department
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HOUSING & COMMUNITY DEVELOPMENT PLANNING
TOPICS
• ALLOCATION OF LAND• HOUSING • LOCATION, LOCATION AND LOCATION• REAL ESTATE ECONOMICS• NEIGHBORHOOD CHANGE• CLASS QUESTIONS
EL PASO'S LAND BY TYPE
71%
15%
14%
RESIDENTIAL
COMMERCIAL
INDUSTRIAL
Source: City of El Paso Planning Department
EL PASO'S LAND TOTAL
RESIDENTIAL
COMMERCIAL
INDUSTRIAL
OTHER
FRANKLIN
VACANT
Source: City of El Paso Planning Department
HOUSING AS A BUNDLE
ACCESSLOCATION
AMENITIES
LANDSOCIAL
NETWORK
ASSET
SHELTER
SCHOOLS
CREDIT
HOUSING
ALONSO’S MODEL OF URBAN LAND MARKETS
• Paradox: the poor live close to the center and the rich in the suburbs.
• There are two important attributes of buying land ( the land itself and location)
• The above paradox can be explained by the trade-off the household made between commuting (distance) and cheaper land
• Distance is a proxy to represent accessibility (to work) costs, then poor people tend to locate close to the center of the city.
THE REAL ESTATE MARKET
• Real estate as space (without a building) and as an asset (with a building)
• The difference between endogenous factors and exogenous factors. What kind of factor is planning?
• Housing is affected by micro forces (location specific) as well as macro forces (those that affect the profitability or use)
• Why are homes close to the mountain worth more than those away from the mountain?
VALUING LOCATION: Mountain View
eNDphcP phc
Sq feet constBedroomsBathroomsYear built
DDistance fromThe mountain
Value ofUndevelopedland
NNeighborhoodTASK scores
EP REAL ESTATE
Dependent Mth Rsq D.f. F Sigf b0 b1
VALUE LIN .615 44 70.27 .000 68529.2 3.0168
VALUE PROPERTY
SQ FEET
2000001000000-100000
700000
600000
500000
400000
300000
200000
100000
0
EP REAL ESTATE MARKET
Dependent Rsq d.f. F Sigf b0 b1
VALUE .710 44 107.48 .000 -32991 71.8823
VALUE PROPERTY
TOTAL LIVING AREA
800070006000500040003000200010000
500000
400000
300000
200000
100000
0
EP REAL ESTATE MARKETCoefficientsa
-30444.0 38989.283 -.781 .440402.122 388.677 .077 1.035 .30749.891 7.254 .585 6.878 .000
18051.798 16822.841 .150 1.073 .290-13441.5 14663.832 -.118 -.917 .365
1.866 .305 .485 6.127 .00018609.941 17298.867 .068 1.076 .289
(Constant)ageTotal living areaBATHSbedroomsSQFEETWEST
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: value proprertya.
Model Summary
.942a .887 .870 39646.89384Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), WEST, Total living area, age,SQFEET, bedrooms, BATHS
a.
EP REAL ESTATECoefficientsa
3.329 .772 4.311 .000-.010 .060 -.010 -.167 .868.756 .117 .572 6.447 .000.245 .072 .278 3.407 .002.263 .145 .166 1.812 .078.131 .106 .071 1.233 .225
(Constant)LNAGELNTLALNSQFLNBTHWEST
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: LNVALUEa.
Model Summary
.948a .899 .887 .24790Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), WEST, LNSQF, LNAGE, LNTLA,LNBTH
a.
SOME ELASTICITIESCoefficientsa
2.312 .599 3.860 .0001.210 .080 .916 15.107 .000
(Constant)LNTLA
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: LNVALUEa.
Coefficientsa
4.837 .709 6.825 .000.715 .078 .811 9.211 .000
(Constant)LNSQF
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: LNVALUEa.
Coefficientsa
12.441 .499 24.938 .000-.318 .141 -.323 -2.260 .029
(Constant)LNAGE
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: LNVALUEa.
HUD’S MODEL OF NEIGHBORHOOD CHANGE
STABLEvalues and incomes
In balanceDeclining: falling valuesImproving: rising values
1Healthy
2Incipient decline
3Clearlydeclining
4Acceleratingdecline
5Abandoned
NEIGHBORHOOD CHANGE
COLLECTIVE ACTION
INSTITUTIONAL ACTIONS
INDIVIUDAL ACTIONS