clute institute: new orleans international academic conference 2011: zoning effect on housing option...

8/7/2019 Clute Institute: New Orleans International Academic Conference 2011: Zoning Effect on Housing Option Value

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Zoning Effect on HousingOption Value

PRATHAMESH MUZUMDAR

ILLINOIS STATE UNIVERSITY



1. What is Zoning.

• Zoning is defined as land underplanned use.

• Zoning segregates different land fordifferent uses.

• Zoning differentiates

neighbourhood into different parcelsand assigns number of lots to certainparcel.



2. Types of Zoning.

• Euclidian.

• Performance.

• Incentive.

• Design Based.



TYPES OF ZONING Euclidean Zoning.Started in village of Euclid, Ohio.Land segregation- Geographical and

dimensional standards.Ex- Small towns, tourist centers, remote

locations. Performance Zoning.

Land Segregation- Proposed developmentprojects.Ex- Corporate parks, hospitals.



TYPES OF ZONINGIncentive Zoning.

First Implemented in New York and Chicago.

Land Segregation- High density is allocated toa certain piece of a land or area.

Ex- Multi storey buildings, towers.

Design Based Zoning.Newest type of zoning which considers the

factors of urban sprawl, deterioration of

historic neighborhoods etc.



3. Advantages of Zoning.

Segregates land as per its use.

Prevents new developments from interfering

into existing residential and business property.Preserves special characteristics of a area.

Ex- Public parks, historic architecture.



Disadvantages of Zoning.Failure to increase efficiency for a proportion of land to its use.

Urban cities, metropolitan areas etc wheremixed zoning is carried out.

Rural areas, low density towns with low amountof mixed zoning are least affected by

disadvantages of zoning.



Types of Housing Price.(Value)Assessed Value.

Assessed by the township assessor.

Market Value.

Market Value= 3 * Assessed Value.

Option Value.

Option value = Market Value with respect to

certain time period.



1. What is meant by option value andhow is it different from the real

housing priceMarket value = 3 * Assessed value.

Housing option value is the change in market value

that takes place due to variations occurring in thezoning characteristics.

Zoning characteristics may directly or inversely effectthe price of residential property.



Types of RegressionModels.Simple Linear Regression analysis.

Multiple linear Regression analysis.



Hedonic Model

Revealed preference method of estimatingdemand or value.

Preferred Method:

1. It decomposes the subject into its

constituent characteristics . Ex- House – No

of bedrooms, bathrooms, sq footage area.

2. It estimates the role of each characteristic

with respect to the final price.



Working Model

Log (value)= f(R1 A, R1 B, R2, S2, log(lotsqft),log(lotdimb), log(lotdima), log(Totbldgft),log(bathroom), Age, Age^2, condition 2, Tax

rate)

Dependent Variable: Log(value)

Independent Variable:

1. Zoning Characteristics.

2. Physical Characteristics.



Definition of Variable ZONING VARIABLE R1 A Single Family Residence District. Equals 1 if zoned R1 A

otherwise 0. R1 B Single Family Residence District and two family residence

district. Also multifamily dwellings are permitted. Equals 1 if zoned R1 B

otherwise 0. R2 Mixed Residence District. Single, two family and multi

family residence district.Equals 1 if zoned R2 otherwise 0.

S2 Public lands and Institution District. Equals 1 if zoned S2otherwise 0.

PHYSICAL VARIABLE lotdima Lot width/ frontage in feet lotdimb Lot depth in feet. lotsqft Lot square feet in feet. Age Age of the building included in the property in years. Age^2 Totbldgft Total building square feet in feet

Bathrooms No of bathrooms occupied by the building. Condition Condition of the building.



Zoning Variable

R1 A

Primarily single familyhousing.

No multi family dwelling.

A single allotted to a singlefamily.

Four dwelling per unit acre.

Lot size are bigger.



Zoning Variable

R1 B

Primarily single familyhousing.

Multi family dwelling- Smallerin size.

A single lot can have multiplehouses belonging to multiple

family.Six dwelling per unit acre.

Lot size are smaller.



Zoning Variable

S2

Public lands and institutiondistrict.

Fewer houses exist buildbefore implementation of zoning.

New regulations don’tpermit building newstructures.

Old houses are allocated tospecial cases



Data Presentation.

Assessed Value Data: Year 2010

Zoning Characteristics: 1990-2010.

Physical Characteristics: 1990-2010.

Data Collection:

Township Assessor Office.

City of Normal office.



Hypothesis

HO =More than 50% of variation in the housingprice

can be explained by the zoning andphysical

variables.

HA =Failure of zoning and physical variables toexplain

more than 50% variation in the housingprice.



HYPOTHESIS TESTING

METHODRegression Analysis- Hedonic Model.

F Test- To test the significance.

t Test – To test the influence and significance of

variables.

R2 - Explanation of variation by variables.



Results

Distribution Chart

Assessed Value- Log(value)

Dependent Variable.

Bell shaped unimodal structure. The mode lie at therange of 9 to 12, at housing price range of

$70000 to $360000.



Zoning Characteristics

R1 A R1 B

R2 S2

Logical value- 0 or 1.



Physical Characteristics

Log(lotsqfeet) Log(lotdimb)

Log(totbldgft) Log(lotdima)

Their distribution charts are found to be unimodal with bell shaped distributions.



Predicted Plot:

Positive linear relationship between the actual

log(value) with predicted log(value).

4

6 8

1 1

g(

u 1 t f c a s h )

A c t u a l



t- Test

Click to edit Master text stylesSecond level● Third level● Fourth level● Fifth level



Results

R Square

0.8952- 89.52 % 0f variation in the dependent

variable can be explained by the variations in

the independent variables.

F Ratio

Fit Model- 402.38

Fcrit - 1.72



Zoning Variables.

R1 A- Significant at 10% significance level.

t value- 13.26-A house zoned R1 A will have a

13.26% increase in option price value.R1 B- Significant at 10% significance level.

t value- 12.08-A house zoned R1 B will have a

12.08% increase in option price value.

R2 - Significant at 10% significance level.

t value- 9.67- A house zoned R2 will have a

9.67% increase in option price value.



Zoning Variable

S2 – Significant at 10% significance level.

t value-(50.59) – A house zoned S2 will have

50.59% decrease in value.



Physical Variable

Log(lotsqft)-Lot square feet- Significant at 10%

significance level.

t value- 3.42- Every 1 feet increase in lot

square feet will result in 3.42% increase

in price.

Log(lotdimb)-Lot depth- Significant at 10%

significance level.

t value- (2.37)- Every increase in lot

depth reduces the price of the house by

2.37%.



Physical Variables

Age- Significant at 10% significance level.

t value- (3)- Increase in the age of housereduces

its price by 3%. Every 5 years.

Tax Rate- Significant at 10% significance level.

t value- 2.41- Increase in the tax rate increases

the price of the house by 2.41%



Results

At R square of 0.89, the 89% changes in thehousing price can be explained by the variationstaking place in the independent variables at 10%significant level for the all considered zones.

All physical variables except for bathrooms andtotal building square feet are significant at 10%

significance level.



Conclusion

Null hypothesis cannot be rejected as the R Square

exceeds 50%.

Significance of model is proved by the F Value.Fcalc Fcrit˃

402.38 1.72˃



Multivariate Correlation

Matrix

Multivariate Cor

Log(u1tfcash)

Click to edit Master text styles

Second level● Third level● Fourth level● Fifth level



Results

Matrix 1

R1 A and R1 B show high collinearity.

Matrix 2Age and Condition show high collinearity.

Matrix 3

lot square feet shows high collinearity with lot width andlot depth.



ConclusionR1 A and R1 B

R1 A and R1 B both together consists of 8752 single family and multiple familyhomes. 73% of total observations.

Age and condition.

Age – Price of the house stabilizes after certain years.

Condition- Depreciation occurs every year.

Lot square feet, lot depth and lot width.

Lot depth- City of Normal- Regulation for single

family houses. Ex Tornado.

Lot Width- Exact shape of the lot.



Overall Conclusion

Null hypothesis is proved.

R square- 0.89

Significance

F value- 402.38

Influence of zoning by Hedonic model.



Question and Answer.

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