Residential Location Choices and Household Activity Engagement

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Residential Location Choices and Household Activity Engagement. 1/14/2013 Roger Chen, Steven Gehrke , Yunemi Jiang, Jenny Liu and Kelly Clifton. O regon M odeling C ollaborative. Introduction. A relationship exists between where we live and what we do. - PowerPoint PPT Presentation

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Residential Location Choices and Household Activity Engagement

Residential Location Choices and Household Activity Engagement

1/14/2013

Roger Chen, Steven Gehrke, Yunemi Jiang, Jenny Liu and Kelly Clifton

1

Oregon

Modeling

Collaborative

Introduction

A relationship exists between

where we live and what we do

Different Location type choices

Lead to different activity engagement

What is the relationship between

where we live and how households

spend their time?

Overview of Study

This study is concerned with loocation at ther elatopnsiip beween where wee vive and how we spend out time

Data on Activity engagement is nucours; as a the alocation of time is distilled

Estimate models of choice to look at connection

3

Study Area and Distribution of Residential Area-Types

4

5

Major Urban Center

Households within five miles of 50,000 people and within a mile of 2,500 people, where the majority of households are within an MPO.

Urban near Major City Household with 2,500 people within one mile of the residential location, that is also within 15 miles of 50,000 people.

Rural near Major City

Household that is immediately surrounded by an area of less than 2,500 people, but is within 15 miles of 50,000 people.

Isolated City

Household is within two miles of 2,500 people and is more than 15 miles away from 50,000 people.

Rural

Household is more than two miles away from 2,500 people and more than 15 miles away from 50,000 people.

Area-Type Distribution of Households in Sample

Major Urban CenterUrban near Major CityRural near Major CityIsolated CityRural0.12080.528000000000000020.14110.11149.8699999999999996E-2

6

Tenure-Housing Type Distribution of Sample

Housing Tenure

Rent

Own

83.64%

16.36%

Single-

Family

Unit

Duplex

Unit

Multi-

Family

Unit

Single-

Family

Unit

Duplex

Unit

Multi-

Family

Unit

96.7%

1.09%

2.21%

36.65

13.17%

50.18%

Rent

Own

SF

DPLX

SF

MF

DPLX

83.64055299539170116.359447004608295

36.65492957746479213.16901408450704250.176056338028175

96.7011019283746551.08815426997245182.2107438016528924

Why we segment into lifestyle classes

Control for heterogeneity

Based on classifications found in the literature

7

8

Household Segmentation

Single Households

Household Size

Non-Single Households

Age >=

65 yrs.

Age <

65 yrs.

with Children

(01With Children

Segment :6

All Adults >= 65 yrs.

Segment :7

Related Adults

Household ( 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 6521932536600521367462732369

Number of Households

Lifecycle Segments within the OHAS Sample

11

Urban Area-Type

Major Urban CenterSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.146830825353397170.103312302839116720.196666666666666660.124760076775431860.113228089275993470.105531643551729630.14774166314900802Urban near Major CitySingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.529411764705882360.632492113564668720.545000000000000040.57005758157389630.563690800217746310.501036186832456540.41705360911777123Rural near Major CitySingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.116279069767441868.7539432176656148E-20.126666666666666689.9808061420345484E-20.126565051714752320.169615813805196890.18151118615449557Isolated CitySingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.132238942088463290.102523659305993697.166666666666667E-20.122840690978886750.103973870440936310.107125777140124350.13170113972140143RuralSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 657.523939808481532E-27.4132492113564666E-20.068.253358925143954E-29.2542188350571583E-20.116690578670492580.12199240185732377

Lifecycle Segments within the OHAS Sample

12

Household Structure Type

Single-FamilySingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.670932358318098720.642433820624259130.772575250836120440.735124760076775410.90936309199782250.898835168342109410.8994932432432432Duplex/TownhomeSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 653.8391224862888484E-25.8870011853022521E-23.8461538461538464E-28.253358925143954E-22.3679912901469789E-21.7871389819690442E-21.3091216216216216E-2Building with 3+ ApartmentsSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.196983546617915890.244172263927301460.137123745819397990.145873320537428024.0827436037016877E-24.7231530237753311E-23.4628378378378379E-2Mobile HomeSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 659.3692870201096887E-25.4523903595416832E-25.1839464882943144E-23.6468330134357005E-22.6129559063690799E-23.6061911600446785E-25.2787162162162164E-2

Lifecycle Segments within the OHAS Sample

13

Tenure

Own or MortgagedSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.772042028323435380.645594626629790610.729549248747913160.664107485604606530.861626637554585130.906958187041174590.9611158072696534RentedSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.227957971676564650.354405373370209390.270450751252086790.335892514395393470.138373362445414849.3041812958825409E-23.888419273034658E-2

Lifecycle Segments within the OHAS Sample

14

Average Household Residents by Work-Status

WorkersSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.550000000000000040.91.580.991.841.570.78StudentsSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.260.261.171.661.830.260.23RetiredSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.560000000000000050.050.320.210.060.341.26HomemakersSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.0100.087.0000000000000007E-20.160.060.04

Average per Household

Lifecycle Segments within the OHAS Sample

15

Average Household Vehicle/Bike Availability

BikesSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.690.771.411.812.581.330.61Vehicles per License HolderSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 651.10000000000000010.991.941.362.272.112.0699999999999998VehiclesSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 651.12000000000000011.12000000000000012.211.642.47000000000000022.462.14

Average per Household

Lifecycle Segments within the OHAS Sample

16

Average Household Income

Average Household IncomeSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 6540081.37999999999742632.9548925.3349311.179765.7877910.28999999999461377.33

Slide about Factor Analysis

17

18

Cut-off at < 1.0

Principal Component Extraction

7 Factors

59.3% Variance Explained

Factor Analysis of Time Allocated per Household

Factor 1 (Work): Strongly and positively correlated

with work activities and negatively correlated with

in-home activity allocation.

Factor 2 (Routine Out-of-Home Activities): strongly

correlated with activity types that are suggestive

of routine activity patterns or activities.

Factor 3 (School Travel): This third factor is characterized

strongly by school related activities. Although passenger

pick-up/drop-off is not specifically identified as being

student-related (student pick-up/drop-off), the bundling

with school activities suggests this may be the case.

Factor 4 (Eating and Recreation): general out-of-home social

activities that are strongly correlated with eating and recreation.

Factor 5 (Work with Errands): bundling between work and

out-of-home errands; suggests that the work

activity may be an anchoring activity in trip-chaining.

Factor 6 (Specialty Shopping and Civic/Religious): bundling between

civic/religious activities and specialty shopping.

Factor 7 (Personal Activities and Civic/Religious): similar to the sixth

factor and suggests a bundling of civic/religious activities

with personal activities.

19

Original Slide

20

Factor LabelPercent VarianceExplainedInfluencing Activities (Time Allocated per Household BOLD: Factors > 0.6)Work (out-of-home)12.6%(-) Home(+) Working from Home(+) Work/Work-relatedRoutine Out-of-Home Activities9.3%(-) Work/Work-related (+) Routine Shopping, HH Errands(+) Personal Business(+) Eating (Out-of-Home)(+) VisitSchool and School-Related Travel7.9%(-) Work/Work-Related(+) Transfer/Drop-off/Pick-up (Travel)(+) Class/Class-Related (School)Eating and Recreation7.6%(+) Recreation/Entertainment(+) Eating (Out-of-Home)(-) Healthcare(-) VisitWork at Home with Errands7.4%(-) Working at Home(+) Work/Work-related(+) Transfer/Drop-off/Pick-up (Travel)(+) Eating (Out-of-Home)Specialty Shopping and Civic/Religious7.3%(+) Civic/Religious(+) Transfer/Drop-off/Pick-up (Travel)(+) Special ShoppingPersonal Activities and Civic/Religious7.2%(+) Personal Business(-) Working at Home(+) Civic/Religious

(Costello & Osborne, 2005) BOLD ARE >0.6

>.8 strong

>.7 moderate

>.4 - low

20

Model Specification

21

Model Specification

(h)

(t)

Assumptions:

)

)

22

Original Slide

Model Estimation

N = Total Number of Households

Likelihood Function

1 if combination TH is chosen by observation n and 0 otherwise.

A Full- Information Maximum Likelihood (FIML) Procedure was used

For identification, the scale parameter for tenure was set to 1;

the own/single-family combination was used as the base;

the retired household segment was used as the base.

(basically you want to optimize this function w.r.t the betas)

23

Original Slide

23

Estimation Results: Coefficients on Accessibility

HH are more likely to rent

single-family homes in rural,

isolated and cities near

MPOs relative to

households in MPOs.

HH are less likely to rent

multi-family and attached

single-family in areas outside

of MPOs.

HH are less likely to own

multi-family and attached

single-family in areas outside

of MPOs; this is least likely in rural areas

In general in rural areas, HHs are more likely

To own a single family unit;

24

Original Slide

25

Estimation Results: Area-Type Model Coefficients

NOTE: Im using this as an introduction slide

Remember the area-types we discussed earlier? Heres how they fair in the model

Estimation Results: Area-Type Model Coefficients

26

Base case

Own/Single-Family

Own/SFMajor Urban CenterUrban near Major CityRural near Major CityIsolated CityRural00000

Estimation Results: Area-Type Model Coefficients

27

HH are more likely to rent

single-family homes in rural,

isolated and cities near MPOs relative to households in MPOs.

Rent/Single-Family

Rent/SFMajor Urban CenterUrban near Major CityRural near Major CityIsolated CityRural08.7999999999999995E-2-0.198000000000000010.275000000000000020.38500000000000001

Estimation Results: Area-Type Model Coefficients

28

HH are less likely to own

multi-family and attached

single-family in areas outside

of MPOs; this is least likely in rural areas

Own/Multi-Family or

Attached Single-Family

Own/MF-ASFMajor Urban CenterUrban near Major CityRural near Major CityIsolated CityRural0-0.787000000000000030.95899999999999996-1.0489999999999999-2.274

Estimation Results: Area-Type Model Coefficients

29

HH are less likely to rent

multi-family and attached

single-family in areas outside of MPOs.

In general in rural areas, HHs are more likely to own a single family unit.

Rent/Multi-Family or

Attached Single-Family

Rent/MF-ASFMajor Urban CenterUrban near Major CityRural near Major CityIsolated CityRural0-0.39200000000000002-1.74-0.378-2.4009999999999998

Estimation Results: Coefficients on Lifestyle Segments

Single Adult >=65

Single Adult =18

Non-related Household

Single Parents with Children

Parents with Children

Related Adults no Children, =65

Relative to retired couples,

All segments are more likely to

Rent a SF home.

Relative to retired couples,

All segments are more likely to

Rent a SF home.

In general, retired households

Are less likely to rent relative to

Owning a SF.

W.R.T owning MF-ASF, single adults

are the most likely segment; the least

likely are parents with children.

30

Original Slide

Lifecycle Segments within the OHAS Sample

31

Household Structure Type

Single-FamilySingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 650.670932358318098720.642433820624259130.772575250836120440.735124760076775410.90936309199782250.898835168342109410.8994932432432432Duplex/TownhomeSingle Adult, Age > 65Single Adult, Age 18-65Non-Related HouseholdSingle Parents with ChildrenParents with ChildrenRelated Adults no Children, Age < 65Related Adults no Children, Age > 653.8391224862888484E-25.8870011853022521E-23.8461538461538464E-28.253358925143954E-22.3679912901469789E-21.7871389819690442E-21.3091216216216216E-2Building with 3+ ApartmentsSingle Adult, Age > 65Single Adult, A...

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