On Distance from Home in Daily Activity Pattern Nagoya Univ. - - PowerPoint PPT Presentation

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On Distance from Home in Daily Activity Pattern Nagoya Univ. - - PowerPoint PPT Presentation

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On Distance from Home in Daily Activity Pattern Nagoya Univ. Toshiyuki Yamamoto Keita Kanetomo 1 1. Background and Objective Japan has experienced many earthquakes, typhoons and floods, and expect to come. Population density (/km2) Big

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On Distance from Home in Daily Activity Pattern

Nagoya Univ. Toshiyuki Yamamoto Keita Kanetomo

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Japan has experienced many earthquakes, typhoons and floods, and expect to come.

  • 1. Background and Objective

10 km 20

Population density (/km2)

Gifu Yokkaichi Toyota Nagoya

Big earthquakes periodically

  • ccurred at Nagoya area
  • M7.9 in 1605
  • M8.6 in 1707
  • M8.4 in 1854
  • M7.9 in 1944

M8.1 is anticipated in 30 years with 60% probability

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Distance from home in daily activity pattern is investigated in this study

How far is each member away from home? How far are parents away from children?

  • 1. Background and Objective

Earthquake occurs Family members are apart from each other Many people try to get home when the earthquake occurs Worker: 70-80 % when safety of family is not confirmed 80+ % when family members are seriously injured Shopper: 60 % when safety of family is confirmed, 70 % not confirmed Student: 60-80 % when safety of family is not confirmed Unable to get home Start to get home Vulnerable members at home if too far

(The Cabinet Office, 2007)

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  • 2. Outline
  • Descriptive analysis

– Individual: longest distance from home in the daily activity pattern – Household: longest distance from home of closer parent from home children are left

  • Statistical analysis

– Tobit models: limitation of zone level data – Find dominant factors

  • Further analysis on the dominant factors

– Bivariate tobit model: interaction of factors

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Individual: longest distance increases along time Household: longest distance of care givers increases at households with elderly of 75+ yrs.

  • 3. Descriptive analysis: distance from home

6.34 7.39 7.61 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 PT81 PT91 PT01 平均値(ｋｍ) 3.25 1.99 2.59 3.84 2.62 3.20 3.96 2.42 3.87 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 全世帯 12歳以下の子供 がいる世帯 75歳以上の高齢者が いる世帯

平均値(km)

PT81 PT91 PT01

Individual

Person trip survey data

4861 11885 90435 224735 2001 2077 10905 74902 196201 1991 1648 19531 90150 244006 1981 HH w elderly (75+ yrs.) HH w children (12- yrs.) Household Person Year

Average (km) Average (km)

Household

Total 1981 1991 2001 With children (12-yrs.) With elderly (75+yrs.)

1981 1991 2001

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Student increases the distance significantly Female has larger increase than male, suggesting the expansion of the activity space by women’s participation in society

  • 3. Descriptive analysis: distance from home

自宅からの距離

10.9 3.7 5.5 2.8 11.4 <1.05> 11.8 <1.08> 5.0 <1.35> 5.5 <1.47> 4.5 4.6 <1.00> 5.0 <1.10> 6.2 <1.14> 6.7 <1.23> 3.3 4.9 <1.50> 5.5 <1.67> 3.6 <1.29> 4.0 <1.44> 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 pt81 pt91 pt01 pt81 pt91 pt01 pt81 pt91 pt01 就業者 就学者 主婦・無職 平均値(km)

男性 女性

平均値 <増加率>:81年比

Individual

Average (km) 1981 1991 2001 1981 1991 2001 1981 1991 2001 Average <Increase from 1981> Male Female Worker Student Non-worker

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0.5 1 1.5 2 2.5 3 3.5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 全世帯 12歳以下の子供がいる世帯 75歳以上の高齢者がいる世帯 平均値(km)

PT81 PT91 PT01

1 2 3 4 5 6 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 時 平均値(km)

PT81 PT91 PT01

  • 3. Descriptive analysis: distance from home

Total With children (12-yrs.) With elderly (75+yrs.) Average (km) 1981 1991 2001

1981 1991 2001

Average (km)

Individual Household

Individual: longest in 11:00 to 14:00 Household: longest in 11:00 but shorter duration at households with children

Time of day

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8 1981 1991 2001

帰宅困難者の算出(出典：東京都防災会議）

  • 3. Descriptive analysis: unable to get home

1 10 20 30 40

Distance from home (km)

Probability of unable to get home

(The Cabinet Office, 2008)

Those who unable to get home increase, especially at zones with working places including Toyota, Kariya, etc.

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  • 4. Statistical analysis: tobit model

Tobit model of distance from home

Measurement of distance from home

Location is observed by zonal centroid as usual travel survey If home and the activity location are within the same zone => Distance becomes 0 However, Actual distance is larger than 0 Exact distance is unknown

1981 1991 2001

10 20 30 40 0～5 5～10 10～15 15～20 20～ ｋｍ 人数割合(%)

pt81 pt91 pt01

Large part in within zone

Sample distribution (%)

  • Logarithm of distance (D)

as dependent variable

  • Diameter of the zone (Z) is

used as threshold for the case of within the same zone ln(D*) = βX + ε ln(D) = ln(Z) if ln(D*) ≤ ln(Z) ln(D) = ln(D*) if ln(D*) > ln(Z)

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  • 4. Statistical analysis: tobit model

0.745 0.785 0.776 Adjusted ρ2 224618 196135 243949 Sample size 0.00 ** 0.023 0.01 ** 0.036 0.00 ** 0.087 Distance from station (km)

  • 0.01

**

  • 0.065
  • 0.01

**

  • 0.036

0.00 ** 0.045 ln(Distance between city center and workplace) (km) 0.06 ** 0.204 0.05 ** 0.187 0.01 ** 0.286 ln(Distance between city center and home) (km) 0.11 ** 0.544 0.10 ** 0.554 0.01 ** 0.339 ln(Commute dist.) (km) 0.00 ** 0.194 0.00 ** 0.231

  • 0.00

**

  • 0.325

Housewife

  • 0.00

**

  • 0.227
  • 0.00

**

  • 0.263
  • 0.00

**

  • 0.213

Student

  • 0.00

**

  • 0.136
  • 0.00

**

  • 0.152
  • 0.00

**

  • 0.341

Government 0.00 ** 0.092 0.00 ** 0.112 0.00 ** 0.077 Management 0.00 ** 0.110 0.00 ** 0.091 0.00 ** 0.094 Transport

  • 0.00

*

  • 0.027
  • 0.00

**

  • 0.055
  • 0.00

**

  • 0.271

Finance

  • 0.00

**

  • 0.165
  • 0.00

**

  • 0.187
  • 0.00

**

  • 0.295

Manufacturing 0.00 ** 0.196 0.00 ** 0.158

  • 0.00
  • 0.016

Construction 0.00 ** 0.319 0.00 ** 0.338

  • 0.00
  • 0.124

Agriculture Employment 0.02 ** 0.065 0.01 ** 0.073 0.00 ** 0.074 #Vehicles

  • 0.00

**

  • 0.028
  • 0.00

**

  • 0.013
  • 0.00

**

  • 0.025

Two-income family

  • 0.00

**

  • 0.019
  • 0.00

*

  • 0.009

0.00 ** 0.035 #Elderly

  • 0.00

**

  • 0.046
  • 0.00

**

  • 0.038

0.00 ** 0.024 #Children 0.00 ** 0.089 0.00 ** 0.069 0.00 ** 0.028 60+ yrs.

  • 0.00

**

  • 0.174
  • 0.00

**

  • 0.160
  • 0.00

**

  • 0.167

Female 0.757 0.712 1.021 Constant Elasticity Coef. Elasticity Coef. Elasticity Coef. 2001 1991 1981

Individual

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  • 4. Statistical analysis: tobit model

Individual

Elasticity 2001 1991 1981 0.06 0.05 0.01 ln(Distance between city center and home) (km) 0.11 0.10 0.01 ln(Commute dist.) (km)

Dominant factor is commute distance Effect of commute distance increases along time Next dominant factor is the distance between city center and home

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  • 4. Statistical analysis: tobit model

Household with children

  • 0.01

**

  • 0.034
  • 0.02

**

  • 0.061
  • 0.00

**

  • 0.050

ln(Distance between city center and workplace of husband) (km) 0.06 ** 0.161 0.07 ** 0.191 0.03 ** 0.257 ln(Distance between city center and home) (km) 0.372 0.319 0.297 Adjusted ρ2 11885 10905 19531 Sample size 0.01 ** 0.047 0.01 ** 0.044 0.00 ** 0.073 Distance from station (km)

  • 0.01

**

  • 0.085
  • 0.02

**

  • 0.123
  • 0.00

**

  • 0.074

ln(Distance between city center and workplace of wife) (km) 0.04 ** 0.400 0.03 ** 0.390 0.01 ** 0.334 ln(Commute dist. of wife) (km) 0.02 ** 0.088 0.03 ** 0.127 0.01 ** 0.091 ln(Commute dist. of husband) (km)

  • 0.00

**

  • 0.122
  • 0.00
  • 0.069
  • 0.00

**

  • 0.080

Government

  • 0.00

**

  • 0.054
  • 0.00

**

  • 0.016
  • 0.00
  • 0.005

Management

  • 0.00
  • 0.055
  • 0.00

*

  • 0.094
  • 0.00
  • 0.023

Transport 0.00 0.002

  • 0.00

**

  • 0.070
  • 0.00
  • 0.027

Finance

  • 0.00

**

  • 0.074
  • 0.01
  • 0.111
  • 0.00

**

  • 0.090

Manufacturing

  • 0.00
  • 0.019

0.00 ** 0.002 0.00 0.014 Construction

  • 0.00

**

  • 0.201
  • 0.00

**

  • 0.306
  • 0.00
  • 0.063

Agriculture Employment 0.00 0.010 0.02 ** 0.087 0.00 ** 0.087 #Vehicles 0.00 0.046 0.01 0.207 0.00 0.100 Two-income family

  • 0.00
  • 0.070
  • 0.00

**

  • 0.123
  • 0.00
  • 0.126

#Elderly

  • 0.00
  • 0.015
  • 0.01

**

  • 0.047

0.00 0.001 #Children 0.555 343 0.402 Constant Elasticity Coef. Elasticity Coef. Elasticity Coef. 2001 1991 1981

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  • 4. Statistical analysis: tobit model

Household with children

0.06 0.07 0.03 ln(Distance between city center and home) (km) Elasticity 2001 1991 1981 0.04 0.03 0.01 ln(Commute dist. of wife) (km) 0.02 0.03 0.01 ln(Commute dist. of husband) (km)

Dominant factor is the distance between city center and home Commute distance of wife has a larger effect than that of husband in 2001

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Interaction

Commute dist.

  • f husband (Dh)

Commute dist.

  • f wife (Dw)

(Phina, 2006)

Bivariate tobit model

  • 5. Further analysis: bivariate tobit model

Distance from home is heavily dependent on commute dist. Commute distances of husband and wife are investigated ln(Dh

*) = βX + γln(Dw) + ε

ln(Dh) = ln(Z) if ln(Dh*) ≤ ln(Z) ln(Dh) = ln(Dh*) if ln(Dh*) > ln(Z)

Husband part

ln(Dw

*) = βX + γln(Dh) + ε

ln(Dw) = ln(Z) if ln(Dw*) ≤ ln(Z) ln(Dw) = ln(Dw*) if ln(Dw*) > ln(Z)

Wife part

Simultaneous estimation as bivariate tobit model

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  • 5. Further analysis: bivariate tobit model

Commute distance of household with two-earner

** 0.46 ** 0.35 Toyohashi

  • 0.13
  • 0.01

Gifu **

  • 0.11

**

  • 0.13

Toyota **

  • 0.59

**

  • 0.46

Nagoya Residence zone 0.07

  • 0.08

Toyohashi ** 0.25 0.07 Yokkaichi ** 0.22 0.00 Gifu

  • 0.04

**

  • 0.18

Toyota ** 0.47 ** 0.34 Nagoya Workplace zone ** 0.19 ** 0.07 Government ** 0.17 ** 0.12 Management 0.19 ** 0.10 Security ** 0.21 ** 0.14 Finance **

  • 0.04
  • 0.01

Manufacturing **

  • 0.34

**

  • 0.58

Agriculture Employment ** 0.24 * 0.16 Driver lisence ** 0.02 * 0.01 #vehicle 0.01 ** 0.05 #elderly **

  • 0.03

** 0.04 #children ** 0.78 ** 1.38 Constant Coef. Coef. Wife Husband 0.108 Adjusted ρ2 23294 Sample size 0.28** Correlation **

  • 0.04

ln(Commute dist. of wife) (km) **

  • 0.07

ln(Commute dist. of husband) (km) ** 0.01 0.00 Distance from station (km) ** 0.29 ** 0.25 ln(Distance between city center and home) (km) Coef. Coef. Wife Husband

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  • 5. Further analysis: bivariate tobit model

**

  • 0.03

** 0.04 #children 0.28** Correlation **

  • 0.04

ln(Commute dist. of wife) (km) **

  • 0.07

ln(Commute dist. of husband) (km) ** 0.29 ** 0.25 ln(Distance between city center and home) (km) Coef. Coef. Wife Husband

Commute distance of household with two-earner Wife decreases the commute distance for children Living in suburb increases the commute distance Commute distance of husband has a larger effect

  • n that of wife than vice versa