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Study on Probability Distribution
of Disaster Losses,
Demographics and Social
Security: A Case Study of
western China
HONG MI, XINHAO LIN, GUOLONG WANG
SCHOOL OF PUBLIC AFFAIRS/ INSTITUTE FOR POPULATION DEVELOPMENT AND
STUDIES
ZHEJIANG UNIVERSITY, CHINA
AUG 31ST, DAVOS
“
”
China, with frequent natural
disasters, has been
suffering a huge economic
loss every year.
 Due to both meteorological
disasters and geological
disasters: the affected crop
area had amounted to 24.891
million hectares, of which
over 3 million hectares crop
failed, while the affected
population was nearly 244
million, including 1818 deaths
and missing, causing a direct
economic loss of 337.4 billion.
* From Stata Statistical Yearbook 2015, by the year 2014
 Mainland China
experienced 20
earthquakes in 2014,
leading to 623
deaths, 3043 injured
and 33.3 billion of
direct economic loss.
Outline
Ⅰ Literature review
Ⅱ Introduction of data
• probability of each disaster types occurred
• demographic characteristics of disaster victims
Ⅲ Regression
Ⅳ Discussion
Ⅰ Literature review
 Human being are disaster-causing factor, their behavior will
induce the occurrence of disasters. Human being are also the
bearer of disasters, they have to withstand direct losses and
consequences disasters caused.
 Chinese literatures about disaster and human beings are mainly
focus on personal injury(Shi Peijun,1996; Liu Huan, 2012), not
economic loss. emphasis the brief characteristics of a whole
disaster area(Shen Maoying, 2008).
Ⅰ Literature review
 Vulnerable population is more easily affected by disasters and
more likely suffering from death risks (Flanagan BE, 2011)
 All individuals had some degree of vulnerability. Women had
higher vulnerability than men, and vulnerability increased with
age.(Andrew M K, 2008; Jencik A, 2010; Sharmin Z, Islam M S,
2013)
 Farming households have higher vulnerability and families’ annual
income affect their vulnerability (Muhammadlawal A, Salau S A,
2013 )
 Demographic vulnerability calls for different patterns of targeted
emergency management. (Chakraborty, 2005; Akerkar S, 2011;
Schwarz S, 2013)
Ⅱ Introduction of data
 ‘Disaster Risk Reduction and Pension’ Survey, 2013
 Sponsored by Ford Foundation
 Baoji City, Shaanxi Province
►2008.5.12
Wenchuan (8.0)
 Respondents: 40+. Mainly live in rural-urban
continuum.
 Questionnaire includes: basic personal information,
family member information, household income and
expenditure, health condition, demand for old-age
(money), living choice, life satisfaction, life expectancy
(self-reported), disaster experience & financial aid.
 Total respondents: 792
Ⅱ Introduction of data
0%
2%
4%
6%
8%
10%
12%
14%
Earthquake Windstorm Fire Flood Drought
Probability of each kind of disaster
Ⅱ disaster types x demographic characteristics
*Ordinate shows the ratio of people affected(suffering economic loss) to
the whole
0%
2%
4%
6%
8%
10%
12%
14%
Earthquake Windstorm Fire Flood Drought
Disaster x Age
40-49
50-59
60-69
70-79
80+
Ⅱ disaster types x demographic characteristics
*Ordinate shows the ratio of people affected to the whole
0%
2%
4%
6%
8%
10%
12%
14%
Earthquake Windstorm Fire Flood Drought
Disaster x Gender
Male
Female
Ⅱ disaster types x demographic characteristics
*Ordinate shows the ratio of people affected to the whole
0%
2%
4%
6%
8%
10%
12%
14%
Earthquake Windstorm Fire Flood Drought
Disaster x Hukou
Non-agricultural household Agricultural household
Ⅱ disaster types x demographic characteristics
*Ordinate shows the ratio of people affected to the whole
0%
2%
4%
6%
8%
10%
12%
14%
16%
Earthquake Windstorm Fire Flood Drought
Disaster x Education
illiteracy
primary school
junior high school
senior high school
college
Ⅱ disaster types x demographic characteristics
*Ordinate shows the ratio of people affected to the whole
0%
2%
4%
6%
8%
10%
12%
14%
Earthquake Windstorm Fire Flood Drought
Disaster x Marital status
Single/Widowed/
Divorced
Married/Remarrie
d
Ⅱ disaster types x demographic characteristics
*Ordinate shows the ratio of people affected to the whole
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
Earthquake Windstorm Fire Flood Drought
Disaster x Children number
0
1
2
3
4
5+
Ⅲ Regression
 Earthquake victims
 Self-reported Loss(property or physical) =1
not =0
 Logistic regression
Prob(self-reported loss=1)=
𝑒 𝑧
1+𝑒 𝑧
z = a0 + a1X1 + a2X2 + ⋯ + apXp
Independent
variables
OR z
Independent
variables
OR z
Age 1.025* 1.83
Social
endowment
insurance
2.523* 1.35
Gender 0.823 -0.63 Living status 0.603* -1.75
Hukou 1.371 0.62 Ln (income) 1.238*** 3.16
Marital
status
0.235 -1.26
Self-reported
life
expectancy
attitude
0.926*** -5.02
Education
years
1.095* 1.92 Cons 0.003** -2.45
Disable 0.597 -1.16 Pseudo R2 0.1038
Prob>chi2 0.000 Obs 398
Ⅲ Regression
 Older people are more likely to report loss when an
earthquake occurs, showing vulnerability of the
elderly.
 Highly-educated people with high annual income are
more likely to report loss. Partly because they have
more assets and more to lose.
 People living at home with their own families are less
likely to report loss than those who live in nursing
house, showing an important role of family support.
Ⅳ Discussion
 The regression shows a positive correlation between
self-reported loss and social insurance participation.
Because the new rural pension system has not
implemented until 2009. There is a possibility that
people’s loss in 2008 earthquake might led to their
enthusiasm of insurance participation.
 Those people who report loss, are more likely to be
positive when reporting their life. The elder-adult Chinese
saying ‘fortune is given to those who survive from big
disasters’ (大难不死必有后福) might explains this.
Ⅳ Discussion
V Conclusion and Recommendations
 Suffering from disaster loss will truly increase people’s
enthusiasm of insurance participation. Commercial or
government catastrophe insurance is needed.
 Suffering from disaster loss will affect people’s living
attitude in the long run , as a rejoicing for their survival.
 It is of great necessity for the government to take
comprehensive demographic vulnerability into
consideration of natural disaster assistance to ensure
policy fairness.
 Carry out disaster education and reduction to diminish
comprehensive social vulnerability.
Ⅳ Discussion: shortcomings
 Small sample size. (398)
 Need further research, Heckman two-steps model.
Hong Mi
spsswork@163.com
Xinhao Lin
linxh1024@zju.edu.cn
Thanks for your attention!

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Study on Probability Distribution of Disaster Losses, Demographics and Social Security A Case Study of Western China, Hong MI

  • 1. Study on Probability Distribution of Disaster Losses, Demographics and Social Security: A Case Study of western China HONG MI, XINHAO LIN, GUOLONG WANG SCHOOL OF PUBLIC AFFAIRS/ INSTITUTE FOR POPULATION DEVELOPMENT AND STUDIES ZHEJIANG UNIVERSITY, CHINA AUG 31ST, DAVOS
  • 2. “ ” China, with frequent natural disasters, has been suffering a huge economic loss every year.
  • 3.
  • 4.  Due to both meteorological disasters and geological disasters: the affected crop area had amounted to 24.891 million hectares, of which over 3 million hectares crop failed, while the affected population was nearly 244 million, including 1818 deaths and missing, causing a direct economic loss of 337.4 billion. * From Stata Statistical Yearbook 2015, by the year 2014  Mainland China experienced 20 earthquakes in 2014, leading to 623 deaths, 3043 injured and 33.3 billion of direct economic loss.
  • 5. Outline Ⅰ Literature review Ⅱ Introduction of data • probability of each disaster types occurred • demographic characteristics of disaster victims Ⅲ Regression Ⅳ Discussion
  • 6. Ⅰ Literature review  Human being are disaster-causing factor, their behavior will induce the occurrence of disasters. Human being are also the bearer of disasters, they have to withstand direct losses and consequences disasters caused.  Chinese literatures about disaster and human beings are mainly focus on personal injury(Shi Peijun,1996; Liu Huan, 2012), not economic loss. emphasis the brief characteristics of a whole disaster area(Shen Maoying, 2008).
  • 7. Ⅰ Literature review  Vulnerable population is more easily affected by disasters and more likely suffering from death risks (Flanagan BE, 2011)  All individuals had some degree of vulnerability. Women had higher vulnerability than men, and vulnerability increased with age.(Andrew M K, 2008; Jencik A, 2010; Sharmin Z, Islam M S, 2013)  Farming households have higher vulnerability and families’ annual income affect their vulnerability (Muhammadlawal A, Salau S A, 2013 )  Demographic vulnerability calls for different patterns of targeted emergency management. (Chakraborty, 2005; Akerkar S, 2011; Schwarz S, 2013)
  • 8. Ⅱ Introduction of data  ‘Disaster Risk Reduction and Pension’ Survey, 2013  Sponsored by Ford Foundation  Baoji City, Shaanxi Province ►2008.5.12 Wenchuan (8.0)
  • 9.  Respondents: 40+. Mainly live in rural-urban continuum.  Questionnaire includes: basic personal information, family member information, household income and expenditure, health condition, demand for old-age (money), living choice, life satisfaction, life expectancy (self-reported), disaster experience & financial aid.  Total respondents: 792
  • 10. Ⅱ Introduction of data 0% 2% 4% 6% 8% 10% 12% 14% Earthquake Windstorm Fire Flood Drought Probability of each kind of disaster
  • 11. Ⅱ disaster types x demographic characteristics *Ordinate shows the ratio of people affected(suffering economic loss) to the whole 0% 2% 4% 6% 8% 10% 12% 14% Earthquake Windstorm Fire Flood Drought Disaster x Age 40-49 50-59 60-69 70-79 80+
  • 12. Ⅱ disaster types x demographic characteristics *Ordinate shows the ratio of people affected to the whole 0% 2% 4% 6% 8% 10% 12% 14% Earthquake Windstorm Fire Flood Drought Disaster x Gender Male Female
  • 13. Ⅱ disaster types x demographic characteristics *Ordinate shows the ratio of people affected to the whole 0% 2% 4% 6% 8% 10% 12% 14% Earthquake Windstorm Fire Flood Drought Disaster x Hukou Non-agricultural household Agricultural household
  • 14. Ⅱ disaster types x demographic characteristics *Ordinate shows the ratio of people affected to the whole 0% 2% 4% 6% 8% 10% 12% 14% 16% Earthquake Windstorm Fire Flood Drought Disaster x Education illiteracy primary school junior high school senior high school college
  • 15. Ⅱ disaster types x demographic characteristics *Ordinate shows the ratio of people affected to the whole 0% 2% 4% 6% 8% 10% 12% 14% Earthquake Windstorm Fire Flood Drought Disaster x Marital status Single/Widowed/ Divorced Married/Remarrie d
  • 16. Ⅱ disaster types x demographic characteristics *Ordinate shows the ratio of people affected to the whole 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% Earthquake Windstorm Fire Flood Drought Disaster x Children number 0 1 2 3 4 5+
  • 17. Ⅲ Regression  Earthquake victims  Self-reported Loss(property or physical) =1 not =0  Logistic regression Prob(self-reported loss=1)= 𝑒 𝑧 1+𝑒 𝑧 z = a0 + a1X1 + a2X2 + ⋯ + apXp
  • 18. Independent variables OR z Independent variables OR z Age 1.025* 1.83 Social endowment insurance 2.523* 1.35 Gender 0.823 -0.63 Living status 0.603* -1.75 Hukou 1.371 0.62 Ln (income) 1.238*** 3.16 Marital status 0.235 -1.26 Self-reported life expectancy attitude 0.926*** -5.02 Education years 1.095* 1.92 Cons 0.003** -2.45 Disable 0.597 -1.16 Pseudo R2 0.1038 Prob>chi2 0.000 Obs 398 Ⅲ Regression
  • 19.  Older people are more likely to report loss when an earthquake occurs, showing vulnerability of the elderly.  Highly-educated people with high annual income are more likely to report loss. Partly because they have more assets and more to lose.  People living at home with their own families are less likely to report loss than those who live in nursing house, showing an important role of family support. Ⅳ Discussion
  • 20.  The regression shows a positive correlation between self-reported loss and social insurance participation. Because the new rural pension system has not implemented until 2009. There is a possibility that people’s loss in 2008 earthquake might led to their enthusiasm of insurance participation.  Those people who report loss, are more likely to be positive when reporting their life. The elder-adult Chinese saying ‘fortune is given to those who survive from big disasters’ (大难不死必有后福) might explains this. Ⅳ Discussion
  • 21. V Conclusion and Recommendations  Suffering from disaster loss will truly increase people’s enthusiasm of insurance participation. Commercial or government catastrophe insurance is needed.  Suffering from disaster loss will affect people’s living attitude in the long run , as a rejoicing for their survival.  It is of great necessity for the government to take comprehensive demographic vulnerability into consideration of natural disaster assistance to ensure policy fairness.  Carry out disaster education and reduction to diminish comprehensive social vulnerability.
  • 22. Ⅳ Discussion: shortcomings  Small sample size. (398)  Need further research, Heckman two-steps model.

Editor's Notes

  1. Good afternoon, professors and fellow colleges, I’m very honored to be here to present my latest work, based on our team’s investigation in Shaanxi, as doc jianing just mentioned. The topic of my presentation today is
  2. Common natural in China includes earthquake, flood, typhoon, droughts and so on.
  3. The Data Statistical Yearbook 2015 of China showed that, due to both meteorological disasters and geological disasters, the affected crop area had amounted to 24.891 million hectares, of which over 3 million hectares crop failed, while the affected population was nearly 244 million, including 1818 deaths and missing, causing a direct economic loss of 337.4 billion. What’s more, mainland China experienced 20 earthquakes in 2014, leading to 623 deaths, 3043 injured and 33.3 billion of direct economic loss.
  4. And my presentation will include those following parts, first a brief literature review, then follows an introduction of the data we used, and the regression part.
  5. As we know, human being are disaster-causing factor, their behavior will induce the occurrence of disasters. Like excessive logging leads to soil erosion and landslides, and sometimes drought. Human being are also the bearer of disasters, they have to withstand direct losses and consequences which disasters cause. Chinese literatures about disaster and human beings are more focused on personal injury, not on economic loss, emphasis the brief characteristics of a whole disaster area.
  6. Vulnerable population is more easily affected by disasters and more likely suffering from death risks. Gender, age, household type and income are all variables that effect on population vulnerability. Therefore, population vulnerability calls for different patterns of targeted emergency management.
  7. The data we use for this research is from 2013 ‘Disaster Reduction and Pension’ Survey, which take place in Baoji, Shaanxi, a midwest province in China. Baoji is 460km away from Wenchuan and in the same earthquake zone. The 2008 Wenchuan earthquake, whose magnitude reached 8, has affected this region.
  8. This survey mainly facing to those who aged 40 or more, likely to be a head of one’s household; The selected sample covers all seven areas of Baoji City. Questionnaire includes: basic personal information, family member information, household income and expenditure, health condition, demand for old-age (money), living choice, life satisfaction, self-reported life expectancy, disaster experience & financial aid. collected 792 samples in total
  9. It shows, earthquake is the most common disaster in this area, probability of earthquake occurrence is more than 12%, partly due to the 2008 Wenchuan earthquake, whose magnitude reaches 8. Then follows windstorm, flood and drought, all between 2 to 4 percentage point. Fire is the most unusual disaster in Baoji.
  10. As shown, apart from fire, disaster victims are mostly 40-60 year-old middle-ages. Probability of disaster occurrence is decreasing with an increasing age. But 80 years old or older population shows significant growth facing earthquakes and floods. Fire is relatively unique, larger hazard existing in human behaviors. The affected population is mainly 40-49 and 70-79 years old.
  11. In most disasters, the probability affected of men are significantly higher than women, but the probability of women affected are slightly higher than men suffer from fire. Probably because, in the countryside, fires generally occur in home, while women are more likely doing housework at home in the daytime.
  12. Agricultural households shows a higher percentage in all most every disaster type. May be because, in baoji city, most of the agricultural households are really engaged in agricultural work, which is closely related to weather and geological conditions, so they’re more sensitive to these disasters.
  13. Unlike what we normally think, the probability doesn’t decrease with a higher level of education. It shows an inverted u-shaped curve in each disaster type except fire. But it is significant that college graduates suffers less disaster.
  14. People with spouses show a slightly higher probability of disaster in each disaster type except fire.
  15. From the overall trend, have more children, means getting more support and help from their kids, lowers the probability of suffering from disasters like earthquake, flood and drought. But there is significant growth when people have 5 or more than 5 kids.
  16. According to the data of 2013 survey, we run a logistic regression between the self-reported loss and demographic characteristics. Because of the very different nature and causal factors of each disaster, we only select those who reported themselves went through an earthquake as research samples, in this survey, it refers to the 2008 Wenchuan Earthquake and 2010 Yushu Earthquake. the whole city went through those two earthquake, but some people reported economic loss, someone not. We select self-reported loss as dependent variable. When people reported economic loss or themselves injured, we consider it as an self-reported loss, because injury also lead to medical expenditure or absences from work. Independent variables are those shows ones’ demographic characteristic, economic status, living attitude and so on.
  17. The regression result shows, age, education years, annual income, pension situation, and self-reported life expectancy is significantly relevant to the loss.
  18. Because most of the respondents’ social endowment insurance is the new rural social pension insurance, which has not implemented until 2009. There is a possibility that people’s loss in 2008 wenchuan earthquake might led to their enthusiasm of insurance participation. Those people who report loss, are more likely to be positive when reporting their life. The old Chinese saying ‘fortune is given to those who survive from big disasters’ might explains this result.
  19. Suffering from disaster loss will truly increase people’s enthusiasm of insurance participation. Commercial or government catastrophe insurance is needed. Suffering from disaster loss will affect people’s living attitude in the long run, as a relief of their survival. It is of great necessity for the government to take comprehensive demographic vulnerability into consideration of natural disaster assistance to ensure policy fairness. Carry out disaster education and reduction to diminish comprehensive social vulnerability
  20. There’re still many shortcomings in this research. The sample size in this regression is only 398, which is relatively small. But considering about the total respondents size of 792, the conclusion is acceptable. Next step, we may try Heckman two-steps model, to study the relationship between the exact amount of economic loss and demographic characteristics.