A brief presentation of results Iran GAR Report A brief presentation of results

Occurrence of natural hazards by type, I.R.Iran, 1986-2007

Trends in occurrence by hazard group, I.R.Iran, 1986-2007 Trends in occurrence of climatic hazards, excluded flooding, I.R.Iran, 1986-2007

Hazard occurrence by Ostan (left) and Shahrestan (right), I. R Hazard occurrence by Ostan (left) and Shahrestan (right), I.R.Iran, 1986-2007

)Left: Geologic hazards, Right: Climatic hazards) Comparison of hazard occurrence and death between 1986-1996 and 1997-2007, I.R.Iran )Left: Geologic hazards, Right: Climatic hazards)

No of death per 10,000 inhabitants by Ostan (left) and Shahrestan (right) and hazard group, I.R.Iran, 1986-2007

No of building damaged and destroyed by Ostan (left) and Shahrestan (right) and hazard group, I.R.Iran, 1986-2007

Cumulative percent of event occurrence and death due to geologic (left) and climatic (right) hazards by death class, I.R.Iran, 1986-2007 Cumulative percent of event occurrence and building damage & destruction due to geologic (left) and climatic (right) hazards by damage class, I.R.Iran, 1986-2007

NATIONAL POVERTY PROFILE Human Poverty Index (HPI-1) There is a clear evidence of significant reduction in human poverty in Iran.

The Correlation between Human Poverty and Income In general, there is a statistically significant correlation between per capita income and human poverty index, indicating the importance of policies regarding improvement of household income. The Correlation between Human Poverty and Income Per Capita GDP (Thousand Rials) HPI (Percent)

Study Methodology Earthquake, flood and drought are the most destructive disasters in Iran. While the first two of them affect peoples well being through human losses (death and casualties) and building damages and destructions, the last one has a long-term effect in most aspects of people's lives through, for instance, immigration pressures on large cities because of rural/agricultural unemployment etc. Data on the number of disaster events by provinces has been collected in DesInventar. The number of dead people per ten thousand populations and the number of buildings destroyed or damaged for a period of 1991 to 2006 has been considered as variables that explain disaster effects. The models applied explain such effects on household expenditures to measure the economic impact of disasters. Using expenditures instead of income has the advantage that, while the household income is subject to variations in different economic conditions, consumption expenditures have a more rigid nature and do not vary significantly and, therefore, are more reliable for future projections. On the other hand, models with human development and human poverty indices and their components as dependent variables count for poverty consequences of natural disasters.

Study Challenges Still a new subject: absence of disaster-related issues in household level statistical questionnaires The existing provincial data available, based on DesInventar, while very abstract and rough (due to short of time to collect the information) only reveal two economic consequences of disasters, namely the number of death and the number of buildings damaged or destroyed Household Expenditure Income Survey (HEIS) considers an urban/rural decomposition of social and economic features of families, but DesInventar only reports the number and socio-economic consequences of disasters for the whole province and does not take care of rural/urban differences. On the other hand, the information on HEIS for rural and urban households could not be summed up to have a unique data set for the whole population within the province. One main reason is that the sampling approaches in different years differ between urban and rural areas. That is why the study is based on the HEIS data for urban areas.

Methodology Model specification and variables defined The main objective: testing for the relationship between natural disasters and the socio-economic well being of the Iranian people. Note: the study is not directly dealing with poverty measures for two main reasons: First, poverty is a human concept that has a wide range of components, from economic to social, cultural, environmental and even political ones. The concept of human poverty has in fact been introduced to depict all such aspects of life, rather than merely the physical satisfaction. Second, the standard poverty metrics like FGT are defined on the basis of a poverty line. For many technical reasons, poverty lines are not calculated and reported officially in Iran. While some rough estimations of the percentage of poor people are reported in chapters one and two, they are based on the international poverty line definitions of $1 and $2 expenditures per person per day.

Data HEIS is the main source of data for average food and non-food expenditures, the family size, and average education and health expenditures. The price index for different components of household expenditures, namely food and non-food as well as education and health expenditures for urban areas is from the CB. Human poverty indicators such as adult literacy and school enrollment ratios, life expectancy, population without access to an improved water source and improved health care are from Human Development Reports. Study covers a period from 1991 to 2006, unless stated otherwise. In 2006, there were 28 provinces. Qom province has been excluded since there were no disasters registered in DesInventar. After changes in political administration of the country during the last decade, four new provinces of Ardebil, Golestan, Qom and Qazvin have been established, which were previously part of other provinces. Khorasan was also split into three new provinces of North Khorasan, Razavi Khorasan and South Khorasan.

Estimation Results for Economic Well-being Econometric model used: is differences in real expenditures of the urban households in ith province at time t (adjusted for prices using the urban CPI), (Death)ti and (Buildings)ti are the number of human losses per thousand populations and buildings damaged or detructed, respectively, due to natural disasters in ith province at time t, (Family Size)ti is included as a factor affecting people's economic well being in many poverty studies.

Estimation Results for Economic Well-being Linear Specification coefficients of the number of death as well as the number of buildings damaged or destroyed for the most disaster-prone provinces were significant. It suggests that in these provinces, natural disasters play a main role in economic disruptions of people's lives. In particular, Ardebil, Chaharmahal-&-Bakhtiari, Lorestan, Mazandaran, Khorasan, Hormozgan and Yazd are among the disaster-prone provinces where the estimated coefficients in number of death, number of damaged and destroyed buildings, or both were significant and consistent with our hypothesis.

Linear Specification – Expenditure Differences as Dependent Variable

Linear Specification – Expenditure Differences as Dependent Variable

Linear Specification – Expenditure Differences as Dependent Variable

Main finding of linear specification Demographic, climate, and style of life differ across provinces, so the results should be interpreted province by province. In Chaharmahal-o-Bakhtiari, for instance, natural disasters (usually in the form of floods) have disturbed people's economic well being mostly through increasing the number of dead people rather than through physical damages. In Hormozgan and Yazd, on the other hand, disasters affect living standards through destruction of buildings. An unexpected result is the positive effect of building damages and destructions on economic well being of people in Mazandaran, Khorasan and Lorestan. The best explanation here, especially for fist two provinces, is that after exposure of intensive disasters in these provinces, considerable amount of financial aid from the government and public charity institutions as well as soft bank loans helped reconstruction of the damaged and destroyed buildings and/or equipping them with new furniture, which eventually resulted in the affected households to become better-off.

Main finding of linear specification Another strange result is the positive sign of the coefficient on the number of death people in Ardebil. It is most probably because the affected (dead) people were aged below 16 or above 64. If so, such an event could lower the dependency ratio, which in turn, would help raising the standards of life for the affected households. The coefficients of disaster-related variables are found to be negative as expected, though manty of them are not statistically significant. The coefficient of family size has a theoretically right sign (ie negative) and very significant in a number of provinces, including East Azerbaijan, West Azerbaijan, Khorasa, Mazandaran and Hormozgan. It means that increases in family size helps in reduction of expenditure changes for the whole family. In other words, larger families enjoy increasing returns to scale.

Estimation Results for Economic Well-being Logarithmic Specification As usual, the logarithmic specification of models reveals much better results. Disaster variables have a significant negative effect on economic well being of people, especially in Ardebil, Khorasa, Khuzestan, Fars, Kordestan, Golestan and Gilan, most of which are highly disaster-prone provinces. The estimation results for family size also show considerable improvements for Ardebil, Tehran, Khorasa, Fars, Kordestan, Gilan and Lorestan, where the coefficients have a negative sign and are statistically significant.

Logarithmic Specification – Expenditure values as dependent variable

Main finding of logarithmic specification For most of the provinces, the elasticity of household expenditures with respect to building damages and destructions has been estimated between -0.01 and -0.04, indicating a small effect of disasters on people's well being. However, it is notable that Khorasan, Kordestan, Golestan and Gilan, suffer considerably from disasters, as the elasticity is estimated in a higher range from -0.13 to -0.31. It is in large part because disasters mostly affect people living in these provinces through physical damages rather than life losses. For almost all provinces, the effect of life losses on people's welfare has been less than that of physical damages, as the respective elasticity ranges from -0.02 to -0.11. One main reason here is that the family bread-winners are less exposed to the risk of death due to disasters.

A Social Attitude towards Well-being Health-Related consequences of Disasters Differences in health situation across provinces as a result of disaster-related human and physical losses as well as other conventional variables such as the average household expenditures on health and the family size. DATA: Since disasters affect social aspects of people's lives only in long term, data for the two disaster-related variables are a 16-year accumulation, while data on health expenditures and family size are 16-year averages. Data on the health variable refer to the final year of our time period. The sample includes 28 provinces. A number of proxies, including the average life expectancy at birth, the average population without access to an improved water source and the average population without access to an improved health care have been considered as dependent variables.

Linear Specification The results for the model with life expectancy as the dependent variable indicate that while building destruction and damages do not affect life expectancy, the number of death due to disasters only have a very small impact. This, in fact, is a reasonable result as life expectancy at birth is a variable that could not be easily affected by a limited number of human and physical losses due to disasters. However, life expectancy is smaller for provinces with larger average size of the family. This is because larger families spend less for healthcare per member of family. In other words, large families are subject to economy of scale in healthcare spending.

Linear Specification In general, the estimation results, especially for models with dependent variables other than the life expectancy at birth are not robust. Even when a logarithmic form was specified, the estimation results did not appear to be satisfactory. A reliable conclusion from this section of the study is that health indicators have a significant and negative relationship with family size.

Logarithmic Specification Here again the results confirm the conclusion from linear model that family size is a main contributor in reduction of the whole family health. For models with population without access to an improved water source and health care as dependent variables, the results also confirm the impact of human and physical losses from disasters on health situation of families.

A Social Attitude towards Well-being Education-Related consequences of Disasters Data on the two disaster-related variables are a 16-year accumulation, and that on education expenditures and family size are 16-year averages. Data on the education variable refer to the final year of our time period. The sample is comprised of 28 provinces. Two proxy variables are adult literacy ratio and the education index (as defined and reported by Human Development Reports). No theoretical and statistical significance in explanation of education indices by natural disasters.