+ Using urban transport policies as a solution to poverty Panori Anastasia. PhD candidate. Panteion University of Athens

+ Overview 1. Methodology 2. Measures 3. Results 2

+ Main idea Assessing Poverty in Small Area Populations SimAthens model Transport Policy Design – Based on a pro-poor growth orientation Implementation Method – Static Spatial Microsimulation Methodological Framework – Poverty & Social exclusion 3

+ Why Athens? Metropolitan Century: increase in number of large urban agglomerations. Literature focuses mostly on national comparisons but local comparisons are also important. The gap between rich and poor within urban space is expanding - Concentration of poverty in urban areas. Athens is a regional metropolis of 4 million people in South-Eastern Europe. One of the most representative cases of urban poverty in the developed world of the EE. 4

+ Metropolitan area of Athens 5

+ 1. Methodology 6

+ Spatial decomposition Methodology: Static spatial microsimulation model (SimAthens). Code: written in R – modification of already existing code developed by Lovelace and Ballas (2013). Data: combination of individual EU-SILC data ( ) with aggregate census data ( ). 7

+ How does it work? SimAthens Model: re-weighting database B to fit results of A using a set of constraint variables Database B: Individual Data from EU-SILC database Small area re-synthesized populations with individual data Database A: Aggregate Census Data 8

+ Validation of the Model ISCO Census (%) SimAthens (%) Census (%) SimAthens (%) Legislators. senior officials and managers & Professionals Technicians and associate professionals Clerks & Service workers and shop and market sales workers Skilled agricultural and fishery workers Craft and related trades workers Plant and machine operators and assemblers Elementary occupations

+ Scatter plot of actual and simulated values 10

+ Mean equivalised income 11

+ 2. Measures 12

+ At-risk-of-poverty rate Headcount ratio of people living under the poverty line (AROP)  60% of the household equivalised median income of the metropolitan area of Athens – not national in our case Material Deprivation rate Headcount ratio of people living under material deprivation (MD)  households who lack at least three of a list of nine basic items (Guio, 2009; Guio et al., 2009) No Car ownership Headcount ratio of people not having a car in their household (NCO)  Lack of car in the household due to economic reasons Unmet medical needs Headcount ratio of people not being able to cover their medical needs due to transport difficulties (UMN)  Transport difficulties include reasons such as too far to travel & no means of transportation 13 Poverty MeasuresTransport Measures

+ Material Deprivation 3 out of 9 items for a house to be deprived Telephone Colour TV Washing machine Car Capacity to pay for arrears (mortgage or rent, utility bills or hire purchase installments) Capacity to face unexpected financial expenses Capacity to afford a meal with meat. chicken. fish or vegetarian equivalent every second day Capacity to afford paying one week annual holiday away from home Ability to keep home adequately warm 14

+ 3. Results 15

+ Results I – AROP and MD rates Municipality At-risk-of-poverty (%)Material Deprivation (%) Highest income Psychiko Filothei Ekali Papagou Neo Psychiko Lowest income Keratsini Drapetsona Ag. Ioannis Rentis Agia Varvara Perama

+ Results II – CO and UMN rates Municipality No Car Ownership (%)Unmet Medical Needs (%) Highest income Psychiko Filothei Ekali Papagou Neo Psychiko Lowest income Keratsini Drapetsona Ag. Ioannis Rentis Agia Varvara Perama

+ AROP rate – Mean equivalised income 18

+ MD rate – Mean equivalised income 19

+ UMN rate – Mean equivalised income 20

+ Results III – MD and UMN rate (2006) MD rate (%)UMN rate (%)

+ Results III – MD and UMN rate (2011) MD rate (%)UMN rate (%)

+ AROP – by age group Municipality < < Highest income Psychiko 24,9819,1026,8024,8321,9822,17 Filothei 26,1218,2725,9823,6121,3922,00 Ekali 26,4019,7024,1922,4722,3123,67 Papagou 26,1918,6424,2321,2321,9224,08 Neo Psychiko 23,2016,6125,5319,2320,2720,79 Lowest income Keratsini 17,1815,6717,7619,1421,4921,73 Drapetsona 17,2415,6617,6619,0321,8520,46 Ag. Ioannis Rentis 15,2715,4217,7019,0521,7622,62 Ag.Varvara 17,1415,7517,8324,6221,6518,63 Perama 16,9615,5016,9320,1822,5818,70 23

+ UMN – by age group Municipality < < Highest income Psychiko 3,702,491,420,000,773,86 Filothei 0,002,210,580,000,794,80 Ekali 0,003,100,870,001,143,97 Papagou 6,251,831,030,000,704,80 Neo Psychiko 7,142,881,920,000,576,69 Lowest income Keratsini 13,513,603,730,000,746,53 Drapetsona 10,983,973,400,000,637,74 Ag. Ioannis Rentis 11,493,933,850,000,567,13 Ag.Varvara 8,843,583,340,000,796,89 Perama 12,434,084,000,000,656,00 24

+ Conclusions Spatial decomposition has revealed large differences within the metropolitan area of Athens. Different structure of at-risk-of-poverty and material deprivation rates between municipalities. No car ownership and unmet medical needs due to transport difficulties, seem to increase as we move to more deprived areas. Unmet medical needs increased during the economic crisis. Age decomposition: UMN due to transportation issues largely decreased between 06/11 for age groups younger than 65 years old. It increased for the elderly. 25

+ Thank you for your attention 26