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Dealing with Complexity in Society:
From Plurality of Data to Synthetic Indicators
September 17th and 18th, 2015
Latent constructs and composite
indicators for measuring well-being
of the households living in Brescia
Veronica Cappa, Maurizio Carpita, Anna Simonetto
Dealing with Complexity in Society 2
Introduction
The negative effects of economic crisis are affecting families’
incomes (Janckins et al.), changing and worsening their health and
needs in terms of social and health services (EU 2013).
Dealing with Complexity in Society 3
AIMS
1. Integration (data linkage) of administrative data concerning residents of the Brescia district
2. Development composite indicators in order to measure poverty and vulnerability
3. To evaluate how poverty and vulnerability influence demand of social and health services
Dealing with Complexity in Society 4
Aim 1: administrative data
Thanks to the collaboration and support of the Statistical Staff of the Bresciadistrict, administrative data were collected and handle using:
1. CIVIL REGISTRY - Subjects and families’ characteristics from 2008 to 2013
2. TRIBUTARY database: Income of subjects from 2008 to 2013
In order to upgrade data about residents of the Brescia and consequently to better measure poverty and vulnerability indicators, DMS StatLab conducted a survey co-funded by Fondazione della Comunità Bresciana – information about subjects and families’ needs in terms of health and social services are collected.
Dealing with Complexity in Society 5
Civil registry
Subjects:
• name, date and place of birth,
• marital status,
• tax code,
• Individual registry code
Families:
• number of components,
• address,
• parental relationship between members of family,
• family registry code
The registry is an integrated archive that records every event of every subject and family living in Brescia (immigration/emigration to/from another district, date of birth/marriage/death, etc…)
PRINCIPAL INFORMATION AVAILABLE FROM 2008 TO 2013 (December, 31)
Dealing with Complexity in Society 6
Description of families living in Brescia from 2008 to 2013
Single
Couple with son
Couple
Single parent
Nu
mb
er
of
fam
ilies
Dealing with Complexity in Society 7
TRIBUTARY database
Called SIATEL, the database is a telematic system concerning an active exchange of civil and tributary information among public agency.
PRINCIPAL INFORMATION AVAILABLE:
• tax code
• individual income from tax returns
(Models 730, Unico, 770-S)
• gross income and taxes
Dealing with Complexity in Society 8
Civil registry
TRIBUTARY DB
Through data linkage is possible to calculate individual and family income
SURVEY
Data linkage through tax code
Dealing with Complexity in Society 9
• Poverty indicator• Vulnerability indicator
Aim 2: composite indicators
Dealing with Complexity in Society 10
DEFINITION OF POVERTY: a household is “absolutely” poor if its monthly shopping (in euros) is lower than a threshold computed on the basis of number of components of the family, the age and the Italian basket of goods (ISTAT 2009).
NIP =
NIP =
NET INCOME POVERTY (NIP) INDICATOR
Poverty threshold for household type – Net income of household ___________________________________________________________________
Poverty threshold for household type*100
Certainly poor if NIP≥20
Quasi poor household if 0<NIP<20
Quasi non-poor household if -20≤NIP≤ 0
Certainly non-poor household if NIP<-20
Dealing with Complexity in Society 11
NIP INDICATOR%
of
fam
ilies
Single
Couple with son
Couple
Single parent
Single
Couple with son
Couple
Single parent
Total
2008 2009 2010 2011 2012 2013 2013
Total
Dealing with Complexity in Society 12
VULNERABILITY INDICATORS
DEFINITION OF VULNERABILITY (OECD): a household is vulnerable to future loss of well-being below some socially accepted norms if it lacks (or is strongly disadvantaged in the distribution of) assets which are crucial for resilience to risks (Morrone 2014).
As vulnerability is a latent aspect, we developed 3 composite indicators* to describe it (Alkire & Foster 2008 and 2009)
1. Disposable Income Poverty (DIP)2. Economic Structural Autonomy (ESA)3. Demographic Structural Autonomy (DSA)
*inspired to indicators proposed by Alkire and Foster
Dealing with Complexity in Society 13
Disposable Income Poverty (DIP) = where:CE3= Consumption Expenditure sum of last 3 years for the household type (ISTAT)NI3=Net Income sum of last 3 years for the household
Economic Structural Autonomy (ESA)= [-100;+100]where:C* = number of weighted-members of the household I = number of members with an income of the householdnI* = number of non I weighted-members of the household*weigh 1.5 persons aged ≤15 or ≥75
Demographic Structural Autonomy (DSA)= [-100;+100]where:A=number of potentially autonomous members (age 16-74) of the householdnA=number of non A members of the household (age ≤15 or ≥75)C=number of members of the household
CE3-NI3_________
CE3 *100
nA-A_________
C *100
nI*-I_________
C* *100
VULNERABILITY INDICATORSPart 2
Dealing with Complexity in Society 14
As for NIP indicator, DIP, ESA and DSA indicators were categorized as:
VULNERABILITY INDICATORSPart 3
Certainly vulnerable if indicator≥20
Quasi vulnerable if 0<indicator<20
Quasi non-vulnerable if -20≤indicator≤ 0
Certainly non-vulnerable if indicator<-20
Dealing with Complexity in Society 15
DIP INDICATOR%
of
fam
ilies
2008 2009 2010 2011 2012 2013 2013
Single
Couple with son
Couple
Single parent
Total
Single
Couple with son
Couple
Single parent
Total
Dealing with Complexity in Society 16
ESA INDICATOR%
of
fam
ilies
Single
Couple with son
Couple
Single parent
Total
2008 2009 2010 2011 2012 2013 2013
Single
Couple with son
Couple
Single parent
Total
Dealing with Complexity in Society 17
DSA INDICATOR%
of
fam
ilies
2008 2009 2010 2011 2012 2013 2013
Single
Couple
Couple with son
Single parent
Total
Single
Couple
Couple with son
Single parent
Total
Dealing with Complexity in Society 18
As explained before, vulnerability is a latent concept, for this reason we used a combination of DIP, ESA and DSA indicators to measure it.
Following Morrone approach (2014) , we categorized DIP, ESA and DSA as dummies variables where 1 indicate the deprivation status, 0 otherwise (DIP=1 indicate “family non-money saver”, ESA=1 indicates “family non economically autonomous”, DSA=“family non demographically autonomous”)
Vulnerability indicator (k)year=DIPyear+ESAyear+DSAyear
0≤kyear ≤3
In our study k mean per year are:k2010 =0,92k2011 =0,93k2012 =0,94k2013 =0,93
Vulnerability
Dealing with Complexity in Society 19
Vulnerability per number of deprivations over time
A family is vulnerable if k≥2*
k=3 k=2 k=1*as suggested by Morrone (2014)
% o
f fa
mili
es
Dealing with Complexity in Society 20
Vulnerability incidence per poverty over time
Incidence calculated as percentage of vulnerable families
2010 2011 2012 2013 2010 2011 2012 2013
Non-poor families Poor families
% o
f fa
mili
es
Dealing with Complexity in Society 21
Aim 3: DEMAND OF SOCIAL AND HEALTH SERVICES
In order to evaluate demand of social and health services of the residents of the Brescia district, a survey was conducted by University of Brescia (DMS StatLab as first in line) focusing attention on children and adults.
The project is a biennial study (June 2014 – May 2016) co-funded by the Comunità Bresciana Foundation and it is already ongoing. Partners of the projects are the Department of Economics and Management with the DMS StatLab - Data Methods and Systems Statistical Laboratory, the Department of Civil Engineering, Architecture, Land and Environment and the Department of Experimental and Clinical Science of the University of Brescia.
Dealing with Complexity in Society 22
AIM 3: future aspects
The main effort will be to upgrade the poverty and vulnerability composite indicators and to link them with the needs of social and health services (private and public) and their evaluations by the citizens.
Indicators regarding family structure and income will be connected to those calculated from the survey in order to develop an composite indicator.
These composite indicators play a key role in the government, the council can (or should) use them to plan its social and economic policies.
CONCLUSIONS
Dealing with Complexity in Society 23
References
• Jenkins SP, Brandolini A, Micklewright J, Nolan B (2013). The great
recession and the distribution of household income, Oxford University
Press, Oxford.
• European Commission (2013). Quality of life in cities, Publications
Office of the European Union, Luxembourg.
• Istituto Nazionale di Statistica (2009). La misura della povertà assoluta
(Volume Metodi e Norme n. 39 – 2009),
http://www.istat.it/dati/catalogo/20090422_00/
• Morrone A (2014). Measuring Conjoint Vulnerabilities in Italy: An
Asset-Based Approach. Ophi working paper No. 70.
• Alkire S and Foster J (revised 2008). Counting and multidimensional
poverty measurement. Ophi working paper No. 7.
• Alkire S and Foster J (2009). Counting and Multidimensional Poverty
Measurement. Ophi working paper No. 32.
REFERENCES
Acknowledgements
Maurizio Carpita
DMS StatLab, Dep. of Economics and Management (University of Brescia)
Maurizio TiraDep. of Civil Engineering, Architecture, Land and Environment (University of Brescia)
Francesco CastelliDep. of Experimental and Clinical Science (University of Brescia)
Marco TrentiniStatistical Staff of the Brescia district
Fondazione della Comunità Bresciana as co-funder of the project
Dealing with Complexity in Society 25
THE END
Call it a clan, call it a network, call it a tribe, call it a family. Whatever you call it, whoever you are, you need one.(Jane Howard)