1. Gli indici di sviluppo locale umano applicati ai territori toscani
XXII° Edizione
Nuovo sviluppo industriale e politiche di sistema 8-10 Ottobre 2012, Villa Medicea di Artimino
Gli indici di sviluppo locale umano applicati ai territori toscani
Mario Biggeri
Dipartimento di Scienze per l'Economia e per l'Impresa, Università di Firenze
Centro interuniversitario di Economia Applicata alle Politiche per l’Industria,
lo Sviluppo locale e l'Internazionalizzazione (c.MET05)
con il contributo di Marco Bellandi, Andrea Ferrannini e Vincenzo Mauro

2. Introduction
- We present a statistical-economic approach based on the integration between the literature on local development and the human development perspective. - This integration focuses on local opportunities and it applies an innovative interpretative framework to sub-regional development paths of Tuscany provinces which jointly analyses the economic and the social dimensions at local level.

3. Premise 1
- Italian literature on the social dimension of local systems (Bacci, Bagnasco, Becattini, Brusco, Dei Ottati, Trigilia, …)
“Multiple paths of local development” (Bellandi and Sforzi, 2003 in Becattini, Bellandi, Dei Ottati and Sforzi, From Industrial Districts to Local Development) 3

4. Premise 2 - Sustainable Human Development (Amartya Sen, 1999)
- Capability approach as an opportunity-based theory
- GDP vs multidimensionality, Human Development Index (HDI)
- Integration among micro-meso-macro levels
 This perspective could bring to important results in terms of analysis and of policy implications from a social and economic point of view and development processes at the local level. 4

5. Premise 3 Inappropriateness of unique mono-dimensional indicator
Going beyond the GDP (Stiglitz – Sen – Fitoussi Commission, 2009)
Need to take into account synergies and complementarities between economic and social dimensions 5

6. Objective
Operationalization of the Sustainable Human Development paradigm at local level and empirical application to the case of Tuscany provinces
Will follow:
Interpretative framework on multiple paths of local development
Methodology of analysis and data
Empirical results regarding Tuscany region provinces 6

7. Interpretative framework on multiple paths of local development

8. Sustainable Human Development (SHD)
The dynamic synergy between economic opportunities and social opportunities and how it shapes SHD trajectories.
- The social-environmental dimension SD
The result at aggregate local level of different components determining the social outcomes in terms of Basic Social Services, social integration and participation and environmental protection.
- The economic dimension ED
The result at aggregate level of different components which determine the economic opportunity/efficiency at local level.

9. Interpretative framework

10. The high road to Sustainable Human Development at local level
Source: Mehrotra and Biggeri (2007: 368) 10

11. Methodology of analysis and data

12. Bi-dimensional index
The idea is to represent the units and try to observe their path or shift over time
 Need for two indexes or a bi-dimensional index that can describe both situations
Many approaches are possible to describe both social and economic components: most of them have to face a step where the variables available are aggregated into a (possibly single) value.

13. Geometric interpretation
The index is one minus the quadratic mean of diff. from max (i.e. 1)
 the synergic evolutionary SHD paths of the unit of analysis 13

14. BRICS ( )

15. Italy, US, Netherlands (1990-2005)

16. Italy, US, Netherlands (1990-2005)

17. Empirical results regarding Tuscany region provinces

18. Local development paths: Tuscany region provinces
Rationales for unit of analysis and data base
Characteristics of the analysis:
Dynamic ( ): medium-term analysis with 4-years intervals
Multidimensional: economic and social dimensions with 5 sub-dimensions each

19. Medium-term analysis - 1998 - 2002 - 2006
(or most recent data: )
 4-years intervals are needed to observe significant movements on Local Human Development trajectories

20. Multidimensional analysis
Economic Dimension
(n° indicators)
Social Dimension
Economic opportunities (4)
Environment opportunities (2)
Employment opportunities (3)
Access to health services opportunities (3)
Credit opportunities (4)
Education opportunities (3)
Entrepreneurship opportunities (3)
Participation and social capital opportunities (6)
Investments opportunities (2)
Equal opportunities (8)

21. Main difficulties in data collection
- Missing data in panel series
e.g. Institutional structures and processes (e.g. start up new enterprises, corruption, …); GDP per capita corrected by inequality; Renewable energy; Job-training for persons with disability.
- Change in some statistical indicators
- Poor territorial disaggregation of data (province level)

22. Tuscany Region provinces
Empirical results:
Tuscany Region provinces

23. Framework: Results (1)
1998
1998
1998
1998
1998

24. Framework: Results (2)

25. Wealth, employment and credit
ED disaggregation (1)
Wealth, employment and credit

26. Wealth, employment and credit
ED disaggregation (2)
Wealth, employment and credit

27. SD disaggregation (1)

28. SD disaggregation (2)

29. Main results (a)
- Most units follow routes quite close to a synergic pattern in Tuscany during the first period
- Similar trajectory except for Livorno and Massa-Carrara (decline ED)
- Impact of recent financial crisis: immediate dramatic decline in SD in all provinces
- ED seems to diminish sensitively its level

30. Main results (b)
The sensitivity analysis confirmed our results (not driven by a unique group of variables).
The disaggregate analysis in the ED indicates a more diffused attention towards variables affecting wealth, employment and credit opportunities.
- The disaggregate analysis in the SD indicates a general tendency towards a more synergistic path before the crisis.
- The economic and social dimensions interactions

31. Main conclusions
- Relevance of changing perspective and objective with an integrated framework focused on ED-SD synergies
- Benefit of path analysis with an evolutionary medium-term view:
Replicable to other case studies
Easy to be continuously updated
Policy implications

32. Next research steps Improving data selection and collection
On-going discussion on dimensions, opportunities and variables
- Application to different regions and to different unit of analysis (e.g. local development systems and/or local labour systems)
Systematic cross-validation with other reports and empirical analyses

33. Comments are more than welcome
Thank you !
Comments are more than welcome
We are grateful to Marco Bellucci and Annalisa Caloffi for their contribution in this research

34. Appendix II: Selected variables for Tuscany provinces (1)
Economic dimension
Wealth
GDP per capita
Entrepreneurship
Industrial value-added per worker
Freedom from Debt per capita
Turn-over of local firms
Bank savings per capita
Density of firms
Financial autonomy
Investments
Hi-Tech firms
Employment
Employment rate
Provincial capital account expenditures
Freedom from CIG hours per worker
Credit
Bank branches per capita
Subsidized credit per capita
ATM per squared km
Freedom from Accounts uncollectible

35. Appendix II: Selected variables for Tuscany provinces (2)
Social dimension
Environment
Provincial expenditure for environmental protection
Health
Coverage of mammography prevention
“Legambiente” Ecosystem Index
Health workers per capita
Education
Graduates per capita
Freedom from Work injuries
Provincial expenditures for professional education
Equal opportunities
<35 in provincial administration
Coverage of professional education courses
Women in provincial administration
Teachers per pupil
Female unemployment
Participation and social capital
Blood donations per capita
Youth unemployment
Waste recycling
Waiting list for kindergarten
Newspapers diffusion
Learning support teachers
Electoral participation
Women in local firms
N° of volunteering organizations
<30 in local firms
Freedom from Juvenile reports
Foreign entrepreneurship

36. Classic perspective: GDP per capita
Source: Sole24Ore and ISTAT