Efficiency analysis of social protection expenditure in the Italian Regions

The attention and demand for greater social protection is increasing among the populations of all European countries. It is difficult to identify which of the structures and infrastructures, sectors and regional budgets are inefficient and/or negligent in respect of providing more social protection. In the political sphere the problem is examined from a qualitative point of view, because it is essential to have a valid decisional support system that provides useful information for structural and economic intervention programs devised to improve social protection. Regional spending on social protection is a fundamental component of individual well-being. This work is precisely aimed at assessing individual well-being in terms of technical expenses efficiency in the Italian Regions. Stochastic frontier analysis and a nonparametric deterministic model structure are the tools used to investigate the social protection determinants in the paper.

[1] European Commission. Impact Assessment accompanying the document Proposal
for a Council recommendation on access to social protection for workers and the
self-employed, SWD (2018) 70 final. 2018.
[2] Bacchini, F., Ruggeri-Cannata, R., & Don a, E. Evaluating economic and social
convergences across European countries: could Macroeconomic Imbalance
Procedure indicators shed some light?. Stat J IAOS, (Preprint), 1-11.
[3] Frenda, A., Scippacercola, S., Integrated indicators for the analysis of the Italian
social security system - conference IES 2019 – statistical evaluation systems at 360◦
– techniques, technologies and new frontiers – july, 4,5/2019 – European
University of Rome.
[4] Piketty T. The economics of inequality. Belknap Press of Harvard Press; 2015.
[5] Rawls J. Justice as Porcelli, F. In: Measurement of technical efficiency. a brief
survey on parametric and non-parametric techniques. University of Warwick;
1985. p. 11. 2009.
[6] European system of national and regional accounts 2010 (ESA2010) published in
the official journal on 26 june 2013. 2013. Eurostat.
[7] Kutzin J. Bismarck vs. Beveridge: is there increasing convergence between health
financing systems?. In: Presentation to the organisation for economic cooperation
and development; 2011.
[8] Istat, Annuario Statistico Italiano (ASI). edizione, ISBN 978-88-458-1966-7.
[9] Istat rapporto annuale. 2019. Roma.
[10] Aigner D, Lovell CA, Schmidt P. Formulation and estimation of stochastic frontier
production function models. J Econom 1977;6:21–37.
[11] Battese GE, Corra GS. Estimation of a production frontier model: with application
to the pastoral zone of eastern Australia. Aust J Agric Resour Econ 1977;21:
169–79.
[12] Meeusen W, Van Den Broek J. Efficiency estimation from cobb-douglas production
functions with composed error. Int Econ Rev 1997;18:435–44.
[13] Farrell MJ. The measurement of Productive. Efficiency Journal of the Royal
Statistical Society Series A 1957;120. Part3.
[14] Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making
units. Eur J Oper Res 1978;2:429–44.
[15] Banker RD, Charnes A, Cooper WW. Some models for estimating technical and
scale inefficiencies in data envelopment analysis. Manag Sci 1984;30:1078–92.
[16] Scippacercola S, D’Ambra L. Estimating the relative efficiency of secondary schools
by stochastic frontier analysis. Procedia Economics and Finance 2014;17:79–88.
[17] Scippacercola S, Sepe E. Critical comparison of the main methods for the technical
efficiency. Electronic Journal of Applied Statistical Analysis 2016;9(4):760–80.
[18] Coelli TJ, Rao DSP, O’Donnell CJ, Battese GE. An introduction to efficiency and
productivity analysis. Springer Science & Business Media; 2005.
[19] Stevenson Rodney E. Likelihood functions for generalized stochastic frontier
estimation. J Econom 1980;13(1):57–66.
[20] Greene WH. Maximum likelihood estimation of econometric frontier functions.
J Econom 1980;13:27–56.
[21] Charnes A, Cooper WW, Rhodes E. Evaluating program and managerial efficiency:
an application of data envelopment analysis to program follow through. Manag Sci
1981;27(6):668–97.
[22] Simar L, Wilson PW. Sensitivity analysis of efficiency scores: how to bootstrap in
nonparametric frontier models. Manag Sci 1998;44(1):49–61.
[23] Sengupta JK. Data envelopment analysis for efficiency measurement in the
stochastic case. Comput Oper Res 1987;14(2):117–29.
[24] Porcelli F. Measurement of technical efficiency. a brief survey on parametric and
non-parametric techniques, vol. 11. University of Warwick; 2009.
[25] Cooper WW, Seiford LM, Tone K. Data envelopment analysis: a comprehensive text
with models applications references and DEA-solver software. New York: Springer;
2006.
[26] Thanassoulis E. Introduction to the theory and application of data envelopment
analysis. Springer; 2001.
[27] Ray SC. Data envelopment analysis: theory and techniques for economics and
operations research. Cambridge: Cambridge University Press; 2004.
[28] ESPN. Access to social protection for people in non-standard employment and in selfemployment,
Synthesis report, European Social Policy Network. Publications Office
of the European Union; 2017.
[29] Istat. The final balance sheet accounts of social security Institutions. https://www.
istat.it/it/archivio/218435; 2018.
[30] Istat. The expenditure of municipalities for social services - year 2016. Press
release; 2019. 3 January 2019, https://www.istat.it/it/archivio/225648.
[31] Annuario Statistico Italiano (ASI), (2019), – ISBN 978-88-458-2003-8.
[32] ESSPROS. European system of integrated social protections statistics). EUROSTAT;
2016 [edition].
[33] Istat. Accounts of social protection. http://dati.istat.it/.
[34] Agasisti T, Dal Bianco A, Griffini M. The public sector fiscal efficiency in Italy: the
case of Lombardy municipalities in the provision of the essential public services.
Technical Report No. 691. Italy: Societ`a Italiana di Economia Pubblica, Universit`a
di Pavia; 2015.
[35] Covip. Relazione per l’anno 2016: considerazioni del Presidente. 2017. Roma.
[36] Giorgiantonio C, Bripi F. Governance of Italian pension funds: problems and
solutions. Bank of Italy Occasional Paper; 2010. 65.
[37] Box GE, Cox DR. An analysis of transformations. Journal of the Royal Statistical
Society Series B (Methodological 1964;21.
[38] Akaike H. Factor analysis and AIC. In: Selected papers of hirotugu akaike. New
York, NY: Springer; 1987. p. 371–86.
[39] Kodde DA, Palm FC. Wald criteria for jointly testing equality and inequality
restrictions. Econometrica: journal of the Econometric Society 1986:1243–8.