Abstract
In-work poverty has risen to become a key feature of European societies. In 2017, the percentage of workers at risk of low pay in Italy reached an estimated 25% and the issue rose to the forefront of the public and political debate. Yet, due to data limitations, few studies analysed the local distribution of this phenomenon and investigated the macro-determinants associated with its rise. By applying Small Area Estimates (SAE) to EU-SILC data we obtain a novel map of the distribution of in-work poverty in Italy, defined as the share of workers at risk of low pay (AROLP) between 2008 and 2017. The unit of analysis of Local Labour Systems, a non-administrative unit based on commuter flows, highlights the deepening of Italian dualism between Northern and Southern areas, as well as rising within-region wage inequality. By means of a panel fixed-effects model linking estimates of AROLP with data on local sectoral employment, we observe that growth in low-skill sectors such as agriculture is associated with increases in AROLP incidence. On the contrary trends of low pay are negatively associated with the growth of manufacturing and construction sectors, and jobs in non-market services, such as public sector jobs. In addition, variations in overall employment represent the strongest predictor for dynamics of low-pay incidence.










Similar content being viewed by others
Data availibility statement
The original survey data analysed in the study containing municipality-level identifiers are not publicly available due to confidentiality protocols in place among the data-sharing institutions.
References
Abadie A, Athey S, Imbens GW, Wooldridge JM (2023) When should you adjust standard errors for clustering? Q J Econ 138(1):1–35
Barbieri P, Cutuli G, Scherer S (2018) In-work poverty in southern europe: the case of Italy. In: Lohmann H, Marx I (eds) Handbook on in-work poverty. Edward Elgar Publishing, Cheltenham, UK
Belloc M, Naticchioni P, Vittori C (2023) Urban wage premia, cost of living, and collective bargaining. J Econ Geograph 23(1):25–50
Bennett F (2013) Researching within-household distribution: overview, developments, debates, and methodological challenges. J Marriage Fam 75(3):582–597
Boeri T, Ichino A, Moretti E, Posch J (2021) Wage equalization and regional misallocation: evidence from Italian and German provinces. J Eur Econ Assoc 19(6):3249–3292
Burgard JP, Münnich R, Zimmermann T (2015) Impact of sampling designs in small area estimation with applications to poverty measurement. In: Pratesi M (ed) Analysis of poverty data by small area estimation. Wiley, New York, USA
Casas-Cordero Valencia C, Encina J, Lahiri P (2016) Poverty mapping for the chilean comunas. In: Pratesi M (ed) Analysis of poverty data by small area estimation. Wiley, New York, USA
Cormier D, Craypo C (2000) The working poor and the working of American labour markets. Cambridge J Econ 24(6):691–708
Crettaz E (2013) A state-of-the-art review of working poverty in advanced economies: theoretical models, measurement issues and risk groups. J Eur Soc Policy 23(4):347–362
DIPE. Principali Indicatori Economici Dell’economia Italiana Dal 2000. https://www.programmazioneeconomica.gov.it/andamenti-lungo-periodo-economia-italiana/#Livello20del20PIL20italiano Accessed 2020-11-30
Datta GS, Ghosh M, Steorts R, Maples J (2011) Bayesian benchmarking with applications to small area estimation. Test 20(3):574–588
David H, Dorn D (2013) The growth of low-skill service jobs and the polarization of the us labor market. Am Econ Rev 103(5):1553–97
Duflo E (2003) Grandmothers and granddaughters: old-age pensions and intrahousehold allocation in South Africa. World Bank Econ Rev 17(1):1–25
D’Amuri F, Nizzi R (2018) Recent developments of italy’s industrial relations system. E J Int Comp Lab Stud 7(2):19–47
EUROSTAT (2022) Living conditions in europe—work intensity, 2020. Technical report, EUROSTAT
Faggio G, Nickell S (2005) The responsiveness of wages to labour market conditions in the UK. Lab Econ 12(5):685–696
Fay RE III, Herriot RA (1979) Estimates of income for small places: an application of James-Stein procedures to census data. J Am Statist Assoc 74(366a):269–277
Filandri M, Struffolino E (2019) Individual and household in-work poverty in europe: understanding the role of labor market characteristics. Eur Soc 21(1):130–157
Foster-McGregor N, Hanzl-Weiss D, Leitner SM, Leitner S, Rabemiafara N, Sanoussi F, Stehrer R, Ward T (2012) Sectoral employment effects of economic downturns. Technical report, wiiw Research Report
Garnero A (2018) The dog that barks doesn’t bite: coverage and compliance of sectoral minimum wages in Italy. IZA J Lab Policy 7(1):1–24
Garnero A, Ciucciovino S, Magnani M, Naticchioni P, Raitano M, Scherer S, Struffolino E (2022) Interventi e misure di contrasto alla povertà lavorativa in italia. Econ lavoro 9(3):9–32
Garnero A, Ciucciovino S, Camillis R, Magnani M, Naticchioni P, Raitano M, Schrerer S, Struffolino E (2021) Relazione del gruppo di lavoro sugli interventi e le misure di contrasto alla poverta’ lavorativa in italia. Technical report, Ministero del Lavoro
Gerlitz J-Y (2018) Rising in-work poverty in times of activation: changes in the distributive performance of institutions over three decades, germany 1984–2013. Soc Indicat Res 140(3):1109–1129
González-Manteiga W, Lombardía MJ, Molina I, Morales D, Santamaría L (2008) Analytic and bootstrap approximations of prediction errors under a multivariate Fay–Herriot model. Comput Statist Data Anal 52(12):5242–5252
Gregg P, Machin S, Fernández-Salgado M (2014) Real wages and unemployment in the big squeeze. Econ J 124(576):408–432
Gregg P, Machin S (2012) What a drag: the chilling impact of unemployment on real wages. September. (Resolution Foundation.)
Hadam S, Würz N, Kreutzmann A-K, Schmid T (2023) Estimating regional unemployment with mobile network data for functional urban areas in Germany. Stat Methods Appl 33:205–233
Halleröd B, Ekbrand H, Bengtsson M (2015) In-work poverty and labour market trajectories: poverty risks among the working population in 22 European countries. J Eur Soc Policy 25(5):473–488
Harmening S, Kreutzmann A-K, Schmidt S, Salvati N, Schmid T (2023) A framework for producing small area estimates based on area-level models in r. R J 15(1):316–341
ISTAT (2022) Dati Complementari Sul Mercato di Lavoro. http://dati.istat.it/Index.aspx?QueryId=56084#
Iadevaia V, et al (2012) Dimensioni e caratteristiche del lavoro sommerso/irregolare in agricoltura. Isfol
Jensen JLWV et al (1906) Sur les fonctions convexes et les inégalités entre les valeurs moyennes. Acta Math 30:175–193
Jiang J, Lahiri P, Wan S-M, Wu C-H (2001) Jackknifing in the Fay–Herriot model with an example. Proc Sem Fund Opport Surv Res 90:75–97
Kreutzmann A-K, Pannier S, Rojas-Perilla N, Schmid T, Templ M, Tzavidis N (2019) The R package emdi for estimating and mapping regionally disaggregated indicators. J Statist Softw 91(7):1–33. https://doi.org/10.18637/jss.v091.i07
Lohmann H (2018) The concept and measurement of in-work poverty. In: Lohmann H, Marx I (eds) Handbook on in-work poverty. Edward Elgar Publishing, Cheltenham, UK
Lohmann H, Marx I (2018) Handbook on In-work Poverty. Edward Elgar Publishing, Cheltenham, UK
Lucifora C, Vigani D (2021) Losing control? unions’ representativeness, pirate collective agreements, and wages. Indus Relat A J Econ Soc 60(2):188–218
Lundberg S, Pollak RA (1996) Bargaining and distribution in marriage. J Econ Perspect 10(4):139–158
Marhuenda Y, Molina I, Morales D (2013) Small area estimation with spatio-temporal Fay–Herriot models. Comput Statist Data Anal 58:308–325
OECD.Stat. National Accounts (2023a) https://data-explorer.oecd.org/?fs[0]=Topic%2C1%7CEconomy%23ECO%23%7CNational%20accounts%23ECO_NAD%23 &pg=0 &fc=Topic &bp=true &snb=105
OECD.Stat. Average Annual Wages (2023b) https://stats.oecd.org/Index.aspx?DataSetCode=AV_AN_WAGE%20#
Rao JN, Molina I (2015) Small area estimation. John Wiley & Sons, Hoboken, New Jersey
Schmid T, Bruckschen F, Salvati N, Zbiranski T (2017) Constructing sociodemographic indicators for national statistical institutes by using mobile phone data: estimating literacy rates in senegal. J R Statist Soc Ser A (Statist Soc) 180(4):1163–1190
Sissons P, Green AE, Lee N (2018) Linking the sectoral employment structure and household poverty in the united kingdom. Work Employ Soc 32(6):1078–1098
Tomassetti P (2016) La nozione di sindacato comparativamente più rappresentativo nel decreto legislativo n. 81/2015. Diritto delle Relaz Ind 26(2):368–392
Tomlinson M, Walker R (2010) Recurrent poverty: the impact of family and labour market changes. Joseph Rowntree Foundation, York
Wannell T, Usalcas J (2012) Labour force survey: 2011 year-end review. Perspect Lab Income 24(2):1
Funding
The authors received no financial support for the research, authorship, and publication of this article.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Tonutti, G., Garnero, A., Bertarelli, G. et al. The local distribution of in-work poverty and sectoral employment: an analysis of local dynamics in Italy. Stat Methods Appl 33, 973–998 (2024). https://doi.org/10.1007/s10260-024-00756-y
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10260-024-00756-y