Title: Modelling unemployment inflows and outflows in the Italian Labour Market
1Modelling unemployment inflows and outflows in
the Italian Labour Market
- Baussola, M., Fabrizi, E., Mussida, C.
- Catholic University of the Sacred Heart
(Piacenza) - Monitoring Italy 2009 Measuring the progress of
Italian society - Isae, Rome, 3-4 June 2009
2Labour mobility and unemployment in Italy
- Labour mobility has always been a controversial
issue - the debate originated in the 70s depicted the
Italian labour market as typically affected by
insider power - the idea that Italian labour market was
substantially tight was prevailing, but no
accurate data were available to investigate this
issue in depth
3- New information available from the Italian
Institute of Statistics (Istat) during the 80s
help to build a dynamic picture of the labour
market - the Italian labour market was treated as a single
and tight market with insufficent mobility - such a pitfall in the analyses has been only
recently recognised (Trivellato, 2005) by
investigating Italian labour mobility in depth - earlier studies (Baussola, 1985) emphasized how
labour market flows were significant and how they
affected the steady-state unemployment rate
4- The 90s had been characterised by debate on the
need of new labour market legislation, aimed to
improve labour flexibility and increasing
employment opportunities - new regulations have been introduced the main
interventions refer to Treus legislation package
and, at the beginning of the new millenium, to
Biagis law - but aggregate comparable data on labour market
flows for the decade 1993-2003 do not show any
significant impact on aggregate labour mobility.
5Stocks and Flows in the Labour Market,
longitudinal population 1993-1994 (thousands)
ue 448 (20.1)
ne 897 (5.6)
eu 392 (2)
en 1,113 (5.7)
un 673 (30.2)
nu 825 (5.2)
Transition probabilities in brackets Source
Authors calculation using weighted longitudinal
LFS micro data (Istat)
6Stocks and Flows in the Labour Market,
longitudinal population 2002-2003 (thousands)
ue 427 (20.3)
ne 831 (5.6)
eu 270 (1.3)
en 701 (3.4)
un 542 (25.7)
nu 664 (4.5)
Transition probabilities in brackets Source
Authors calculation using weighted longitudinal
LFS micro data (Istat)
7Stocks and Flows in the Labour Market, EU-SILC
longitudinal population 2004-2005 (thousands)
ue 519 (19.2)
ne 627 (3.5)
eu 564 (2.6)
en 1,345 (6.2)
un 586 (21.7)
nu 764 (4.2)
Transition probabilities in brackets Source
Authors calculation using weighted longitudinal
EU-SILC micro data
8Stocks and Flows in the Labour Market,
longitudinal population 2006-2007 (thousands)
ue 395 (21)
ne 729 (5.6)
eu 300 (1.3)
en 751 (3.3)
un 401 (23.5)
nu 325 (2.5)
Transition probabilities in brackets Source
Authors calculation using weighted longitudinal
LFS micro data (Istat)
9The determinants of labour market transitions a
multinomial logit approach
- Explanatory variables
- sex, age, agesq, married (unmarried), hhsize
- northwest, northeast, centre, (southislands)
- unempl2004, empl2004
- qu1, qu2, qu3, qu4, (qu5)
- comp, diploma, (degree)
- transition
- () base categories in brackets
10Marginal Effects after MNL for outflows from U
11(continue)
() dy/dx is for discrete change of dummy
variable from 0 to 1 () only vaiables relevan
for our investigatio are reported
12Marginal Effects after MNL for outflows from E
13(continue)
() dy/dx is for discrete change of dummy
variable from 0 to 1 () only vaiables relevan
for our investigatio are reported
14Estimates and implications
- Successful exits from U (UE) are more strongly
determined by geographical dummies, lagged U
status, quintiles of income distribution,
presence of labour market transitions within the
twelve months. Also education plays a role - Sex, age and its squared, and marital status are
the main drivers for the exits from the labour
force (UN) - There is evidence of state dependence for UE the
state of U acts as a trap for individual by
causing a sort of lock-in into this condition and
by alimenting the persistence - The estimated coefs for quintiles of the
equivalised disposable income are all negative
and significant with respect to the fifth
quintile (base)
15(continue)
- Education plays a role relevance of tertiary
education attainment title - The presence of labour market transitions within
the twelve months increases the probability of
making other transitions in the consecutive
period - Being male reduces the odds of exiting the labour
force relative to remaining U (UN) by 30
compared to a female being male raises the
likelihood of leaving U with success (UE) by 21
percentage points in 2005-2006
16Conclusions
- We have set up an empirical framework to
analyzing labour market transitions and their
determinants - our findings suggest that human capital, income,
geographical residence, experienced mobility and
state dependence strongly determine UE - these variables, with the exclusion of human
capital proxy and the inclusion of the sex dummy,
are also crucial in causing EU - these results enable us to complete the puzzle of
labour mobility in Italy and its effect on U and
U duration - an increase in this latter is inferred although
labour mobility is not negligible, especially
with respect to U stock
17(continue)
- Labour mobility is encouraged, on tho one hand,
by previous transitions in the labour market, and
by variables reflecting personal characteristics
or structural factors such as the geographical
location - Labour mobility is strongly affected and as
concern the U outflow, is strongly reduced by
previous U conditions - This evidence suggests existence of hard core
unemployment not affected by those changes in
labour legislation introduced in the last decade
this core U is therefore related to structural
factors which implicitly suggest the need of
policy interventions.