Labor reallocation in transition economies has been described using relatively simple models, where workers migrate from the less productive public sector to the private sector. While this might be true, it is only a part of the stories. Other changes happened at the same time as well, in particular a global shift towards services and a generational change. Our presentation explores the relative importance of those changes.

1. Can we really explain worker flows in transition economies?
Can we really explain worker flows in transition
economies?
Evidence from the Life in Transition Survey
Joanna Tyrowicz
Lucas van der Velde
GRAPE
Group for Research in APplied Economics
December 2014,
Warsaw Economic Seminars

2. Can we really explain worker flows in transition economies?
Table of contents
1 Introduction
2 Stories of reallocation
3 Hypotheses
4 Data and methods
5 Results
6 Conclusions

3. Can we really explain worker flows in transition economies?
Introduction
Introduction
Motivation
Analyses so far is highly selective - few countries, few periods
Lack of a solid, complete theoretical basis.
Is transition over? Poland over half million people still in public or
mixed ownership companies. In our sample, public size reduced by
half till 2005.
Our goal: to understand better worker flows in transition economies
Advantage: new, comprehensive retrospective data: Life in
Transition Survey (EBRD)

4. Can we really explain worker flows in transition economies?
Introduction
Countries under study
Table : Countries analysed by previous literature
Year N 89 90 91 92 93 94 95 96 97 98 99 00
Estonia 2
Russia 2
Ukraine 3
Bulgaria 1
Poland 3
Romania 1
Slovenia 2
Slovak 1
Note: Ticks indicate that the countryperiod was analysed in the literature. Papers were searched
for in the EconLit database with keywords: ‘reallocation’; ‘transition’ ‘job creation’ ‘job
destruction’

5. Can we really explain worker flows in transition economies?
Stories of reallocation
Aghion & Blanchard (1994) - optimal speed of transition
Inefficient (public sector) jobs collapse
State can subsidize firms (postpone collapse) or redundant workers
(with safety nets)
Taxes raised to finance this make creating jobs costly,
desynchronizing JD & JC
⇒ Simple link between U, JC and pace of privatization, state can
alleviate social costs of transition by choosing the adequate pace of
job destruction in the public sector
Limits
Simplifications concerning the role of sectoral reallocation
Simplification of the dynamics of the two sectors
Workers homogeneous: no demographics or changes in education -
inconsistent with empirical evidence ???
Extensions: International migration (Bruno, 2006); heterogeneous
workers (Boeri, 2000; Balla, 2008); job-to-job flows (Tichit, 2006)

6. Can we really explain worker flows in transition economies?
Stories of reallocation
Caballero & Hammour (several papers)
Main concept: appropriability
Endogenous job creation and destruction based on capital specificity
and incomplete contracts.
⇒ Used to explain reallocation and technological change in
advanced economies.
Limits
No treatment of public sector / taxes / subsidies
Workers homogeneous: no demographics or changes in education -
inconsistent with empirical evidence (???)
Sectoral changes increase productivity, which is not always true.
(Dimova, 2008; Orazem and Vodopivec, 2009)

7. Can we really explain worker flows in transition economies?
Stories of reallocation
Common limitations in applying these theories to the data
Data limitations on controlling for gross (individual level) and net
(firm level) flows
The different role of worker flows (reallocations) vs job flows
(privatizations)
Privatized vs new (de novo) firms – all private equal?
What if a worker holds more than a one job during the transition
period? Which transition do we capture?

8. Can we really explain worker flows in transition economies?
Hypotheses
Our statements to be tested
1 Flows are generally not AB or CH
2 Demographic changes (new entries and early exits) explain most of
the reallocation
3 AB explains unemployment better than CH in transition countries,
but they both poorly explain employment
4 Channels of mediation suggested by AB and CH do not seem to be
driving the processes, demographics do

9. Can we really explain worker flows in transition economies?
Data and methods
Data sources
Life in transition Survey - 27 transition countries, 18 years
Homogeneous survey compiled by the EBRD in 2006 and 2010.
Life history in the 2006 edition. Sample covers years from 1989 to
2006.
Limitations: missing variables (e.g. wages, firm size), identification
of flows (privatized vs de novo), recall bias.
Other sources
ILO Stat and Fondazione: Wages and EPL
EBRD: Transition measures.
World Bank: GDP per capita.
Penn tables: Labour share in GDP, Employment to population ratio.

10. Can we really explain worker flows in transition economies?
Data and methods
LiTS and other data sources
Country Year
Services Industry Private Services Industry Private
(LFS) (LFS) (SES) (LiTS) (LiTS) (LiTS)
Bulgaria
2000 51.8 39.6 57.2 36.0 48.7
2002 54.9 38.3 55.9 60.0 34.4 53.5
Estonia
1997 53.1 33.1 58.4 30.6 52.7
2002 56.0 32.9 91.8 59.8 30.9 62.2
Latvia
1998 47.4 30.1 67.1 23.6 51.2
2002 49.0 27.7 88.0 67.1 24.4 59.7
Poland
2000 46.1 40.1 59.6 34.6 50.0
2002 51.5 37.8 47.1 59.0 34.3 53.4
Romania
1997 48.4 22.8 54.1 39.7 44.2
2002 58.0 24.7 65.3 58.8 36.1 54.8
Slovakia
1998 50.2 29.2 62.6 30.1 39.7
2002 52.7 27.7 63.0 65.6 28.6 45.9
Note: Own calculation on the basis of data from LiTS, the EU-Labour Force Surveys (LFS) and
the Structure of Earnings Survey (SES).

11. Can we really explain worker flows in transition economies?
Data and methods
Unemployment rates
Figure : Fit of the unemployment rates

12. Can we really explain worker flows in transition economies?
Data and methods
Overall labour market trends
Figure : Changes in the labour market composition.4.45.5.55.6.65
Female
1990 1995 2000 2005
30354045
Age
1990 1995 2000 2005
.1.2.3.4.5.6
HighEd.
1990 1995 2000 2005
0.2.4.6.8
Private
1990 1995 2000 2005

13. Can we really explain worker flows in transition economies?
Results
Definitions
AB: public ⇒ private sector (within the same industry)
CH: manufacturing ⇒ services (within the same sector)
ABCH: public manufacturing ⇒ private services
NONE: private service ⇒ public manufacturing
SAME: within sector and industry
EXIT: To retirement
ENTRY: Into employment

14. Can we really explain worker flows in transition economies?
Results
H1: which flows dominate? How much the models explain?
Figure : Relative importance of different flows
0 .2 .4 .6 .8 1
AZE
ARM
TJK
GEO
MKD
BIH
MNE
KGZ
ALB
MDA
SRB
SVK
BLR
HRV
UZB
SVN
POL
LTU
UKR
ROM
BGR
KAZ
CZE
EST
RUS
HUN
LVA
AB CH SAME ABCH
NONE To retirement From school

15. Can we really explain worker flows in transition economies?
Results
One speed of transition? + job-to-job flows dominate!
Figure : Evolution of different flows0246
1990 1995 2000 2005
AB
CH
ABCH
SAME
NONE

16. Can we really explain worker flows in transition economies?
Results
H2: which flows explain employment?
Table : Movements to employment
N⇒ E U⇒ E E⇒ E
AB 0.968*** 0.868*** 0.917***
CH 0.649*** 0.662*** 0.594***
ABCH -0.623*** -0.592*** -0.531***
Same industry - Manufacturing 0.102*** 0.348*** 0.479***
Same sector - Public 0.883*** 0.882*** 0.916***
Same Sector - de novo 0.854*** 0.892***
Reincidence of unemployment -0.207*** -0.004***
Personal characteristics Yes Yes Yes
Country dummies Yes Yes Yes
Year dummies Yes Yes Yes
Number of id 15,131 9,968 13,107
R2
between 0.825 0.276 0.641
R2
within 0.834 0.314 0.641
Notes: Panel linear probability models (RE). Robust standard errors used but not reported.
Asterisks denote 1 % confidence levels

17. Can we really explain worker flows in transition economies?
Results
H3: which flows explain unemployment (better)?
Table : Link between unemployment rates and flows
AB CH SAME ABCH NONE EXIT ENTRY
flow2
0.057*** 0.089 0.009 0.220* 0.026 0.006 0.037*
flow -0.789*** -0.688 -0.533*** -1.067** -0.595* -0.060 -0.762***
N 486 486 486 486 486 486 486
R2
0.888 0.885 0.890 0.886 0.886 0.885 0.889
Notes: In all cases the dependent variable was detrended Unemployment Rate. The independent
variables are the total number of flows of each type in each country.

18. Can we really explain worker flows in transition economies?
Results
Tehnical note on duration models
Used to model in a time-event framework → event is ”death”
We employ proportional hazard model :
λ(t, x, α, β) = λ0(t, α)φ(xβ)
Cox partial likelihood method:
Conditional probability that an observation finishes in t
= λt (t,β,x)
n
i=1 λt (t,β,x)
In a competing risks model, individuals can ”die” in different ways

19. Can we really explain worker flows in transition economies?
Results
Examples of survival and hazard functions
0.000.250.500.751.00
0 5 10 15 20
analysis time
Primary Secondary Tertiary
Kaplan-Meier survival estimates

20. Can we really explain worker flows in transition economies?
Results
Examples of survival and hazard functions
.04.06.08.1.12
0 5 10 15 20
analysis time
Primary Secondary Tertiary
Smoothed hazard estimates

21. Can we really explain worker flows in transition economies?
Results
H4: do the channels of mediation work?
Table : Durations models
VARIABLES TOTAL CH AB (de novo)
Unemployment rate 8.850*** 9.035*** 8.435***
Unemployment rate 2 -12.305*** -18.396*** -16.145***
Entry 3.727*** 8.737*** 6.219***
Exit 2.950 0.676 7.472**
ULC dynamics -0.062 0.878 -0.601
Public 0.472*** 0.346** 2.917***
De novo 0.049 -0.001 0.486
Manufacturing 0.455*** 0.190 0.522***
Construction 0.457*** 0.190 0.834***
Services 0.527*** -0.283* 0.756***
High skill jobs -0.340*** -0.210 -0.143
Personal characteristics Yes Yes Yes
AIC 39362.182 6618.8377 8937.4545
BIC 39517.767 6774.4224 9093.0392
Notes: Estimates from a proportional hazard Cox model with country specific baseline hazard
ratios.

22. Can we really explain worker flows in transition economies?
Results
Bonus round: Winners and losers of transition
N⇒ E U⇒ E E⇒ E
Female -0.003*** 0.002 -0.003***
(-3.257) (0.510) (-3.395)
Age (in tens) 0.002*** 0.200*** -0.012***
(4.351) (30.095) (-5.400)
Age (In thous) -0.004*** -0.294*** 0.008***
(-8.930) (-35.521) (3.263)
Urban 0.001 0.000 0.001
(0.637) (0.062) (0.718)
Secondary education 0.003*** 0.049*** -0.001
(3.344) (10.823) (-0.864)
Tertiary education 0.015*** 0.133*** -0.004**
(6.010) (19.091) (-2.281)
Observations 196,743 65,194 133,619
Number of id 15,131 9,968 13,107
R2
between 0.641 0.641 0.641
R2
within 0.641 0.641 0.641

23. Can we really explain worker flows in transition economies?
Conclusions
Summarizing
1 The focus on AB and CH movements is not enough in transition
economies.
2 Demographic flows were of great significance and should be considered in
further analysis
3 Individual characteristics played an important role: winners and losers of
transition.
4 Unemployment rates have an impact on flows, but the transmission
mechanisms should be reconsidered
What is next?:
Corroborate our findings with national data sources.
Deepen the analysis of the role of institutions on labor market transitions.
Develop an integrated ABCH model of transitions.

24. Can we really explain worker flows in transition economies?
Conclusions
Questions or suggestions?
Thank you for your attention