can we really explain worker flows in transition?
TRANSCRIPT
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Can we really explain worker flows in transition economies?
Can we really explain worker flows in transitioneconomies?
Evidence from the Life in Transition Survey
Joanna TyrowiczLucas van der Velde
GRAPEGroup for Research in APplied Economics
December 2014,Warsaw Economic Seminars
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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
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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 ormixed ownership companies. In our sample, public size reduced byhalf till 2005.
Our goal: to understand better worker flows in transition economies
Advantage: new, comprehensive retrospective data: Life inTransition Survey (EBRD)
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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 01 02 03 04
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 searchedfor in the EconLit database with keywords: ‘reallocation’; ‘transition’ ‘job creation’ ‘jobdestruction’
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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 canalleviate social costs of transition by choosing the adequate pace ofjob destruction in the public sector
Limits
Simplifications concerning the role of sectoral reallocationSimplification of the dynamics of the two sectorsWorkers homogeneous: no demographics or changes in education -inconsistent with empirical evidence ???
Extensions: International migration (Bruno, 2006); heterogeneousworkers (Boeri, 2000; Balla, 2008); job-to-job flows (Tichit, 2006)
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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 specificityand incomplete contracts.
⇒ Used to explain reallocation and technological change inadvanced economies.
Limits
No treatment of public sector / taxes / subsidiesWorkers 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)
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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 transitionperiod? Which transition do we capture?
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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 ofthe 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 bedriving the processes, demographics do
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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 to2006.Limitations: missing variables (e.g. wages, firm size), identificationof flows (privatized vs de novo), recall bias.
Other sources
ILO Stat and Fondazione: Wages and EPLEBRD: Transition measures.World Bank: GDP per capita.Penn tables: Labour share in GDP, Employment to population ratio.
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Can we really explain worker flows in transition economies?
Data and methods
LiTS and other data sources
Country YearServices Industry Private Services Industry Private(LFS) (LFS) (SES) (LiTS) (LiTS) (LiTS)
Bulgaria2000 51.8 39.6 57.2 36.0 48.72002 54.9 38.3 55.9 60.0 34.4 53.5
Estonia1997 53.1 33.1 58.4 30.6 52.72002 56.0 32.9 91.8 59.8 30.9 62.2
Latvia1998 47.4 30.1 67.1 23.6 51.22002 49.0 27.7 88.0 67.1 24.4 59.7
Poland2000 46.1 40.1 59.6 34.6 50.02002 51.5 37.8 47.1 59.0 34.3 53.4
Romania1997 48.4 22.8 54.1 39.7 44.22002 58.0 24.7 65.3 58.8 36.1 54.8
Slovakia1998 50.2 29.2 62.6 30.1 39.72002 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) andthe Structure of Earnings Survey (SES).
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Can we really explain worker flows in transition economies?
Data and methods
Unemployment rates
Figure : Fit of the unemployment rates
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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
.5.5
5.6
.65
Fem
ale
1990 1995 2000 2005
3035
4045
Age
1990 1995 2000 2005
.1.2
.3.4
.5.6
Hig
h E
d.
1990 1995 2000 2005
0.2
.4.6
.8P
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e
1990 1995 2000 2005
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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
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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
AZEARMTJK
GEOMKDBIH
MNEKGZALB
MDASRBSVKBLRHRVUZBSVNPOLLTUUKRROMBGRKAZCZEESTRUSHUNLVA
AB CH SAME ABCH
NONE To retirement From school
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Can we really explain worker flows in transition economies?
Results
One speed of transition? + job-to-job flows dominate!
Figure : Evolution of different flows0
24
6
1990 1995 2000 2005
ABCH
ABCHSAME
NONE
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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 YesCountry dummies Yes Yes YesYear dummies Yes Yes Yes
Number of id 15,131 9,968 13,107R2 between 0.825 0.276 0.641R2 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
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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
flow 2 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 486R2 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 independentvariables are the total number of flows of each type in each country.
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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)∑ni=1 λt (t,β,x)
In a competing risks model, individuals can ”die” in different ways
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Can we really explain worker flows in transition economies?
Results
Examples of survival and hazard functions
0.00
0.25
0.50
0.75
1.00
0 5 10 15 20analysis time
Primary Secondary Tertiary
Kaplan-Meier survival estimates
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Can we really explain worker flows in transition economies?
Results
Examples of survival and hazard functions
.04
.06
.08
.1.1
2
0 5 10 15 20analysis time
Primary Secondary Tertiary
Smoothed hazard estimates
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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 -0.601Public 0.472*** 0.346** 2.917***De novo 0.049 -0.001 0.486Manufacturing 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 -0.143Personal characteristics Yes Yes YesAIC 39362.182 6618.8377 8937.4545BIC 39517.767 6774.4224 9093.0392
Notes: Estimates from a proportional hazard Cox model with country specific baseline hazardratios.
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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 65,194 133,619Number of id 15,131 9,968 13,107R2 between 0.641 0.641 0.641R2 within 0.641 0.641 0.641
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Can we really explain worker flows in transition economies?
Conclusions
Summarizing
1 The focus on AB and CH movements is not enough in transitioneconomies.
2 Demographic flows were of great significance and should be considered infurther analysis
3 Individual characteristics played an important role: winners and losers oftransition.
4 Unemployment rates have an impact on flows, but the transmissionmechanisms 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.
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Can we really explain worker flows in transition economies?
Conclusions
Questions or suggestions?
Thank you for your attention