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TITLE : Employment and Unemploymen tafter Communism
AUTHOR : Simon Johnso n
THE NATIONAL COUNCI LFOR SOVIET AND EAST EUROPEA N
RESEARC H
TITLE VIII PROGRA M
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CONTRACTOR :
Duke Universit y
PRINCIPAL INVESTIGATOR :
Simon Johnso n
COUNCIL CONTRACT NUMBER :
806-30
DATE :
February 2, 1994
COPYRIGHT INFORMATION
Individual researchers retain the copyright on work products derived from research funded b yCouncil Contract. The Council and the U.S. Government have the right to duplicate written reportsand other materials submitted under Council Contract and to distribute such copies within th eCouncil and U .S. Government for their own use, and to draw upon such reports and materials fo rtheir own studies; but the Council and U.S. Government do not have the right to distribute, o rmake such reports and materials available, outside the Council or U .S. Government without thewritten consent of the authors, except as may be required under the provisions of the Freedom o fInformation Act 5 U.S. C. 552, or other applicable law.
The work leading to this report was supported in part by contract funds provided by the National Counci lfor Soviet and East European Research, made available by the U. S. Department of State under Title VIII (th eSoviet-Eastern European Research and Training Act of 1983) . The analysis and interpretations contained in th ereport are those of the author.
Employment and Unemployment After Communis m
Simon JohnsonThe Fuqua School of Busines s
Duke UniversityDurham, NC 27708
Revised January 24, 1994
Prepared for a Hoover Institution bookon economic reform in Eastern Europe and the former Soviet Union ,
edited by Edward Lazear .
Generous financial support was provided by Xerox Faculty Research Funds and The NationalCouncil for Soviet and East European Research . Very helpful comments on an earlie rversion were provided by participants at Second Workshop, World Bank Research Project o n"The Labour Market in Transitional Socialist Economies" in April 1993, and at the NBE RSummer Workshop on Labor Economics in August 1993 .
Summary
Evidence from 12 countries in Eastern Europe and the former Soviet Union suggest s
that a significant increase in unemployment is an unavoidable consequence of economi c
reform . Initially, state enterprises try to maintain employment levels even in the face o f
steep output declines, preferring to reduce hours worked and to cut real wages . Over time
they begin to fire workers, starting with those they consider least essential . In the first two
years of serious economic reform, state industrial employment usually falls by 25-30 percent .
There are a large number of new employment opportunities in the private sector, bu t
many of these are taken by people who voluntarily quit the state sector . Once fired, man y
former state workers have difficulty obtaining a new job . Rates of reemployment are
particularly low for women and older people .
In almost every country in Eastern Europe unemployment starts close to zero, rises 5 -
10 percentage points in the first year and a further 5-10 percentage points in the second yea r
of serious reform . The same pattern is seen irrespective of whether the government is tryin g
to go "fast" or "slow" on economic reform . Unemployment rates in Eastern Europe ar e
likely to remain over 15 percent in the foreseeable future, with a high proportion of th e
total -- probably over 50 percent -- being long-term unemployed . The evidence available so
far for the former Soviet Union suggests that serious reform has not yet begun in earnest, bu t
when it does the unemployment outcomes will be similar to those in Eastern Europe .
1
l . Introduction
It has become painfully obvious that the transformation of post-communist economie s
involves a far-reaching change in the structure of employment . The evidence so far -- base d
mostly on experience in Eastern Europe -- indicates a pattern of net job destruction in th e
state sector and net job creation in the private sector . In large part the costs of economic
transformation depend on the relative speeds with which old jobs disappear and new job s
appear, and on the ability of different kinds of people to move between these jobs .
This chapter examines the details of unemployment and employment in the post -
communist countries of Eastern Europe and the former Soviet Union, primarily using officia l
government statistics . However, this data is weak on several key points, particularl y
concerning the precise nature of employment reduction and the rate at which people leav e
unemployment in the former Soviet Union . I therefore also report results from a study o f
unemployment and employment conducted by my own research team in Ukraine .
The four questions addressed and the most important answers provided in this chapte r
are as follows. First, how fast are jobs lost in the state sector? The evidence suggests that
state enterprises are initially reluctant to fire workers, but nevertheless there is a gradual an d
steady reduction in state sector employment . After the first two years of serious economi c
reform, we find that employment in state industry has typically been reduced by around 25 -
30 percent .
Second, precisely who leaves state enterprises and under what circumstances? Th e
facts indicate that the first people to leave are voluntary quits and various types of retiree .
Layoffs grow in absolute and relative size over time, although the first people to be fired are
2
white collar workers and blue collar workers seen by management as not essential to th e
production process .
Third, what happens to people who are fired from the state sector? The official dat a
we report indicates that unemployed people find it very hard to obtain a new job in Easter n
Europe. This is surprising given the rapid growth of the private sector, but several compel -
ling pieces of evidence from Hungary and Poland indicate that the private sector hires people
directly from the state sector rather than from the pool of unemployed .
However, survey evidence from Ukraine suggests that a high proportion of peopl e
who are fired in the former Soviet Union are able to find a new job quickly . The period of
unemployment for these people is so short that they do not register as being unemployed and
it is as if they passed directly from the state sector to the private sector . Even in this more
upbeat interpretation of the evidence, rates of reemployment are lower for women, olde r
people and people with higher education . In addition, many of the new jobs pay low wage s
and represent a fall in people's standard of living . It is probably also true that the hig h
growth rate of private sector employment in 1992-93 in the former Soviet Union cannot be
sustained.
Fourth, what are the outcomes in terms of the unemployment rate in each country ?
We find that in almost every country, irrespective of the precise reform path followed, th e
unemployment rate begins close to zero, shows an increase of up to 10 percentage points i n
the first year after serious economic reform starts and a further 5-10 percentage points in th e
second year .
3
The striking exception is the Czech Republic in which unemployment has already
peaked and is now at around 5 percent, a level which is low by international standards an d
extremely low in comparison with other countries in the region . This unusual performance i s
not yet fully understood, but is probably due to a combination of good luck and good policy
which is difficult to duplicate in other countries .
In summary, the evidence reviewed in this paper indicates that there is a broadl y
similar labor market adjustment process underway in all the post-communist countries o f
Eastern Europe and the former Soviet Union . Real economic reform requires and begin s
with a fall in state sector employment . State industrial enterprises are reluctant to fire
workers and initial employment reductions are due more to voluntary quits and retirements .
Voluntary quits are hired directly by the private sector, although at wages which are usuall y
not much higher than those in the state sector .
Over time state enterprises increasingly fire workers . In Eastern Europe, unemployed
workers find it very difficult to obtain a new job and not many are hired by the privat e
sector on net . In the former Soviet Union, rates of reemployment in the private sector ar e
higher but it is unlikely they can be sustained . If they cannot, then the result will be as i n
Eastern Europe -- the combination of low inflow rates to unemployment and even lowe r
outflow rates mean that the unemployment rate grows and the proportion of long-ter m
unemployed increases .
Section 2 reviews the available cross-country evidence on the four questions outline d
above . Section 3 reports more detailed data on employment reductions and outflows fro m
unemployment in Ukraine . Section 4 concludes with an assessment of the extent to which
4
unemployment outcomes in the former Soviet Union are likely to resemble those in Easter n
Europe .
2 . Cross-Country Evidence
Employment Reduction s
In all these countries, the overall macroeconomic context has been characterized b y
the elimination of excess demand, severe reductions in the production of military goods an d
the complete disruption of the COMECON trading system . As a result, there have bee n
sharp falls in industrial output throughout the region . State enterprises in post-communis t
countries have proved reluctant to fire their workers and have done so only gradually .
In all East European countries the rate of employment reduction in the first 1-2 year s
after reform has been less than the fall in state sector output. In part this is because very
few large state enterprises have been forced to close and various forms of hidden subsidie s
have continued -- such as tax breaks and special credits .
However, it appears true that serious economic reform requires that the budge t
constraint for state enterprises be hardened considerably . All attempts at reform in Eastern
Europe and the Soviet Union without this condition have failed . As a result economi c
reform begins with serious pressure being put on state enterprises to improve their financia l
performance. The combination of adverse macroeconomic conditions and tighter budget
constraints has therefore meant that state enterprises have released workers steadily and thi s
has had a large cumulative effect .
5
For example, economic reform began in earnest in Poland with the Balcerowicz Pla n
which was initiated at the beginning of 1990. At that time almost all industry was in the
state sector. Employment in Polish industry fell from 3 .979 million to 3 .632 million, i .e. by
8 .7 percent, in the course of 1990 . Industrial employment declined further to reach 3 .554
million by June 1991, a fall of 2.2 percent from December 1990 and a total cumulative fal l
of 11 percent (Coricelli and Revenga 1992, Table l) . However, from that date these
aggregate numbers become increasingly unreliable because they do not allow us to distinguis h
the effect of growing private sector industrial production .
More reliable evidence in this regard is provided by a survey of 75 state firms i n
Poland which showed a total cumulative reduction in employment of 26 .8 percent fro m
September 1989 to June 1992 . Employment rose 0 .8 percent from September to Decembe r
1989 -- the quarter before economic reform really began . In the immediate aftermath o f
reform, employment fell 5 percent from December 1989 to June 1990 and a further 5 percen t
from June to December 1990. It then fell 6 .6 percent from December 1990 to June 1991 ,
7.0 percent from June to December 1991 and 7 .1 percent from December 1991 to June 1992
(Pinto, Belka and Krajewski 1993, Table 2) .
However, the output and sales declines in these firms were initially much larger - -
around 20-30 percent by the middle of 1990 . Differences in performance subsequentl y
emerged, but even the group of firms which did best showed a continued fall in employment .
In mid-1992 most managers said that their firms continued to have excess employment ,
although in all cases other than the worst performing firms, the percent of excess labor wa s
considered to be less than 10 percent (Pinto, Belka and Krajewski 1993, Table 14) .
6
The former Soviet Union appears to be following the same path, although in most
places it is still at the early stage in which output has fallen but state enterprises continue t o
hold onto labor . For example, in Kazakhstan there was a 10 percent fall in output in 199 1
and a 14 percent fall in 1992 (EBRD 1993, p .118) . But state enterprises have preferred to
reduce hours worked, close temporarily and cut real wages rather than fire people . With a
workforce of 7.3 million, unemployment rose from 18,000 in December 1992 to 70,000 i n
March 1993 . However, further firings may be imminent -- the Minister of Labor predicte d
unemployment would reach 500,000 by the end of 1993, so unemployment could rise from 1
percent to 7 percent (Rutland and Isataev 1993, p .8) .
The same pattern was clearly exhibited in Russia during 1992 . Physical output for a
sample of firms drawn from a wide range of industrial activities fell by 14-15 percent fro m
early 1991 to early 1992 . Over the same period employment in these firms fell by only 3
percent. The firms with the worst output performance showed a decline of 35-50 percent i n
output from 1991 to 1992, yet their average employment contraction was only 15 percen t
(Commander, Liberman and Yemtsov 1993a, p .20 and 1993b, p .24) . 2
Pattern of Job Losses
There is some evidence that the first round of employment reduction is accounted fo r
by retirement, voluntary quits, and the firing of "non-core" workers . The proportion o f
unemployed who are laid off rises over time .
The change in retirement behavior has been noted in several countries . In Poland
there was a sharp fall in the participation rate, from 65 .3 percent in 1988 to 61 .4 percent in
7
1992, along with a decline of 1 million in the total number of people in the labor force .
Most of this decline was accounted for by an increase in early retirement (Hagemejer an d
Rybinski, p .2) . There was also an increase in people retiring due to a disability of som e
kind .
In Russia the previous rate of labor force participation was high for pensioners : 30-35
percent were still working in early 1980s (Commander, Liberman and Yemtsov 1993a ,
p.10) . Article 35 of the 1991 Russian Employment Law allows the Federal Employmen t
Service to offer early retirement to people who are within two years of retiring -- the
retirement ages are 55 for women and 60 for men -- and in 1992, 50,000 people wer e
offered early retirement (Mamie 1993, p .4. 1) .
Much of the early employment reduction in the state sector is due to voluntary quits ,
most of whom presumably move directly to the private sector . In the last two quarters o f
1992, voluntary quits accounted for more than 60 percent of all separations in Russi a
(Commander, McHale and Yemtsov, p.7). In Hungary, over 70 percent of new hires in th e
private sector in 1992 came directly from the state sector and only 11 percent were previous-
ly unemployed (Kollo 1993) .
There is survey evidence from Poland which suggests that less than 13 percent o f
entrepreneurs were ever unemployed and only 8 percent ever received unemploymen t
benefits (Johnson 1993a) . Most of these entrepreneurs worked in the state sector before
1990 and most of them voluntarily quit the state sector .
The evidence that noncore workers are fired first is more anecdotal . However, thi s
was the strong conclusion of a World Bank study based on both official data and a survey of
8
41 state firms, which argued that, while limited in 1992, net employment reductions were
concentrated on the ancillary and clerical categories of staff (Commander, Liberman an d
Yemtsov 1993b, p .43) . In the last two quarters of 1992, production workers accounted fo r
70 percent of the quits and 80 percent of the hires in state industry, while 50 percent of
involuntary separations involved clerical workers (Commander, McHale and Yemtsov 1993,
p .7) .
The reluctance to fire workers in the face of massive output decline naturally implie s
a sharp fall in the number of hours worked . Evidence on this point is available for Rumania ,
where total hours worked in industry fell 36 percent from 1989 to 1992 and hours worke d
per worker per year declined by more than 27 percent (Earle and Oprescu 1993, Table 2 .2 ,
p .10) .
The proportion of mass layoffs rises over time . The proportion of unemployed i n
Poland who had lost their jobs through "mass layoffs" was 4 .3 percent in January 1990, but
rose to 10 .2 percent in June, 16 .3 percent in December 1990 and 20 .0 percent in June 199 1
(Coricelli and Revenga 1992, Table l) .
Mass layoffs may also have been discouraged or delayed by legislation . For example ,
the Polish legislation passed in 1989 allowed mass layoffs but also required 30-90 day s
advance notice and up to 90 days severance pay for layoffs of 10 percent or more o f
employees (Coricelli and Revenga 1992) . Similar legal requirements exist in Russia wher e
the Federal Employment Service and trade union organizations in principle have the right t o
order that mass layoffs be delayed for up to six months (Mamie 1993) . Given these
9
restrictions, it would not be surprising if firms tried to disguise mass layoffs by firing people
more gradually and in small groups .
Outflows from Unemployment
Most of the people who are fired in these countries become unemployed and onc e
unemployed have difficulty finding a new job . This statement would not be surprising for a
western market economy, but given the sharp shift in employment from the state sector to th e
private sector in post-communist countries, it was expected that the private sector would hir e
unemployed people . Based on western experience, it was assumed that people would pass
from state sector employment to private sector employment through an intermediate phase o f
unemployment .' Unfortunately, this assumption is not confirmed by the facts .
There has certainly been a rapid increase in private sector employment in all post -
communist countries since 1990 . In Hungary and Poland the private sector accounted for 8 -
10 percent of urban employment before 1990 and by 1992 had risen to 25-35 percent . 4
Total private sector employment in Poland is even higher, in some estimates close to 5 0
percent, because agriculture is almost entirely private and is very labor intensive . In the
Czech Republic and other countries of Eastern Europe, the private sector started smaller an d
employed between 5-10 percent by the end of 1992 (Johnson 1994) .
However, the important evidence concerns what happens to unemployed people, in
particular the likelihood that they will be reemployed somewhere -- often summarized in
terms of their "transition probabilities ." Evidence on this issue is far from complete, but a t
least in Hungary, the unemployed have a higher probability of being hired into the state
1 0
sector than into the private sector (Kollo 1993, Tables 2 and 5) . Less than 8 percent of th e
new hires by the private sector come from unemployment . Furthermore, the net flow in
Hungary is balanced from private employment to unemployment and back . There is not a
net flow from unemployment to private employment .
In other words, the private sector hires most of its new workers from the state sector .
When private sector firms fire workers, these workers become unemployed and this privat e
sector firing almost exactly balances the private sector hiring from unemployment . Unem-
ployed workers are more likely to get hired back into the state sector than to get hired int o
the private sector .
As a result, despite the sharp increase in private sector employment in these countrie s
there has been relatively little hiring from the pool of unemployed . Table 1 shows two
measures of the rate of outflow from unemployment, where the outflow is the fraction of
unemployed people who will cease being unemployed in a particular month . If this rate i s
lower then the average time an unemployed person stays unemployed -- known as th e
average duration of unemployment -- will be higher .
The first measure is of total outflow from unemployment (in the third column o f
Table l), irrespective of where unemployed people go . This measure is flawed for ou r
purposes because it includes people who withdraw from the labor force or who are placed on
some kind of training program. However, good cross-country data is available for thi s
measure so we provide it in order to compare Eastern Europe with western economies . In
terms of total outflow, the East European economies are much closer to Western Europe than
1 1
to the U.S . or Japan. In common with France, Italy, Spain and the U .K., post-communis t
Eastern Europe has a low monthly inflow rate and a low monthly outflow rate .
Viewed in terms of the overall outflow rate, Eastern Europe seems to doing better
than some West European economies . However, rates of outflow to jobs are lower than tota l
outflow rates . Unemployment has become a partially "stagnant pool" in which there is a
rising proportion of long-term unemployed . '
For example, in Poland the number of unemployed who found a job using the
services of employment offices each month was roughly constant during the period 1990-92 .
As a result, the outflow rate to employment fell from 4 percent in the third quarter of 199 0
to 2 .3 percent on average in the first three quarters of 1992 (Hagemejer and Rybinski, p .7) .
Part of the explanation for these low outflow rates may lie with the wage distributio n
in the private sector . The available evidence suggests that private sector average wages ar e
no higher than state sector wages . In Hungary, wages and incomes are higher in the private
sector but hourly earnings are equal . People in the private sector work 3 hours more pe r
week compared to people in the state sector (Kollo 1993) . In Poland average private sector
wages at the beginning of 1993 appear to have been slightly lower than in the state secto r
(Johnson 1993a) . 6 In addition, although the availability of nonwage benefits -- ranging from
cheap vacations to day care -- has declined in the state sector, it is probably greater tha n
currently in the private sector .' Some people fired from the state sector may prefer t o
remain unemployed and seek a new state sector job, rather than go to work in the privat e
sector .
1 2
The most plausible interpretation of the available information on labor flows is tha t
high skilled people are hired directly from the state sector while low skilled people who are
fired from the state sector remain unemployed and may prefer to return to the state sector .
Anecdotal evidence suggests there is a good deal of turnover among the unskilled when the y
work in the private sector . We also know that, contrary to initial expectations of observ-
ers, state firms continue to hire new workers, up to 10 percent of their labor force per year -
- presumably to fill vacancies in essential production work left by voluntary quits .
Registered Unemploymen t
There are many reasons to regard registered unemployment in post-communis t
countries as an inadequate measure of real unemployment . It is likely that some people are
registered as unemployed even while they have some work. The Polish labor force survey o f
1992 suggested that 30 percent of the registered unemployed actually had som e work.8
However, the direction of the bias in official unemployment statistics is not unambig-
uous . Official data on registered unemployment in Warsaw gives a rate of 5 percent but the
1992 labor force survey indicates the true rate is actually 13 percent . In Russia there is a
significant difference between the number of unemployed people who look for a job using th e
official labor exchanges, and those who are registered by those exchanges as actuall y
unemployed. In addition, many people presumably look for and find work without consult-
ing labor offices . In Poland, apparently only 20 percent of vacancies are actually posted i n
labor offices .
1 3
Notwithstanding these reservations, Table 2 enables us to compare outcomes acros s
countries in terms of the number of registered unemployed. While the data is not complete
and the numbers for the end of 1992 are only estimates, three points can be made .
First, it is evident that in almost all countries there was no officially recorde d
unemployment before real economic reforms began . There was probably almost no rea l
unemployment, with the exception of some unrecorded frictional unemployment -- in Russi a
estimates of this vary from 0 .6 to 2 .7 percent (Commander et al 1993a) .
Consideration of direct evidence on the policy changes and the effectiveness of refor m
policies suggests that the beginning of real reform can be dated from the moment whe n
unemployment begins to rise . Real reform appears to require effective pressure on state
enterprises to reduce employment . This is because reform involves both changes in th e
macroenvironment and the requirement that firms adjust their performance so as to at leas t
break-even or to reduce their reliance on subsidies .
Thus Poland, as Table 2 shows, had very little unemployment in 1989 under th e
influence of partial communist reform but the unemployment rate rose sharply in 1990 when
the more comprehensive Balcerowicz Plan was introduced . In part the higher unemployment
can be attributed to the collapse of trade within COMECON, including the loss of markets i n
the Soviet Union and the sharp increase in the price of imported energy . However, the real
trade disruption came at the beginning of 1991 and Poland in particular shows a shar p
increase in unemployment before that. Similarly, Hungary showed a significant rise i n
unemployment when the pressure on state enterprises intensified in 1990 .
1 4
Second, although unemployment emerged in all these countries at roughly the sam e
time, there are significant differences . Among East European countries unemployment rose
much more sharply in Bulgaria during 1991 and in Rumania during 1992 . In both cases thi s
can be attributed to the government becoming unwilling or unable to provide additiona l
financing to state enterprises, thus forcing them to release labor (Beleva and Jackman
1993) . 9
There is a striking difference between countries from the former Soviet Union and
Eastern Europe . Russia, Ukraine and Uzbekistan show zero or almost zero unemploymen t
through the end of 1991 . Even the low rates of unemployment shown for the end of 199 2
suggest that reform had not had its full effect on state enterprises .
Even in Estonia, which introduced restrictive a new money and restrictive monetar y
policies from June 1992, unemployment had only reached 2 .7 percent by mid-1993 (Hansson
1993 p .5) . Given that there is no reason to expect easier adjustment in the Baltics compare d
with Eastern Europe, we would expect the unemployment rate to follow the same upward
path seen further west if the Baltic states continue with their intention to implement seriou s
economic reform .
Third, several countries exhibit unusual performances in Table 2 . Slovenia had
significant unemployment in 1989 as a result of previously implemented reforms . In fact ,
unemployment had been a persistent problem in Yugoslavia during the 1970s and 1980s .
Overall unemployment in Yugoslavia was 7 .7 percent in 1970, 11 .9 percent in 1980 and 16 . 4
percent in 1990 (Wyzan 1993, Table 2) . Within Yugoslavia, Slovenia had low unemploy-
ment: 3 .0 percent in 1970, 1 .3 percent in 1980 and 5 .2 percent in 1990 . At the other
1 5
extreme was Macedonia with unemployment of 17 .8 percent in 1970, 21 .5 percent in 198 0
and 23 .0 percent in 1990 . Recent Slovenian experience is interesting because despite havin g
an economy which appeared to be significantly different from the rest of Eastern Europe, an d
a slightly higher starting unemployment rate, it has experienced a similar increase i n
unemployment .
In part the rise in Slovenian unemployment from 1990 can be attributed to th e
particular problems of Yugoslavia's break-up and civil war . But labor market condition s
changed as in other East European countries . Apparently not more than one fifth of the 3 8
percent fall in industrial production from June 1989 to June 1992 can be attributed to th e
collapse of Yugoslav market . The remaining decline is due to the disruption of Comeco n
and policies adopted to combat inflation : state enterprises were required to become mor e
nearly self-financing and there have also been legal changes which reduced job security . In
February 1991, the advance notification period for redundant workers was reduced from 2 4
to 6 months (Cvikl, Kraft and Vodopivec 1993) . All these elements indicate that Slovenia ,
just like most post-communist countries, is now in a new phase of real economic reform .
Albania shows an increase in unemployment earlier than one would have expected an d
a lower level for 1991 than seems plausible . Albanian real GDP fell by 10 percent in 199 0
and by 30 percent in 1991, so these unemployment numbers may have been subject to som e
statistical manipulation in addition to the measurement problems experienced in other post -
communist countries .
Tajikistan had an extraordinary rise in unemployment in 1992, from zero to 1 3
percent in one year, which is much higher than the reported numbers so far for other parts of
1 6
the former Soviet Union . The primary reason for this performance is the civil war which
had a severe negative effect on the economy in the second half of 1992 . Although there are
no reliable unemployment figures, similar disruptions due to civil war have been reported fo r
Georgia (Conway and Pant 1993), and Armenia .
The most interesting exception to the general pattern is that of the former Czechoslo-
vakia -- referred to in Table 2 as the Czech and Slovak Republic . While unemployment rose
in 1990 and 1991 as could be expected, it actually fell in 1992 and ended at the remarkabl y
low level of 5 percent . What can explain this performance?
Table 1 indicates that it is the Czech Republic rather than Slovakia which is an outlier
in terms of its unemployment performance . Czech unemployment peaked in the fourt h
quarter of 1991 at 221,700 and subsequently fell steadily -- reaching 134,800 by the end of
1992 . The overall unemployment rate of 3 .2 percent in the first three quarters of 1992 wa s
surprisingly low. The primary difference appears to lie not with inflow rates, because this i s
the same as that of Hungary and close to that of Poland, but with much higher outflows fro m
unemployment, particularly to jobs .
The Czech Republic was fortunate, in that many of the sectoral shocks -- particularl y
due to the breakup of COMECON which affected all countries in the region -- fell more i n
Slovakia, because heavy industry had been concentrated there . In addition, relatively lo w
interest rates in the Czech Republic may have helped stimulate the private sector . Rapid
privatization and the substantial inflow of foreign investment were probably also helpful .
There have also been some government schemes to provide jobs temporarily (Ham, Svejna r
and Terrell 1993, pp .32-38) .
1 7
Summary Findings
There are four conclusions from this survey of the available cross-country evidence .
First, unemployment begins to rise when pressure is put on state enterprises . Since 1990
throughout this region, state enterprises have felt sufficient pressure to begin cuttin g
employment, although their budget constraints may not have become completely "hard, "
because they have not been cut off from all forms of government support . The reductions in
employment so far have been gradual but steady . The evidence so far suggests that a tota l
employment reduction in state industrial enterprises of 25-30 percent can be expected in th e
first 2-3 years of real reform . Given this fact, it is reasonable to conclude that real reform
has not yet begun in earnest in the former Soviet Union .
Second, the initial employment reduction is accounted for primarily by retirement s
and voluntary quits. There is also a substantial reduction in hours worked . Over time the
proportion of layoffs increases . Anecdotal evidence strongly suggests that firms initially fir e
small groups of workers who are considered not essential to the production process but ove r
time they turn also to larger group firings of core workers . Nevertheless, monthly inflow
rates to unemployment reinain low .
Third, once people are unemployed they find it difficult to get a new job in Eastern
Europe . Although the evidence is as yet far from complete, there is a strong suggestio n
that -- with the exception of the Czech Republic -- the new private sector does not hire muc h
from the pool of unemployed. It is easier to be find another job in the state sector and state
sector hiring has continued at higher than expected levels, particularly to fill production jobs
which are left vacant by voluntary quits . Even so the state sector hires far fewer than it fires
1 8
and this combination of conditions explains the low rates of outflow from unemployment t o
employment, rising unemployment and the increasing share of long-term unemployed .
Fourth, as a result unemployment displays the following characteristics . The
unemployment rate begins to rise as soon as pressure is put on state enterprises . Typically ,
within one year the rate can rise from close to zero to above 5 percent and within two years
it is above 10 percent .
Unemployment rises sharply when the external trade system is disrupted and even faster i n
countries which have experienced severe internal disruption, such as a civil war. Unemploy-
ment only appears to have peaked in one country, the Czech Republic, which has specia l
features that are not yet fully understood. For the other countries unemployment appear s
likely to peak in the range of 15-20 percent with a relatively high percentage of long-ter m
unemployed -- probably over 50 percent . In all likelihood unemployment in Eastern Europe
will remain high for the foreseeable future .
3 . Survey Evidence from Ukraine 1 0
The preceding discussion identified the outflow rate from unemployment to employ-
ment as a key issue in all post-communist countries and showed that according to officia l
statistics this rate is very low . Given the limitations of official statistics it makes sense t o
verify this finding through independent surveys .
This section reports a survey in Ukraine which directly interviewed people who had
been fired from state enterprises in an attempt to determine how many of them had found
new jobs . This survey finds higher rates of reemployment for fired people than one would
19
expect based on cross-country official statistics and suggests that so far unemployment in th e
former Soviet Union has differed somewhat from unemployment in Eastern Europe .
Employment Reductions in Ukraine
Table 2 shows there was no unemployment in Ukraine at the end of 1991 and a
recorded rate of only l .2 percent at the end of 1992 . Direct evidence on policies suggests
that economic reform, in the sense of real pressure on state enterprises, only really began i n
1992 and has remained less complete than in most parts of Eastern Europe and in Russi a
(Johnson and Ustenko 1993) .
Our sample of firms was chosen from a list of state industrial enterprises operating i n
the city of Kiev. We divided the sample into two parts so that six firms were involved i n
military production of some kind and the other seven produced only consumer goods . In
1992 many military production firms continued to receive subsidies of some kind but mos t
civilian firms did not and we wanted to compare outcomes in terms of employment and wha t
happened to fired people for these two sets of firms .
Table 3 shows the initial employment in all thirteen firms as well as whether the y
produced only military goods, only civilian goods or some mix of goods . Interviews wer e
conducted in December 1992 . Most of the people with whom we spoke had been fired sinc e
September 1992 . "
Total employment in all 13 firms was 65,053 in December 1991, 64,869 in Januar y
1992 and 56,446 in November 1992 . The total reduction in employment in our sample was
13 percent from December 1991 to November 1992 . 12
20
Due to the size distribution of firms in our sample, 73 percent of the employmen t
reduction -- 6,280 of 8,607 jobs lost -- was in three enterprises : #5, #7 and #10, two of
which are military and one of which is military/civilian . (Enterprises are identified b y
number in Tables 3 and 5 .) However, the percentage reduction in employment in almost al l
military and military/civilian enterprises was less than in almost all civilian enterprises . The
employment reduction in civilian firms was across the board : -12%, -38%, -40%, -36%, -
15%, -55%, and -32% . The employment reduction was greater than 20 percent in fiv e
civilian enterprises -- the exceptions were #2 with only a 12 percent fall and #11 with a 1 5
percent fall . In contrast, two military enterprises had only a one percent reduction i n
employment, while the other two military enterprises had reductions of 19 percent and 14
percent, and the two military/civilian enterprises had reductions of 13 percent and 2 4
percent .
Table 4 further shows the different average employment reductions between the thre e
types of enterprises . Employment fell only 11 percent in pure military enterprises, whil e
dropping 15 percent in mixed military/civilian enterprises ." The striking contrast is with
civilian enterprises which had a total employment reduction of 27 percent .
Table 5 provides further details on the composition of employment reduction betwee n
its two main components : firings and retirements . Of the two, firings are obviously an
involuntary reduction in employment, but anecdotal evidence suggests a large fraction o f
retirements may also be considered involuntary .14
The number of people fired as a percent of total involuntary job losses ranges between
29 percent and 80 percent, with an average of 61 percent . One of the two military enterpris-
2 1
es which had a significant employment reduction (#10) reported that only 29 percent of it s
involuntary reduction was accounted for by people who had been fired . Similarly, one of the
two military/civilian enterprises (#5) showed an unusually low ratio of fired people to tota l
involuntary reduction -- only 32 percent .
Interestingly, there were relatively few voluntary quits from enterprises in ou r
sample . The total number of voluntary quits can be calculated from Table 5 as the tota l
reduction in 1992 minus the total involuntary reduction -- which gives 1,526, or 18 percent
of the total employment reduction of 8,572 . However, of this amount, 1,111 people (7 3
percent) were accounted for by one enterprise (#10) . For the other 12 enterprises, tota l
voluntary quits was 415, which was only 0 .2 percent of the total employment reduction o f
these enterprises (6,061) and of which 71 percent was accounted by one enterprise (#5) . 1 5
In summary, Tables 4 and 5 show that the employment reduction in 1992 in civilia n
firms has three main characteristics . First, it was large -- Table 4 shows an averag e
employment reduction of 27 percent . Second, the employment reduction was fairly evenl y
distribution across enterprises . Third, the share of fired people in the total involuntary
reduction was high -- this share was 65 percent for the seven civilian enterprises in ou r
sample .
In contrast, on the first point, Table 4 shows military enterprises had a much lowe r
average rate of employment reduction in 1992 -- 11 percent for pure military enterprises an d
12 percent for military and military/civilian combined . Second, there was a very uneve n
distribution of employment reduction across military and military/civilian enterprises . In two
enterprises (#l and #6) hardly anyone was fired and in two other enterprises (#10 and #5) the
22
number of people fired was less than 5 percent . On the other hand, in two enterprises (# 7
and #9) the employment reduction was more in line with the reductions in civilian enterpris-
es .
Military and military/civilian enterprises resembled civilian enterprises more closely
on the third point . The average share of fired people in total involuntary employmen t
reduction at military enterprises was 63 percent, which was very close to the number fo r
civilian enterprises . However, there were two outliers among the pure military enterprises - -
the share of fired people in total involuntary reduction was 80 percent in enterprise #7 an d
only 29 percent in enterprise #10 . Furthermore, the other two pure military enterprise s
have had less than a one percent involuntary employment reduction, so this aspect of thei r
performance is not fully comparable .
In conclusion, at least in this sample of industrial enterprises in Kiev, there was a
significant reduction of overall employment in 1992 . However, the pattern is uneven, with a
much larger reduction in civilian rather than military enterprises . Enterprises producing both
military and civilian goods appear to be an intermediate case .
What explains this result, particularly given that military enterprises are likely to hav e
suffered a larger fall in output than have civilian enterprises? 16 The most likely reason is
that enterprises still producing military goods received enough subsidies to protect thei r
workers either by minimizing the amount of involuntary employment reduction or b y
skewing this reduction towards forcing people into retirement .
23
However, by late 1992, Ukrainian civilian industrial enterprises beginning to fir e
workers. Some military enterprises had also fired people . What happened to the people wh o
became unemployed ?
Outflows from Unemploymen t
We contacted 491 people, of whom we were able to interview 349 . Our sample of
fired people was constructed so as to contain an equal number of people with highe r
education and with secondary education . We were particularly interested in comparing th e
outflow rates for people with different education levels . But we also have some interestin g
results on the age structure of which unemployed found new jobs .
Table 6 shows the age-education composition of our sample . Of the age group 20-25 ,
91 percent of our sample has only a secondary school education . This is not surprising given
that the average age at completion of university or other higher education is about 23 i n
Ukraine .
In both the age groups 26-30 and 31-35, precisely 71 percent of our sample have
higher education . However, this percentage falls for subsequent groups : 34 percent of the
36-40 age group have higher education, 59 percent of the 41-50 age group have highe r
education, and 30 percent of people over the age of 50 have higher education .17
Table 7 shows that a high percentage of job losers in our sample are young -- 4 9
percent of the job losers are aged 30 or under and 74 percent are aged 40 or under . There
are almost no people in our sample over 50 years of age, which is particularly interestin g
given that the retirement age is 60 for men and 55 for women . One strong implication from
24
our survey is that very few people over the age of 40 have been fired in Kiev, although the
previous section showed that a significant number of people retired in 1992 .
However, younger job losers are less likely to end up as unemployed . Only 1 8
percent of the 20-25 age group became unemployed, 9 percent of the 31-35 age group, 1 6
percent of the 36-40 age group . In contrast, 34 percent of the 41-50 age group becam e
unemployed and more than 80 percent of the over 50 age group were without a job . The
exception to this pattern is the 26-30 group, in which 37 percent were unemployed -- thi s
finding is discussed further in connection with Table 9 below . 1 8
There are also major differences between age groups in terms of where they are no w
working . Younger people were both more likely to find a job and more likely to work in the
nonstate sector . Of those finding work, 78 percent of the 20-25 age group, 74 percent of th e
26-30 age group, and 66 percent 31-35 age group found work in the nonstate sector . In
contrast, of those finding work, 41 percent of the 36-40 age group, 17 percent of the 41-5 0
age group, and no one older than 50 found work in the nonstate sector .
Table 7 also shows that a much higher percentage of younger people either have thei r
own business or plan to establish a business . Of the people aged 35 and under, 34 percent
(77 out of 228) already had their own business . For people aged 36 and older, the figure i s
only 11 percent (13 out of 121) . The same comparison also holds for those with plans for a
new business . Of those aged 35 and under, 24 percent (54 out of 228) had a plan, while of
those aged 36 and older, only 10 percent (12 out of 121) had a plan . 1 9
Almost no one who worked in the state sector had any plans to start their ow n
business and the same was largely true of the unemployed -- although 7 unemployed people
25
did say they wanted to start a trading business . In contrast, a relatively high proportion of
people working in the non-state sector wanted to start their own business, of which a
surprisingly large percentage (42 percent) wanted to start production . 2 0
The conclusion from Table 7 is that reemployment rates were higher for younge r
people, and the key break point appears to be at 35 years of age -- with the important cavea t
that a relatively high percentage of people aged 31-35 found work in the state sector .
Similarly, the share of people aged 26-30 who are not reemployed was higher than
the age groups both older and younger, which suggests there may be a particular problem for
relatively young people who have just finished higher education . We turn now to examin e
how the outflow from unemployment depends depend on people's education level .
Table 8 shows the main results of our sample broken down by education level . Our
results indicate a very similar percent of people with higher and secondary education foun d
work in the state sector : 32 percent and 29 percent respectively . The difference seems to lie
in the fact that a higher proportion of people with secondary education found work in th e
nonstate sector (48 percent versus 38 percent) and a lower proportion were unemployed (2 3
percent versus 30 percent) . The new jobs in the nonstate sector seem more suited to worker s
with only secondary school education .
Table 8 further shows the new jobs were usually not in the same branch of industry - -
only 16 percent of both people with higher and secondary education reported they no w
worked in the same "sphere" -- meaning the same branch of industry . Anecdotal evidence
suggests that many new nonstate jobs are in trading activities .
26
Conditional on being fired, Table 9 shows that 39 percent of women say they ar e
unemployed, while only 22 percent of women work in the nonstate sector and a mere 1 0
percent say they have their own business.21 In contrast, only 12 percent of men are unem-
ployed, 62 percent work in the state sector and 34 percent have their own business .
We should also mention one further relevant hypothesis, which is that given th e
uneven pattern of employment reduction across types of firms, the characteristics of peopl e
fired may differ according to the type of enterprise in which they worked before. In fact, we
find no evidence to support such a view . From all three types of enterprise -- military ,
military/civilian or civilian enterprises -- the job losers appear equally likely to becom e
unemployed . The shares are 27 percent, 27 percent and 26 percent . However, people wh o
worked in civilian enterprises previously do seem slightly more likely to have secured jobs in
the nonstate sector .
In summary, the overall rate of outflow from unemployment for this sample is hig h
and much higher than one would expect from reviewing the evidence on Eastern Europe .
Younger people are much more able to find some form of reemployment . Once they hav e
been fired, older people are more likely to be unemployed, less likely to work in the nonstat e
sector and less likely to start their own business . Women are less likely than men to find a
new job -- particularly a new job in the nonstate sector .
4. Conclusion
Cross-country statistical evidence identifies low outflow rates from unemployment a s
a key problem for Eastern Europe. Particularly disappointing have been the low rates of
27
reemployment for unemployed people in the private sector . In comparison, our survey
results for Ukraine indicates very high rates of reemployment in the private sector for peopl e
who are fired from state enterprises and who remain unemployed for only a short period .
There are three possible explanations for this difference between Eastern Europe and the
former Soviet Union .
First, because our study directly reaches people who have been fired it avoid s
problems inherent in measuring only what happens to people who pass through the officia l
unemployment system. If, as appears to be the case from our study, a high proportion of
people find new jobs right away after being fired, then they may be entirely missed fro m
official statistics on flows into and out of unemployment . This would bias downwards both
inflow rates and outflow rates, with probably a more serious effect on the latter because th e
people who are missed have very short durations of unemployment .
Second, in the former Soviet Union during 1992 there was rapid growth in the privat e
sector and in private sector employment . However, this growth may have been primarily a
one time adjustment as the private sector expanded into trade and small-scale services . The
same expansion occurred at least l-2 years earlier in Eastern Europe . If East European
experience is repeated in the former Soviet Union, then the rate of new jobs creation wil l
slow in 1993 and 1994 . This would reduce the number of fired people who can find a jo b
immediately in the private sector and would increase the measured inflow rate to and reduc e
the measured outflow rate from unemployment .
Third, all our results should be interpreted with caution and treated as the findings o f
a preliminary study with a limited sample . In particular, the people surveyed so far were
28
part of the first wave of firings in Ukraine, and may have different characteristics fro m
people who are fired subsequently . For example, although we do not have wage or othe r
corroborating data, it is possible that many of the sampled people -- particularly the young
men with secondary education -- in Ukraine moved voluntarily into the nonstate sector an d
were fired from their state jobs after they had already effectively quit . This would sugges t
that the reemployment rates for people who were really fired are lower than indicated by ou r
study .
Unfortunately, even if only 27 percent of people who are fired remain unemployed ,
the likely scale of job losses will generate large scale unemployment in the former Sovie t
Union . Furthermore, the burden of unemployment so far has fallen quite unequally .
Conditional on being fired, older people are less likely to be reemployed or if they ar e
reemployed, their new job is more likely to be in the state sector . Anecdotal evidence and
experience in other countries suggests we should be skeptical about whether those new stat e
jobs will prove lasting . Furthermore, the extent of retirements in 1992 -- and further
anecdotal evidence -- suggests that this is the most important form of involuntary loss o f
employment for older people .
Conditional on being fired, unemployment rates are also somewhat higher for peopl e
who have finished higher education -- although if these people find further work, more than
half of them work in their professional capacity . We would interpret this as mixed news .
The worst news is for women . Once they are fired, the evidence in our sampl e
suggests women are much less likely to find another job . Furthermore, if they do find
29
another job, this is more likely to be in the state sector . At least in our sample, women are
also much less likely than men to start their own business .
Overall, our results show job losses which are at least as substantial as in Easter n
Europe. Firms in the former Soviet Union are firing workers . For people over the age of
40, it is very difficult to find another job after being fired . Once fired, women may be more
likely to withdraw from the labor force . A major difference from Western Europe is that
younger workers are better able to find new jobs in Ukraine .
Furthermore, while the emergence of a low productivity, low wage private sector in
the former Soviet Union may generate sufficient new jobs to keep unemployment rates belo w
East European levels, it will not by itself create acceptable living standards . The future of
Russia and Ukraine probably involves a 10-15 percent unemployment rate, a high share o f
long-term unemployed and a low standard of living for people who lost their job but are now
reemployed . Being employed in the low wage sector will be better than being unemployed ,
but for many people the difference may not be great .
30
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Beleva, Iskra and Richard Jackman 1993 . "The Labor Market in Bulgaria, II : Unemploy-ment." Presented at the World Bank workshop "Labor Markets in Transitional Socialis tEconomies," Prague, April 16-17, 1993 .
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Boeri, Tito 1993 . "Unemployment Dynamics and Labour Market Policies ." Paper preparedfor the World Bank Conference on Unemployment, Restructuring and the Labor Market i nEast Europe and Russia, October 7 & 8, 1993, Washington D .C .
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Cvikl, Milan, Evan Kraft and Milan Vodopivec 1993 . "Costs and Benefits of Independence :Slovenia ." Presented at the conference on "First Steps Toward Economic Independence, "Stockholm School of Economics, 23-24 August 1993 .
Earle, John S . and Gheorghe Oprescu 1993 . "Employment and Wage Determination ,Unemployment and Labor Policies in Romania ." Paper prepared for the World Ban kConference on Unemployment, Restructuring and the Labor Market in East Europe an dRussia, October 7 & 8, 1993, Washington D .C .
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Hansson, Ardo H . 1993 . "Transforming an Economy While Building a Nation : The Case o fEstonia ." Presented at the conference on "First Steps Toward Economic Independence, "Stockholm School of Economics, 23-24 August 1993 .
Johnson, Simon 1993a . "Entrepreneurs and Employment in the Polish Private Sector . "Paper prepared for the World Bank Conference on Unemployment, Restructuring and th eLabor Market in East Europe and Russia, October 7 & 8, 1993, Washington D .C .
Johnson, Simon 1994 . "Private Business in Eastern Europe ." Forthcoming i nThe Transition in Eastern Europe, NBER Conference Volume, edited by Olivier Blanchard ,Kenneth Froot and Jeffrey Sachs, University of Chicago Press, forthcoming 1994 .
Johnson, Simon and Oleg Ustenko 1993 . "The Road to Hyperinflation : Economic Indepen-dence in Ukraine, 1991-93 ." Forthcoming in the proceedings of a conference on "First Step sToward Economic Independence," held at Stockholm School of Economics, 23-24 August1993 .
Kollo, Janos 1993 . "Flows of Labour, Employment, and Wages in the Private Sector i nHungary ." Presented at the World Bank workshop "Labor Markets in Transitional Socialis tEconomies," Prague, April 16-17, 1993 .
32
Layard, Richard, Stephen Nickell and Richard Jackman 1991 . Unemployment : Macroeco-nomic Performance and the Labour Market . Oxford University Press .
Mamie, Sheila 1993 . "Who and Where are the Russian Unemployed?" RFE/RL ResearchReport, Vol . 2, No . 33, 20 August, pp .36-37 .
Pinto, Brian, Marek Belka and Stefan Krajewski . "Transforming State Enterprises i nPoland: Evidence on Adjustment by Manufacturing Firms ." Brookings Papers on Economi cActivity, l :1993, pp.213-270 .
Rutland, Peter and Timur Isateev 1993 . "Kazakhstan : First Steps Towards Economi cIndependence ." Presented at the conference on "First Steps Toward Economic Indepen-dence," Stockholm School of Economics, 23-24 August 1993 .
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33
Endnotes
1. A similar pattern is apparent in total Polish nonagricultural public sector employment, define dto include both state enterprises and cooperatives. There was a cumulative fall of 37 .3 percentin this measure of employment between the end of 1988 and the end of 1992 . The total changewas comprised of a fall of 4 percent in 1989, 14 percent in 1990, 13 percent in 1991 and 1 3percent in 1992 (Coricelli, Hagemejer and Rybinski 1993) .
2. In the first quarter of 1993, despite the continuing recession, industrial employment actuall yrose slightly (Commander, McHale and Yemtsov 1993 . )
3. For example, the model of Aghion and Blanchard 1993, applies standard western labor marke tanalysis to post-communist conditions and includes this assumption .
4. One estimate is that the Polish private sector accounted for 38 percent of nonagricultural job s(Frydman, Rapaczynski and Earle 1993, p .174) .
5. For example, in Slovakia the long-term unemployed (out of work for 12 months or more) ros efrom 6.1 percent of unemployment at the end of 1991 to 36 .3 percent at the end of 1992 . Evenin the Czech Republic, which has relatively low unemployment and relatively high outflows fro munemployment, the share of long-term unemployed in total unemployed rose from 3 .9 percentto 17.1 percent in 1991-1992 (Boeri 1993) .
6. Supportive evidence on this point is provided by a World Bank survey of private Polis hmanufacturing firms in spring 1991 . This found that many private sector jobs required unskille dlabor, who earned 10 percent more than in the state sector, and there was a large private secto rwage premium -- up to twice what could be earned in the state sector -- only for skilled worker s(Webster 1992, p .22, paragraph 4 .18). The rise in unemployment since spring 1991 may hav epushed down unskilled wages in the private sector relative to wages in the state sector .
7. These average numbers mask the distribution of wages in the private sector . There is noclear dichotomy between good and bad jobs but there is a marked distribution of wages from lessthan half what can be earned in the state sector to about double state sector wages (Johnso n1993a) .
8. The benefits for unemployed people were generous, at least initially and this may haveencouraged people who were not really in the labor force to register as being unemployed .
9. The Bulgarian program started in earnest in February 1991 (Belva, Jackman and Nenova-Amar 1993, p.1) . Reforms in Rumania began in 1990 but became much more serious in 199 1and 1992 (Earle and Oprescu 1993, pp .10-16) .
34
10. This section draws on joint ongoing work with Oleg Ustenko of Kiev State Economi cUniversity .
11. Table 3 also indicates whether an enterprise was under the jurisdiction of a central ministr yin Moscow or a ministry in Kiev before the break-up of the Soviet Union . We looked for bu tdid not find an independent effect of previous jurisdiction.
12. Anecdotal evidence suggests that employment reductions only really accelerated in th esecond half of 1992, and this is particularly true of the number of people who were fired .
We only obtained a monthly breakdown of firings from one enterprise (#13), whic hshowed that of the 49 people fired in 1992 (through November), only 9 were fired through th eend of June and 22 were fired in the last three months of the year . People retired at a steadyrate during the first eight months of the year -- of the 107 who went onto a pension in the wholeof 1992, 17 went in the first quarter, 15 went in the second quarter, 19 in the third quarter - -but 61 retired in the last quarter and of this total, 52 left in November .
13. The difference between results for military and civilian/military enterprises should not b eoveremphasized, particularly because we have only 2 mixed enterprises in our sample an dbecause it is fairly difficult to be sure precisely how much civilian output is produced by amilitary enterprise .
14. It is hard to see why anyone would want to retire at the present time : the average pensio nis around 4,800 rubles per month and there is very little variation about this mean .
15. It is possible that enterprises fired people who they think or know would like to quit -- o rperhaps who have already effectively quit by not coming to work . However, we have noreliable evidence on this point .
16. It is not possible to obtain information on the level of production in enterprises whichproduce military goods .
17. The 50/50 split in our sample on education levels meant we probably oversampled the 26-35age group, to compensate for the high number of 20-25 year olds who were fired and wh oalmost never have higher education .
18. The explanation of this point is that many of these people have just finished highe reducation. This is explored further in the discussion of Table 9 below .
19. Some people said they were planning a new business although they already operated thei rown private business. This number should be interpreted as an indicator of people's expectation sabout the extent of new business opportunities in the private sector .
20. Of course, these numbers indicate only the preferences of actual and would-be entrepreneur sand not necessarily where the real opportunities are .
35
21 . Given the low level of living standards at present in Ukraine, it is unlikely that these wome nhave voluntarily withdrawn from the labor force .
Table 1
Unemployment Statistic s
Unemployment Monthly Outflow Outflow PercentRate Inflow
RateRates
(Total)Rates
(to Job)Long-term
Unempl .1992 dataBulgaria 14.7 1 .6 n .a . 1* 7 . 2
Czech Republic 3 .2 0.6 25 .8 18.0 15 . 0
Slovak Republic 11 .6 l .1 9.8 4 .8 25 .5
Hungary 10.3 0 .6 7.0 2-3* 37. 3
Poland 13 .0 0 .7 4.0 2 .3 43 .4
1988 dataFrance 11 .1 0.6 5 .0 n.a . 45 .0
Italy 8.6 0.2 3 .0 n.a . 69 .0
Spain 23 .6 0.2 1 .0 n .a . 62 . 0
UK 9.l 0.9 10.0 n .a . 45 . 0
USA 5 .8 2 .2 33 .0 n .a . 7 . 0
Japan
n .a . : not available .
2.6 0.5 20.0 n .a . 21 .0
Notes :Long-term unemployed are those without a job for more than 12 months, except in Bulgari awhere it is for more than 9 months .Hungarian inflow and outflow data refer to unemployment benefit recipients . The inflow ratefor total unemployment is 0 .76 .
Sources are on the next page .
Sources for Table l :1) 1992 data are OECD and national unemployment registers, as presented by Tito Boeri at th eWorld Bank workshop "Labor Markets in Transitional Socialist Economies," Prague, April 16 -17 1993 . Monthly inflow data are given in Boeri 1993, Table 2 .All data are average of first three quarters of 1992, except outflow rates for Hungary which ar eonly for the first five months of 1992 .Monthly inflow rates are the ratio of average monthly inflows to average yearly labor force .Outflow rates are the proportion of unemployed who find a job each month . Outflow rates withan asterix (*) were calculated from data on absolute outflows from unemployment to employmen tprovided by Janos Kollo at the World Bank workshop "Labor Markets in Transitional Socialis tEconomies," Prague, April 16-17 1993, combined with OECD data on registered unemploymen tin these countries .2) 1988 data are from Layard, Nickell and Jackman 1991, p .51 and p .222. Monthly outflows(total) are calculated as the inverse of the average duration given by this source .
Table 2
Registered Unemployment(as Percent of the Labor Force )
End of Year1987 1988 1989 1990 1991 1992
Albania 2.1 2 .1 l .9 2.1 5 .1 n.a .
Bulgaria n .a . n .a . n .a . l .5 10.4 15-1 6
Czech and SlovakRepublic n.a . n .a . n .a . l .0 6.6 5
Hungary n.a . n .a . 0 .3 2 .5 8 .0 1 2
Poland 0 0 0 .1 6 .1 11 .8 1 4
Rumania n .a . n .a . l .6 2 .0 2.9 1 0
Russian 0 0 0 0 0 .1 1 .3Federation
Slovenia 1 .6 2 .2 2 .9 4 .7 8 .2 13 .4
Tajikistan 0 0 0 0 0 1 3
Ukraine 0 0 0 0 0 1 .2
Uzbekistan 0 0 0 0 0 1
Kazakhstan 0 0 0 0 n.a. 0.2
n.a . : not available (all are probably zero, except for Albania in 1992) .
Sources :1) All countries except Slovenia : European Bank for Reconstruction and Development, AnnualEconomic Review 1992 . Figures for 1992 are estimates .2) Slovenia: Cvikl, Kraft and Vodopivec 1993, Table 3 . Their numbers match those providedby the EBRD for 1990-92 but the EBRD does not give 1987-89 data .3) Kazakhstan : Rutland and Isataev 1993, p .8 .
Table 3
Sample Compositio n
Enterprise Jurisdiction Type of Employment i n
I.D.Number Enterprise December 199 1
1 Moscow Military 10,117
2 Kiev Civilian 900
3 Kiev Civilian 61 1
4 Kiev Civilian 650
5 Moscow Military /Civilian
7,080
6 Moscow Military 6,560
7 Moscow Military 20,700
8 Moscow Civilian 714
9 Kiev Military/Civilian
l,53 1
10 Moscow Military 12,35 0
11 Moscow Civilian 2,460
12 Moscow Civilian 560
13 Kiev Civilian 820
Total 65,053
"Jurisdiction" indicates whether the firm was under all-Union (Moscow) or republican (Kiev )
control in mid-1991 .
Table 4
Average Changes in Employmen t
Type of Employment Change in Percen tEnterprise Dec. 1991 Employment Change
Military 49,727 5,510 11 %
Mixed(Military/Civilian)
8,611 1,299 15 %
Civilian
Notes :
6,715 1,798 27%
1) The type of enterprise is as defined in Table 1 above . In our sample there are 4 militaryenterprises, 2 mixed enterprises (military and civilian production), and 7 civilian enterprises .2) The figures for civilian enterprises assume that employment in enterprise #13 was the sam ein December 1991 as in January 1992 .3) "Change in Employment" is calculated as :(November 1992 employment - December 1991 employment)4) "Percent Change" is calculated as :Change in Employment/December 1991 employmen t
Table 5
Composition of Labor Force Reductions
Ent .
Total Number Fired Ret . Total Total Fired/#
Reduction Fired as % of +Inv . Invol . % Invol .in 1992 Dec.91 Reduc .
1 M 86 30 0 .3% 20 50 0.5% 60 %
2 C 87 49 5% 38 87 10% 56 %
3 C 223 146 24% 77 223 36% 65 %
4 C 218 138 21% 80 218 34% 63 %
5 M/C 1051 241 3% 516 757 11% 32 %
6 M 30 21 0 .3% 8 29 0.4% 72 %
7 M 2,900 2,326 11% 574 2,900 14% 80 %
8 C 245 167 23% 78 245 34% 68 %
9 M/C 338 230 15% 108 338 22% 68 %
10 M 2,511 400 3% 1000 l,400 11% 29 %
11 C 336 245 10% 91 336 14% 73 %
12 C 287 202 36% 85 287 51% 70 %
13 C 260 69 8% 107 176 21% 39 %
Total 8,572 4,264 7% 2,782 7,046 11% 61%
Variables in this table are defined on the next page .
In the column for "enterprise I .D. number," military firms are identified by M, military/civilia nfirms are identified by M/C and civilian firms are identified by C .
Definition of Variables in Table 5 :1) "Total Reduction in 1992" is the total reduction of employment during 1992 . This does notmatch in some cases with Table 2, because firms reported numbers to mid-December .Unfortunately, the question we asked did not result in consistent information about the numbe rof people who left the firms of their own free will . However, we do know that "about 1,000"left firm 10 for this reason and that 84 left firm 13 voluntarily . However, in our opinion thes enumbers are unusually high .2) "Number Fired" is the number of people who were dismissed .3) "Fired as % of Dec . 91" expresses the number of people dismissed as a percentage of tota lemployment in that firm in December 1991 .4) "Ret. + Inv ." is Retirees plus Invalids -- the sum of retirees and people who retired on adisability pension.5) "Total Invol . Reduc." is the Total Involuntary Reduction in employment -- the sum of"Retirees + Invalids" plus "Number Fired . "6) "Total %" is "Total Involuntary Reduction" divided by employment in December 92 .7) "Fired/Invol ." is "Number Fired" expressed as a percentage of "Total InvoluntaryReduction . "(The number of voluntary quits can be calculated as the total reduction minus involuntar yreduction . This number is zero for all enterprises with the exception of enterprise #1, with 3 6quits, #5, with 294 quits, #6 with 1 quit, #10 with 1,111 quits and #13 with 84 quits .)The difference between number fired plus retired/invalid and the total reduction is due to severa lelements: death, call-up to the army, voluntary quits .
Table 6
Composition of Sample by Age and Educatio n
Age Total Education Leve lHigher Secondary
20-25 82 7 75[23%] (9%) (91% )
26-30 91 65 26[26%] (71%) (29%)
31-35 55 39 1 6[16%] (71%) (29% )
36-40 32 11 2 1[9%] (34%) (66% )
41-50 79 47 32[23%1 (59%) (41% )
> 50 10 3 7[3%] (30%) (70% )
Total 349 172 177[100%] [49%] [51%]
[.] brackets express the number they are below as a percentage of the total sample size (i .e . ,
349) .( .) brackets express the number they are below as a percentage of the row total .
Table 7
Employment Status of People who had been Fired
Current Employment Statu sAge(years)
TotalNumber State Nonstate Unemp.
OwnBusiness
Bus .Plan
20-25 81 15 52 14 30 18[23%] (19%) (64%) (18%) (38%) (23%)
26-30 92 15 43 34 26 2 1[26%] (16%) (46%) (37%) (28%) (23% )
31-35 55 17 33 5 21 1 5[16%] (31%) (60%) (9%) (38%) (27%)
36-40 32 16 11 5 7 4[9%] (50%) (34%) (16%) (22%) (13%)
41-50 79 43 9 27 6 6[23%] (54%) (11%) (34%) (8%) (8% )
> 50 10 2 0 8 0 2[3%] (20%) (0%) (80%) (0%) (20% )
Total 349 108 148 93 90 66[100%] [31%] [42%] [27%] [26%] [19%]
(.) brackets express numbers as a percent of total in that age group .[ .] brackets express numbers as percent of the total sample (i .e., 349)
Notes :1) Everyone is classified as either "state" for current employment in the state sector, "nonstate "for current employment in the nonstate sector, or "unemp ." for currently unemployed .
2) People with business plans may have any current employment, including being currently self-employed .
Table 8
Employment Status by Education Leve l
Current Employment Statu sEduc. Total State Non state Unemp. Same Same
Level Sector Sphere Spec.
Higher 171 56 64 52 27 9 1
[49%] (32%) (38%) (30%) (16%) (53% )
Second .School 178 52 84 41 29 48
[51%] (29%) (48%) (23%) (16%) (27%)
Total 349 108 148 93 56 139[100%] [30%] [42%] [27%] [16%] [40%]
(.) brackets are percent of row tota l[ .] brackets are percent of total sample (i .e., 349) .
Table 9
Employment Status by Sex
Current Employment Statu sSex Total State Non-state Unemp . Own
Business
Female 148 57 33 58 1 5[53%] (39%) (22%) (39%) (10% )
Male 131 34 81 16 45[47%] (26%) (62%) (12%) (34% )
Total 279 91 114 74 60[100%] (33%) (41%) (27%) (22%)
[.] brackets express the number they are below as a percentage of the sample for which relevan tdata is available (i .e., 279) .( .) brackets express the number they are below as a percentage of the row total .
Notes :Data on the sex of respondents is available for all enterprises with the exception of numbers 2 ,11 and 12 . This gives a total sub-sample size of 279 .
