Policies of Human Capital Formation: The Issue of Occupational Mobility in Transition

1
Policies of Human Capital Formation The Issue
of Occupational Mobility in Transition

• Nauro F. Campos
• Brunel University,
• WDI-Michigan, CEPR-London, IZA-Bonn

For presentation at CMTEA 2005 Sofia,
September 30 2005
2
Introduction

• Problem of human capital formation in TEs is very
  different from that in other emerging markets
• Conventional wisdom is that Communism failed in
  everything but in providing flat income
  distribution, education and health.
• But structural composition of the labor force
  in terms of occupations was inadequate to the
  needs of a modern market economy.

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Introduction

• There were too many rocket scientists, athletes,
  astronauts, mathematicians, and chess players and
  NOT ENOUGH marketing clerks, marketing
  executives, stock brokers, rock bands, plumbers
  and (why not?) people flipping burgers at
  McDonalds.
• The stock had to adjust!
• At least two different ways of adjusting

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Introduction

• One depends on how fast educational system
  changes AND how large is inflow of newcomers. For
  rapidly growing (and young) populations and
  careful educational reform this would take maybe
  10 to 15 years.
• Another is to workers to change occupation. For
  slowly growing populations and relatively small
  inflows, without government policy (radical
  reform of labour market and education system)
  this will take a very very long time.

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Objectives

• Try to convince you that the (largely neglected)
  process of occupational change matters
• It happened (and will happen) and was (will be)
  crucially important
• It was driven by radical economic reform, in
  particular, by active labour market policies

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How I will try to do this?

• Look closely at experience of one country
  Estonia
• ELFS 1995 (arguably best Db in region)
• Unusual wage, work histories, 1989-1995
• Representative sample 5,000 FT workers
• Describe PMOC in excruciating detail
• Investigate determinants and consequences

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Main finding

• 35 to 50 change occupations 1989-1995

• ISCO 88 (10, 28, 116, 390)

ISCO88 one-digit 1 Legislators, senior officials
and managers 2 Professionals 3 Technicians and
associate professionals 4 Clerks 5 Service
workers and shop and market sales workers 6
Skill agricultural and fishery workers 7 Craft
and related workers 8 Plant and machine
operators and assemblers 9 Elementary
occupations 0 Armed forces
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Main finding

• 35 to 50 change occupations 1989-1995

ISCO88 Four-digit (10, 28, 116, 390) 2
PROFESSIONALS 21 Physical, mathematical and
engineering science professionals 211
Physicists, chemists and related professionals
2111 Physicists and astronomers 2112
Meteorologists 2113 Chemists 2114
Geologists and geophysicists (more) 22 Life
science and health professionals 23 Teaching
professionals 231 College, university and
higher education teaching professionals
(more) 24 Other professionals 244 Social
science and related professionals 2441
Economists 2442 Sociologists, anthropologists and
related professionals
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Main findings

• 35 to 50 change occupations 1989-1995
• Bulk of switches occur just after reform
  implemented
• Step down schooling earnings ladders
• Dets1 gender (female) job tenure matter
• Dets2 (present or future) returns to current
  and alternative occupations dont

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Outline

• Estonia
• Related literature
• Describing the PMOC
• The determinants
• Conclusions

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Estonia

• Smallest of the Baltic states (pop 1.3 mil ?)
• Former Soviet republic (independent 1991)
• Testing ground for M. Gorbatchevs reforms
• Ethnic minorities (1999, Estonians 65 pop).
• 1st wave EU candidate
• Among TES, fast reformer Aggressive LMP

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Estonias Aggressive LMP

• Up to 6 mos. free job training (incl. lessons in
  Estonian language and job searching techniques)
• If training, receive higher unemployment benefits
  (gt40 of unemployed Estonians receive training,
  vis-à-vis lt10 in Central Europe)
• Unemployed can qualify for start-up loan
  (present approved business plan)
• From outset, unemployment benefits in Estonia set
  extremely low and eligibility period short

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Related literature
Little on occupational change (lots on
occupational choice)

• Shaw (JHR 1984, SEJ 1987)
• McCall (JPE 1990)
• Sicherman and Galor (JPE 1990)
• Dolton and Kidd (BER 1998)
• Neal (JLE 1999)
• Sabirianova (2001, WDI WP)
• Campos and Zlabkova (2001, WP)

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Related literature

• Focus on determinants
• Sunk costs of occupational investment
• Transferability of acquired skills
• Quality of the occupation match
• Career as goodie
• Look at young men yardsticks?
• T OC impacts in late T

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Describing PMOC

• 1995 Estonian Labour Force Survey (ELFS95)
• Wider than normal LFS (retrospective 89-94)
• All standard ISCO-88, ISCED, ISIC
• Sampling proc random draw 1/every 100 aged
  16-75 in 1995. Of 10955 selected, 9608 answer
  
• What about pitfalls of retrospective data?

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Pitfalls of retrospective data

• Difficult to remember
• Aggravated by the severity of initial years of
  transition
• Solution 1 No wage data for hyperinflation years
  (1991 1992)
• Solution 2 recode all to Soviet std and
  double-check (CCCP 1989 Census)

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Occupational mobility in Estonia, 1989-1995
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Percentage change in occupational shares
(Estonia, 1989-95)
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The complexity of occupational switches, 2-digit
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So far we found...

• In Estonia, 1989-95 POC is M indeed
• 35.2 to 47.1 switch
• Peaks 1992-93
• Most switches are complex
• Data accords to expectations share of plant and
  machine operators ? and service workers ?
• Anything on direction? Which way switches? Rocket
  scientists to marketing executives or marketing
  clerks?

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Ranking occupations (the two ladders)
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Upward and downward occupational mobility
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Summary of objective 1

• In Estonia, 1989-95 POC is indeed M
• 35.2 to 47.1 switch
• Peaks 1992-93
• Most switches are complex
• Data accords to expectations share of plant and
  machine operators ? and service workers ?

• Typically, occup. switches down the ladder(s)

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• What determines the probability of
• switching occupations?

• returns to current occupation ( - )
• returns to alternative occupation ( )
• Skills transferability (or STI ())
• returns job/firm tenure ( - )

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Measuring Occupational Returns

• Returns current and alternative occupations. From
  Mincerian equations for each year.
• Returns to current occupation coefficient on
  occupational dummy one on age interacted with
  relevant occupation times the workers age.
• Returns to alternative occupation weighted
  average of returns to all other occupations
  (weights are probability of actual occupational
  switches in t-1).

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Measuring Skills Transferability (STI)

• STI per qualification 1 highly transferable
  (across occupations)
• STI good job ranking 2-digit qualific
  secondary and basic educ are two most easily
  transferable qualifications and home economics
  and theology are two most untransferable
  qualifications

• J is of occupation cats,
  
• Nq is workers w/ qualification q,
• Nq,j is workers with qualification q in
  occupation j.
• If STI1 then qualifications are uniformly
  distributed among occupational categs (otherwise,
  value ?).

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The Determinants of Occupational Mobility in
Estonia Probit, 2-digit occupations, returns
based on current wages
Not shown Basic education, Secondary, Spec.
Secondary, Higher, Ac. Degree, Sector (secondary,
tertiary), Ownership (private, co-operative), and
Location (countryside, abroad).
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The Determinants of Occupational Mobility in
Estonia Probit, 2-digit occupations, returns
based on future wages
Not shown Basic education, Secondary, Spec.
Secondary, Higher, Ac. Degree, Sector (secondary,
tertiary), Ownership (private, co-operative), and
Location (countryside, abroad).
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Sensitivity analysis

• Ethnicity issues
• Add ethnic Estonian dummy or language (probits)
  no change
• Gender issues
• The gender divide for MEN returns show expected
  signs and sig as early as 1992 employment rates
  are sig firm tenure is sig
• While men neg return to current, women is
  positive returns to alternative

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Sensitivity analysis (2)

• Heterogeneity issues
• of occupations held
• of jobs lost per year
• cumulative of jobs lost
• of months of nonemployment per year
• Have secondary job? 1 always, 2 not always, 3 no
• Push factors
• Add employment rates (province level) (probits)
  positive and significant after 1992 (no other
  change)

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Conclusions

• ELFS 1995 (best DB in region), 5000 FT, 1989/95
• Described PMOC in excruciating detail,
  investigate its determinants and consequences.
• 35 to 50 (not just young) change occupation
  1989/95
• Bulk of switches occurred early, following reform
• Typically, stepping down schooling and earnings
  ladders
• Dets 1 gender (female) longer job tenure
  matter matter
• Dets 2 (present or future) returns to current
  alternative occupations dont

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7. Suggestions for future research

• Different ways calculating returns IV?
• Improving measurement of STI
• HK-adjusted speed of T

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Table 1. Selected macroeconomic
indicators,Estonia (1990-2000)
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(No Transcript)
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Differentiating the product

• Diff 1 Sabirianova links data sets
• Diff 2 Sabirianova Russia (CCCP) 1988-1998
• Depiction 1988-1998
• Bulk of switches 1991-1994
• Dets and impact 1994-1998
• The tail in detail
• Diff 3 Sabirianova restructuring drives it.
• Not sure how much R in Russia, 1991-95
• We less R and more fall of communism

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Determinants of Intra- and Inter-firm
Occupational Mobility MULTINOMIAL LOGIT
ESTIMATES Iinterfirm (new occup in new firm),
Intrafirm (new occup in same firm), no occup chg
Not shown Basic education, Secondary, Spec.
Secondary, Higher, Ac. Degree, Sector (secondary,
tertiary), Ownership (private, co-operative), and
Location (countryside, abroad).
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Consequences of occupational mobility, OLS
estimates
Not shown Basic education, Secondary, Spec.
Secondary, Higher, Ac. Degree, Sector (secondary,
tertiary), Ownership (private, co-operative), and
Location (countryside, abroad).