Is there crowding out among the young and old in the public sector?- results from a period of raising retirement age in Hungary and an information system to increase the efficiency of matching

Co-financed by the TÁMOP-2.3.2-09/1-2009-0001 and the OTKA 101803 programme

3rd IE-SEBA workshop Fragrant Hill – Beijing, 26-27 October 2012

Zsombor Cseres-Gergely, Institute of Economics, CERS HAS

Motivation: uneven employment growth by age

… and similarly for unemployment

Question for all ageing societies

• Is there a trade-off between helping the labour market integration of the young…

• …and keeping the old on the labour market?• If yes, what is the “exchange rate”?• At what time horizon?

Europe already faces these challenges, the crisis being the first big challenge.

Literature on old-young crowding out- Theory: Layard, Nickell, and Jackman (1991). No effect should be

present due to wage-adjustment (intro. of early retirement)- Simple x-country panel regressions on aggregate data:

Herbertsson (2001). No negative effect of early retirement on youth employment.

- Jousten et al. (2008): refined time-series evidence using retirement incentives with early retirement. No effect on youth.

But:- Gruber-Wise (2010): Follow-up research to early-retirement. No

effect- Skans (2005): Negative effect on the young with regional data

in Sveden- Grant-Hamermesh (1980): older women crowd out younger

men in the US

A potential driver of older employment: increasing retirement age

Source: Calculation by Cseres-Gergely, Kátay and Szörfi (2012), based on Kátay and Nobilis (2009)

Aggregate results for Hungary - employment

Data- Wage Survey of the Employment Office- Microdata on individual wages and demographics (age,

schooling)- Indicator of recent recruitment- Connected to workplace (“plant” and firm) characteristics- Panel from 1992 to today- Almost complete coverage of the public sector

- Use of data: aggregate to the workplace-level. Counts, shares, average wages.

Why the public sector?

Production in private sector clearer to model, but in the public sector….

- mobility to and from workplace is less frequent (less opportunity for alternative adjustment),

- wages are set by a wage grid (downward rigidity).- institutions operate a payroll-management system

all of which makes it likely that estimates from the public sector will pick up an effect if there is any.

Inspiration: dynamic model of labour demand of municipalities in the presence of uncertainty by Holtz-Eakin and Rosen (1990) w/ conditional demand.

Employment at a workplace („plant“):

e: no. of employed, w=wage (p=prime age, o=old, y=young)

Recruitment of new entrants:

dynamic panel model (strict and semi) – Arrelano-Bond (1991) method

Estimation with disaggregated data: estimating equations

Results for employment

Results stable for fewer, but not for many more lags. Also robust for inclusion of the prime-age.

Similar results if we use experience (-2 and 40+) instead of age.

Results for recruitment

Wages

Unemployment is not defined with employment data. Use wages to approximate pressure on local market.

Base: Mincerian wage regression. Extend to allow for flexible age-earnings profiles, effect of share of age-groups and their interaction:

w: wage, X: demographics, a: age, s: share of group

Share shows direct effect, interaction shows indirect effect.

Results for wages

Also includes:- Profile withoutInteraction- Profile interacted with short experience

What can we do about it?

Reduce frictional unemployment through information

Principles to create an information system

1. Communicate both schooling and occupation-specific information

2. Provide forecasted and life-course information

3. Use credible information sources but an easy to understand graphical representation

4. Create a contemporary, compatible and accessible interface

“Pályasúgó” = Job advisor (“Job whisperer”)

Wages and employment over the life-course

Forecasts by occupations

Modules for market providers

Thank you for your attention!