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Recruitment in Recovery. Mark Sanders Utrecht School of Economics, Netherlands and Riccardo Welters University of Newcastle, Australia. Motivation. Outflow from unemployment fails to increase in proportion to the hiring rate. Why? Self Selection/Sorting Signaling Recruiting Strategies

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Recruitment in recovery

Recruitment in Recovery

Mark Sanders

Utrecht School of Economics, Netherlands


Riccardo Welters

University of Newcastle, Australia


  • Outflow from unemployment fails to increase in proportion to the hiring rate. Why?

    • Self Selection/Sorting

    • Signaling

    • Recruiting Strategies

    • Search Behavior

In the literature
In the Literature

  • Burgess (1993): Unemployed job-seekers benefit less than proportional from hiring rate increases due to increasing competition from employed job seekers.

  • Russo (2000): Firms switch to more expensive advertising in tight labor markets to maintain a target arrival rate of applicants per vacancy.

Our main argument
Our Main Argument

  • Firm and job-seeker search behavior interact.

  • This interaction helps explain why the outflow rates move less than proportional to hiring rates.

  • And has important ALM policy implications.

Facts for the netherlands
Facts for the Netherlands

  • Unemployed rely more on LEO (72% vs. 13%) than employed.

  • Employed rely more on adds (54% vs. 27%) than unemployed.

  • In tightening markets:

    • Ads become more (36-49%) and LEO less (11-8%) effective in matching.

    • Ads are more frequently used by firms, LEO less.


  • Build a search model that:

    • Predicts the search channel switch

    • Predicts the recruitment channel switch

    • Allows for the interaction to produce counter cyclical outflow/hiring rates for unemployed.

    • Test these predictions in a dataset for the Netherlands

The model


Search Channel 2

The Model




Choose search effort

in Channel 2



Choose search effort

in both Channels


Search Channel 1


Recruitment Channel 2

Recruitment Channel 1



Open vacancies and choose recruitment channel

Testable hypotheses
Testable Hypotheses

  • Hypothesis I: In tight labor markets OJS increases, increasing the probability of filling a vacancy in channel 2.

  • Hypothesis II: In tight labor markets firms therefore switch to channel 2.

    In tight labor markets unemployed job searchers increase total search effort.

    The allocation of search effort between channels depends on firm recruitment channel switch (into channel 2) and the on-the-job search response (out of channel 2).

    The effect of tightness on outflow is ambiguous.

  • Hypothesis III: The least competitive unemployed searchers will switch to channel 1 first/more.

The data
The Data

  • OSA Supply Panel:

    • 4.000 persons 1994-2000 pooled

    • On Job Search yes/no

    • Search channel information only for unemployed

  • OSA Demand Panel:

    • Only one year used (2001) 800 firms

The results
The Results

  • In a logit on OJS(1,0) we find the vacancy rate has a positive and significant impact controlling for education, sector, contract type and experience. This supports HI.

  • In an ordered logit on the importance of open recruitment channels (1-5) we find the vacancy rate has a positive and significant impact, controlling for size class, private-public and educational level of workforce.

  • Similarly for the importance of the public channel (1-5) the effect is insignificant (not negative!).

  • But in a logit on preference for the public channel (1,0) the vacancy rate again has a negative significant impact. Supporting HII.

  • In a logit on choosing open search channels for unemployed job searchers we find the aggregate vacancy rate has a small positive impact, controlling for education (+), search duration (0), self-confidence (-) and interaction between education and confidence (mixed). No strong support for HIII.

The results1
The Results

  • We can accept HI and II.

  • But must we reject HIII?

    • Institutional changes

    • Other channels are not considered

    • “Most intensely used channel” may not be the relevant dependent variable

Hard conclusions
Hard Conclusions

The model works so our logic is sound.

The data supports the key assumptions.


…to prove our point:

We need to probe the data further

Control for institutional change

Improve our tightness (per channel) measure

Run an ordered logit on all possible channels

Bring in search intensity

Other suggestions?

Tentative conclusions
Tentative Conclusions

Iff we can prove our point:

Unemployed job searchers require assistance in tightening labor markets to compete in the open channel

So that ALM-policy effort should be pro-cyclical.

The model1
The Model

Matching in closed (1) and open (2) channel:

Flow probability of filling a vacancy through (1) and (2):

The model2
The Model

Job finding flow probability for unemployed JS:

Job finding flow probability for employed JS:

The model3

Firing Rate=λ(1-u)

Hiring Rate=φ2e+(φ1u+φ2u-φ2e)u

The Model








Channel 1


Channel 2

φ2e(1-u)L +φ2uuL

The model4
The Model

Firms choose search effort per channel:

First Order Condition on search effort:

sf1,2 is negative in channel specific flow cost and

the marginal effect on the probability of filling the

vacancy through that channel and positive

in interest rate and job value as well as, obviously,

the probability of filling the vacancy through that channel.

The model5
The Model

Firms open vacancies in both channels:

Together with the FOC his implies:

As the marginal probability is decreasing in the vacancy rate:

Higher job value increases number of vacancies in both channels.

Higher costs will reduce vacancies in that channel.

The model6
The Model

Value of a filled vacancy (job):


Allows for expressing optimal search effort per channel in

aggregate variables only. Effort in a channel depends positively

on the effort of job searchers in that channel. Tightening markets

Will cause firms to shift towards the open channel.

The model7
The Model

Unemployed Job Searchers:


Which implies that unemployed job searchers set effort

such that marginal probabilities equalize. This implies

they switch to channel 1 when employed job searchers

search effort increases in channel 2.

The model8
The Model

Employed Job Searchers:

Setting effort to maximize yields:

Which implies that employed job searchers set effort

in response to a wage mark-up and reduce effort when

unemployment or the search effort of unemployed in

channel 2 increases.

The model9
The Model

Solve for equilibrium wage:

Which yields:

And closes the model.

The results2
The Results

Table 1: Job search decision employees, pooled 1992-2000, clustered1

The results3
The Results

Table 2: Recruitment intensity in open channels, 2001

The results4
The Results

Table 3: Recruitment intensity in public channels, 2001

The results5
The Results

Table 4: Recruitment preference for public channel, 2001

Recruitment in recovery

Table 5: Channel choice unemployed job searcher, pooled 1994-2000, clustered1