04/19/23 1

Recruitment in Recovery

Mark SandersUtrecht School of Economics, Netherlands

and

Riccardo WeltersUniversity of Newcastle, Australia

04/19/23 2

Motivation• Outflow from unemployment fails

to increase in proportion to the hiring rate. Why?– Self Selection/Sorting– Signaling– Recruiting Strategies– Search Behavior

04/19/23 3

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.

04/19/23 4

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.

04/19/23 5

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.

04/19/23 6

Strategy• 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

04/19/23 7

The Model

Employed

On-the-JobSearchers

Choose search effortin Channel 2

UnemployedSearchers

Choose search effort in both Channels

FirmsOpen vacancies and choose recruitment channelHires

Firing

Open

Closed

Search Channel 1

Search Channel 2

Recruitment Channel 2Recruitment Channel 1

04/19/23 8

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.

04/19/23 9

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

04/19/23 10

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.

04/19/23 11

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

04/19/23 12

Hard ConclusionsThe model works so our logic is sound.The data supports the key assumptions.

But……to prove our point:

We need to probe the data furtherControl for institutional changeImprove our tightness (per channel) measureRun an ordered logit on all possible channelsBring in search intensityOther suggestions?

04/19/23 13

Tentative ConclusionsIff we can prove our point:

Unemployed job searchers require assistance in tightening labor markets to compete in the open channelSo that ALM-policy effort should be pro-cyclical.

04/19/23 14

The Model

),)1((

),(

22222

1111

LvsLusuLsmLm

LvsuLsmLmfeu

fu

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

),/)1(/(/)),/1/1(,/(

),/(/)/,(

22222222222222

111111111

feufeu

fuuf

svusvusmvmsθvsθsφ

svusmvmθssφ

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

04/19/23 15

The ModelJob finding flow probability for unemployed JS:

Job finding flow probability for employed JS:

21221

2121

222

22

11

11

)1()1(

ususus

vvss

usus

vs

us

vseuu

iu

iu

eu

iu

u

iu

u

222

22

)1(

usus

vseu

ie

e

04/19/23 16

The Model

Employed(1-u)L

On-the-JobSearchers

UnemployedSearchers

uL

Firing Rate=λ(1-u)

Hiring Rate=φ2e+(φ1

u+φ2u-φ2

e)u

Channel 1φ1

uuLChannel 2

φ2e(1-u)L +φ2

uuL

04/19/23 17

The Model

))(,/( 2,12,12,12,12,12,12,12,1 VJsvusφscrV fuf

First Order Condition on search effort:

Firms choose search effort per channel:

2,1

2,1

2,1

2,1 (.)'

(.) fsφ

φr

c

Jr

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.

04/19/23 18

The Model

02,1 V

Together with the FOC his implies:

Firms open vacancies in both channels:

2,1

2,1

'φ

cJ

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.

04/19/23 19

The Model

JψλwprJ e )(

Implies:

Value of a filled vacancy (job):

eψλr

wpJ

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 marketsWill cause firms to shift towards the open channel.

04/19/23 20

The Model

)( UWψzrU u

Implies:

Unemployed Job Searchers:

0(.)

)(.))('(.)'(2

21

u

su

su

ψr

zrWψψ iu

iu

Which implies that unemployed job searchers set effortsuch that marginal probabilities equalize. This implies they switch to channel 1 when employed job searchers search effort increases in channel 2.

04/19/23 21

The Model

wμψUWλswrW eie )()1( 2

Setting effort to maximize yields:

Employed Job Searchers:

μψ i

ese 1

(.)' 2

Which implies that employed job searchers set effortin response to a wage mark-up and reduce effort when unemployment or the search effort of unemployed in channel 2 increases.

04/19/23 22

The Model

ββ

wwJVwJwWUwWw 1)))(()(()))(()((maxarg*

Which yields:

Solve for equilibrium wage:

ee μψs

zβw

21

)1(*

And closes the model.

04/19/23 23

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

OJS[1,0]=βθ+γX+εModel 1

Logit

Vacancy Rate 1.053 (0.03)

Education: Primary education 0.663 (0.10)

Lower vocational 0.662 (0.07)

Intermediate vocational 0.816 (0.08)

Higher vocational 0.950 (0.11)

University reference

Contract type: Fixed term (future) 5.238 (0.52)

Fixed term (no future) 1.78 (0.13)

Permanent reference

Experience 0.954 (0.00)

Sector Dummies Jointly significant

04/19/23 24

The ResultsTable 2: Recruitment intensity in open channels, 2001

Open[1…5]= βθ+γX+ε

Model 1 Model 2 Model 3

Tightness Proxy Vacancies/Employment Difficult Vacancies/ Employment

Difficult Vacancies/ Vacancies

Β 5.27 (3.03) 8.92 (2.64) 1.74 (2.94)

Size 0 - 9 0.24 (6.25) 0.24 (6.21) 0.32 (3.29)

Size 10 - 24 0.41 (5.30) 0.41 (5.29) 0.52 (2.65)

Size 25 - 49 0.65 (2.44) 0.64 (2.49) 0.75 (1.26)

Size 50 - 100 0.78 (1.30) 0.80 (1.18) 0.93 (0.30)

Size > 100 reference reference reference

Private sector 0.59 (2.40) 0.58 (2.45) 0.56 (2.03)

Public sector reference reference reference

75-100% < MAVO 0.50 (3.62) 0.51 (3.50) 0.54 (2.33)

50-74% < MAVO 0.64 (2.35) 0.62 (2.51) 0.84 (0.69)

25-49% < MAVO 1.32 (1.79) 1.36 (1.92) 1.46 (1.97)

< 25% < MAVO reference reference reference

Sector Dummies Jointly significant Jointly significant Jointly significant

04/19/23 25

The ResultsTable 3: Recruitment intensity in public channels, 2001

Public[1…5]=

βθ+γX+ε

Model 1 Model 2 Model 3

Tightness Proxy Vacancies/Employment Difficult Vacancies/ Employment

Difficult Vacancies/ Vacancies

Β 2.68 (1.61) 1.92 (0.76) 1.28 (1.26)

Size 0-9 0.37 (4.05) 0.38 (4.06) 0.47 (2.07)

Size 10-24 0.59 (2.88) 0.60 (2.78) 0.47 (2.83)

Size 25-49 0.91 (0.51) 0.90 (0.58) 1.07 (0.30)

Size 50-100 0.71 (1.69) 0.72 (1.60) 0.81 (0.81)

Size > 100 reference reference reference

Private sector 0.79 (0.99) 0.77 (1.12) 1.00 (0.00)

Public sector reference reference reference

75-100% < MAVO 1.08 (0.38) 1.07 (0.34) 1.23 (0.51)

50-74% < MAVO 1.10 (0.51) 1.10 (0.50) 1.34 (1.17)

25-49% < MAVO 1.02 (0.09) 0.99 (0.03) 0.94 (0.31)

< 25% < MAVO reference reference reference

Sector Dummies Jointly significant Jointly significant Jointly significant

04/19/23 26

The ResultsTable 4: Recruitment preference for public channel, 2001

PublicPref[1,0]=

βθ+γX+ε

Model 1 Model 2 Model 3

Tightness Proxy Vacancies/Employment Difficult Vacancies/ Employment

Difficult Vacancies/ Vacancies

Β 0.18 (2.08) 0.03 (2.92) 0.80 (1.00)

Size 0-9 3.34 (5.35) 3.36 (5.41) 2.06 (2.15)

Size 10-24 2.29 (4.57) 2.40 (4.81) 1.76 (2.15)

Size 25-49 1.87 (3.23) 1.92 (3.32) 1.73 (2.18)

Size 50-100 1.26 (1.04) 1.26 (1.01) 1.13 (0.45)

Size > 100 reference reference reference

Private sector 1.04 (0.29) 1.06 (0.37) 1.08 (0.41)

Public sector reference reference reference

75-100% < MAVO 1.64 (2.52) 1.63 (2.48) 1.07 (0.24)

50-74% < MAVO 1.59 (2.37) 1.61 (2.42) 1.27 (0.94)

25-49% < MAVO 1.05 (0.27) 1.02 (0.11) 0.83 (0.75)

< 25% < MAVO reference reference reference

Sector Dummies Jointly significant Jointly significant Jointly significant

04/19/23 27

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

Open[0,1]=

βθ+γX+ε

Model 1 Model 2 Model 3

Vacancy rate 1.072 (3.46) 1.044 (1.96) 1.067 (3.50)

Higher education 1.174 (0.53) 9.118 (2.08) 2.516 (3.05)

Lower education reference reference reference

Search duration (mths) 0.995 (0.52) 0.997 (0.29) 1.002 (0.60)

Search duration (>1 y.) 1.000 (0.49) 1.000 (0.46) -

Search duration (< 1 y.)

reference reference -

Confidence (very high=1..very low=5)

1.165 (1.78) - -

C=1: very high conf. - reference 9.24*10-7 (17.31)

C=2: high conf. - 3.365 (1.08)

referenceC=3: neutral - 3.860 (1.98)

C=4: low conf. - 2.443 (1.05)

C=5: very low conf. - 5.883 (2.17) 3.967 (1.75)

Dummies C - Jointly significant Jointly significant

C=1xE=1 - reference 2.96*10-8 (-)

C=2xE=1 - 0.073 (1.66)

referenceC=3xE=1 - 0.090 (1.85)

C=4xE=1 - 0.179 (1.25)

C=5xE=1 - 0.039 (2.46) 0.146 (2.30)

Interactions CxE - Jointly significant Jointly significant