Using linked employer-employee data to analyse fringe benefits

policies. Norwegian experiences.

Workshop on Making Linked Employer-Employee Data Policy Relevant

Harald Dale-OlsenInstitute for Social Research

Why study fringe benefits?

• Non-wage labour costs account for between 15 and 40 percent of total labour costs in major OECD countries (Hart et al.,1983).

• Non-wage elements are becoming more important. Fringe benefits in percent of total compensation increase in the USA from 4.9% to over 10% from 1960s to 1990s (Woodbury, 1983;Hashimoto,2000).

• In Norway establishments offering fringes have increased from 29.4% in 1995 to 57.9% in 2002, but only small changes in the amount of fringes on average.

Fringe benefits 1995-2002 for five educational qualifications

0

1

2

3

4

5

1995 1996 1997 1998 1999 2000 2001 2002

Welders Oil well drillers and miners Economists, universityEconomists, MBA Lawyers National average

Policy related questions

• Why do employers provide fringe benefits?

• What are the gains for the employers? Do fringes ”work” as intended?

• Do workers appreciate fringes? More than wages?

• Is it possible to identify a ranking of fringes?

Answers and implications• Fringe benefits are very effective means to achieve the desired

supply of labour. For a given level of total compensation, more fringes reduces worker turnover.

• In 2002 workers in private large establishments willing to pay (on the margin) 11 NoK in wages for fringes valued 2 NoK. Child care is particularly valued. Economy average 1995-2002 for workers MWP is 3 NoK.

• Employers seldom offer fringes to save pay-roll tax, but primarily to recruit/retain workers (which they also achieve).

• Increasing the share of fringes yields higher total factor productivity.

• Increasing the share of fringes is associated with lower establishment closure hazard.

• Provide a well-designed menu of fringe benefits and achieve reduced worker turnover, improved productivity and improved longevity.

Outline of the presentation

• How should fringe benefits be understood? A brief discussion of previous studies on fringe benefits.

• Data issues.

• How to evaluate workers’ MWP for fringes?

• Fringes and the impact on productivity.

• Fringes and the impact on closure hazards.

Perspectives on fringe benefits

• Equivalent to money wages?

• Price issue 1– market power and ownership

• Price issue 2– pay roll and earnings taxes

• Price issue 3 – fringes not readily available as medium of exchange

• Equivalent to non-wage amenities, i.e., non-pecuniary?

• Fringes singled out from the basic wage: endowment/framing effects and biases of judgement.

• Regardless of perspective: deferred compensation, bargaining, discrimination, motivation

Fringe benefits in previous literature

• Overtime and tax issues (Ehrenberg,1971),• Fringe benefits used as a discriminatory device

(Carrington, McCue and Pierce,2002),• Employer-provided health insurance (Olsen, 2002),• Pension schemes create job lock issues (Madrian, 1994;

Ippolito, 2002) • Pension schemes do NOT create job lock issues (Kapur,

1998; Gilleskie and Lutz, 2002); • Increasing the relative amount of fringes in the

compensation package reduces worker turnover even when controlling for unobserved worker ability (Dale-Olsen, 2005).

How to measure workers’ MWP for fringe benefits?

• Traditional method: Hedonic wage regressions;• Alternative method: Assume workers’ quit rate

depends on the utility flow from the job. Study how the quit behaviour of workers is affected by wages and fringes, i.e., use the quit behaviour as a linking key;

• Method developed and used to evaluate work environment hazards (Gronberg and Reed,1994; Hwang, Mortensen and Reed,1998) and commuting(Van Ommeren, van den Berg and Gorter, 2000).

Data 1

• Linked employer-employee data. Comprise all jobs, all establishments and all workers 1995-2003.

• Possible to study mobility of workers and entry/exit-dynamics of establishments.

• Data contains information on employment spells, wages (hourly wage 2002-2003 only), fringe benefits as valued by tax authorities, working hours, educational attainment, gender, industry codes, location.

• For establishments in Flexi97/ABU2003 and industry statistics: value added, capital, investments.

Data 2

• Questionnaires, Flexi97 and ABU2003. Answered early winter 1997/2003 by the daily manager or personnel manager of roughly 2300 Norwegian establishments.

• Sampled from both public and private sectors establishments with more than 10 employees.

• Stratified sample of establishments, over-sampling of large establishments.

• Non-public administration employers in ABU2003 asked about what kind of fringes provided and motivation.

Provision of fringe benefits 2002

Average in

economy

Reported daily fringe

value

Number of fringes benefits

Daily wages incl. fringes(Nkr)

739.5 Min 0 Min 0

Fringe benefits (%-points) 1.7 1 % 0 1 % 0 At least one fringe benefit 78.4 5 % 0 5 % 0 Pension scheme 54.4 10 % 0 10 % 0 Extended sickness absence 26.5 25 % 1.1 25 % 1 Private physician 15.3 50 % 5.5 50 % 1 Gym 33.4 75 % 17.1 75 % 3 Child care 2.9 90 % 39.7 90 % 4 Cleaning assistance 0.4 95 % 68.3 95 % 4 Holiday home 14.9 99 % 160.2 99 % 5 Extended vacation 21.7

Interval of the distribution

over reported fringe benefits

Max 1672.6

Interval of the distribution

over the number of fringes

provided

Max 7

Establishment size, wages and fringes

Interval of the distribution over average establishment wages 0 – 10% 11 – 25% 26 – 50% 51 – 75% 76 – 90% 91 – 100% All establishments and their workers 1995-2002 Number of employees 5.82 11.73 16.55 18.22 18.59 15.84 Average daily wage 254.27 519.60 689.33 856.49 1063.22 1597.11 Fringe benefits (%-points) 1.15 1.13 1.68 2.81 4.08 4.97 Establishments with more than 10 employees and their workers 1995-2002 Number of employees 29.71 34.86 45.48 56.30 60.44 69.90 Average daily wage 324.70 527.69 692.38 859.40 1068.13 1556.33 Fringe benefits (%-points) 0.60 0.59 1.18 2.34 3.23 4.45 ABU-sample of establishments with more than 10 employees and their workers 2002 Number of employees 32.90 36.33 41.37 49.07 59.36 89.27 Average daily wage 334.18 530.45 701.67 857.54 1076.93 1565.49 Fringe benefits (%-points) 0.57 0.62 0.88 2.05 3.80 4.28

Variation in wage and fringe benefits policies. 2002.

Interval of the distribution over average establishment wages 0 – 10% 11 – 25% 26 – 50% 51 – 75% 76 – 90% 91 – 100% Pension (%) 28.36 59.38 45.99 59.20 77.73 97.59 Extended sickness absence (%) 12.34 29.69 28.54 31.09 27.06 30.25 Private physician (%) 8.72 10.37 19.15 18.07 18.50 17.53 Gym (%) 30.05 25.85 27.35 38.16 53.85 41.79 Child care (%) 3.54 4.28 1.48 1.38 5.90 2.82 Cleaning assistance (%) 0 0.17 0 0.66 2.02 0.67 Holiday home (%) 3.89 11.80 13.11 21.76 19.78 37.58 Extended vacation (%) 25.97 17.81 18.83 19.28 26.20 42.84

Fringes primarily related to establishment productivity contingent on workforce qualification. But establishments with low qualified workers often provide child care, while establishments with high qualified workers provide holiday home.

The impact of wage and fringe benefits policies on workers’ quit hazards (in percent)

Private sector Manufacturing Mod.1 Mod.2 Mod.1 Mod.2 Hourly wage (10 NoK) -2.7*** -2.6*** -5.0** -5.0*** Pension scheme -5.7 -4.3 Extended sickness absence -20.5*** -13.9 Private physician 8.0 7.3 Gym -4.8 -20.9* Child care -40.0*** -38.0* Cleaning assistance -16.2 -5.3 Holiday home -15.7*** -7.4 Extended vacation 7.3 -10.9 Fringe benefits (1 percentage point) -3.0*** -3.0**

The impact of fringe benefits policies on workers’ quit hazards

0 %

1 %

2 %

3 %

4 %

5 %

0 2 4 6 8 10 12 14 16 18 20

Years of seniority

Average

No fringes

3% fringes

5% fringes

10% fringes

Marginal willingness to pay for fringes

-50

0

50

100

150

200

Pensio

nschem

e

Ext.s

ickness

absence

Priv

ate

physic

ian

Gym

Child

care

Cle

anin

gassis

tance

Holid

ay

hom

e

Exte

nded

vacatio

n

Frin

ges

(1%

-poin

t)

Private sector Manufacturing

Compensation policy and worker turnover 1995-2002.

Fixed Dynamic Population: All Private Private 10+ Private ABU 25% Private 10+ Dependent variable: Quit rate Quit rate Quit rate Quit rate Quit rate Increase daily wage by 100NoK -1.9*** -1.9** -0.8*** -0.8** -6.6*** Increase fringes by 10%point -0.6** -0.6** -3.5*** -3.0* -11.7** Controls: Establishment YES YES YES YES Year YES YES YES YES YES Industry (3-digit)/ county YES N 238541 232610 54884 1368 8108 NxT 1136976 1094886 253525 9483 34100 Implied MWP for increasing fringe benefits share of total compensation by 1 percentage point

3.0** 3.0** 41.1** 38.7 17.7*

Why provide fringe benefits?

Employees prefer fringes to wages

Recruit and retain

We achieve lower prices than employees

To save pay-roll tax

Mean (%) 25.5 55.0 24.1 2.0 Single motivation (sm) 7.7 74.9 19.6 0.5 Size-relationship No Positive Positive No Impact on quit hazard No -23.0% No No Impact on quit hazard after fringe control

No -18.5 No No

The impact of fringe benefits policies on total factor productivity (in percent).

ABU2003 and manufacturing. Non-dynamic Dynamic Fringes (%) 5.7*** -1.9 4.6*** 3.3** 2.4 Fringes (%) previous period 2.6 11.8** 10.9** Controls: Homogeneous labour YES YES YES Heterogeneous labour YES YES Pay-roll tax rate YES Capital YES YES YES YES YES Year YES YES YES YES YES Industry YES YES YES YES Major cities YES YES YES Establishment YES

The impact of fringe benefits policies on establishment closure

Cox-regression Cohorts 1996-2000 All Manufacturing Log workforce size -19.8*** -15.5*** Multiple-establishment organisation -23.9*** -29.8*** Log daily wages -7.4*** -9.9*** Fringe benefits (%) -0.2*** -0.7*** Women (in % of workforce) -0.4 -2.1 Average years of education -0.2 -0.3 Number of educational qualifications 1.4*** 1.0*** Part-time workers (in % of workforce) -6.9*** -13.2*** Union workers (in % of workforce) 6.6** 16.7** Average municipality wage 0.1*** 0.1* Industry and cohort dummies YES YES

The impact of new work practices on establishment closure

Flexi97 Manufacturing Log workforce size -35.6*** -46.7*** Multiple-establishment organisation 36.7 32.7 Log total labour costs per employee -26.6** 1318.7*** Fringe benefits (%) -5.2 -11.2 Women (in % of workforce) 6.5 44.3 Average years of education -37.9** -32.5* Union workers (in % of workforce) 43.5 35.2 Average municipality wage 476.6 449.7 Total factor productivity (TFP) -61.8*** Log capital -19.2*** Pay-roll tax rate 13.9** Index for new work practices -69.8*** Index for new work practices squared 10.8*** Index for competition issues 207.1***

The impact of new work practices on establishment closure

0 %

5 %

10 %

15 %

20 %

25 %

30 %

35 %

40 %

45 %

0 5 10 15 20 25 30

Low fringe, lowNWP

Low fringe, highNWP

High fringe, lowNWP

High fringe, highNWP