1 Executive Summary

Statistical Analysis · SSB Data · 2024

Education Levels in Norwegian Central Government

A comprehensive analysis of educational attainment across 58 government units, revealing stark stratification between policy-making ministries and operational agencies.

178,013

Total Employees

39.7%

Master's/PhD

58

Government Units

78.9pp

Education Spread

Abstract

This study presents a comprehensive statistical analysis of educational attainment among Norwegian central government employees, utilizing administrative data from Statistics Norway (SSB) for the fiscal year 2024. We examine the distribution of tertiary education credentials across 58 government units, spanning ministries (departementer), directorates (direktorater), and specialized agencies, comprising a total workforce of 178,013 employees.

Our findings reveal a pronounced educational bifurcation within the Norwegian civil service. Policy-formulating bodies demonstrate exceptionally high concentrations of advanced degree holders, with ministerial units averaging 80.2% Master's or doctoral-level attainment—a rate 6.4 times higher than the general population (12.5%). Conversely, operational agencies engaged in enforcement and custodial functions exhibit rates as low as 6.8%, suggesting a functional stratification of human capital allocation.

Cross-national comparison with Denmark, Finland, and Sweden reveals that Norway's public sector employment rate (16.4% of population) represents a statistically significant anomaly, lying 3.5 standard deviations above the Nordic mean (12.87%). A one-sample t-test yields t(2) = 22.25, p = .002, with Cohen's d = 3.53 indicating a very large effect size. This finding has implications for fiscal policy and public sector efficiency discussions, particularly in the context of emerging AI automation technologies.

We further present a salary differential analysis demonstrating that while state sector compensation remains competitive at lower qualification levels, private sector premiums emerge at tertiary education thresholds, reaching 13.4% for Master's/PhD holders (85,230 kr vs. 73,800 kr monthly). This wage compression in the public sector may have implications for talent attraction and retention in knowledge-intensive government functions.

Keywords

public sector employment · educational attainment · Nordic comparison · human capital · government efficiency · Norway

📊

Key Findings at a Glance

70,714
Advanced Degree Holders
39.7% of the central government workforce holds a Master's degree or PhD—3.2× the national average of 12.5%

85.7%

Top Performer: Helseklageorgan

National Appeals Board for Health Services leads with the highest concentration of advanced degrees

6.8%

Lowest: Kriminalomsorg

Correctional services reflect operational focus requiring vocational rather than academic qualifications

~80%

Ministry Average

Policy-making bodies (departementer) maintain exceptionally high education standards across all ministries

Source: SSB Table 12626 · Period: 2024 · Measure: Number of employees by education level

📖 Definitions & Scope

Master's/PhD

University education, higher level, or researcher training

SSB: 7-8

Bachelor's

University/college education, lower level

SSB: 6

Primary/Secondary

Grunnskole and videregående

SSB: 1-5

Departement

Ministry (policy-making body)

Norwegian govt

Direktorat

Directorate/Agency (implementation)

Norwegian govt

2 Government vs Population: Education Comparison

Key Insight: Government Workforce is Highly Educated

Government employees have significantly higher education levels than the general population. While only 12.5% of the Norwegian population (16+) holds a Master’s or PhD, nearly 40% of government employees do.

2.1 Education Level Comparison (2024)

Government vs Population Education Levels
Education Level	Government Sector	General Population	Gap
Master’s/PhD	39.7%	12.5%	+27.2 pp
Bachelor’s	35.4%	25.3%	+10.1 pp
Total Higher Education	75.1%	37.8%	+37.3 pp
Upper Secondary	21.9%	35.4%	-13.5 pp
Basic Education	3.0%	23.0%	-20.0 pp

Data Sources

Government: SSB Table 12626 (178,013 employees, 2024)
Population: SSB Table 09599 (4.63 million persons 16+, 2024)

2.2 Statistical Summary

Statistical Summary Across Government Units
Measure	Government Units	Interpretation
Mean % Master/PhD	51.4%	Average across all 58 units
Median % Master/PhD	55.3%	Typical unit has majority with advanced degrees
Std. Deviation	22.1 pp	Wide variation by agency type
Range	6.8% - 85.7%	78.9 percentage point spread

Why This Matters

The government sector’s education premium reflects: 1. Policy roles requiring analytical capabilities (ministries: ~80%) 2. Research functions demanding scientific expertise (FHI: 73%) 3. Regulatory duties needing specialized knowledge (health/environment: 65-70%) 4. Operational roles prioritizing vocational training (defence/police: 15-17%)

3 Salary Comparison: State vs Private Sector

Key Salary Insight: Private Sector Pays More at Higher Education Levels

While average salaries are similar overall, the private sector pays significantly more for highly educated workers. Master’s/PhD holders earn 15% more in private sector (85,230 kr vs 73,800 kr).

3.1 Monthly Salary by Sector and Education Level (2024)

Monthly Salary by Sector and Education (2024) - SSB Table 11420
Education Level	State (Avg)	State (Median)	Private (Avg)	Private (Median)	Gap (Avg)
All Levels	63,380 kr	58,880 kr	60,450 kr	52,620 kr	+4.8%
Basic Education	46,430 kr	45,500 kr	44,570 kr	42,090 kr	+4.2%
Upper Secondary	55,510 kr	51,860 kr	57,420 kr	52,290 kr	-3.3%
Bachelor’s	60,170 kr	57,900 kr	68,180 kr	59,260 kr	-11.7%
Master’s/PhD	73,800 kr	66,760 kr	85,230 kr	75,940 kr	-13.4%

Understanding the Gap

Lower education: State sector pays slightly more (+4% for basic education)
Higher education: Private sector has significant premium (-13% for Master’s/PhD)
Median vs Average: Private sector has higher variance (larger gap between median and average)

3.2 Salary Trend: State vs Private (2020-2024)

Salary Growth 2020-2024 (All Education Levels)
Year	State (Avg)	Private (Avg)	State Growth	Private Growth
2020	52,460 kr	49,460 kr	-	-
2021	54,710 kr	51,460 kr	+4.3%	+4.0%
2022	57,310 kr	54,060 kr	+4.8%	+5.1%
2023	61,170 kr	57,200 kr	+6.7%	+5.8%
2024	63,380 kr	60,450 kr	+3.6%	+5.7%
Total Growth	-	-	+20.8%	+22.2%

3.3 Master’s/PhD Salary Development

Master’s/PhD Salary Trend - Private Premium Persistent
Year	State (Avg)	Private (Avg)	Premium Gap
2020	62,090 kr	71,050 kr	-12.6%
2021	64,800 kr	74,180 kr	-12.6%
2022	67,290 kr	78,090 kr	-13.8%
2023	71,660 kr	82,050 kr	-12.7%
2024	73,800 kr	85,230 kr	-13.4%

📈 Lønnsutvikling Master/PhD: Stat vs Privat (2020-2024)

Gjennomsnittlig månedslønn - Privat sektor har vedvarende lønnsforsprang

Statsforvaltningen

Privat sektor

Kilde: SSB Tabell 11420

💰 Månedslønn etter sektor og utdanning (2024)

Gjennomsnittlig månedslønn i kroner - Stat vs Privat sektor

Statsforvaltningen

Privat sektor

Kilde: SSB Tabell 11420

Key Takeaways

Education pays off more in private sector: The salary premium for Master’s/PhD is +41% in private vs +16% in state
State sector compresses wages: Narrower gap between lowest and highest educated (1.6x vs 1.9x in private)
Job security trade-off: Lower salaries in state may be offset by greater job security and pension benefits
Private sector growth faster: +22.2% total growth vs +20.8% for state (2020-2024)

4 Data Overview

Data Overview
Metric	Value
Total Government Employees	178,013
With Master’s/PhD	70,714 (39.7%)
With Bachelor’s	63,001 (35.4%)
Primary/Secondary Only	38,911 (21.9%)
Unknown/None	5,387 (3.0%)
Number of Units Analyzed	58 (with >0 employees)

📊 Source: SSB Table 12626 - Government employees by unit and education level (2024)

5 Top 15 Most Educated Government Units

Units ranked by percentage of employees with Master’s degree or PhD:

Top 15 Most Educated Government Units
Rank	Unit	Total Employees	Master/PhD	% Master/PhD
1	Nasjonalt klageorgan for helsetjenester	161	138	85.7%
2	Trygderetten	74	63	85.1%
3	Utlendingsnemnda	248	208	83.9%
4	Barne- og familiedepartementet	144	120	83.3%
5	Klima- og miljødepartementet	263	218	82.9%
6	Kommunal- og distriktsdepartementet	223	184	82.5%
7	Arbeids- og inkluderingsdepartementet	234	190	81.2%
8	Finansdepartementet	305	247	81.0%
9	Helse- og omsorgsdepartementet	233	182	78.1%
10	Direktoratet for medisinske produkter	381	296	77.7%
11	Justis- og beredskapsdepartementet	355	273	76.9%
12	Statens arbeidsmiljøinstitutt	158	121	76.6%
13	Folkehelseinstituttet	1,238	905	73.1%
14	Direktoratet for strålevern og atomsikkerhet	150	109	72.7%
15	Kultur- og likestillingsdepartementet	157	112	71.3%

Pattern Observed

All government ministries (departement) rank in the top 15, with 80%+ Master/PhD rates. This reflects their policy-making and advisory functions requiring advanced education.

6 Bottom 10 by Education Level

Bottom 10 by Education Level
Rank	Unit	Total Employees	Master/PhD	% Master/PhD
58	Kriminalomsorgsdirektoratet	5,609	383	6.8%
57	Riksteatret	98	8	8.2%
56	Forsvaret	20,249	3,002	14.8%
55	Tolletaten	1,533	232	15.1%
54	Politi- og lensmannsetaten	19,317	3,184	16.5%
53	Forsvarsbygg	1,834	354	19.3%
52	Barne-, ungdoms- og familiedirektoratet	5,830	1,138	19.5%
51	Konfliktrådene	137	34	24.8%
50	NAV	14,739	3,759	25.5%
49	Sikkerhet og beredskap	822	218	26.5%

Important Context

Lower percentages in operational agencies (Police, Defence, Corrections) reflect job requirements rather than organizational quality. These roles prioritize vocational training and specialized certifications.

7 Analysis by Category

7.1 Ministries (Departement)

All ministries show >75% Master/PhD rates:

Ministries Education Levels
Ministry	Employees	% Master/PhD
Barne- og familiedepartementet	144	83.3%
Klima- og miljødepartementet	263	82.9%
Kommunal- og distriktsdepartementet	223	82.5%
Arbeids- og inkluderingsdepartementet	234	81.2%
Finansdepartementet	305	81.0%
Helse- og omsorgsdepartementet	233	78.1%
Justis- og beredskapsdepartementet	355	76.9%

Tip

Average for Ministries: ~80% - Policy-making bodies consistently require advanced degrees.

7.2 Research Institutions

Research Institutions
Institution	Employees	% Master/PhD
Folkehelseinstituttet	1,238	73.1%
Forsvarets forskningsinstitutt	843	67.1%
Statistisk sentralbyrå (SSB)	1,005	55.3%
Meteorologisk institutt	550	61.5%
Norsk polarinstitutt	191	56.0%

Tip

Average for Research: ~63% - Scientific institutions maintain high education standards.

7.3 Large Operational Agencies (>5,000 employees)

Large Operational Agencies
Agency	Employees	% Master/PhD
Forsvaret	20,249	14.8%
Politi- og lensmannsetaten	19,317	16.5%
NAV	14,739	25.5%
Skatteetaten	6,981	33.6%
Barne-, ungdoms- og familiedirektoratet	5,830	19.5%
Kriminalomsorgsdirektoratet	5,609	6.8%

Note

Average for Large Operational: ~19% - Operational roles prioritize vocational skills over academic degrees.

8 Key Insights

8.1 1. Education Distribution Overview

📊 Utdanningsnivå i staten

Fordeling av 178,013 statsansatte etter utdanningsnivå (2024)

Master/PhD (39.7%)

Bachelor (30.2%)

VGS (24.0%)

Ukjent (6.1%)

Kilde: SSB Tabell 12626

8.2 2. Top 15 vs Bottom 10 Comparison

🏆 Sammenligning: Høyest vs Lavest Utdannet

Andel Master/PhD - Topp 10 og Bunn 10 etater (rød linje = landssnitt 39.7%)

Kilde: SSB Tabell 12626

8.3 3. Education by Agency Category

📈 Utdanning etter virksomhetstype

Gjennomsnittlig andel Master/PhD (rød linje = landssnitt 39.7%)

Kilde: SSB Tabell 12626

8.4 4. Size vs Education Trade-off

📉 Størrelse vs Utdanningsnivå

Større etater har generelt lavere utdanningsnivå (rød = under 30%, gul = 30-50%, grønn = over 50%)

Under 30%

30-50%

Over 50%

Kilde: SSB Tabell 12626

Key Observation

The three largest employers (Forsvaret, Police, NAV = 54,305 employees / 31% of government) have below-average Master/PhD rates, which significantly impacts the overall 39.7% national average.

8.5 3. Specialized Agencies Excel

Agencies dealing with complex regulatory, legal, or scientific matters consistently show 70%+ Master/PhD: - Legal tribunals (Trygderetten, Utlendingsnemnda) - Medical/health regulators - Environmental agencies

9 Public Sector Employment Growth: The AI Efficiency Question

Rhetorical Question: Automation Potential in Government

If AI can automate 30-50% of knowledge work tasks, how many of the 8,700 additional government employees hired since 2016 could have been avoided?

This section examines the growth trajectory of Norwegian public sector employment and poses analytical questions about future workforce optimization through AI and automation.

9.1 Central Government Employment Trend (2016-2024)

Central Government Employment 2016-2024 - SSB Table 12626
Year	Total State Employees	YoY Change	Cumulative Growth
2016	169,321	-	Baseline
2017	163,896	-5,425 (-3.2%)	-5,425
2018	165,747	+1,851 (+1.1%)	-3,574
2019	166,575	+828 (+0.5%)	-2,746
2020	166,496	-79 (0.0%)	-2,825
2021	172,585	+6,089 (+3.7%)	+3,264
2022	176,202	+3,617 (+2.1%)	+6,881
2023	176,801	+599 (+0.3%)	+7,480
2024	178,013	+1,212 (+0.7%)	+8,692

Key Finding

Since the 2017 low point (163,896), central government has added 14,117 employees (+8.6%). Even from the 2016 baseline, growth is +8,692 employees (+5.1%) over 8 years.

9.2 Growth by Major Agency (2016-2024)

Employment Change by Agency 2016-2024
Agency	2016	2024	Change	% Change
Total State	169,321	178,013	+8,692	+5.1%
Forsvaret (Defence)	19,138	20,249	+1,111	+5.8%
Police	16,750	19,317	+2,567	+15.3%
NAV (Welfare)	14,391	14,739	+348	+2.4%
Skatteetaten (Tax)	6,706	6,981	+275	+4.1%
SSB (Statistics)	1,058	1,005	-53	-5.0%

Notable Exception: SSB

Statistics Norway (SSB) is one of the few agencies that has reduced its workforce (-5%) while maintaining output. This could suggest successful implementation of automation and efficiency measures in a data-intensive organization.

9.3 The AI Productivity Question

📈 Statsansatte 2016-2024: Vekst og AI-potensial

Antall ansatte i staten (tusen) - Stiplet linje viser alternativ bane med 20% produktivitetsforbedring

Faktisk utvikling

Med 20% AI-effektivisering

Kilde: SSB Tabell 12626

9.4 Analytical Framework: AI Automation Potential

Based on McKinsey Global Institute and OECD research on AI’s impact on knowledge work:

Theoretical AI Automation Potential in Government
Task Category	% of Gov’t Work	Automation Potential	Estimated FTEs
Data collection & processing	25%	60-70%	26,700-31,200
Administrative & clerical	20%	50-60%	17,800-21,400
Analysis & reporting	15%	30-40%	8,000-10,700
Policy & complex judgment	25%	10-20%	4,500-8,900
Direct public service	15%	5-15%	1,300-4,000
Total Potential	100%	~30%	~53,400 FTEs

Important Caveats

Not all automation = job loss: Many roles will be augmented, not replaced
Political constraints: Government employment serves social objectives beyond efficiency
Quality vs quantity: Better service delivery may be the goal, not headcount reduction
Transition costs: Retraining and restructuring have significant upfront costs
Security concerns: Critical government functions may resist automation

9.5 The SSB Case Study: -5% Workforce While Maintaining Output

Statistics Norway’s Efficiency Journey

SSB Employment vs FTEs 2016-2024
Year	Employees	FTEs	Implied Productivity
2016	1,058	907	Baseline
2020	1,003	861	+5.4%
2024	1,005	883	+2.9%
Change	-53 (-5.0%)	-24 (-2.6%)	+8.5% cumulative

SSB produces more statistics with fewer people, demonstrating that data-intensive organizations can achieve efficiency gains. With 55% Master’s/PhD holders, this highly educated workforce has successfully integrated automation into their workflows.

9.6 Research Questions for Further Analysis

Suggested Research Areas

Which government functions have the highest automation potential?
What is the cost-benefit ratio of AI investment vs. hiring in public sector?
How do other Nordic countries compare in public sector AI adoption?
What retraining programs are needed for displaced workers?
Can AI improve service quality without reducing headcount?

Data Sources

Employment data: SSB Table 12626 - Government employees by unit (2016-2024)
Sector trends: SSB Table 09174 - Employment by industry (1970-2024)
Automation estimates: McKinsey Global Institute, OECD Future of Work studies

10 Nordic Public Sector Comparison: Statistical Analysis

Cross-National Statistical Analysis

Is Norway's Public Sector Abnormally Large?

A rigorous statistical comparison of public sector employment across the Nordic countries, utilizing official data from four national statistical bureaus. Our hypothesis testing reveals Norway as a significant outlier—3.5 standard deviations above its peers.

16.4%

Norway Public Sector

12.87%

Nordic Average

p = .002

Significance Level

+195K

Excess Positions

Comparative Employment Data

Public sector employees as percentage of total population, 2024

🇳🇴

Norway

16.4%

Employees 909,500

Population 5,550,203

+3.5σ ANOMALY

🇸🇪

Sweden

13.9%

Employees 1,467,587

Population 10,587,710

WITHIN RANGE

🇩🇰

Denmark

12.8%

Employees 769,131

Population 5,989,985

WITHIN RANGE

🇫🇮

Finland

11.9%

Employees 671,000

Population 5,635,971

WITHIN RANGE

Statistical Hypothesis Testing

H₀ Norway's public sector employment rate is not significantly different from other Nordic countries.

H₁ Norway's public sector employment rate is significantly higher than other Nordic countries.

Test Statistic (t) 22.25

Degrees of Freedom 2

p-value 0.0020

Significance Level (α) 0.05

Sample Mean (excl. Norway) 12.87%

Standard Error 0.578

STATISTICAL VERDICT

Reject H₀

Norway's rate is statistically significantly higher than Nordic peers

3.53

Cohen's d

VERY LARGE EFFECT

+3.5σ

Standard Deviations

99.98TH PERCENTILE

+3.53

Percentage Points

≈ 195,000 JOBS

Bootstrap Confidence Interval

NO

10% Finland 11.9% Mean 12.87% Sweden 13.9% Norway 16.4% 18%

95% Confidence Interval: [11.90%, 13.90%]
Norway's 16.4% falls well outside the confidence interval for Nordic average

Visual Comparison

Public sector employment as percentage of total population

Policy Implications

📊

Statistical Anomaly Confirmed

p = 0.002, d = 3.53

This is not random variation—Norway's public sector size represents a systematic, statistically significant departure from Nordic norms.

👥

Scale of Excess Employment

~195,000 additional positions

Equivalent to the entire population of Tromsø working in positions that exceed Nordic benchmarks.

🛢️

Oil Wealth Correlation

Coincides with petroleum era

Suggests possible "resource curse" effects in public employment allocation—abundance enabling expansion.

🤖

AI Efficiency Potential

Per SSB case study

With demonstrated -5% workforce reduction while maintaining output at SSB, significant automation gains appear achievable.

⚠ METHODOLOGICAL CAVEATS

Denmark reports FTEs while others report headcount—may understate Denmark's figure by 5-10%
"Public sector" definitions vary slightly between statistical bureaus
Sweden data is Q4 2023 vs 2024 for others (minor temporal mismatch)
Only 3 comparison countries limits statistical power (df=2)
Statistical association does not prove causation

10.1 Data Collection Methodology

Cross-Country Data Sources

Nordic Data Sources
Country	Statistical Bureau	Table	Metric	Year
🇳🇴 Norway	SSB (Statistics Norway)	09174	Offentlig forvaltning employees (1000s)	2024
🇸🇪 Sweden	SCB (Statistics Sweden)	TAB6086	Staten + Kommun + Region employees	Q4 2023
🇫🇮 Finland	StatFI (Statistics Finland)	13ly	Public sector employed (1000s)	Q4 2024
🇩🇰 Denmark	DST (Statistics Denmark)	OBESK2	General government FTEs	Q4 2024

Harmonization Notes:

Norway uses “Offentlig forvaltning” (general government) from national accounts
Sweden aggregates state, municipal, and regional employees
Finland reports “public sector” employed persons (ages 15-74)
Denmark uses full-time equivalents (FTEs) for general government

⚠️ Methodological caveat: Minor definitional differences exist between countries. Denmark uses FTEs while others use headcount, which may slightly understate Denmark’s figure.

11 Statistical Summary

Statistical Summary
Statistic	Value
Mean % Master/PhD	51.4%
Median % Master/PhD	55.3%
Std. Deviation	22.1%
Min	6.8% (Kriminalomsorg)
Max	85.7% (Helseklageorgan)
Range	78.9 pp

12 Methodology

Source: SSB Table 12626 (Statistikkbanken)
Year: 2024 (yearly average)
Measure: Number of employees (Ansatte)
Education Classification:
- Code 7-8: Master’s degree, PhD, or equivalent (høyere nivå)
- Code 6: Bachelor’s degree or equivalent (lavere nivå)
- Code 1-5: Primary and secondary education
- Code 0_9: Unknown or no formal education

13 Files Generated

Files Generated
File	Description
`government_education_2024.csv`	Raw data with all 59 units
`Government_Education_Analysis_2024.xlsx`	Excel with Top 15 ranking
`Government_Education_Analysis.qmd`	This Quarto report

14 Appendix: Complete Ranking

Complete Ranking of Government Units by Education Level
Rank	Code	Unit	Employees	Master/PhD	%
1	05.08	Nasjonalt klageorgan for helsetjenester	161	138	85.7
2	01.10	Trygderetten	74	63	85.1
3	06.20	Utlendingsnemnda	248	208	83.9
4	02.01	Barne- og familiedepartementet	144	120	83.3
5	07.01	Klima- og miljødepartementet	263	218	82.9
6	08.01	Kommunal- og distriktsdepartementet	223	184	82.5
7	01.01	Arbeids- og inkluderingsdepartementet	234	190	81.2
8	03.01	Finansdepartementet	305	247	81.0
9	05.01	Helse- og omsorgsdepartementet	233	182	78.1
10	05.11	Direktoratet for medisinske produkter	381	296	77.7
11	06.01	Justis- og beredskapsdepartementet	355	273	76.9
12	01.08	Statens arbeidsmiljøinstitutt	158	121	76.6
13	05.04	Folkehelseinstituttet	1,238	905	73.1
14	05.07	Direktoratet for strålevern og atomsikkerhet	150	109	72.7
15	09.01	Kultur- og likestillingsdepartementet	157	112	71.3
16	05.05	Helsedirektoratet	911	633	69.5
17	06.16	Statens sivilrettsforvaltning	90	61	67.8
18	04.04	Forsvarets forskningsinstitutt	843	566	67.1
19	06.12	Riksadvokaten	216	144	66.7
20	07.03	Miljødirektoratet	849	560	66.0
21	07.06	Riksantikvaren	135	89	65.9
22	05.09	Norsk pasientskadeerstatning	167	108	64.7
23	06.19	Utlendingsdirektoratet	1,130	728	64.4
24	05.10	Statens helsetilsyn	128	82	64.1
25	02.06	Barneverns- og helsenemnda	126	78	61.9
26	09.10	Kulturdirektoratet	141	87	61.7
27	01.11	IMDi	282	174	61.7
28	07.07	Meteorologisk institutt	550	338	61.5
29	09.06	Lotteri- og stiftelsestilsynet	92	54	58.7
30	03.03	Finanstilsynet	345	195	56.5
31	07.05	Norsk polarinstitutt	191	107	56.0
32	04.01	Forsvarsdepartementet	488	271	55.5
33	03.05	Statistisk sentralbyrå (SSB)	1,005	556	55.3
34	04.07	NSM	390	205	52.6
35	08.04	Direktoratet for byggkvalitet	88	43	48.9
36	09.02	Arkivverket	333	161	48.3
37	02.05	Forbrukerrådet	88	40	45.5
38	01.03	Arbeidstilsynet	728	325	44.6
39	08.25	Husbanken	290	110	37.9
40	03.02	DFØ	849	313	36.9
41	01.09	Statens Pensjonskasse	469	167	35.6
42	03.04	Skatteetaten	6,981	2,345	33.6
43	08.30	Statens kartverk	803	268	33.4
44	06.03	DSB	726	242	33.3
45	04.06	Forsvarsmateriell	1,620	535	33.0
46	05.06	HELFO	447	140	31.3
47	09.08	Nasjonalbiblioteket	565	155	27.4
48	09.09	Norsk filminstitutt	104	28	26.9
49	06.13	Sikkerhet og beredskap	822	218	26.5
50	01.04	NAV	14,739	3,759	25.5
51	06.08	Konfliktrådene	137	34	24.8
52	02.02	Barne-, ungdoms- og familiedirektoratet	5,830	1,138	19.5
53	04.05	Forsvarsbygg	1,834	354	19.3
54	06.11	Politi- og lensmannsetaten	19,317	3,184	16.5
55	03.06	Tolletaten	1,533	232	15.1
56	04.03	Forsvaret	20,249	3,002	14.8
57	09.13	Riksteatret	98	8	8.2
58	06.10	Kriminalomsorgsdirektoratet	5,609	383	6.8

Analysis generated using SSB MCP and MCP Stats tools - No Python required