Labour Market in Lithuania (edition 2020)
Earnings, working time and labour costs
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In 2019, average gross monthly earnings in the whole economy (individual enterprises included), eliminating the effect of the change of indexation in the existing gross earnings from 2019, exceeded the 2018 level by 8.8 per cent and amounted to EUR 1,296.4. In the public sector, gross monthly earnings increased by 12.3 per cent and accounted for EUR 1,370; in the private sector, it increased by 7.3 per cent and accounted for EUR 1,264.5.
Average gross monthly earnings
From 1 January 2019, the rates of the state social insurance contributions paid by the employer and the employee were changed. Gross earnings were indexed 1.289 times.
The latest and detailed data are available in the Database of Indicators
Average net monthly earnings
The latest and detailed data are available in the Database of Indicators
In 2019, an increase in average gross monthly earnings by eliminating the effect of the change of indexation in the existing gross earnings from 2019, in the whole economy was observed in all economic activities, from 5.1 per cent (in transportation and storage) to 13.5 per cent (human health care and social work).
Changes in average gross monthly earnings in the whole economy by economic activity, 2019
Compared to 2018
Change in earnings was calculated by eliminating the effect of the change of indexation in the existing gross earnings from 2019.
The latest and detailed data are available in the Database of Indicators
Average net monthly earnings (after taxes) in the whole economy amounted to EUR 822.1 and, compared to 2018, increased by 14.2 per cent. In the public sector, net monthly earnings increased by 17.6 per cent and amounted to EUR 864.4, in the private sector – by 12.7 per cent and totalled EUR 803.8.
In 2019, against 2018, real earnings in the whole economy increased by 11.6 per cent: in the public sector – by 15 per cent, in the private sector – 10.2 per cent.
Changes in average monthly earnings in the whole economy
Compared to the previous year
Change in earnings was calculated by eliminating the effect of the change of indexation in the existing gross earnings from 2019.
The latest and detailed data are available in the Database of Indicators
Changes in average gross monthly earnings by sector
Compared to the previous year
Change in earnings was calculated by eliminating the effect of the change of indexation in the existing gross earnings from 2019.
The latest and detailed data are available in the Database of Indicators
Changes in earnings were influenced by the following changes since 1 January 2019: increased basic wages for politicians, judges, civil servants, public service employees and employees of budgetary institutions, increased minimum monthly wage, revised new pay system for civil servants, changed calculation procedure of tax-free amount and other reasons.
Average gross monthly earnings remained the highest in enterprises engaged in information and communication and financial and insurance activities (1.8 times higher than the national average). More than half (60.2 per cent) of the employees of enterprises engaged in different economic activities (water supply; sewerage; waste management and remediation; wholesale and retail trade; construction; transportation and storage activities, etc.) received less than the national average gross monthly earnings.
In 2019, the lowest earnings were received by the employees of enterprises engaged in accommodation and food service activities (2.6 times lower compared to information and communication enterprises, where the earnings were the highest, and by 30.2 per cent lower than the national average), arts, entertainment and recreation activities (respectively, 2.2 times and by 18.7 per cent lower), and other service activities (respectively, 2.2 times and by 18.1 per cent lower).
Average gross monthly earnings in the whole economy by sex and economic activity, 2019
The latest and detailed data are available in the Database of Indicators
Changes in average gross monthly earnings in the whole economy by sex and economic activity, 2019
The latest and detailed data are available in the Database of Indicators
In 2019, the biggest average gross monthly earnings were in the Capital region, (EUR 1,452.6) and against 2018, by eliminating the effect of the change of indexation in the existing gross earnings from 2019, increased by 8.9 per cent. Gross monthly earnings in the Central and Western Lithuania region increased by 8.3 per cent and totalled EUR 1,178.8. Over the year, gross monthly earnings gap between these two regions totalled EUR 273.8.
In 2019, against the previous year, by eliminating the effect of the change of indexation in the existing gross earnings from 2019, the average gross monthly earnings in the whole economy increased in all counties – from 6.5 per cent in Telšiai county to 9.6 per cent in Kaunas county.
Average monthly earnings by county, 2019
The latest and detailed data are available in the Database of Indicators
In 2019, against 2018, average gross monthly earnings, by eliminating the effect of the change of indexation in the existing gross earnings from 2019, increased in all municipalities – from 1.6 per cent in Kazlų Rūda municipality to 12.8 per cent in Alytus district municipality.
In 2019, the largest average gross monthly earnings were in Vilnius city (EUR 1,501.5), and the smallest – in Kalvarija municipality (EUR 922.1). Over the year, gross earnings gap between Vilnius city and Kalvarija municipality totalled EUR 579.4.
In 19 municipalities, the average gross monthly earnings did not reach EUR 1,000. In Vilnius city, Kaunas city and Klaipėda city municipalities, the average gross monthly earnings exceeded the average gross monthly earnings in the whole economy (by EUR 205, EUR 32 and EUR 26 respectively).
In 2019, difference in earnings in the whole economy was observed in all economic activities. The highest earnings were recorded for wholesale and retail trade; repair of motor vehicles and motorcycles in Kaunas county (EUR 1,305.5), the lowest – in Tauragė county (EUR 811.4). Peak in the earnings was most noticeable in enterprises engaged in transportation and storage activities in Klaipėda county (EUR 1,294.3), while the lowest – in Marijampolė county (EUR 814.8). Employees in construction enterprises received the highest earnings in Vilnius county (EUR 1,253.6 EUR), the lowest – in Utena county (EUR 972.8). Peak in the earnings was fixed in education institutions in Vilnius county (EUR 1,311.4),while the lowest – in Utena county (EUR 1,008.5).
The highest earnings gap among the counties was most noticeable in information and communication activities (EUR 1,655.5) between Vilnius and Telšiai counties.
In 2019, employees of enterprises engaged in information and communication as well as financial and insurance activities in Vilnius county earned the highest net earnings (after taxes): on average – EUR 1,515.5 and EUR 1,471.7 respectively. Professionals of enterprises engaged in information and communication activities in Kaunas county were in the third place: on average – EUR 1,257.6 (after taxes) in 2019.
Employees in enterprises engaged in accommodation and food service activities in Tauragė county were paid the lowest net earnings: on average – EUR 450.3.
Over the year, gross monthly earnings of employees of budgetary institutions increased by 13.1 per cent and was by EUR 53.3 higher than the national average, though by 1.5 per cent lower than in the public sector. Gross monthly earnings of employees of budgetary institutions increased in all counties, with the highest growth in Kaunas county – 14.5 per cent and Vilnius county – 13. In the counties, the average gross monthly earnings of employees of budgetary institutions was higher than the average in the county – from 1.9 per cent (in Telšiai county) to 14.3 per cent (in Tauragė county).
Average gross monthly earnings of employees of budgetary institutions by county, 2019
The latest and detailed data are available in the Database of Indicators
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Labour statistics indicators are presented by six enterprise size groups which are classified according to the number of employees (individual enterprises included). In 2019, against 2018, by eliminating the effect of the change of indexation in the existing gross earnings from 2019, average gross monthly earnings in enterprises of different size were different: the highest growth was recorded in enterprises having 500–999 employees – 11.3 per cent, in enterprises having 10–49 employees and in enterprises having 1 thousand and more employees, average gross monthly earnings over the year increased by 9.4 and 9.1 per cent respectively. Over the year, the average gross monthly earnings in enterprises having 50–249 employees and 250–499 employees increased by 8.6 and 7.7 per cent respectively, while the lowest growth was recorded in enterprises having 1–9 employees – 6.6 per cent.
In 2019, average gross monthly earnings in enterprises having 500–999 employees amounted to EUR 1,463.9 and by 37.7 per cent exceeded the earnings in the smallest enterprises (having 1–9 employees). Average gross monthly earnings of employees in the smallest enterprises totalled EUR 912.1 and was by 29.6 per cent lower than the national average; average earnings of employees of the enterprises placed in the second group by the enterprise size remained behind the national level by 5.5 per cent. Average earnings of employees in the remaining four groups exceeded the national level.
Average gross monthly earnings by sector and enterprise size class in the whole economy, 2019
The latest and detailed data are available in the Database of Indicators
Average gross monthly earnings in the public and private sector, 2019
____________________
Accommodation and food service activities in public sector – confidential data.
The latest and detailed data are available in the Database of Indicators
Changes in average gross hourly earnings¹ by economic activity, 2019
Compared to the previous year
____________________
¹ Excluding individual enterprises.
The latest and detailed data are available in the Database of Indicators
Number of hours paid and worked per employee by economic activity, 2019
The latest and detailed data are available in the Database of Indicators
In October 2019 employees working full-time and receiving a minimum monthly wage in the whole economy (individual enterprises included) accounted for 2.6 per cent (26.6 thousand) of the total number of full-time employees: in the public sector – 2 per cent (6.2 thousand), private – 2.8 per cent (20.4 thousand). Against the same period in 2018, the proportion of such employees remained almost the same: in the whole economy increased by 0.1 percentage point, in the public sector – decreased by 0.2 percentage point, private – 0.1. This was influenced by the changes of tax system since 1 January 2019 (changed rates of state social insurance contributions paid by the employer and employee, average gross monthly earnings indexed 1.289 times, etc), revised new pay system for civil servants, the increased minimum monthly wage (MMW) and other reasons.
The largest number of employees working full-time and receiving minimum monthly wage was recorded in enterprises engaged in real estate activities: in October 2019, the share of such employees accounted for 9.6 per cent of total number of full-time employees engaged in this activity, which is by 0.7 percentage points more than a year ago.
In October 2019, in the first quarter employees working full-time in the whole economy earned up to EUR 755, in the second quarter – from EUR 755 to EUR 1,092, in the third quarter – from EUR 1,092 to EUR 1,581.5, last quarter – EUR 1,581.5 and more.
Number of full-time employees¹ in the whole economy by sector and gross earnings size class, October 2019
Full-time employees – 100 per cent
____________________
¹ Compared to the total number of employees in the respective sector.
The latest and detailed data are available in the Database of Indicators
In October 2019, the largest share of employees working full-time and receiving minimum monthly wage was recorded in small (having 1–9 employees) enterprises – 11 per cent of the total number of full-time employees in the small enterprises, or by 0.6 percentage points more than a year ago.
Minimum monthly wage and average gross monthly earnings
From 1 January 2019, the minimum monthly wage, compared to the same period of the previous year, was increased by EUR 30.
Minimum monthly wage and average gross monthly earnings were indexed 1.289 times due to the changed rates of state social insurance contributions paid by the employer and employee.
The latest and detailed data are available in the Database of Indicators
In Lithuania, as of 1 January 2020, minimum monthly wage totalled EUR 607 (as of 1 January 2019, EUR 555) and, against the same period last year, increased by EUR 52. In Latvia, minimum monthly wage remained unchanged and, as of 1 January 2020, amounted to EUR 430, while in Estonia – increased by EUR 44 and totalled EUR 584.
In Luxembourg as well as in Ireland and Netherlands, as of 1 January 2020, minimum monthly wage exceeded minimum monthly wage in Lithuania 3.5 and 2.7 times respectively. The highest minimum monthly wage was in Luxembourg (EUR 2,142), Ireland (EUR 1,656), the Netherlands (EUR 1,654), Belgium (EUR 1,594), Germany (EUR 1,584), France (EUR 1,539), while the lowest – in Bulgaria (EUR 312).
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In 2019, the gender pay gap in the whole economy¹, except for agriculture, forestry and fishing enterprises, stood at 12.4 per cent per cent and, against 2018, decreased by 0.6 percentage points.
____________________
¹ In enterprises with 10 and more employees.
In 2019, the highest gender pay gap was recorded in enterprises engaged in financial and insurance activities – 36.3 per cent, information and communication – 30.2 per cent, human health and social work activities – 26.8 per cent. In enterprises engaged in transportation and storage, as well as construction activities, the women’s average gross hourly earnings exceeded the men’s average gross hourly earnings and therefore the gap was negative and accounted for minus 10.7 and minus 2.9 per cent respectively.
The gender pay gap was influenced by social and economic rather than legal factors – number of men and women in particular economic activity, their occupation, education, age, length of service and other reasons.
Gender pay gap in the whole economy by economic activity, 2019
The latest and detailed data are available in the Database of Indicators
In 2019, the gender pay gap in the whole economy, except for agriculture, forestry and fishing enterprises, as well as public administration and defence; compulsory social security, decreased in all age groups, from 0.8 (in the employees’ age group of 25–34) to 3.3 percentage points (in the employees’ age group over 65 years).
The highest gender pay gap was recorded in the employees’ age group of 35–44 (16.9 per cent), while the lowest – in the employees’ age group of 55–64 (9.5 per cent).
In 2019, the gender pay gap in the whole economy, except for agriculture, forestry and fishing enterprises, as well as public administration and defence; compulsory social security, stood at 13.3 per cent (in the public sector – 14, in the private sector – 14.4 per cent) and, against 2018, decreased by 0.7 percentage point: in the public sector – by 0.1, and in the private sector – by 0.2 percentage points.
Gender pay gap by employees’ age, 2018–2019
The latest and detailed data are available in the Database of Indicators
In 2018, the gender pay gap in the EU stood at 14.8* per cent and, against 2017, decreased by 0.1 percentage point.
In 2018, the lowest gender pay gap was recorded in Romania (3ᵉ per cent), Luxembourg (4.6* per cent) and Italy (5* per cent), while the highest – in Estonia (22.7* per cent) and Germany (20.9* per cent).
Gender pay gap in the EU countries², 2018
____________________
2 Greece – 2014, Ireland and Italy – 2017.
* Provisional data.
e Eurostat's estimate.
Source: Eurostat's database
Minimum monthly wage in the EU countries, 1 January 2020
Source: Eurostat's database
Composition of gross remuneration by sector, 2019
EUR, thousand
The latest and detailed data are available in the Database of Indicators
Photo from Pixabay.com
The latest and detailed data are available in the Database of Indicators
In 2019, labour costs per hour worked in industrial, construction and service enterprises totalled EUR 9.12 and, against 2018, increased by 5.1 per cent. The increase in labour costs per hour worked was recorded in all enterprises, except the enterprises engaged in construction, transportation and storage, administrative and support service activities. The largest growth was observed in enterprises engaged in human health and social work (12.7 per cent), public administration and defence, compulsory social security (10.2 per cent) activities.
The lowest growth was recorded in enterprises engaged in mining and quarrying (4.8 per cent), wholesale and retail trade, repair of motor vehicles and motorcycles (5.9 per cent).
In Lithuania, gross earnings and remuneration in kind per hour worked in industrial, construction and service enterprises (except public administration and defence; compulsory social security) having 10 and more employees were lower than in other EU member states (except Poland, Hungary, Latvia and Bulgaria) and amounted to EUR 8.8 in 2019. Earnings in Denmark and Luxembourg exceeded those in Lithuania 4 times; in Belgium, the Netherlands, Ireland, Germany, Finland, Austria, Sweden and France – approximately 3 times.
Labour costs per hour actually worked and their structure in the whole economy by economic activity, 2018–2019
NACE Rev. 2 |
Kind of economic activity |
|
Labour costs (hourly), EUR |
Structure of labour costs, per cent |
||||
---|---|---|---|---|---|---|---|---|
Gross wages and salaries in cash and in kind |
Other labour costs |
|||||||
Total |
10 and more employees |
Total |
10 and more employees |
Total |
10 and more employees |
|||
B–S |
Industry, construction and services |
2019 |
9.12 |
9.50 |
94.8 |
94.8 |
5.2 |
5.2 |
2018 |
8.68 |
9.04 |
71.0 |
71.2 |
29.0 |
28.8 |
||
B |
Mining and quarrying |
2019 |
10.31 |
10.60 |
95.6 |
95.6 |
4.4 |
4.4 |
2018 |
9.84 |
10.12 |
73.2 |
73.1 |
26.8 |
26.9 |
||
C |
Manufacturing |
2019 |
9.40 |
9.29 |
96.6 |
96.6 |
3.4 |
3.4 |
2018 |
8.53 |
8.77 |
72.8 |
72.7 |
27.2 |
27.3 |
||
D |
Electricity, gas, steam and air conditioning supply |
2019 |
10.87 |
11.19 |
95.2 |
95.2 |
4.8 |
4.8 |
2018 |
10.09 |
10.39 |
72.1 |
72.1 |
27.9 |
27.9 |
||
E |
Water supply; sewerage, waste management and remediation activities |
2019 |
8.48 |
8.57 |
96.2 |
96.3 |
3.8 |
3.7 |
2018 |
7.79 |
7.88 |
74.0 |
74.0 |
26.0 |
26.0 |
||
F |
Construction |
2019 |
7.91 |
8.42 |
95.2 |
95.3 |
4.8 |
4.7 |
2018 |
8.23 |
8.76 |
67.6 |
68.3 |
32.4 |
31.7 |
||
G |
Wholesale and retail trade; repair of motor vehicles and motorcycle |
2019 |
8.31 |
8.81 |
96.1 |
96.1 |
3.9 |
3.9 |
2018 |
7.85 |
8.32 |
73.2 |
73.3 |
26.8 |
26.7 |
||
H |
Transportation and storage |
2019 |
9.06 |
9.47 |
82.4 |
82.3 |
17.6 |
17.7 |
2018 |
9.77 |
10.21 |
56.5 |
56.2 |
43.5 |
43.8 |
||
I |
Accommodation and food service activities |
2019 |
6.00 |
6.29 |
95.8 |
95.8 |
4.2 |
4.2 |
2018 |
5.49 |
5.76 |
73.6 |
73.5 |
26.4 |
26.5 |
||
J |
Information and communication |
2019 |
15.97 |
17.65 |
95.8 |
95.7 |
4.2 |
4.3 |
2018 |
14.68 |
16.23 |
72.5 |
72.3 |
27.5 |
27.7 |
||
K |
Financial and insurance activities |
2019 |
16.63 |
17.23 |
93.9 |
93.9 |
6.1 |
6.1 |
2018 |
15.52 |
16.08 |
71.4 |
71.3 |
28.6 |
28.7 |
||
L |
Real estate activities |
2019 |
7.70 |
9.01 |
95.9 |
95.9 |
4.1 |
4.1 |
2018 |
7.24 |
8.47 |
73.7 |
73.8 |
26.3 |
26.2 |
||
M |
Professional, scientific and technical activities |
2019 |
11.13 |
13.31 |
96.1 |
96.1 |
3.9 |
3.9 |
2018 |
10.30 |
12.32 |
73.0 |
72.9 |
27.0 |
27.1 |
||
N |
Administrative and support service activities |
2019 |
7.60 |
7.70 |
97.6 |
97.5 |
2.4 |
2.5 |
2018 |
7.70 |
7.81 |
69.7 |
69.4 |
30.3 |
30.6 |
||
O |
Public administration and defence; compulsory social security |
2019 |
11.14 |
11.13 |
95.4 |
95.3 |
4.6 |
4.7 |
2018 |
10.11 |
10.10 |
72.9 |
72.9 |
27.1 |
27.1 |
||
P |
Education |
2019 |
8.65 |
8.72 |
96.4 |
96.4 |
3.6 |
3.6 |
2018 |
7.94 |
8.00 |
74.4 |
74.4 |
25.6 |
25.6 |
||
Q |
Human health and social work activities |
2019 |
9.77 |
9.83 |
96.9 |
96.9 |
3.1 |
3.1 |
2018 |
8.67 |
8.72 |
74.6 |
74.6 |
25.4 |
25.4 |
||
R |
Arts, entertainment and recreation |
2019 |
7.12 |
7.31 |
96.7 |
96.7 |
3.3 |
3.3 |
2018 |
6.52 |
6.70 |
74.3 |
74.3 |
25.7 |
25.7 |
||
S |
Other service activities |
2019 |
6.76 |
7.92 |
97.0 |
96.9 |
3.0 |
3.1 |
2018 |
6.19 |
7.25 |
74.8 |
74.1 |
25.2 |
25.9 |
The latest and detailed data are available in the Database of Indicators
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Low wage trap shows financial losses occurred due to taxes and benefits when the gross earnings of the employee increase from 33 (from average gross earnings for a specific household category) to 67 per cent. Low wage trap characterises such situation when employed persons refuse to work more working hours or a better paid job because additionally earned income is too low. This indicator shows the share of individual income tax and social security contributions payable by an employee in gross earnings when the gross earnings of the employee increase from 33 to 67 per cent of average gross earnings in the business sector of the economy and the employee loses social benefits. In case of high low wage trap indicator, employed persons lose quite a considerable share of earned income after taxes and social benefits, which potentially results in the decrease of motivation to work more working hours or search for a better paid job. In Lithuania, compared to other EU countries, financial losses of single persons are not very big, while in the households consisting of spouses with only one employed adult and with two dependent children, such losses are quite significant.
Low wage trap
The latest and detailed data are available in the Database of Indicators
Low wage trap in the EU countries, 2019
Single person without children, 100% of AW
Source: Eurostat's database
In 2019, in Lithuania, unemployment trap indicator stood at 87.4 per cent and, against 2018, increased by 0.6 percentage points. This indicator shows that an employee, after being unemployed for a long time, “preserves” 12.6 per cent of gross earnings when returns to employment and loses the unemployment social security contribution, social benefit, etc. In 2019, the highest unemployment trap was recorded in Belgium (93.1 per cent), Luxembourg (90.9 per cent), Denmark (88.9 per cent), while the lowest – in Estonia, Greece and Slovakia (32.2, 34.6 and 46.4 per cent). Average of the EU countries stood at 74.1 per cent.
Unemployment trap
The latest and detailed data are available in the Database of Indicators
From the perspective of the value of the unemployment trap in Lithuania in the context of the EU countries, it can be stated that in 2019, in Lithuania, the unemployment trap rate was quite high. Such situation could be determined by the fact that employees in Lithuania have little incentive to move from significantly high unemployment contributions (social assistance) and quite long payment term to a low-paid job.
Unemployment trap in the EU countries, 2019
Source: Eurostat's database
Photo from Unsplash.com
In 2019, the highest tax wedge on labour costs was recorded in Belgium (45.4 per cent), Germany (45.2 per cent), Hungary (44.6 per cent), and the lowest – in Cyprus (18.1 per cent), Ireland (24.6 per cent), the United Kingdom (26.1 per cent). In Lithuania, tax wedge on labour costs over the year decreased by 2.4 percentage points and stood at 34.8 per cent in 2019.
Tax wedge on labour costs in the EU countries, 2019
Source: Eurostat's database
Photo from Pixabay.com
In 2018, monthly earnings of managers amounted to EUR 1,585.6, specialists – EUR 1,187.4, technicians and associate professionals – EUR 898.1. The earnings of managers and professionals (excluding agriculture, forestry and fishing enterprises) exceeded the average gross earnings in the whole economy (EUR 949.8) by 66.9 and 28 per cent respectively. In 2018, the lowest earnings were recorded for elementary occupations – EUR 548.1, service and sales workers – EUR 634.9; gross earnings thereof were by, respectively, 42.3 and 33.2 per cent lower than the average gross earnings in the whole economy.
In 2018, women’s gross earnings were lower than men’s in all major occupational groups. Female managers earned by 8.1 per cent less than male managers, female professionals – by 22.7 per cent less than males of the same occupational group. Earnings of female employees of elementary occupations were by 13.2 per cent lower than those of male employees of the same occupational group.
In 2018, employees with higher education received the highest earnings. In 2018, employees with higher education earned EUR 1,229.3 per month, which is by 29.4 per cent more than the average gross monthly earnings in the whole economy, 1.9 times more than those having primary and general lower secondary (EUR 643.9) and 1.8 times more than those having general upper secondary (EUR 696.5) education. Gross earnings of women having higher education were by 21.8 per cent lower than those of men having the same education.
In 2018, employees aged 30–39 earned the most: their average gross monthly earnings (EUR 1,084.1) were by 14.1 per cent higher than the average gross monthly earnings in the whole economy. In 2018, within the 30–39 age group, men earned EUR 1,166.6 (by 14.8 per cent more than all men on average), women – EUR 987.1 (by 11.5 per cent more than all women on average). The employees aged 30–39 with higher education earned by 20.6 per cent more than all employees with higher education on average in the said age group.
In 2018, median of gross earnings was EUR 794.3, or by 16.4 per cent less than average gross monthly earnings in the whole economy (EUR 949.8). According to the major occupational groups, the largest gap was observed in the manager group: difference between the third and first quartile – 2.4 times. Less significant difference was observed for earnings of employees of elementary occupations: the third quartile was only 1.5 times higher than the first quartile.
Average gross monthly earnings in the whole economy by major occupational group, 2018
The latest and detailed data are available in the Database of Indicators
Average gross monthly earnings in the whole economy by age of employees, 2018
The latest and detailed data are available in the Database of Indicators
Average gross monthly earnings in the whole economy by education, 2018
The latest and detailed data are available in the Database of Indicators
Distribution of average gross monthly earnings in the whole economy by major occupational group, 2018
The latest and detailed data are available in the Database of Indicators
The highest earnings were received by managers of enterprises engaged in financial and insurance activities (EUR 3,133.8), mining and quarrying (EUR 2,566) and information and communication (EUR 2,423.9). The highest earnings of professionals were recorded in enterprises engaged in financial and insurance activities (EUR 1,730.2), information and communication (EUR 1,709.7) and manufacturing (EUR 1,343.3).
Average gross monthly earnings in the whole economy by major occupational group and economic activity, 2018
NACE Rev. 2 |
Kind of economic activity |
Total |
Main occupation group¹ |
|||||||
---|---|---|---|---|---|---|---|---|---|---|
1 |
2 |
3 |
4 |
5 |
7 |
8 |
9 |
|||
A–S |
Whole economy, total |
949.8 |
1,585.6 |
1,187.4 |
898.1 |
788.2 |
634.9 |
776.4 |
783.2 |
548.1 |
B |
Mining and quarrying |
1,134.6 |
2,566 |
1,210.6 |
1,052.9 |
730.9 |
• |
1,085.1 |
937.3 |
598.6 |
C |
Manufacturing |
951.5 |
1,725.6 |
1,343.3 |
1,035.8 |
853.2 |
639.4 |
803.6 |
883 |
641.8 |
D |
Electricity, gas, steam and air conditioning supply |
1,160.8 |
1,952.8 |
1,273.6 |
1,103.1 |
824.3 |
507.4 |
840.5 |
872.8 |
517.5 |
E |
Water supply; sewerage; waste management and remediation activities |
921.6 |
1,646 |
1,117.8 |
970.2 |
870.5 |
682.6 |
826.7 |
822.6 |
541.1 |
F |
Construction |
879.6 |
1,401.9 |
1,148.2 |
872.4 |
806 |
(674.5) |
752.2 |
918 |
532.9 |
G |
Wholesale and retail trade; repair of motor vehicles and motorcycles |
850.1 |
1,393.1 |
1,124.8 |
811.6 |
791.1 |
627.6 |
751.1 |
784.5 |
570.7 |
H |
Transportation and storage |
869.2 |
1,490.8 |
1,217.5 |
1,015.8 |
779.2 |
842.4 |
848.6 |
705.8 |
649.1 |
I |
Accommodation and food service activities |
654.5 |
991.8 |
883.2 |
725.4 |
696.9 |
599.2 |
649.7 |
(495.2) |
533.1 |
J |
Information and communication |
1,627.2 |
2,423.9 |
1,709.7 |
940.8 |
886.5 |
741.9 |
(976.0) |
(735.3) |
525.5 |
K |
Financial and insurance activities |
1,682.2 |
3,133.8 |
1,730.2 |
1,109.8 |
850.3 |
(771.0) |
• |
- |
505.7 |
L |
Real estate activities |
858.9 |
1,271.8 |
1,034.9 |
772.2 |
618.3 |
585.3 |
737.5 |
727.5 |
518.5 |
M |
Professional, scientific and technical activities |
1,236.3 |
1,983.3 |
1,245.5 |
822.4 |
813.5 |
549.1 |
575.9 |
816.7 |
572.9 |
N |
Administrative and support service activities |
804.4 |
1,622.1 |
1,218.4 |
(1,145.8) |
867.4 |
596.3 |
735.5 |
843.2 |
548.4 |
O |
Public administration and defence; compulsory social security |
1,123.9 |
1,666.1 |
1,170.2 |
996.1 |
784.6 |
940.8 |
(661.3) |
662.3 |
472.3 |
P |
Education |
865.2 |
1,443.6 |
972.3 |
680.6 |
564.9 |
554.4 |
650.1 |
606.5 |
452.3 |
Q |
Human health and social work activities |
1,020.2 |
1,468.6 |
1,231.1 |
778.3 |
618.5 |
603.3 |
621.7 |
722.7 |
487.3 |
R |
Arts, entertainment and recreation |
787.4 |
1,063.6 |
828.8 |
773 |
745.2 |
655.8 |
641.4 |
613.2 |
470.4 |
S |
Other service activities |
792.9 |
1,264.6 |
1,099.6 |
673 |
709.5 |
544.2 |
674.9 |
553.0 |
518.7 |
The latest and detailed data are available in the Database of Indicators
¹ Major groups of occupations are provided by the Lithuanian Classification of Occupations (LPK 2012), which is based on the International Standard Classification of Occupations ISCO-08.
- category not applicable.
( ) insufficient accuracy of statistical estimate.
• confidential data.
Major groups of occupations
1. Managers
2. Professionals
3. Technicians and associate professionals
4. Clerical support workers
5. Service and sales workers
7. Craft and related trades workers
8. Plant and machine operators, and assemblers
9. Elementary occupations
More:
Average monthly earnings by sector and economic activity
Indices of average monthly earnings by sector and economic activity
Average gross monthly earnings in the whole economy by enterprise size class and economic activity
Number of full-time employees by gross earnings size class and economic activity, October
Labour costs per hour actually worked and their structure in the whole economy by economic activity
Kind of economic activity
A | Agriculture, forestry and fishing |
B | Mining and quarrying |
C | Manufacturing |
D | Electricity, gas, steam and air conditioning supply |
E | Water supply; sewerage; waste management and remediation activities |
F | Construction |
G | Wholesale and retail trade; repair of motor vehicles and motorcycles |
H | Transportation and storage |
I | Accommodation and food service activities |
J | Information and communication |
K | Financial and insurance activities |
L | Real estate activities |
M | Professional, scientific and technical activities |
N | Administrative and support service activities |
O | Public administration and defence; compulsory social security |
P | Education |
Q | Human health and social work activities |
R | Arts, entertainment and recreation |
S | Other service activities |
For further terms, see the Dictionary of Statistical Terms.