MediuM to Long-terM LABOR SUPPLY-DEMAND
ForeCASt
2013
12000
10000
8000
6000
4000
2000
0
Billio
n tu
grik
2012 2012 2012 2012 20122022 2022 2022 2022 2022
Agriculture Mining and Quarrying Manufacturing Service GDP
8071272
976
2104705
1360 3010
5678
5,498.5
10,414.1
huMAn reSourceS DeveloPMent Service of koreA
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
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We have developed a medium to long-term
labor market forecasting (pilot) model for
Mongolia for the first time. The timing of this
model development coincides with the structural
changes in population and the rapid economic
growth expected in the country which require
changes in labor policies on the labor force
participation rate and labor productivity.
We have forecasted major changes in the labor
market until 2022 in terms of 19 industries and
10 major occupational groups using the model.
One of the major objectives of labor policies is
to promote inclusive growth by developing the
national labor force. It implies to improve the
higher and vocational education system, and
labor productivity in industries.
On the other hand, labor studies provide
school leavers and the current labor force with
information on the choices of occupation and
directions to enhance their skills.
We will be working to promote the forecast
results for policy making and information
purposes. In 2014, we have two objectives to
improve the forecast. First, the forecast will be
based on the sub-classifications of industries
and sub-groups of occupations. As a result,
there will be more detailed information for a
policy making purpose. Second, we will consider
various policy scenarios so that we will be able to
forecast the effects of proposed policy changes
on the labor market outcomes.
During the period in which we publicized
the results of the pilot model, the President
of Mongolia initiated the manifesto on the
principles of a smart government and the
government reported that it would keep a policy
not to increase the number of government
employees. When we introduce these policy
changes in the model, the forecast results would
be quite different as the additional employees
in the government sector forecasted by the pilot
model would have to be allocated across the
other industries.
It is important to maintain the capacity building
taking place in the modelling and forecasting
sector at the Institute of Labour Studies and
develop its cooperation with other advisory
organizations.
I would like to thank the officials at the
Ministry of Labour of Mongolia and Ministry of
Employment and Labor of the Republic of Korea
who supported our work.
Foreword
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I would also like to congratulate to Human
Resources Development Services of Korea
and “Gerege Partners” LLC on their successful
collaborations with us.
I hope that you will find the forecast results
useful for the purposes of policy making and
information providing leading to the efficient
allocation of national human recourses.
CHIMEDDORJ MUNKHJARGAL
Director of Institute for Labour Studies
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Table of ConTenTs
Chapter 1. Medium to Long-term Labor Supply-Demand ForecastIntroduction and Method
1. Significance of labor supply-demand forecasting ............................................................. 5
2. Forecasting procedure and method ................................................................................... 5
3. Statistical data used for forecasting ...................................................................................7
4. Work required to be undertaken further............................................................................7
Chapter 2. Major Results of the 2013-2022 Medium to Long-term Forecast
1. Labor force forecast .......................................................................................................... 9
2. Employment forecast by industries .................................................................................. 16
3. Employment forecast by occupation ................................................................................ 21
4. Unemployment rate forecast ............................................................................................25
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
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Medium to Long-term Labor Supply-Demand ForecastIntroduction and Method
Chapter 1
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ForeCasting proCedure and Method
signiFiCanCe oF Labor suppLy-deMand ForeCasting1
2
Labor supply-demand forecasting acts as a signal
that prevents and alleviates likely imbalances in
the labor market. One type of an imbalance in
the labor market is labor force with a university
degree is unable to find suitable employment
opportunities for an extended period of
time. The main reason for such a situation is
asymmetric employment information between
labor providers and employers. In this case,
the supply-demand forecast acts as a signal
that contributes to the efficient development
and allocation of national human resources. In
general, the forecast performs both a policy
function and an information function. The policy
function: the forecast acts as the main data for
the government policies on employment, industry
and education (human resources development).
The information function: the data provided
by the forecast is used for decision making
on career or occupation selection. Through its
information function, the forecast assists the
labor market entrants to reach rational decisions
which improve the efficiency of the labor
market.
In this respect, a need to develop a labor market
projection system for Mongolia has arisen. The
development of this system has been initiated
by the Institute of Labor Studies of the Ministry
of Labor and the first pilot model of the labor
market and its results are presented in this report.
On the pilot model, two consultancy teams have
participated as well. The national consultant is a
team of economists from Gerege Partners LLC
the main role of which was to carry out the
model simulations. The international consultant
is a team of labor market experts of HRD Korea
advised on the model development.
The medium to long-term forecast consists of
the following two parts:
§ labor supply forecasting (labor force
forecasting)
§ labor demand forecasting (employment
forecasting).
Figure 1-1 shows the sequence of steps to carry
out the medium to long-term forecast. This
is the simplified version of the Korean labor
supply-demand forecasting system.
1 The Korean model is the adaptation of the US Bureau of Labor Statistics model.
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Working age population forecasting GDP by industries
Employment coefficient forecasting (by industries)
Labor force participation rate forecasting
Economically active population forecasting (Labor supply)
Employment forecasting by industries and in aggregate (Labor demand)
Labor supply-demand forecasting “Industry-occupation” matrix forecasting
Figure 1-1. Medium to long-term labor market forecasting system
Based on the population forecast, the labor
supply forecasting initially projects 1) the
working age population (15 and older), 2)
the labor force participation rate, and 3) the
economically active population. In particular, the
working age population and the economically
active population are determined by age (age
strata in five-year increments) and gender
(male, female). The forecast period is 10 years.
The employment forecasting calculates 1) the
employment size in aggregate and by industries
by using projected industry growth rates and
the employment coefficients (the inverse of
labor productivity) by industries. Next, 2)
the employment by industries is converted to
employment by occupations using the forecast
of the industry-occupation matrix. Finally, 3) the
labor force forecast and employment forecast
results are used to calculate the economy’s total
unemployment rate and employment rate. The
employment forecast is disaggregated by 19
industries as well as by 10 major occupational
groups of National Statistical Office (NSO)
of Mongolia. The forecast period for the
employment is 10 years, the same as that for the
labor force forecast.
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statistiCaL data used For ForeCasting
Basic statistical data used for the forecasting
includes the International Monetary Fund
(IMF)’s GDP projections for Mongolia, the NSO’s
population growth projection, the NSO’s labor
force survey and the NSO’s GDP by industries
(for a detailed description, refer to Table 1-1).
The NSO’s population growth projections, in
particular, the Medium Fertility Scenario (2B) is
used for the labor supply forecast. The working
age population is the total number of people
who are aged 15 years of age and over and
is determined by using the NSO’s labor force
survey (LFS). The economically active population
is also derived from the LFS and is the sum of
employed and unemployed population.
The IMF’s GDP projections, the share of each
industry’s GDP in the country’s aggregate GDP in
the NSO’s statistical reports and the data on the
number of employees in each industry in the LFS
reports are used for the employment forecast.
As mentioned above, the pilot model for the
medium to long-term labor supply-demand
forecast of Mongolia has been developed through
this project. From the experience of the Korean
labor market studies, the extension of this model
is possible as well as required. For example, the
employment forecast by sub-industries and sub-
occupational groups will generate more detailed
information. Also, by determining labor supply
by each occupational group and forecasting
the labor market for each occupational group,
the entrants in the labor market and school
leavers will have an opportunity to choose their
occupations rationally.
3
4 work required to be undertaken Further
Table 1-1. Statistical data used for the forecasting
Indicators Source Prepared by CommentPopulation projection Renewed population growth
projection /2010-2040/NSO by age and gender
Working age population Labor force survey NSO by age and gender
Economically active population Labor force survey NSO by age and gender
GDP by industries National income NSO by main industries
GDP projections IMF in total
Employment by industries Labor force survey NSO by main industries
Employment by occupations Labor force survey NSO ҮАМАТ-08 /ISCO-08/
by major groups
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Major Results of the 2013-2022Medium to Long-term Forecast
Chapter 2
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We forecast the labor force (or the economically
active population) of Mongolia until 2022 by
using the historical data on the economically
active population and the working age (15 and
older) population and labor force participation
rates.
A. Working age population forecast
The annual “labor force survey” (LFS) reports
the actual working age population who are 15
years of age and older. However LFS does not
forecast the working age population. To forecast
the working age population, we use the NSO’s
population growth projection 2010-2040. The
projection is based on “Population and Housing
Census - 2010” and has six scenarios for each
age group because of different projections of
fertility rate, mortality rate and net migration.
The projected 15 and older population until 2022
from the Medium Fertility Scenario or 2B – the
most suitable scenario of the population growth
projections - has been used in this study. The
projected 15 and older population from the NSO’s
projected population growth could not be taken
and used straight away due to methodological
difference of the LFS - the size of the working
age population in the LFS tends to be smaller
than the population of 15 and older reported
in the statistical yearbooks. Therefore, it was
required to adjust the forecast of the 15 and
older population until 2022 by forecasting this
difference.
1 Labor ForCe ForeCast
Population Trend and Projection
(by age, 15 and older)
Participation Rate Projection
Economically Active Population (Labor Force)
Projection
The labor force (or labor supply) forecast has been carried out in accordance with the following
three steps.
Figure 2-1. Process for aggregate labor supply forecast
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Figure 2-2. Projected 15+ population (by gender, age groups, 1000 people, 2000-2022)
65+
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
65+
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
65+
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
65+
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
Male Male
Male Male
Female Female
Female Female
150 50 50 150
150 50 50 150 150 50 50 150
150 50 50 150
* Source: “Annual Population Employment Reports” submitted by aimags and UB offices of NSO.** Source: NSO’s labor force survey *** Projections
2000*
2017*** 2022***
2012**
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The age group of 30-54 years, which has the
highest employment rate, is forecasted to
increase by 2.3 percent in the first half and by
2.2 in the second half of the projected period.
This group will be expanded by 21,900 people
annually in the period of 2012-2022.
Table 2-1 shows that the 15-64 population will
have a roughly constant share of 93-94 percent
in the total population in 2007-2022. The share
of young people of 15-29 years of age in the
total population has been declining constantly
in the last ten years and this trend is likely to
continue until 2022.
Table 2-2 shows the 15 and older population by
gender. It is evident that the share of women
is much higher compared to men and this
trend is likely to continue in the next ten years.
Approximately 48 percent of the population of
this age group is men and 52 percent is women.
In the first five years, it is estimated that the
number of men will increase by 2.1 percent but
decline to 1.4 percent annually in the last five
years of the projected period. In contrast, the
increase in numbers of women will be relatively
steady around 1.6 percent.
Table 2-1. Projected 15+ population (by age groups, 2002-2022) (unit: 1000 people, %)
Total15-29 30-54 55+
15+ 15-64
Population(1000)
2007 1632 1529 664 758 2102012 1812 1700 670 881 2612017 1982 1872 693 989 3012022 2139 1993 642 1100 397
(%) 2007 100.0 93.7 40.7 46.4 12.92012 100.0 93.8 36.9 48.6 14.42017 100.0 94.5 35.0 49.9 15.22022 100.0 93.2 30.0 51.4 18.5
Growth/Decline(1000)
‘07-’12 180 171 6 123 52‘12-’17 169 173 23 108 39‘17-’22 157 121 -51 111 96
Annual average growth rate (%)
‘07-’12 2.1 2.1 0.2 3.1 4.5‘12-’17 1.8 2.0 0.7 2.3 2.8‘17-’22 1.5 1.3 -1.5 2.2 5.7
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B. Labor force participation rate forecast
The labor force participation rate is determined
by the ratio of the economically active population
to the working age (15 and older) population.
Based on the data of labor force participation
rate for 2006 to 2012, we forecast the labor
force participation rate by gender and age
groups until 2022 (Table 2-3).
From Table 2-3, one can see that the general
labor force participation rate which was 63.5
percent in 2012 will increase slightly to 63.7
percent in 2017 and will decline to 62.5 percent
in 2022. With respect to age groups, the labor
force participation rate has the biggest decline in
the age group of 15-29 which may be linked to
the desire to attain education. The participation
rate is the highest in the age group of 30-49
– over 80 percent. However, disaggregation
by gender shows that men’s participation rate
is the highest between 25-49 years of age
while for women it occurs later between 30-
49 years of age. Men’s labor force participation
rate will increase by 1.4 percent until 2017 and
thereafter it will decline. Meanwhile women’s
labor participation rate will decline between 15-
44 years of age. However, with the family life
becoming relatively stable between the ages of
45-54, women’s labor force participation rate
will increase.
Table 2-2. Projected 15+ population (by gender, 2002-2022) (unit: 1000 people, %)
Total Male FemalePopulation(1000)
2007 1632 786 8462012 1812 870 9422017 1983 965 10182022 2139 1036 1103
(%) 2007 100.0 48.2 51.82012 100.0 48.0 52.02017 100.0 48.7 51.32022 100.0 48.4 51.6
Growth/Decline(1000)
‘07-’12 180 84 96‘12-’17 170 95 75‘17-’22 156 71 86
Annual average growth rate (%)
‘07-’12 2.1 2.1 2.2‘12-’17 1.8 2.1 1.6‘17-’22 1.5 1.4 1.6
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Table 2-3. Labor force participation rate forecast (by gender, age groups, 2000-2022)
Participation rate (%) Change
2000* 2012 2017p 2022p 2012-
2017p2017p-2022p
2012-2022p
Total
Total 62.9 63.5 63.7 62.5 0.1 -1.1 -1.0
15~19 44.9 27.9 21.2 22.2 -6.7 1.0 -5.7
20~24 58.4 53.7 50.9 49.9 -2.9 -1.0 -3.9
25~29 65.6 77.3 75.8 75.2 -1.5 -0.6 -2.1
30~34 70.4 81.4 80.7 80.2 -0.7 -0.6 -1.3
35~39 67.7 85.4 85.4 85.5 0.0 0.1 0.2
40~44 68.8 86.0 86.0 85.8 0.0 -0.2 -0.2
45~49 64.6 82.1 83.1 83.4 1.0 0.2 1.3
50~54 59.0 71.4 73.4 74.3 2.0 0.9 2.9
55~59 76.9 49.2 49.4 49.2 0.1 -0.2 0.0
60~64 25.7 25.8 24.7 0.1 -1.1 -1.0
65+ 15.1 12.5 12.1 -2.6 -0.4 -3.0
Male
Total 64.8 69.0 70.5 69.6 1.4 -0.9 0.5
15~19 47.6 30.7 25.0 26.6 -5.7 1.5 -4.2
20~24 61.6 60.4 58.9 58.2 -1.5 -0.7 -2.2
25~29 67.3 86.3 84.9 84.6 -1.4 -0.2 -1.7
30~34 73.1 88.4 88.3 88.1 -0.1 -0.1 -0.2
35~39 69.7 89.9 90.0 90.1 0.0 0.1 0.1
40~44 69.3 87.6 88.5 88.1 0.9 -0.4 0.5
45~49 62.5 83.7 85.8 86.1 2.1 0.2 2.4
50~54 61.7 77.3 78.9 79.2 1.5 0.3 1.9
55~59 62.3 62.7 63.0 62.3 0.3 -0.7 -0.4
60~64 33.7 33.0 32.0 -0.7 -1.0 -1.7
65+ 18.9 17.7 17.4 -1.1 -0.3 -1.5
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C. Economically active population forecast
The forecasts of the 15 and older population and
labor force participation rate are used for the
estimation of the economically active population
forecast by age group and gender (Table 2-4),
which determines the total labor supply.
Table 2-4 shows that while the economically
active population was 1,151 thousand in 2012 it
will increase by 186 thousand people reaching
1,337 thousand in 2022. By gender, the number
of men is higher than women and this trend is
likely to continue in the next 10 years. In the
last five years the annual average growth rate
of the male labor force was 3.2 percent, this
number is forecasted to decline to 2.5 percent in
the first half of the projected period and drop
further to 1.2 percent in the second half of the
projected period. This latter reduction is asso-
ciated with both the reduction of men’s labor
force participation rate in the final five years of
the projected period (2018-2022) and the steep
decline in the number of men of 15 years of age
and over in the same period. Women’s annual
average growth rate is relatively stable around
1.1-1.2 percent over the projected period.
Female
Total 61.0 58.4 57.2 55.9 -1.2 -1.3 -2.5
15~19 42.3 25.0 17.3 17.8 -7.8 0.5 -7.3
20~24 55.4 46.7 42.7 41.3 -4.0 -1.4 -5.4
25~29 63.9 68.8 66.7 65.7 -2.1 -1.0 -3.1
30~34 67.8 74.9 73.2 72.2 -1.6 -1.0 -2.7
35~39 65.8 81.4 80.9 81.1 -0.5 0.2 -0.3
40~44 68.2 84.5 83.6 83.6 -0.9 -0.1 -1.0
45~49 66.7 80.6 80.6 80.8 0.0 0.2 0.2
50~54 56.6 66.5 68.5 69.9 2.0 1.4 3.5
55~59 38.5 37.6 37.9 -0.9 0.2 -0.6
60~64 18.8 20.0 18.9 1.2 -1.1 0.1
65+ 12.2 9.0 8.7 -3.2 -0.3 -3.5
* Source: Annual population employment report (NSO)
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Table 2-4. Economically active population forecast (by gender, 1000 people, 2002-2022)
Total Male FemaleEconomically active population (1000)
2002* 901 454 4472007 991 514 4772012 1151 601 5512017 1262 680 5822022 1337 720 617
(%) 2002 100.0 50.4 49.62007 100.0 51.9 48.12012 100.0 52.2 47.82017 100.0 53.9 46.12022 100.0 53.9 46.1
Growth/Decline (1000)
‘03-’07 89 59 30‘08-’12 161 87 74‘13-’17 111 80 31‘18-’22 75 40 35
Annual average growth rate
‘03-’07 1.9 2.5 1.3‘08-’12 3.0 3.2 2.9‘13-’17 1.9 2.5 1.1‘18-’22 1.2 1.2 1.2
* Annual Population Employment Report (NSO)
Table 2-5. Economically active population (by age, 1000 people, 2007-2022)
Total (15 and older)15-29 30-54 55 and over
15+ 15-64Economi-cally active population (1000)
2007 990 974 317 614 592012 1151 1134 354 721 762017 1262 1248 359 813 902022 1337 1320 318 905 114
(%) 2007 100.0 98.3 32.0 62.0 6.02012 100.0 98.5 30.7 62.6 6.62017 100.0 98.9 28.4 64.4 7.22022 100.0 98.7 23.8 67.7 8.5
Growth/ Decline (1000)
‘07-’12 161 160 37 107 17‘12-’17 111 114 5 92 14‘17-’22 75 71 -41 92 24
Annual average growth rate
‘07-’12 3.0 3.1 2.2 3.3 5.2‘12-’17 1.9 1.9 0.3 2.4 3.5‘17-’22 1.2 1.1 -2.4 2.2 4.7
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In order to forecast the labor demand, we project
the value added of each of 19 industries of the
Mongolian economy as well as the employment
coefficient (the inverse of labor productivity) of
each industry.
A. Industry value added forecast
In Mongolia, there is no medium to long-term
forecast for GDP by industries. The reason could
be that it depends on many factors and putting
them together requires complicated techniques.
In this study, we simply extrapolate the observed
share of each industry’s value added in the
aggregate GDP by using data for 2000 to 2012.
Next, we adjust IMF’s projection for Mongolian
GDP*2.
2 According to the IMF, the unemployment rate in Mongolia would decrease continuously and reach 3 percent by 2018 (source: World Economic Outlook (October 2013)). We think that it is debatable to consider it as the long-term (natural) rate of unemployment. Instead, we assume that the natural rate of unemployment is about 6 percent.
The economically active population forecast
by age groups is shown in the Table 2-5. The
population aged 15-29 was 354 thousand in 2012
and is forecasted to increase to 359 thousand
in 2017 but decline to 318 thousand in 2022.
While in the first half of the projected period
the annual average growth rate of this age
group is 0.3 percent, in the second half it will
have a sharp decline and drop to -2.4 percent.
However, the population aged 30-54, which
forms the significant portion of the economically
active population, is forecasted to grow but with
a diminishing rate. The annual average growth
rate of the population aged 55 and over, that
has the smallest share in the economically active
population, is likely to increase.
2* To forecast GDP by industries, we first used IMF’s projections of Mongolian GDP until 2018 carried out in October 2012. However, we found that with these projections, the unem-ployment rate is likely to be lower than its as-sumed long-term (natural) rate of 6 percent. Other things being equal (such as the trend of foreign labor import), it means overheating in the labor market hence could have an adverse impact on the growth rate by increasing the wage rate to adjust to the long-term equilibri-um. For this reason, we revise down the IMF’s GDP projections in our forecasting.
eMpLoyMent ForeCast by industries
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
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We forecast that real GDP growth 7.1 percent
until 2017 and 6.6 percent for 2018 to 20223. In
the next five years, industries will experience the
highest growth rates are mining and quarrying
(I2), transportation and storage (I8), information
and communication (I10). In the final five years,
however, the growth rate of these industries
tend to decline (see Table 2-6).
3 According to the IMF’s projections, the average GDP growth is 8.5 percent until 2017 and 7.7 percent for 2018 to 2022.
Table 2-6. Real GDP by industries (million MNT, at 2005 constant prices)
Industries* 2007 2012 2017p 2022p
Growth (%)
2007-2012
2012- 2017p
2017p- 2022p
2012- 2022p
I1 732,275 807,208 947,449 1,170,091 2.0 3.3 4.3 3.8
I2 691,862 976,400 1,579,082 2,127,438 7.1 10.1 6.1 8.1
I3 328,067 383,449 637,422 846,806 3.2 10.7 5.8 8.2
I4 84,994 104,469 141,928 172,519 4.2 6.3 4.0 5.1
I5 18,459 22,676 32,969 42,854 4.2 7.8 5.4 6.6
I6 118,078 194,570 226,370 312,802 0.5 3.1 6.7 4.9
I7 534,378 1,199,157 1,504,011 2,109,736 17.5 4.6 7.0 5.8
I8 361,745 576,071 941,601 1,333,769 9.8 10.3 7.2 8.8
I9 28,998 64,930 69,752 96,008 17.5 1.4 6.6 4.0
I10 149,735 240,099 394,010 556,910 9.9 10.4 7.2 8.8
I11 128,635 280,834 347,503 491,645 16.9 4.4 7.2 5.8
I12 167,681 222,886 331,329 423,442 5.9 8.3 5.0 6.6
I13 18,470 63,400 76,357 110,696 28.0 3.8 7.7 5.7
I14 43,622 100,195 145,685 209,313 18.1 7.8 7.5 7.6
I15 69,847 75,198 107,878 127,897 1.5 7.5 3.5 5.5
I16 89,203 101,097 111,978 106,312 2.5 2.1 -1.0 0.5
I17 45,480 45,265 74,587 92,952 -0.1 10.5 4.5 7.5
I18 9,896 13,447 20,910 28,495 6.3 9.2 6.4 7.8
I19 18,561 27,130 40,121 54,397 7.9 8.1 6.3 7.2
Total 3,639,988 5,498,482 7,730,943 10,414,084 8.6 7.1 6.1 6.6
* see Annex for the meaning of the abbreviations.
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
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B. Employment coefficient forecast
The employment coefficient is an indicator
measuring the required employment or the
number of workers to produce value added
worth 1 million MNT. In other words, this is the
inverse of labor productivity. Data on the value
added and employment of all 19 industries of the
economy for 2000 to 2012 are used to forecast
this coefficient at an industry level.
C. Employment forecast by industries
The total number of employees was 1.05 million
in 2012 and it is forecasted to increase to 1.18
million in 2017 and further by 205,446 to 1.26
million in 2022. The annual average growth rate
of employment is forecasted to be 2.3 percent
in 2012-2017 but decline to 1.3 percent in 2017-
2022. In the entire projected period (2012-
2022), the total employment tends to increase
on average by 1.8 percent or 20,545 employees
annually.
The forecast indicates that employment in the
Agriculture, Forestry and Fishing Sector (I1)
will decline by 51,706 employees by 2022. The
employment in the Construction Sector (I6)
is likely to increase with a relatively constant
annual average growth rate of 6 percent. The
Arts, Entertainment and Recreation Sector (I18)
has the highest annual growth rate of 12.3
percent in the first five years. Compared to this,
the employment in the Other Services Activities
Sector (I19) will have a slight annual growth in
the next 2 years but decline on average by 3.1
percent annually until 2022.
The employment in sectors such as Mining and
Quarrying (I2), Water Supply, Sewerage, Waste
Management and Remediation Activities (I5),
Professional, Scientific and Technical Activities
(I13), Public Administration and Defence,
Compulsory Social Security (I15), Human Health
and Social Work Activities (I17) are projected to
have a relatively high annual average growth rate
of 5-8 percent by 2022. Figure 2-3 compared
the weight of each sector’s employment in total
employment in 2012 and 2022.
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
19
Table 2-7. Employment forecast by industries (persons, 2012-2022, %)
Sectors 2012 2017p 2022p
Change Growth (%)
2012- 2017p
2017p- 2022p
2012- 2022p
2012- 2017p
2017p- 2022p
2012- 2022p
I1 369,960 330,890 318,254 -39,070 -12,636 -51,706 -2.2 -0.8 -1.5
I2 46,696 71,848 91,480 25,152 19,632 44,784 9.0 4.9 7.0
I3 64,897 81,600 88,754 16,703 7,154 23,857 4.7 1.7 3.2
I4 14,497 15,546 16,265 1,050 719 1,768 1.4 0.9 1.2
I5 6,681 9,891 12,856 3,210 2,965 6,175 8.2 5.4 6.8
I6 59,204 79,230 109,481 20,025 30,251 50,276 6.0 6.7 6.3
I7 131,340 147,710 128,148 16,370 -19,562 -3,192 2.4 -2.8 -0.2
I8 56,091 65,704 65,585 9,613 -119 9,494 3.2 0.0 1.6
I9 30,235 31,986 38,341 1,751 6,355 8,106 1.1 3.7 2.4
I10 14,740 19,262 23,433 4,522 4,171 8,693 5.5 4.0 4.7
I11 17,376 21,832 22,882 4,456 1,050 5,506 4.7 0.9 2.8
I12 1,208 1,301 1,659 93 358 451 1.5 5.0 3.2
I13 11,341 17,036 24,734 5,695 7,698 13,393 8.5 7.7 8.1
I14 13,334 14,483 11,772 1,150 -2,711 -1,562 1.7 -4.1 -1.2
I15* 62,919 89,184 108,962 26,265 19,779 46,043 7.2 4.1 5.6
I16 86,269 95,865 94,793 9,596 -1,072 8,524 2.1 -0.2 0.9
I17 37,529 59,184 73,829 21,655 14,645 36,300 9.5 4.5 7.0
I18 7,357 13,123 16,181 5,766 3,058 8,824 12.3 4.3 8.2
I19 19,783 18,507 14,477 -1,276 -4,030 -5,306 -1.3 -4.8 -3.1
Total 1,051,4571 1,184,181 1,261,886 127,740 77,705 205,446 2.3 1.3 1.8
* I15 represents “Public administration and defence; compulsory social security”. The increase projected in the number of employees in this industry reflects the historical pattern only in a sense that it does not reflect policies that the government intends to implement such as the “From the bureaucratic government to a smart govern-ment” manifesto.
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
20
It can be seen that 35 percent of employees of
15 and older were employed by the Agriculture,
Forestry and Fisheries (I1) in 2012 tends to de-
cline to 25.2 percent by 2022. Also the employ-
ment share in the sectors such as Wholesale and
Retail Trade, Repair Motor Vehicle and Motor-
cycles (I7), Administrative and Support Service
Activities (I14), Education (I16) and Other Service
Activities (I19) is likely to lower in 2022 com-
pared to 2012. In contrast, the shares of other
sectors are likely to increase.
Figure 2-3. Observed and forecasted employment by industries (%)
Other service activities
Arts, entertainment and rec
Human health and social work activities
Education
Public administration and defence;..
Administrative and support service activitie
Professional, scientific and technical activities
Real estate activities
Financial and insurance
Information, communication
Accommodation and food service activitie
Transportation and storage
Wholesale and retail trade, repair of motor..
Construction
Water supply, sewerage, waste..
Electricity, gas, steam and air conditioning..
Manufacturing
Mining and quarring
Agriculture, Forestry, Fishing and Hunting
0 10 20 30 40
2022p
2012*
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
21
eMpLoyMent ForeCast by oCCupation
In Mongolia, ISCO-08 occupational classification
groups are used and we carry out the
employment forecast for 2013 to 2022 for
each of the ten major groups (1-digit). In doing
so, we use the “industry-occupation” matrices
for 2007 to 2012. This matrix divides the total
employment size in a given year into industries
and occupational groups. For each industry,
by extrapolating the observed share of the
employment in each occupational group in the
total industry employment, we forecast the
“industry-occupation” matrix for 2013 to 2022
(see Tables 2-9, 2-10). Summing up across the
industries, we derive the total (economy-wide)
employment size in each occupational group
(Table 2-8).
For the period of 2012-2022, the fastest growing
occupations are М1 (manager), М3 (technicians
and associated professionals), М7 (craft and
related trades workers) and М9 (elementary
occupation)4. The average growth of the
employment in these occupations is over 4
percent. On the other hand, the demand for M6
(skilled agriculture, forestry, and fishery workers)
3
Table 2-8. Employment forecast by 10 major occupational groups (number, %)
Major occupational groups 2007-08* 2012* 2017p 2022p
Growth (%)
2012-2017p
2017p-2022p
2012-2022p
M1 41,646 58,429 76,423 87,788 5.5 2.8 4.2
M2 114,433 161,560 196,699 227,045 4.0 2.9 3.5
M3 44,044 37,069 52,135 57,916 7.1 2.1 4.6
M4 16,840 27,064 30,022 34,177 2.1 2.6 2.4
M5 110,567 162,105 177,769 173,289 1.9 -0.5 0.7
M6 363,511 362,750 319,927 306,790 -2.5 -0.8 -1.7
M7 90,479 93,241 127,043 145,660 6.4 2.8 4.6
M8 70,029 78,240 101,578 110,298 5.4 1.7 3.5
M9 48,254 70,734 96,987 112,027 6.5 2.9 4.7
M10 5,250 5,600 6,897 1.3 4.3 2.8
Total 899,802 1,056,441 1,184,181 1,261,886 2.3 1.3 1.8
* NSO’s labor force survey /only domestic workers/p Projected results /the sum of domestic and foreign workers/
4 М2 is for professionals, М4 is for clerical support workers, М5 is for service and sales workers, М8 is for plant and machine operators and assemblers.
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
22
Figure 2-4. Observed and projected employment by 10 major occupational groups (%)
Below we show the projected “industry-occupation” matrices as of 2017 and 2022.
2022p 2012*
M10
M9
M8
M7
M6
M5
M4
M3
M2
M1
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0
tends to decrease. The decrease in M6 tends to
contribute to the increase in employment in the
most occupational groups.
The following figure compares the observed
share of the employment in each occupational
group in the total employment in 2012 with its
projected in 2022. In 2012, М6 (skilled agriculture,
forestry, and fishery workers) accounted for
34.3 percent of the total employment while in
2022, it tends to account for 24.3 percent. The
share of М10 (armed force occupation) tends
to remain roughly the same around 0.5 percent.
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
23
Tabl
e 2-
9. “
Indu
stry
-occ
upat
ion”
mat
rix (
num
ber, 2
017)
IndustriesO
ccup
atio
nal g
roup
s
M
1M
2M
3M
4M
5M
6M
7M
8M
9M
10To
tal
I117
9113
8298
024
717
2631
7120
2177
2303
3165
33
0890
I257
3795
5328
7017
3339
6311
885
1921
333
1802
271
848
I379
8581
5917
2814
3648
2156
844
155
5906
6844
8160
0
I482
044
6712
4850
125
40
4385
1813
2058
1554
6
I540
576
261
855
475
60
2021
1337
3437
9891
I664
0012
032
2615
1617
2135
216
4188
441
6981
6279
230
I794
7872
8034
3325
3510
2563
435
1019
131
2786
6714
7710
I817
4326
6813
7233
0731
3710
719
8847
387
3995
6570
4
I969
0786
545
010
3617
587
8730
559
141
5831
986
I10
3887
8756
2282
1501
930
090
431
468
819
262
I11
3151
7731
2328
5238
1208
020
510
0896
421
832
I12
532
443
326
--
--
--
1301
I13
1102
9875
3848
231
460
168
211
334
807
1703
6
I14
2906
2156
610
739
3875
159
995
880
2164
1448
3
I15
1569
024
102
1170
149
8010
073
386
1478
6949
8313
5511
8918
4
I16
3783
5817
633
3727
3592
3020
815
6814
3015
309
8895
865
I17
1140
3140
410
228
910
5945
146
1497
2290
5624
5918
4
I18
1580
5093
712
313
1477
121
764
232
2831
1312
3
I19
1386
1797
1450
409
7630
8837
9517
417
7818
507
To
tal
7642
319
6699
5213
530
022
1777
6931
9927
1270
4310
1578
9698
756
00
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
24
Tabl
e 2-
10. “
Indu
stry
-occ
upat
ion”
mat
rix (
num
ber, 2
022)
IndustriesO
ccupat
ional
gro
ups
M
1M
2M
3M
4M
5M
6M
7M
8M
9M
10To
tal
I119
3215
04
1052
258
1808
3038
69
2279
2382
3170
31
825
4
I274
5011
659
3603
2324
4940
102
1014
827
953
2330
191
480
I3874
09425
1926
1692
5647
494
470
44
625
175
348875
4
I4875
5059
1228
454
211
0435
215
7025
1716
265
I550
8963
875
808
1032
027
84
1694
419
212
856
I6920
917
428
3637
2494
2996
281
57622
5030
1078
310
9481
I777
39659
628
85
2243
9051
937
9820
327
146868
12814
8
I817
88
2678
1340
3569
3030
110
1913
472
3639
2065
585
I98959
998
598
1294
2029
310
418
274
251
7038
341
I10
5112
1129
426
2116
2611
510
847
89
693
23433
I11
3351
7567
2271
6047
1235
021
711
7210
2222
882
I12
668
545
447
--
--
--
1659
I13
1393
14486
5810
239
688
249
150
445
1273
2473
4
I14
2422
1603
489
682
3023
128
860
748
1816
1177
2
I15
19636
30494
12886
616
511
414
477
1670
850
710
903
6809
10896
2
I16
3728
57459
2156
2699
9638
209
1583
1003
1623
187
9479
3
I17
1201
3978
412
041
1055
7465
183
2015
2557
7528
73829
I18
2033
611
3861
190
1921
145
901
163
3853
1618
1
I19
1045
1389
1191
337
627
659
2889
40
1250
14477
To
tal
877
88
2270
45
5791
634
177
1732
89
3067
9014
5660
1102
9811
2027
6897
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
25
uneMpLoyMent rate ForeCast
We derive the unemployment rate forecast by
using the labor force (labor supply) forecast and
the employment (labor demand) forecast.
In 2012, the unemployment rate was 8.2
percent and we assume that the long-term
unemployment rate is around 6 percent (± 0.5
percentage points) to derive the results in the
forecasting model. In other words, we assume
that the natural (or structural, NAIRU) rate of
unemployment is about 6 percent. We revise
down the growth of GDP projected by IMF and
derive the labor demand such that the economy
will experience the natural rate of unemployment
in the long-term.
4
Table 2-11. Unemployment rate forecast (number, %, 2012-2022)
Labor demand Labor supply Unemployment rate (%)
2012* 1,056,441 1,151,146 8.2
2013 1,110,160 1,180,712 6.0
2014 1,137,663 1,203,672 5.5
2015 1,150,724 1,224,913 6.1
2016 1,168,275 1,244,381 6.1
2017 1,184,181 1,262,139 6.2
2018 1,198,089 1,278,435 6.3
2019 1,211,819 1,293,652 6.3
2020 1,229,756 1,308,260 6.0
2021 1,244,758 1,322,684 5.9
2022 1,261,886 1,337,189 5.6
* Source: NSO’s labor force survey
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
26
annex: abbreviated words
I1
I2
I3
I4
I5
I6
I7
I8
I9
I10
I11
I12
I13
I14
I15
I16
I17
I18
I19
М1
М2
М3
М4
М5
М6
М7
М8
М9
М10
Agriculture, Forestry, Fishing and Hunting
Mining and quarrying
Manufacturing
Electricity, gas, steam and air conditioning supply
Water supply, sewerage, waste management and remediation activities
Construction
Wholesale and retail trade, repair of motor vehicles and motorcycles
Transportation and storage
Accommodation and food service activitie
Information, communication
Financial and insurance activities
Real estate activities
Professional, scientific and technical activities
Administrative and support service activities
Public administration and defence; compulsory social security
Education
Human health and social work activities
Arts, entertainment and recreation
Other service activities
Manager
Professionals
Technicians and associate professionals
Clerical support workers
Service and sales workers
Skilled agriculture, forestry and fishery workers
Craft and related trades workers
Plant and machine operators and assemblers
Elementary occupation
Armed forces occupation