MediuM to Long-terM LABOR SUPPLY-DEMAND ForeCASt 2013 12000 10000 8000 6000 4000 2000 0 Billion tugrik 2012 2012 2012 2012 2012 2022 2022 2022 2022 2022 Agriculture Mining and Quarrying Manufacturing Service GDP 807 1272 976 2104 705 1360 3010 5678 5,498.5 10,414.1 HUMAN RESOURCES DEVELOPMENT SERVICE OF KOREA
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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
1
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
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
2
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
MediuM to Long-terM LABOR SUPPLY-DEMAND FORECAST
3
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
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
17
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)
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,