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Modeling of the multiplicative effects of opening of the work places on the bases of “Intersectoral labor balance” (on example of Azerbaijan and Kazakhstan)
Yadulla HASANLI1, Saylau BAYZAKOV2 , Vilayat VALIYEV3,
Gulbara SARSEMBAEVA4
Abstract.
In the article on an example of Azerbaijan and of Kazaxstan on the basis of the «input - output» balance table in cost expression there are analysed an end-product, a surplus value and a number of their relevant members. The general production and structure of value added was comparatively analyzed for Azerbaijan and Kazakhstan and the conditions for balanced development were given for resource-rich countries. The interdisciplinary balance of a manpower is compounded, the applicable model is realised and simulations are effected. On the basis of the analysis of the received results recommendations are made. Calculations revealed that either in Azerbaijan or Kazakhstan, oil sector holds major part in job creation, but agriculture only negligible part. In general, in the fields where direct and full labor capacity coefficients per unit of last production growth are smaller, it creates less vacancies, where they are bigger, it creates more vacancies.Key words: Input – output table, intersectorial labor balance, direct labor capacity, oil sector, non-oil sector, value-added norm, profit norm, balanced development.
1. Introduction
Balance of labor market is one of the most important elements for creation of macroeconomic balance. It is evident that the employment issue becomes the vital one either while the period of financial crisis or economic crisis. To control unemployment at the market relations condition is the main task of the government [1, p.94].
The structure of economy is widely used in macroeconomic research and “Input - Output” tables (schedules) in intersectorial research and models worked out on the basis of these schedules. The method of “Input - Output” services for 2 purposes: statistic and analytic. They ensure the detailed analysis of production process and allow investigate the use of goods and services and whether the income obtained from it coincide to each other. As a rule, the persons who are busy with working out the economic policy are interested in changes occurred in any sector of economy how shall create changes in other sectors. As well as they want to know the importance of every sector of the economy in the provision of employment of the country economy. Therefore, the reciprocal relation of sectors occurs in two directions, as usual: direct and indirect. For instance, the change of total issue in any sector of the economy (product reserve) is reason for change of employment in the very sector directly. The change of the capacity of product in this field changes the product capacities or final product of other sectors indirectly that it causes for the change of employment in all sectors. This study deals with the modeling and comparative of multiplicative analysis of total issue capacity of change of final products of sectors in the example of Azerbaijani and Kazakhstan economies, the influence of total issue capacity to employment – opening to new working places.
2. Literature review
1Scientfic Advisor of Institute for Scientific Research on Economic Reforms of Ministry of Economic Development of the Republic of
Azerbaijan (IER), [email protected], [email protected], [email protected])2 Scientfic Advisor of Economic Research Institute of Ministry of Economic Development and Trade of the Republic of Kazakhstan (ERI), [email protected] 3Director of IER, [email protected], [email protected] ERI,[email protected]
1
Advantages of the balance models or “input-output” tables are their ability to express the inter-dependence among the different sectors of the economic system. This is not a new concept. The history of inter-dependence principles is too long. This concept is found in Walras’s and Pareto’s works. Marx also worked on similar models, which can be found in the second volume of his book “Capital”[2]. However, a more detailed theoretical approach was developed by Walras. He constructed utility, demand-supply functions and production coefficient which allowed determining the quantity and the price of the goods. But Walras’s model was based on theoretical approach and its application was seemed unrealistic given economic data. For the long time this remained an unsettled problem. Only in 1930 Abraham Wald, who was a mathematician, managed to prove the existence of the solution this problem. But his model was not sufficient to sustain the equilibrium [3, p.135]. Hicks and Samuelson tried to build a system which adequately responded to the changes of the parameters in the model [4, p.150]. One of the main difficulties in Walrasian approach was its requirement to solve the thousands of the equations for each sector of the whole economy. The input-output tables were the first important tools for forecasting, developed by W.Leontief in his seminal paper “The structure of the American economy, 1919-1929” [5]. After some years later Wassily Leontief extended his research in this field [6]. This table allows analyzing the economy in the national and regional levels. Theoretically the equilibrium is achieved when the interests of the producer and consumer are satisfied simultaneously, which is almost impossible because of disbalances in real life. Nevertheless the importance of the balance model could not be denied. “Input-output” function based on the direct and full input cost coefficients. The input and output of the each group of goods should sum up to the disposable resources. The disposable and used resources form the total production in each sector. There are immense literature in journals and in internet resources concerning the analysis and the modeling of the theoretical and empirical problems of interdependence among the sectors in the economy [7,8,9,10,11,12,13,14,12,13,14, 15].
Input-output table are built on nominal and real terms. During the years after the transition period of the Azerbaijani and Kazakhstan economy to the market economy various “input-output” researches conducted by Statcom [16,17,18,19,20,21,22,23]. But the inter-dependence balance and comparative analysis were not conducted in labor markets in these economies.
3. Summary of literatures and learning level of the problem
It is known that intersectoral balance schedules are made as natural and cost description. Different research carried out by Statkom on “Input - Output” schedules after the transition of Azerbaijani and Kazakhstan economy to market relations systems. But the intersectoral balance of labor reserves was not considered in a comparative way and comparative analysis of stimulations for opening new working places in these studies.
4. Methodology
Matrixes are made from direct and total expenses coefficient using the table of “Manufacture of product and intersectoral balance for rendering services” composed in the cost description.
It is clear that the main equation of “Input - Output” model is as follows:
X=AX +Y (1)
A – is called a direct expenses coefficient matrix. Matrix A is also called technological matrix for representing production technology. X- is general issue, and Y- last product vector.
X=(E−A)−1Y (2)
This solve is called very productive matrix. There is E measure is unit matrix equal to n.
2
Static and dynamic balance models are used in intersectoral labour-market equilibrium as well as in productive division of labour reserves. The base of information provision of balance moleds are expense coefficient matrix of reserves. We may review application of Intersectoral balance method to the analysis of labour indicators. While reviewing this problem direct and full labour expenses over unit product shall be defined. According to it balance model of labour is to be worked out. Correlation of economic activity sector to the product issue of labour reserses’ relevant sector is accepted as a direct labour coefficient.
t i=Li
X i, i=1 , n ( 3)
There is X i - is total production issue of product (may be economic activity sector), Li - is labor force for manufacturing product.
The full labor coefficient is calculated by using this coefficient.
If we sign full labor expense quantity to the first type unit product by T i :
T j=∑i=1
n
aij T i+¿ t j ,=1 , n¿ (4)
There is aij is a direct material expense coefficient. Tj is full labor coefficient. If we include direct labor coefficient as t=(t1 , t2 ,…,t n) line vector and full labor coefficient asT=(T1 ,T 2 , …,T n) then we may write relation (4) like matrix as following:
T=T A+ t (5)
T=t (E−A)−1 (6)
(E−A )−1 matrix is full material expense coefficients known from intersectoral balance.
In this case we may write occasion (6) as
T=T B (7)
If we mark all expenses paid for animated labor on products of all kinds as L
L=∑j=1
n
R j=¿∑j=1
n
t j X j=tX ¿ (8)
Here X is product issue.
If we multiply both sides of (7) by y-final product vector from the right,
we take T Y =T BY and if we take into account (3) in this equality, we take
T Y =T X (9)
Left side is ¿T Y .
Because, the right side of the equation (9) shows the number of busy people according to (8). It is clear that coefficient of full labor capacity shows the number of necessary workers for manufacturing of final product in common quantity.
Equality (9) taking by coefficients of full and direct labor capacity represent principle balance equality of intersectorial relations of labor. Equality of right side with left side of (9) identity is obliterated, if determinant of matrix (E-A) is about zero. In this case it is advisable to use approximate methods in the accounting of persistent matrix.
Model (3) gives an opportunity for determination of common influence to capacity of product issue of different economic indicators (example, additional value, employment, principle capital
3
and import).
Common influence to the capacity of product issue is determined by
ΔX=(E−A)−1 ΔY =BΔY (10)
Here common influence to ΔX issue, in other words shows the change of product issue in the result of the change of ΔY final product issue. Common influence to the employment by proper way is
ΔL=tΔX (11)
if we take into an account (10) in (11).
ΔL=tBΔY (12)
Calculates as foolowing. Here, ΔL shows changes in employment as a result of change in final good (ΔY ). t - this is the vector of direct labor capacity (expenditure) parameters, in other words, this is the employment of goods production in every sector (spent person-hour, person-day, person-year).
Now let’s specify the impact of change level of goods (ΔY ) volume of goods production (ΔX ), to the change of value added value (ΔV ) və change of employment level (ΔL). Note that, it is possible to optimize simuliations by (10) və (11).
Firstly let’s look at the issue of impact optimization of change level of final good ( ΔY ) to the employment change (ΔL ).
∆ L=tB∆ Y =T ∆ Y → max (13)
∑ ∆ Y=I (14)
∆ Y ≥ 0 (15)
Here I characterizes the exogenious increased level of final production in the economic activity. In other words, this is the parameter of problem və forms free limit of restricion condition. Solution of problems of (13)-(15) answers the following questions. Increase of final production by one unit creates how many jobs and the number of this employment being the most in itself and other sectors.
If we look at problems of (13)-(15) we see that thi is the linear programming problem and restriction condition (14) consists of only one equation. That is why in the result of problem solution only one variable, in other words one of ∆ y1 ,∆ y2 ,…, ∆ y n will be different number from zero (for being the only one basis variable). This basis variable (13) will be corresponding variable to the biggest parameter of intention function. In other words in which sector the complete labor capacity is bigger same secotr’s final production change the most increases employment. However for and speeding simuations it is expedient to solve (13)-(15) optimazation problems.
If there emerges any problems in the calculation of reverse matrix then in the estimation of T- complete labor capacity may occur moving away. Such as, in finding of T as it is shown in (7) participates B reverse matrix. That is why for the passing by from the calculation deviation it is expedient to solve the following problem.
B ∆ Y=∆ X equation, considering in (14) and (15) ∆ X=( E−A )−1 ∆ Y and ∆ Y =( E−A ) ∆ X .
∆ L=t ∆ X →max (17)
4
{∆ X=( E−A )−1 ∆ Y∑ ∆Y =I ❑
} (18)
∆ X ≥ 0 , ∆ Y ≥ 0 (19)
In (19) ∆ X ≥ 0, ∆ Y ≥ 0 shows that increase in final good and aggregate production can’t be negative.
In (18) restriction condition has n+1 times equation, 2n times variable. In intention function parameters of ¿) variables equals to zero.
It is possible to simplify the example. Such as, finding ∆ Y from the first part of (18) equation
and putting it to the second part:
∆ L=t ∆ X→max (20)
∑ (E−A ) ∆ X=I (21)
∆ X ≥ 0 (22)
5. Processing of informations and composition of intersectoral balance of labor resources
Intersectoral balance of labor resources was composed by the calculation of parameter of direct labor capacity with the formula (3), complete labor capacity with the formula (4) in the basis of input-output table of Azerbaijan and Kazakhstan Republic.
Intersectoral balance table was composed by the 15 Azerbaijan economy and 29 Kazakhstan economy’s labor indicators
Labor capacity of any product is a complex indicator for finalizing labor costs in production processes. This indicator is tightly telated with labor productivity. Such as, productivity becomes more as labor capacity becomes less. Decrease of labor capacity means increase of labor productivity. When said labor capacity understood quantity of total employee’s labor costs for producing one unit product in economic sciences.
Complete labor capacity parameter calculated by the intersectoral balance table characterizes demanded labor force in total production. If it is calculated by the sectors in that case it becomes possible to estimate the demand for the labor in economic activity areas.
The estimates of direct and total labor capacity coefficients calculated according to (3) and (6) for Azerbaijan and Kazakhstan is given in Appendix 1 and Appendix 2.
Table 1.Structure of total output and value added in Azerbaijan and Kazakhstan
Names of indicators
Azerbaijan KazakhstanOil sector
Non-oil sector
Whole economy
Oil sector
Non-oil sector
Whole economy
Total output 100% 100% 100% 100% 100% 100%Share of intermediate consumption in total output 9,4 52,9 37,1 36,5 49,1 46,7Share of value added in total output (value added ratio) 90,3 45,8 62.0 47,0 50,7 50,2Share of net taxes in total output 0,3 1,3 0,9 16,5 0,2 3,2
5
Value added 100% 100% 100% 100% 100% 100%Share of the wage in value added 5,5 24,00 14,2 13,3 35,8 33,8Share of capital formation in value added 2,8 15,00 8,5 31,8 11,8 15,0Share of profit in value added 90,2 52,90 72,7 46,4 51,5 49,0Share of social transfers and taxes in value added 1,5 8,10 4,6 8,5 0,9 2,2
Share of value added of oil sector in total value added,percentage - - 53,0 - - 18,0
Source: Authors calculations due to input-output tables.
In Table 1 we can see that, in Azerbaijan added value of the oil industry was 53% of total country’s added value, whereas in Kazakhstan this indicator was only 18.0%. This shows higher dependency of Azerbaijan’s econmy obn oil industry compared to Kazakhstan’s economy.
In Azerbaijan added value norm in the oil industry is equal to 90.3%, while in Kazakhstan it is 47.0%. The main reason of this situtation is that the cost of intermediate products in oil industry and the taxes on output in Kazakhstan are higher than in Azerbaijan.
Azerbaijan's oil sector's share of profit in value added is significantly high (90.2%) because the level of wages, consumption of the main assets, social and corporate taxes are significantly lower than in Kazakhstan.
In general, the main reason of high value added norm in oil and gas industry is that the cost of land and natural capital, which are the main production factors is not paid off. As in K.Marx’s scheme of prduction [2, p.441-596] where surplus value is created due the incomplete payment to the worker, which results in the increase of explotation of the worker and increase of capitalist’s wealth, in the oil industry incomplete payoff to natural capital creates surplus money. This in its own turn, results in swallen value added and profit margins in natural resouces (such as oil industry). Increase in value added norm in the oil sector means decrease in the demand of this sector to the products of the non-oil sector. If the cost of natural capital was completely paid off (for expample higher level of land tax, mining tax, environment tax) it would naturally have increased the demand to the products of non-oil sector and it would have resulted in the balanced economic development. [24, p.152-165]. It can be concluded that, there three direction of the effective use of oil revenues:
The first direction: In order to decrease the value added norm in the oil industry to implement tax differentiation and increase in the production taxes in the oil industry( for expmple increase in the value added and excise taxes); moreover implement programs aimed at increse of the the costs of the intermediate products in the oil industry.
The second direction: In order to decrease the profit margins in the oil industry increase of the production taxes and social payments, wages and consumption of the main capital;
According to third approach in order to increase value added and profit ratio in non-oil sector, especially in agriculture, proccesing, education and medicare, measurement as tax reduction in both production and goods, imposing of tax reduxtion, lending discounted loans and subsidies can be implemented. Otherwise, measurements as land-improvement, protection of environment, solution of ecological issues, increasing social costs can stimulate non-oil sector demand.
6. Calculation of multiplier effect of new employments by realising simulation models and 6
analysing of results:
Let’s indefy the effects of changes in volumes of final good to the employment levels in sectors..
For this firstly ∆ Y - in the result of changes in final goods assess the impact to the production change ∆ X by the (10) model. After ∆ X - definig production change assess the total impact of this change to the employment by (11) model. We can combine effects of (10) and (11) and implement it under (12). Simulations reflecting multiplier effects of change of final product to employment are automated in EXCEL system (Appendix 5 and appendix 6). Estimated results with different cases for Azerbaijan and Kazakstan are given in Appendix 5 and 6.
Solution of optimized issues on creating new jobs (16)-(18) and (23)-(25) imply that both in Azerbaijan and Kazakstan unit change of final agricultural product (else investment change) creates more new jobs (direct and total). Oil-gas sector contributes only negligible part of creating new job.
Table 2 represents impact of change of 1 mln. $ final product to change in created job in different sectors.
Table 2.Change of employment in different sectors due to change 1 mln. $ of final product, person (person-year)
Sectors
Azerbaijan Kazakstan
Direct jobs
Indirect jobs
Total jobs
Direct jobs
Indirect jobs
Total jobs
Processing 53 155 208 16 59 75
Medical and social services 401 64 465 136 39 175
Agriculture, hunting and forestry 836 53 889 285 2 287
Oil-gas extraction (oil sector) 4 17 21 2 19 21
Fish and other fishing fields 43 39 82 173 14 187
Evidently, increase 1 mln. $ of final product in oil sector creates only 4 jobs in Azerbaijan (direct job), other sectors creating 17 new jobs (indirect jobs) totalized 21 new jobs (total jobs), but in Kazakstan oil sector creating 2 jobs, totalized 21 new jobs with respect to 19 jobs in other sectors. Consequently we generalize, both in Azerbaijan and Kazakstan oil sector holds minor part of job creation, nevertheless agriculture contributes majority.
Literature
1. Макконнелл К.Р., Брю С.А. Экономикс. В 2 т.: Пер. с анг.- Том 1, Баку, «Азербайюджан», 1992. – 400 c. 2. Kарл Marркс «КАРИТАЛ», Том Второй, Книга II , М.:Политиздат, 1978, 648с. 3. Селигмен Б. Основные течения современной экономической мысли.- М., 1968. – 284 с. 4. Бункина М.К. Экономические модели Василия Леонтьева.//Финансовый менеджмент.- М., 2002, №1.С. 13-28. 5. Леонтьев В.В.Исследование структуры американской экономики. – М. 1958. – 231 с.6. Леонтьев В.В. Межотраслевая экономика М.,1997. -315 с.; Леонтьев В.В. Экономические эссе. М. 1990. -280 с.
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7. Леонтьев В.В.Исследование структуры американской экономики. – М. 1958. – 231 с. 8. Руководство по составлению таблиц затрат-выпуска и их анализу, ООН, Нью-Йорк, 2000, Серия F, N 74, 204 c. 9. Гранберг А. Г. Василий Леонтьев в мировой и отечественной экономической науке // Вопросы экономики.-М.,1999. № 3 .С. 24-3210. Российский статистический ежегодник.- М., 2003.-362с. 11. Экономико-математические методы и прикладные модели: Учебное пособие для вузов /В.В.Федосеев, А.Н. Гармаш и др.-М., 2001. -264 с. 12. Кубанива М., Табата М., Табата С., Хасэбэ Ю. «Математическая экономика на персональном компютере» (перевод с японского), М.:Финансы и статистика, 1991.-304с.13. www.dvgups.ru/metdoc/eemen/eteor/ekteor/ - математические модели14. www.math.omsu.omskreg.ru/info/learn/pprimer/afterword.htm -модель МОБ15. www.wassily.leontief.net – Сервер Леонтьева В.В.16. Yadulla Hasanli, The analyisis and modeling of inter-industral communications in the econmy (Model Input-Output),// The Azerbaijan Republic Ministry of Economical Development Centre of Economical Reforms, Features and problems of (the) carrying out in Azerbaijan of the economical reforms, Collection of scientific works, VI issue, Baku, 2005, pp.50-77 (in Azerbaijani)17. Imanov Q.C., Hasanli Y.H., Rzayev R.R. Identification of Input-Output balance model bu Soft Computing \\ ISEECE,2006, 3 rd International Simposium on Electrical, Electronic and Computer Enginecring, November 23-25, 2006, Nicosia, North Cyprus, pp.230-23718. Гасанлы Я.Г., Сулейманов Н. Aнализ межотраслевых связей в экономике Азербайджана на основе модели «Затраты - выпуск», Вопросы статистики, №1, Москва, 2007, с.36-42. (in Russian) 19. Orujov H., Hasanli Y.H., Valiyev V.M. Linear algebra and economocal models. Caucasus University press, Textbook for high schools, Baku, 2009, p. 132 (in Azerbaijani). 20. Hasanli Y., Hasanov F., Mansimli M. Equilibrium prices model for sectors of azerbaijan economy based on input-output tables\ EcoMod 2010, İnternational Conference on Economic Modeling, İstanbul, Julu 7-10, 2010, İstanbul Bilgi University, pp.63.21. Abbasov A.M., Hasanli Y.H., Jafarov R.J., Tahirova G.I. “Evaluation Of Increase Of Job Places Based On “Input-Output” Models”// First İnternational Conference on Soff Computing Technologies in Economy, ICSCTE-2007, Baku, Azerbaijan, November 19-2022. Гасанлы Я.Г., Таирова Г.И. “Aнализ межотраслевых связей трудовых ресурсов Азербайджана на основе таблицы «Затраты – Выпуск»”, Формування ринкоих еiдносин в Украiнi (Формирование рыночных отношений в Украине), №9 (112), 2010, ст.200-206 23. Байзаков С., Сагинтаева С. «Совокупная Факторная производительность как мера мировых валют, Астана, 2009.-81 с. 24. Yadulla Hasanli, Analyses economic development of countries which have rich natural resources by using scheme of reproduction, A Glimpse of the World, №5, 2007, p. 152-165 (in Azerbaijani)
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Appendix 1. Direct and total labor capacity coefficients according to the economic activity spheres in Azerbaijan
Spheres Line code
Direct labor capacity
coefficients (person year
unit per thousand
manats of gross output)
Total labaor capacity
coefficients (person year
unit per thousand manat
final output)
Ratio of total labor
coefficint to direct labor coefficient
t=L/x T=B*t T/tAgriculture, hunting and forestry products 1 0,756873 1,041091 1,375515Fishing products 2 0,040149 0,049775 1,239754Mining industry 3 0,004256 0,307621 72,282270Processing industry 4 0,040676 0,806925 19,837807Electricity, gas and water 5 0,064934 0,166067 2,557469Construction works 6 0,061489 0,474036 7,709291Trade services 1) 7 0,404722 0,545240 1,347196Hotel and restaurant services 8 0,141838 0,187279 1,320379Transportation,Warehouse and Communication 9 0,088695 0,324666 3,660474Financial intermediation, insurance and pension services 10 0,038684 0,055524 1,435348Real estate, renting and other commercial services 11 0,182893 0,304807 1,666585Education services 12 0,609555 0,623089 1,022203Healthcare and social services 13 0,459166 0,466120 1,015145Public adminstration and defence, compulsory social insurance services 14 0,327101 0,373047 1,140465Communal and other services 15 0,266841 0,321369 1,204344
9
Appendix 2. Coefficients of full and direct labor capacity over the sectors of economy in Kazakhstan
Industry sectorsLine code
Coefficient of direct labor
capacity (person/year per thousand tenge output)
Coefficient of direct labor
capacity (person/year per thousand tenge output)
Ratio of the coefficient of
full labor capacity to the coefficient of direct labor
capacityAgriculture, hunting and forestry 1 0,001585 0,002275 1,435116Fishing 2 0,001260 0,001486 1,179099Coal and lignite, extraction of peat 3 0,000128 0,000290 2,261712Row oil and natural gas extraction 4 0,000011 0,000163 15,541851Metal ore mining 5 0,000142 0,000320 2,251947Other mining and quarrying industries 6 0,000324 0,000482 1,485816Processing of agricultural products 7 0,000105 0,000598 5,700708Textiles industry 8 0,000359 0,000898 2,503560leather, leather products and footwear manufacturing 9 0,000139 0,000894 6,429361Wood and wood products production 10 0,000043 0,000273 6,314243Paper and paperboard production, printing 11 0,000097 0,000198 2,043536Coke, refined petroleum products and nuclear fuel production 12 0,000031 0,000122 3,891987chemical industry 13 0,000119 0,000221 1,858699Rubber and plastics production 14 0,000085 0,000209 2,464972Production of other non-metal mineral products 15 0,000136 0,000238 1,748528Metallurgy and metal processing 16 0,000063 0,000180 2,850727Machinery and equipment repair, spare parts manufacturing 17 0,000146 0,000274 1,871183Other manufacturing industries 18 0,000067 0,000134 1,992012Production and distribution of electricity, gas and water 19 0,000265 0,000403 1,521580Construction 20 0,000203 0,000319 1,576284Trade and repair of household goods 21 0,003739 0,005628 1,505321Hotels and restaurants 22 0,000521 0,000895 1,715685Transport, supporting and auxiliary transport activities 23 0,000271 0,000525 1,936630Post and telecommunications 24 0,000183 0,000330 1,805645Financial industry 25 0,000231 0,000628 2,711372Real estate and renting 26 0,000108 0,000597 5,522674Education 27 0,001375 0,001571 1,142110Healthcare and social services 28 0,001078 0,001388 1,288408Other utlity and social services 29 0,000728 0,001020 1,400723
10
Appendix 3.Outcomes of the simulations for Azerbaijan: The impact of the change in final product volume on employment.
Spheres Code
Versions of the increase in employment as a result of the increase in final products in different spheres by one million manat (person-year)
Prossesing industry
Health and social services
Agriculture, hunting and forestry products
Mining industry
Fish and other fishing products
∆L1 ∆L2 ∆L3 ∆L4 ∆L5Agriculture, hunting and forestry products 1 121 32 1313 5 0Fish and other fishing products 2 0 0 50 0 0Mining industry 3 2 0 13 4 0
Prossesing industry 4 61 16 175 2 0Electricity, gas and water 5 4 2 99 1 0Construction works 6 5 3 177 1 0Trade services 1) 7 28 9 582 4 0Hotel and restaurant services 8 0 0 177 0 0Transportation,Warehouse and Communication 9 7 4 212 3 0Financial intermediation, insurance and pension services 10 0 0 43 0 0Real estate, renting and other commercial services 11 7 3 314 2 0Education services 12 0 0 627 0 0Healthcare and social services 13 0 460 467 0 0Public adminstration and defence, compulsory social insurance services 14 2 1 398 1 0Communal and other services 15 2 2 321 0 0Total 241 534 4967 25 0
11
Appendix 4. Outcomes of the simulations for Kazakhstan: The impact of the change in final product volume on employment.
Industry sectorskod
Versions of the increase in employment as a result of the increase in final products in different spheres by one million manat (person-year)
Proc
essi
ng o
f ag
ricul
tura
lpr
oduc
ts
Hea
lthca
re
and
soci
al
serv
ices
Agr
icul
ture
, hu
ntin
g an
d fo
rest
ry
Row
oil
and
natu
ral g
as
extra
ctio
n
Fish
ing
∆L1 ∆L2 ∆L3 ∆L4 ∆L5Agriculture, hunting and forestry 1 418 93 2259 3 22Fishing 2 14 1 0 0 1373Coal and lignite, extraction of peat 3 0 1 1 0 1Row oil and natural gas extraction 4 0 0 0 12 0Metal ore mining 5 1 2 0 1 1Other mining and quarrying industries 6 1 7 0 1 1Processing of agricultural products 7 123 10 1 0 5Textiles industry 8 1 1 0 1 3leather, leather products and footwear manufacturing 9 0 0 0 0 0
Wood and wood products production 10 0 0 0 0 0Paper and paperboard production, printing 11 3 0 0 0 0
Coke, refined petroleum products and nuclear fuel production 12 0 2 0 1 1
chemical industry 13 0 42 1 1 0Rubber and plastics production 14 0 0 0 1 1Production of other non-metal mineral products 15 1 2 0 2 1
Metallurgy and metal processing 16 1 4 0 3 1Machinery and equipment repair, spare parts manufacturing 17 2 2 2 2 2
Other manufacturing industries 18 0 0 0 0 0Production and distribution of electricity, gas and water 19 5 12 2 4 7
Construction 20 1 5 1 2 1Trade and repair of household goods 21 11 86 4 73 14Hotels and restaurants 22 1 2 0 2 1Transport, supporting and auxiliary transport activities 23 7 10 2 20 43
Post and telecommunications 24 1 3 0 2 2Financial industry (25)+government (27)+direct purchases abroad by residents +Direct purchases in local market by non-residents
25 1 2 0 3 2
Real estate and renting 26 4 9 1 29 4Education 28 0 0 0 0 0Healthcare and social services 29 0 1078 0 0 0Other utlity and social services 30 0 15 0 0 0Total 598 1390 2275 163 1486
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Appendix 5. Example for the outcome of job place creating simulation model (Azerbaijan)
Spheres Code
Change in final product (ex.investment) in thousand manats
Increase in employment, person
∆y ∆LAgriculture, hunting and forestry products 1 5
Fish and other fishing products 2 0Mining industry 3 1000 4Prossesing industry 4 2Electricity, gas and water 5 1Construction works 6 1Trade services 7 4
Hotel and restaurant services 8 0Transportation,Warehouse and Communication 9 3Financial intermediation, insurance and pension services 10 0Real estate, renting and other commercial services 11 2Education services 12 0
Healthcare and social services 13 0Public adminstration and defence, compulsory social insurance services 14 1
Communal and other services 15 0Total 1000 25
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Appendix 6. Example for the outcome of job place creating simulation model (Kazakhstan)
Industry sectors CodeChange in final product
(ex.investment) in thousand tenge
Increase in employment, person
1 2 3 4 ∆Y ∆L
Agriculture, hunting and forestry 1 3Fishing 2 0Coal and lignite, extraction of peat 3 0Row oil and natural gas extraction 4 1000000 12Metal ore mining 5 1Other mining and quarrying industries 6 1
Processing of agricultural products 7 0Textiles industry 8 1leather, leather products and footwear manufacturing 9 0
Wood and wood products production 10 0
Paper and paperboard production, printing 11 0
Coke, refined petroleum products and nuclear fuel production 12 1
chemical industry 13 1Rubber and plastics production 14 1Production of other non-metal mineral products 15 2
Metallurgy and metal processing 16 3Machinery and equipment repair, spare parts manufacturing 17 2
Other manufacturing industries 18 0Production and distribution of electricity, gas and water 19 4
Construction 20 2Trade and repair of household goods 21 73
Hotels and restaurants 22 2Transport, supporting and auxiliary transport activities 23 20
Post and telecommunications 24 2Financial industry 25 3Real estate and renting 26 29Education 28 0Healthcare and social services 29 0Other utlity and social services 30 0Total 1000000 163
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