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ISSN 1075�7007, Studies on Russian Economic Development, 2014, Vol. 25, No. 5, pp. 431–438. © Pleiades Publishing, Ltd., 2014. Original Russian Text © M.S. Gusev, 2014.

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Economic growth forecasting is an integral part of decision�making support (including strategic deci� sion�making) on the level of both individual compa� nies and entire countries. This means that arguments of economic forecasting are used to justify decisions and economic policy measures. In other words, eco� nomic forecasting can be seen as a system of argu� ments in favor of economic growth trajectory and its possible variations.

The analysis of economic growth factors in eco� nomic forecasting and their comparison with the the� oretical narrative of economic growth1 allows one to verify the reliability of economic forecasts for the for� mulation of economic policy.

The effect of the factors of economic growth is most fully manifested at long intervals; therefore, their analysis should be based on published long�term fore� casts. When short�and medium�term forecasts are elaborated, the explicit (or implicit) hypotheses are made about the immutability of many factors, most important of which is existing technology. In general, this assumption can be justified because the main task of short� and medium�term forecasting is to assess the inertial scenarios of development and their possible variations related to the application of economic policy measures.

This paper analyzes long�term global economic projections and analytical studies on the long�term trends of economic growth.

The Description of Factors of Economic growth in the Forecast and Analytical Materials2. The most popular

1 In this paper, the theoretic narrative of economic growth refers to a set of factors of economic growth justified by A. Smith in [1]. In this paper, the economic growth is understood, first of all, as per capita income growth, which is the result of labor produc� tivity growth due to the accumulation of capital and labor divi� sion.

2 In this section, the description of forecasts is given according to the publications of the respective organizations.

global economic forecast is the probably the IMF’s World Economic Outlook. Although the timeline of this forecast is limited to 5 years, this publication often contains abstracts that describe and analyze long�term trends. For example, the latest issue of the World Eco� nomic Outlook [2] contains the analysis of the eco� nomic slowdown in BRICS countries in 2013. The analysis concludes that the economic slowdown in these countries is due to a cyclical deceleration of eco� nomic activity and a decreasing growth rate of poten� tial output3.

According to IMF experts, the cyclical slowdown is due to the following factors. In the midst of the global financial crisis, the BRICS countries decided to launch unprecedented measures to support the econ� omy. The unfolding global economic recovery led to an increase in external demand, lower interest rates, and higher commodity prices. However, the effect of these factors was exhausted by 2011; the economic stimula� tion programs were ended, the external demand slowed down, and the commodity prices stabilized.

The slower growth of the potential output was due to various factors in different countries. For example, in India, it was entailed by the problems related to the expanding offer in mining, energy, telecommunica� tions, and others sectors. The issuance of permits was suspended and the approval of new projects slowed down. Corporate balance sheets were overwhelmed by debt.

A decreasing long�term balanced economic growth in China and Russia is due to the exhaustion of resources, which fuelled the previous models of eco� nomic growth. The Chinese model relied on the extensive economic growth, where economic expan� sion is achieved at the expense of a high savings rate, the creation of new capacities, and the population’s

3 The concept of potential output is analyzed below.

MACROECONOMIC PROBLEMS

Modeling Economic Growth for Long�Term Global Economic Forecasting

M. S. Gusev Institute of Economic Forecasting, Russian Academy of Sciences, Moscow, Russia

e�mail: [email protected] Received November 13, 2013; in final form December 2, 2013

Abstract—The correspondence between the factors of economic growth described in long�term economic forecasts and long�term forecasting modeling tools, as well as the classical theoretical interpretation of eco� nomic growth is analyzed.

DOI: 10.1134/S1075700714050049

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migration from the countryside to the city. By now, the high savings rate has led to the excessive capacities and lower returns on capital. At the same time, it is expected that, starting from 2014, the economically active population will decline in absolute terms and, thus, result in a labor shortage by 2020. In Russia, the economic growth of the 2000s was propelled by the exploitation of idle capacities and growing global commodity prices. At the same time, the growth was originally constrained by the worn infrastructure (especially, transport and power networks) and the unfavorable business climate. The effect of the above mentioned factors, which used to fuel the economic growth, has by now exhausted in Russia. The situation in the country is aggravated by unfavorable demo� graphic trends translated into the declining population of the working age.

One can distinguish between the following growth factors in the IMF outlook: business cycle stages, external demand, government spending, expansion of production capacity, accumulation rate, increase in manpower, business climate, and quality of infrastruc� ture.

The description that accompanies the forecast refers to the methodology of determining the cyclical component in the dynamic output. According to this method, the cyclic component is calculated as the dif� ference between the actual rate of economic growth and the growth of potential output. The assessment of the latter is primarily a result of econometric calcula� tion based on the use of a set of indicators, such as out� put, unemployment, and the actual economic growth rate (this method is discussed in more detail below).

In this context, the process of establishing the potential output growth rate plays a key role. The fac� tors that support the achieved growth rate of potential output and the assessment of business cycle stages are of secondary, auxiliary importance.

In addition, it should be noted that the actual description of the economic growth factors in the IMF outlook is reduced to how fast and with the help of which economic policies different countries can regain the potential output growth.

In the Conference Board’s Global Economic Out� look [3], the main factor that propels the acceleration of economic growth in the medium term in the United States and other countries is the restored growth of output to the potential economic growth, which can be achieved by increasing workforce capacity and technological advancement.

In the long�term outlook, the global economic slowdown will be affected by the slowdown in develop� ing countries, especially India and China, which will shift from a growth model based on the accelerated investment growth to a more balanced model.

The description of the factors of growth contained in this outlook suggests that in the long run the global economy and national economies will grow at the rate

equal to the growth rate of potential output affected by the investment dynamics.

To justify the economic slowdown in developing countries, the Goldman Sachs BRICS outlook [4] relies on the hypothesis of the converging growth of labor productivity in developing and developed coun� tries. The rest of the forecast provides the description of results and refers to the shares of specific countries in the global economy.

The PwC’s World in 2050 outlook [5] lists the fol� lowing factors of economic growth:

—the dynamics of the working�age population;

—the assessment of human capital growth (calcu� lated based on the number of years spent on educa� tion);

—The volume growth of productive assets as a result of investment dynamics;

—Total factor productivity (the evaluation based on the hypothesis of a reducing labor productivity gap with regard to a leading country).

At the same time, the potential of a reducing labor productivity gap is associated with an increased open� ness of the economy and the enhanced competition, as well as improved business climate.

The OECD Looking to 2060 outlook [6] assumes that the financial crisis of 2007–2008 did not alter the potential global economic growth. Once the conse� quences of the global financial crisis have been over� come, it is expected that the growth rate of global GDP will reach the target of 3% per year and will remain at this level for the next 50 years. The GDP growth will be supported by fiscal reforms (aimed at stabilizing the share of public debt in GDP) and struc� tural changes, as well as the growing share of develop� ing, dynamically growing countries in the global GDP. If economic policy is not changed, the current account imbalances of biggest economies could again drop to the level of 2007–2008 by 2030, which will result in higher interest rates and lower GDP growth.

Possible impact of the continuing low�end demand on the potential output growth was not considered in the forecast. Similarly, possible debt defaults by indi� vidual countries, violation of trade relations between two countries, scarcity of natural resources due to the excessive pressure on the environment (depletion and the emerging scarcity of natural resources) were ignored by this particular outlook.

It is argued that the scientific and technological progress will be the main factor of economic growth. In various forecasts, the contribution of this factor is measured by total factor productivity.

It is expected that, for individual countries, the productivity growth rate will depend on the degree of openness of the domestic market and the intensity of domestic competition. The higher these characteris� tics are, the faster can the productivity grow.

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In general, the description of the factors of eco� nomic growth in the OECD forecast is reduced to the description of those that enable individual economies to achieve the growth of potential output. The first group of these factors includes fiscal consolidation (reduction or stabilization of public debt in relation to GDP) and the removal of global imbalances (defi� cit/surplus of the current accounts). The second group of factors includes demographic trends, participation of the population in education, the increasing age of retirement, intensifying liberalization of domestic markets in developing countries, growing public spending on social security, and the increasing avail� ability of consumer credit4.

According to the Long�Term Forecast of the Socio� economic Development of the Russian Federation for the Period until 2030, prepared by Ministry of Economic Development [7], long�term global economic growth will depend on the pace of technological progress and the possible use of capital and human resources. Given the population growth and environmental constraints, the economic growth in developed countries will be based on productivity growth stimulated by the scien� tific and technological advancement. Intensifying glo� balization will promote opportunities to catch up to growth in developing countries and will expand the access to the achievements of global technological development by promoting susceptibility to techno� logical innovations and improving the business cli� mate. However, growing population and natural resources constraints, as well as the increasing neces� sity of financial balance will prevent the global econ� omy from regaining high pre�crisis growth rates (at the annual level of 4% or higher).

By 2030, the global economic slowdown will be unfolding under the influence of the following factors:

—Shrinking workforce in leading developed coun� tries and a slowdown in the labor force growth in developing countries;

—Gradual decreasing productivity growth in fast� growing Asian countries, which will accompany the narrowing gap between the latter and the leading countries;

—A decreasing rate of accumulated fixed capital, reduced funding of cutting�edge basic research and development;

—Intensifying environmental constraints associ� ated with the rising costs incurred by the need to pre� serve acceptable habitat and environmental standards of production and consumption not only in developed countries but also in developing countries.

As projected by the Russian Ministry of Economic Development, long�term economic growth in Russia will be determined by the following:

—changes in the external demand;

4 According to the forecast, the share of consumer credit in GDP in all countries will reach the U.S. level of 2% per year.

—productive capital growth; —an increase in total factor productivity (at the

first stage, by adopting the existing procurement prac� tices and purchase of advanced equipment and, later, based on qualitative improvement of education and domestic scientific research and innovation develop� ments);

—higher quality of human capital. Classical theoretical model of economic growth. The

classical economic theory [1] associates the level of economic income with the size of accumulated capital and the degree of labor division. Rising income levels (or economic growth) depend on increasing produc� tivity. In turn, the level of productivity is achieved due to the level of division of labor, which is made possible by the accumulation of a certain amount of capital. A higher level of division of labor provides a higher level of manpower productivity (specialization at various stages of production), helps reduce production costs (including by increasing the scale of production), and frees up resources for their subsequent investment in development and improvement of productive assets.

The enhanced division of labor also results in the increasing accumulation of knowledge and human capital in the society. Furthermore, the division of labor stimulates the further accumulation of capital, which is associated not only with the quantitative expansion, but also with qualitative changes reflected in the emergence of new industries, products, technol� ogies, and manufacturing capacities.

The reinforced division of labor and specialization entails an increase in the number of linkages between individual production stages and raw material pro� cessing stages. When more steps are included in the production of finished goods and services, manufac� turers are more highly specialized, the relationships between producers are greater, the manufacturing of the final product is more effective, and the level of pro� ductivity and economic income are higher. However, specialization growth has its limitations. The rein� forced division of labor is constrained by the market size. In other words, it becomes unprofitable if the obtained additional amount of product cannot be sold or exchanged for other products.

Since the second half of the 20th century, the pro� cesses of the enhanced division of labor and capital export, which was reflected in the system of foreign economic relations and the structure of world trade, have played important roles in expanding opportuni� ties for economic growth in both developed and devel� oping countries. Meanwhile, according to the above economic forecasts, no source describes the changes in the most significant qualitative components of eco� nomic growth, such as intensifying specialization and closer linkages between producers. The discrepancy between the description of the factors of economic growth in the classical theory of economic growth and the quantitative long�term forecasts designed based on

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economic models is so great that one can argue that the currently developed long�term forecasts do not provide a sufficient explanation of the published esti� mates of economic growth. Specifically, as shown above, no source considers the division of labor and specialization as a factor in economic growth.

The current narrative practices of economic growth and their difference from the theoretical postulates might be due to certain characteristics and ideology of econometric models applied for designing economic forecasts.

Modeling tools of long�term forecasting. The World Economic Outlook is based on the aggregation of fore� casts obtained for individual countries [8]. The fore� cast for each country is developed by a separate group of experts; therefore, there is no single methodology for forecast estimates.

However, based on the description of factors underpinning the economic dynamics in BRICS countries, one can conclude that the analysis of eco� nomic growth largely relies on the concept of potential output. This concept is based on Okun’s law, which links output growth to unemployment, and the Phil� lips curve, which relates inflation to unemployment.

Essentially, the concept of potential output is based on the search for the production volume that can be obtained at full employment without accelerating inflation. The employment rate, which has no effect on the acceleration of inflation (or the level of natural unemployment), is determined based on the following equation [9]:

(1)

where Pe is the level of expected inflation, P is the fac� tual inflation, U* is the level of natural unemploy� ment, is the factual level of unemployment, and α is the coefficient.

In other words, the natural rate of unemployment is the level at which inflation expectations coincide with actual inflation. If it is roughly assumed that inflation expectations are equal to the inflation in the previous period, it is possible to assess the level of nat� ural unemployment based on the above equation.

Then, relation (2) [10] allows us to estimate the potential output at the natural rate of unemployment as follows:

(2)

where Y* is the potential output growth rate and is the factual output growth rate.

A comparison of the actual growth rate and the estimated potential output growth rate allows one to assess the relevance of various economic policy mea� sures applied to stimulate economic growth or, con� versely, to cap it. The slowdown is due to a downward wave of the business cycle where the actual output growth rate is below the potential one. Alternatively, it is due to a decreasing long�term growth rate of poten�

( ), e

P P U U= + α −*

U

[( )/ ],U U Y Y Y− = α −* * *

Y

tial output. Similarly, one can explain the acceleration of economic growth.

The long�term growth rate of potential output is primarily defined by two methods: either based on a trend extracted from the GDP time series by the Hedrick�Prescott filter, or by estimating the maximum possible production with the help of the production function for a given natural rate of unemployment.

In addition to the World Economic Outlook, the IMF also elaborates global economic forecasting models, e.g., The Global Projections Model (GPM) [11], which are designed based on a single methodol� ogy. These models are based on the assessment of the potential growth rate. Possible deviations from this rate and the speed at which this rate is regained are described by the system of equations for individual macroeconomic indicators.

The methodology of the Conference Board’s Long� Term Global Economic Outlook is based on the con� struction of production functions for each country, which is included in the forecast. Production func� tions allow one to decompose the contribution of indi� vidual components made to the economic growth, including labor; capital; and total factor productivity, which is estimated as the residue in the historical period.

The specification of the applied production func� tion is described in detail in [12, p. 4]. The difference between this specification and the Cobb–Douglas production function consists of introducing an addi� tional factor of economic growth, which is associated with a qualitative change in the labor force and is cal� culated as a measure of total wage weighted by the level of qualification and the number of hours worked.

Economic growth forecasting requires one to assess the dynamics of individual components of the produc� tion function. As a result, GDP growth forecast is based on lagged values of the model parameters and exogenously defined indicators, such as population dynamics, taking the age composition, life expectancy, inflation, the share of manufacturing and services sec� tors in GDP, the level of education, and trade and financial openness into account.

Goldman Sachs’s Long�Term Outlook [13] is based on an assessment of the standard production function where GDP growth depends on changing labor resources, accumulated productive capital stock, and technological advancement. The labor force dynamics is set according to the UN projections [14]. The accu� mulation of productive assets is determined by their deterioration and investment dynamics. The techno� logical advancement of individual countries is set based on a hypothesis of converging levels of produc� tivity in a given country and the leading country (United States). The approach velocity is defined using the Growth Environment Score, which allows one to assess the ability of the economy to grow,

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depending on a variety of political, social, and eco� nomic factors.

PwC’s outlook [5] calculates the economic growth rates for each country based on the production func� tion, which, in addition to the factors of capital, labor, and technological progress, includes components such as the quality of the labor force, which reflects the level of education. Volume capital growth is based on hypotheses of dynamic capital intensity and the accu� mulation rate. The labor force dynamics is set accord� ing to the UN projections. The quality of labor is determined by the number of years spent on educa� tion. The pace of technological progress is defined according to a gap between a given country and the leading country (United States). The larger the gap, the faster the speed of technological progress.

The OECD’s Long�Term Outlook is based on the forecast of potential output, which is assed using a modified Cobb–Douglas production function with constant returns on scale. This function includes the following factors: labor, fixed assets, human capital, and labor�saving technological advancement. The extrapolation of factor values (with the exception of accumulated capital) allows one to obtain a long�term forecast of potential output5.

The OECD long�term global economic model is the most developed one compared with the others. This model consists of the following blocks: the use of GDP, income generation, the population’s income and expenditure, prices, public finances (income, expenditure, and public debt), foreign trade, foreign direct investment and foreign exchange reserves, and the monetary assets and liabilities of institutional sec� tors (households, government, private sector, and the external sector).

One of the features of the OECD model is the interdependence of calculations for individual coun� tries, which is achieved by taking estimated trade flows, foreign direct investment, and balance sheets of the external sector into account.

The structural saturation of the model is used to describe the deviation of the current values of the eco� nomic growth from the potential values.

Unfortunately, the Ministry of Economic Develop� ment does not substantiate the methodology applied for long�term forecasting of global and Russian econ� omies. However, given the forecast emphasis on human capital, workforce dynamics, physical volume of capital, hypotheses about labor productivity and total factor productivity, one can assume that the long� term forecast was developed using the production function.

This thesis is indirectly confirmed by the transcript of the report prepared by the experts of the Federal Budget Research Organization at the Institute of Macroeconomic Research [16], which specifically

5 The long�term model is described in more detail in [15].

refers to the fact that one of the key methodological features of long�term forecasting consists of “using factor models to generate a potential trajectory of growth with the embedded parameters of factor effi� ciency depending on hypotheses of the technological advancement linked to structural solutions in the field of innovation and infrastructural progress.” At the same time, one of the complex tasks of long�term fore� casting is associated with the “macrobalancing of sce� nario conditions and the elaboration of a potential trend of economic development, with the enlarged macrostructure of production and use.”

Macroeconomic models and models based on the intersector balance can also be applied as modeling methods of long�term forecasting independent of the calculations based on the production function.

Other possible methods of calculating long�term forecasts of economic growth. Calculations based on macroeconomic models are substantially similar to the calculations based on the production function, where the components related to the use of GDP account are perceived as the primary drivers of GDP growth, rather than labor, capital, and technological advance� ment. Usually, an equation is constructed for each component of the use of GDP account; the obtained equations are later combined into a system, while the forecast calculations are based on the principles of iterative account. These models can vary significantly by structural content from the simplest options to the options with multiple blocks and the interactions between the blocks in the form of forward and back� ward communications.

Calculations based on modern intersector models usually represent a synthesis of intersector and macro� economic calculations. Their main difference from the macroeconomic models consists of the use of the sectoral dimension and the relationship between the value dynamics demonstrated by an individual indus� try and the dynamics of indicators of all other sectors and elements of final demand.

Cross�sectoral and macroeconomic models allow one to build a forecast based on more complex scenar� ios and to consider a greater number of economic pol� icy parameters and economic relationships. However, cross�sectoral and macroeconomic models describe the economic growth at the same quality level as the models based on the production function, i.e., as a weighted sum of growth (reduction) of the individual output components (GDP).

CONCLUSIONS

The analysis of the described long�term global eco� nomic forecasts and their modeling tool shows that in most cases such forecasts are based on the model of aggregate production function. The superstructure of additional units to the production function is mainly used to assess the rate at which an individual country

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can reach the growth rate of potential output calcu� lated based on the production function.

It should be noted that, despite criticism against the use of the production function as a tool for analysis and projection [17], it is still widely used to elaborate long�term growth forecasts6.

Similar to the production function, cross�sectoral and macroeconomic models reduce the explanation of economic growth to the quantitative estimates of the contribution made by individual factors, which are usually similar to the components of the use of GDP account.

The approach to the assessment of economic growth in the economic forecasts based on the con� struction of a production function, as well as macro� economic and intersectoral models, can be described as quantitative.

At the same time, the economic theory explains economic growth through qualitative changes associ� ated with the enhanced division of labor and special� ization, which are not considered in the quantitative estimates of economic growth. Therefore, macroeco� nomic arguments in favor of certain strategic decisions and policy measures designed to achieve long�term results, which are not based on the quantitative approach, have at least no less weight than the argu� ments based on quantitative assessments. Moreover, arguments that are not based on quantitative princi� ples eventually determine the quantitative results of the elaborated long�term forecasts.

Possible ways to improve modeling tools. The ana� lyzed global economic models are designed according to the inevitable logic of economic growth. In other words, it is assumed that all countries will continue to experience economic growth in the long�term out� look. Perhaps, these results are largely due to the exog� enous prediction of the technological development pace.

The applied forecasting tools suggest that underde� veloped countries will inevitably improve their stan� dards of living. In accordance with the assumptions of the model structures, poverty in some countries is due to low capital. This circumstance suggests a high rate of return on invested capital, which should stimulate the growth rate of accumulation and the acceleration of economic growth (maintaining economic growth at a high level). However, the analysis of economic

6 This fact can be explained by the simplicity with which the pro� duction function model allows one to decompose the economic growth into single components and to explain the contribution value of single factors. At the same time, the remaining component, which assumingly, reflects the contribution of scientific and technolog� ical progress, remains unexplained in practically all works on long� term forecasting. As noted in [18, p. 260], “Rather than explaining the peers and the society that the theory (theoretical justification of the production function – author’s note) does not clarify anything based on the observed productivity growth, the empirical studies reported on their “finding” that 80% (or 85 or 75%) of the observed productivity growth were due to technological changes.”

dynamics in less developed countries shows that the level of per capita GDP may remain at a low level for decades.

Therefore, it is far from being clear that the enhanced specialization should last forever. As shown in some theoretical studies (e.g., [18–20]), it is possi� ble that due to low capital intensity in the economy no further enhancement of division of labor can take place and no capital accumulation will occur as a result of the initial specialization in the production of goods within a narrow intermediate production range. Accordingly, economic growth will be limited by the population growth.

In turn, the premises underlying the classical pro� duction function are only applicable to the economy if all firms produce identical goods (or the same set of goods). This means that economic growth is actually included in the forward�looking construction as a hypothesis, rather than a simulated phenomenon.

Given that it is possible to construct a successful approximation of the output dynamics using the pro� duction function, it does not follow that this model adequately takes into account the real mechanisms of economic growth. After all, in the long�term outlook, it is possible to identify a trend model for any economy with an observable economic growth based exclusively on the use of time series that will reproduce the histor� ical output dynamics with no less accuracy than the production function.

In the form in which the production function is used for long�term global economic forecasting, the following weaknesses can be identified in this model in terms of a complete set of factors of economic growth:

—Explaining changes in production specialization depth;

—Taking the impact of specialization on efficiency into account;

—Taking the impact of constraints on the depth of specialization into account;

—Taking crowding forward and backward com� munications between producers (especially between producers of intermediate goods) into account.

In the applied models used to develop long�term economic growth forecasts, the factor of specializa� tion can be considered by taking into account the product diversity. In other words, macroeconomic models should include the sector and product dimen� sions. The distinction of individual sectors is already present in the models designed based on the intersec� tor balance. In addition, models of the two� (three�) sector economy where individual sectors are described by production functions are well known. These models are inherently fairly close to the intersector balance model.

In general, the introduction of the sector dimen� sion in the model does not entail any difficulties (with the exception of a magnified problems of calculation);

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however, the product range of individual sectors is not considered under forecast constructions anyhow. Regardless of the extent to which sectoral and product diversity can be taken into account, the key issue is related to the consideration of new emerging indus� tries and products. In the long term, economic growth is always accompanied by the creation of new prod� ucts, as well as the emergence of new industries and markets, and their strong growth. Eventually, one pos� sible solution to this problem is the enrichment of sce� nario forecasts with the hypotheses about the emer� gence of new industries based on the available infor� mation about promising technologies.

Theoretical studies, which analyze the construc� tion of economic models that take the impact of spe� cialization on economic growth into account, approach the product diversity rather formally. Specif� ically, they postulate the existence of a certain number of industries (products), and the specification of the production function is designed in such a way that the production volume, along with the technological progress factor, depends on the diversity of produced (consumed) products as an additional factor.

Similarly to the theoretical studies, in practical cal� culations, the diversity (range) factor of products out� put (consumption) could be introduced into the pro� duction function by analogy with other factors. Add� ing the diversity factor of produced (consumed) products creates new demands with regard to the sta� tistical data used in calculations.

One strategy to finalize the production function is associated with the introduction of the intermediate product factor and the intermediate product diversity factor. The more diverse is the offer of intermediate goods, the lower are the costs of the final products [20]. A limited variety with incomplete interchange� ability of intermediate products will result in higher costs incurred by additional processing of intermedi� ate products.

In turn, the intermediate products can also be divided into two or more levels. For example, the first level, which is closest to the final product, is the level of components; the second level is formed by the raw material for the production of components. Accord� ingly, it would be fair to assume that, in case of inter� mediate products, a greater variety of intermediate products of the lower level entails the more efficient production of intermediate goods of the upper level. Ultimately, this may mean that the existence of a rich and diverse resource base is indispensable for enhanced specialization [20].

The inclusion of the industry dimension and the range of manufactured products into the model can help solve the second and the fourth problems speci� fied in the above list.

The most problematic issue is related to the formal� ization of changes in the degree of specialization. A general tendency of enhanced division of labor con�

sists in the displacement of manual labor by mecha� nized work or a complete replacement of manual work by equipment, where equipment of a new generation replaces more outdated equipment. The replacement of human labor by equipment and the emergence of new types of technology lead to longer production processes and an increasing contribution of the labor factor to the final product in indirect form. The mass introduction of new technologies that contribute to longer production methods requires the expansion of markets in order to ensure return on investment.

This means that long�term forecasting models of economic growth should describe the technological progress, including the following elements: R&D funding, the amount of accumulated knowledge, human potential in research and development, sus� ceptibility of producers to the emergence of new tech� nologies, and return on new technologies. The payoff criterion of new technologies that get into mass distri� bution allows one to formalize the third problem. If the new technology does not sufficiently reduce the production costs of the entire economy so that this particular technology is distributed on a mass scale (in other words, there is a sufficient demand for products manufactured by using new technology), further spe� cialization in this direction does not take place.

This approach does not allow one to directly for� malize the processes of enhanced specialization; nev� ertheless, this formalization of a link between the tech� nological progress (e.g., in the form of indirect mea� sures of material consumption) and the changing size of markets distributing the products manufactured with the help of new technologies makes it possible to take indirectly the changes in the level of specializa� tion into account.

* * *

The use of economic models is not unjustifiably becoming more common in decision�making at vari� ous levels. It is possible that the main advantage of the rich structural economic models that take the existing economic relations into account as much as possible lies in their ability to balance proposed development scenarios and targets against the existing resource con� straints. At the same time, the analysis of long�term forecasts and models applied for long�term global eco� nomic forecasting shows that the factors that, accord� ing to the classical economic theory, directly form the economic growth, are not accounted for in long�term forecasting. The functional relationship between out� put and production factors or elements of final demand and gross industry benchmarks in the models can help explain the economic growth as a result of the growing supply of factors, the intensity of their use or an increase in final demand. In turn, these compo� nents can be reduced to the dynamics of labor produc� tivity and technological progress, which are either specified exogenously or under an iterative solution

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method show a positive trend due to the values of the equation parameters.

This means that the results of economic modeling and, above all, the economic dynamics are implicitly or explicitly set by the forecast scenario conditions. In other words, the results of calculations are of a subor� dinate character in relation to the arguments and the logic underlying the development of the forecast sce� nario, which may depend on subjective reasons.

One could achieve more rigor in the validity of eco� nomic modeling results by taking into account the fac� tors of product diversity and enhanced specialization, as well as their relation to the technical progress and the size of markets in the designed models.

REFERENCES

1. A. Smit, An Inquiry into the Nature and Causes of the Wealth of Nations (EKSMO, Moscow, 2007) [in Rus� sian].

2. World Economic Outlook (International Monetary Fund, Washington, October 2013). Available at http://www.imf.org/external/pubs/ft/weo/2013/02/

3. The Conference Board Global Economic Outlook 2013. September 2013 Update. Available at https://www.conference�board.org/data/globaloutlook.cfm

4. D. Wilson, K. Trivedi, S. Carlson, and J. Ursú, The BRICs 10 Years On: Halfway. Through The Great Trans� formation, Available from Goldman Sachs Global Eco� nomics Paper, No. 208 (December, 7 2011). Available at http://blogs.univ�poitiers.fr/o�bouba�olga/files/2012/ 11/Goldman�Sachs�Global�Economics�Paper�208.pdf

5. J. Hawksworth, The World in 2050. How Big Will the Major Emerging Market Economies Get and How Can the OECD Compete? Available from PricewaterhouseCoopers LLP (March, 2006). Available at http://www.pwc.com/en_GX/gx/ world� 2050/pdf/world2050emergingeconomies.pdf

6. Looking to 2060: Long�Term Global Growth Prospects, Available from OECD Economic Policy Papers, No. 3 (Paris, November 2012). Available at http://www.oecd.org/eco/outlook/2060%20policy%2 0paper%20FINAL.pdf

7. Long�term Forecast of the Social�Economic Develop� ment of the Russian Federation until 2030, Available from the Ministry of Economic Development of the Russian Federation (Moscow, March 25, 2013) http://www.economy.gov.ru/wps/wcm/connect/eco nomylib4/mer/activity/sections/macro/prognoz/doc� 20130325_06

8. Frequently Asked Questions of the IMF World Eco� nomic Outlook http://www.imf.org/exter� nal/pubs/ft/weo/faq.htm#q1g

9. L. Ball, and N. G. Mankiw, “The NAIRU in theory and practice”, Journal of Economic Perspectives, No. 4, 16 (2002). Available at http://scholar.har� vard.edu/files/mankiw/files/jep.ballmankiw.pdf

10. A. M. Okun, “Potential GNP: its measurement and significance”, in Proceedings of the Business and Eco� nomics Statistics Section (American Statistical Associ�

ation, Alexandria, Virginia, 1962). Available at http://cowles.econ.yale.edu/P/cp/p01b/p0190.pdf

11. I. Carabenciov, Ch. Freedman, R. Garcia�Saltos, D. Laxton, O. Kamenik, and P. Manchev, GPM6 – The Global Projection Model with 6 Regions. Available from IMF working paper No. WP/13/87 (April 2013). Available at http://www.imf.org/exter� nal/pubs/ft/wp/2013/wp1387.pdf

12. V. Chen, B. Cheng, G. Levanon, A. Ozyildirim, and van Ark Bart, Projecting Global Growth, Available from The Conference Board, Economics Working Papers, EPWP #12 – 02 (November 2012). Available at http://www.conference�board.org/pdf_free/GEO2012_ Methodology.pdf

13. J. O’Neill and A. Stupnytska. The Long�Term Outlook for the BRICs and N�11 Post Crisis, Available from Goldman Sachs Global Economics Paper No. 192 (December, 4 2009). Available at http://www.gold� mansachs.com/our�thinking/archive/brics�at�8/brics� the�long�term�outlook.pdf

14. World Population Prospects, Available from United Nations, Department of Economic and Social Affairs, Population Division. Available at http://esa.un.org/unpd/ wpp/Excel�Data/popula� tion.htm; http://knoema.com/UNWPP2012R/ world� population�prospects�the�2012�revision�updated�13� june�2013

15. K. Hervé, N. Pain, P. Richardson, F. Sédillot and P.�O. Beffy. The OECD’S New Global Model, Available from OECD Economics Department Working Paper No. 768 (May 5, 2010). Available at http://search.oecd.org/officialdocuments/displaydoc� umentpdf/?doclanguage=en&cote=eco/wkp(2010)24

16. G. O. Kuranov and L. A. Strizhkova. “On the System of Methods and Models for the Development of Long� Term Forecast”, in Proceedings of the Round Table How to forecast in Russia? International Conference Gaidar Forum 2013 Russia and the World: Challenges of Integration (Russian Academy of Economy and Public Administration under the President of the Rus� sian Federation, Moscow, January 16�19, 2013). http://www.macroeconomics.ru/index.php/news/22� kak�prognoziruut�v�rossii

17. A. J. Cohen and G. C. Harcourt, “Whatever happened to the Cambridge capital theory controversies?”, Jour� nal of Economic Perspectives, No. 1, 17 (2003).

18. R. R. Nelson and S. G. Winter, Evolutionary Theory of Economic Changes (Delo, Moscow, 2002) [in Rus� sian].

19. A. M. Lavezzi, Division of Labor and Economic Growth: from Adam Smith to Paul Romer and Beyond (University of Pisa, 2001). Available at http://time.dufe.edu.cn/article/romer/5.pdf

20. A. Rodrfguez�Clare, “The division of labor and eco� nomic development”, Journal of Development Eco� nomics, No. 49 (1996). Available at http://www.isid.ac.in/~tridip/Teaching/DevEco/Rea dings/03Expectations/03RodriguezClareJDE1996.pdf

Gusev, Mikhail Sergeevich, Cand. Sci. (Ecom.), Head of Laboratory

Translated by V. Kupriyanova�Ashina

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.