**4. Research algorithm**

Methodological development offered by the author allows to overcome successfully listed problems and also develops the methodology of statistical research of regional investment appeal according to the concept of the Russian state statistics development, which makes them relevant not only for theory but also for the practice of statistical research of the invest-

The proposed methodological developments expand the methodology of Kaplan and Norton [10]. They allow realizing the monitoring of region investment policy on the basis of an integral statistical measure of the region investment appeal. The quantitative level of the integral statistical measure is the proportion of the number of completed relationships between the growth rates of the actual indicators characterizing a particular investigated object to the

The essence of the method of the dynamic standard is the formation in accordance with some objective (e.g., maximization of the company's profit, increasing the cost of equity, increasing regional investment appeal), groups of indicators characterizing the purpose and, to the greatest extent, reflecting the real state of the object of research in dynamics. The quantitative composition of the indicators should be no lower than the established (no less than 6 and no more than 25). The method of the dynamic standard is the procedure of selection of economic

The main idea of the method belongs to Syroezhin [11], it was further developed by his students [12]. It consists of the fact that not commensurable indicators in statics become com-

In modern scientific works and publications, there are examples of the application of the

Syroezhin noticed that noncomparable static characteristics of the national economy are comparable in dynamics. The proposed dynamic standard is organized by pace (coefficients, indexes) growth (or base chain) set (system) of indicators, such that maintaining for a longtime interval specified in a dynamic normative order of indicators provides the maximization of integral evaluation. Form of expression the ordering of the indicators is the ranking of performance (assigning grades), if not all indicators are able to link strictly in order, the presentation days to serve the count of preferences and/or the corresponding matrix of preferences, in this case, the integral meter has the form of a normative model. The quantitative level of the integrated meter (integrated assessment) in this case is the ratio of the number of performed correlations between growth rates (indices) of growth of actual indicators characterizing the specific object under study, to the number of set relations in a normative model. Accordingly, the resulting quantitative levels vary in the range from 0 to 1, the closer the value is to 1, the

The algorithm for constructing normative models is disclosed in detail in the work of Pohostinsky [18]. The normative model differs from the matrix of preferences and its indicators

ment regional situation, including in perspective of its development.

number of given ratios in the normative model.

52 Statistics - Growing Data Sets and Growing Demand for Statistics

**3. The method of the dynamic standard**

indicators and their ordering.

method of dynamic standard [13–17].

more quantitative is the valuation level.

mensurable in dynamics.

### **4.1. Step 1: indicators of region investment appeal**

The classical concept of "*investment appeal*" means the existence of certain investment conditions that affect the investor's goals and determine its choice when considering investment objects. The efficiency of the investment policy of the region is characterized by the degree of achievement of long-term goals of its development, the reproduction of the potential of the region and the growth of the quality of life of the population. Therefore, from our point of view, region investment appeal (RIA) is a complex of natural, geographical and socioeconomic factors that determine the effectiveness of the investment policy of the region and its socioeconomic development.

For the statistical research of investment appeal of Russian regions is proposed to use an integrated statistical indicator, which is based on measures that assess the "state of capacity development in the region" and the influence of the factors such as "the performance of business activities in the region" and "the performance of activities of public administration bodies in the region." **Figure 1** shows the structure of regional investment appeal. This interpretation is based on the scientific idea that the RIA is determined not only by the factors of the investment potential of the region, but also by the factors of the effectiveness of its investment policy.

Statistical estimation of the region potential is a traditional task of statistical measurement. The region potential includes components such as natural and geographical potential, property potential, financial potential, human potential and innovative potential. New for statistical measurement of its factors are "performance of government in the region" and "performance of business in the region."

**Figure 1.** The structure of the region investment appeal as an object of statistical study.

Statistical assessment and monitoring of these factors are new tasks of statistical research. Their solution requires improvement and refinement of the methodology of statistical research of RIA in the search for adequate scientific methods of assessment, the principles of the formation of its information basis.

The study of existing methods for estimating RIA (the methodology of the agency "Universe," the agency "Expert-RA" and others) made it possible to find out that a large number of statistical indicators are used for its construction. The solution of such a problem became possible in the framework of the system approach. Therefore, the region was considered by us as a socioeconomic system, and its investment attractiveness as its system-wide property, for the study of which a system of statistical indicators was formed. It consists of indicators that assess the potential and the results of the development of the region, which characterize the identified factors of the RIA. Absolute indicators selected in the system are presented in **Table 1**.

#### **4.2. Step 2: the normative model of region investment appeal**

The dynamic standard and the normative model of region investment appeal are presented in **Tables 2** and **3**. Formalization of the dynamic standard was tested using pairwise comparisons in accordance with targets of research (see **Table 2**). If, in accordance with the target installation rate in the row of the matrix needs to grow faster than the rate in the column below target was performed setting the "growth" that is put in matrix 1 at the intersection of row and column, while the symmetrical choice is −1. Otherwise, the −1, while the symmetric place puts 1. If relationship between the indicators is not set, then put a zero, the matrix diagonal has only zeros. Thus, in the matrix set 49 targets.

The matrix E is described as follows:

**Table 1.** Absolute indicators of RIA (Pi).

**No. Indicator name**

1 Population in the region

2 Value of fixed assets in the region

5 Investments in fixed assets (Capex)

10 Gross regional product (GRP)

3 Residual value of fixed assets of the region

 *Number of employed in the economy of the region* Incomes of the population of the region Total number of unemployed in the region Fund for remuneration of workers in the region

11 Tax revenues of the consolidated budget of the region 12 Revenues of the consolidated budget of the region 13 Expenditures of the consolidated budget of the region

14 Balanced financial performance of organizations in the region 15 Number of employees employed in small enterprises in the region

4 Internal costs for research and development of the region

*Factor "Potential for development of the region"*

*Factor "Performance of government in the region"*

*Factor "Performance of business in the region"*

⎧ ⎪ ⎨ ⎪ ⎩

16 Number of small enterprises in the region 17 Number of organizations in the region

1, if GR(Pi

18 The number of unprofitable organizations in the region

−1, if GR(Pi

GR(Pi

) > GR(Pj) ;

) < GR(Pj) ; <sup>0</sup>, if the reference

ratio between

where i, j are the numbers of indicators in DS; Pi, Pj are indicators having the i-th and j-th numbers in DS, respectively; GR(Pi) > GR (Pj) and GR (Pi) < GR (Pj) are reference of ratio

)and GR(Pj),

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55

(1)

eij

between rates (indices) of growth.

Formally, the dynamic standard of preferences is set by a matrix (Е = {еij}nxn), each element of which reflects the normative relation between performance (faster/slower) of the row and column of the matrix (see **Table 2**).


**Table 1.** Absolute indicators of RIA (Pi).

Statistical assessment and monitoring of these factors are new tasks of statistical research. Their solution requires improvement and refinement of the methodology of statistical research of RIA in the search for adequate scientific methods of assessment, the principles of

The study of existing methods for estimating RIA (the methodology of the agency "Universe," the agency "Expert-RA" and others) made it possible to find out that a large number of statistical indicators are used for its construction. The solution of such a problem became possible in the framework of the system approach. Therefore, the region was considered by us as a socioeconomic system, and its investment attractiveness as its system-wide property, for the study of which a system of statistical indicators was formed. It consists of indicators that assess the potential and the results of the development of the region, which characterize the identified

factors of the RIA. Absolute indicators selected in the system are presented in **Table 1**.

The dynamic standard and the normative model of region investment appeal are presented in **Tables 2** and **3**. Formalization of the dynamic standard was tested using pairwise comparisons in accordance with targets of research (see **Table 2**). If, in accordance with the target installation rate in the row of the matrix needs to grow faster than the rate in the column below target was performed setting the "growth" that is put in matrix 1 at the intersection of row and column, while the symmetrical choice is −1. Otherwise, the −1, while the symmetric place puts 1. If relationship between the indicators is not set, then put a zero, the matrix diago-

of which reflects the normative relation between performance (faster/slower) of the row and

}nxn), each element

**4.2. Step 2: the normative model of region investment appeal**

**Figure 1.** The structure of the region investment appeal as an object of statistical study.

nal has only zeros. Thus, in the matrix set 49 targets.

column of the matrix (see **Table 2**).

Formally, the dynamic standard of preferences is set by a matrix (Е = {еij

the formation of its information basis.

54 Statistics - Growing Data Sets and Growing Demand for Statistics

The matrix E is described as follows:

$$\begin{cases} \text{1, if } \text{GR(P\_{\downarrow})} > \text{GR(P\_{\downarrow})} \; ; \\ \text{-1, if } \text{GR(P\_{\downarrow})} < \text{GR(P\_{\downarrow})} \; ; \\ \quad \text{0, if the reference} \\ \quad \text{ratio between} \\ \text{GR(P\_{\downarrow})} \text{and } \text{GR(P\_{\downarrow})} . \end{cases} \tag{1}$$

where i, j are the numbers of indicators in DS; Pi, Pj are indicators having the i-th and j-th numbers in DS, respectively; GR(Pi) > GR (Pj) and GR (Pi) < GR (Pj) are reference of ratio between rates (indices) of growth.


Thus, formed matrix E, after identifying additional relationships, is a normative model

Reflection of the results of the adopted and implemented managerial decisions is the actual relation matrix of indicators Pi. The closer the actual ordering of the indices to a given normative order in the model, the higher is the level of region investment attractiveness. The matrix of actual correlations of growth performance (F = {fij}nxn) is described

) > *GR*(P*j*) ;

) = *GR*(*Pj*),

) <sup>&</sup>lt; *GR*(*Pj*)

1, *if eij* = 1 *simultaneously with f*

*or if eij* <sup>=</sup> −1 *simultaneously with <sup>f</sup>*

0, *otherwise*

*ij* ≥ 0 ;

*ij* ≤ 0)

(4)

*ij* ≤ 0 ;

*ij* ≥ 0) *or* (*eij* = −1 *and f*

<sup>0</sup>, *if others case*

;

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(2)

57

(3)

(**Table 3**).

as follows:

respectively.

y =

Δ*Y*(*Pi*

where ΔY(P<sup>i</sup>

of indicators; b0

) = ∑ *j*=1 *n bij* <sup>0</sup> − ∑ *j*=1 *n bij b*

\_\_\_\_\_\_\_\_\_\_\_\_ ∑ *i*=1 *n* ∑ *j*=1 *n* ∣ *eij* ∣

ij, bb

*f*

∑ *i*=1 *n* ∑ *j*=1 *n bij* \_\_\_\_\_\_\_\_\_\_\_\_ ∑ *i*=1 *n* ∑ *j*=1 *n* ∣ *eij* ∣

*ij*

where *bij*

element of the matrix NM, fij is the element of the matrix F = {fij}nxn.

on Y growth, which is the effective rate, determined by the formula:

and *bij*{

relationships between indicators implemented in reality.

⎧ ⎪ ⎨ ⎪ ⎩ **1**, *if GR*(*Pi*

−**1**, *if GR*(*Pi*

**0**, *if GR*(*Pi*

actual and normative models set in order the rates (indices) of growth indicators (Y).

⎧ ⎪ ⎨ ⎪ ⎩

where i, j are the numbers of indicators; Pi, Pj are indicators having the i-th and j-th numbers, respectively; GR(Pi), GR (Pj) are actual rate (index) of growth of the ith and jth indicators,

An integrated assessment of region investment attractiveness is the estimation of proximity of

n is the number of indicators in DD; i, j are the numbers of indicators in DD; bij is the element of the matrix of coincidence of actual and reference ratios of growth rates (В = {bij}nxn); еij is the

Score Y varies from 0 to 1. Equal to 1, if all regulations set the ratio of the rate of improvement is actually implemented. Equal to 0, if the actual order of indices is opposite to the normative order of indicators in the model. The closer Y is to 1, the greater is the proportion of regulatory

The generated model can be considered as the factor system. The influence of each indicator

1, *if*(*eij* = 1 *and f*

growth rate of the ith indicator with others; n is the number of indicators; i, j are the numbers

) is the increase in the assessment caused by the dynamics of the ratio of the

ij are the elements of the matrix of coincidence of actual and reference

**Table 2.** The dynamic standard (DS) of region investment attractiveness.

Thus, formed matrix E, after identifying additional relationships, is a normative model (**Table 3**).

**No and indicator name** 

3. Number of employed in the economy of the region

4. Number of employees employed in small enterprises in the region

6. Fund for remuneration of workers in the region

8. Value of fixed assets in

9. Residual value of fixed assets of the region

unprofitable organizations

13. Internal costs for research and development

15. Balanced financial performance of organizations in the

16. Tax revenues of the consolidated budget of

17. Revenues of the consolidated budget of

18. Expenditures of the consolidated budget of

**Table 2.** The dynamic standard (DS) of region investment attractiveness.

10. Number of small enterprises in the region

11. Number of organizations in the

12. Number of

in the region

of the region

region

the region

the region

the region

region

the region

5. Total number of unemployed in the region

1. Population in the

2. Incomes of the population of the region **No indicator in DS**

56 Statistics - Growing Data Sets and Growing Demand for Statistics

**1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18**

0 −1 −1 −1 0 0 −1 −1 −1 −1 −1 0 −1 −1 0 0 −1 1

1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0

1 0 0 −1 1 −1 −1 −1 −1 0 0 0 0 −1 0 0 −1 0

1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0

0 0 −1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 −1 1 0 0 0 −1 0 0 0 −1 0 0 0 −1 0 0 0

1 0 1 0 0 0 −1 0 −1 0 1 0 0 −1 0 0 0 0

1 0 1 0 0 0 −1 1 0 0 1 0 0 −1 0 0 0 0

1 0 0 −1 0 0 0 0 0 0 1 0 0 0 0 0 0 0

1 0 0 0 0 1 0 −1 −1 −1 0 1 −1 −1 −1 1 0 0

0 0 0 0 0 0 0 0 0 0 −1 0 0 0 0 0 0 0

1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0

0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 0 0

0 −1 0 0 0 0 −1 0 0 0 −1 0 0 0 0 0 1 1

1 0 1 0 0 0 −1 0 0 0 0 0 0 0 0 −1 0 1

−1 0 0 0 0 0 −1 0 0 0 0 0 0 0 0 −1 −1 0

7.GRP 1 0 1 0 0 1 0 1 1 0 0 0 −1 1 −1 1 1 1

14.Capex 1 0 1 0 0 0 −1 1 1 0 1 0 0 0 −1 0 0 0

**in DS, Pi**

region

Reflection of the results of the adopted and implemented managerial decisions is the actual relation matrix of indicators Pi. The closer the actual ordering of the indices to a given normative order in the model, the higher is the level of region investment attractiveness. The matrix of actual correlations of growth performance (F = {fij}nxn) is described as follows:

as 1010Ws: 
$$f\_{\boldsymbol{\psi}} \begin{cases} \mathbf{1}, \boldsymbol{\text{if}} \, \text{GR}(\boldsymbol{\text{P}}\_{\boldsymbol{\text{i}}}) > \text{GR}(\boldsymbol{\text{P}}\_{\boldsymbol{\text{i}}}) \; ; \\ \mathbf{-1}, \boldsymbol{\text{if}} \, \text{GR}(\boldsymbol{\text{P}}\_{\boldsymbol{\text{i}}}) < \text{GR}(\boldsymbol{\text{P}}\_{\boldsymbol{\text{i}}}) \; ; \\ \mathbf{0}, \boldsymbol{\text{if}} \, \text{GR}(\boldsymbol{\text{P}}\_{\boldsymbol{\text{i}}}) = \text{GR}(\boldsymbol{\text{P}}\_{\boldsymbol{\text{i}}}) \; \end{cases} \tag{2}$$

where i, j are the numbers of indicators; Pi, Pj are indicators having the i-th and j-th numbers, respectively; GR(Pi), GR (Pj) are actual rate (index) of growth of the ith and jth indicators, respectively.

An integrated assessment of region investment attractiveness is the estimation of proximity of actual and normative models set in order the rates (indices) of growth indicators (Y).

$$\mathbf{y} = \frac{\sum\_{i=1}^{k} b\_i}{\sum\_{i=1}^{k} |\boldsymbol{e}\_{i\cdot}|} \\ \text{where } b\_{\boldsymbol{\eta}} \text{ where } b\_{\boldsymbol{\eta}} \text{ if } \boldsymbol{e}\_{\boldsymbol{\eta}} = \boldsymbol{1} \text{ simultaneously with } f\_{\boldsymbol{\eta}} \ge \boldsymbol{0} \text{ ;} \\ \text{where } \begin{cases} \mathbf{1}, \text{if } \boldsymbol{e}\_{\boldsymbol{\eta}} = \mathbf{1} \text{ simultaneously with } f\_{\boldsymbol{\eta}} \ge \boldsymbol{0} \text{ ;} \\ \text{if } \boldsymbol{e}\_{\boldsymbol{\eta}} = -\mathbf{1} \text{ simultaneously with } f\_{\boldsymbol{\eta}} \le \mathbf{0} \text{ ;} \\ \mathbf{0}, \text{ otherwise} \end{cases} \tag{3}$$

n is the number of indicators in DD; i, j are the numbers of indicators in DD; bij is the element of the matrix of coincidence of actual and reference ratios of growth rates (В = {bij}nxn); еij is the element of the matrix NM, fij is the element of the matrix F = {fij}nxn.

Score Y varies from 0 to 1. Equal to 1, if all regulations set the ratio of the rate of improvement is actually implemented. Equal to 0, if the actual order of indices is opposite to the normative order of indicators in the model. The closer Y is to 1, the greater is the proportion of regulatory relationships between indicators implemented in reality.

The generated model can be considered as the factor system. The influence of each indicator on Y growth, which is the effective rate, determined by the formula:

$$\begin{array}{l}\text{Ohm I'z groowhu, wenn is une eneunve } \mathbf{1ae}; \text{ une\'eunnneu dy une norma.}\\\Delta Y[P\_{\rangle}] = \sum\_{i=1}^{\tilde{\mathbf{e}}} b\_{\tilde{\mathbf{e}}}^{\tilde{\mathbf{e}}} - \sum\_{j=1}^{\tilde{\mathbf{e}}} b\_{\tilde{\mathbf{e}}}^{\tilde{\mathbf{e}}} \\\ \frac{1}{\sum\_{i=1}^{\tilde{\mathbf{n}}} |\\_{\tilde{\mathbf{e}}\_{\tilde{\mathbf{e}}}}}{|\!|} \quad \text{and} \quad b\_{\tilde{\mathbf{e}}} \begin{cases} 1, & \text{if} \{e\_{\tilde{\mathbf{e}}} = 1 \text{ and } f\_{\tilde{\mathbf{e}}} \ge 0 \} \text{ or } \{e\_{\tilde{\mathbf{e}}} = -1 \text{ and } f\_{\tilde{\mathbf{e}}} \le 0\} \\\ 0, & \text{if others} \end{cases} \end{array} \tag{4}$$

where ΔY(P<sup>i</sup> ) is the increase in the assessment caused by the dynamics of the ratio of the growth rate of the ith indicator with others; n is the number of indicators; i, j are the numbers of indicators; b0 ij, bb ij are the elements of the matrix of coincidence of actual and reference


ratios of rates (indices) of growth in current and base periods, respectively; еij is the matrix

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In this chapter, the presented results allow to claim that the proposed methodological developments can be applied to a large variety of tasks related to the monitoring of development strategies of regions and other objects of strategic planning. The decline in balance performance or growth with their help received a quantitative rating, which in turn allows you to implement monitoring of investment strategy in the tactical period. This methodology does not require serious mathematical tools; however, if growth of indicators is necessary to apply automated processing for calculation of the estimates, so the author used her own computer program and implemented the development of regulatory models for integrating quantitative evaluations of the investment attractiveness of the region, the city and municipal district.

As the periods of research are selected: 2001–2007 (base period) and 2009–2015 (reporting period) as well as chain dynamics for 2009–2015. The choice of study periods for the baseline dynamics is due to the fact that in 2006–2007, Russia and its regions were given an investment rating by international agencies. The sense of the reporting period is that this was the period when the regions of Russia left the financial crisis and actively attracted foreign investments,

**Tables 4** and **5** show the quantitative levels of investment attractiveness of regions—leaders

Thus, the imposition of sanctions in 2014 significantly affected the investment climate of the Kaluga region, since its economy is more dependent on the activities of foreign investors. For the Tula, Voronezh and Moscow regions, Moscow and Russia in general, the sanctions played

**Regions Y ΔY National rating of investment** 

**attractiveness of regions in 2015 2001–2007 2009–2015**

element of the reference relationships between the growth indicators.

and implemented a large number of investment projects.

in Russia, calculated according to the author's algorithm.

Tula region 0.57 0.79 0.22 2 Russia 0.69 0.76 0.08 — Voronezh region 0.52 0.76 0.24 4 Moscow region 0.61 0.66 0.05 5 Kaluga region 0.65 0.61 −0.04 1 Moscow 0.69 0.52 −0.17 3

**Table 4.** Quantitative levels of investment attractiveness of regions.

**4.3. Step 3: Calculations**

**5. Results**

a stimulating role.

**Table 3.** The normative model of region investment appeal.

ratios of rates (indices) of growth in current and base periods, respectively; еij is the matrix element of the reference relationships between the growth indicators.

#### **4.3. Step 3: Calculations**

**No and indicator name** 

3. Number of employed in the economy of the region

4. Number of employees employed in small enterprises in the region

6. Fund for remuneration of workers in the region

8. Value of fixed assets in

9. Residual value of fixed assets of the region

unprofitable organizations

13. Internal costs for research and development

15. Balanced financial performance of organizations in the

16. Tax revenues of the consolidated budget of

17. Revenues of the consolidated budget of

18. Expenditures of the consolidated budget of

**Table 3.** The normative model of region investment appeal.

10. Number of small enterprises in the region

11. Number of organizations in the

12. Number of

in the region

of the region

region

the region

the region

the region

region

the region

5. Total number of unemployed in the region

1. Population in the

2. Incomes of the population of the region **No indicator in DS**

58 Statistics - Growing Data Sets and Growing Demand for Statistics

**1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18**

0 −1 −1 −1 0 −1 −1 −1 −1 −1 −1 0 −1 −1 −1 −1 −1 1

1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1 1 1

1 −1 0 −1 1 −1 −1 −1 −1 −1 −1 0 −1 −1 −1 −1 −1 1

1 0 1 0 1 1 0 0 0 1 1 1 0 0 0 1 1 1

0 −1 −1 −1 0 −1 −1 −1 −1 −1 −1 0 −1 −1 −1 −1 −1 0

1 −1 1 −1 1 0 −1 −1 −1 −1 −1 0 −1 −1 −1 0 0 1

1 0 1 0 1 1 −1 0 −1 0 1 1 −1 −1 −1 1 1 1

1 0 1 0 1 1 −1 1 0 0 1 1 −1 −1 −1 1 1 1

1 0 1 −1 1 1 0 0 0 0 1 1 0 0 0 1 1 1

1 0 1 −1 1 1 −1 −1 −1 −1 0 1 −1 −1 −1 1 1 1

0 0 0 −1 0 0 −1 −1 −1 −1 −1 0 −1 −1 −1 0 0 0

1 0 1 0 1 1 1 1 1 0 1 1 0 1 0 1 1 1

1 0 1 0 1 1 1 1 1 0 1 1 0 1 0 1 1 1

1 −1 1 −1 1 0 −1 −1 −1 −1 −1 0 −1 −1 −1 0 1 1

1 −1 1 −1 1 0 −1 −1 −1 −1 −1 0 −1 −1 −1 −1 0 1

−1 −1 −1 −1 0 −1 −1 −1 −1 −1 −1 0 −1 −1 −1 −1 −1 0

7.GRP 1 0 1 0 1 1 0 1 1 0 1 1 −1 1 −1 1 1 1

14.Capex 1 0 1 0 1 1 −1 1 1 0 1 1 −1 0 −1 1 1 1

**in DS, Pi**

region

In this chapter, the presented results allow to claim that the proposed methodological developments can be applied to a large variety of tasks related to the monitoring of development strategies of regions and other objects of strategic planning. The decline in balance performance or growth with their help received a quantitative rating, which in turn allows you to implement monitoring of investment strategy in the tactical period. This methodology does not require serious mathematical tools; however, if growth of indicators is necessary to apply automated processing for calculation of the estimates, so the author used her own computer program and implemented the development of regulatory models for integrating quantitative evaluations of the investment attractiveness of the region, the city and municipal district.
