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National Research University Higher School of Economics

Saint Petersburg University - Graduate School of Management

Global Entrepreneurship Monitor 2011 in Russian Federation

National Report on Entrepreneurship in Russia in 2011

Moscow - Saint Petersburg2012

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National Report on Entrepreneurship in Russia in 2011 is prepared by Russian GEM Team. Team Leader, National Research University Higher School of Economics

Chepurenko Alexander

Team Members:National Research University Higher School of Economics

Obraztsova Olga Alimova TatianaGabelko MariaMurzacheva EkaterinaPopovskaya Ekaterina

Saint Petersburg University - Graduate School of ManagementVerkhovskaya OlgaDorokhina MariaShirokova Galina

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Acknowledgements

We gratefully acknowledge the support of the GEM Team, and especially Jonathan Levie, Niels Bosma, Yana Litovsky and Chris Aylett, for their support during the course of the 2011 cycle.

In particularly, the team of GEM RUSSIA is indebted to Sponsoring Institutions as National Research University Higher School of Economics and (SPb) for their financial supports for GEM Russia.

We also thanks the Analytical Levada Center that has held 2011 Russia GEM Adult Population Survey in Russian Federation

GEM Team Russia 2011

DisclaimerThe National Report is based on data collected by the GEM consortium and the GEM Russia Team. Responsibility for statistical and analytical work on the datasets and interpretation of those data is the sole responsibility of the authors.

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Contents

Introduction.....................................................................................................................................51. National Executive Summary 2011 - GEM Russia...............................................................102. Russian Entrepreneurship in a GEM Global Context................................................................173. Review of Macroeconomic Statistics for Russia in 2011..........................................................244. Adult Population Survey of GEM in Russian Federation.........................................................285. Entrepreneurial Activity of Russian Adult Population in 2011.................................................29

Socio-Demographic Structure of Entrepreneurially Active Population.......................................30Dynamics of the Motivational Structure of Early Entrepreneurship in 2006–2011....................34Motivational Structure of Early-Stage Entrepreneurship in Russia in 2011...............................35Demographic, Social and Economic Characteristics of Opportunity-Driven and Necessity-Driven Early-Stage Entrepreneurs in 2011...................................................................................35Brief Conclusions..........................................................................................................................36

6. Dynamics of Russian Entrepreneurship Innovation Activity Characteristics in 2006–2011....377. Business Discontinuance: Forms and Factors...........................................................................40

Brief Conclusions..........................................................................................................................448. Specifics of Entrepreneurial Activity by Settlement Type........................................................449. Entrepreneurship Framework Conditions in the Russian Federation: Population’s Opinions and Expert Reponses............................................................................................................................46

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Introduction

In 2011, Russian economy was characterized by some contradictory trends – surviving after the recent economic slowdown of 2008-2009, on the one hand, but showing decreasing economic dynamic, on the other.

In the times like these, marked by significant changes in the economic landscape, it becomes clear that the understanding of the relationship between entrepreneurship and development is still far from complete. The quest to unravel the complex relationship has been particularly hampered by a lack of cross-national harmonized data sets on entrepreneurship. Since 1997, the GEM Research program has sought to address this by collecting relevant harmonized data on an annual basis. GEM focuses on three main objectives:

• To measure differences in the level of entrepreneurial activity among countries • To uncover factors determining national levels of entrepreneurial activity • To identify policies that may enhance national level of entrepreneurial activity

Traditional analyses of economic growth and competitiveness have tended to neglect the role played by new and small firms in the economy. GEM takes a comprehensive approach and considers the degree of involvement in entrepreneurial activity within a country, identifying different types and phases of entrepreneurship.

While as a first step the first GEM reports included high income countries only, the ambition has always been to include as many countries as possible in order to present policy makers with helpful directions in their efforts to stimulate economic development through entrepreneurial activity. The participation of a Russian team in the GEM Consortium made it possible to collect data for Russia on the level of development and the structure of entrepreneurial potential that are comparable to analogous indicators in other countries participating in the GEM. This year GEM has made a significant step in this direction. In the 2011th annual national report, we present the results of GEM research that has been conducted in 2011 in Russian Federation as a country with a high variation in terms of economic development among its different regions.

According to international statistical standards, three major phases of economic development are recognized: factor-driven economics, which are primarily extractive in nature, efficiency-driven economics in which scale-intensity is a major driver of development, and innovation-driven economicsi. As country develops economically, it tends to shift from one phase to the next.

There is wide agreement on the importance of entrepreneurship for economic developmentii. Entrepreneurs drive and shape innovation, they speed up structural changes in the economy, and they force old incumbent companies to shape up their act, thereby making an indirect contribution to productivity.

While important, the contribution of entrepreneurs to an economy also varies according to its phase of economic developmentiii. As previous GEM reports have shown, the level of necessity-driven self-employment activity is high particularly at low levels of economic development, as the economy may not be able to sustain a high enough number of jobs in high-productivity sectors. As an economy develops, the level of necessity-driven entrepreneurial activity gradually declines as productive sectors grow and supply more employment opportunities. At the same time, opportunity-driven entrepreneurial activity tends to pick up, introducing a qualitative change in overall entrepreneurial activity.

Economic development consists of changes in the quantity and character of economic value added (Lewis, 1954). These changes result in greater productivity and rising per-capita incomes, and they often coincide with migration of labor across different economic sectors in the society, for

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example from primary and extractive sectors to the manufacturing sector, and eventually, services (Gries & Naude, 2008). Country with low level of economic development typically has a large agricultural sector, which provides subsistence for the majority of population who mostly still live in the countryside. This situation changes as industrial activity starts to develop, often around the extraction of natural resources. As extractive industry starts to develop, this triggers economic growth, prompting surplus population from agriculture to migrate toward extractive and emergent scale-intensive sectors, which are often located in specific regions. The resulting oversupply of labor feeds subsistence entrepreneurship in regional agglomerations, as surplus workers seek to create self-employment opportunities in order to make a living.

As the industrial sector develops further, institutions start to emerge to support further industrialization and the build-up of scale in the pursuit of higher productivity through economies of scale. Typically, national economic policies in scale-intensive economies shape their emerging economic and financial institutions to favor large national businesses. As increasing economic productivity contributes to financial capital formation, niches may open in industrial supply chains that service these national incumbents. This, combined with the opening up of independent supply of financial capital from the emerging banking sector, would spur opportunities for the development of small-scale and medium-sized manufacturing sectors. Thus, in a scale-intensive economy, one would expect necessity-driven industrial activity to gradually fall and give way to an emerging small-scale manufacturing sector.

As an economy matures and its wealth increases, one may expect the emphasis in industrial activity to gradually shift toward an expanding service sector that caters to the needs of an increasingly affluent population and supplies the services normally expected of a high-income society. The industrial sector evolves and experiences improvements in variety and sophistication. Such a development would be typically associated with increasing Research & Development and knowledge intensity, as knowledge-generating institutions in the economy gain momentum. This development opens the way for the development of innovative, opportunity-seeking entrepreneurial activity that is not afraid to challenge established incumbents in the economy. Often, small and innovative entrepreneurial firms enjoy an innovation productivity advantage over large incumbents, enabling them to operate as ‘agents of creative destruction.’ To the extent that the economic and financial institutions created during the scale-intensive phase of the economy are able to accommodate and support opportunity-seeking entrepreneurial activity, innovative entrepreneurial firms may emerge as significant drivers of economic growth and wealth creation (Henrekson, 2005).

Given the different nature of entrepreneurial activities and its role for economic development, national policy makers will need to prioritize their socio-economic programs given the context of their country. Figure 1 provides a very rough scheme of priorities for each major phase of economic developmentiv. Whereas enabling entrepreneurship in factor-driven economies may certainly be a good policy, it is unlikely to sort out substantial improvements in terms of wealth creation if basic requirements are in bad shape. Entrepreneurs with high aspirations fare better in countries with a stable economic and political climate and well-developed institutions (in fact they may migrate to other countries for pursuing their ideas). Thus, enhancing basic requirements should be the key focus of governments in developing countries in their aims to make the transition to the next phase; it would lead to a more sustainable environment for entrepreneurs. In other words, entrepreneurship should certainly not be discouraged but improving the entrepreneurial framework conditions should perhaps not attract too many financial resources in this phase of economic development. At the other end of the spectrum, policy-makers in some of the most-advanced countries do well in stimulating the entrepreneurial framework conditions, making their economy more dynamic and innovation-oriented. However, they should not forget about the state of basic requirements and efficiency-enhancers.

Figure 1 illustrates the GEM conceptual model of the institutional environment and its impact on entrepreneurship. As this figure shows, two sets of conditions, basic requirements and efficiency enhancers, are foundation conditions that influence the way a society functions and the wellbeing of

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its people. These have been adopted from the World Economic Forum’s (WEF) Global Competitiveness Report.1 They are general framework conditions that impact economic activity more generally. But they are critical to entrepreneurship because, without a solid institutional foundation, the entrepreneurship-specific factors cannot function effectively.

The entrepreneurship-specific conditions are represented in nine entrepreneurship framework conditions (EFC). Information on these is collected through a national expert survey (NES) conducted by GEM national teams. The determinants of entrepreneurship are complex and not well understood to the extent that specific variables can be tied to the rate or profile of entrepreneurship in a particular economy. The institutional environment, however, is of critical significance to the study of entrepreneurship because it can represent conditions that entrepreneurs must navigate and levers that policy makers can address.

Figure 1: The institutional context and its relationship to entrepreneurship

Social, Cultural,Political Context

Basic requirements

- Institutions- Infrastructure- Macroeconomic stability- Health and primary

educationEstablished Firms

Socio-Economic Development

(Jobs, Innovation, Social value)

Efficiency enhancers

- Higher education & training

- Goods market efficiency- Labor market efficiency- Financial market

sophistication- Technological readiness- Market size

Innovation and entrepreneurship

- Entrepreneurial finance- Government policy- Government

entrepreneurship programs

- Entrepreneurship education

- R&D transfer- Internal market openness- Physical infrastructure for

entrepreneurship- Commercial, legal

infrastructure for entrepreneurship

- Cultural and social norms

Attitudes:Perceived opportunities & capabilities; Fear of Failure; Status of entrepreneurship

Aspirations:Growth, InnovationInternational orientationSocial value creation

Activity:Opportunity/Necessity-driven, Early-stage; Inclusiveness; Industry; Exits

Entrepreneurship Profile

From other available sources Employee

Entrepreneurial Activity

From GEM National ExpertSurveys (NES)

From GEM Adult PopulationSurveys (APS)

From GEM 2011 Adult Population Surveys (APS)

The Phases and Profile of Entrepreneurship GEM recognizes that an economy’s prosperity is highly dependent on a dynamic entrepreneurship sector. This is true across all stages of development. Yet the rate and profile of entrepreneurs varies considerably. Figure 2 illustrates the GEM measures across phases of entrepreneurial activity, with an added emphasis on profile factors.

Figure 2 - The entrepreneurship process and GEM operational definitions

1 Schwab, Klaus, ed. The Global Competitiveness Report 2011–2012. Geneva: World Economic Forum, 2011.

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Potential Entrepreneurs: beliefs and abilities

Nascent Established New

Entrepreneurship Phases

Intentions

Entrepreneurship Profile Inclusiveness

Sex Age

Impact Business growth Innovation Internationalization

Industry Sector

Discontinuance

(TEA) Total Early-Stage Entrepreneurial Activity

PhasesGEM represents entrepreneurship as occurring in phases. Because the conditions impacting entrepreneurship in different societies are diverse, complex, and interdependent, it is difficult to state that one phase necessarily leads to another. For example, a society with many potential entrepreneurs may have a low rate of entrepreneurial activity due to particular environmental constraints. Consequently, the arrow connecting the phases is uneven to remind us that the relationship is not definitive.

It is therefore important to focus, not just on one single indicator, but to look at patterns across the phases in order to assess the state of entrepreneurship for an economy. For example, an economy with a low number of established business owners may also have few individuals starting new businesses and therefore a low supply of entrepreneurs that could otherwise become business owners. At the same time, a lot of startup activity accompanied by a relatively low number of established businesses could point to either a lack of sustainability of these startups or environmental constraints that make it difficult to stay in business over time.

The phases identified in Figure 2 start out with potential entrepreneurs: those that see opportunities in their area and believe they have the capabilities to start businesses. Other beliefs include the extent they are undeterred by fear of failure when they recognize opportunities. In addition, the broader society can influence entrepreneurship with perceptions about entrepreneurship as a career choice, the status of entrepreneurs in society and how they are represented in the media.

The cycle continues as intent to start a business is followed by nascent activity, represented as those in the process of starting a business less than three months old. New business owners are former nascent entrepreneurs, who have been in business more than three months, but less than three and a half years. Together, nascent and new entrepreneurs compose total early-stage entrepreneurial activity (TEA).

Additional phases include established business ownership as well as business discontinuation, which can supply society with experienced entrepreneurs that may go on to start another business or to use their expertise and resources to benefit entrepreneurs in some way (by financing, advising, or other forms of support).

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ProfileGEM emphasizes that it is not enough to study only the numbers of entrepreneurs, and to compare numbers with other economies. The profile of entrepreneurship--the individuals participating in this activity—differs considerably across economies.

First, the full potential of a society’s entrepreneurial human resources is more likely to be realized when entrepreneurship is inclusive, that is, available to all people in a society, like women and young people. Second, entrepreneurs will differ in terms of the sector in which they start businesses (consumer, extractive, manufacturing, business services). Finally, entrepreneurs impact their societies through their innovativeness, their international reach, and their growth ambitions.

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1. National Executive Summary 2011 - GEM Russia

General Characteristics* GEM 2011 Entrepreneurship Indicators*

Population (x 1,000): 142,958 Perceived Opportunities 27

Area (x 1,000 km2): 16,377 Perceived Capabilities 33

Density (persons / km2): 8.4 Fear of Failure 46

GDP Per Capita (PPP): 16,687 Human Development Index for Entrepreneurshiop (HDIE Index)

0.044(76/79)

Nascent Entrepreneurship Rate: 2.4

Global Happiness Index: 5.5 (91/149)

Owner-Managers in New Businesses Rate:

2.3

Human Development Index:

0.76 (66/187)

Owner-Managers in Established Businesses Rate:

2.8

Total early-stage Entrepreneurial Activity Rate (TEA):

4.6

Global Competitiveness Index:

4.2 (66/142)

- Necessity-Driven TEA Rate: 1.2

Global Innovation Index: 36 (56/125)

- Medium-High Job Expectation Rate: (MHEA)

2.0

Doing Business Index: (120/183) Entrepreneurial Employee Activity Rate (EEA):

0.4

GEDI Index: 0.18 (62/79)

- Private Sector EEA Rate (PEEA): 0.4

Classification Phase of Economic Development:

Efficiency-Driven Economies

Classification Entrepreneurship Profile

Low overall entrepreneurial activity (low SLEA, MHEA and EEA)

* For definitions and sources of the indicators, see the next part of this Report

The main obstacles for the development of entrepreneurial activity in Russia are: lack of juridical security, bribes and corruption connected with decreasing but still relatively high administrative barriers, lack of transparent and stable state policy on federal and regional level, huge differences in the level of entrepreneurial activity between Russian regions.

After some years of absence of any state activity on the field of entrepreneurship support (2000-2005) a new Program of SME support is now governed.

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Entrepreneurial Profile

Note: Medium-High Job Expectation TEA and Solo & Low Job Expectation TEA are based on GEM 2009-2011 APS data, all other indicators based on GEM 2011 APS data. Values of group level indicators are based on averaging the country-level Z-scores (standardized values obtained from the entire GEM 2011 sample).

The profile of entrepreneurial activity in Russia differs both from efficiency driven economies and even from countries with low overall entrepreneurial activity – it is in general more negative. Only the level of perceived opportunities is some higher than in countries with low overall entrepreneurial activity, and the level of medium-high job expectation is in line with the indicator of this group as a whole. A relative advantage of Russian entrepreneurial activity is a very low level of necessity driven entrepreneurial activity.

Entrepreneurship Institution Profile

Note: Based on GEM 2011 NES data. Values of group level indicators are based on averaging the country-level Z-scores (standardized values obtained from the entire GEM 2011 sample).

According to experts, Russian entrepreneurs have a relatively high level of human capital; despite the general agenda of state policy towards entrepreneurship seems to be adequate, the over-regulation

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and lack of governmental programs, scarce external funding are the most critical points. Bad physical infrastructure, problems with market entry and low socio-cultural embeddedness of entrepreneurship mark the state of EFC in Russia.

Sector Structure Total early-stage Entrepreneurial Activity (TEA) and Established Business Activity

The sectoral structure of Russian entrepreneurial activity does not differ between early-stage and established business owners – indicating on the one side a natural character of most bottom-up venturing activity, on the other side, the absence of significant structural changes in the economy after the economic crisis (2009). Over 50 % of entrepreneurs are active in consumer oriented industries; the share of business oriented services remains relatively small.

Table 1 gives the dynamic of main indicators of entrepreneurial activity of Russian population during the whole period of project realization in Russia (2006-2011).

Table 1: Main indicators of entrepreneurial activity of Russian population according to the “Global Entrepreneurship Monitor” (2006-2011)2

Indicator Item 2006 2007 2008 2009 20102011

TEA, % % 4,9 2,7 3,5 3,9 3,94,5

NasEnt, % % 3,5 1,3 1,7 1,8 2,22,4

BBO, % % 1,4 1,3 1,8 2,1 1,72,2

EBO, % % 1,2 1,4 1 2,1 2,72,8

TEA_OPP, % % 3,4 1,9 2,5 2,6 2,53

TEA_NEC, % % 1,4 0,5 0,7 1,1 1,31,2

TEAf, % % 2,5 1,6 2,5 3,2 3,54

TEAm, % % 7,3 3,8 4,5 4,6 4,55,1

Nas_nec, % % 0,7 0,4 0,2 0,6 0,70,5

BBO_nec, % % 0,9 0,2 0,7 0,5 0,60,7

EBO_nec, % % 0,1 0,2 0,2 0,6 1,21,1

TEA pers. 92 52 58 66 68339

NasEnt pers. 65 26 29 30 39181

2 See App. 1, Glossary of Main Measures and Terminology.12

BBO pers. 27 26 29 36 30162

EBO pers. 23 28 17 36 46208

TEA_OPP pers. 65 37 42 45 43221

TEA_NES pers. 27 10 12 19 2290

TEAf pers. 25 16 22 28 32158

TEAm pers. 67 35 36 37 37181

Nas_nec pers. 13 7 3 10 1235

BBO_nec pers. 18 3 12 9 1056

EBO_nec pers. 3 4 3 10 2084

Main Findings:

1. The average age of potential and early entrepreneurs coincides at 36 years, which along with visually similar forms of distribution evidences a lack of considerable rejuvenation of the entrepreneurial class in Russia. Considering the high level of informality of the relations in which entrepreneurs find themselves in Russia, the start of a new business requires, in addition to the “entrepreneurial euphoria” characteristic of people of a younger age, a sufficient level of accumulated social experience and connections usually being attained by the middle age. Considering the above, target support of entrepreneurship among the young should not overestimate the possibilities of “rejuvenation” of the entrepreneurial class – except high-tech clusters and the like.

2. The tendency toward male dominance in the entrepreneurial sphere is steady and will, most probably, persist in the near future. In this sense Russia is not an exception and, considering the prevailing share of necessity-driven entrepreneurship among females repeatedly mentioned in literature, the lower share of females in Russia’s entrepreneurial class ought to be regarded rather as evidence of existence of alternative options for economic activity (wage employment jobs, household work) and a consequence of natural differences between the life paths of men and women. In any case, it seems that the economic crisis did not make a strong enough impact on economic activity of females to overcome this long standing tradition.

3. The education level does not have any significant impact on involvement in entrepreneurial activity. This means that (a) other circumstances and factors of human capital play an important role and (b) the national system of educational institutions is arranged in such a manner that an increase in the level of education does not entail considerable additional advantages (competences, social connections, etc.) at the start. Apparently, the development of students’ entrepreneurial potential should become an important element of education reform if Russia wants to form an orientation towards innovative, i.e. “skilled and knowledge-based” entrepreneurship in the mid- and long-term perspective.4. Although there has been no statistically significant change in the share of necessity-driven entrepreneurs in the period from 2006 to 2011, except a sharp increase of opportunity-driven entrepreneurs in 2007 among the owners of new businesses (according to Student’s t-test, a 5% level

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of significance), the share of opportunity-driven entrepreneurs demonstrated an upward tendency in 2011, which may be a sign of improving economic climate.5. On the whole, the motivational structure of Russian early entrepreneurs in 2011 can be described as quite favorable in terms of proportions of opportunity-driven and necessity-driven entrepreneurs. The share of opportunity-driven entrepreneurs is much higher than that of necessity-driven entrepreneurs both among nascent entrepreneurs and the owners of new businesses.6. Comparative analysis of opportunity-driven and necessity-driven early entrepreneurs showed that opportunity-driven entrepreneurs are characterized with a higher level of formal education, higher risk appetite, better financial standing, and greater involvement in entrepreneurial networks as compared to necessity-driven entrepreneurs.7. The socio-demographic characteristics of early entrepreneurship are generally identical in different types of settlements: an early entrepreneur is a male aged 25–34 with a rather high educational level.8. Considerable differences are observed in the education structure of early entrepreneurs depending on the type of settlements, with the share of early entrepreneurs with higher or incomplete higher education declining as the size of the settlement becomes smaller (from metropolis to village).9. Early starters in metropolises are the least optimistic about the prospects of starting a business in their settlement environments, and they are also the least involved in social networks of entrepreneurs and demonstrate the highest rate of fear of business failure. Early entrepreneurs who live in Moscow and St. Petersburg are the most confident in success. Therefore, cities-millionaires, most of which are regional centers seemingly disposing of a more developed business support infrastructure and a wider range of opportunities for entrepreneurial activity, turn out to be the most problematic in contemporary Russia not so much from the point of view of development levels, but rather in terms of psychological and motivational characteristics of early entrepreneurs.10. Nevertheless, the overwhelming majority of early-stage entrepreneurs in all settlement types is involved in social networks (on average, about 70% of early entrepreneurs across the country are acquainted with an entrepreneur who has started a business in the last two years).11. The gender structure is characterized with a slight excess of the share of females among early entrepreneurs in metropolises. To all appearances, this is the only place where conditions are ripe for genuine equality of women in the choice of the form of economic self-activity.12. The motivational structure of the Russian early entrepreneurship in most settlement types can be described as quite favorable in terms of the proportion between opportunity-driven and necessity-driven entrepreneurship. Even the rural areas today are no longer the sphere of concentration of predominantly necessity-driven entrepreneurship.13. 2011 saw a positive dynamic of almost all main financial measures of multilateral lending institutions (MLI), which is a sign of a shaping out long-term development trend and, possibly, a new period of active growth.14. The growth of the MLI loan portfolio outpaces the growth of the credit portfolio in the banking sector (an increase of 12.33% and 5.97% over the quarter, respectively). This means that MLIs are ahead of banking institutions in terms of the operations development dynamics, which is an important indicator of demand for small loans, including those needed for micro-business and early-stage entrepreneurship.15. Within this context, in 2011 MLIs started more actively financing the development of small business.

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16. Meanwhile, the owners of nascent businesses so far make up only a small part of MLI clients in terms of the size of extended loans, whereas the need for informal external financing of both nascent entrepreneurs and the owners of new businesses exceeds MFO offer approximately 10 times.17. The gradual economic rise is accompanied by a growing share of early entrepreneurs who are ready to invest exclusively their own money in the developing business. Most people in this group have a permanent source of income from a wage employment job or self-employment, and also are opportunity-driven. 18. As the economic situation improves, the intensity of using “amicable capital” becomes less, but for a time being it remains the prevailing source of external financing of early entrepreneurship.19. Most of the starting businesses require rather moderate investments. As a matter of fact, the differentiation of early entrepreneurs according to the volume of startup capital to a certain extent depends on different motivations (opportunity-driven entrepreneurship is less limited in resources and intentions).20. The group of comparatively large early-stage entrepreneurs is mainly comprised by persons already involved in individual labor (self-employment, etc.). Wage employment, and even more so unemployment, restricts the scope of an early-stage business, which is in these cases oriented on cheaper and more easily available sources of financing.21. The proportion of personal stakes in financing startup businesses remains stable, leaving room for informal capital as the most sought-after source of money for early-stage entrepreneurship.22. The amount of capital investment depends on relationships with the borrower: the closer the bond (kinship), the larger the invested amount irrespective of the availability of a permanent income source.23. The key role in innovation activity of Russian early entrepreneurs is played by their orientation on foreign markets – both in the product and technological segments.24. Socio-demographic and motivational-psychological characteristics did not demonstrate any significant influence on the level of innovation activity of early entrepreneurs. It seems that the traditional image of an innovator as a rather young and well educated male is more of a myth, at least as far as Russia is concerned.25. Apparently, the level of innovative entrepreneurial activity is influenced by more fundamental factors, such as the availability of long-term money, a favorable institutional and legal environment, and a tightly secured triple spiral – university – government – business; but analysis of these factors goes beyond the frames of this report and requires the scrutiny of extensive data of official government and international statistics.26. Analysis of strategies of early-stage entrepreneurs shows that:- The phenomenon of parallel entrepreneurship is probably not commonly spread across Russia today and was demonstrating a steady downward trend until 2011. In 2011, however, the sample showed a tendency towards the growth in the share of parallel entrepreneurship, possibly, due to improvements of the economic climate.- Parallel entrepreneurs have higher education levels. As a result, they are more optimistic in perceiving their own entrepreneurial skills. However, they are less involved in entrepreneurial networks. Taking these factors in the aggregate, the group of parallel entrepreneurs is best of all adaptable to conditions of the external environment and the most promising in terms of potential.27. As for the strategies involving temporary business discontinuations or leading to total discontinuation of a business, no significant differences were found between groups of entrepreneurs

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temporarily or permanently discontinuing their businesses in terms of socio-demographic characteristics, levels of social capital or income levels.28. The assumption that complete discontinuation of a business is more frequently connected with age and other personal considerations and temporary discontinuation of business operations – with economic and financial factors was not confirmed either.29. Finally, the nature of discontinuation of a business has no impact on perception of the socioeconomic role of small business at respondents’ place of residence. This perception is on the whole positive for both groups and involves high appraisal of the contribution made by small entrepreneurship to addressing the problems of employment and the population’s welfare.

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2. Russian Entrepreneurship in a GEM Global Context In 2011, the Global Entrepreneurship Monitor (GEM) conducted its 13th annual survey of the rate and profile of entrepreneurial activity around the globe. GEM interviewed over 140,000 adults (18-64 years of age) in 54 economies, spanning diverse geographies and a range of development levels. Based on this survey, GEM estimated that there were 388 million entrepreneurs actively engaged in starting and running new businesses in 2011. Of these, there were an estimated:

163 million women early-stage entrepreneurs 165 million young early-stage entrepreneurs between the ages of 18 and 35 years 141 million early-stage entrepreneurs expecting to create at least five new jobs in the next five

years 65 million early-stage entrepreneurs expecting to create twenty or more new jobs in the next

five years 69 million early-stage entrepreneurs with innovative products and services that are new to

customers and with few other competitors 18 million early-stage entrepreneurs selling at least 25% of their products and services

internationally

For 2011, the GEM consortium3 chose to additionally research entrepreneurial employee activity (EEA) as a special topic. EEA was measured in 52 of the 54 participating economies. In these economies, GEM estimates that 46 million employees had a leading role in entrepreneurial activities within existing organizations.

ENTREPRENEURIAL ACTIVITY

This section examines the rate of individual participation in various phases of entrepreneurship across the 54 economies. We discuss potential entrepreneurs, individuals with the intent to start businesses, people starting and running new businesses (early-stage entrepreneurs), those running established businesses, and the discontinuation of businesses.

GEM groups the participating economies into three levels: factor-driven, efficiency-driven, and innovation-driven. These are based on the World Economic Forum’s (WEF) Global Competitiveness Report4, which identifies three phases of economic development based on GDP per capita and the share of exports comprising primary goods.

Potential EntrepreneursEntrepreneurship starts out with potential entrepreneurs: those that may or may not actually venture into this activity, but that have the beliefs and abilities that position them to do so. Measures include believing one has the capabilities to start a business, seeing opportunities in one’s area and feeling undeterred by fear of failure when seeing opportunities.

3 GEM is composed of a consortium of national teams in each participating economy. These teams oversee an annual survey of at least 2,000 adults in their economies.4 According to the WEF classification, the factor-driven phase is dominated by subsistence agriculture and extraction businesses, with a heavy reliance on labor and natural resources. The efficiency-driven phase is accompanied by industrialization and an increased reliance on economies of scale, with capital-intensive large organizations more dominant. In the innovation-driven phase, businesses are increasingly knowledge intensive, with an expanding service sector.

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According to Table 2, Russia, belonging to efficiency-driven countries, shows relatively low levels of both perceived opportunities and capabilities to become entrepreneurial as well as significantly high level of fear of failure, compared with other BRICS countries; however, the figures for Russia are very similar to those for Baltic states and some other CEE countries. The same is true for estimations of social status and entrepreneurship as a career choice. Media attention for entrepreneurship is, again, the lowest among the BRICS countries – whilst in Hungary and Bosnia and Herzegovina it is even lower.Russia and the United Arab Emirates, countries with a high emphasis on extractive resources, exhibit the lowest entrepreneurial intention rates. In contrast, expectations to start a business are expressively high in all other BRICS countries.

Table 2: Entrepreneurial perceptions, intentions, and societal attitudes in 54 economies, 2011

Perceived Opportunitie

sPerceived

capabilitiesFear of failure*

Entrepre-neurial

intentions **

Entrepreneurship as a

good career choice

High Status to successful entrepreneur

s

Media attention for entrepreneur

shipFactor-driven economies

Algeria 54 60 43 42 80 82 51Bangladesh 64 24 72 25 73 49Guatemala 55 71 25 26 85 68 62Iran 32 46 33 30 61 73 58Jamaica 49 79 29 19 81 82 76Pakistan 40 43 35 23 74 73 48Venezuela 48 67 24 20 83 77 63 average (unweighted) 49 56 37 26 77 79 58

Efficiency-driven economiesArgentina 56 64 28 30 76 69 66Barbados 44 67 19 11 60 64 50Bosnia and Herzegovina 21 49 30 17 82 71 43Brazil 43 53 31 28 86 86 82Chile 57 62 27 46 73 69 65China 49 44 36 43 73 73 76Colombia 73 61 29 56 89 79 67Croatia 18 49 34 18 65 47 41Hungary 14 40 35 20 54 78 34Latvia 24 47 41 25Lithuania 23 35 40 17Malaysia 37 31 30 9 52 51 73Mexico 43 61 27 24 57 58 48Panama 46 64 14 21Peru 70 73 41 38 85 82 78Poland 33 52 43 23 73 64 58Romania 36 42 36 25 68 69 57Russia 27 33 43 4 65 65 55Slovakia 23 53 32 18 55 64 55South Africa 41 43 24 14 73 72 74Thailand 40 43 55 26 77 79 84Trinidad & Tobago 62 81 17 35 84 82 61Turkey 32 42 22 9Uruguay 54 61 34 38 58 59 33

average (unweighted) 40 52 32 25 70 69 60Innovation-driven economiesAustralia 48 47 43 12 54 68 70Belgium 43 44 41 11 64 55 47Czech Republic 24 39 35 14 49Denmark 47 35 41 7Finland 61 37 32 7 46 83 67

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France 35 38 37 18 66 68 47Germany 35 37 42 5 55 78 50Greece 11 50 38 10 61 69 32Ireland 26 46 33 6 46 83 56Japan 6 14 42 4 26 55 57Korea Rep. 11 27 45 16 61 67 62Netherlands 48 42 35 9 83 67 62Norway 67 33 41 9 53 80 60Portugal 17 47 40 12Singapore 21 24 39 12 54 63 77Slovenia 18 51 31 9 54 70 45Spain 14 51 39 8 65 66 45Sweden 71 40 35 10 52 71 62Switzerland 47 42 31 10Taiwan 39 29 40 28 69 63 86United Arab Emirates 44 62 51 2 71 73 63United Kingdom 33 42 36 9 52 81 47United States 36 56 31 11 average (unweighted) 35 41 38 10 57 69 58* fear of failure assessed among those seeing opportunities.** intentions assessed in non-entrepreneur (nonTEA) populationSource: GEM 2011 Adult Population Survey

Total Early-Stage Entrepreneurial Activity

Table 3 shows the percentage of individuals in the adult population of each economy that are engaged in a variety of phases of entrepreneurship: those in the process of starting businesses (nascent activity), those operating new businesses up to 3 ½ years old, total entrepreneurial activity (TEA: combined nascent and new), established business ownership, and discontinuance. In addition, we include information about necessity and opportunity motives. Again, Russia scores much worse than other BRICS countries and worse than all CEE and Baltic states. The minor but significant difference is the relatively high level of improvement-driven opportunity entrepreneurship (which is responsible for innovation, economic structure improvement and new jobs) – higher than for instance in China.

Table 3: Entrepreneurial activity in 54 economies by phase of economic development, 2011

EconomiesNascent entrepreneur-ship rate

New business ownership rate

Early-stage entrepreneurial activity (TEA)

Established business ownership rate

Discontinuation of businesses

Necessity-driven (% of TEA)

Improvement-driven opportunity (% of TEA)

Factor-driven economiesAlgeria 5.3 4.0 9.3 3.1 9.5 37 46Bangladesh 7.1 7.1 12.8 11.6 2.5 27 50Guatemala 11.8 9.1 19.3 2.5 3.8 33 33Iran 10.8 3.9 14.5 11.2 6.4 53 32Jamaica 9.0 5.0 13.7 5.1 12.7 33 40Pakistan 7.5 1.7 9.1 4.1 1.6 47 25Venezuela 13.1 2.6 15.4 1.6 3.2 29 43 average (unweighted) 9.2 4.8 13.4 5.6 5.7 37 38Efficiency-driven economiesArgentina 11.8 9.2 20.8 11.8 4.3 33 45

19

Barbados 10.8 1.8 12.6 4.2 5.5 5 58Bosnia and Herzegovina 5.4 2.8 8.1 5.0 6.7 61 22Brazil 4.1 11.0 14.9 12.2 3.8 31 45Chile 14.6 9.6 23.7 7.0 6.8 27 54China 10.1 14.2 24.0 12.7 5.3 41 29Colombia 15.2 6.7 21.4 7.5 6.0 25 30Croatia 5.3 2.1 7.3 4.2 3.6 35 31Hungary 4.8 1.6 6.3 2.0 2.3 31 29Latvia 6.8 5.3 11.9 5.7 3.0 26 46Lithuania 6.4 5.0 11.3 6.3 2.9 28 47Malaysia 2.5 2.5 4.9 5.2 2.6 10 72Mexico 5.7 4.0 9.6 3.0 5.0 19 55Panama 12.0 9.1 20.8 6.0 2.1 27 40Peru 17.9 5.4 22.9 5.7 5.1 22 52Poland 6.0 3.1 9.0 5.0 4.2 48 32Romania 5.6 4.5 9.9 4.6 3.9 41 34Russia 2.4 2.3 4.6 2.8 1.5 27 42Slovakia 9.2 5.3 14.2 9.6 7.0 28 34South Africa 5.2 4.0 9.1 2.3 5.6 35 39Thailand 8.3 12.2 19.5 30.1 4.5 19 67Trinidad & Tobago 13.9 9.3 22.7 6.9 3.9 15 44Turkey 6.3 6.0 11.9 8.0 3.9 32 45Uruguay 11.0 6.0 16.7 5.9 4.3 11 10 average (unweighted) 8.4 5.9 14.1 7.2 4.3 28 42Innovation-driven economiesAustralia 6.0 4.7 10.5 9.1 4.3 15 73Belgium 2.7 3.0 5.7 6.8 1.4 10 72Czech Republic 5.1 2.7 7.6 5.2 2.7 27 57Denmark 3.1 1.6 4.6 4.9 2.3 7 64Finland 3.0 3.3 6.3 8.8 2.0 18 59France 4.1 1.7 5.7 2.4 2.2 15 71Germany 3.4 2.4 5.6 5.6 1.8 19 55Greece 4.4 3.7 8.0 15.8 3.0 25 37Ireland 4.3 3.1 7.2 8.0 3.4 29 37Japan 3.3 2.0 5.2 8.3 0.7 25 64Korea Rep. 2.9 5.1 7.8 10.9 3.2 41 36Netherlands 4.3 4.1 8.2 8.7 2.0 9 62Norway 3.7 3.3 6.9 6.6 2.5 4 70Portugal 4.6 3.0 7.5 5.7 2.9 18 58Singapore 3.8 2.8 6.6 3.3 2.1 16 53Slovenia 1.9 1.7 3.7 4.8 1.5 12 51Spain 3.3 2.5 5.8 8.9 2.2 26 39Sweden 3.5 2.3 5.8 7.0 3.2 6 68Switzerland 3.7 2.9 6.6 10.1 2.9 11 61Taiwan 3.6 4.4 7.9 6.3 4.9 17 50United Arab Emirates 3.7 2.6 6.2 2.7 4.8 14 67United Kingdom 4.7 2.6 7.3 7.2 2.0 17 46United States 8.3 4.3 12.3 9.1 4.4 21 59

20

average (unweighted) 4.0 3.0 6.9 7.2 2.7 18 57Source: GEM 2011 Adult Population Survey

Figure 4 shows TEA rates across all the economies in the sample, ranked within economic development level by increasing levels of TEA. On average, the sixteen efficiency-driven economies participating in GEM in both 2010 and 2011 showed a nearly one-quarter average increase in TEA rate. Argentina, Chile and China were among those economies with an already above average TEA rate in 2010, followed by large increases in 2011. Russia shows the lowest results in this important issue.

Figure 4: Total early-stage entrepreneurial activity (TEA) in 54 economies, by phase of economic development, 2011

0%

5%

10%

15%

20%

25%

30%

Paki

stan

Alg

eria

Ban

glad

esh

Jam

aica

Iran

Vene

zuel

aG

uate

mal

aR

ussi

aM

alay

sia

Hun

gary

Cro

atia

Bos

nia

and

Her

zego

vina

Pola

ndSo

uth

Afr

ica

Mex

ico

Rom

ania

Lith

uani

aLa

tvia

Turk

eyB

arba

dos

Slov

akia

Bra

zil

Uru

guay

Thai

land

Arg

entin

aPa

nam

aC

olom

bia

Trin

idad

& T

obag

oPe

ruC

hile

Chi

naSl

oven

iaD

enm

ark

Japa

nG

erm

any

Bel

gium

Fran

ceSw

eden

Spai

nU

nite

d A

rab

Emira

tes

Finl

and

Switz

erla

ndSi

ngap

ore

Nor

way

Irela

ndU

nite

d K

ingd

omPo

rtug

alC

zech

Rep

ublic

Kor

eaTa

iwan

Gre

ece

Net

herla

nds

Aus

tral

iaU

nite

d St

ates

Factor-driveneconomies

Efficiency-driven economies Innovation-driven economies

Perc

enta

ge o

f adu

lt po

pula

tion

betw

een

18-6

4 ye

ars

Source: GEM 2011 Adult Population Survey

Established Business Ownership

Early-stage entrepreneurs provide dynamism in an economy to the extent they introduce novel ideas and create new value for their societies. Established business owners play an essential role as well. For example, they can offer employment and stability in their societies. The level of established business ownership can thus provide some indication about the sustainability of entrepreneurship in a society.

Figure 5 shows a comparison of established business ownership and TEA rates across the sample. The economies are ranked by rate of established business ownership within each economic development level. This figure clearly illustrates the generally low established business ownership rate relative to TEA in the efficiency-driven group compared with the innovation-driven group. Russia shows a median proportion between the TEA and EBO rates, however, taken into consideration the absolutely lowest levels of both indicators among all countries in the sample.

21

Figure 5: Comparison of established business ownership and TEA rates for 54 Economies, organized by established business ownership rate within economic development levels, 2011

0%

5%

10%

15%

20%

25%

30%Ve

nezu

ela

Gua

tem

ala

Alg

eria

Paki

stan

Jam

aica

Iran

Ban

glad

esh

Hun

gary

Sout

h A

fric

aR

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aM

exic

oB

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Cro

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Rom

ania

Pola

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d H

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govi

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sia

Latv

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rugu

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nam

aLi

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nia

Trin

idad

& T

obag

oC

hile

Col

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rkey

Slov

akia

Arg

entin

aB

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Thai

land

Fran

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tes

Sing

apor

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ark

Cze

ch R

epub

licG

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any

Port

ugal

Taiw

anN

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ayB

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eden

Uni

ted

Kin

gdom

Irela

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Net

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Finl

and

Spai

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nite

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ates

Aus

tral

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itzer

land

Kor

ea R

ep.

Gre

ece

Factor-driveneconomies

Efficiency-driven economies Innovation-driven economies

Perc

enta

ge o

f adu

lt po

pula

tion

betw

een

18-6

4 ye

ars

Total early-stage Entrepreneurial ActivityOwners-Managers in Established Firms


Women’s Participation in Entrepreneurship

Figure 6 reveals the rates of female and male participation in entrepreneurship across the sample. In just eight of the 54 economies surveyed, the rates of female early-stage entrepreneurship are comparable to their male equivalents. These eight—Panama, Venezuela, Jamaica, Guatemala, Brazil, Thailand, Switzerland and Singapore—come from various global regions and represent every phase of economic development. In the rest of the sample, entrepreneurship rates are lower among women relative to men.

Among the efficiency-driven economies, Russia belongs to a small group countries with relatively high women participation rates – despite, lower compared to men. Conversely, the lowest relative rates of women’s involvement in entrepreneurship can be found in the Eastern European economies.

Figure 6: Comparison of female and male early stage entrepreneurship (TEA) rates in 54 economies, organized by female TEA rate with economic development levels, 2011

0%

5%

10%

15%

20%

25%

30%

Paki

stan

Ban

glad

esh

Iran

Alg

eria

Jam

aica

Vene

zuel

aG

uate

mal

aM

alay

sia

Rus

sia

Hun

gary

Cro

atia

Pola

ndB

osni

a an

dSo

uth

Afr

ica

Turk

eyLi

thua

nia

Rom

ania

Slov

akia

Latv

iaM

exic

oB

arba

dos

Uru

guay

Bra

zil

Col

ombi

aA

rgen

tina

Trin

idad

&Pe

ruPa

nam

aTh

aila

ndC

hile

Chi

naSl

oven

iaD

enm

ark

Fran

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pan

Kor

eaIre

land

Nor

way

Cze

chFi

nlan

dU

nite

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erm

any

Swed

enB

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umSp

ain

Port

ugal

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eN

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itzer

land

Sing

apor

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ustr

alia

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ted

Factor-DrivenEconomies

Efficiency-Driven Economies Innovation-Driven Economies

Perc

enta

ge o

f mal

e / f

emal

e po

pula

tion

18-6

4 ye

ars

Male Female


22

Impact

The entrepreneurs have the impact on their economies in terms of growth, innovation, and internationalization. Growth ambitions refer to the job-creation potential of entrepreneurship. Innovation benefits society through new and improved products and services.

GrowthGrowth projections measure how many additional people entrepreneurs expect to employ in five years. We recognize that anticipated growth levels will not be the same as realized growth; the latter is likely lower than predicted. However, several reputable research studies have reported associations between projected and actual growth.5

In Figure 7 we show growth expectations for 54 economies at three levels: 0-4 (low growth expectations), 5-19 (medium growth expectations), and 20 or more employees (high growth expections). As this figure shows, Chile is also notable in the efficiency-driven group for its high level of moderate growth expectations and China stands out for its large proportion of entrepreneurs with high growth ambitions. Russian data seems to show rather modal structure among this group.

Figure 7: Growth expectations in 53 economies, organized by phase of economic development, on the base of 2009-2011 dataset

0%

5%

10%

15%

20%

25%

Paki

stan

Alge

riaBa

ngla

desh Ira

nJa

mai

caVe

nezu

ela

Guat

emal

aRu

ssia

Mal

aysi

aCr

oatia

Rom

ania

Bosn

ia a

ndHu

ngar

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uth

Afric

aPo

land

Mex

ico

Turk

eyLa

tvia

Lith

uani

aBa

rbad

osUr

ugua

ySl

ovak

iaPa

nam

aBr

azil

Arge

ntin

aTr

inid

ad &

Chile

Chin

aTh

aila

ndCo

lom

bia

Peru

Japa

nDe

nmar

kBe

lgiu

mGe

rman

ySl

oven

iaSp

ain

Fran

ceSw

eden

Finl

and

Unite

d Ki

ngdo

mPo

rtuga

lSw

itzer

land

Sing

apor

eIre

land

Kore

a Re

p.Gr

eece

Neth

erla

nds

Czec

h Re

publ

icNo

rway

Taiw

anUn

ited

Arab

Aust

ralia

Unite

d St

ates


Efficiency-Driven Economies Innovation-Driven Economies

Perc

enta

ge o

f Adu

lt Po

pula

tion

18-6

4 ye

ars

Job expectations: 0-4 jobs

Job expectations: 5-19 Jobs

Job Expectation: 20 or More Jobs

Source: GEM 2009-2011 Adult Population Survey

Innovation

5 For example: Baum, R., Locke, E., and Smith, K. (2001) “Multidimensional Model of Venture Growth.” In The Academy of Management Journal, 44(2): 292–303. Wiklund, J. and Shepherd, D. (2003). “Aspiring for, and Achieving Growth: The Moderating Role of Resources and Opportunities”. Journal of Management Studies 40(8):1919–1941.

23

Figure 8 shows the percentage of entrepreneurs with innovative products. Innovativeness increases on average with economic development level. In the factor-driven economies, the highest levels on this measure can be seen in Guatemala, which also reports a high TEA rate. In the efficiency-driven group, high innovation rates can be seen among those with both high (Chile, Peru) and low (South Africa, Poland) TEA rates. Russian results are higher than in Brazil, equal to China, but significantly lower than in South Africa and lower than in any CEE country.

Figure 8: Percentage of total early-stage entrepreneurs (TEA) with innovative products in 54 economies, 2011

0%

10%

20%

30%

40%

50%

60%

Bang

lade

shJa

mai

caIra

nVe

nezu

ela

Alge

riaPa

kist

anGu

atem

ala

Trin

idad

&Br

azil

Mal

aysia

Chin

aRu

ssia

Bosn

ia a

ndHu

ngar

yBa

rbad

osSl

ovak

iaCr

oatia

Thai

land

Mex

ico

Lith

uani

aRo

man

iaTu

rkey

Urug

uay

Pana

ma

Latv

iaCo

lom

bia

Pola

ndAr

genti

naSo

uth

Afric

aPe

ruCh

ileSi

ngap

ore

Japa

nKo

rea

Spai

nPo

rtug

alFi

nlan

dBe

lgiu

mTa

iwan

Germ

any

Unite

dN

ethe

rland

sSw

eden

Unite

dN

orw

ayAu

stra

liaGr

eece

Czec

hUn

ited

Arab

Slov

enia

Switz

erla

ndIre

land

Fran

ceDe

nmar

k


Efficiency-Driven Economies Innovation-Driven EconomiesPerc

enta

ge o

f Tot

al e

arly

-sta

ge E

ntre

pren

euria

l Acti

vity

Source: GEM 2009-2011 Adult Population Survey

3. Review of Macroeconomic Statistics for Russia in 2011Population. According to the estimate the resident population size of the Russian Federation as of

December 1, 2011 was 142.9* mln. persons and from the beginning of year decreased by 47.1 thousand people or by 0.03%. This decrease was caused by the natural decrease of the population. The number of deaths exceeded the number of births by 1.1 times; the natural decrease rate amounted to – 1.2‰ in 2011. There was a decrease of migration inflow to Russia in 2011 in comparison to 2010. The natural decrease of population was compensated by the migration increase of 77.6 thousand persons by 62.3% only.

Employment and unemployment. The economically active population size was 76.6 million persons or about 54.0% of the total population of the country in 2011. This number includes 71.9 million people or 93.8% of economically active population who were employed in the economy and 4.8 million persons (6.2%) had no occupation but were actively looking for job (according to the methodology of International Labor Organization they are classified as unemployed). At the end of September 1.3 million persons were registered by the State Employment Services as unemployed.

Living standards. The welfare of population is determined first of all by the money income. Per capita monthly money income6 was 19325.2 RUR in 2011 and has risen in comparison with the corresponding period of 2010 by 9.2%, money expenditures and savings came to 19266.4 RUR and increased by 10.1% respectively.

Real disposable money income of population (income excluding compulsory payments corrected by the consumer price index) in 2011 decreased by 0.2% in comparison to the corresponding period of 2010. Let us note that the share of income of population from the social

6 The indicator is estimated with regard to preliminary results of 2010 All-Russia population census24

payments, remuneration and entrepreneurial activity, increased, vice versa the share of income from property and income of employees decreased.

Preliminary data shows that 76.3% of money incomes of population were spent to purchase goods and services, 10.1 – for compulsory payments and dues, 9.4 - for savings, 4.2% – for purchasing of foreign currency.

According to preliminary data 10% of well-off population received 30.2% of the total money income and 10% of less secured population – only 2.0% (for the corresponding period of 2010 – 30.5% and 1.9% correspondingly) in 2011.

The average nominal accrued monthly wage in 2011 accounted for 22622 rubles and has risen compared to the corresponding period of 2010 by 11.9%, the actual wages and salaries - by 2.6%.

The average monthly fixed pension in 2011 amounted to 8175.9 rubles (provisional data) and increased by 10.0% compared to the 9 months of 2010 and the actual value of monthly fixed pensions in 2011 also increased by 0.9% in comparison with the corresponding period of 2010.

Gross Domestic Product. The total volume of GDP at current prices for the 1 st half of 2011 made 24167.1 bln. RUR and its volume index compared to 1st half of 2010 amounted to 103.7%.

Index of industrial production7 comprised 105.2% in 2011 compared to 2010.Production index for mining and quarrying8 amounted to 102.4% in 2011 including for

mining and quarrying of energy producing minerals – 101.2% and for mining and quarrying except energy producing minerals – 106.1%.

Production index for manufacturing9 made 107.2% in 2011 compared to 2010. The growth of production output was observed for the following kinds of economic activities: manufacture of pulp and paper products; publishing and printing – 100.1%, manufacture of food products, including beverages and tobacco – 100.5, manufacture of basic metal and fabricated metal products – 102.9, manufacture of cock, refined petroleum products – 103.8, manufacture of textile and textile products – 104.6, manufacture of wood and wood products – 105.7, manufacture of electric, electronic and optical equipment – 105.8, manufacture of chemical products – 106.6, other manufactures – 106.6, manufacture of leather, leather products and footwear – 110.0, manufacture of other non-metallic mineral products – 110.2, manufacture of machinery and equipment – 112.0, manufacture of rubber and plastic products – 115.1, manufacture of transport equipment – 129.6%.

Production index for the kind of activity “Electricity, gas and water production and supply”10 accounted for 100.6% in 2011 compared to 2010.

Agriculture. According to preliminary estimates the volume of agricultural production of all producers (agricultural enterprises, private peasants’ farms, individual entrepreneurs, household farms) at actual current prices amounted to 2465.6 bln. RUR in 2011 or 115.9% to 2010. As of November 1, 2011 according to the estimate, production of grain in initially registered weight of agricultural farms of all types amounted to 96.0 mln. tons, sunflower – by 7.5, sugar beet (fabricated) – 34.5 potato – 32.1, vegetables – 13.5 mln. tons. In current year compared to the last year production of grain increased by 53.3%, sunflower – by 52.1%, sugar beet (fabricated) – by 88.5%. Production of potato and vegetables increased correspondingly by 55.0 and 19.0%. The production of cattle and poultry for slaughter (live weight) of agricultural farms of all types amounted to 7.1 mln. tons (104.4% to the level of the 9 months of 2010), production of milk – 25.1 mln. tons (98.6%), of eggs – 31.3 bln. pieces (100.8%) in 2011.

Construction. The value of works performed for the kind of activity “Construction” amounted to 3295,6 bln. RUR in 2011 or 104,1% to the level of 2010.

7 Index industrial production is calculated for kinds of activity “mining and quarrying”, “manufacturing”, “production and distribution of electricity, gas and water” on the basis of time series of production of goods- representatives (in quantity and value). The structure of the gross value added by kinds of economic activity for 2008 the base year is used as weights for calculations (with due regard for informal activities).8 With due regard for informal activities9 With due regard for informal activities10 With due regard for informal activities.

25

During the 9 months of 2011 organizations of all types of ownership have put in place 402.0 thousand new flats of total floor space of 33.8 mln. sq. m.

Transport and communication. The freight turnover of transport amounted to 3639.4 bln. ton-kilometers in 2011 (103.8% to the level of 2010), including railway – 1573.2 (105.5%), motor transport – 160.4 (111.4%), maritime – 58.3 (76.5%), inland water – 49.0 (109.5%), air – 3.6 (104.8%), pipeline – 1794.9 bln. ton-kilometers (102.8%). Passenger turnover of public transport accounted for 338.9 bln. passenger-kilometers (104,0% to the level of 2010) including railway – 108.8 (100.3%), motor vehicle transport – 102.1 (97.7%), air transport – 127.3 bln. passenger-kilometers (113.6%). The value of service rendered by all operators of communication was 1051.4 billion roubles in 2011. Number of dispatched mail (letters and documents), parcels increased, number of intra-zone, intercity and international trunks of fixed communication network also increased in 2011 to 2010. Number of user terminals of moving radiotelephone (cellular) communication reached 250.0 million, their increase in comparison to the beginning of 2011 made 12.3 million or 5.2 %.

Trade. Retail trade turnover of 2011 amounted to 13611.0 billion roubles and makes in terms of trade mass 6.2% increase in comparison to the year 2010. In the structure of retail trade turnover the share of non-food products amounted to 51.9% in 2011 (from 51.3% in 2010).

Market services rendered to population. Services rendered to population accounted for 3993.4 billion RUR in 2011. The volume index is made 103.3% in comparison to 2010. Housing communal service took the first place in the structure of market service rendered to population in 2011 and its share reached 26.9% of the total volume of market services.

Finance. According to data of the Federal Treasury of Russia the consolidated budget including extra-budget state funds was executed with the proficit (surplus) of 2425.4 billion RUR in 2011. Expenditures comprised of 12745.4 billion RUR, revenue – 15170.8 bln. RUR. The major part of the revenue was made up by income tax for individuals – 1378.5 bln. RUR (9,1%), taxes on profit of organizations – 1772.7 bln. RUR (11.7%), insurance benefits on compulsory social security – 2564.3 bln. RUR (16.9%), VAT on goods (works, services) sold on the territory of the Russian Federation – 1341.1 bln RUR (8.8%), revenue from external economic activity – 3224.5 bln RUR (21.3%). There were allocated 7571.3 billion RUR (or 59.4% of total expenditures of the consolidated budget expenditures in 2011) to social and cultural arrangements, 870.0 bln. RUR (6.8%) to the public administration needs, 908.4 bln RUR (7.1%) to the national defense, 944.8 bln RUR (7.4%) to national security and militia, and 1520.1 bln RUR (or 11.9% of total expenditures) to national economy. In accordance with data of the Federal Treasury of Russia the federal budget was executed with the proficit (surplus) of 1130.9 billion RUR for 2011. Revenue amounted to 8213.0 billion RUR, expenses – 7082.1 billon RUR. Money supply (M2) according to the Bank of Russia as of October 1, 2011 accounted for 21497.4 billion RUR and increased by 7.4% in comparison with the beginning of 2011.

Investments. Organizations of all institutional types had used 6355.5 billion RUR of investments in fixed capital for the economic and social development (or 104.8% compared to the level of 2010).

The share of investments (excluding small business) at own expenses amounted to 45.3%, attracted funds – 54.7%, including 8.0% - from the federal budget.

For the 9 month of 2011 the total foreign investments allocated in non-financial sector of the economy, according to data of organizations presented statistical reports (excluding monetary and crediting institutions, commercial banks), including roubles investments converted in US dollars, amounted to 133.8 billion USD.

In the structure of foreign investments allocated to Russia for the 9 months of 2011 the direct investments made up 8.8%, portfolio investments – 0.4, other investments – 90.8%.

Prices and tariffs. Consumer price index for 9 months of 2011 (September to December 2010) comprised 104.7%, of which for food products – 102.1, non-food products – 105.0, for service – 108.1%.

26

At the end of September 2011 the cost of the fixed basket of consumer goods and service in average for Russia used for international comparison of purchasing power of population accounted for 9094.4 RUR calculated per month. Its decrease compared to the end of May was 0.5% (from the beginning of year – increased 5.3%).

Producer price indices for selected sectors of the economy for the 9 months of 2011 (September to December 2010) were as follows: for manufactured goods – 110.7%, for agricultural production – 96.1%, for construction production – 106.8%, index of freight transportation tariffs – 117. 7%.

In September 2011 compared to December 2010 the producer price index of mining and quarrying comprised 121.8%, including for mining and quarrying of energy producing materials – 122.7%, for mining and quarrying, except of energy producing materials – 115.5%.

For 9 months of 2011 producer price index of manufacturing compared to December 2010 made 108.2% including for manufacture of food products, including beverages and tobacco – 101.5, manufacture of textile and textile products – 113.0, leather products and footwear – 111.3, wood and wood products – 105.9, pulp and paper products; publishing and printing – 103.1, manufacture of cock – 101.6, refined petroleum products – 115.3, chemical products – 112.1, rubberand plastic products – 105.8, manufacture of other non-metallic mineral products – 114.1, basic metals and fabricated metal products – 107.6, machinery and equipment – 105.3, electrical, electronic and optical equipment – 104.5, manufacture of transport equipment – 108.1%.

In September 2011 compared to December 2010 the producer price index for “Electricity, gas and water production and supply” amounted to 103,4%.

External economic activity. The external trade turnover for the 9 months of 2011 reached the value of 612.5 billion US dollars, including exports – 380.4 billion US dollars, imports – 232.1 billion USD and made the external trade balance netting of 148.3 bln. US dollars.

In comparison with the 9 months of 2010 the external trade turnover increased by 33.2%, exports by 32.3, imports – 34.7%.

The share of the far abroad countries in total external trade turnover comprises 84.4%. Fuel and energy resources prevailed in commodity structure of exports (68.9%). Machinery,

equipment and transport means took the leading position in imports (46.9%).

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4. Adult Population Survey of GEM in Russian Federation

GEM Adult Population Survey is an economic and social survey directed at individuals. In GEM’s research perspective, it is individuals who are primary agents in setting up, starting, and maintaining new and entrepreneurial businesses. The Adult Population Survey (APS) investigates the role of the individual in the lifecycle of the entrepreneurial process, and his or her characteristics or actions. A representative sample of the adult population is used to measure the entrepreneurial activity that represents the entire country. The APS is unique because it studies entrepreneurship through peoples’ motives and attitudes as they strive to set up, start and maintain businessesThis year’s National Report on GEM in Russian Federation is based on the APS that was held among a representative sample of 7,500 adults who were interviewed in May (outside holiday seasons) by face-to-face method (because telephone coverage is insufficient) and answered questions on their attitudes toward and involvement in entrepreneurial activityv. The survey was based on the nationwide, multi-stage, stratified and probability sample that represents the adult population in age 18-64 years old. All individuals were included, those considered in and OUT of the labor force (homemakers, retirees, students), urban and rural areas from all geographic regions. Only exclusions are those visiting the country, in institutions (prisons, mental institutions), group quarters or the military. On the first stage urban settlements and rural administrative districts as primary sampling units were selected. Stratification. The nationwide sample (N=7500) was divided among: a) 7 large geographical macro regions (Federal Okrugs) proportionate to the size of the local population aged 18-64 of each macro region b) 5 types of rural districts and urban settlements in each of 7 macro regions proportionate to the size of the local population aged 18-64 of each type:

1) Cities > 1,000 000 inhabitants 2) Cities > 500 000 - 1,000 000 3) Cities > 100 000 – 500 000 4) Cities and small urban settlements < 100 000 5) Rural districts.

Taking into account that in the North-West region there are no cities of 500-1,000 thousands of residents, in Far East region there are no cities of more than 1,000 thousands of residents the total number of strata is 33.Selection of primary sampling units (PSUs). All cities over 1,000,000 inhabitants were included in the sample as self-representative units.Urban settlements and rural districts were considered as primary sample units (PSUs). In each stratum (except strata of cities over 1,000,000 inhabitants) the number of PSUs was calculated with the limitation of 25 interviews per PSU and the PSUs as well were selected with the probability proportionally to the size (PPS). The total numbers of interviews accounted for a stratum was distributed approximately equally among selected PSUs. Totally 249 PSUs were selected including 176 urban and 73 rural PSUs. On the second stage the secondary sampling units (SSUs) were selected from the lists of electoral districts (blocks, streets) in urban settlements and villages in rural districts.In the large cities (more then 500 000 inhabitants) the number of surveyed SSUs was defined by condition of 12-13 interviews per SSU. 46 SSUs were selected In Moscow, 19 SSUs - in S-Petersburg. In the each of middle and small towns and in rural districts 2 SSUs were randomly selected from the list of electoral districts (blocks, streets) in urban settlements and villages in rural districts. Totally 609 SSUs were selected.

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On the third stage the households were selected by a random route method. If members of a household refuse to participate in the survey, or were not achieved for 3 visits, the interviewer was required to visit the next door address. If a selected household member was not at home an interviewer was required to visit this address at least 3 times to obtain the potential respondent. A part of call-backs was back-checked (e.g. supervisor checked later whether back visits took place). The Russian stratified sample frame structure and its statistical base are described in Appendix 2 and Appendix 3.

5. Entrepreneurial Activity of Russian Adult Population in 2011A population pyramid showing lower numbers or percentages of younger entrepreneurs. The country will have a graying entrepreneurial population which means that enterprises are generally older, as the country has long life expectancy in entrepreneurship, a low Enterprise death rate, but also a low Enterprise Birth rate. This pyramid has been occurring more frequently in ‘old’ capitalist countries, especially when immigrants are factored out, and is often a typical pattern for a very developed country, a high over-all education and easy access to the market, good entrepreneurial framework conditions and few or no negative environmental factors.

Figure 9: Stage and Gender Structure of Entrepreneurial Cohorts’ in Russia (thousands of people)

Potential entrepreneurs

Nascent entrepreneurs

Baby business owners-managers

Established business owners-managers

-5000 -4000 -3000 -2000 -1000 0 1000 2000 3000 4000 5000MaleOpp MaleNec FemaleOpp FemaleNec

Note: This diagram typically consists of two back-to-back bar graphs, with the population plotted on the X-axis and entrepreneurship phase (as firm age) on the Y-axis, one showing the number of males and one showing females in a particular population in entrepreneurial strata (phases). Males are conventionally shown on the left and females on the right, and they are measured by raw number (thousands of people in Russian Federation).

The structure of Russian entrepreneurial cohorts shows (1) the crisis impact on entrepreneurial activity – the number of nascent entrepreneurs practically coincides with the number of baby business owners (no increase on entrepreneurial potential may be expected in the nearest future), (2) even the prevalence of established business owners compared with baby business owners (a decrease of already thin entrepreneurial population in coming 2 years is granted), (3) the share of necessity driven entrepreneurship grows steadily – from nascent entrepreneurs to established business owners among men and among women.All these features reflect negative processes within the entrepreneurial strata.

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Socio-Demographic Structure of Entrepreneurially Active Population

Socio-demographic characteristics, such as gender, age, education level, have a considerable influence on the willingness to become an entrepreneur and start one’s own business.

The main phases of entrepreneurial activity were analyzed in the process of review of the socio-demographic structure in accordance with the Global Entrepreneurship Monitor: potential entrepreneurs; early entrepreneurs, including nascent ones and owners of a new business; established entrepreneurs.

GenderThe gender structure of entrepreneurship in Russia is typical: males demonstrate more intensive

involvement in all entrepreneurial groups.Given 5.9% level of potential entrepreneurship (calculated as percent of respondents who gave

an affirmative answer to the question whether they are planning to start their own business in the nearest three years), the share of males planning to organize their own business within the nearest three years is slightly higher: 55.6% of potential entrepreneurs are males, and 44.4% – females. The activeness of potential entrepreneurs among males totaled 6.8% as compared to 5.1% of potential entrepreneurs among females.

A total of 5% of all males and 3.8% of females are involved in early entrepreneurship, their proportion is 55% and 44.7%, accordingly. Practically 60% of all owners of new businesses are males, whereas the gender structure of the nascent entrepreneurs is essentially homogeneous. The proportion of males and females among the owners of running businesses is also practically equal: 53% of males and 47% of females. Among established entrepreneurs males were more active in 2011: 2.9% compared to 2.4% among females.

The tendency of the past years of males being more active in setting up new businesses continued in 2011. Presumably, more differences among the factors significant for entrepreneurial activity will be manifested in individual characteristics rather than in national characteristics of entrepreneurship development. Analysis of results of the GEM survey confirmed empirically that considerable differences exit in the Russian Federation between males and females in the following aspects:

perception of their knowledge and skills for starting a new business; perception of the risk level of setting up a new company; perception of the role of the media in popularizing success stories.

At the same time, there are no significant differences between males and females in Russia in the following areas:

perception of the appeal of a business career; perception of the status of an entrepreneur in society; personal acquaintances with entrepreneurs; perception of the friendliness of the external environment for starting a business.

Different perceptions among males and females of the skills and knowledge necessary for starting and running a business are among the most important factors influencing entrepreneurial choice. On the whole, 89% of males and 83% of females who are entrepreneurs presume they do have special knowledge needed for starting a business. At the same time, the differences in self-efficacy evaluation are significant among established entrepreneurs, but there are no differences in perceptions of knowledge among males and females who are early-stage entrepreneurs.

Gender differences exist in perception of knowledge and skills among non-entrepreneurial population strata. As a matter of fact, if the gap in average assessments of knowledge and skills among entrepreneurs does not exceed 13%, it was also more significant among non-entrepreneurs and made up 35% in favor of males.

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The fear of failure in setting up and running a business is a factor that has strong differences in assessments by males and females in all population groups under survey. Moreover, the fear of failure is much stronger among females involved in entrepreneurship than among males (the gender differences in this factor evaluation make up as high as 40% for all categories of entrepreneurs). These differences are not as striking for non-entrepreneurs – a mere 15%. Presumably, ones having started a business, women encounter a greater degree of resistance.

AgeComparison of the age samples for different types of entrepreneurs demonstrates significant

differences among age groups. The average age of an early Russian entrepreneur is 35.8 years. The median age is practically the same and stands at 35 years.

Entrepreneurs’ age allocation is presented in table 3.2. The prevalence of the “23–34” age group is characteristic of the majority of entrepreneurial groups. As far as early entrepreneurs are concerned, this is true for both males and females.

Table 3.2. Distribution of Russian Entrepreneurs According to Age, Gender and Phases of Entrepreneurial Activity in 2011

Phases of Entrepreneurial Activity

Gender Age

18-24 25-34 35-44 45-54 55-64

Potential

Male% at the population 25,9 37,0 19,8 13,6 3,7% belonging to the resp. group 11 10,1 6,8 4,3 1,4

Female

% at the population 22,2 29,9 24,2 21,6 2,1% belonging to the resp. group 7,5 7,3 5,9 5,2 0,5

Early entrepreneu

rs

Male% at the population 13,7 36,6 27,9 18,0 3,8% belonging to the resp. group 4,3 7,3 7,1 4,2 1,1

Female


Nascent


Female


New business owners


Female

% at the population 7,7 30,8 34,6 19,2 7,7% belonging to the resp. group 0,7 2 2,2 1,2 0,5

Established business owners


Female


31

Exceptions are made by potential and established entrepreneurs. The activeness of potential entrepreneurs subsides with age. Young people aged from 18 to 24 years demonstrate the greatest activeness. 11% of young males and 7.5% of young females in that age group are planning to start a new business. Older age groups show a tendency towards decrease of activeness.

The owners of established businesses are characterized with the prevalence of the “35–44” and “45–54” age groups. The activeness of males exceeds the activeness of females among the owners of new businesses and established entrepreneurs in all age groups. There are practically no differences in the group of nascent entrepreneurs.

There are no significant differences in the attitude to entrepreneurship among early-stage entrepreneurs. Potential entrepreneurs are especially sensitive to various factors influencing the evaluation of the entrepreneurial conditions. The testing of independent samples of potential entrepreneurs points to the existence of significant differences between age groups in perceptions of knowledge and skills, career preferences, assessments of the status of an entrepreneur, and media coverage of successful business development stories. The frequency analysis (figure 3.1) shows that the “18–24” age group demonstrates a relatively lower level of confidence in perception of knowledge and skills – 60% of potential entrepreneurs in this age group consider their skills and knowledge sufficient for starting their own business. Older age groups of potential entrepreneurs evaluate their knowledge and skills higher (from 76% to 89% of respondents).

Figure. Measurements of Entrepreneurship Framework Conditions (EFC) Perception by Potential Entrepreneurs, by the Age Groups

Личное знакомство

Благоприятные условия

Знания и опыт

Страх провалаВыбор карьеры

Высокий статус

Информация в СМИ

-10

40

90

"18-24" "25-34" "35-44" "45-54" "55-64"

On the other hand, younger groups – aged from 18 to 34 years – regard entrepreneurship as the desirable career choice more often than senior respondents. The same tendency is observed in assessment of the status of entrepreneur in society. Only 45% of respondents aged 45–64 years evaluate the position of entrepreneurs in society as high, whereas the evaluation of the status of entrepreneur in society is high among 75% of potential entrepreneurs younger than 44 years.

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Strong age differences are observed among the non-entrepreneurial population groups in evaluation of the entrepreneurial climate. The gap is especially strong among those who are not planning to start a business and those who are planning to start a company within the next three years in perception of the knowledge and skills. The perception of knowledge and skills by potential entrepreneurs is nearly twice higher than by non-entrepreneurs.

EducationResearch in the area of entrepreneurship does not provide an unequivocal answer to the

question of the influence of the education level on the population’s entrepreneurial activity. Presumably, people with higher educational levels have better prospects for entrepreneurship. However, they also have a greater variety of job offers and wider opportunities for applying their skills beyond the sphere of entrepreneurship.

The GEM methodology highlights four educational groups of people: respondents with incomplete secondary education, secondary education, incomplete higher or technical vocational education, and respondents with higher education (the latter category also includes persons with a scientific degree of candidate or doctor of sciences and master of business administration, MBA).

Respondents with incomplete higher, technical vocational, and higher education prevail in the group of entrepreneurs, both early-stage ones and owners of an established business (table 3.3). They account for over 80% of entrepreneurs. Respondents with higher education demonstrate the highest level of activity among early-stage (7.09%) and established (4.86%) entrepreneurs.

Table 3.3. Distribution of Entrepreneurs by Education Groups

Level of education

Early entrepreneurs EBO Potential предприниматели

% at adult population

% of target group

% at adult population

% of target group %

High school, not completed 2,4 2,35 1,5 0,77 2,1

High school 12,4 3,13 11,5 1,89 13,3Higher school, not completed 42,9 3,89 43,0 2,41 46,2

Higher school 41,4 7,09 44,0 4,68 38,4

Respondents with different levels of education differ in their assessments of the entrepreneurial climate in the country. Analysis of entrepreneurs as a whole (early starters and established ones) has revealed significant differences in perception of knowledge and skills required for starting a new business and the fear of failure among different education level groups. The perception of knowledge and skills for starting a new business by entrepreneurs with higher education is about 90%, whereas the percentage of respondents with incomplete higher education is 66.7%.

The most significant differences among early-stage entrepreneurs are manifested in the level of fear of failure. It becomes lesser as the education level increases. E.g.., the fear of failure is present among 50% of respondents with incomplete secondary education compared to 21% among respondents with higher education.

Serious differences among established entrepreneurs are observed in their perception of sufficiency of entrepreneurial skills and media coverage of success stories of entrepreneurs. Some 33% of respondents with incomplete secondary education believe they have the necessary knowledge. As the educational level increases the self-efficacy level also grows (perception of one’s own skills as sufficient). It makes up 90.5% among people with higher education.

Main Conclusions:33

1. The tendency of the previous years of males demonstrating greater activeness in starting a new business continued in 2011.

2. Males and females demonstrate considerable differences in perceptions of their skills and knowledge as sufficient for starting their own new business (self-efficacy) and of the level of risk involved in starting a business: males demonstrate a higher level of self-efficacy and lower risk perception.

3. In Russia, males and females do not demonstrate strong differences in evaluations of the appeal of an entrepreneurial career and the status of entrepreneur in society.4. No significant differences were revealed in the attitude to entrepreneurship among different age groups of early entrepreneurs. At the same time, potential entrepreneurs are more sensitive to different factors influencing the evaluation of the entrepreneurial conditions.5. Respondents with different educational levels make different assessments of the entrepreneurial climate in the country. Specifically, serious differences were revealed in self-efficacy perceptions and the fear of failure among different education level groups – the higher is the educational level of a respondent, the higher the level of self-efficacy and the lower the fear of failure in business.

Motivation of Entrepreneurial Activity

The opportunities provided by GEM data enable to comprehensively examine the motivational structure of early-stage entrepreneurship in Russia and also review it within an international context. Analysis of motivations towards the start of one’s own business and its differences caused by various factors helps reveal both the existence of macro-institutional restrictions and opportunities for entrepreneurship development. Specifically, the dynamics of development of entrepreneurship in relevant regions may be forecasted on the basis of analysis of regional differences in the level of preparedness for starting a personal business, and measures may be proposed to improve the perception of the business development environment.

Opportunity-driven and necessity-driven entrepreneurs constitute two groups the differences between which are connected with the nature of motivation for starting a business. However, we presume that they are separated by more than just different answers to the question: “What is the purpose of doing business?” There are a number of other distinctive features, including socio-demographic characteristics and perception of their personal traits.

The review of literature analyzing motivational characteristics of entrepreneurship and the returns of the surveys conducted by the Russian GEM team in 2006–2010 made it possible to evaluate the development of the revealed tendencies in conditions of gradual pullout from the economic crisis. We presume that:1) positive dynamics can be expected in the share of opportunity-driven entrepreneurship and, on

the contrary, a drop in the share of necessity-driven entrepreneurship;2) males, middle-aged individuals, and people with a higher level of education become opportunity-

driven entrepreneurs more often;3) the share of persons who have acquaintances among owners and managers of running businesses

is higher among opportunity-driven than among necessity-driven entrepreneurs;4) a positive perception of one’s knowledge and skills, a lack of fear of starting a business condition

the voluntary choice of entrepreneurship.

Dynamics of the Motivational Structure of Early Entrepreneurship in 2006–2011

34

Analysis of the dynamics of the measure of opportunity-driven early entrepreneurship shows that the share of opportunity-driven entrepreneurs involved in early-stage entrepreneurship exceeded the share of necessity-driven entrepreneurs during the entire period under survey. This is the evidence of a predominantly opportunity-driven nature of the motivational structure of Russia’s early entrepreneurship.

In 2011, not less than 60% of Russians were opportunity-driven into early entrepreneurship. The share of opportunity-driven entrepreneurs did not go lower than 61% of the overall number of early entrepreneurs since 2006. The maximum number of opportunity-driven entrepreneurs was registered in 2007 reaching 80%, which means that on the eve of the 2008 economic crisis the Russian population was striving to join the business environment. However, in 2008 the share of opportunity-driven entrepreneurs dropped by 11% and stayed at the level of 69% for two years.

To all appearances, the growth of the share of necessity-driven entrepreneurs and decrease of the share of opportunity-driven entrepreneurs is caused by the negative impact of the economic crisis on societal life, namely, the situation on the labor market. Dismissals and wage cuts (and reduction of working time) in general were among the consequences of the economic crisis. Under such circumstances, entrepreneurial activity could be regarded by people who had lost their job as the only way to survive and maintain their level of wellbeing. This tendency persisted in 2010 as well: the number of necessity-driven entrepreneurs grew to 36% while the number of opportunity-driven entrepreneurs dropped almost to the 2006 level of 64%.

In 2011, however, in conditions of gradual pullout from the economic crisis, the motivational structure of entrepreneurial activity demonstrated a tendency towards improvement: the proportion of opportunity-driven early entrepreneurs rose to the level of 71%.

Figure 3.3.1Motivational Structure of Early Entrepreneurship in 2011

Ранние Нарождающиеся Владельцы нового бизнеса0%

20%40%60%80%

100%

45% 48% 41%

26% 30%22%

29% 22% 37%

Добровольная: рост дохода Добровольная: независимость Вынужденная

The tendency towards a reduction of the share of opportunity-driven entrepreneurs in favor of necessity-driven entrepreneurs was also manifested among early-stage entrepreneurs after the economic crisis broke out. Its impact is particularly vivid as far as the motivational structure of the owners of new businesses is concerned. The rapid growth in 2007 of the number of owners of new businesses who started their activity voluntarily (their share grew by 44%) was followed by a similarly rapid slump (the proportion of opportunity-driven owners of new businesses dropped by 30%) in 2008. Following a period of stabilization in 2009, the situation deteriorated again in 2010. An upward tendency has transpired again in 2011, as well as for all early-stage entrepreneurs in general.

Analysis of the dynamics of the measures of opportunity-driven and necessity-driven entrepreneurship in 2006–2010 suggests that the structure of entrepreneurs’ motivation during 5 years of surveys has not experienced statistically significant changes, except the sharp increase in the number of opportunity-driven entrepreneurs among the owners of new businesses in 2007 (according to Student’s t-test, a 5% level of significance).

Motivational Structure of Early-Stage Entrepreneurship in Russia in 2011

35

On the whole, the motivational structure of Russian early-stage entrepreneurship in 2011 can be described as quite favorable. E.g., economic activity of more than two thirds of the Russian early-stage entrepreneurs (71%) is driven by a quest of opportunities provided by business, specifically, 78% of nascent entrepreneurs and 64% of owners of new businesses are characterized by opportunity-driven motivation for entrepreneurial activity. Nevertheless, for 29% of the polled early-stage entrepreneurs the organization of their own business was a necessity-driven step. On the whole, the motivational structure of Russia’s early entrepreneurship in 2011 was close to the 2008–2010 structure.

Opportunity-driven motivation aimed at incomes increase (45%) strongly prevails over the motivation aimed at independence (26%) both among early entrepreneurs in general and among nascent entrepreneurs and owners of new businesses.

It is noteworthy that the share of opportunity-driven entrepreneurship among early-stage entrepreneurs is 15% higher than among the owners of new businesses (statistically significant difference, according to Student’s t-test, a 5% level of significance), which suggests that the tendency towards an improvement of the motivational structure has only transpired.

Demographic, Social and Economic Characteristics of Opportunity-Driven and Necessity-Driven Early-Stage Entrepreneurs in 2011

The differences in entrepreneurial motivation also suggest the existence of differences in socio-demographic characteristics and perceptions by opportunity-driven and necessity-driven early entrepreneurs of their capabilities.

The survey results show that that the younger and more active population group is mainly motivated by a quest of advantages provided by business: the average age of opportunity-driven entrepreneurs is 36 years, and 77% of them are not older than 45 years old. Necessity-driven entrepreneurs are, on average, two years older than opportunity-driven ones (the average age is 38 years old), and the age of 32% of them varies between 45 and 64 years old. But the differences in the average age between opportunity-driven and necessity-driven early entrepreneurs are insignificant (at 5% level of significance), which deflates the assumption that the middle-aged population is more inclined towards the choice of opportunity-driven entrepreneurship.

The results obtained show that midlife is precisely the right time to start a business, which partially substantiates our hypothesis. On the whole, age is not a decisive factor influencing the nature of an individual’s motivation, although on the trend level (10% level of significance) the older age cohort is less adaptable to conditions of the economic environment. The loss of a job as the main income source often leads them to necessity-driven entrepreneurship – mainly self-employment or starting a micro-business.

The gender structure analysis has also failed to reveal statistically significant differences between opportunity-driven and necessity-driven early entrepreneurs. Some 71–72% of both males and females are motivated by the advantages of running one’s own business and less than a third are necessity-driven entrepreneurs. Therefore, gender does not influence the motivation type.

The definition of the concept of opportunity-driven entrepreneurship as a choice based on consideration of relative pros and cons of various opportunities for organizing one’s own economic activity suggests that opportunity-driven entrepreneurs launch their own business only having thoroughly weighted the available options and on condition of high perception of one’s entrepreneurial capabilities. If this is true, opportunity-driven entrepreneurs cannot be distinguished by a considerably higher level of available human, social and economic capital than necessity-driven entrepreneurs starting their business under the impact of circumstances.

The results of the survey on the whole confirm the hypothesis about the differences in educational levels of opportunity-driven and necessity-driven entrepreneurs. Although there are as many respondents with higher education among necessity-driven entrepreneurs as among opportunity-driven entrepreneurs (a 5% level of significance), the share of people with secondary

36

education is considerably higher among the former (30% as compared to 19% among opportunity-driven entrepreneurs). On the whole, individuals with secondary specialized education prevail both among opportunity-driven and necessity-driven entrepreneurs.

In spite of the differences in the level of formal education, no statistically significant (5% level of significance) distinctions were revealed between opportunity-driven and necessity-driven early entrepreneurs in perception of their human capital (agreement with the statement that they have the knowledge, skills, and experience necessary for starting their own business): 85% vs 77%.

Nevertheless, opportunity-driven entrepreneurs have a higher appetite for risk than necessity-driven ones: 73% vs 61% of respondents disagree with the statement that fear or insufficient entrepreneurial capabilities could prevent them from starting a new business.

The financial standing of necessity-driven entrepreneurs is considerably worse than that of opportunity-driven entrepreneurs: the average monthly family per capita income of necessity-driven entrepreneurs over the past year was RUR 13,700, compared to RUR 21,900 for opportunity-driven entrepreneurs.

The surveys of entrepreneurship often emphasize the importance of such factor as involvement in social networks of entrepreneurs (acquaintance with owners/managers of a running business). Being acquainted with such people not only makes a potential entrepreneur confident that the organization of one’s own business is a realistic and quite feasible process, but also helps disseminate the necessary information and useful connections within the business environment more quickly.

The survey results show that those who are acquainted with owners-managers of a running business, i.e., are to some or other measure involved in social networks of entrepreneurs, prevail both among opportunity-driven (72%) and necessity-driven (61%) early entrepreneurs. The differences between opportunity-driven and necessity-driven entrepreneurs in terms of involvement in social networks are significant (5% level of significance), which confirms our initial assumption.

Therefore, our comparative analysis showed that opportunity-driven entrepreneurs are characterized with a higher level of formal education, higher risk appetite, better financial standing, and greater involvement in entrepreneurial networks as compared to necessity-driven hypothesis.

Brief Conclusions

1. Despite the fact that in the period from 2006 to 2011 the share of necessity-driven entrepreneurs did not undergo statistically significant changes, except the sharp increase of opportunity-driven entrepreneurs in 2007 among the owners-managers of a new business (according to Student’s t-test, 5% level of significance), the share of opportunity-driven entrepreneurs started growing in 2011, which may be an indication of an improving economic climate.

2. On the whole, the motivational structure of the Russian early-stage entrepreneurship in 2011 can be described as quite favorable in terms of proportions between opportunity-driven and necessity-driven entrepreneurs. The share of opportunity-driven entrepreneurs is much higher than the share of necessity-driven entrepreneurs both among nascent entrepreneurs and owners-managers of a new business.

3. Comparative analysis of opportunity-driven and necessity-driven early entrepreneurs has shown that opportunity-driven entrepreneurs are characterized with a higher level of formal education, higher risk appetite, better financial standing, and greater involvement in entrepreneurial networks compared to necessity-driven entrepreneurs.

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6. Dynamics of Russian Entrepreneurship Innovation Activity Characteristics in 2006–2011

The issue of interconnection and interdependence of the size of a company and its innovative activity has long been the focus of research of the innovative activity of entrepreneurship. Small innovative companies play an important role on the market of innovative produce in industrially developed countries and are more active participants in innovative activities. More recent literature points out, however, that the attempts to establish a connection between the size of a firm and its ability to offer an innovative product have not produced the anticipated results. One of the few aspects in respect of which researchers see eye to eye is the key role of startups and young firms in new sectors.

The GEM data for 2011 (figure 3.7.1) evidence that the share of entrepreneurs offering a product new to all customers has dropped significantly (by 7% to 12% of entrepreneurs) in 2011 as compared to 2010 mainly due to an increased share of entrepreneurs offering a product which is not new to any of its customers. Therefore, following a substantial rise in this characteristic in 2007 and attainment of a peak level in 2008, when products new to all customers was offered by 23% of entrepreneurs, this characteristic has been declining for a third year in a row.

As far as technological innovations are concerned, their dynamics are, on the contrary, characterized by a positive tendency. E.g. the share of entrepreneurs applying technologies that, according to their estimate, have been available for less than one year has grown by 7% in 2011 to the level of 19% of all entrepreneurs, predominantly owing to a reduction in the share of entrepreneurs applying old technologies available for over five years, and has therefore reached its peak value during the entire period under review (2006–2011). This way, the upward tendency of this parameter, which became vividly manifest in 2010, continued in 2011.

As for the innovative activity characteristics by business development stages, figure 3.7.1 shows that early entrepreneurs have been more active in implementing product innovations throughout all these years than established entrepreneurs, except the years 2007 and 2008, and in 2009 and 2010 the gap was 11% and 7%, accordingly. The leadership of early-stage entrepreneurs persisted in 2011, but the gap has shrunk to a mere 2%.

The proportion between the characteristics shows that early entrepreneurs on the whole remain more active in introducing product innovations, which vividly confirms the validity for Russia, too, of the results of systematic research of the role of startups in developing sectors conducted by Axe and Aldrich.

0%

5%

10%

15%

20%

25%

30%

35%

2006 2007 2008 2009 2010 2011

TEA+EB TEA EB

0%

5%

10%

15%

20%

25%

2006 2007 2008 2009 2010 2011

TEA+EB TEA EB

Figure 3.7.1. Share of entrepreneurs offering a peroduct new to ALL customers

Figure 3.7.2. Share of entrepreneurs using technologies available on the market for less

38

than one year

A similar situation can be observed in the sphere of technological innovations (figure 3.7.2) implemented by entrepreneurs depending on their business development stage. The leading role of early-stage entrepreneurship is even more obvious here. Admittedly, starting 2007, early-stage entrepreneurs played the role of innovative activity flagships, as they did in the case of product innovations.

The special role of early entrepreneurs in innovative process implementation established by foreign researchers (Axe, Alrdich) and substantiated by the data obtained within the framework of GEM surveys in Russia in 2006–2011 calls for a need for isolation and a more profound study of the factors that may be the crucial drivers of innovative activity of early-stage entrepreneurship in Russia. Russian and foreign innovative activity theoreticians have traditionally categorized as such the following factors: socio-demographic characteristics of the entrepreneurs under survey (above all, gender, age,

education, and social environment), pychological and motivational characteristics (knowledge and skills perception, motivation for

entrepreneurship), concentration level of the markets on which they operate, integration in global market processes.

However, the empirical data obtained in the course of the survey demonstrated that none of the socio-demographic factors has a significant impact on innovative activity. As far as age, educational level and social environment of respondents are concerned, these qualitative characteristics are not significant in explaining the differences in the level of product and technological innovative activity of esrly entrepreneurs. Gender has become the decisive factor of differences in the level of technological innovative activity of early entrepreneurs but, contrary to our hypothesis, females have demonstrated considerably higher activeness in implementing new technologies, which challenges the myth about men’s dominant role as innovators. As fas as product innovations are concerned, a product new to all or some customers was offered by 33% of males compared to 26% of females, which, nevertheless, does not make such a striking difference to substantiate the hypothesis regarding the significance of this characteristic at a 5% level of significance, which means that the hythophesis is dismissed.

Figure 3.7.3. Share of Early Male and Female Entrepreneurs Offering Innovative Products and Using Innovative Technologies

39

Male Female

The hypothesis concerning the significant role of motivational and psychological characteristics of an entrepreueur as a factor determining his involvement in innovative activity was not confirmed either.

Significant results were obtained in the process of checking the hypothesis concerning the influence of the market structure and entrepreneurs’ orientation on foreign markets on the level of innovative activity, and therefore, involvement in global trade and economic relations and competition on international markets. In the case of the market structure, however, the results turned out to be directly the opposite to our expectations and were very much similar to the situation with product innovations: respondents happened to be considerably more innovative on the markets they characterized as having a small number of actors offering the same product. In the case of entrepreneurs’ orientation on global markets, the results produced by the hypothesis testing coincided with our expectations: a considerably higher share of entrepreneurs participating or planning to participate in trade and economic relations with foreign partners offer products new to all or some customers and use technologies available on the market during not more than five years.

Technology innovation Export No export

Figure 3.7.4. Share of entrepreneurs using innovative technologies depending on competitiveness of the market on which they operate

Figure 3.7.5. Share of entrepreneurs using innovative technologies and offering innovative products depending on their orientation on export or the domestic market

Brief Conclusions1. A key role in innovative activity of early-stage entrepreneurs in Russia is played by their orientation on foreign markets, both in the product and technological segments.

40

2. Socio-demographic and motivational-psychological characteristics have not demonstrated any significant influence on the level of innovational activity of early entrepreneurs. The existing image of an innovator as a rather young well educated male seems to be more of a myth, at least as far as Russia is concerned.3. To all appearances, the level of innovatinal activity of entrepreneurs is influenced by more fundamental factors, such as availability of long-term money, a favorable institutional and legal environment, a “tight” triple spiral: university – government – business, but analysis of these factors lies beyond the scope of this report and requires the scrutiny of extensive data of official government and international statistics.

7. Business Discontinuance: Forms and Factors

In keeping with the GEM methodology, persons with experience of business discontinuation can be divided into two large categories: those who have left business permanently and those who continue in some way or another to be involved (or plan to be involved) in entrepreneurship.

More than half of all people with business discontinuation experience in Russia have left business for good in 2011 (58.5%). Slightly less than half (41.5%) comprise the group still in some way or another associated with business, most of whom are parallel entrepreneurs (54.2% of the group), i.e. successful entrepreneurs who own more than one business or are planning to start another one in the near future (see fig. 3.8.2).

Figure 3.8.2. Groups with Business Discontinuation Experience

22,5%

8,0%

11,0%

58,5%

параллельные предпринимателипотенциальные предприниматели

серийные предпринимателиокончательно выбывшие

Business Discontinuation: Socio-Demographic Differences between Entrepreneurs Permanently Leaving Business and Staying in Business

The average age of serial, parallel, and potential entrepreneurs with business discontinuation experience coincides at approximately 39 years (see fig. 3.8.3). Age allocation of serial, parallel, and potential entrepreneurs with business discontinuation experience (table 3.8.3) does not have significant differences either, with males prevailing in the group of potential entrepreneurs – more than 75% of the entire group.

Table 3.8.3.Distribution of Subgroups Staying in Business with Business Discontinuation Experience

by Gender, Absolute Frequencies, Percentage, Standardized Remains

41

33,43 34,8830,97

41,25

54,9

45,11

37,34

44,89

38,04

25

30

35

4045

50

55

60

параллельные

потенциальные

серийные

Proceeding from the results obtained, it is necessary to acknowledge the homogeneous gender and age structure (distribution) of all three groups of entrepreneurs with business discontinuation experience (staying in business as parallel entrepreneurs, serial entrepreneurs or merely potential entrepreneurs after the shutting down of their previous business).

The hypothesis concerning equal average incomes of serial, parallel, and potential entrepreneurs was not substantiated, i.e. the level of financial resources of serial, parallel, and potential entrepreneurs is different.

Comparison of socio-demographic characteristics of those leaving business permanently and those staying in business shows that the average level of these groups, approximately equal in size, does not differ substantially and equals some 39 years. A similar situation is observed in respect of the gender structure (table 3.8.4). Males with business discontinuation experience prevail over females in both groups.

Table 3.8.4. Gender Distribution of Persons Leaving Business Permanently and Staying in Business, %

mail female Total:

Active 55,32% 44,68% 100,00%

Discent 54,55% 45,45% 100,00%

The average income of persons leaving business for good and those who stay in business coincides as well: entrepreneurs leaving business permanently have an average income at a level not less than those who stay in business (or intend to stay).

Business Discontinuation: Social Capital of Entrepreneurs Permanently Leaving Business and Staying in Business

The availability of social capital (including acquaintance with established entrepreneurs) seems to be an additional factor enabling not to fall out of the business environment permanently after shutting down a business.

Table 3.8.5 characterizes the social capital of entrepreneurs staying in business and leaving business: the share of persons who have connections with relatives who are entrepreneurs is higher among those who leave business only temporarily than among those who have permanently discontinued business operations (32% compared to 12%, accordingly).

Table 3.8.5.Social Capital of Entrepreneurs Staying in Business and Permanently Leaving Business,

Connections, % (the total exceeds 100% as a respondent could choose several response options)

42

Response options (see Questionnaire) Active Discent Z –test

Close relatives 14 7 <0,0532% 12%

other relatives 7 10 <0,0516% 16%

friends 24 32 <0,0554% 51%

Знакомые 28 34 <0,0564% 54%

Colleagues 8 9 <0,0519% 14%

No entrepreneurs 2 6 <0,054% 10%Total: 44 62

Success or failure of running a business by acquaintances who have lost their job during the crisis (i.e. during the past two years) and tried to become entrepreneurs does not influence the decision to discontinue a business, whereas personal knowledge of a business failure stimulates permanent business discontinuation (43% against 58%, see table 3.8.6).

Table 3.8.6. Social Entourage with Experience of Failure of those who Stayed in Business and who Permanently Discontinued Business Operations, Connections, % (the total

exceeds 100% as a respondent could choose several response options)Response options (see

Questionnaire) Active Discent Z –test

нет таких знакомых 16 27 <0,0534% 40%попытались начать свое дело, но неудачно

14 16 <0,0534% 40%удачно начали, но потом прекратили бизнес

4 12 <0,059% 18%удачно начали и до сих пор продолжают бизнес

13 13 <0,0528% 19%

затрудняюсь ответить 3 6 <0,056% 8%Всего: 46 67

Assessment of the Reasons and Consequences of Small Business Development by those who Permanently Discontinued a Business and who Stayed in Business

Analysis of the structure of assessments of the role of entrepreneurship by respondents who have temporarily or permanently suspended business operations has not revealed any significant differences in the opinions of those who have permanently left business and stayed in business (figure 3.8.5). Representatives of both groups view the development of small business first and foremost as an additional job opportunity and a source of raising the population’s living standards.

Figure 3.8.5. Small Business Development Importance Evaluations

43

Reasons of Business Discontinuation by Respondents Permanently Shutting Down their Business and Staying in Business

0% 10% 20% 30% 40% 50% 60% 70% 80%

рост неравенства в доходах

рост числа трудовых мигрантов

снижение цен на товары иуслуги

рост качества товаров и услуг

снижение социальнойнапряженности

больше возможностей покупкитоваров и услуг

повышение уровня жизнибольшинства жителей

дополнительные возможноститрудоустройства

не окончательно выбывшие окончательно выбывшие

Comparative analysis of the reasons of shutting down a business showed that the main motive of permanent business discontinuation is the striving for a quieter life, whereas temporary discontinuation of entrepreneurial activities is mainly connected with unprofitability or fund raising problems (table 3.8.7). The share of entrepreneurs permanently leaving business who said that the main cause was the “unprofitability of their business” is higher than the share of those who stayed in business (47% vs 27%).

The reasons indicated as “other” do not strongly differ between the two groups under consideration. Both those permanently and temporarily leaving business name, first of all, strong competition, high taxes, administrative pressure, and some others – also personal reasons.

Table 3.8.7.Main Reasons of Failure of Starting a Business

Response options (see Questionnary) Active Dissent Z –тест

Possibility to sell the business 2 3 <0,056% 5%

Business not profitably 11 31 <0,0527% 47%

Problems with access to external finance

5 8 <0,0512% 13%

Possibility of another job or business 3 2 <0,057% 3%

Closure planned from very beginning 1 1 <0,053% 2%

Skip to rent 1 0 <0,052% 0%

Personal reasons 8 14 <0,0519% 21%

Force major 6 1 <0,0514% 2%

Other reasons 4 5 <0,0510% 8%

Total 41 65100% 100%

44

Brief Conclusions

Analysis of early entrepreneurial strategies shows that:

1. In Russia, groups of entrepreneurs temporarily shutting up their business and permanently leaving business do not differ significantly by their socio-demographic characteristics, or the level of social capital, or the income level.

2. Permanent business discontinuation is connected with the age and other personal reasons, whereas temporary discontinuation of business operations is caused by economic and financial factors.

3. The form of business discontinuation is in no way connected with the respondents’ perception of the socioeconomic role of small-time entrepreneurship: it is on the whole favorable in both groups and involves high appraisal of the contribution made by small business in tackling the problems of employment and the population’s living standards.

8. Specifics of Entrepreneurial Activity by Settlement Type

Based on Russian GEM database of APS survey five types of settlement by the number of residents were been differentiated:

rural areas - rural and urban settlements with population less than 10 000 people; small towns - towns with population from 10 000 till 100 000 people; medium-sized towns - towns with population from 100 to 500 thousand people; cities - big cities with population from 500 thousand to 1 million people; megalopolises - large cities with population over 1 million people.

These clusters are standard classification of settlements used in demographic statistics, nevertheless, the last one requires more detailed description.

Gender

Gender structure of entrepreneurial activity is an indirect indicator of the degree of women emancipation within certain types of settlement. It can be assumed that the rate of female entrepreneurial activity will be higher in the largest and the smallest settlements (although due to diametrically different factors). However, calculations don’t confirm this assumption.

As it’s shown at the table 2, the rate of men among early-stage entrepreneurs is higher than the rate of women (55,5% against 44,5% in the whole sample). Such conclusion is right for all types of settlements except middle-sized towns. The biggest difference between male and female entrepreneurial activity is observed in small towns, where the share of men among early entrepreneurs is almost 60%.

Table 3. Gender structure of early-stage entrepreneurs in Russia by settlement types, 2006-2011

Type of settlement

Gender structure 95% confidence interval (Women)

95% confidence interval (Men)

Men Women The lower bound

The upper bound

The lower bound

The upper bound

45

MegapolisesN 51 42

38,95 51,37 49,28 60,40% 54,84% 45,16%

CitiesN 52 44

39,62 52,05 48,60 59,73% 54,17% 45,83%Medium-sized

townsN 54 58

45,55 58,02 42,63 53,79% 48,21% 51,79%Small towns N 76 51 34,04 46,27 54,37 65,32

% 59,84% 40,16%

Rural areasN 75 52

34,81 47,08 53,56 64,55% 59,06% 40,94%

TotalN 308 247

38,31 50,70 49,95 61,05% 55,50% 44,50%

Education

Almost half of the early entrepreneurs have higher education (see tab. 4). This is typical for all settlements besides small towns and rural areas (there are 59% and 44% of early-stage entrepreneurs that have high education, respectively).

Table 4. Educational structure of early-stage entrepreneurs in Russia by settlement types, 2006-2011

Type of settlement Educational structureLow Intermediate High

Megapolices N 9 31 50% 10,00% 34,44% 55,56%

Cities N 7 37 44% 7,95% 42,05% 50,00%

Medium-sized towns N 12 44 54% 10,91% 40,00% 49,09%

Small towns N 13 71 37% 10,74% 58,68% 30,58%

Rural areas N 29 55 41% 23,20% 44,00% 32,80%

Total N 70 238 226% 13,11% 44,57% 42,32%

Age

Age structure of early entrepreneurs doesn’t so much differ among different settlement types - the average age varies from 34 years in middle-sized towns till 36 in cities, small towns and rural areas.

Age distribution of early-stage entrepreneurship is shown at figure 1. Almost third of early-stage entrepreneurs is 25-34 years old in every types of settlement. Also, it was founded that group of young people (18-24) is significant part of early-stage entrepreneurs in megapolisies (they represent the fifth of all early-stage entrepreneurs in megapolisies).

Figure 1. Age structure of early-stage entrepreneurs in Russia by settlement types, 2006-2011

46

21% 16% 16% 13% 13%

36%31% 37%

34% 39%

16% 29% 25% 31% 21%

24% 19% 17% 18% 21%

3% 5% 5% 4% 6%

0%10%20%30%40%50%60%70%80%90%

100%

Megapolises Cities Medium-sizedtowns

Small towns Rural areasTypes of settlement

55-64

45-5435-44

25-3418-24

Motivation structure of early-stage entrepreneurs by settlement type

People launch businesses for a variety of reasons. They may be led into entrepreneurship out of necessity: the pursuit of self-employment when there are no better options for work. In contrast, their efforts may be powered by the desire to maintain or improve their income, or to increase their independence. GEM methodology allows to assess the motives of entrepreneurs.

Figure 2. Motivation structure of early-stage entrepreneurs in Russia by settlement types, 2006-2011

22%

8%

18%

25%

26%

92%

82%

75%

74%

78%

0% 20% 40% 60% 80% 100%

Megapolises

Cities

Medium-sized towns

Small towns

Rural areas

Opportunity-motivatedNecessity-motivated

In all types of settlement close to 3/4 of early-stage entrepreneurs are opportunity driven, except in cities where the rate of opportunity-motivated entrepreneurs equals 92 %. The share of necessity-driven entrepreneurial activity in megapolises (22%) is, on the contrary, much higher than in cities. This can be explained by the density of labor market in megapolises by highly-qualified workers and, consequently, high competition among the employees for a better place.

9. Entrepreneurship Framework Conditions in the Russian Federation: Population’s Opinions and Expert Reponses

47

Innovative development of the Russian economy needs more than mere formation of development institutions and their provision with resource support within the context of relevant governmental programs. Development of the SME innovative segment can be considered guaranteed only when it proceeds against the background of constant emergence of new startups – which is generally possible on the basis of natural selection within the framework of a powerful ongoing process of renovation of grass-root entrepreneurship. Specific regional traits of entrepreneurship development conditions (EFC) characterize the social environment and government policy of support of entrepreneurship. Notably, population’s opinions and expert evaluations of EFC in different countries may coincide or differ strongly.

Returns of the Population Poll on Entrepreneurship Development Conditions

The population’s opinion about the entrepreneurship framework conditions state and development is a powerful factor of involvement of adult able-bodied population in entrepreneurship. In this sense, EFC are a combination of external impacts on forming the population’s entrepreneurial potential on some or other territory.

However, in addition to the external environment conditions, the decision to start or continue entrepreneurial activity is influenced by an individuals’ self-evaluation of his competences, i.e. (from the point of view of the Concept of the UN Human Potential Development Program) perception of resources or one’s own human capital. The probability of an individual’s start (or continuation and development) of entrepreneurial activity varies depending on the combination of perceptions of external opportunities and his own entrepreneurial competences (knowledge, skills, psychological risk resistance, etc.) (Chepurenko, 2004).

This means that the entrepreneurial activity (at the stage of potential, early or established entrepreneurship) is a sort of response to the combination of an individual’s perception of external opportunities for entrepreneurship and his own capabilities (competences) for such activities. Only when the population’s perceptions of external opportunities are supplemented with the necessary competences economy and society receive a social stratum representing a potential for replenishing entrepreneurial ranks. The competences self-evaluation factor plays a special role in a situation of economic recession and crisis, including under the influence of economic information disseminated via the media. Consequently, analysis of the factors of raising the population’s business capabilities self-evaluation can provide a lever for forecasting development of entrepreneurial potential, which is a particularly acute task presently facing the Russian socioeconomic environment, inter alia, due to the growing tension on the labor market and other manifestations of the current crisis.

The returns of the poll conducted within the context of the GEM survey provided data for empirical analysis of development trends of the necessary and sufficient conditions for implementing the entrepreneurial potential of the Russian population.

The Russian non-entrepreneurial stratum comprises the adult population with the exception of active entrepreneurs (the aforementioned early and established entrepreneurs). This group is very huge (92.8% of the adult population of Russia) and non-homogeneous and includes 8.4% of potential entrepreneurs. The bulk of the Russian population not only has nothing to do with entrepreneurship, but does not regard the start of a business as a career development option.

Statistical analysis of the population’s assessments of competences (knowledge, skills, and experience) and external conditions for starting a business accepted for consideration only informative responses: “yes,” “no,” and “I don’t know,” whereas respondents who refused to answer were excluded from the analysis. Hence, we have identified three population categories among the population at large: optimists, pessimists, and respondents doubtful about their assessments.

48

Individual perception of entrepreneurship by the Russian population is described by the following variables:

1. Do you know someone personally who started a business in the past 2 years? 2. In the next six months, will there be good opportunities for starting a business in the area

where you live?3. Do you have the knowledge, skill and experience required to start a new business? 4. Would fear of failure prevent you from starting a business?

Cultural perception of entrepreneurship by the Russian population is described by the following variables:1. In your country, most people would prefer that everyone had a similar standard of living2. In your country, most people consider starting a new business a desirable career choice3. In your country, those successful at starting a new business have a high level of status and respect4. In your country, you will often see stories in the public media about successful new businesses

The assessments of national and cultural specifics of entrepreneurship perception by active entrepreneurs and the non-entrepreneurial part of the population coincide, and the responses distribution structure of the two population groups under comparison is practically the same. However, individual perception of conditions for starting a business differs strongly between entrepreneurs and non-entrepreneurs. This can largely be explained by a low level of the population’s awareness of entrepreneurship. Less than 35% of the population are acquainted with someone who is starting a business.

Fig. 1. Distribution of Assessments on Entrepreneurship Conditions by Active Entrepreneurs and Non-Entrepreneurial Population of Russia

ЛИЧНО ЗНАКОМЫ С ЧЕЛОВЕКОМ, КОТОРЫЙ ЗА ПОСЛЕДНИЕ ДВА ГОДА НАЧАЛ БИЗНЕС

В СЛЕДУЮЩИЕ 6 МЕСЯЦЕВ В МЕСТНОСТИ, ГДЕ ВЫ ЖИВЕТЕ, БУДУТ ХОРОШИЕ УСЛОВИЯ ДЛЯ НАЧАЛА БИЗНЕСА

ЕСТЬ ЗНАНИЯ, КВАЛИФИКАЦИЯ И ОПЫТ, НЕОБХОДИМЫЕ ДЛЯ НАЧАЛА НОВОГО БИЗНЕСА

СТРАХ ИЛИ НЕДОСТАТОЧНЫЕ СПОСОБНОСТИ К ПРЕДПРИНИМАТЕЛЬСТВУ МОГУТ ПРЕПЯТСТВОВАТЬ ВАМ В ОРГАНИЗАЦИИ БИЗНЕСА

СОГЛАСНЫ, ЧТО В РОССИИ БОЛЬШИНСТВО ЛЮДЕЙ ПРЕДПОЧИТАЕТ, ЧТОБЫ ВСЕ ИМЕЛИ ОДИНАКОВЫЙ ЖИЗНЕННЫЙ СТАНДАРТ

СОГЛАСНЫ, ЧТО В РОССИИ БОЛЬШИНСТВО ЛЮДЕЙ РАССМАТРИВАЕТ НАЧАЛО НОВОГО БИЗНЕСА КАК ЖЕЛАТЕЛЬНЫЙ ВЫБОР КАРЬЕРЫ

СОГЛАСНЫ, ЧТО В РОССИИ ТЕ, КТО УСПЕШНО ОРГАНИЗОВАЛ НОВЫЙ БИЗНЕС, ИМЕЮТ ВЫСОКИЙ СТАТУС И ПОЛЬЗУЮТСЯ УВАЖЕНИЕМ

СОГЛАСНЫ, ЧТО В РОССИИ МОЖНО ЧАСТО УЗНАТЬ ИЗ СРЕДСТВ МАССОВОЙ ИНФОРМАЦИИ ОБ УСПЕШНЫХ НОВЫХ БИЗНЕСАХ

.0%

50.0%

100.0%

непредпринимательская часть населения

About a half of non-entrepreneurs believe they do not have sufficient entrepreneurial capabilities. Most of entrepreneurs have overcome this fear or lack it altogether, although 25% of entrepreneurs do experience a lack of capabilities for running a business, which is being compensated for by experience.

In 2011, the assessment of conditions for starting a business by the non-entrepreneurial group of the population was very pessimistic: only 19% of this group consider business startup conditions favorable. The assessment of conditions by entrepreneurs is more optimistic due to their involvement (approximately 37% of entrepreneurs characterized conditions for starting a business as favorable).

49

Table. Difference in Assessments of Business Startup Conditions by Entrepreneurial and Non-Entrepreneurial Population Groups in Russia

Active entrepreneurs Non-entrepreneurial population Totaloptimists 36.9 19.1 20.4pessimists 46.3 55.6 54.9doubtful 16.8 25.3 24.7Total 100 100 100

Optimistic perception of entrepreneurship and attitude toward business in society prevails among non-entrepreneurs favorably assessing startup conditions, which makes this group strongly different from pessimists and respondents doubtful about their evaluations of the business startup conditions. All three groups of respondents are unanimous in their assessments of preferences of the living standards and inability for entrepreneurship (about 48% of non-entrepreneurs).

Figure. Factors of Assessment of Entrepreneurial Startup Conditions by Non-Entrepreneurial Groups of Russian Adult Population



СОГЛАСНЫ, ЧТО В РОССИИ ТЕ, КТО УСПЕШНО ОРГАНИЗОВАЛ НОВЫЙ БИЗНЕС, ИМЕЮТ ВЫСОКИЙ СТАТУС И ПОЛЬЗУЮТСЯ УВАЖЕНИЕМ?

СОГЛАСНЫ, ЧТО В РОССИИ МОЖНО ЧАСТО УЗНАТЬ ИЗ СРЕДСТВ МАССОВОЙ ИНФОРМАЦИИ ОБ УСПЕШНЫХ НОВЫХ БИЗНЕСАХЛИЧНО ЗНАКОМЫ С ЧЕЛОВЕКОМ, КОТОРЫЙ ЗА ПОСЛЕДНИЕ ДВА ГОДА НАЧАЛ БИЗНЕС


СТРАХ ИЛИ НЕДОСТАТОЧНЫЕ СПОСОБНОСТИ К ПРЕДПРИНИМАТЕЛЬСТВУ МОГУТ ПРЕПЯТСТВОВАТЬ ВАМ В

.0%

50.0%

100.0%

оптимисты пессимисты сомневающиеся

Optimists are often acquainted with entrepreneurs (over 55% of optimists in the non-entrepreneurial group), whereas the number stands at not more than 30% among pessimists and doubtful respondents. Twice as more optimists then non-entrepreneurs from other groups consider their knowledge and skills sufficient for starting a business.

Representatives of different types of Russian settlements are practically unanimous in their assessments of social attitudes toward entrepreneurship and individual perceptions of business startup conditions. In large cities with more than 500,000 populations the smallest percentage of non-entrepreneurs (42%) confirms media coverage of business success stories, but this difference is statistically insignificant. In towns with populations ranging from 100,000 to 500,000, there is a prevailing share of non-entrepreneurs speaking in favor of a high status and respect for successful businessmen, and also those who regard the start of a business as a desirable career option.

Figure. Distribution of Assessments of Entrepreneurship Conditions by Non-Entrepreneurs in Different Types of Russian Settlements

50









0

50

100

более 1 млн. чел0,5-1 млн. чел 100-500 тыс. чел до 100 тыс. чел села

The majority of representatives of the younger generation (under 25 years) support the opinion of a business startup being a good career option and of a high status of successful entrepreneurs. This opinion is shared by the overwhelming majority of non-entrepreneurs representing slightly older generations (25–45 years). The opinion about the preference of a uniform living standard is spread among representatives of the senior generation (45–55 years) and those who are least personally acquainted with entrepreneurs. The greatest share of people personally acquainted with starting entrepreneurs and confident in the sufficiency of their own knowledge and skills for starting a business is found among the most active part of the population (25–35 years). Half of non-entrepreneurs representing the middle generation (35–45 years) admit that fear and lack of confidence in their capabilities prevent them from organizing a business. The greatest gap was revealed between non-entrepreneurs who are and are not acquainted with startup entrepreneurs.

Figure. Distribution of EFC Assessments by Russian Non-Entrepreneurs in Different Age Groups

51









0.00

50.00

100.00

18-24 25-34 35-44 45-54 55-64

Evaluation of the prospects for organizing a new business in the course of the next three years by the Russian population was based only on informative responses to the question: “Do you plan to organize a new business within the next three years – on your own or jointly with others?” Three groups of respondents were formed as a result: those planning, not planning to organize a business and respondents doubtful about their prospects for organizing a new business.

The assessments made by respondents planning to organize their business practically coincide with the other groups of entrepreneurs in their preference of uniform living standards, but differ quite substantially from doubtful respondents and especially those who do not plan to start their own business in other social and individual characteristics of entrepreneurship perception. This difference is the strongest in perception of their own knowledge and skills needed for starting a business and in personal acquaintance with entrepreneurs. The share of those who are acquainted with early entrepreneurs is twice higher among respondents planning to start a business than among those who has not considered organizing a business.

Figure Factors of Distribution of Non-Entrepreneurial Groups of Adult Population of the Russian Federation by their attitude toward Entrepreneurship

52









0

0.5

1

планирую не планирую сомневаюсь

Most of the people planning to start a business belong to the younger generation (under 35 years). Most middle-aged people, as well as representatives of the older generation do not plan to organize their own business.

Most of the people planning to start a business live in cities with the population up to 500,000. Cities with populations from 500,000 to 1,000,000 have the greatest share of residents planning to start their own business among representatives of different types of settlements.

Figure Distribution of Inclination toward Entrepreneurship among Non-Entrepreneurial Groups of the Adult Russian Population in Different Age Groups and Settlements

18-24

25-34

35-4445-54

55-64

.0%

20.0%

40.0%

планирую не планируюсомневаюсь

более 1 млн. чел.

0,5-1 млн. чел.

100-500 тыс. чел.до 100 тыс. чел.

села

.0%

20.0%

40.0%

планирую не планируюсомневаюсь

Expert Evaluations of EFC in Russia

53

Expert interviews are used as the source of information for characterizing framework conditions for entrepreneurship development in the country. The sample of respondents includes “entrepreneurs” and “professionals”:

“Entrepreneurs” – respondents with practical entrepreneurial experience, including those enabling to evaluate one and more framework condition. They are selected above all on the basis of active experience of entrepreneurship in the country. They might be, e.g., the founders of companies or organizations.

“Professionals” – respondents directly involved in the implementation or evaluation of some structural entrepreneurial condition in the country. Experts may include politicians, scientists, government officials or other professionals working in the sphere of entrepreneurship.

In 2011, the sample consisted of 36 experts. The experts used a 5-grade scale to evaluate the entrepreneurship framework conditions and identified the factors positively and negatively influencing entrepreneurship development. They also set forth the measures which, in their opinion, stimulate entrepreneurship in Russia. Each framework condition was evaluated on the basis of 5–7 questions. For example, to evaluate entrepreneurial firms’ access to financing, experts were asked to assess the availability of different sources of financing: owner capital, loan funds, venture capital, and government subsidies. And to evaluate government policy they were asked to assess government support measures, on the one hand, and the difficulty of registering new companies and licensing their activities, on the other. Figure 4.1 shows the mean values11 of expert responses to different blocks of questions.

Figure 4.1. Mean Values of Expert Evaluations of Entrepreneurship Framework Conditions in Russia

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Внед

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вхо

да

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уп к

фин

анси

рова

нию

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льно

е и

сред

нее

обра

з...

Госу

дарс

твен

ные

прог

рам

мы

Куль

турн

ые

и со

циал

ьны

е ...

Госу

дарс

твен

ная

поли

тика

Ком

мер

ческ

ая и

нфра

стру

к...

Проф

есси

онал

ьное

обр

азо.

..

Физ

ичес

кая

инфр

астр

укту

ра

Дина

мик

а ры

нков

0

0.5

1

1.5

2

2.5

3

3.5

1.83 1.9 1.97 2.02 2.14 2.162.34 2.39

2.772.85

3.1 3.18

11 Internal consistency of the blocks of questions was tested during the mean value calculation using Cronbach’s alpha. The assessment of the level of education and government policy did not allow calculating the mean average for the entire block of questions with a high degree of reliability, therefore those blocks were divided into two subgroups.

54

In expert opinions, four framework factors – dynamics of markets, state of the physical infrastructure, professional education, and commercial infrastructure development – do not have a strong negative impact. These particular factors had been named by experts in 2010 among those that have a favorable impact on entrepreneurial climate in Russia. All the other evaluations are below the 2.5 level, which means that the state of those factors hampers the opening of new companies and development of the already existing businesses.

Experts traditionally name government policy implementation as a factor negatively influencing entrepreneurship development in the country (mean value of 2.39 estimated by the experts). Experts view as the critical factors in this sphere the length of time needed to obtain most of the required permits and licenses (mean value of 1.44 estimated by the experts) and consistency of governmental policy in respect of small and growing firms (mean value of 1.94 estimated by the experts). The evaluations of priorities of the tasks of supporting new and growing firms by the federal (mean value of 2.69 estimated by the experts) and local authorities (mean value of 2.6 estimated by the experts) seem to be relatively favorable against this backdrop. Yet the analysis of these two factors shows a considerable dispersion of assessments between high made by public officials and low made by entrepreneurs and other expert groups.

The absence of a vividly manifested orientation toward entrepreneurship in national culture (mean value of 2.34 estimated by the experts) also has a negative impact on entrepreneurship development in Russia. Experts are especially critical in respect of public opinion concerning personal successes achieved by people using their own resources (mean value of 2.22 estimated by the experts) and personal (rather than collective) responsibility for one’s own business supported by the national culture (mean value of 2.23 estimated by the experts).

Another reason of low entrepreneurial identity of Russian citizens is the existing system of elementary and secondary education (mean value of 2.14 estimated by the experts) which, in the opinion of experts, does not enable to develop in schoolchildren the knowledge and skills necessary for opening their own business (mean value of 1.74 estimated by the experts) and does not encourage students’ creative approach, self-sufficiency, and personal initiative (mean value of 2.35 estimated by the experts).

Many experts doubt the efficiency of government programs of small business support (mean value of 2.16 estimated by the experts). Although experts admit the existence of a considerable number of programs of support, it is impossible to receive it by applying to a single organization (mean value of 1.75 estimated by the experts). In addition, experts doubt the competence of officials of government bodies engaged in support of small and growing companies (mean value of 1.81 estimated by the experts), and they pointed to the selectiveness of the support programs. Compared to this, the activity of technological parks and incubator centers was recognized as quite efficient (mean value of 2.88 estimated by the experts).

In most cases negative assessments were made of the block of questions connected with the availability of financial resources for new and growing companies. Evaluating the availability of financing, experts assumed that entrepreneurial ventures experience a shortage of owner capital and it is as difficult for them to gain access to government subsidies. Obtaining investments by placing shares on the market is practically impossible for young companies. All those factors were rated from 1.65 to 1.94 according to the 5-grade scale. Experts see a source of financing more easily available to entrepreneurs in funds raised from private sources: friends, relatives, and colleagues. In addition, in expert opinion, entrepreneurs can attract venture capital (mean value of 2.34 estimated by the experts).

55

Russian experts evaluate the dynamics of the market of consumer goods and services positively whereas entry barriers, in their opinion, are becoming a serious obstacle for the companies developing new markets (mean value of 1.97 estimated by the experts). New and growing firms are the ones experiencing particular resistance from companies well established on the market (mean value of 1.86 estimated by the experts). High costs of entry on new markets along with inefficient employment of the antimonopoly legislation result in low survivorship of small and growing companies.

Active discussion of the innovation development issues during the past two years led to experts’ close attention to problems of implementation and transfer of R&D to small and growing companies. As in 2010, experts evaluated this factor quite low, giving it less than 2 grades on average. In expert opinion, the existing system of government subsidies does not allow new and growing firms to purchase new technologies (mean value of 1.68 estimated by the experts). In addition, not every company can afford it (mean value of 1.74 estimated by the experts). Moreover, there is no effective means of new knowledge transfer from universities and research centers to small companies (mean value of 1.79 estimated by the experts), whereas large well established companies have greater access to new technologies and R&D than the new and growing companies. The most favorable fact in this respect is that R&D available in the country can become the basis for establishment of world level high-tech companies (mean value of 2.58 estimated by the experts).

Experts believe that a high level of red tape and excess tax burden on new and growing companies is a serious impediment to entrepreneurship development in Russia. This factor was given the most critical assessments – an average of 1.83 estimated by the experts.

The blocks of questions included in expert interviews were not restricted to framework factors examination. The questionnaire included questions similar to those used to analyze the attitude toward entrepreneurship in society among adult able-bodied population. Among them were such factors as exploring the opportunities for creating a new business, perception of the knowledge and skills required for setting up new ventures, and assessment of the social image of an entrepreneur.

Evaluating the existence of opportunities for setting up a new business the experts expressed optimism. In their opinion, there are more such opportunities than the people willing to use them. In addition, they noted an increase in the number of opportunities for new forms during the past five years. The mean value of assessment of this factor exceeded 3.5 grades. At the same time, belief that people can easily make use of these opportunities was graded much lower (mean value of 2.54).

Analysis of results of the survey of the adult able-bodied population showed that the non-entrepreneurial part of the population perceives its knowledge and skills extremely low for starting a new business. Experts also believe that most people do not know how to create a company and run it and cannot promptly react to the emerging opportunities and raise resources necessary for a new business. The mean values of these factors’ estimates vary from 1.97 to 2.19 grades.

The opinions of experts and ASP respondents also coincide in evaluation of the social image of entrepreneurs. Experts believe that successful entrepreneurs on the whole have high status and are respected in society. Experts also think that entrepreneurship is not a desirable career option for the majority of the population (2.64 grades). Experts and entrepreneurs were not unanimous in responding to this question. Assessments made by the latter were considerably higher than evaluations made by experts who do not own their own business.

A separate block of expert interviews was devoted to protection of intellectual property rights. Experts are unanimous in their opinion that legislation in this sphere is not exhaustive and its

56

enforcement is not efficient. It is hardly possible for new and growing firms to count on strict abidance by copyrights.

The final blocks of questions were devoted to individual aspects of entrepreneurship development, such as female entrepreneurship, high growth potential entrepreneurship, innovativeness of firms, and intra-partnerships.

Experts do not think there are any special obstacles for women who wish to set up their own business. The ability to use an opportunity does not depend on gender factors, on which most experts agreed (mean value of 3.8). However, this fact also has its reverse side: in the opinion of experts, there are practically no efficient women’s support programs encouraging them to start their own business.

As the contribution made by companies to GDP is not the same, researchers found particular interest in businesses with high growth potential. The mean expert evaluation within this block of questions totaled 2.84 grades. The sufficiency of initiatives specially targeting entrepreneurship with high growth potential and acknowledgement of its importance by politicians were evaluated higher than the competence of the persons responsible for support of intensively growing companies.

Analysis of expert assessments of the interest to innovation in Russia shows the difference in the interest in innovations among customers and manufacturers of goods and services. In expert opinion, customers evaluate higher the possibility to test (mean expert evaluation of 3.33) and use innovative products (mean expert evaluation of 3.14), whereas customers are not ready to experiment with new products and services (mean expert evaluation of 2.5).

Most experts noted that the adoption of strategic decisions “from top to bottom” prevails over the adoption of decisions “from bottom to top” both in large and small and medium companies (mean expert evaluation of 4.26 and 3.86, accordingly). Apparently, Russian companies do not encourage entrepreneurship among their staff. At the same time, employers support hired employees offering new ideas (mean expert evaluation of 3.37), which is conducive to proactive (initiative) behavior of their staff. Nevertheless, many experts do not see formal restrictions if a hired employee uses resources, knowledge and contacts of the company for opening a business (mean expert evaluation of 2.94).

Using a unified questionnaire for different countries enables to evaluate the state of framework conditions in countries involved in the project. Although it seems hardly possible to give recommendations on the basis of these evaluations as they characterize framework conditions within a country and similar evaluations of some or other condition in different countries may not reflect its qualitative development level, comparison enables to reveal critical development factors in different countries. For a more vivid illustration the values of characteristics were converted into a scale from –3 (very poor state of the framework factor) to +3 (very good state of the framework factor).

Bureaucracy (Red Tape) in different types of economies, by country

57

Браз

илия

Арге

нтин

а

Иран

Ямм

айка

Венг

рия

Хорв

атия

Слов

ения

Литв

а

Порт

угал

ия

Гват

емал

а

ЮАР

Трин

идад

и Т

обаг

о

Барб

адос

Мек

сика

Слов

акия

Банг

ладе

ш

Голл

анди

я

Алж

ир

Коре

я

Норв

егия

Герм

ания

Фин

лянд

ия

Пана

ма

Тайв

ань

Синг

апур

-1.5

-1

-0.5

0

0.5

1

1.5

Ресурсно-ориентированные экономики Эффективностно-ориентированные экономикиИнновационно-ориентированные экономики

R&D, in different types of economies, by country

Ниге

рия

Слов

акия

Паки

стан

Иран

Венг

рия

Гват

емал

а

Латв

ия

Перу

Испа

ния

Чеш

ская

рес

публ

ика

Поль

ша

Вели

кобр

итан

ия

Хорв

атия

Арге

нтин

а

Коре

я

Фра

нция

Авст

рали

я

Турц

ия

ОАЭ

Фин

лянд

ия

Шве

ция

Норв

егия

Голл

анди

я

Тайв

ань

Шве

йцар

ия

-1

-0.5

0

0.5

1

1.5


Entry Barriers in different types of economies, by country

58

Иран

Босн

ия и

Гер

ц.

Колу

мби

я

Грец

ия

Хорв

атия

Венг

рия

Браз

илия

Турц

ия

Трин

идад

и Т

обаг

о

Вене

суэл

а

ЮАР

Уруг

вай

Слов

ения

Шве

ция

Ямм

айка

Фин

лянд

ия

Алж

ир

Банг

ладе

ш

Пана

ма

Чеш

ская

рес

публ

ика

Поль

ша

Авст

рали

я

Вели

кобр

итан

ия

Синг

апур

Тайв

ань

-1.5

-1

-0.5

0

0.5

1

1.5


Property Rights in different types of economies, by country

Иран

Гват

емал

а

Паки

стан

Арге

нтин

а

Грец

ия

Трин

идад

и Т

обаг

о

Банг

ладе

ш

Турц

ия

Барб

адос

Испа

ния

Венг

рия

Литв

а

Чили

Алж

ир

Поль

ша

Мал

айзи

я

ЮАР

Чеш

ская

рес

публ

ика

Слов

акия

Норв

егия

Ирла

ндия

Фра

нция

Голл

анди

я

Авст

рали

я

Синг

апур

-2

-1.5

-1

-0.5

0

0.5

1

1.5


In addition to the quantitative evaluation of entrepreneurship framework conditions, experts highlight factors preventive and conducive to improvement of the entrepreneurial climate in the country and

59

also make recommendations for improvement of the situation. Figure 4.2 reflects expert evaluations of the factors making a particularly strong impact.

Figure 4.2. Assessment of Factors Preventing or Stimulating Entrepreneurship Development by Russian Experts, %

Figure 4.3 shows the aspects where the gaps between evaluations by experts who are active entrepreneurs (“entrepreneurs”) and representatives of other expert groups (“experts”) are the widest. It turns out that entrepreneurs are on the whole more optimistic about special measures – financial support, government programs, but far less positive about the overall evaluation of the government policy, existing market entry barriers, and the population’s mentality.

Figure 4.3. Assessment of the Degree of Favorability of Various Factors by Different Groups of Experts

60

9. APPENDIX

61

Appendix 1Glossary of Main Measures and Terminology Measure Description

Entrepreneurial Attitudes and PerceptionsPerceived opportunities Percentage of 18-64 population (individuals involved in any stage of entrepreneurial activity excluded)

who see good opportunities to start a firm in the area where they livePerceived capabilities Percentage of 18-64 population (individuals involved in any stage of entrepreneurial activity excluded)

who believe to have the required skills and knowledge to start a businessEntrepreneurial intention Percentage of 18-64 population (individuals involved in any stage of entrepreneurial activity excluded)

who intend to start a business within three yearsFear of failure rate Percentage of 18-64 population with positive perceived opportunities (individuals involved in any

stage of entrepreneurial activity excluded) who indicate that fear of failure would prevent them from setting up a business

Entrepreneurship as desirable career choice

Percentage of 18-64 population who agree with the statement that in their country, most people consider starting a business as a desirable career choice

Media attention for entrepreneurship

Percentage of 18-64 population who agree with the statement that in their country, you will often see stories in the public media about successful new businesses

Entrepreneurial Activity Nascent entrepreneurship rate

Percentage of 18-64 population who are currently a nascent entrepreneur, i.e., actively involved in setting up a business they will own or co-own; this business has not paid salaries, wages, or any other payments to the owners for more than three months

New business ownership rate

Percentage of 18-64 population who are currently a owner-manager of a new business, i.e., owning and managing a running business that has paid salaries, wages, or any other payments to the owners for more than three months, but not more than 42 months

Early-stage entrepreneurial activity (TEA)

Percentage of 18-64 population who are either a nascent entrepreneur or owner-manager of a new business (as defined above)

Established business ownership rate

Percentage of 18-64 population who are currently owner-manager of an established business, i.e., owning and managing a running business that has paid salaries, wages, or any other payments to the owners for more than 42 months

Overall entrepreneurial activity rate

Percentage of 18-64 population who are either involved in early-stage entrepreneurial activity or owner-manager of an established business (as defined above)

Business discontinuation rate

Percentage of 18-64 population who have, in the past 12 months, discontinued a business, either by selling, shutting down, or otherwise discontinuing an owner/management relationship with the business. Note: This is NOT a measure of business failure rates.

Improvement-driven opportunity entrepreneurial activity: relative prevalence

Percentage of those involved in early-stage entrepreneurial activity (as defined above) who (i) claim to be driven by opportunity as opposed to finding no other option for work; and (ii) who indicate the main driver for being involved in this opportunity is being independent or increasing their income, rather than just maintaining their income

Entrepreneurial AspirationsHigh growth expectation early-stage entrepreneurial activity(HEA)

Percentage of 18-64 population who are either a nascent entrepreneur or owner-manager of a new business (as defined above) and expect to employ at least 20 employees five years from now

High growth expectation early-stage entrepreneurial activity: relative prevalence

Percentage of early-stage entrepreneurs (as defined above) who expect to employ at least 20 employees five years from now

New product-market oriented early-stage entrepreneurial activity: relative prevalence

Percentage of early-stage entrepreneurs (as defined above) who indicate that their product or service is new to at least some customers and indicate that not many businesses offer the same product or service

Early-stage entrepreneurial activity in technology sectors: relative prevalence

Percentage of early-stage entrepreneurs (as defined above) who are active in the ‘high technology’ or ‘medium high’ technology sector, as classified by OECD (2003)

62

Appendix 2NATIONAL STATISTICS BY AGE/GENDER/STRATA USED BY Russian GEM TEAM as a statistical base for a STARTIFIED SAMPLE (AGES 18 TO 64)

Strata

Male Female18-24

25-34

35-44

45-54

55-64

18-24

25-34

35-44

45-54

55-64

North-West: cities > 1,000 ths 266 327 260 304 221 245 343 305 407 310North-West: cities 100 - 500 ths 189 248 194 229 135 204 259 216 291 189North-West: towns < 100 ths 236 310 254 303 157 192 300 270 360 218North-West: rural districts 133 175 178 205 115 104 158 162 200 144Central: cities > 1,000 ths (Moscow) 585 928 735 749 510 526 831 711 855 655Central: cities 500 - 1,000 ths 147 191 153 185 123 150 201 175 234 174Central:cities 100 - 500 ths 454 590 483 574 378 456 629 554 726 543Central: towns < 100 ths 524 746 631 767 468 492 757 693 911 659Central: rural districts 336 503 512 577 402 310 486 473 569 539Volga: cities > 1,000 ths 337 446 344 404 261 363 475 395 518 374Volga: cities 500 - 1,000 ths 275 360 280 325 207 291 382 323 420 278Volga: cities 100 - 500 ths 272 379 310 348 205 305 401 352 432 282Volga: towns < 100 ths 382 545 486 564 312 385 564 526 642 420Volga: rural districts 398 652 671 654 422 365 618 602 643 541South: cities > 1,000 ths 137 168 126 145 105 138 175 141 183 146South: cities 500 - 1,000 ths 78 90 69 79 55 82 96 77 98 76South: cities 100 - 500 ths 341 366 276 306 205 338 390 320 383 280South: towns < 100 ths 280 355 295 330 214 260 373 326 384 295South: rural districts 460 663 577 559 383 459 664 575 594 507Ural: cities > 1,000 ths 157 197 139 162 107 166 211 160 213 154Ural: cities 500 - 1,000 ths 40 42 32 34 18 41 44 36 43 25Ural: cities 100 - 500 ths 143 214 163 191 102 151 215 177 229 140Ural: towns < 100 ths 262 393 319 372 187 257 388 331 418 244Ural: rural districts 117 172 169 189 104 112 166 160 189 130Siberia: cities > 1,000 ths 178 211 160 185 115 181 221 180 232 161Siberia: cities 500 - 1,000 ths 184 225 159 178 113 209 243 179 231 162Siberia: cities 100 - 500 ths 279 332 238 278 160 285 342 263 348 221Siberia: towns < 100 ths 304 424 337 412 211 292 419 358 469 274Siberia: rural districts 288 414 395 461 245 277 410 387 470 297Far East: cities 500 - 1,000 ths 93 101 72 81 60 81 106 77 102 82Far Easta: cities 100 - 500 ths 106 125 88 100 61 98 127 91 121 80Far East: towns < 100 ths 157 223 171 215 116 130 212 171 241 145Far East: rural districts 116 132 109 126 71 78 120 104 130 82

Total8253

11249

9384

10593

6550

8024

11324

9870

12287

8823

* Strata numbers and labels must correspond to XXSTRATA variable

63

Appendix 3

2011 GEM Russia APS Strata Definition and Fieldwork Report

Description of strata

Number of

different phone

surveys called /

households called on (f-f

surveys)

Number of

answered calls/doo

rs

Number of

eligible househol

ds contacted

Number of

interviews

agreed to*

Number of

interviews

refused*

Number of

incomplete

interviews*

Number of

completed

interviews*

North-West: cities > 1,000 ths 1224 252 335 257 78 24 233North-West: cities 100 - 500 ths

1194 276 224 169 55 0 169

North-West: towns < 100 ths 1033 233 252 202 50 0 202North-West: rural districts 518 88 160 123 37 1 122Central: cities > 1,000 ths (Moscow)

2145 506 684 564 120 16 548

Central: cities 500 - 1,000 ths 389 104 180 150 30 19 131Central:cities 100 - 500 ths 1708 355 547 452 95 42 410Central: towns < 100 ths 1749 324 657 555 102 38 517Central: rural districts 839 160 422 392 30 32 360Volga: cities > 1,000 ths 1263 379 381 306 75 2 304

Volga: cities 500 - 1,000 ths 785 371 280 246 34 0 246

Volga: cities 100 - 500 ths 933 288 361 280 81 20 260

Volga: towns < 100 ths 1207 352 475 383 92 3 380

Volga: rural districts 1242 424 529 431 98 3 428

South: cities > 1,000 ths 653 220 162 119 43 0 119

South: cities 500 - 1,000 ths 85 7 64 62 2 0 62

South: cities 100 - 500 ths 890 257 314 253 61 1 252

South: towns < 100 ths 593 124 274 245 29 2 243

South: rural districts 1104 232 508 435 73 0 435

Ural: cities > 1,000 ths 471 196 198 129 69 0 129

Ural: cities 500 - 1,000 ths 224 75 43 30 13 1 29

Ural: cities 100 - 500 ths 390 109 193 131 62 0 131

Ural: towns < 100 ths 569 143 303 246 57 0 246

Ural: rural districts 227 50 123 118 5 0 118

Siberia: cities > 1,000 ths 373 92 167 148 19 5 143

Siberia: cities 500 - 1,000 ths 502 164 191 154 37 6 148

Siberia: cities 100 - 500 ths 618 176 253 221 32 5 216

Siberia: towns < 100 ths 804 240 341 274 67 3 271

Siberia: rural districts 693 141 335 288 47 3 285

Far East: cities 500 - 1,000 ths 164 54 87 68 19 0 68

Far Easta: cities 100 - 500 ths 212 53 122 75 47 0 75

Far East: towns < 100 ths 242 39 153 137 16 0 137

Far East: rural districts 150 15 102 83 19 0 83

Total 25193 6499 9420 7726 1694 226 7500

64

i These phases coincide with the classification by the most recent Global Competitiveness Report into factor driven, efficiency driven and innovation driven economies. See Global Competitiveness Report (2008). ii Evidence is documented by e.g. Carree and Thurik (2003), Acs (2006), Audretsch, (2007).iii See Wennekers, Van Stel, Thurik, and Reynolds (2005), Gries & Naude (2008)iv In the construction of the annual Global Competitiveness Index, weights are used in accordance with these notions. Thus, for factor-driven economies the state of basic requirements adds most to the overall index.- v The sample sizes in the GEM study typically range from 2,000 to 3,500. Notable exceptions are Spain (31,000 respondents) and the UK (8,000 respondents) and Russian Federation (7,500 respondents).

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