Source document: https://docs-lawep.s3.us-east-2.amazonaws.com/1698060243911.pdf (Georgia)
Survival(ship) and Entrepreneurship Empirical evidence from Georgia and Armenia PHILIPPE RUDAZ IRINA GURULI HRANT MIKAELIAN Survival(ship) and Entrepreneurship Empirical evidence from Georgia and Armenia PHILIPPE RUDAZ IRINA GURULI HRANT MIKAELIAN Acknowledgements It was supervised by Prof. Paul Dembinski at the University of Fribourg, Switzerland whose This paper is a consolidated analysis of the results of two research projects –the Emergence and comments, thoughts and advices were precious and crucial to its success.
Data analysis Evolution of Entrepreneurship in Georgia and the Emergence and Evolution of Entrepreneurship was greatly enhanced by the contribution of his collaborator, Hannah Soisson.

Both research in Armenia - which examined self-employed, micro and small entrepreneurs in two post-Soviet projects were parts of the Academic Swiss Caucasus Net (ASCN) project at University of economies through survey data.

Friburg, Switzerland, coordinated by Denis Dafflon and directed by Prof. Nicolas Hayoz.
We thank them both for their support and availability.

It was coordinated and supervised by Prof. Paul Dembinski whose comments were precious.

Data analysis was greatly enhanced by the contribution of his collaborator, Ms. Hannah Soisson.

In Georgia, the data was gathered by the Business Statistics department, led by Gogita Todradze, Both projects were parts of the Academic Swiss Caucasus Net (ASCN) project at University of of the National Georgian Statistical Agency.
In Armenia, the research project partnered Freiburg coordinated by Denis Dafflon and directed by Prof. Nicolas Hayoz.

with the Caucasus Resource Research Centers - Armenia, directed by Heghine Manasyan and coordinated by Naira Vardanyan.

Since its inception, this research received feedback, The entire project was made possible by the Gebert Rüf Foundation in Switzerland, directed by comments and support from many colleagues.
We thank in particular Nino Evgenidze (EPRC), Dr. Philipp Egger to whom we express the deepest gratitude.

Koba Turmanidze (CRRC), Eric Livny, (Tbilinomics Policy Advisors), Paata Brekashvili (Caucasus University), Susanne Fehlings (University of Frankfurt), Hasan Karrar (Lums University), Leila Rekhviashvili (Leipzig University), Angela Prigozhina (World Bank), Helen Bradbury (Mercy Corps), Adam Pellilo (La Salle University), Norbetto Pignatti (ISET), Karine Torosyan (ISET), Jayne Winter (UNCTAD).
The entire project was made possible by the Gebert Rüf Foundation in Switzerland, directed by Philipp Egger to whom we express the deepest gratitude for his support, trust and flexibility.

Table of Contents Acknowledgements Executive summary The making of the informal entrepreneur The study The emergence of entrepreneurship in Georgia Introduction General characteristics of the sampled population Escaping survival Formal and informal activities Motivations Accepting risks… …For a reward?
The emergence of entrepreneurship in Armenia General characteristics of the sampled population Escaping survival Formal and informal activities Motivations Accepting risks… …For a reward?

Conclusion Annex 1 Annex 2 Annex 3 Annex 4 Bibliography 2 4 6 14 18 18 19 23 23 24 26 27 31 32 34 34 36 38 40 44 48 49 50 51 53 3 Executive summary Entrepreneurship in developing and transition economies appears to be “of a different kind” to entrepreneurship in the developed world.
The majority of entrepreneurs in developing econ- omies are usually informal self-employed.

The incentive structure in which entrepreneurs in transition economies evolve reflects rapid change and extreme uncertainty, restructuring, im- balances between supply and demand, weak market institutions and numerous informal rules and norms inherited from the previous regime.
To account for the difference, a distinction has been made between “entrepreneurship by op- portunity” and “entrepreneurship by necessity”, with the assumption that entrepreneurs shift from one category to the other automatically, provided the “ecosystem” is conducive to entre- preneurship.

Yet, researchers and practitioners are starting to understand how difficult the tran- sition from “entrepreneurship by necessity” to “entrepreneurship by opportunity” is.
“Entrepre- neurship” is a hard phenomenon to define, for it crosses the boundaries of several disciplines.

The particular context of “transition” adds a layer of complexity into the issue of entrepreneur- ship.

This phenomenon must be understood in the context of the vacuum left by the disappear- ance of the USSR, which resulted in a restructuring of economic, social, political and territorial structures.
These realignments have produced multiple trajectories that move away from the liberal model towards which the “transition” should have carried them.

Self-employment, large- ly based on trading and farming, rose as the economic activity par excellence for survival.

It still occupies the majority of the population in former soviet economies.

This study addresses the knowledge gap left by current international programmes and research on entrepreneurship.
Through a series of surveys about attitudes and behaviours, it assesses 4 E X E C U T I V E S U M M A R Y the extent to which people engaged in running small scale businesses in Georgia and Armenia can be thought of as entrepreneurs.

The initial findings of the research projects strengthen the case for attempting to reach a more nuanced understanding of entrepreneurial activity in tran- sition economies.
The study conducted in Georgia is based on a two-year, longitudinal panel survey of a cohort of 600 self-employed, micro and small businesses.

The study surveyed of the same panel of 350 self-employed, 150 micro and 100 small firms in three regions of Georgia (Tbilisi, Kakheti and Adjara) four times.

In Armenia only one round of interviews was conducted in Yerevan and Lori Province in April 2016.
In Yerevan, 420 face-to-face interviews were planned, in Lori province, 180 face-to-face interviews were planned.

One of the limitations of the Armenian survey was the low number of people who were self-employed in agriculture who were surveyed, since most of farmers do not pay taxes except when they process food or hire people outside of their house- hold.

Very few of them are in the State Revenue Committee’s taxpayers list, which was used to draw the sample of the surveyed population.
This makes the sample used to survey Armenian self-employed biased towards more formal activities.

In spite of the differences in the implementation of the research in Georgia and Armenia, the study sheds light on how similar the self-employed and micro firms are.

Micro firms are formally registered as such, obliged to keep accounting records and are mostly active in service indus- tries located in urban areas.
The self-employed tend to be unregistered, keep no records and are generally based in rural areas.

Yet, despite these important differences, in many other dimen- sions related to entrepreneurship micro-enterprises behave like the self-employed, suggesting that registration and accounting does not constitute a trigger to full formalization.
Independence tests1 reveal significant relationships between the degree of formality of self-employed and micro firms and their degree of motivation, the extent to which they plan future activities and the resources they rely on.

For self-employed and micro firms, formalization is strongly linked to the other dimensions of entrepreneurship in all the four rounds.

This is not the case at all for small firms.


The way self-employed people and micro business representatives structure their activities is related to all the other dimensions of entrepreneurship.

This further consolidates the argument that micro firms should be viewed in the same light as the informally self-employed.
1 Kendall B and Spearman Rho 5 The making of the informal entrepreneur A blog entry on the site of the World Economic Forum lists the “9 countries with the most entre- preneurs”.2 It is based on a research by Approved Index, a business-networking group.

Its list is the perfect product of the confusion that reigns in entrepreneurship studies and perhaps more widely in the field of economic development studies.
The index identifies the level of entrepre- neurial activity by calculating the percentage of the adult population that owns or co-owns a new business and that has paid salaries or wages for three or more months.

On this basis it lists Uganda, one of the poorest countries on earth, as number one.

This is because self-employment is often taken as an indicator of entrepreneurship (Naudé, 2013), despite the fact that it does not reflect the reality of developing countries.
At the root of the problem lies the occupational approach to entrepreneurship, which views it as the result of an individual’s voluntary choice between waged employment and self-employment (Murphy et al., 1991).

Even though entrepreneurship and self-employment are different, the majority of research on the subject conflates these two concepts (Parker, 2004).
Some researchers maintain that self-employment (which, in developing countries, is mostly informal) is a form of incipient en- trepreneurship by people who prefer to have low levels of income and high independence.

In other words, we can call this type of entrepreneurship voluntary self-employment (Benneth & Rablen, 2015).

In the same vein, according to Albrecht et al.


(2009), people choose freely between four types of economic activity: unemployment, informal self-employment, formal self-employ- ment and formal employment.

The type of economic activity undertaken, from this perspective, is a voluntary choice.

This is not trivial.

It influences how the overwhelming majority of economic activity in the de- veloping world is categorized.
ILO database estimates that self-employment accounts for 45 2 World Economic Forum, Blog entry: https://www.weforum.

org/agenda/2015/06/ the-9-countries- with-the-most- entrepreneurs/ The same article was published in Business Insider with the title “The countries with the most entrepreneurship percent of global total employment.
This figure rises up to 74 percent for Sub-Saharan Africa.3 Moreover, the figure includes only non-agriculture employment, and so excludes subsistence farmers from this global picture.

Another study estimates that half of the workers in the devel- oping world are self-employed and most of them participate in the informal economy (Margolis, 2014).

The concept of entrepreneurship in the developing world usually refers, in fact, to informal, sub- sistence self-employment.
This is a far cry from the Schumpetarian creative destruction process with its emphasis on innovation.

To understand if the notion of the ‘informal entrepreneur’ is therefore just an illusion, we should review the concepts of “entrepreneurship” and “informal- ity”.

“Entrepreneurship” is a hard phenomenon to define, for it crosses the boundaries of several disciplines.
Economics and management, law, political science and anthropology have all con- tributed to the development of “entrepreneurship” as an academic field of study.

Entrepreneur- ship is a multidimensional concept.

The supply and demand sides of entrepreneurship comprise many factors of demographic, technological, industrial and economic development.

Government intervention and culture can also shape entrepreneurial activity (Verheul et al., 2001).
It is hard to agree on a definition of entrepreneurship and entrepreneurs because of their heterogeneity.

A manager and even an employee can display entrepreneurial qualities.

There are also the falsely self-employed who, in practice, work for a single firm and cannot be considered as entrepre- neurs.

One can understand the difficulties in identifying entrepreneurship in the light of the lack of data gathered on micro, small and medium-sized enterprises.
The Micro-, Small- and Medium Enter- prise (MSME) Country Indicator published by the World Bank gathers data on MSMEs from all kind of sources.

It presents secondary data, which are not always standardized across countries and time.
The original data are collected by diverse institutions (statistical institutes, ministries, international organizations, small business promotion agencies, research institutions and others) using different methods (survey, census and others).4 Data on the number of SMEs are available for only 50 percent of non-OECD countries.

Data on contribution of those SMEs to employment are available only for 30 percent of all countries.
When it comes to the contribution of those SMEs to GDP, the percentage of countries for whom data are available drops to 10 percent.

3 World bank data https://data.worldbank.

org/ 4 See the methodological note http://www.ifc.org/ wps/wcm/connect/ b06d0b004958619ba722 b719583b6d16/MSME- CI-MethodologyNote.
pdf?MOD=AJPERES&- CACHEID=b06d0b00495 8619ba722b719583b6d16 7 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P To illustrate how vague the definition of entrepreneurship can be, consider the Global Entrepreneur- ship Monitor (GEM), which defines entrepreneurship as “any attempts at new business or new ven- ture creation, such as self-employment, a new business organization, or the expansion of an existing business by an individual, a team of individuals, or an established business” (GEM, 2017).
The GEM applies a very broad definition of entrepreneurship and thus has had to develop a distinction between “entrepreneurship by opportunity” and “entrepreneurship by necessity”.

It does not indicate if entrepreneurs can shift from one category to the other or how they would do so.

Moreover, it does not survey existing functioning formal or informal enterprises, but only individuals with entrepreneurial ambition and national experts.
The GEM can therefore provide a valuable assessment of the environment of entrepreneurial aspiration but does not survey the level of entrepreneurial activity as a process.

The World Bank’s Doing Business index5 focuses only on the formal procedures for registering and closing a business and provides some indicators on access to finance.

It is therefore limited to the regulatory environment of formal enterprises, large or small.
The World Bank’s Enterprise Survey6 does provide researchers with a large database of small, medium and large enterpris- es and, in some cases, offers panel data for these enterprises for some countries.

The major limitation of the Enterprise Survey is that it surveys only formal enterprises which are active in manufacturing, retail and services.

As a result, the self-employed, who are mostly active in agri- culture, are not taken into account.
The Global Entrepreneurship Index7 focuses on the extent to which each country’s ecosystem favours or impedes entrepreneurship.

It is based on interviews with experts and the private sector, but it does not focus on enterprises or self-employment.

5 http://www.doing- business.org/rankings 6 http://www.enterpri- sesurveys.org/ 7 https://thegedi.
org/global- entrepreneurship- and-development- index/ 8 https://unstats.un.org/ sdgs/metadata/ From a policy perspective there is a large overlap between the economic agenda related to entrepreneurship and informality issues.
The policy question is as follows: how to create oppor- tunities so “informal entrepreneurs by default” become “formal entrepreneurs by opportunity”, even if, from an empirical point of view, we have very little information about the shift from an informal entrepreneurship by default to a high growth entrepreneurship driven by opportunity.
Despite this lack of empirical evidence, the international development community continues to use the concept of “entrepreneurship” and opportunity creation as a means of reducing infor- mality.
This is clearly shown by the way “entrepreneurship” is introduced by direct citation in the Sustainable Development Agenda (SDG 4 and SDG 8 – table 1 below). Target Indicator Indicator 4.4.1: Proportion of youth and adults with information and com- munication technology (ICT) skills, by type of skills.

Source: UNESCO Institute for Statistics.

Indicators 8.3.1: Proportion of informal employment in non-agriculture em- ployment, by sex.
Source: ILO SDG 4 Target 4.4: By 2030, substantially SDG 8 increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship.
Target 8.3: Promote development-ori- ented policies that support produc- tive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enter- prises, including through access to financial services.
Table 1: SDG 4 and SDG 4 and their corresponding indicators SDG 4 associates entrepreneurship with quality education and proposes to measure it with increased skills and training in ICT, while SDG 8 links entrepreneurship with formalization.
This results in a tendency to formulate entrepreneurship policies designed to reduce poverty, educate vulnerable groups of population and move the informal sector into formality, while at the same time developing the private sector, without a clear definition of what “entre- preneurship” really means or whether it can achieve these goals.
As Hoffmann, Larsen and Oxholin (2006: 10) put it: “available indicators measure everything from personal attributes of entrepreneurs like gender to outcomes of the entrepreneurial process like start-up rates”.

This underlines the need for a more precise and contextualized definition of entrepreneurship.

A better understanding of the impact of entrepreneurship on economic development will be otherwise difficult.
The heterogeneity of the informal sector has led to the use and misuse of labels that attempt to capture accurately the phenomena of informality.

The difficulty of grouping diverse activ- ities under the same term is reflected by the myriad different names: hidden economy, grey 9 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P economy, shadow economy, subterranean economy, underground economy, informal em- ployment, unobserved economy.
Many different schools of thought, influenced by different disciplines, contributed to the impressive literature on the informal sector.

The structuralist school considers the informal sector to be a product of capitalism.

The “legalist” point of view, facilitated by the use of the Institutional Economy framework made famous by North (North, 1991, North, 1997), connects formal and informal economies via a web of formal and informal institutions.
The dualist approach argues that the informal sector is separate from the formal one (La Porta and Shleifer, 2014), contending that there are almost no linkages between the two.

It was previously thought that the informal sector rests on unregistered, sometime illegal, activities.

Current thinking recognizes that it contributes significantly to GDP and employment and that is it made up of diverse activities (Chen, 2007).
Since the turn of the millennium, the entrepreneurship literature has started to consider informally self-em- ployed people as entrepreneurs.

Entrepreneurship in emerging and transition countries appears to be different to entrepreneur- ship in the developed world.
The incentive structure in which entrepreneurs in transition econo- mies evolve reflects rapid change and extreme uncertainty, restructuring, imbalances between supply and demand, weak market institutions and numerous informal rules and norms inherited from the previous regime.

A focus on status could differentiate between self-employed and those who seek to grow their business.

One could also single out push versus pull factors in a dichotomy based on motivational factors (Estrin et al., 2005).
The particular context of “transition” adds a layer of complexity into the issue of entrepreneur- ship.

This phenomenon must be understood in the context of the vacuum left by the disappear- ance of the USSR, which resulted in a restructuring of economic, social, political and territorial structures.

These realignments have produced multiple trajectories that move away from the liberal model towards which the “transition” should have carried them.
Self-employment, large- ly based on trading and farming, rose as the economic activity par excellence for survival.

It still occupies the majority of the population in former soviet economies.

There is therefore a need to understand what triggers the emergence entrepreneurial activi- ty.

Some studies do not corroborate the conception of informal self-employment as incipient entrepreneurship, but rather view it as a survivalist strategy (Temkin, 2009).
Yet such empirical 10 studies are extremely rare in the context of post-soviet economies.

This study addresses the knowledge gap left by current international programmes and research on entrepreneurship.
The initial findings of the research projects conducted in Georgia and Armenia, presented in detail in the following chapters, strengthen the case for attempting to reach a more nuanced under- standing of entrepreneurial activity in transition economies.

This attempt to address this gap was at the core of the two research projects conducted in Georgia and in Armenia between 2012 and 2017 and supported by Academic Caucasus Swiss Net and the Gebert Rüf Foundation.
The working definition “entrepreneurship” chosen for these two projects was founded on “pro- cesses of discovery, evaluation and exploitation of opportunities” (Shane and Venkataraman, 2000, p. 218).

It covers the grounds between “intention to” and the actual “action of” creating and managing an enterprise or a business with the objective of creating a sustainable source of income.

It supposes the establishment of an organizational unit, which may or may not be a legal entity.
It also supposes that the discovery and exploitation of opportunity is influenced by the institutional framework in which entrepreneurs are embedded.

The interplay between avail- able resources, perceived opportunities and socio-economic institutions, in conjunction with the motivation and vision of entrepreneurs, shape entrepreneurship as it is emerging in Georgia and Armenia.

Entrepreneurship is a multi-dimensional process (Dembinski 2006, UNCTAD, 2012).
As the dia- gram below shows, available resources and opportunities depend on a given socio-economic reality, which can be characterized by its level of economic, educational and technological de- velopment.

But resources and opportunities are not necessarily available for everybody.

Laws are the institutional constraints that define legal opportunities and thus what might count as a profitable activity.
By the same token, informal institutions (norms, mindsets, traditions) in- fluence what is seen as socially acceptable profitable activity.

At the intersection of these two modes, the changer (the agent) is the entrepreneur who is able to transform a perceived prof- itable opportunity into reality.

The motivation to do so is more complex than mere financial reward and encompasses for example, the desire to be one’s own boss, work independently, and to innovate.
11 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P IDEAL MODE Vision TECHNOLOGICAL MODE Motivation EFFICIENT MODE Changer capabilites identification feasability check implementation new profitable activities Available resources & opportunities MATERIAL MODE Formal & informal institutions FORMAL MODE Diagram 1: Multimodal causation grid applied to entrepreneurship (Dembinski, 2006) This framework is well adapted to the problematic of entrepreneurship in transition.
Network and relations are important features of post-communist economies.

Parallel circuits, blat and networks are entrepreneurial responses to the shortages of centrally planned economies and part of the resources available (Smallbone and Welter, 2001).

The framework is also well adapt- ed to the study of the informal sector.
In fact, these dimensions of entrepreneurship overlap with the dimensions of informality identified by Guha-Khasnobis, Kanbur and Ostrom (2006), namely, the degree of structuring of enterprises and the reach of official governance.

The first dimension relates to the organization of an activity and the predictability of the framework according to which individuals in the organization act.

The second dimension relates to the interaction of the organization with the structure of official governance.
Let us consider the two cases this report deals with: Georgia and Armenia.

12 The graph below describes the percentage of self-employment in transition countries in 2017.
As graph 1 shows, self-employment represents a large proportion of total employment in both coun- tries.9 According to mainstream entrepreneurship research, influenced by the framework cited above, these self-employed people predominantly operate in the informal sector and are “entre- preneurs by necessity”.

In this case, self-employment is a survival response to the lack of other employment opportunities.
Conversely, self-employed people might have opted out of employ- ment to start a business because they discovered an opportunity and have the chance to exploit it.

The so-called necessity-driven entrepreneurship is more prevalent in less developed and de- veloping economies, while necessity as a motivating factor gradually decreases with the level of economic development.

At the same time opportunity driven entrepreneurship increases (Kelley, Singer, and Herrington, 2012).
This echoes the U-shape relationship between self-employment and GDP per person employed, describing a negative correlation between the two, which is strong ev- idence for the inadequacy of self-employment as a measure of entrepreneurship (UNCTAD, 2018).
80 70 60 50 40 30 20 10 Graph 1: Total self-employed in Armenia and Georgia, from 1995 to 2017 Armenia Georgia Thus, the prevalence of self-employment and the informal economy across Caucasus countries deserves more attention.
On the one hand, institutional theories and measurement methods have allowed some progress in the understanding of informal economic activity in general.

On the other hand, there is still a lack of empirical material that would help to clarify the contextual specificities of the countries.

What are the activities, gender, age, education (just to state basic characteristics) of these economic actors producing one third of the GDP of the two countries?
3 Self-employed workers include four sub-cat- egories of employers, own-account workers, members of producers cooperatives and con- tributing family workers https://data.worldbank.

org/indicator/SL.EMP.

SELF.ZS 13 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P The study The study conducted in Georgia is based on a two-year, longitudinal panel survey of a cohort of 600 self-employed, micro and small businesses.
The study surveyed of the same panel of 350 self-employed, 150 micro and 100 small firms in three regions of Georgia (Tbilisi, Kakheti and Adjara) four times.

Longitudinal studies try to establish the sequence of a process.

Thus “cross-sectional information deals with status, while longitudinal information concerns with progress and change in status.
This implies that the term “longitudinal data” denotes repeated measurements of the same individuals over a time span long enough to encompass a detecta- ble change in their developmental status” (Rajulton, 2001:170).

Longitudinal cohort studies have the advantage of tracking processes.

The deeply evolutionary aspect of the phenomenon of en- trepreneurship requires such a methodology.
Different competencies are used at different time in the entrepreneurial process, making a longitudinal research design very useful.

Furthermore, the environment in which potential and active entrepreneurs evolve in Georgia is very uncertain and many reforms were planned from 2012 to 2014.

It is important to state the limitation of this research design.

The time span of observation needs to be “long enough to encompass a detectable change in their developmental status” (Rajul- ton, 2001:171).
There is no optimal length of time and it depends on the subject.

However, social change (of which entrepreneurship can be part) is complex and its diffusion can take many years.

Four waves of interviews cannot prove a causal mechanism underlying the emergence of entrepreneurship.

Furthermore, there is a problem of bias because the sample population is not representative of the population at large.

The self-employed might all share a common charac- teristic that introduces a bias in the study.
In Georgia, sampling frame for small enterprises was provided by internal sources from the Georgian Statistical Agency.

The Tax Office provided a database of micro-entrepreneurs to form the sampling frame for the corresponding cohort.

Household survey results were used to build the sampling frame for the cohort of self-employed.

Sampling was conducted for the first round, and selected respondents participated in all rounds.
A stratified random sampling method was used for the survey study in both Georgia and Ar- menia.

The sample is only representative of the enterprise population in the regions of Kakheti, 14 Adjara, and Tbilisi, Lori and Yerevan.

It does not cover the enterprises population of the entire two countries.

Table 2 below gives an overview of the number of enterprises interviewed in Georgia and Ar- menia, by size and region.
The different definition of self-employed, micro and small firms in Georgia and Armenia can be found in annex 1.
Self-employed Self-employed Micro-firms Self-employed Small firms Self-employed Total Self-employed Georgia Adjara Kakheti Tbilisi Armenia Lori Yerevan 125 186 39 105 245 22 26 102 45 105 24 20 56 30 70 171 232 197 180 420 Table 2: Overview of the numbers of interview done by regions and size of enterprises in Georgia and Armenia Empirical evidence of the state of affairs of Armenian small entrepreneurship sector is very sparse and insufficient to give a clear understanding of the phenomena of small and micro entrepreneurship.
Some fragmentary data can be collected from the Tax Service website.

Al- though it includes the whole enterprise population, the amount of published data is very limited and can only provide basic numerical variables.

Sociological issues such as motivation, read- iness to risk, to invest, self-esteem, problem solving skills and others remain outside of the picture.
Moreover, state agencies register only formal enterprises, formal workers, or formal parts of enterprises – not the cases when enterprises hide parts of their income, employees, or turnover from the state agencies.

The main source for the study is data gathered from a survey of 600 small and micro-enterprise representatives and self-employed people.

In addition to the survey data, the external sources were used to provide context, strengthen argumentation and add international comparisons.
That exact same methodology could unfortunately not be replicated in Armenia, where only one round of interview was conducted in Yerevan and Lori Province in April 2016.

In Yerevan, 420 face-to-face interviews were planned, in Lori province, 180 face-to-face interviews were 15 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P planned.
One of the limitations of the Armenian survey was the low number of people who were self-employed in agriculture who were surveyed, since most of farmers do not pay taxes except when they process food or hire people outside of their household.

Very few of them are in the State Revenue Committee’s taxpayers list, which was used to draw the sample of the surveyed population.

This makes the sample used to survey Armenian self-employed biased towards more formal activities.
There are some limitations of the study.

In some cases, especially regarding the size of the in- come, entrepreneurs could be either dishonest or avoid answering, which could lead to a shift in the overall results.

At the same time, even though the number of surveyed individuals is rather large, it might be insufficient to be fully representative, especially regarding small enterprise.
The fact that fieldwork was conducted in two out of ten provinces of Armenia and primarily in urban places is also a limitation; especially given that rural areas, which account for more than a third of Armenia’s population, were excluded from the study, since most of activities there are unregistered.

Another limitation is the low number of self-employed agricultural workers included.
Most farmers do not pay taxes unless they process food or hire people outside of their household, meaning so there were few in the State Revenue Committee’s taxpayers list.

The following definitions were used for the purposes of this research: Self-employed – a person, who generates income through his/her self-employment, or works for free in family enterprise for family benefits.
Micro enterprise – a legal form of enterprise with fewer than ten employees, including phys- ical entities registered as taxpayers.

Small enterprise – a legal form of enterprise, where the number of employees does not ex- ceed 50 people.

In spite of the differences in the implementation of the research in Georgia and Armenia, the study sheds light on how similar the self-employed and micro firms are.
Micro firms are for- mally registered as such, obliged to keep accounting records and are mostly active in service industries located in urban areas.

The self-employed tend to be unregistered, keep no records and are generally based in rural areas.
Yet, despite these important differences, in many oth- er dimensions related to entrepreneurship, micro-enterprises behave like the self-employed, suggesting that registration and accounting does not constitutes a trigger to full formaliza- 16 tion.
Independence tests10 reveal significant relationships between the degree of formality of self-employed and micro firms and their degree of motivation, the extent to which they plan fu- ture activities and the resources they rely on.

For self-employed and micro firms, formalization is strongly linked to the other dimensions of entrepreneurship in all the four rounds.

This is not the case at all for small firms.


The way self-employed people and micro business representatives structure their activities is related to all the other dimensions of entrepreneurship.

This further consolidates the argument that micro firms should be viewed in the same light as the informally self-employed, not as entrepreneurs.
Moreover, the dynamic picture provided by the four rounds of interviews in Georgia shows also that between 2013 and 2015, no self-employed and micro entrepreneurs grew nor formalized.

Reflecting on the way self-employed people and micro entrepreneurs organize their activity, one can conclude that the informal sector is not necessarily a building block for formal private sector development.

The results from the study in Armenia confirm this insight.
As mentioned, the State Revenue Committee’s taxpayers list was used to form the sampling frame, thereby excluding informal self-employed,11 most of whom work in agriculture.12 10 Kendall B and Spearman Rho 11 http://www.armstat.am/ file/doc/99499388.pdf 68 12 Ibid 69 17 The emergence of entrepreneurship in Georgia Introduction Starting from the early 2000s, the government of Georgia has implemented a number of signif- icant reforms directed towards reducing state intervention, simplifying business regulation and making Georgia an attractive place for business and investment.
It became the region’s best performer in the World Bank’s Doing Business indicator, ranking 6th in the world (WB, 2018).

Significant efforts were made towards lowering corruption: Georgia ranks amongst 19 Eastern European and Central Asian countries with low levels of corruption.

These achievements have not, however, been translated into the development of a strong network mid-size businesses.

The creation of a vibrant private sector and formal jobs still remain major challenges (OECD, 2016).
According to the Global Entrepreneurship Monitor (GEM) Georgia generally lags behind in “entrepreneurial intention”, defined by the percentage of population, 12.78 percent in Georgia, who are latent entrepreneurs and intend to start a business within three years (GEM Report, 2016).

Entrepreneurs in Georgia operate in both formal and informal economies.

Aside from officially registered private sector enterprises, there are slightly over one million self-employed individ- uals in Georgia.
In most cases, these people run de-facto micro enterprises and could be even referred to as potential entrepreneurs.

In 2014, the Government of Georgia established two new agencies: the Entrepreneurship Devel- opment Agency (Enterprise Georgia) and Georgia’s Innovation and Technology Agency (GITA).

Specific strategies dedicated to SME promotion and innovation development were drafted.
Since 2012, public spending on entrepreneurship, innovation, tourism and agricultural develop- 18 ment has also been on the rise.

In the period 2012-2017 over 1.2 billion Georgian Lari (GEL) was spent on what the entrepreneurship literature calls “direct support” measures for stimulating entrepreneurship and SME development.
These measures include offering support schemes among others soft loans, technical assistance, start-up grants.

A large share of Georgia’s employed population (57 percent) are self-employed.

Over the last decade, self-employment has remained high, even reaching 65 percent of total employed.

Self-employment is concentrated largely in older populations and the rural sector: as of 2016, 63 percent of self-employed people reside in rural areas and 56 percent are over 50.
This is due to the fact that self-employed people are mostly subsistence farmers or in the informal sector.

The methodology used to compile employment statistics states that self-employment includes own-account workers, as well as producers of goods for own final use, performing some work for at least one hour during the reference period for profit or family gain, in cash or in kind.
The fact that employment is a major issue in Georgia is proven by the public opinion polls that have not changed much over the course of the past years.

In response to the question: “do you con- sider yourself employed”, a high 63 percent of those surveyed answer NO (NDI, 2017).

Efforts have been made towards formalizing economic transactions and incorporating the self-employed population into the formal economy.
A major step taken in this direction was the introduction of special tax regimes for micro and small enterprises and an exemption for them from income taxes in 2012.

Another initiative was the introduction of a tax receipts lottery, designed to increase the issuance of receipts in business to consumer transactions.

In this way, transactions were more likely to become part of the official economy and collection of the value added tax was guaranteed.
The incentive for the consumer was that, at no extra cost, just by asking for a receipt one could win a prize.

The initiative lasted only for some months and was cancelled with the change in government in 2012 parliamentary elections.

General characteristics of the sampled population The majority of respondents in the Georgia survey had been engaged in the economic activity that they were pursuing for more than 5 years.
In fact, 40 percent of the self-employed peo- ple sampled have been working for themselves for more than 15 years and for the majority of 19 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P them, it is their first business.

For the majority of the micro enterprise representatives and the self-employed group, the activity that they were pursuing was their first and only business.

In 83 percent of cases, the respondents are the sole owners and managers of the firm.
They do not employ any additional workers, since they are debarred from doing so by their status as micro-enterprises.

Some of them use the help of the family members.

There is an equal distribution among male and female self-employed respondents, but the ma- jority of the micro enterprises were established by men.

The reason may lie in the type of busi- ness activity that they are engaged in.

Some professions are culturally distinguished as male or female (e.g.
the repair work, that the majority of micro enterprises are engaged in, is a male dominated occupation).

68 percent of micro firm representatives reside in larger cities, with population of 500,000 or more.

While self-employed people are mainly from smaller, generally rural areas, holders of the micro status are mainly urban residents, who have information about the preferable tax regime.
Since the occupation of micro firms is mainly service provision, they are more concentrated in urban areas with larger populations and larger pools of customers.

The main activity of self-employed people (71 percent of the self-employed respondents), on the other hand, is agriculture, mainly subsistence farming.

It is a proportion that reflects the structure of the Georgian economy.

Agriculture employs almost half of the population of Geor- gia (Geostat, 2016).
Following the structure of the Georgian economy, there is a difference in activities between the respondents from rural and urban areas.

The majority of self-employed respondents from rural areas are employed in agriculture, 90 percent of interviewed self-em- ployed in Tbilisi are active in services and trading.

The micro firms on the other hand, irrespec- tive of rural/urban residence, are mainly engaged in services (such as repair works) and small- scale manufacturing activities (figure 1).
Self-employed and micro-enterprise owners are therefore active in very different sectors and locations and yet, as we will see, they share striking characteristics when it comes to their level of formality, motivation, risk acceptance and performances.

Despite different levels of educa- tion, as the next paragraph shows, the business practices of the self-employed and micro-en- terprise owners are very similar: their activities can be better described as “survivalship” than “entrepreneurship”.
20 Activities of micro and self-employed 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Self-employed Micro Small AGRICULTURE MINING, MANUFACTURING, CONSTRUCTION TRADE, REPAIR OF VEHICLE SERVICE Figure 1: Activities of micro and self-employed (% of respondents) Education As figure 2 shows, self-employed, micro and small firm representatives have different levels of education.
A higher percentage of micro firm and, to a greater extent, small firms’ representa- tives hold a university degree.

The progression of educational level echoes the size of the en- terprise.

17 percent of self-employed have university degree, micro-enterprise representatives with the same level of education make up 33 percent of our sample, against 87 percent of small firms’ representatives.
Moreover, the majority (up to 90 percent) of self-employed people surveyed claim that they have learned what they are doing by practice on the job.

Formally acquired education is only re- motely useful for their economic activity.

On the other hand, there are proportionally more micro and small business representatives who recognize the usefulness of the knowledge acquired through formal education.
21 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P Level of Education 100 90 80 70 60 50 40 30 20 10 0 Self-employed Micro Small GENERAL EDUCATION PROFESSIONAL EDUCATION UNIVERSITY DEGREE Figure 2: Educational background (% of respondents) Age The age distribution in both groups is similar.

The mean age in both groups is 50 years, the youngest respondent in case of self-employed is 19 and the oldest 85, in case of micro, it is 29 and 82 respectively.
The age variable in this study is independent from activity.

Age is also independent from “formality variables” such as having a bank account, keeping accounting, and dealing with written contracts.

And while the majority of the self-employed group are “neces- sity driven entrepreneurs” at all ages, the oldest segment of this study clearly differentiates itself from the youngest when it comes to motivation, confidence, and attitude towards risks.

Age is an important variable in this case.


There is a higher percentage of younger self-em- ployed people who plan to sell more of their products and services during the next six months to two years.

Similarly, 57 percent of those below 39 are willing to take more financial risk for a chance to produce more.

Only 14 percent of those above 60 would take that risk.
Half of the self-employed below 39 feel confident enough to start another activity with the skills they have, against 32 percent of those above 60.

Similarly, fear of failure would prevent 39 percent of the young self-employed group from starting another activity, while it would prevent 60 percent of 22 the older group from doing so.
Fear of failure would prevent approximately 50 percent of both groups from starting new activities or proposing new products and services.

By and large, these results confirm that the “entrepreneurial drive” decreases when people grow older.

Escaping survival Formal and informal activities Formalization, it is argued here, goes beyond the registration process and also encompasses the “formalized” practices of doing business.

Almost all self-employed surveyed do not carry out formal accounting.
Slightly more than half of the micro firm representatives keep accounting re- cords.

The majority do so for the revenue service, to whom, in Georgia, micro firms must submit a simplified annual declaration.

We can assume that these records are quite primitive in nature and are not enough for analytical purposes, such as longer-term planning and management decisions.

More than half of those who keep records do so themselves, the rest use the help of an accountant.
When it comes to other “formality indicators”, such as terms of transaction, 90 percent of micro enterprise representatives state that they mainly operate verbally and do not use written terms of contract.

The response was similar in case of the self-employed.

More than half of the micro representatives believe that contracts represent a strong guarantee, yet, notwithstanding this trust, they use them infrequently.
The graph below illustrates similarities between the business practices of the micro and self-em- ployed groups.

Despite the key differences discussed above (in business activity, registration, rural/urban location) both groups can be considered equally “informal” when it comes to their business and managerial practices.

In other words, informality does not stop at registration, which on its own does not make micro enterprises run their businesses more formally than the self-em- ployed.
The Georgian cohort study contained four waves of interview and therefore allowed the observation of changes, or the lack thereof.

The “level of formalization” (crudely defined by the three informal variables in figure 3 below) did not generally change for self-employed people and micro-enterprises, whereas the cohort of small firms continued to become more formal between 2013 to 2015.
Moreover, the degree of formality of self-employed people and micro-enterprises is significantly associated with other variables, like motivation, the planning of future activities and 23 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P the resources they rely on.13 We did not find such associations for the small firm cohort, reinforcing the argument that micro firm share more characteristics with the informal self-employed.
Informal variables 120 100 80 60 40 20 0 Bank account Written contract Account records SELF-EMPLOYED MICRO SMALL Figure 3 Informal variables (% of answers to selected questions) The respondents appear to be well adjusted to the “informal” practices shown in the graph above and find ways accommodate their needs.
For example, trade credit from a supplier is a common way of gaining access to material resources without having a bank account or credit line, an approach taken by one third of the micro firm representatives.

Interestingly, the most frequent reason for not having credit or loans is that respondents felt they had no need for it.
Motivations For 60 percent of the self-employed, the activity that they pursue is “necessity driven”, since there are no other job opportunities, and the majority of them have been self-employed for more than five years.

Moreover, 51 percent would not even describe what they do as a “busi- ness”.

“Entrepreneurship by necessity” is also a prevalent answer among micro-enterprises.

Taking advantage of possible opportunities is a rare response.
Yet, unlike the self-employed, for micro-enterprise representatives, the need to run a business is mixed with the desire to make more money.
Furthermore, when asked if they would quit what they are doing for the same rev- enue as an employee, only 56 percent of self-employed said no, while 73 percent of micro busi- 13 Independence test (Kendall B and Spearman Rho) 24 ness representatives would rather maintain their current activity than earn the same income working for someone else.
It is difficult to interpret this attachment to “independence”, given that the independent business activity was usually initiated by lack of opportunity in the labour market.

Even if the stability offered by the status of an employee is greatly sought after, it is not to be found in the Georgian labour market, further reducing the attractiveness of the employee status.

Yet, the difference between self-employed and micro-firms is worth acknowledging.
In case of micro enterprises, one can assume that they have a sector specific knowledge, since up to 30 percent of the respondents from this group chose the business activity based on their previous work experience as an employee in the same sector.

This does not hold true for the self-employed, where the prevailing answer for choosing sector-specific activity is again “no other choice”.
These findings suggest that there are still some differences in the level of ambi- tion between the self-employed and micro-enterprise representatives.

Could we say that micro enterprise representatives value “independence” more than self-em- ployed people?

These findings illustrate the multi-dimensionality of “entrepreneurship” and the different forms that “entrepreneurial intentions” can take.

The decision to start a business is also dependent on an individual’s level of self-confidence.
The survey results show a gradua- tion of confidence level, starting from self-employed ending with small firms (figure 4).

Do you feel that you have the knowledge, skills and experience to start another business?

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Self-employed Micro Small YES NO DO NOT KNOW Figure 4: Do you feel that you have the knowledge, skills and experience required to start a business different from the one you are running now?
(% of respondents) 25 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P Accepting risks… Risk taking is at the core of entrepreneurial ventures.

Accepting the potential risks of a business venture for a future reward is the defining function of the entrepreneurial process.

Entrepre- neurs make a conscious decision to risk a resource (time, land, infrastructure, money) to create a return on that investment.
Risk acceptance in our study is gauged by two questions about the readiness of business representatives to invest financial resources in their business or in training.

An overwhelming majority of respondents in the micro and small enterprises refuse to take any financial risks to develop their businesses (figure 5).

This is true for decisions on spending money to gain access to new technology, equipment or other types of improvement that need additional financial resources.
The basis of these decisions is not only risk aversion, but a belief that additional financial investment will not lead to business improvements or translate into a higher income.

According to the respondents, external factors play a major role in the way their business performs: up to 40 percent in both groups believes that outcomes mostly depend upon factors external to their own actions.
Would you be ready to take more financial risks to develop your business 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Self-employed Micro Small YES NO DO NOT KNOW Figure 5: Would you be ready to take more financial risks to develop your business?

(% of respondents) 26 There is lack of readiness from the respondents to participate in training or courses.
When asked if they would be willing to participate to improve their business, more than half of the self-employed and micro-enterprise representatives answered negatively.

Small business rep- resentatives, on the other hand, seem to be more conscious of the value of training for their business ventures.

66 percent of them answered positively (see figure 6).
Would you be ready to undertake training to improve your business 70 60 50 40 30 20 10 0 Self-employed Micro Small YES NO DO NOT KNOW Figure 6: Readiness to undertake training to improve business performances (% of respondents) …For a reward?

An understanding of the value that the self-employed, micro and small enterprises generate is important.

It is the reward for having accepted the risks.


It is virtually impossible to examine in detail the “economic performance” of these cohorts of enterprises and measure, even vaguely, the value added produced.

Proxies must be found.

Access to markets, futures plans for business development, subjective assessment of livings standard and revenue stability can provide a valuable insight into the success of these businesses.
These variables shed light on the precarious nature of self-employed and micro-enterprises: most of them represent “survival-ship” rather than “entrepreneurship”, as defined previously.

It 27 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P is important to restate that self-employed people and micro-enterprises evolve in two different kinds of ecosystem.

The latter mostly sell services in urban areas, the former are essentially active in subsistence farming.
Yet the “performance” variables are strikingly similar for these two cohorts and, as with the other aspects of entrepreneurship mentioned before, bring the experiences of self-employed and micro-enterprise representatives closer.

For 30 percent of the self-employed, revenue is below 200 GEL, which is about USD 2.50 a day.

This level of revenue is too close to the poverty line to allow any kind of risk to be taken.
Yet, the “self-employed” label they receive from state authorities integrates them in the “entrepre- neurs” category.

This exposes the importance of semantics and definition and the confusing tendency of a purposefully broad definition of entrepreneurship.

Planning variables Self- employed Micro- businesses Small businesses Do you plan to expand your business?
No During the next three months During the next six months Within two years % 90 2 3 5 % 94 2 2 2 Do you plan to sell new products or services, or products or services of better quality?
No New products or services Products or services of better quality 95 4 1 96 2.5 1.5 % 76 6 7 11 82 10 8 Table 3: Planning and risk variables, self-employed and micro-entrepreneurs 28 “Performance” variables Self- employed Micro- businesses Small businesses Do you think that you earn enough income from your business?

To live comfortably To live very normally To live very simply To survive Do you think that your revenue is?
Very stable More or less stable Not stable at all % 0 12 31 57 1 27 72 % 0 15 31 55 1 36 63 % 1 51 29 1 4.5 63.5 32 Table 4: “Performance” variables, self-employed and micro-entrepreneurs Considering the above, it is not surprising that about 80 percent of self-employed and mi- cro-businesses are not able to save any money.

However, 25 percent express a readiness to reinvest in their business if there were any savings available.
When asked what they would do with an extra financial resource for their business, the most frequent answers were buying material resources for the business and buying real estate.

These answers mirror the saving and investment patterns of the Georgian population.

Investing in real estate and gaining reve- nue from rent is a popular choice.

This type of investment is considered to be less risky, hinting at the risk averse nature of the people surveyed.
More than 70 percent of the self-employed people surveyed describe their activity as stagnating or decreasing.

For almost 73 percent of them, business activity has not grown since its foundation.

The same holds true for 59 percent of micro and small business representatives.

Only 19 percent of the micro firms interviewed de- clared that their businesses were growing and they generally could not state by how much.
It is not then surprising that the majority of respondents are sceptical about growing their business or introducing new products or services in the coming months.

Their assessment of the future economic outlook is dim: altogether, 34 percent believe that the situation for SMEs in general will get worse in the near future, 20 percent think that it will not change and only 11 percent think that it will get better.

The rest don’t know.


Finally, a closer look at the market that the three cohorts can access is informative of their potential for growth (figure 7).

In comparison to self-employed and micro-entrepreneurs, a greater proportion of small enterprises sell in other 29 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P regions, but municipalities (a territorial unit bigger than a village and sometimes comprising of several villages) are clearly the main markets for all three cohorts.
This is an indication of the level of market development, where only larger enterprises might have a chance to expand do- mestically and internationally.

This type of structure, at the bottom of the enterprise pyramid, is to be acknowledged in economic policy documents, as it changes the political economy of free trade agreement, for example.
Do you sell most of your product in... 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Self-employed Micro Small VILLAGE MUNICIPALITY OTHER REGIONS Figure 7: Market outreach of self-employed, micro and small enterprises (% of respondents) 30 The emergence of entrepreneurship in Armenia Entrepreneurship has developed in post-Soviet Armenia over the past 30 years.
Before Pere- stroika, all private entrepreneurial activity was prohibited in the Soviet Union until, in late 1986, the law on “Individual labour activity” was adopted.

In 1987, a new law on “cooperatives” was introduced, which allowed certain level of private economic activity on an experimental basis.

It was further enhanced in 1988 to allow new forms of enterprise to have earn higher incomes legally (Duker, 1992).
It was not until August 1990 that the Soviet Government allowed individu- als to own small private businesses and to hire and fire workers (US Congress, Joint Economic Committee).

Since Armenia gained independence in late 1991 there have been no legal limi- tations on business activity.

Entrepreneurship still faces difficulties; a lack of initiative rather than the legal framework is the biggest issue here.
Private entrepreneurship in Armenia was born out of a Soviet parallel market built on private initiative, which was illegal for decades.

Its size was estimated to be around 12 percent of NMP14 in 1965, 18 percent in 1980 and 21 percent by 1989 (Kim and Shida, 2014).

After the collapse of the Soviet Union, the share of the informal economy increased, exceeding 60 percent of GDP in 1995-1996 (UNDP, 2001).
The growth of the informal economy was accompanied by the process of primitive capital accumulation and mo- nopolization of many of business markets in Armenia (Mikaelian, 2016).

Oligarchs, insiders and high-level public sector workers were projected to become the primary beneficiaries of the initial stage of the post-Soviet reforms, while new entrants to the market were expected to become winners at the next stage (WB, 2002).
However, the time needed for the reforms to take effect was underestimated and, in most cases, reforms were partial (Hellman, 1997).

The tran- sition was accompanied by a sharp decline in the economy as well as a change in its structure.
While the Soviet economy was characterized by a huge and not very efficient industrial sector with large volumes of capital investments and construction, in the post-Soviet period the ser- 31 14 NMP (Net Material Product) – core indicator of the Soviet system of National accounts.

It included mostly material production and excluded most of services.

In 1989, NMP consisted 71% of Armenia’s GDP S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P vices sector and trade grew.
A large number of people were left unemployed; in return the share of agriculture increased, since it is less dependent on foreign markets and less vulnerable to political shocks.

General characteristics of the sampled population The study of the demography of small businesses and self-employed people in Armenia re- veals several interesting features.
While the demographic structure of the self-employed and microbusiness representatives in Armenia is similar to the demographic structure of the so- cial groups relevant to them (the urban population of Yerevan and Lori), in the small business sector there are quite noticeable differences compared to the whole population.

The overall number of men and women included in both datasets combined was equal.

However, there were differences considering the size of the enterprises and region of their location.
Among small businesses, males were in the majority (about 57 percent of respondents), while among micro businesses and self-employed, there were more females (52 percent).

Males were more present in Yerevan, while females in Lori.
Notably, Lori province is characterized by rel- atively high levels of equality on the local self-governance level compared to other Armenian provinces.15 Apart from the local cultural peculiarities, there is another reason – mass labour migration of males left several villages completely without men and distorted the age and sex structure of the region’s population.16 Interestingly, the average age of women involved in small business is significantly lower than that of the self-employed and women involved in microbusiness.
According to our hypothesis, the age and sex structure of the self-employed and microbusiness representatives is quite close to the structure of general population in the respective regions.

For the same reason, the average age of local female politicians was higher than that of males: women needed to acquire more social capital to be able to get involved in politics.

Another reason is that female life expectancy in Armenia exceeds that of men by 6.5 years (Mikaelian, 2011).
However, the average age of women in the small busi- ness dataset appeared to be lower than the average age of men.

This fact requires additional explanations.

Most likely the explanation is technical: in some cases, the respondents were not the owners themselves.

The engagement of young, educated women in top managerial positions in the small firms is rather high, so that could explain the shift in the age and sex structure of the small business representatives.

32 15 http://www.armstat.


am/file/article/kanajq_ ev_txamardik.pdf pp.

156-158 16 http://www.bbc.com/ news/world-europe- 14386472 As could be expected, parenthood affected women’s business activity in small business, but had a very small impact on their activity in micro business and self-employment.
Partly this could be explained by the relatively young age of women involved in the small business, but the more likely explanation is that businesswomen still have to choose between family and career.

At the same time, there was no connection between the number of children and size of business among men; the numbers match the population average.
As mentioned, the number of children of women in- volved in micro business and the self-employed virtually matched the number of children among the corresponding population group, with the discrepancy being within the margin of error.

Education Most of the respondents in both groups (micro and small businesses) combined had received higher education – 56 percent; 23 percent had general education and 21 percent a professional one.
The number of people with university degree among small business owner is twice as high as among general population.17 The variation based on the size of business is high: 83 percent of surveyed small business representatives have university degree compared to just 50 percent of micro business representatives and the self-employed.

Males are more likely to have attained higher education than females: 61 percent versus 51 percent.
The data on the educational profile of micro business representatives shows that that the num- ber of people with a university degree was higher than amongst the general population.

For example, among the urban population of Armenia, 32 percent of those aged over 20 had a uni- versity degree, according to the 2011 population census.
Narrowing this group to 25-49, the most relevant for business, would increase their number to 35 percent.18 In Yerevan, where most of respondents came from, the numbers were higher still: 40 percent and 46 percent respective- ly.19 Drilling down to the employed population would likely further increase these percentages.
Since 50 percent of the self-employed and micro business representatives had a university degree, we can assume that the education level of micro business and the self-employed was very close to the indicators of the corresponding demographic groups.

Age Looking at age, a pronounced pattern is noticeable: younger entrepreneurs are more likely to have a higher education.
In the group from 18 to 24 years, 73 percent of entrepreneurs and 17 According to the 2011 Population Census, which was held in 2011, 21.7% of people aged 14 and older had higher education, 20.4% had technical education and 55.6% secondary and lower.

According to the CRRC Caucasus Barometer 2015, 27% of Armenian adults’ education level was higher than secondary, 28% – secondary technical and 44% had secondary or lower education.
http://caucasusbaro- meter.org/en/cb2015am /RESPEDU/ Most of the difference can be explained by the difference between age groups surveyed – aged 15 and older by the census, 18 and older – by the survey.

Another reason is fast growing of enrollment in higher education.

18 2011 Population Census national results.

Population (rural, urban) Distribution by Educational Attainment, Scientific Degree, Sex and Age.

http://www.armstat.am/ file/doc/ 99486173.pdf 19 2011 Population Census results in Yerevan.
Population (rural, urban) Distribution by Educational Attainment, Scientific Degree, Sex and Age (in Armenia).

http://www.armstat.am/ file/doc/99483658.pdf 33 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P self-employed respondents have higher education while in the group from 55 to 64 years only 41 percent of those surveyed have a higher education.

This also correlates with national data.


Although the share of those with a university degree among small and micro-business repre- sentatives (combined) is higher than the national average, it reveals the same trend: younger people tend to be better educated.

As self-employment is often associated with lower income and entrepreneurship by necessity, the high percentage of well-educated people in self-em- ployment reflect the slow integration of students in the labour market.
The high level of educa- tion among the over 65 year-old self-employed group shows the inadequacy of soviet education within the market economy.

Education profile of small and micro business 80 70 60 50 40 30 20 10 0 18-24 25-34 35-44 45-54 55-64 65+ SECONDARY TECHNICAL HIGHER Figure 8: Educational profile of small and micro business representatives, by age Escaping survival Formal and informal activities The informal sector is prominent in Armenia.
As in most developing economies, a significant share of the total number of those who are employed is concentrated in the informal sector.
The 34 National Statistical Service of Armenia estimates the share of informally employed to account for 49 percent out of the total number of employed (average in 2013-2015), mostly concentrated in agriculture.20 At the same time, one in five of those employed outside of agriculture is infor- mally employed.21 OECD survey on Public Policies, Migration and Development detected a higher share of informality at 29 percent (OECD, 2017).
Given that fieldwork in Armenia was conducted in early 2015, these results come close to the author’s estimate of the informal economy – 35 percent of the GDP in early 2015 and 28 percent of the GDP as of the end of August 2017.22 The informal economy generates such a significant share of GDP in Armenia in part be- cause it encompasses a significant proportion of the activity conducted by registered firms, including large enterprises attempting to evade paying taxes.
Since large enterprises may also not register all of their employees, the share of informally employed outside of agri- culture is a good benchmark by which to understand the scale of the informal economy.

Overall, the informal economy has been shrinking in size during the past decade, sinking below 30 percent threshold lately, and despite some fluctuation, this trend still continues in 2017-2018.

The survey included several questions that can be used to determine informality.
As they grow, enterprises tend to become more formal in their organization.

They keep account- ing records and sign written contracts.

They still might hide part of their turnover, but the general trend is towards the formalization of their activities.

Micro businesses generally also have accounting records, however most of their contracts are informal.

They do not use written contracts and tend to deal with their counterparts verbally.
One in three micro enterprises do not have a bank account, compared with only one in twenty small businesses.

Individual entrepreneurs, micro businesses and family enterprises in Armenia are granted the right to not file all of their tax receipts – in most cases they pay a fixed amount of money.

Thus, they can remain in a formal economic environment without complete accounting.
Yet their in- clination toward verbal contracts clearly indicates that they prefer not to register all of their turnover and activity.

35 20 National Statistical Service of Armenia.

2016.

Statistical Year- book of Armenia: 69. http://www.armstat.am/ file/doc/99499388.pdf 21 As per statistical convention, agricultural workers are usually excluded from such measures 22 Hrant Mikaelian, 2016.

“Shadow Economy in Armenia.” Yerevan: Caucasus Institute.
http://c-i.am/wp- content/uploads/ shadow_econ_ print_1.pdf S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P Country Small Business Micro business* Georgia Armenia Georgia Armenia Hold an accounting record Operate mainly with written terms and contract Hold bank account 99 77 82 88 75 94 47 9 30 69 29 66 Table 5: Informality variables among small and micro businesses and the self-employed, Georgia vs Armenia, percentage.

Survey data.
Survey data.

Note: * In Armenia, both micro business and self-employed are included, as they were counted in the same category, while in Georgia – only micro business.

“Self-employed” in Georgian case refers to mainly unregistered and agricultural activities and therefore were excluded from this comparison.

Only data on small business are fully comparable, while “micro businesses” category in Armenian case still includes some self-employed.
Motivations The motivation of the small business representatives is different to that of the micro-business representatives and self-employed, and clearly marked by the “by default” answer.

Family-cen- tred motivation is marginal.

One in four business representatives from both groups declared that their primary motivation was to be their own boss, with women citing this reason a little more frequently than men.
One in three micro business representatives mentioned this as a reason for running a business, while only 1 in 13 small business representatives mentioned this as the main reason of maintaining their activity.

Micro business representatives are engaged in en- trepreneurial activity in order to survive, while small business representatives are carrying out entrepreneurial activity to generate more income.
The behaviours might be similar, but these two different intentions relate differently to risk acceptance.

Motivations are also different de- pending on the level of income, as the graph below shows.
36 Selected motivations of small and micro businesses 50 40 30 20 10 0 No better choice for work To increase the income For own satisfaction and growth To have job security SMALL BUSINESS MICRO BUSINESS / HIGH INCOME MICRO BUSINESS / AVERAGE INCOME MICRO BUSINESS / LOW INCOME Figure 9: Selected motivations for activity of small and micro businesses representatives and the self- employed.
Note: Size of income refers to subjective assessment of income by the representatives of micro business and the self-employed As we can see in figure 9 above, even those having relatively high income among micro busi- ness representatives mention “no better choice for work” in at least 20 percent of cases, which is much higher than amongst small businesses.
The level of education also affected the answer – those with higher education are less likely to mention “no better choice for work” among micro enterprises.

Stronger motivation amongst the better educated could be the result of a better understanding of the activity they are engaged in.

As we have already seen income and motivation create a “two-way street”, showing a clear interconnection and interdependence.
Both groups of entrepreneurs were asked the question “would you stop doing what you do for the same fixed salary as an employee”.

Unsurprisingly, the status of an employee is less attractive as business size and income increase.

Only 11 percent of small businesspersons would take up with this offer.

Among the representatives of micro businesses, the frequency of responses was dependent on the level of income.
20 percent of those who consider their earnings enough to “live comfortably” or “normally” were ready to become a wage earner compared to 30 percent of those who earned “enough to live very simply” and 38 percent of those who earn enough to just “survive.” Given the significant share of the informal economy in Armenia’s GDP, it is rather difficult to col- lect data on business revenues.

In nation-wide surveys, people tend to understate their income.
37 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P According to the PovcalNet database, in 2014, people have reported their average monthly per cap- ita consumption expenditure at 39,500 Armenian Dram.23 The national accounts data for the final household consumption expenditure are much higher – around 114,000 Dram24 (2.88 times higher).
Although there still might be a methodological issue regarding the data, including the involuntary selection bias in poverty surveys, or the national accounts data inaccuracy, the difference – almost 3 times – suggests a significant level of underreporting of reported consumption expenditure.

This seemingly obvious interconnection between size, income and motivation comes as a re- minder that entrepreneurial activities require, by definition, the undertaking of a certain level of risk.
Readiness to be exposed to risk is therefore a crucial variable.

Accepting risks… The willingness to take risks to a large extent determines the ability of a business to produce a new product service or to master a new market.

For this reason, readiness to undertake risks is one of the key characteristics of any business, especially at the initial stage of its development.

As with the motivation variable discussed earlier, readiness to take on risks appear to depend on business size and level of income.
Risk readiness in Armenia varies depending on size of business.

Just 29 percent of micro business representatives said they were ready to take risks compared to 47 percent of small business representatives.

24 percent of micro enterprises have already taken risks during the past six months compared to 38 percent of small business repre- sentatives.
Those micro-business representatives who perceived their income to be relatively high tended to behave similarly to small business representatives with regards risk, while only one in five out of those who earn enough just to survive are prepared to take risks.

An unwillingness to undertake risk is caused by the high cost of failure for micro business representatives, especially those who do not have stable income or who earn enough just to survive.
More than two in three of them expressed fear of failure as a reason not to propose new products to the market.

Observation of micro business representatives’ and self-employed people’s motivation and readiness to take risks suggests that there is a threshold which di- vides entrepreneurship between income-generating business and self-employment as a sur- vival strategy.

Micro businesses operate as a business from self-employment, mainly used as a means of survival.
23 World Bank PovcalNet database http://iresearch.
worldbank.org/ PovcalNet/home.aspx 24 Calculation is based on the official data 38 Subjective assessment of income, relative Small Business Afraid of failure No fear DR/RA 44.1 50 5.9 Micro business High Medium 48.7 49.6 1.7 60.4 36.9 2.7 Low 67.8 29.6 2.6 Table 6: Fear of failure as factor preventing new entrepreneurial activity (by size of business and subjective assessment of revenue) In-depth consideration of demographic, educational and other personal characteristics of rep- resentatives of the micro business reveals other patterns: sex does not affect the willingness to take risks.
Education has a positive association with willingness to take risks: 33 percent of entrepreneurs with higher education are willing to take risks compared to of those who had professional (27 percent) or general education (24 percent).

36.2 percent of those who were not married at the time of interview took financial risks in the period of 6 months before the inter- view, while just 20.4 percent of those were married took risks in the corresponding period.
Age has even a greater impact on the willingness to take risks, as Figure 10 below shows.
Readiness to take risks to develop their business among micro entrepreneurs, by age 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 18-24 25-34 35-44 45-54 55-64 65+ READY TO TAKE RISKS NOT READY TO TAKE RISKS DO NOT KNOW / REFUSED Figure 10: Readiness to take risks to develop their business among micro entrepreneurs, by age % of respondents These findings might seem obvious and yet they shed light on a side of the “entrepreneurship” coin that is seldom considered closely: the ability and material condition (biological or psycholog- 39 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P ical even) that allows individual to take risks.
Even though entrepreneurship can be taught to and learned by everyone, the external conditions (endemic poverty) or internal conditions (personal income, age, “given” psychological attributes) at which people feel ready to accept the risk tied to entrepreneurial ventures are not necessarily met, even in “business-friendly” booming economies.

…For a reward?

As already mentioned, many of the people surveyed did not answer the question concerning their firm’s monthly revenue.
Non-response rate for this question was 26.4 percent among micro enterprise representatives and 40 percent among small business representatives.

The data on monthly revenue thus should be considered “less reliable” – it gives a very approximate under- standing of the real size of income of the people surveyed.

The vast majority of micro enterpris- es and the self-employed reported that they had a monthly income of less than 3 million AMD (6,250 USD).
It can be assumed that those who had higher incomes tended to refuse to disclose their incomes, thus the percentage excluding those who did not answer might misrepresent the general picture.

Statistical data can provide us with a general understanding of the situation in the field, however, most probably, these data will also underestimate the real size of incomes, due to their inability to count undeclared turnover and the income generated by it.
Subjective assessment of income is also an unreliable source for income estimation, however, it is still useful.

First, virtually all of those surveyed answered this question.

Second, even if it does not provide us with numerical values, it is a tool for understanding the self-assessment of the businessperson at the time of interview.

Would you say that the revenue you get from your current business activity is stable?
80 60 40 20 0 Yes, very stable More or less stable Not stable at all Do not know / refuse to answer MICRO SMALL Figure 11: Self-assessment of revenue stability (% of respondents) 40 From these data we can see that while the average small business representative earns enough to afford most of their needs, most of the micro-business representatives and the self-em ployed work just to escape poverty.
Less than one in four from the sample of micro-business representatives and the self-employed said that they earn enough either to live comfortably of normally.

Thus, the question arises: is micro-business in Armenia actually entrepreneurship – or just a matter of survival?

Further underlining this, 89 percent of those surveyed said they cannot save any money.

As expected, the lower the revenue (in this case, perceived), the lower the share of those who think that they are doing business.
As people start earning more they start to consider them- selves “in business”.

The survey results show that a majority of those who earn enough just to escape poverty do not conceive of their activity as “business.” Do you describe what you do as “business”?
Subjective assessment of income and activity To live comfortably To live normally To live very simply To survive YES NO DK / RA / IE Figure 12: Self-description of activity as “business”, by subjective assessment of income 0% 20% 40% 60% 80% 100% Another significant difference between the small and micro businesses is the stability of busi- ness activity and revenue, which is also crucial for self-identification as a businessperson.
Micro-enterprises which have more stable income tend to consider their activity as business.

However, most micro-enterprises (around 70 percent) described their revenue as highly un- stable, while only a third of small business representatives expressed this opinion about their revenue.

13 percent of small businesses in our sample had very stable income compared to just 4 percent of micro businesses.

The results are presented in the chart below.


41 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P Do you think that you earn enough from your business to...?
60 50 40 30 20 10 0 Live comfortably Live normally Live very simply Survive MICRO SMALL Do not know / refuse to answer Figure 13: Subjective assessment of living standard (% of respondents) Summary The survey was carried out during the regional crisis of the post-Soviet economies, when the volatility of exchange rates of regional currencies was noticeable.

This affected the business representatives’ assessment of their development prospects, and the effectiveness of state institutions.
April 2016 saw a serious escalation of violence in the Karabakh conflict zone, which killed about 100 people from the Armenian side alone.

However, in general, distrust and fear of risk are chronic problems of Armenian society.

Legal entrepreneurship, which was first permitted less than thirty years ago, faces numerous prejudices, including a predisposition towards rent extraction, distrust of the market economy and contradistinction of large, medium and small businesses.
Many micro enterprise representatives and self-employed people do not consider their activ- ities as a business, and this belief is highly correlated with lower incomes.

Amongst the least successful of them, economic activity is aimed at survival and therefore it is difficult to con- sider it an entrepreneurial activity.
As the business representatives and self-employed people 42 themselves do not perceive their activity as a business, they also do not believe it necessary or possible to exert additional efforts to expand their own business and they avoid risk.
This study did not touch upon agriculture in a meaningful way, since people working in this sector in Armenia generally consider themselves to be unemployed, rather than business man- agers.

The exclusion of the agricultural sector could be considered an omission, but at the same time, agriculture differs from industry, trade and services so much that it requires a separate study.
The regulatory environment in which small and micro-enterprises operate in Armenia is char- acterized by a relatively low level of corruption, but the perceived level of corruption is much higher.

In many respects, this is due to the fact that micro enterprises avoid contact with state institutions and often do not register their activity: seven out of ten micro-enterprise represent- atives and self-employed people surveyed conduct their business mainly verbally.
The habit of doing business verbally is in part a consequence of the Soviet experience, and in part an attempt to avoid tax regulations.

However, surveys, conducted in the last two decades in Armenia, show that tax evasion is less and less acceptable for the majority of the population.

43 Conclusion The findings of these two studies shed light on the very complex nature of “entrepreneurship”.
Some of its components – relationships with institutions, motivations, risk acceptance and per- formance – have been examined closely for different cohorts of enterprises and, in the case of Georgia, over time.

The findings are relevant: they indicate a clear division between “sur- vival-ship” and “entrepreneurship”.

Self-employed and micro-entrepreneurs are very similar to each other (even if some fundamental characteristics like, registration, sector of activity, geographical location are different).
Given the conclusions we have drawn about the survey respondents’ attitudes to their businesses, they show little potential to be a driving force of economic development.

In light of these findings, we ask whether the transition from “entre- preneurship by necessity” to “entrepreneurship by opportunity” (which has become accepted in economic development policy) is truly natural or automatic.
The policy implications are multiple and have consequences for the way the informal sector, entrepreneurship policy and social policy should be approached.

The informal sector The results of both studies give weight to the argument that entrepreneurship, being defined as the process of “discovery and exploitation of profitable opportunities” (Shane and Venkatara- man, 2000:17) starts in Georgia and Armenia, with small enterprises.
In Georgia, self-employed and micro-enterprise representatives did not grow their business and did not formalize their activity in the two years during which the study took place.

From this point of view, the informal sector does not seem to be a building block for formal private sector development.

One must 44 C O N C L U S I O N therefore conclude that the informal sector in Georgia is still unproductive and stagnant.
In- formal entities did not transition to formality, viewed broadly as the way enterprises structure their activities.

This confirms La Porta and Shleifer’s view of the informal sector as separated from the rest of the economy and add strengths to the dual view of the informal economy (2014).

Secondly, the studies show that Georgia and Armenia’s informal self-employed display the same characteristic with regard to informality as the registered micro-firms.
Registration and holding of accounting records do not provide satisfactory indicators for the boundaries of the informal economy.

The informal economy in Georgia encompasses the activities of registered micro enterprises.

Indeed, self-employed and micro enterprise representatives share many sim- ilarities in the way they are organized, in their motivation and their risk-taking behaviours.
These findings cast doubt on the value of the insistent focus on the tax and regulatory environment in linking institutions and the size of informal sectors (Jonson et al., 1998, Hibbs and Piculescu, 2005, Torgler et al., 2010).

Finally, another dimension of informal sector is the reach of official governance.

It can be argued that the existence of informal sector is not an issue of economic development exclusively, but is also related to the state building.
Economic policies that are designed in non-participatory ways and implemented in a top-down manner are likely to fail.

The inclusion of self-employed and micro businesses into the policy making process is important, if that policy aims at reducing the informal sector.
Entrepreneurship Policies – beyond business as usual This subtitle is inspired by UNCTAD’s Least Developed Countries Report (2018), which call for a more nuanced approach when it comes to the design and implementation of entrepreneurship policies in Least Developed Countries.

The studies presented here conducted in two “transition economies” reaches the same conclusion.

Entrepreneurship strategies should include a mix of horizontal and vertical policies.
This study provides detailed data on entrepreneurial processes and show that entrepreneurship is a complex process that involves both the motivation of entrepreneurs and an institutional environment.
45 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P Technical programmes focusing on the development of business plan and registration process will not achieve a lot, if not accompanied by “soft skills” development programs based on competencies that entrepreneurs must acquire to explore and exploit opportunities.

This in turn implies that entre- preneurship training programs and access to finance programmes alone are not enough.

The range of policy options are wide.


They correspond to the multi-dimensional nature of entrepreneurship and therefore are to be envisaged in a “whole-of-government” approach.

This holistic approach has the merit of acknowledging the complexity of the development of the entrepreneurial environment.

UNCTAD’s Entrepreneurship Policy Framework is a good example of the overarching policy frame- work necessary to build an efficient and consistent approach to entrepreneurship development.
A holistic approach and a strategic vision of policy making is important for shaping a successful en- trepreneurial policy.

Developing countries are characterized by lack of strategic planning and con- sistent approach in policy making, thus resulting in one-off initiatives that bring little or no impact.

However, the studies conducted in Georgia and Armenia also suggest that it is necessary to realize that not everybody can become an entrepreneur, no matter how entrepreneurial the environment is.
In other words, entrepreneurship policy must be carefully designed so as not to sustain artificially more self-employed and micro enterprises run by entrepreneurs by necessity.

As we have seen, the overwhelming majority of the surveyed “entrepreneurs” by necessity are in fact just managing to survive.

They do not think of their activity as “business”, do not plan to develop it, only access local markets and are not part of any association.
There are material conditions in which one can realisti- cally take risks, explore and exploit a perceived opportunity and these conditions do not seem to be met for most of the self-employed and micro enterprises in the Georgia and Armenia.

These material conditions are the ones designed and implemented by social policies still in place in Western liberal democracies, with varying degrees of individual protection, even if globalization and the “retreat of the state” has reduced that social safety net.
In comparison, former Soviet states underwent a transition which not only tore down planned economies, but also completely erased the safety net of social protection.

It is sometimes overlooked by economists that the construction of the market economy in former Soviet states corresponds with the destruction of the Soviet social policy.
Against this background, how can policy makers expect self-employed people and micro enterprises, who are just surviving with unstable revenue, to risk even more in the hope of developing an activity that they do not even consider to be a business?

The results of these studies indicate that the difference between entrepreneurship by necessity and entrepreneurship by opportunity is fundamental and that the first does not automatically 46 C O N C L U S I O N lead to the other.
Yet at the policy level, this automatic graduation is assumed.

It is also an as- sumption that opportunities will be seized by “entrepreneurs by necessity”, as long as they are granted access to finance and a “business-friendly” regulatory environment.

Therefore, policies are developed for the creation of opportunities, with the state as an enabler, for both categories of entrepreneurs.
Yet, if entrepreneurs by opportunity need the state as an enabler, entrepre- neurs by necessity need the state as a “risk moderator”.

Annex three shows a list of several influential “entrepreneurship policy” frameworks in use.

None of them integrates the necessity of reducing risks to entrepreneurs while building entrepreneurial ecosystems.

Emerging econo- mies are characterized by high levels of uncertainty and vulnerability towards the external con- ditions.
Entrepreneurs operate in an unpredictable political and economic environment, which is responsible for their short-term orientation and lack of long-term planning culture.

On the one hand, we can conclude that selective programmes and support offered to high- growth potential start-ups will be more effective if the goal is to change the structure of the economy.

This would call for more vertical (industrial/innovation and technology) policies.
On the other hand, it is hard to see how governments can expect a shift from survival to entrepre- neurship, without some level of protection for the most vulnerable, which would call for more horizontal social policies.

Policy frameworks usually insist on the coordination and the estab- lishment of synergies between different kind of government intervention.

Social policy is, how- ever, rarely mentioned as part of a strategy for private sector development.
Yet, social policy is the other side of the entrepreneurship coin.

Designing and implementing elements of social policy aligned with entrepreneurship strategies is all the more important as social inequality is rising globally (WIR, 2018).

Social inequality is more than income and revenue inequality.

It also comprises inequality toward risks.


The most vulnerable population of developing and least-de- veloped countries are vulnerable because they are over-exposed to climate change and envi- ronmental catastrophe, food shortage, input price volatility, etc… According to Rehm (2017) risk inequalities has been closely related to the public provision of insurances, which explains the rise of the welfare state.
Even if such provisions cannot be replicated everywhere, mechanisms for insuring the most vulnerable should still be established.

Entrepreneurial ventures are risky, by definition.

It therefore seems unrealistic to build policy strategies around the emergence of entrepreneurship among the most vulnerable population of a country without plans to expand insurance coverage to that same class of people.
47 Annex 1 Definition: self-employed, micro and small enterprises in Georgia Geostat’s household statistic recognize self-employment as the ownership of “personal en- terprise during the accounting period, in order to generate profit or family income (cash or in kind) or a person working for free in family enterprise/holding”.

Georgian tax codes recognize micro-businesses as those with an annual turnover below GEL 30,000 (approx.
18,000 USD) and small business as those with an annual turnover below GEL 100,000 (approx.

USD 60,000).

It has no definition of medium firms.

According to GeoStat, the national statistical office, small firms are those that employ fewer than 20 persons and have an annual turnover of less than GEL 500,000 (approx.

USD 300,000).
USD 300,000).

Definition: self-employed, micro and small enterprises in Armenia A self-employed person is someone who receives income from any activities not prohibited by law, employee, contractual income recipient, entrepreneur and natural person who is not a notary.

Micro firm are commercial organizations and individual entrepreneurs, the average number of employees does not exceed five people.
A small, commercial organization and individual entrepreneur, which does not exceed the average number of employees: Industry and other productive spheres – 50, Construction and power engineering sphere – 25, science and education – 25, transport, trade and services sector – 15 employees.

48 Annex 2 Planning and risk variables Self-employed in Georgia (%) Micro business in Georgia (%) Self-employed and micro business in Armenia (%) Do you plan to expand your business ?
No During the coming 3 months During the coming 6 months Within two years 90 2 3 5 94 2 2 2 70 14 6 4 Do you plan to sell new product or services, or products or services of better quality ?

No New product or services Products or services of better quality 95 4 1 96 2.5 1.5 56 20 23 Would you be ready to follow training courses if it could improve your business?

Yes No 35 55 45 55 Would you be ready to take more financial risks to develop your business ?
Yes No 19 69 19 81 50 45 30 70 49 Annex 3 Performance variables Self-employed in Georgia (%) Micro business in Georgia (%) Self-employed and micro business in Armenia (%) Do you think that you earn enough revenue from your business To live comfortably To live very simply To live normally To survive Do you think that your revenue is?

Very stable More or less stable Not stable at all 0 12 31 57 1 27 72 Where do you sell most of your products and services?
Village Municipality Other region in Georgia/Armenia Outside of Georgia/Armenia 39 44 6 0 0 15 31 55 1 36 63 4 93 2 0 2 20 30 46 3.6 25 70 2 92 4 1 50 Annex 4 Framework Organization Domains Babson College Babson Entrepreneurship Ecosystem Project (BEEP) Doing Business World Bank Entrepreneurial Ecosystem World Economic Forum The BEEP clusters the entrepreneurial ecosystem in to 6 different domain: Policy considers regulation and support programmes, Finance examines the financial instruments and services for entrepreneurs, societal norms are accounted by Culture, Support looks at the infrastructure, Human capital analyses education and skills and Markets identifies the presence of network and customers.
http://entrepreneurial-revolution.com/ The Doing Business Index provides a measure of regulation directly affecting business and allows the ranking of countries along the areas of starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting minority investors, paying taxes, trading across borders, enforcing contracts resolving insolvency.
http://www.doingbusiness.org/methodology WEF considers entrepreneurship as being supported by personal enablers (mentors, teachers), financial enablers (banks, microfinance), business enablers (incubators) and environmental enablers (infrastructure, regulations).
http://www3.weforum.org/docs/WEF_II_Entrepreneurial EcosystemsEarlyStageCompany_Report_2014.pdf 51 S U R V I V A L ( S H I P ) A N D E N T R E P R E N E U R S H I P Framework Organization Domains ANDE Entrepreneurship Ecosystem Diagnostic Toolkit OECD Entrepreneurship Measurement framework UNCTAD Entrepreneurship Policy Framework (EPF) GEDI Global Entrepreneurship and Development Index 52 ANDE identifies domains with direct influence (finance and support), partially direct influence (policy, markets, human capital, infrastructure, R&D) and indirect influence (culture) on entrepreneurship.
https://assets.aspeninstitute.org/content/uploads/files/ content/docs/pubs/FINAL%20Ecosystem%20Toolkit%20 Draft_print%20version.pdf The OECD framework provides indicators on regulation, market condition, access to finance, knowledge creation and diffusion, entrepreneurial capabilities, culture.

It considers these pillars seek as determinants of entrepreneurship.
http://www.oecd.org/std/business-stats/theentrepreneur- shipindicatorsprogrammeeipbackgroundinformation.htm The EPF takes into account the strategic components of formulating an entrepreneurship policy.
It is the fundament on which specific areas of interventions (pillars) can be developed, such as optimizing the regulatory environment, enhancing entrepreneurship education and skills development, facilitating access to technology exchange and innovation, improving access to finance, promoting awareness and networking.

http://unctad.org/en/Pages/DIAE/Entrepreneurship/Entrepre- neurship-Policy-Framework-and-Implementation-Guidance.
aspx The GEDI framework seeks to identify the different component of a “system of entrepreneurship”.

Opportunity perception, startup skills, networking, cultural support, opportunity startup, tech sector, quality of human resource, competition, new product, new technology, high growth, internationalization and risk capital are the 14 different elements considered.

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