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Cross-national variations in the scale of informal employment: An exploratory analysis of 41 less developed economies

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Purpose – The purpose of this paper is to evaluate critically the competing explanations for the cross-national variations in the scale of informal employment which variously correlate higher levels of informal employment with economic under-development (“modernization” theory), corruption, higher taxes and state interference (“neo-liberal” theory) and inadequate state intervention to protect workers from poverty (“structuralist” theory). Design/methodology/approach – To do this, data on the prevalence of informal employment collected by the International Labour Organisation using a common survey method across 41 less developed economies are analysed and compared using bivariate regressions with World Bank development indicators. Findings – Some 34.4 per cent of the non-agricultural workforce is in informal employment across these 41 countries, with the share in informal employment ranging from 83.6 per cent in India to 6.1 per cent in Serbia. Evaluating critically the competing explanations, a call is made for a synthesis of the modernisation and structuralist theoretical perspectives in a new “neo-modernisation” theory that tentatively associates higher levels of informal employment with economic under-development, smaller government and inadequate state intervention to protect workers from poverty. Research limitations/implications – Based on 41 cases, a multivariate regression analysis was not possible to determine how important each characteristic is to the final outcome whilst controlling for the other characteristics. Practical implications – This paper tentatively displays that wider economic and social policies, such as social protection, are significantly correlated with the level of informal employment. Originality/value – This is the first paper to use a direct survey to analyse and explain cross-national variations in informal employment in less developed economies.
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International Journal of Manpower
Cross-national variations in the scale of informal employment: An exploratory
analysis of 41 less developed economies
Colin C Williams
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Colin C Williams , (2015),"Cross-national variations in the scale of informal employment",
International Journal of Manpower, Vol. 36 Iss 2 pp. 118 - 135
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Cross-national variations in the
scale of informal employment
An exploratory analysis of 41 less
developed economies
Colin C. Williams
Management School, University of Sheffield, Sheffield, UK
Abstract
Purpose The purpose of this paper is to evaluate critically the competing explanations for the cross-
national variations in the scale of informal employment which variously correlate higher levels of
informal employment with economic under-development (modernizationtheory), corruption, higher
taxes and state interference (neo-liberaltheory) and inadequate state intervention to protect workers
from poverty (structuralisttheory).
Design/methodology/approach To do this, data on the prevalence of informal employment
collected by the International Labour Organisation using a common survey method across 41 less
developed economies are analysed and compared using bivariate regressions with World Bank
development indicators.
Findings Some 34.4 per cent of the non-agricultural workforce is in informal employment
across these 41 countries, with the share in informal employment ranging from 83.6 per cent in India to
6.1 per cent in Serbia. Evaluating critically the competing explanations, a call is made for a synthesis of
the modernisation and structuralist theoretical perspectives in a new neo-modernisationtheory that
tentatively associates higher levels of informal employment with economic under-development, smaller
government and inadequate state intervention to protect workers from poverty.
Research limitations/implications Based on 41 cases, a multivariate regression analysis was not
possible to determine how important each characteristic is to the final outcome whilst controlling for
the other characteristics.
Practical implications This paper tentatively displays that wider economic and social policies,
such as social protection, are significantly correlated with the level of informal employment.
Originality/value This is the first paper to use a direct survey to analyse and explain cross-national
variations in informal employment in less developed economies.
Keywords Working practices, Industrial relations, Informal economy, Conditions of employment,
Contingent workers, Disadvantaged groups
Paper type Research paper
Introduction
From the middle of the twentieth century, a view predominated that the informal
economy was purely a developing country phenomenon and represented a pre-modern
mode of production that was steadily disappearing with the advent of modernisation
and economic development (Geertz, 1963; Gilbert, 1998; Lewis, 1959). Since the turn of
the new millennium, however, there has been growing recognition that informal
employment prevails in developed as well as developing economies and is growing in
many global regions (Slavnic, 2010; Webb et al., 2009; Williams and Lansky, 2013).
Indeed, in many developing countries, the majority of non-agricultural workers are in
informal employment (ILO, 2013; Dibben and Williams, 2012). The result is that there is
a need for scholarship on human resources and labour economics to broaden its
scope beyond formal employment to explaining the scale of informal employment
(e.g. Darwish and Singh, 2013; Lopes and Teixeira, 2013). In this paper, the aim is to
International Journal of Manpower
Vol. 36 No. 2, 2015
pp. 118-135
© Emerald Group PublishingLimited
0143-7720
DOI 10.1108/IJM-01-2014-0021
Received 24 January 2014
Revised 22 May 2014
26 August 2014
6 September 2014
Accepted 8 September 2014
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0143-7720.htm
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contribute to the advancement of knowledge on this expanded view of human
resources and labour economics by evaluating critically the competing explanations
for the cross-national variations in the scale of informal employment across less
developed economies.
To do this, the first section will briefly review how informal employment has been
defined and measured along with how the cross-national variations in the scale of
informal employment have been variously explained to result from either economic
under-development (modernisation theory), corruption, high taxes and state interference
(neo-liberal theory) or inadequate state intervention to protect workers from poverty
(structuralist theory). Revealing that there has been little attempt to evaluate critically
these competing explanations in relation to the variations in the scale of informal
employment across less developed economies, this paper seeks to fill that gap. To do
so, the second section will introduce the database, namely the International Labour
Organisations (ILO) country surveys on informal employment which covers 41 less
developed economies, along with the development indicators here used to evaluate
critically the validity of the rival explanations for the cross-national variations in the
level of informal employment. The third section then reports the descriptive results on
the varying share of all non-agricultural jobs that are in informal employment across
these 41 less developed economies followed in the fourth section by a preliminary
analysis of the validity of the competing explanations for the varying prevalence of
informal employment across less developed economies (albeit only using bivariate
correlations rather than multivariate regression analysis due to only 41 cases being
available). The fifth and final section draws some conclusions by summarising the
findings about the share of non-agricultural jobs in informal employment and how
this varies cross-nationally, and tentatively calls for a synthesis of existing theories in
the form of a new neo-modernisationtheory.
Informal employment: definitions, measurements and explanations
Defining informal employment
This paper adheres to the widely agreed definition of informal employment developed
by the International Conference of Labour Statisticians (ICLS) (Hussmanns, 2005; ILO,
2011, 2012). Informality can be defined using either enterprises or jobs as the unit of
observation. As Table I displays, if enterprises are the unit used, then the result is to
define informality in terms of employment in the informal sector(A+B) whilst if jobs
are used, informality is defined in terms of informal employment(A+C).
Here, those in informal employment (A+C), akin to the 17th ICLS in 2003, are defined
as those persons whose main jobs lack basic social or legal protections or employment
benefits and may be found in the formal sector, informal sector or households. Persons
in informal employment include: (a) own-account workers self-employed in their own
informal sector enterprises; (b) employers self-employed in their own informal sector
enterprises; (c) contributing family workers; (d) members of informal producers
Economic units Informal jobs Formal jobs
Informal economic units A B
Formal economic units C D
Source: ILO (2012)
Table I.
The anatomy of
informality
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cooperatives; (e) employees with informal jobs in formal sector enterprises, informal sector
enterprises, or as paid domestic workers employed by households; (f) own-account
workers engaged in self-provisioning, if considered employed in the sense that the
production makes an important contribution to household consumption (ILO, 2012, 2013).
With regard to (e) above, an employee is defined as in informally employment if the
employment relationship is, in law or in practice, not subject to national labour legislation,
income taxation, social protection or entitlement to certain employment benefits
(e.g. notice of dismissal, severance pay, paid annual or sick leave) (ILO, 2012, 2013).
This definition thus enables informal employment in informal sector enterprises
(A) to be distinguished from formal jobs in informal sector enterprises (B) as well as
informal employment in formal sector enterprises (C). Informal enterprises are defined
by the 15th ICLS in 1993 as private unincorporated enterprises which are unregistered
or small in terms of the number of employed persons. An unincorporated enterprise is a
production unit that is not constituted as a separate legal entity independently of the
individual (or group of individuals) who owns it, and for which no complete set of
accounts is kept. An enterprise is unregistered, meanwhile, if it is not registered under
specific forms of national legislation (e.g. factoriesor commercial acts, tax or social
security laws, professional groupsregulatory acts). Holding a trade license or business
permit under local regulations does not qualify as registration. An enterprise is small,
meanwhile, if its size in terms of employment levels is below a specific threshold
(e.g. five employees) determined according to national circumstances (Hussmanns,
2005; ILO, 2011, 2012).
Measuring the level of informal employment
In a developing world context, it is often difficult to compare cross-national variations
in the level of formal employment due to the lack of national-level formal labour market
data. Analysing cross-national variations in the level of informal employment, which is
by definition hidden from view, is therefore even more problematic. To overcome this,
two options are available. Estimates of the cross-national variations in the level of
informal employment can be produced using direct surveys of the level of informal
employment and/or indirect measurement methods that use proxy indicators of informal
employment or seek statistical traces of informal employment in macroeconomic data
collected for other purposes (OECD, 2002, 2012; Ram and Williams, 2008).
These indirect methods for measuring cross-national variations can be divided into
four broad techniques: those using individual non-monetary proxy indicators such as the
number of very small enterprises (ILO, 2002) or electricity demand (e.g. Friedman et al.,
2000; Lacko, 1999); those employing individual monetary proxy indicators such as
the level of cash deposits (Gutmann, 1977) or money transactions (Feige, 2012; Frey
and Weck, 1983), income/expenditure discrepancies (Paglin, 1994) and those using
multiple indirect proxy indicators (e.g. Schneider, 2013; Schneider and
Williams, 2013). The problem with all of these methods in a developing world
context is that the data are often not available on these proxy indicators.
Direct surveys, meanwhile, can either take the form of quantitative, qualitative or mixed
methods surveys. On the whole, the use of direct surveys to evaluate cross-national
variations has taken the form of quantitative surveys. Examples include a three-country
comparison of European nations (Pedersen, 2003) and a 2007 Eurobarometer survey of
informal employment in the 27 member states of the European Union (Williams, 2013). Until
now, direct survey methods have not been used to evaluate and explain cross-national
variations in the level of informal employment in the developing world, despite the ready
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availability of a data set of 41 countries where the ILO has conducted surveys of the scale of
informal employment (ILO, 2011, 2012). Here, therefore, it is this data set which will be
analysed to calculate the cross-national variations in the level of informal employment.
Before doing so, however, it is necessary to outline how the cross-national variations
in the scale of informal employment have been so far explained since the intention in
this paper is to evaluate critically these competing explanations in less developed
economies.
Explaining cross-national variations in the level of informal employment
Until now, three competing perspectives have sought to explain the cross-national
variations in the level of informal employment. These view higher levels of informal
employment to be a result of either economic under-development (modernisation
explanation), high taxes, public sector corruption and state interference in the free
market (neo-liberal explanation) or inadequate state intervention to protect workers
from poverty (structuralist perspective). Each is here considered in turn.
Modernisation explanation. During the twentieth century, informal employment was
widely represented as a legacy of a pre-modern mode of production and viewed as
fading from view as the modern formal economy became ever more hegemonic.
Informal employment was therefore commonly portrayed as a residue from an earlier
mode of production and disappearing. Viewed in this manner, those developing world
countries in which informal employment is extensive are seen as portraying the
characteristics of under-developmentand even backwardnesswhilst extensive
formal sectors are viewed as representing advancementand development(Geertz,
1963; Gilbert, 1998; Lewis, 1959). The result is that informal employment is represented
as an expression of under-development (in the normative sense of a lack of progress)
that will disappear with economic advancement and modernisation. Applying this to
explaining the cross-national variations in the extent of informal employment, it can be
suggested that in less developed economies, there will be a higher prevalence of
informal employment. To explore its validity, the following hypothesis can be tested:
H1. Informal employment will be more prevalent in less developed economies.
Neo-liberal explanation. Over the past few decades, nevertheless, not least due to the
persistence and even expansion of informal employment globally, a range of competing
explanations have emerged. For neo-liberal commentators, high levels of informal
employment are a product of high taxes, a corrupt public sector and too much state
interference in the workings of the free market. Informal employment is therefore a
rational economic decision which people and businesses pursue in order to voluntarily
exit the formal economy so as to avoid the costs, time and effort associated with formal
employment (e.g. Becker, 2004; De Soto, 1989, 2001; London and Hart, 2004; Nwabuzor,
2005; Sauvy, 1984). As Becker (2004, p. 10) asserts, informal work arrangements are a
rational response by micro-entrepreneurs to over-regulation by government
bureaucracies. For such neo-liberal commentators, therefore, informal employment
is a rational economic strategy pursued by those stifled by high taxes and state-
imposed institutional constraints (De Soto, 1989, 2001; Perry and Maloney, 2007). The
ongoing prevalence and even growth of informal employment is consequently a
product of high taxes, public sector corruption, over-regulation and state interference in
the free market and the resultant remedy is seen to be to pursue tax reductions, reduce
corruption, deregulation and minimal state intervention. From this neo-liberal perspective,
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therefore, informal employment will be higher in countries with higher taxes, public sector
corruption and state interference in the workings of the free market. To explore the
validity of this neo-liberal explanation, the following hypothesis can be tested:
H2. Informal employment will be more prevalent in less developed countries with
higher tax rates, greater public sector corruption and higher levels of state
interference in the free market.
Structuralist explanation. For structuralist scholars in contrast, the widespread
existence and even expansion of informal employment in economies is represented as a
direct by-product of the emergence of a de-regulated open world economy (Castells and
Portes, 1989; Gallin, 2001; Hudson, 2005; Slavnic, 2010). The ongoing functional
integration of a unified global economic system is resulting in subcontracting and
outsourcing becoming a key vehicle for integrating informal employment into
contemporary capitalism, resulting in further downward pressure on wages and the
erosion of incomes and welfare provision, and the growth of yet more informal
employment. As Fernandez-Kelly (2006, p. 18) states, the informal economy is far from
a vestige of earlier stages in economic development. Instead, informality is part and
parcel of the processes of modernization. Indeed, for Davis (2006, p. 186), such
primitive forms of exploitation [] have been given new life by postmodern
globalization.
From this structuralist perspective, in consequence, informal employment is a
largely unregulated realm composed of low-paid and insecure work carried out under
sweatshop-likeconditions as a survival tactic by marginalised populations excluded
from employment in the formal economy (Castells and Portes, 1989; Davis, 2006; Gallin,
2001). Informal employment is therefore necessity-driven, and participants forced into
this realm by their inability to find formal employment (e.g. Castells and Portes, 1989;
Gallin, 2001; ILO, 2002). In the new post-Fordist and post-socialist era, those engaged in
informal employment are unwilling pawns cast into this sphere as a survival
mechanism. To evaluate the validity of this structuralist explanation, the following
hypothesis can be tested:
H3. Informal employment will be more prevalent in those less developed countries
with lower levels of state intervention to protect workers from poverty.
Evaluations of the competing explanations. Most commentators explaining the cross-
national variations in the scale of informal employment have done so by adopting one
of these logics. For example, the ILO (2012) adopt the modernisation perspective that
the preponderance of informal employment decreases as GDP per capita grows, whilst
Schneider and Williams (2013) has largely sought to display the validity of various
tenets of the neo-liberal perspective such as the need to reduce taxes and the level of
public sector corruption so as to decrease the scale of informal employment.
Few scholars have evaluated critically the competing theories. When they have done
so, however, the finding has been that no one perspective is universally valid. It has
been contended, for example, that structuralist explanations are more valid with regard
to informal waged work and the neo-liberal perspective more valid when explaining
informal self-employment (Perry and Maloney, 2007; Williams et al., 2013), or that the
structuralist explanation is valid when explaining informal employment in relatively
deprived populations but the neo-liberal perspective when explaining informality in
relatively affluent populations (Evans et al., 2006; Pfau-Effinger, 2009; Williams, 2004;
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Williams and Windebank, 2006). Studies have similarly argued that the structuralist
explanation is more valid when explaining womens necessity-driven informal employment
and the neo-liberal explanation to the voluntary exit rationales that characterise mens
engagement (Franck, 2012; Grant, 2013; Williams, 2011). The only study that has evaluated
critically the competing theories as explanations for cross-national variations in the scale
of informal employment has focused upon the member states of the European Union and
finds evidence to support the tenets of both the modernisation and structuralist
perspectives but little evidence to support most of the tenets of the neo-liberal perspective
(Williams, 2013).
Until now, however, no studies so far as is known have evaluated critically the
validity of these perspectives when explaining the cross-national variations in the level
of informal employment across less developed economies. It is to filling this gap that
attention now turns.
Methodology: examining cross-national variations in the level of informal
employment
To estimate the variations in the level of informal employment across less developed
economies, the ILO surveys of informal employment conducted in 41 countries are here
analysed. The main advantage of using these surveys is that they use the same
common broad definition of informal employment as discussed above and also employ
a very similar survey methodology when collecting data on the extent of informal
employment using either an ILO Department of Statistics questionnaire sent to
countries or information from national labour force or informal sector surveys (for
further details, see ILO, 2012).
Although the ILO (2012) provides brief statistical portraits of the size of informal
employment, this paper will focus for the first time on how and why this varies
cross-nationally and across global regions. It is important to state at the outset,
nevertheless, that the findings reported here relate solely to non-agricultural
employment. The ILO survey does not analyse employment in agriculture, hunting,
forestry and fishing. If it was included, the level of informal employment would be
doubtless much higher. Analysing the quality of the data collected using this survey
method so far as the prevalence of informal employment is concerned, it is unknown
whether the current data set provides an accurate description of the level of informal
employment. This is because there is no benchmark available for evaluating this. It is
sometimes stated in developed economies that such direct surveys under-estimate the
scale of informal employment relative to indirect measurement methods (Eurofound,
2013; OECD, 2012). This is similarly the case in developing countries (see Bardasi et al.,
2010), particularly in relation to womens informal work (Franck and Olsson, 2014;
Langsten and Salen, 2008). If anything, therefore, the prevalence of informal employment
might be higher than suggested by this survey. Moreover, people in different countries
may well have differing tendencies to report or not report their informal work due to
variations in whether this is deemed acceptable in terms of national norms, values and
codes of conduct. Although this possibility cannot be ruled out, by adopting the same
definition of informal employment and the same survey method and interview schedule
for collecting the data, the survey reported here has sought to minimise the effects of
such tendencies on the findings. As such, although some caution must be exercised with
regard to this data set due to such caveats, the country-level data reported in this paper
are here deemed sufficiently comparable between countries to allow comparative
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analysis. It is also important to note that throughout this paper, employmentrefers to
what participants self-report as their main job if the person has more than one job.
To analyse the wider economic and social characteristics that each theoretical
perspective associates with higher levels of informal employment, meanwhile,
indicators have been used from the World Bank database of development indicators for
the year in which the survey of informal employment was conducted in each country
(World Bank, 2013). The only indicators taken from a non-official sources are on
perceptions of public sector corruption, which has been taken from Transparency
Internationals Corruption Perceptions Index (CPI) for the relevant year in each country
(Transparency International, 2013) and the Social Progress Index as a measure of
development(Social Progress Imperative, 2014).
To evaluate the validity of the modernisation explanation that the level of development
relates to the level of informality, the conventional indicator used in previous studies is
GNP per capita (ILO, 2012; Yamada, 1996), although there is widespread criticism of this
indicator as a proxy measure of the developmentof an economy or the standard of living
of its citizens (Kuznets, 1962). Here, therefore, both this and additional measurements of the
level of developmentare used, namely:
GNP per capita.
Household final consumption expenditure per capita (i.e. private consumption per
capita). This covers the market value of all goods and services, including durable
products (e.g. cars, washing machines and home computers), purchased by
households (World Bank, 2013).
Human Development Index (HDI) this is a composite of life expectancy,
education and income indices intended to shift the focus of development from
national income accounting to people-centred policies (United Nations
Development Programme, 2014).
Social Progress Index (SPI) this measures the extent to which countries provide
for the social and environmental needs of their citizens. In total, 52 indicators in
the areas of basic human needs, foundations of wellbeing and opportunity show
the relative performance of nations (Social Progress Imperative, 2014).
To evaluate the validity of the neo-liberal explanation that higher levels of informal
employment are the product of high taxes, corruption and state interference in the free
market meanwhile, indicators previously used by Eurofound (2013) and the European
Commission (2013) when assessing the assumptions of the neo-liberal perspective are
used, namely the World Bank (2013) country-level indicators on:
Taxes on goods and services as a percentage of revenue, which includes general
sales and turnover or value added taxes, selective excises on goods, selective
taxes on services, taxes on the use of goods or property, taxes on extraction and
production of minerals, and profits of fiscal monopolies.
Taxes on revenue (excluding grants) as a percentage of GDP. Revenue is cash
receipts from taxes, social contributions and other revenues such as fines, fees,
rent and income from property or sales. Grants are also considered as revenue
but are excluded here.
Tax revenue as a percentage of GDP. Tax revenue refers to compulsory transfers
to the central government for public purposes. Certain compulsory transfers such
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as fines, penalties and most social security contributions are excluded. Refunds and
corrections of erroneously collected tax revenue are treated as negative revenue.
Meanwhile, the corruption assertion of the neo-liberal perspective is assessed using:
Transparency Internationals CPI (Transparency International, 2013). This is a
composite index of perceptions of public sector corruption that draws on 14
expert opinion surveys and scores nations on a 0-10 scale, with zero indicating
high levels and 10 low levels of perceived public sector corruption.
The percentage of firms stating that they are expected to give gifts in meetings
with tax officials.
The percentage of firms giving informal payments to public officials.
To evaluate both the neo-liberal explanation that state interference results in greater
levels of informal employment, as well as the structuralist explanation that it is a
product of inadequate levels of state intervention, the indicator used is that previously
employed in reports by the European Commission (2013) and Eurofound (2013) when
assessing the assumptions of the neo-liberal and structuralist perspectives, namely:
Social contributions as a percentage of revenue. Social contributions include
social security contributions by employees, employers and self-employed
individuals, and other contributions whose source cannot be determined. They
also include actual or imputed contributions to social insurance schemes
operated by governments.
State revenue (excluding grants) as a percentage of GDP.
Expense of government as a percentage of GDP, which is a measure of the size
of government and therefore a loose proxy of the degree of intervention.
The expense of government is the level of cash payments for the operating
activities of the government in providing goods and services. It includes
compensation of employees (such as wages and salaries), interest and subsidies,
grants, social benefits, and other expenses such as rent and dividends (World
Bank, 2013).
Meanwhile, and to analyse the structuralist thesis that informal employment is
associated with the level of poverty, two indicators are analysed:
The percentage of the population living below the national poverty line (ILO,
2012).
The size of the poverty gap at $1.25 per day in personal purchasing power
standards. The poverty gap is here taken as the mean shortfall from the poverty
line (counting the non-poor as having zero shortfall), expressed as a percentage of
the poverty line. This measure reflects the depth of poverty as well as its
incidence (World Bank, 2013).
To analyse the relationship between cross-national variations in the level of informal
employment and these economic and social characteristics that each perspective
contends are associated, and given the small sample size of just 41 countries for which
data are available and lack of necessary controls to include in a multivariate regression
analysis, it is only possible here to conduct bivariate regression analyses. Here,
Spearmans rank correlation coefficient (r
s
) is used due to the non-parametric nature of
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the data. As will become apparent, however, despite the limitation of only using bivariate
regression analysis, meaningful findings are produced with regard to the validity of the
different theories.
Below, therefore, first the variable level of informal employment across the 41 less
developed economies for which data are available will be reported and second,
a preliminary analysis will be carried out of the wider economic and social conditions
that each theory asserts are correlated with higher levels of informal employment in
order to evaluate the competing theories.
Findings: cross-national variations in the level of informal employment
Examining the findings for the 41 countries for which data are available on the level of
informal employment, Table II reveals that the simple unweighted average is that the
majority (53.9 per cent) of non-agricultural workers in these less developed economies
are in informal employment as their main job. However, and given the variable size of
the workforce across countries, a weighted average figure is here employed that takes
into account the variable size of the workforce in each country. The resultant finding is
that across all 41 countries, just over one-third (34.4 per cent) of non-agricultural
workers are in informal employment as their main job. Informal employment, therefore,
is not some minor leftover of little importance. As the main occupation of over one in
three of the non-agricultural workforce, this is a sizeable realm that employs a
significant proportion of the labour force in these less developed economies.
However, these figures for the 41 countries hide some marked variations across
global regions. To analyse this, the 41 countries for which data are available are
divided, using the World Bank (2013) classification into six regions, namely East Asia
and the Pacific (China, Indonesia, Philippines, Thailand and Vietnam), Europe and
Central Asia (Armenia, FYR Macedonia, Moldova, Serbia and Turkey), Latin America
and the Caribbean (Argentina, Bolivia, Brazil, Colombia, Costa Rica, Dominican
Republic, Ecuador, El Salvador, Honduras, Mexico, Nicaragua, Panama, Paraguay,
Peru, Uruguay and Venezuela), the Middle East and North Africa (Egypt and the
West Bank and Gaza), South Asia (India, Pakistan and Sri Lanka) and sub-Saharan
Africa (Lesotho, Liberia, Madagascar, Mali, Namibia, South Africa, Tanzania, Uganda,
Zambia and Zimbabwe).
Analysing the variations in informal employment across less developed economies in
these global regions, the finding is that the weighted proportion of the non-agricultural
workforce in informal employment as their main job ranges from one in four (26.8 per cent)
Global region
% of non-agricultural
workforce in informal
employment, unweighted
% of non-agricultural
workforce in informal
employment, weighted
Number of
countries
East Asia and Pacific 44.1 44.0 5
Europe and Central Asia 17.0 26.8 5
Latin America and Caribbean 57.0 50.5 16
Middle East and North Africa 54.9 51.5 2
South Asia 74.7 82.6 3
Sub-Saharan Africa 59.4 53.2 10
All global regions 53.9 34.4 41
Source: Derived from ILO (2012)
Table II.
Informal
employment as
percentage of total
non-agricultural
employment
(unweighted and
weighted) in less
developed economies:
by global region
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in Europe and Central Asia to over four out of five (82.6 per cent) in South Asia. The share
of the working population in informal employment as their main job, therefore, is not
evenly distributed across the globe.
The variations between countries within each of these global regions, nevertheless,
are as marked as the variations between global regions. As Table III displays, the
proportion of the non-agricultural workforce that is in informal employment ranges
Country Year
% of jobs in
informal
employment
% of informal
employment which
is waged work
Global region (World Bank
classification)
India 2009/2010 83.6 52.8 South Asia
Mali 2004 81.8 21.9 Sub-Saharan Africa
Pakistan 2009/2010 78.4 47.0 South Asia
Tanzania 2005/2006 76.2 26.8 Sub-Saharan Africa
Bolivia 2006 75.1 46.4 Latin America and Caribbean
Honduras 2009 73.9 39.8 Latin America and Caribbean
Madagascar 2005 73.6 42.3 Sub-Saharan Africa
Indonesia 2009 72.5 50.8 East Asia and Pacific
Paraguay 2009 70.7 59.8 Latin America & Caribbean
Philippines 2008 70.1 52.8 East Asia and Pacific
Peru 2009 69.9 41.0 Latin America and Caribbean
Zambia 2008 69.5 35.3 Sub-Saharan Africa
Uganda 2010 69.4 34.8 Sub-Saharan Africa
Vietnam 2009 68.2 40.2 East Asia and Pacific
El Salvador 2009 66.4 42.4 Latin America and Caribbean
Nicaragua 2009 65.7 41.6 Latin America and Caribbean
Sri Lanka 2009 62.1 50.3 South Asia
Ecuador 2009 60.9 52.5 Latin America and Caribbean
Liberia 2010 60.0 17.5 Sub-Saharan Africa
Colombia 2010 59.6 29.9 Latin America and Caribbean
West Bank and Gaza 2010 58.5 76.5 Middle East and North Africa
Mexico 2009 53.7 55.6 Latin America and Caribbean
Zimbabwe 2004 51.6 na Sub-Saharan Africa
Egypt 2009 51.2 na Middle East and North Africa
Argentina 2009 49.7 54.3 Latin America and Caribbean
Dominican rep 2009 48.5 42.1 Latin America and Caribbean
Venezuela 2009 47.5 34.3 Latin America and Caribbean
Namibia 2008 43.9 73.9 Sub-Saharan Africa
Panama 2009 43.8 39.7 Latin America and Caribbean
Costa Rica 2009 43.8 43.9 Latin America and Caribbean
Thailand 2010 42.3 na East Asia and Pacific
Brazil 2009 42.2 53.7 Latin America and Caribbean
Uruguay 2009 39.8 34.3 Latin America and Caribbean
Lesotho 2008 34.9 89.9 Sub-Saharan Africa
South Africa 2010 32.7 64.5 Sub-Saharan Africa
China 2010 32.6 40.2 East Asia and Pacific
Turkey 2009 30.6 na Europe and Central Asia
Armenia 2009 19.8 66.9 Europe and Central Asia
Moldova Rep 2009 15.9 55.7 Europe and Central Asia
Macedonia 2010 12.6 60.0 Europe and Central Asia
Serbia 2010 6.1 53.4 Europe and Central Asia
Source: Derived from ILO (2012)
Table III.
Informal
employment as share
of non-agricultural
employment, 41 less
developed countries
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from 83.6 per cent of the non-agricultural workforce in India to 6.1 per cent in Serbia.
Indeed, in 24 (59 per cent) of the 41 nations, over half of the non-agricultural workforce
is in informal employment. Informal employment, in consequence, is not some small
segment of the economy of limited importance.
Table III also displays the proportion of informal employment in each country that
is waged employment as opposed to own-account work conducted on a self-employed
basis. This reveals importantly that that not all informal employment is waged work.
Again, there are some marked variations across countries in the proportion of informal
employment that is waged work, ranging from 89.9 per cent in Lesotho to 17.5 per cent in
Liberia. On the whole, however, there is a statistically significant correlation between the
proportion of the non-agricultural workforce which is in informal employment and
the proportion of informal employment that is waged work. As Figure 1 reveals, the more
informalised the economy, the more likely is informal employment to be waged work.
Indeed, using Spearmans rank correlation coefficient (r
s
) due to the non-parametric
nature of the data, the finding is that the greater the degree of informalisation of a
country measured in terms of the proportion of the non-agricultural workforce in
informal employment, the greater is the proportion of the informal workforce in waged
employment, and this is statistically significant within a 99 per cent confidence interval
(r
s
¼0.413**).
How, therefore, can these cross-national variations in the level of informalisation
across less developed economies be explained? Is there an association between the level
of informal employment and the various economic and social conditions in countries
identified by the various theories earlier discussed? It is to this attention now turns.
Analysis: evaluating the competing theories
To explain the above cross-national variations in the level of informal employment, a
preliminary analysis of the validity of each of the three theoretical perspectives is here
conducted. First, and to evaluate the validity of the modernisation perspective that the
share of informal employment is lower in developedwealthier economies and greater
in less developedeconomies, the correlation between such employment and GNP per
capita is analysed across these 41 less developed economies. As Figure 2 reveals, and
again using Spearmans rank correlation coefficient due to the non-parametric nature of
the data, there is a strong significant relationship between the level of informal
employment in a country and its GNP per capita (r
s
¼0.560**). The direction of this
relationship is that the share of the non-agricultural workforce in informal employment
is higher in less developed economies with lower levels of GNP per capita. This is akin
to previous findings (ILO, 2012; Yamada, 1996). Similar to this survey, nevertheless,
100
90
80
70
60
50
40
30
20
10
0
0 1020304050607080 90 100
% of informal employment which is waged work
R2= 0.1835
% of non-agricultural workforce in
informal employment
Figure 1.
Relationship between
level and nature of
informal employment
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these studies cannot establish the direction of the correlation in terms of any
cause-effect relationship. This, in consequence, is a limitation of both the current as well
as previous studies.
In recent years, alternative indicators of the level of developmenthave emerged
that take into account a wider range of variables other than simply economic
productivity. Evaluating these other measures of developmentmore widely defined,
the finding is that there is a strong significant correlation between cross-national
variations in the level of employment and cross-national variations in not only
household consumption expenditure per capita (r
s
¼0.613**) but also the Human
Development Index (r
s
¼0.497**) and Social Progress Index (r
s
¼0.509**). Informal
employment therefore, by a range of indicators of development, is larger in less
developed economies, thus confirming H1.
To evaluate the neo-liberal perspective, whether the cross-national variations in the
level of informal employment are correlated with taxes, corruption and state interference
are analysed. Starting with the neo-liberal assertion that informal employment is higher
when there is public sector corruption because this results in citizens exiting the formal
economy so as toseek livelihoods beyond the corruptpublic sector officials, the finding is
that countries with higher perceived levels of public sector corruption have higher rates
of informal employment (r
s
¼0.564**). Some support is therefore found for this
neo-liberal thesis in less developed economies. However, moving beyond perceptions and
analysing whether citizens have encountered problems with corruption in practice, the
finding is that there is no correlation between cross-national variations in the level of
informal employment and cross-national variations in either the share of firms expected
to give gifts in meetings with tax officials (r
s
¼0.224) or the percentage of firms making
informal payments to public officials (r
s
¼0.066). No support is thus found that public
sector corruption is in practice associated with the level of informal employment across
these 41 less developed economies.
Is it valid therefore, that the level of informal employment is a product of exitfrom
the formal economy due to high taxes? Given that this is a core aspect of both
neo-liberal explanations as well as a key policy measure they advocate, several measures
of taxation levels are here analysed. Beginning with the relationship between the
cross-national variations in the scale of informal employment and the level of taxes on
goods and services as a percentage of revenue, the inverse of the neo-liberal suggestion is
found. The scale of informal employment increases as taxes on goods and services
decreases and this is a statistically significant correlation (r
s
¼0.400**).
This is similarly the case when two further measures of tax levels are analysed.
There is a strong significantly correlation between cross-national variations in the level
100
90
80
70
60
50
40
30
20
10
0
0 2,000 4,000 6,000 8,000 10,000 12,000
GNP per capita
R2= 0.2046
% of non-agricultural workforce in
informal employment
Figure 2.
Relationship between
level of employment
and GNP per capita
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Cross-national
variations
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of revenue (excluding grants) as a share of GDP and the level of informal employment
(r
s
¼0.626**). The levels of informal employment are significantly lower in countries
where revenue is a higher proportion of GDP. Similarly, the same strong statistically
significant relationship exists between the level of informal employment and
cross-national variations in the level of tax revenue as a proportion of GDP
(r
s
¼0.637**). Again, informal employment is significantly lower in less developed
economies where the level of tax revenue as a proportion of GDP is higher.
There is thus no evidence to support the neo-liberal argument that cross-national
variations in the level of informal employment is associated with levels of public sector
corruption practice and thus by a desire to exitthe formal economy due to public
sector corruption practices. There is also insufficient evidence to validate the
neo-liberal thesis that higher tax rates result in exit from formal employment and a
shift into informal employment. Instead, the inverse is the case; higher tax levels are
correlated with lower levels of informal employment, presumably since this provides
greater state revenue for social transfers so that citizens can receive some level of social
protection.
To evaluate the validity of the neo-liberal argument that state interference in the
operation of the market leads to higher levels of informal employment, as well as
the contrary structuralist argument that the scale of informal employment reduces with
greater state intervention, the relationship between cross-national variations in the
scale of informal employment and both state revenue as a share of GDP as well as
the expense of government as a share of GDP are analysed. The finding is that there is
a steep decline in the scale of informal employment as both state revenue as a share of
GDP increases (r
s
¼0.605**) as well the expense of government as share of GDP
(r
s
¼0.555**). Bigger government leads to a decline, rather than increase, in the
prevalence of informal employment. Similarly, when the level of social contributions as
a percentage of revenue increases, there is a steep decline in the scale of informal
employment. This is statistically significant (r
s
¼0.560*). The neo-liberal assertion
that state interference leads to greater informal employment is therefore refuted and
instead, support found for the structuralist thesis that such employment is associated
with too little state intervention in the form of social protection.
The structuralist thesis that cross-national variations in informal employment are
associated with the level of poverty is also supported. There is a strong statistically
significant relationship between cross-national variations in the proportion of the
population living below the national poverty line and the scale of informal employment.
The greater is the share of the population living below the national poverty line in less
developed economies, the higher is the scale of informal employment (r
s
¼0.396*).
There is also a strong statistically significant relationship between cross-national
variations in the size of the poverty gap, expressed as a percentage of the poverty line
of $1.25 per day in personal purchasing power standards, and cross-national variations
in the scale of informal employment (r
s
¼0.692**). The intimation is that informal
employment might well be a last resort turned to by marginalised groups with no other
means of livelihood or support, as the structuralist perspective posits.
Conclusions
To explain the cross-national variations in the scale of informal employment, an
exploratory analysis has been conducted of the validity of three competing theoretical
perspectives in relation to less developed economies. These variously assert that higher
levels of informal employment are correlated with economic under-development
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(modernisation theory), corruption, higher taxes and state interference (neo-liberal
theory) and inadequate state intervention to protect workers from poverty
(structuralist theory). Analysing data from direct surveys conducted in 41 less
developed economies by the ILO, the finding is that just over one in three (34.4 per cent)
of the non-agricultural workforce participate in informal employment as their main job
across these less developed economies, although there are marked cross-national
variations, ranging from 83.6 per cent in India to 6.1 per cent in Serbia. Informal
employment in consequence, is not some small segment of the labour market. In 59
percent of the less developed economies surveyed, the majority of the non-agricultural
workforce is engaged in informal employment.
Evaluating the competing explanations, the finding is that although the
modernisation perspective tentatively appears to be valid that informal employment
is associated with under-development, none of the tenets of the neo-liberal thesis are
validated. Instead, there is tentative support for the structuralist thesis that high taxes
and social transfers are associated with lower levels of informal employment because
these reduce the necessity to engage in such work in the absence of other means of
support and livelihood. There is also support for the structuralist viewpoint that
informal employment is closely associated with the level of poverty in less developed
economies.
The outcome is a call for a synthesis of the tenets of the modernisation and
structuralist explanations. This finding in relation to less developed economies is
similar to the earlier finding when seeking to explain cross-national variations across
the 27 member states of the European Union (Williams, 2013). The tentative intimation
is that cross-national variations in the scale of informal employment across less
developed economies can be explained using the same broad economic and social
characteristics as cross-national variations in the more developed world of Europe.
Put explicitly, lower levels of informal employment are associated with development
and state intervention in the form of higher tax rates and social transfers to protect
workers from poverty. This new neo-modernisationexplanation not only applies
when explaining the cross-national variations in informal employment in the developed
world (Williams, 2013) but also, as shown in this paper, the developing world.
To further evaluate the validity of this new neo-modernisation perspective, what is
now required is to test whether similar findings result when using different measures
of the scale of informal employment, such as indirect measurement methods
(e.g. Schneider, 2013) as well as when time-series data are examined for individual
nations. Moreover, future studies need to analyse a wider range of indicators of state
intervention to explore whether the findings hold for all types of state intervention or
whether some types lead to a rise in the scale of informal employment. If a broader range
of countries were analysed furthermore, multivariate regression analysis might also be
used to determine how important each characteristic is to the final outcome whilst
controlling for the other characteristics. This would then overcome a limitation of this
paper which is based on just 41 less developed country cases and bivariate regressions.
This relationship between informal employment and under-development, lower tax
rates and inadequate state protection to protect workers from poverty moreover, has
practical policy implications for governments. In stark contrast to the previous policy
literature that has focused upon whether repressive measures need to be introduced
and/or incentives to encourage formalisation (Eurofound, 2013; Feld and Larsen, 2012;
OECD, 2012), this paper has displayed that wider economic and social policies associated
with the overarching modernisation of economies, state bureaucracies and social protection
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are also important. Put another way, it tentatively reveals that dealing with informal
employment cannot be treated separately from wider economic and social policies.
In sum, this paper has displayed that a sizeable share of the total workforce across
these 41 countries are in informal employment as their main job and that marked
cross-national variations exist in the proportion in informal employment, which is
associated with the level of development, tax rates, the size of government, level of social
contributions and poverty rates. Given that such conclusions have to be cautious due to
the limited data set and the sensitivity of the results in such cross-national comparisons,
this re-theorisation now needs to be tested longitudinally within nations and to a wider
range of countries, using more refined multivariate regression analysis, so as to evaluate
whether the relationship holds as well as which characteristics are most significantly
correlated with informal employment. If this paper encourages such research as well as
wider evaluation of the type of modernisation of economies and societies required, then it
will have achieved its intention.
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About the author
Colin C. Williams is a Professor of Public Policy in the Management School at the University of
Sheffield in the UK. His research interests include the informal economy, work organisation and
the future of work. His recent books include Informal Work in Developed Nations (2010,
Routledge), Rethinking the Future of Work: Directions and Visions (2007, Palgrave Macmillan),
The Hidden Enterprise Culture (2006, Edward Elgar), A Commodified World? Mapping the Limits
of Capitalism (2005, Zed) and Cash-in-Hand Work (2004, Palgrave Macmillan). Professor
Colin C. Williams can be contacted at: C.C.Williams@sheffield.ac.uk
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... A previous study by Banik and Padalkar (2021) states that the occurrence of technological advancement creates a higher opportunity for the gig economy to arise with the availability of technology that smoothens the process on an online basis. However, modernization practices will increase the country to become more developed and able to shift the status of the informal economy towards formal activities as time goes by that differ from the usage of technological practice that allows higher opportunities in the informal economy of a country (Williams, 2015). From all of that, the modernization theory tends to play a role in the impact of the changes in the informal economy output of a country with the possible effect on certain explanatory variables. ...
Article
This study aims to assess the role of technological advancement and institutional quality in mitigating the formal economy and fostering more inclusive economic well-being for families and consumers in ASEAN countries. This study employed panel data analysis using yearly data for the ten countries in ASEAN, spanning from 2008 to 2018. Findings indicate significant and diverse impacts of technological advancement on the informal economy. The study found that the interaction between technological advancement and economic growth strengthens the relationship between the informal economy across models. The higher economic growth in a country is associated with reduced informal economic activities, as reflected in the principles of modernization theory. The finding further shows the significance of institutional quality in shaping the informal economy. Strong institutional quality helps to create a structured environment that reduces informal economic activities, aligning with neoliberal theory. Governance quality, including the absence of violence and terrorism and the control of corruption, plays a role in mitigating informalities. The study’s primary contribution is its specific focus on the informal economy and the intricacies of ASEAN nations. The study also provides empirical insights into the behavior and determinants of the informal economy in ASEAN nations. Even though the study acknowledges limitations related to data availability and the challenges of quantifying the gig economy, it holds valuable policy implications.
... The high level of informality in the Ugandan labour market and the economy (Bbaale, 2014;Williams, 2015) shapes the nature of youth transitions to the labour market or 234 to work. The youth transitioning to the labour market either from school or those without formal education qualifications make use of the informality in their labour market transitions. ...
Thesis
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Sub-Saharan Africa is currently experiencing a youth bulge that is expected to continue growing for a few decades. Uganda, one of the countries with the highest youth population uses an approach that emphasises education and skills development (human capital approach) alongside promoting self-employment and youth entrepreneurship in response to the labour market and employment challenges experienced by the youth. In Uganda, vocational education and training (VET), youth entrepreneurship funds, job search assistance and career guidance address unemployment and the lack of required labour market skills. However, this approach emphasises education and skills, yet the youth are treated as a homogenous cohort; hence, the risk of exclusion of some of the youth arises. The capability approach (CA) to the youth-oriented active labour market policies (ALMPs) is broader and holistic as it considers unobserved heterogeneity, capabilities and the functionings of the youth. Therefore, this study attempted to use and apply the CA to youth-oriented active labour markets for inclusive policy design and social integration. The core argument of the study is that social policy is a means to inclusive development and social integration. Through the qualitative research method, data were collected using focus group discussions and follow-up semi-structured interviews with the youth in Arua city/district in Uganda. The youth were subdivided into eight subgroups which include youth in non-standard formal employment, self-employed youth, youth in rural employment, online workers, youth in general education, youth in vocational education and training (VET), NEET (not in employment, education, or training) and Refugee youth. A total of 8 participants participated in each of the eight (08) focus groups; follow-up individual interviews consisted of 2 participants from each of the subgroups. Research findings reveal that the high level of informality of the economy and the labour market shape the nature of labour market transitions, self-employment, work precarity and NEET. Youth entrepreneurship, the promotion of self-employment, VET, job search assistance and career guidance hardly consider the youth diversity and their voices/choices. Homogeneity, specialisation and aligning of the youth aspirations (voices/choices) with the labour market requirements are essential in expanding the functionings and capabilities of the youth for inclusive policy design and social integration. The study makes both theoretical and policy contributions. Theoretical contributions include the demonstration of how the CA can be applied to ALMPs in a highly informal labour market, proposing a framework for the application of the CA to youth labour market transition, the expansion of the active NEETs, and the notion that self-employment is a buffer against being NEETs and work instability. The policy contributions include expanding the refugee right to work policy, a call to establish labour market re-integration policies etc. Finally, the study concludes that the CA is practical and applicable in the formulation of inclusive labour market policies and understanding concepts like NEET, work precarity, self-employment and informality in the context of a developing country like Uganda.
... Despite this, the principal and persistent view has been that work in the informal economy is disproportionately conducted by marginalised populations. This is witnessed in claims that the informal economy is more prevalent in deprived global regions (ILO, 2018a), less developed nations (Schneider, 2013;Schneider and Williams, 2013;Williams, 2015e), poorer localities and neighbourhoods (Kesteloot and Meert, 1999;Williams and Windebank, 2001b), and rural rather than urban areas (Button, 1984). It is also witnessed in claims that the informal economy is more likely to be undertaken by unemployed people (Brill, 2011;Castells and Portes, 1989;Leonard, 1994;Slavnic, 2010;Taiwo, 2013;Williams and Nadin, 2014b), women rather than men (ILO, 2018a;Leonard, 1994Leonard, , 1998Stănculescu, 2005), those with greater financial difficulties (Barbour and Llanes, 2013;Katungi et al., 2006;Williams, 2004a), and even offenders (Nguyen et al., 2022). ...
... Despite this, the principal and persistent view has been that work in the informal economy is disproportionately conducted by marginalised populations. This is witnessed in claims that the informal economy is more prevalent in deprived global regions (ILO, 2018a), less developed nations (Schneider, 2013;Schneider and Williams, 2013;Williams, 2015e), poorer localities and neighbourhoods (Kesteloot and Meert, 1999;Williams and Windebank, 2001b), and rural rather than urban areas (Button, 1984). It is also witnessed in claims that the informal economy is more likely to be undertaken by unemployed people (Brill, 2011;Castells and Portes, 1989;Leonard, 1994;Slavnic, 2010;Taiwo, 2013;Williams and Nadin, 2014b), women rather than men (ILO, 2018a;Leonard, 1994Leonard, , 1998Stănculescu, 2005), those with greater financial difficulties (Barbour and Llanes, 2013;Katungi et al., 2006;Williams, 2004a), and even offenders (Nguyen et al., 2022). ...
... Despite this, the principal and persistent view has been that work in the informal economy is disproportionately conducted by marginalised populations. This is witnessed in claims that the informal economy is more prevalent in deprived global regions (ILO, 2018a), less developed nations (Schneider, 2013;Schneider and Williams, 2013;Williams, 2015e), poorer localities and neighbourhoods (Kesteloot and Meert, 1999;Williams and Windebank, 2001b), and rural rather than urban areas (Button, 1984). It is also witnessed in claims that the informal economy is more likely to be undertaken by unemployed people (Brill, 2011;Castells and Portes, 1989;Leonard, 1994;Slavnic, 2010;Taiwo, 2013;Williams and Nadin, 2014b), women rather than men (ILO, 2018a;Leonard, 1994Leonard, , 1998Stănculescu, 2005), those with greater financial difficulties (Barbour and Llanes, 2013;Katungi et al., 2006;Williams, 2004a), and even offenders (Nguyen et al., 2022). ...
... Despite this, the principal and persistent view has been that work in the informal economy is disproportionately conducted by marginalised populations. This is witnessed in claims that the informal economy is more prevalent in deprived global regions (ILO, 2018a), less developed nations (Schneider, 2013;Schneider and Williams, 2013;Williams, 2015e), poorer localities and neighbourhoods (Kesteloot and Meert, 1999;Williams and Windebank, 2001b), and rural rather than urban areas (Button, 1984). It is also witnessed in claims that the informal economy is more likely to be undertaken by unemployed people (Brill, 2011;Castells and Portes, 1989;Leonard, 1994;Slavnic, 2010;Taiwo, 2013;Williams and Nadin, 2014b), women rather than men (ILO, 2018a;Leonard, 1994Leonard, , 1998Stănculescu, 2005), those with greater financial difficulties (Barbour and Llanes, 2013;Katungi et al., 2006;Williams, 2004a), and even offenders (Nguyen et al., 2022). ...
... Despite this, the principal and persistent view has been that work in the informal economy is disproportionately conducted by marginalised populations. This is witnessed in claims that the informal economy is more prevalent in deprived global regions (ILO, 2018a), less developed nations (Schneider, 2013;Schneider and Williams, 2013;Williams, 2015e), poorer localities and neighbourhoods (Kesteloot and Meert, 1999;Williams and Windebank, 2001b), and rural rather than urban areas (Button, 1984). It is also witnessed in claims that the informal economy is more likely to be undertaken by unemployed people (Brill, 2011;Castells and Portes, 1989;Leonard, 1994;Slavnic, 2010;Taiwo, 2013;Williams and Nadin, 2014b), women rather than men (ILO, 2018a;Leonard, 1994Leonard, , 1998Stănculescu, 2005), those with greater financial difficulties (Barbour and Llanes, 2013;Katungi et al., 2006;Williams, 2004a), and even offenders (Nguyen et al., 2022). ...
... Reviewing the studies that evaluate these theories by examining the cross-national variations in these economic and social conditions, and cross-national variations in the size of the formal economy, the same findings continuously emerge. Whether one measures the size of the informal economy using Schneider's MIMIC estimates (Williams, 2014d) or using direct surveys (Williams, 2014a(Williams, ,b,c, 2015a(Williams, ,b, 2016Williams and Martinez-Perez, 2014) and whether one compares the 28 member states of the European Union (Williams, 2014c;2016;Williams and Horodnic, 2016), post-socialist transition economies (Williams, 2014a(Williams, , 2015b or countries across the developing world (Williams, 2014b(Williams, , 2015a, the finding is that there is no evidence to support the state over-interference thesis. Instead, the prevalence of the informal economy is positively associated with the tenets of the modernisation and state underintervention theses. ...
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This diagnostic report evaluates the extent, nature and drivers of the informal economy in Azerbaijan followed by recommendations regarding how this sphere can be tackled.
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This study explores marketing strategies informal enterprises employ for growth in the Ghanaian context through the lens of the Theory of Critical Success Factors. Reporting on a sample size of 30 at East Legon in Accra (Capital of Ghana), this study adopts a qualitative perspective, considering the informal context in which the study was conducted as a case. Data were gathered through face-to-face in-depth interviews and analysed qualitatively using themes in line with the three-stage iterative methodology developed by Miles et al. (Qualitative data analysis: An expanded sourcebook. Sage, 1994): data reduction, data display, and drawing and verifying conclusions. The study finds that although traditional marketing is not inherent in the informal entrepreneurial space of Ghana, developing key growth strategies such as diversification, ploughing or plowing back of profit, business expansion, gaining financial support, and hiring the correct number of employees are critical factors that necessitate enterprise growth in the informal economy. The findings also suggest traditional growth strategies such as the Ansoff matrix and others may not be applicable in the informal economy. Therefore, the study calls for specific growth strategies akin to the informal economy to be adopted by informal entrepreneurs.
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Recognizing that the current conceptualizations of men's and women's undeclared work derive almost entirely from a limited range of small-scale studies of specific localities, sectors and occupations, this article begins to resolve this dearth of evidence by reporting the findings of an extensive cross-national survey of undeclared work conducted in 2007 across 27 European Union (EU) nations. The outcome is fresh and extensive EU-wide evidence that extends existing conceptualizations of the gender differences in terms of participation, sector, contract type and pay. However, the recognition that undeclared work is conducted for closer social relations and sometimes for motives other than financial gain, is shown to apply not only to women, as previously contended, but to men as well and to constitute most of the undeclared work in the EU. The result is a call for a fundamental reconceptualization of the nature of undeclared work that recognizes the heterogeneous work relations involved.
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For a long time, it has been the declared aim in many countries to fight tax evasion in all its different manifestations, from undeclared work by cleaners and gardeners in private households to tax evasion in the international capital markets. This study focuses on the phenomenon of undeclared work and the case of Germany, presenting the most comprehensive analysis of tax non-compliance for Germany to date, based on surveys conducted by the Rockwool Foundation. Theoretically, the analysis starts from the standard model of tax evasion as being influenced by the subjectively perceived extent of deterrence, the perceived marginal tax burden and social norms. Evidence is provided on the impact of deterrence and other factors on tax non-compliance, and several descriptive statistics are presented to better illustrate the natrure of undeclared work with regard to industry, region, education and other socio-economic characteristics. © Springer-Verlag Berlin Heidelberg 2012. All rights are reserved.
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