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COS0010.1177/0020715213519458International Journal of Comparative SociologyRoberts
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Article
Peripheral accumulation in the
world economy: A cross-national
analysis of the informal economy
International Journal of
Comparative Sociology
2014, Vol. 54(5-6) 420­–444
© The Author(s) 2014
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DOI: 10.1177/0020715213519458
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Anthony Roberts
University of California, Riverside, USA
Abstract
The persistence and growth of the informal economy have puzzled researchers and challenged mainstream
explanations of the development of the informal economy. This study utilizes a world-systems approach for
explaining cross-national variation in the size of the informal economy for a sample of 74 developing and
developed countries observed over a recent 8-year period (1999–2007). According to this approach, the
informal economy is a characteristic of peripheral accumulation in the world economy and its development
is driven by unequal exchange in international trade and foreign capital penetration. Based on estimates from
random and fixed-effects regression models using multiple measures of world-system position, countries
in the periphery and semi-periphery of the world economy have larger informal economies than core
countries. More importantly, this difference in the development of the informal economy between the core,
semi-periphery, and periphery is partially explained by the effects of international trade and foreign direct
investment. Overall, the findings indicate that the development and persistence of the informal economy are
driven by the structure of the world economy and processes of economic globalization.
Keywords
Economic development, economic globalization, government regulation, informal economy, world-systems
Introduction
The informal economy, or the aggregation of unrecorded and unregulated economic activities,
remains an important element of contemporary capitalism. Over the last 40 years, an extensive literature emerged across several academic fields as researchers attempt to document and explain the
development of the informal economy in developed and less-developed countries. Given the proliferation of research on the informal economy, it is unsurprising that disagreement over the nature and
determinants of the informal economy remains. However, the scarcity of internationally comparable
data on the size of the informal economy limits the ability to adjudicate competing arguments in the
literature. This difficulty in conceptualizing and measuring the informal economy is primarily
Corresponding author:
Anthony Roberts, Sociology Department, University of California, Riverside, 1206 Watkins Hall, Riverside, CA 92521,
USA.
Email: [email protected]
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attributable to the clandestine nature of informal economic activity (Feige, 1990; Portes and Haller,
2005; Schneider et al., 2010). Recently, researchers address this issue by treating the informal economy as an unobservable component of national economies which is indirectly measurable through
a set of observable indicators. Utilizing this ‘latent variable approach’, these researchers develop
internationally comparable estimates of the size of the informal economy (Giles, 1999; Schneider,
2005; Schneider et al., 2010).1 The recent availability of internationally comparable data on the size
of the informal economy allows for a systematic assessment of competing views on the nature and
determinants of the informal economy using a macro-comparative approach.
A number of country-specific case studies document the roles of a wide range of social, political, and economic factors in promoting the development of informal economy (Borocz, 2000;
Bosch and Maloney, 2010; Davies and Thurlow, 2010; De Soto, 1989; Hart, 1973; Kaya, 2008;
Kesteloot and Meert, 1999; Williams and Round, 2008). While these case studies provide valuable
information on the informal economy, the generalizability of this information is extremely limited.
Previous studies systematically study cross-national variation in the size of the informal economy,
but rely on proxies of the informal economy, such as the size of the service labor force (Evans and
Timberlake) or self-employment (Ihrig and Moe, 2001; Loayza and Rigolini, 2011). Based on this
limitation in the literature, recent studies use direct and internationally comparable estimates of the
size of the informal economy to explain cross-national variation (Djankov and Ramalho, 2009;
Ihrig and Moe, 2004; Kus, 2010). This article continues this approach by examining variation in
the size of the informal economy across a large cross section of countries from 1999 to 2007 using
recently available national estimates of the size of the informal economy (see Schneider et al.,
2010).
Originally, the informal economy was associated with the subsistence activities of the marginalized urban poor or the pre-capitalist economic activities of rural populations (Hart, 1973; International
Labor Organization (ILO), 1972; Sethuraman, 1976; Tokman, 1978). Yet, the persistence and
growth of the informal economy in highly developed countries (Castells and Portes, 1989;
Organisation for Economic Co-operation and Development (OECD), 2009; Portes and SassenKoob, 1987; Sassen, 1997, 2001; Schneider and Enste, 2002; Tanzi, 1980, 1983) and industrializing
less-developed countries (Borocz, 2000; Davis, 2006; De Soto, 1989; Ihrig and Moe, 2001; ILO,
2002; Maloney, 2004; Schneider, 2005; Schneider et al., 2010) raised doubts over this nascent view
of the informal economy. The empirical shortcomings of this early perspective generated several
new theories of informalization, which identified processes of economic governance, globalization,
and socioeconomic development as the main causes of informality. However, recent theorization
omits the general argument that the informal economy is a necessary component of capitalist accumulation in the world economy (Portes, 1978; Portes and Walton, 1981). In this article, I address this
omission by investigating the relationship between the informal economy and the world economy.
In the current literature, researchers recognize that the informal economy is composed of a
highly heterogeneous set of income-generating activities and past theorization is insufficient for
adequately conceptualizing its diverse nature (Williams and Round, 2008). Based on this criticism,
it is important to investigate how informal activities are directly or indirectly linked to the production of goods and services in the formal economy (Castells and Portes, 1989; Portes and SassenKoob 1987; Portes and Walton, 1981). From this alternative perspective, the informal economy is
defined as the aggregation of income-generating processes which are unregulated by the national
laws and regulations and embedded in the production processes of formal goods and services
(Castells and Portes, 1989; Portes and Haller, 2005). Instead of conceiving of the informal economy as a social safety net for the marginalized poor or simply the economic activities of rural
populations, this perspective emphasizes the interdependence between formal and informal economic activities.
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Theories of informal economy are grounded in three general perspectives: (1) the dualist perspective, (2) the legalist perspective, and (3) the structural perspective (Chen, 2009). The dualist
perspective conceives of the informal economy as a separate sector of economic activity which is
primarily driven by macroeconomic conditions and economic development. According to this
view, during periods of economic growth and strong labor market performance, the informal sector
contracts as informal producers and workers migrate to the formal sector (Hart, 1973; ILO, 1972).
The legalist perspective views the informal economy as an unregulated sector composed of smallscale entrepreneurs trying to avoid the economic burden of overt regulation (De Soto, 1989; Kus,
2010; Maloney, 2004). Based on this argument, conditions of overt economic regulation and lax
enforcement incentivize informal petty production, which causes the informal economy to expand.
These conceptualizations of the informal economy are inaccurate because they assume that informal economic activity is independent of the formal economy. The structural perspective emphasizes how formal and informal economic activities are utilized in the production of formal goods
and services as way to subsidize the cost of labor-intensive production (Castells and Portes, 1989;
Moser, 1978; Portes and Walton, 1981; Tabak and Crichlow, 2000).
Structural theories of the informal economy view the informal economy as a persistent feature of
capitalist accumulation in the world economy. Specifically, the informal economy is viewed as a
critical component of capitalist accumulation in countries occupying peripheral and semi-peripheral
roles in world economy (Evans and Timberlake, 1980; Portes, 1978; Portes and Walton, 1981).
According to world-systems perspective, countries occupy stratified roles in the world economy
which corresponds to an unequal international division of labor (IDL) (see Babones, 2005; ChaseDunn, 1989; Lloyd et al., 2009 for a review). Countries located in the periphery and semi-periphery
of the world economy tend to specialize in labor-intensive and competitive industries, while countries located in the core specialize in capital- and skill-intensive production in monopolized industries (Arrighi and Drangel, 1986; Chase-Dunn, 1989; Evans, 1979; Wallerstein, 1974a). In turn, this
unequal IDL is reproduced through exploitive economic relations between the core and periphery
where economic value is re-appropriated from the periphery and semi-periphery to the core through
processes of trade and investment.
This article’s main contention is that the informal economy is an essential structural component
of peripheral accumulation – profit-making in competitive and labor-intensive industries through
minimizing labor costs (Portes, 1978: 37; Portes and Walton, 1981: 84). Since local firms in the
periphery and semi-periphery primarily specialize in labor-intensive production, profits are directly
tied to the cost of labor. These firms are reliant on the informal economy to suppress formal wages,
to supply low-wage informal workers, and to reproduce low-wage workers with inexpensive goods
and services (Bienefeld, 1975; Portes, 1978; Portes and Sassen-Koob, 1987; Portes and Walton,
1981). Yet, even though this argument originated in the late 1970s and early 1980s, few empirical
studies investigate the relationship between the IDL and the informal economy. This is surprising
given Alejandro Portes (1978) criticism that ‘… the informal economy represents a fundamental
concept for understanding the operation of capitalism as a world phenomenon and constitutes a
missing element in contemporary world-system formulations of core and periphery’ (p. 35). The
main purpose of this article is to address Portes’ critique by empirically analyzing how the structure
of the world economy affects the size of the informal economy in 74 developed and less-developed
countries observed over a recent 8-year period (1999–2007).
The persistence and growth of the informal economy
The persistence and growth of the informal economy in developed and less-developed countries
during periods of economic growth and deregulation challenge the dualist and legalist perspectives
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Figure 1. Trends in informal economic development by income group, 1999–2007.
Source: Schneider et al. (2010).
GDP: gross domestic product.
on the informal economy. For example, from 1975 to 2000, less-developed regions (North Africa,
Sub-Saharan Africa, Latin America, and Southeast Asia) experienced an average growth of 2.5–3.5
percent in gross domestic product (GDP) per capita, while the informal share of non-agricultural
employment increased by about 10 percent (OECD, 2009: Figure 3.3). This trend is not unique to
less-developed regions. Over the same period, in the United States and Western Europe, the informal economy grew from 5.3 percent of official GDP to 16.5 percent of official GDP (Schneider and
Enste, 2002), while the informal share of the non-agricultural labor force grew from 10 percent to
15 percent (OECD, 2009: Figure 2.3). The important questions are whether the informal economy
continued to grow since 2000 and whether cross-national differences in the size of the informal
economy remain.
Figure 1 shows the average size of the informal economy, based on estimates from Schneider et
al. (2010), across high-, upper-middle-, low-middle-, and low-income countries, as defined by the
World Bank’s 2010 Income Group classification scheme. Indeed, as seen in Figure 1, while the
informal economy grew in developed and less-developed countries from 1999 to 2007, the size of
the informal economy varied by level of development. In high-income countries, where gross
national product (GNP) per capita exceeds US$12,500, the informal economy expanded by 26
percent, growing from 15 percent of official GDP to 19 percent of official GDP, even though official GDP grew by over 2 percent over this period. Similarly, in low-income countries, where GNP
per capita is less than US$1000, the informal economy expanded by 36 percent, growing from 28
percent of official GDP to 38 percent while the official GDP grew by 3 percent over this period
(World Bank, 2012).
This ubiquitous growth of the informal economy across all income groups challenges the general claims of the early dualist and legalist perspectives. According to the dualist perspective,
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Figure 2. Average size of the informal economy by world-system position.
Source: World-system position – Snyder and Kick (1979) as updated in Bollen and Appold (1993); size of the informal
economy – Schneider et al. (2010).
GDP: gross domestic product.
***p < .001 for mean difference t-tests comparing group means.
economic growth should reduce the size of the informal economy as higher labor demand and
entrepreneurial opportunities in the formal sector attract workers and petty producers from the
informal sector (Tokman, 1978). However, over the last few decades the informal economy grew
in low-, middle-, and high-income countries even though these countries experienced growth in the
formal economy. According to the legalist perspective, the recent expansion and persistence of the
informal economy are attributable to the enactment of new economic regulations (Djankov and
Ramalho, 2009), but the growth of the informal economy during a period of rapid deregulation in
developed countries raises concerns over the validity of this argument (Heintz and Pollin, 2003).
Economic development, regulation, and the informal economy
A revision to the dualist perspective emerged in the literature to address the empirical shortcomings
of that perspective on the relationship between the informal economy and economic development.
While this revised dualist perspective retains the basic view on the relative autonomy of the informal economy, it advances the original dualist position by identifying how processes of internal
economic development (e.g. urbanization, industrialization, and unemployment) affect the development of the informal economy. However, the failure to associate these internal processes with
world economy continues to limit this revised perspective.
Starting with the observed subsistence activities of the urban poor in Ghana (Hart, 1973) and
Kenya (ILO, 1972), researchers associate the expansion of the informal economy with the rapid
urbanization of less-developed countries (Gugler, 1982; Koo and Smith, 1983; McGee, 1973;
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Moser, 1978; Sethuraman, 1976). These observations are fairly consistent with the early ‘overurbanization hypothesis’, which argues that growth of the informal economy in less-developed
countries is caused by the rapid in-migration of rural populations into industrializing urban centers
(Gibbs and Martin, 1962; Smith, 1987). In more recent studies, researchers argue that international
migration into urban centers induces a growth in the informal economy because international
migrants are unable to find employment and business opportunities in the formal economy due to
legal and cultural barriers (Chiang, 2004; Raijman and Tienda, 2000; Waldinger and Lapp, 1993).
According to the ‘urbanization hypothesis’, the informal economy expands as both international
and rural migrants are incorporated into the urban economy as informal petty producers and/or
informal labor because of barriers to entry in the formal sector.
An explicit and central argument of the dualist perspective is the distinction between enterprises in the formal and informal sectors. The formal sector is composed of large-scale industrial
firms employing unskilled and semi-skilled manufacturing workers, while the informal sector is
made up of small-scale petty producers, street vendors, and home-based workers (Chen, 2009;
Gerry, 1987; Kus, 2010). Accordingly, rapid growth in the formal industrial sector causes a
decline in the informal sector as large-scale industrial firms increase their demand for manufacturing labor. This argument is based on the assumption that the informal sector operates as an
autonomous arena for income-generating activity during periods of economic downturn. In particular, during slow growth periods, industrial firms in the formal sector reduce their demand for
labor as they attempt to lower production costs. Thus, as opportunities for employment in the
industrial sector decline, the size of the informal economy is expected to grow. Therefore, according to the ‘industrialization hypothesis’, the size of the informal economy decreases with the
growth of the manufacturing sector because industrial expansion induces a labor force shift from
the informal to the formal industrial sector.
Recent evidence suggests that the unemployment rate is positively associated with the size of
the informal sector because a reduction in the effective demand for labor in the formal sector
causes workers to migrate into the informal sector (Bajada and Schneider, 2009; Bosch and
Maloney, 2008, 2010; Henry, 1987). However, some researchers suggest that the unemployment
rate is negatively related to the size of the informal economy. For example, the unemployment rate
in South Africa exceeded 40 percent in 2002, but the size of the informal workforce remained relatively small compared to previous periods (Kingdon and Knight, 2004). This observation is primarily attributable to the availability of private credit to households and wage inflation, which
limited labor migration from the formal sector to informal sector (Davies and Thurlow, 2010). The
inconclusive relationship between the formal unemployment rate and the size of the informal economy warrants more in-depth investigation.
In the late 1980s, a new theory of the informal economy emerged in the literature which contends that participation in the informal economy is voluntary and based on the rational decisionmaking of petty entrepreneurs and workers. Specifically, this perspective argues that firms,
entrepreneurs, and workers decide to operate informally to avoid the additional costs created by
excessive regulations and taxation (Chen, 2009). These researchers posit that the size of the informal economy depends on the intensity of economic regulations (De Soto, 1989; Ihrig and Moe,
2001, 2004; Loayza and Rigolini, 2011; Macias and Cazzavillan, 2009; Maloney, 2004; Ulyssea,
2010) and the quality of regulatory enforcement (Kus, 2010).
In Hernando De Soto’s (1989) The Other Path, the informal economy in Peru is seen as a
response to the expansion of the state regulations. De Soto argues that the decision of rural migrants
to operate as informal vendors is primarily attributable to the extensive regulatory requirements for
acquiring a business license and operating a formal business in Peru. Based on this important case
study, researchers began to analyze the effects of business flexibility on the informal economy in
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Mexico (Macias and Cazzavillan, 2009), Brazil (Ulyssea, 2010), and in a sample of 54 developed
and less-developed countries (Loayza and Rigolini, 2011). These studies find that business flexibility reduces the size of the informal economy and the informal labor force by minimizing the
costs associated with operating a business and employing workers in the formal economy. Thus,
according to the ‘regulatory burden hypothesis’, an increase in business flexibility is associated
with a decrease in the size of the informal economy as the costs of entering and operating in the
formal economy decrease.
While most of the literature focuses on the degree of economic regulations, a recent study calls
attention to the quality of enforcement – the degree to which countries effectively and consistently
enforce economic regulations (Kus, 2010: 494). Drawing on insights from Max Weber, this study
argues that economic actors are more likely to engage in informal economic activity when there is
a low likelihood of being sanctioned by state actors (see also Portes and Centeno, 2006; Portes and
Haller, 2005). The study finds that the quality of enforcement is a greater determinant of the size
of the informal economy than the intensity of economic regulations based on a cross-sectional
analysis of 78 countries. Thus, the ‘regulatory enforcement hypothesis’ states that the size of the
informal economy is inversely related to the quality of enforcement because economic actors are
more likely to operate informally when economic regulations are inadequately enforced.
Overall, the dualist and legalist perspectives received extensive theoretical and empirical attention in the recent literature on the informal economy, while structural perspectives are largely
ignored. This is troubling given the persistent and valid argument that developmental processes
and economic regulations are products of a country’s structural position in the world economy
(Chase-Dunn, 1989; Evans, 1979, 1995). More importantly, despite recent research on the effect of
international trade and investment on the recent expansion of the informal economy (Carr and
Chen, 2002; Heintz and Pollin, 2003; Phillips, 2011; Standing, 1999), most studies testing the
legalist and dualist perspectives fail to adequately account for the effects of international trade and
investment on the informal economy. In response to these theoretical and empirical gaps in the
literature on the informal economy, I analyze how a country’s structural position in the world
economy, international trade, and foreign direct investment (FDI) affect the development of the
informal economy.
The structure of the world economy and the informal economy
The main purpose of the article is to investigate the relationship between the structure of the world
economy and the size of the informal economy. Specifically, I test whether countries located in the
periphery and semi-periphery of the world economy exhibit larger informal economies than countries located in the core. This analysis is based on the argument that a large informal economy is a
vital condition of peripheral capitalism because it subsidizes formal firms engaged in laborintensive production (Portes and Walton, 1981: 84–88).
A central insight of the world-systems perspective is that the world economy is hierarchically
organized around three structural roles: the core, the semi-periphery, and the periphery (Wallerstein,
1974b: 401).2 This tripartite organization induces countries to develop differentiated regimes of
capitalist accumulation according to their role in the world economy (Chase-Dunn and Rubinson,
1977: 456–457; Evans, 1979). Core countries tend to specialize in capital- and skill-intensive production of high-value commodities in monopolized industries which requires investment in human
and productive capital for profit accumulation. Peripheral countries specialize in labor-intensive
production of low-value commodities in highly competitive industries that require a large workforce of unskilled and low-wage labor for profit accumulation (Arrighi and Drangel 1986; ChaseDunn, 1989; Mahutga, 2006; Mahutga and Smith, 2011). Semi-peripheral countries perform a
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structurally important role in stabilizing the world economy by specializing in a mix of skillintensive and labor-intensive production processes and serving as an intermediary between the
core and periphery (Arrighi and Drangel, 1986: 12; Chase-Dunn and Rubinson, 1977; Evans, 1979;
Wallerstein, 1974c). As a consequence of this international division, core countries developed
highly sophisticated and diversified economies with strong governance institutions, while periphery countries tend to develop simple economies and weak governance institutions (Chase-Dunn,
1989; Chase-Dunn and Rubinson, 1977). Overall, the structure of the world economy is important
for explaining cross-national variation in social, economic, and political development.
Indeed, over the last 30 years an extensive empirical literature validated the general claim that
the structural position of a country in the world economy directly affects national inequality
(Alderson and Nielsen, 1999; Lee et al., 2007; Mahutga et al., 2011; Nolan, 1983), economic
development (Clark, 2010; Mahutga and Smith, 2011; Nolan, 1983), industrialization (Bollen and
Appold, 1993), and democratic governance (Bollen, 1983; Clark, 2012). However, to date, no
study tests whether the structure of the world economy accounts for cross-national variation in the
size of the informal economy. The lack of empirical evidence on the relationship between the structure of the world economy and the informal economy is problematic, given the persistent argument
in the world-systems literature that the informal economy is a component of peripheral accumulation (Chase-Dunn, 1989: 235; Portes, 1978; Portes and Walton, 1981; Smith, 1987).
Figure 2 reports the average size of the informal economy in the core, semi-periphery, and
periphery based on internationally comparable estimates from Schneider et al. (2010). Figure 2
shows a significant difference in the average size of the informal economy between core, semiperipheral, and peripheral countries. In the periphery, the average size of the informal economy
is about 34 percent the size of the official economy, while in the semi-periphery, the average size
of the informal economy is about 31 percent the size of the official economy. Compared to the
core, the size of the informal economy in peripheral and semi-peripheral countries is twice as
large. This difference in size provides tentative support for the general claim that informal economic activity is far more prevalent in the periphery and semi-periphery. The next step is to
identify the world economic processes that produce this difference in the size of the informal
economy across the IDL.
Unequal exchange, disarticulation, and the informal economy
Over the last decade, an emerging literature argues that economic globalization is the primary force
causing the persistence and recent expansion of the informal economy in developed and less-developed countries (Carr and Chen, 2002; Heintz and Pollin, 2003; Phillips, 2011; Standing, 1999).
According to this new perspective, the rapid intensification of global trade induces local firms to utilize
informal labor and products as a means of reducing production costs to maintain competitiveness in an
increasingly global economy. The main problem with this argument is the assumption that economic
globalization has the same effect on the informal economy in the core, periphery, and semi-periphery.
Drawing on insights from the world-systems perspective, I argue that the effects of economic globalization are conditioned by a country’s location in the structure of the world economy (Bornschier and
Chase-Dunn, 1985; Wallerstein, 1974b). I contend that both international trade and investment have a
stronger effect on the size of informal economy in peripheral and semi-peripheral countries.
According to the world-systems perspective, processes of trade and investment are the primary
mechanisms reproducing the IDL by transferring value from the periphery and semi-periphery to
the core and hindering growth in the non-core (Bornschier and Chase-Dunn, 1985; Wallerstein,
1974b). Trade in the world economy is characterized as an unequal exchange between core and
non-core countries because core states primarily export high-tech manufacturing goods or
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high-value services, while periphery and semi-periphery states primarily export labor-intensive
light manufacturing goods and raw materials (see Arrighi and Drangel, 1986; De Santos, 1970;
Mahutga and Smith, 2011; Wallerstein, 1974a). The difference in the relative value of traded commodities re-appropriates surplus value from the non-core to the core, which reproduces the noncore’s subordinate status in the IDL. Additionally, investment in the world economy reproduces the
IDL by suppressing the development of non-core economies through creating a condition of sectoral disarticulation, where economic growth is concentrated in foreign-dominated sectors. Since
the periphery and semi-periphery specialize in low-value and labor-intensive industries, they are
dependent on the transfer of capital and technology from the core (Caporaso, 1981; De Janvry and
Garramon, 1977). Dependence on foreign capital causes local sectors to stagnate when economic
development is induced by FDI because the local economy is unable to supply the requisite inputs
for production in foreign-dominated sectors.
Commodity trade between the core and the non-core re-appropriates value to the core through
exploiting international differences in production capacity and commodity value (Arrighi and
Drangel, 1986; Emmanuel, 1972; Wallerstein, 1974a: 401). The returns from international trade for
periphery and semi-periphery countries are minimal because these countries specialize in the production of low-value goods and the extraction of raw materials. The low rate of returns from international trade forces local firms to utilize the informal economy to subsidize the formal production
of labor-intensive and low-value goods and services. Therefore, according to the ‘unequal exchange
hypothesis’, international trade should increase the size of the informal economy in the semiperiphery and periphery, while having no effect on the size of informal economy in the core.
The inflow of foreign capital into the periphery and semi-periphery creates a condition of sectoral disarticulation, where export-oriented sectors dominated by foreign capital experience rapid
growth while becoming ‘disarticulated’ from the local economy (Amin, 1974; Beer and Boswell,
2002; Bornschier and Chase-Dunn, 1985; Dixon and Boswell, 1996; Stokes and Anderson, 1990).
In peripheral and semi-peripheral countries, foreign capital has a tendency to concentrate into a few
industrialized and export-oriented sectors, increasing the capital intensity of production in these sectors vis-a-vis local sectors (Amin, 1974; Evans and Timberlake, 1980; Mahutga and Bandelj, 2008).
Gains from the development of the export-oriented sector are unable to spread to other sectors
because the local economy is unable to provide the requisite capital inputs and skilled labor to the
foreign-dominated sector. Additionally, the profits generated in export-oriented sectors are primarily
captured by foreign investors and firms, which reduce the capacity for local investment (Bornschier
and Chase-Dunn, 1985). The main consequence of this developmental pattern is the increasing reliance on the informal economy to subsidize labor-intensive production in local sectors.
Additionally, the capital intensity of production in foreign-dominated sectors reduces the
demand for unskilled labor in these sectors (Feenstra and Hanson, 1997). For example, Evans and
Timberlake (1980) argue that foreign capital dependence induces growth in service sector employment in less-developed countries because foreign-dominated industrial sectors are unable to absorb
a large portion of the local unskilled labor force. This decrease in the demand for unskilled labor
reduces the wages of unskilled workers and increases the demand for inexpensive goods and services from the informal economy. According to the ‘disarticulation hypothesis’, an increase in FDI
is expected to increase the size of the informal economy in periphery and semi-periphery countries,
while having no effect in the core countries.
Data and method
In this article, I analyze the direct and conditional effects of the structure of the world economy on
the size of the informal economy using unbalanced panel data for 74 developed and less-developed
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countries from 1999 to 2007.3 Data are restricted to 74 countries because of missing data and the
exclusion of countries with less than three observations during the observed period. The sample
includes 24 high-income, 16 upper-middle-income, 20 lower-middle-income, and 14 low-income
countries. Overall, the sample contains 554 country-year observations.
Dependent variable: size of the informal economy
Data on the size of the informal economy are drawn from a recent study which utilized confirmatory factor analysis (CFA) to derive estimates of the informal economy (Schneider et al., 2010).
This ‘latent variable approach’ provides comparable estimates of the size of the informal economy
by treating the informal economy as an unobservable latent construct measured by a series indicators and proximate causes (Frey and Weck-Hanneman, 1984; Giles, 1999; Schneider, 2005;
Schneider et al., 2010).4 In the study, the authors estimate the relative size of the informal economy
for 162 countries over an 8-year period (1999–2007) using a linear model based on the following
variables: size of the public sector, the Heritage Foundation’s Fiscal Freedom Index, the Heritage
Foundation’s Business Freedom Index (BFI), and GDP per capita (Schneider et al., 2010: 453).5 I
include two of the four variables (the BFI and size of the public sector) from the estimation model
in the regression models to create a more conservative test for the partial effects of the main independent variables. Due to missing data in the independent variables, the analysis uses estimates for
74 countries. Based on these estimates, the size of the informal economy ranges from 8.4 percent
(Switzerland 1999) to 68.1 percent of official GDP (Panama 2006) with an average size of 28.2
percent of official GDP.
Independent variables: international trade, investment, and world-system position
I examine the direct and conditional effects of three variables: trade openness, foreign capital penetration, and world-system position. All independent variables are lagged by a year. Trade openness is measured as the summation of exports and imports as a percentage of total GDP. Data on
imports and exports are drawn from the World Development Indicator database (World Bank,
2012). The variable is transformed using a natural log function in order to adjust for univariate
outliers and non-normality.
Based on previous studies on foreign capital penetration and economic growth (Beer and
Boswell, 2002; Dixon and Boswell, 1996; Mahutga and Bandelj, 2008), foreign capital penetration
is measured as the total inward stock of FDI as a percentage of total GDP. Foreign capital penetration is transformed using a natural log function in order to adjust for univariate outliers and nonnormality. I include the rate of inward FDI, which is measured as the ratio of total inward FDI
flows to total inward stocks of FDI, and domestic investment, measured as gross capital formation
as a percentage of official GDP. The inclusion of these controls is based on the misspecification of
models in the early foreign capital penetration literature (see Dixon and Boswell, 1996; Firebaugh,
1996). Data on inward FDI are drawn from the World Investment database (United Nations
Conference on Trade and Development (UNCTAD), 2009). Data on gross capital formation are
drawn from the World Development Indicators database (World Bank, 2012).
World-system position is based on the categorization developed by Snyder and Kick (1979) and
updated by Bollen (1983) and Bollen and Appold (1993). Based on the block modeling of four
political and economic networks (international trade, diplomacy, military interventions, and treaties), countries are categorized into three general world-system positions: core, semi-periphery,
and periphery. This measure is preferred over other world-system position measures for three reasons. First, the Snyder and Kick measure is the most utilized indicator of world-system position in
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International Journal of Comparative Sociology 54(5-6)
the sociological literature (e.g. Alderson and Nielsen, 1999; Beckfield, 2003; Lee et al., 2007;
Lloyd et al., 2009; Mahutga et al., 2011). Second, the measure classifies the largest number of
countries compared to alternative measures. Third, recent research finds that the Snyder and Kick
measure exhibits greater predictive validity than other world-systems measures for explaining
national income inequality (Mahutga et al., 2011). Given the disagreement over world-system
position measurement (Babones, 2005; Lloyd et al., 2009), I re-estimate the models using two
alternative world-systems measures based on international trade networks. The first measure utilizes bilateral trade in 15 ideal-typical industries and a regular equivalence strategy for identifying
structural roles (Mahutga and Smith, 2011). The second measure utilizes all bilateral trade from
1980 to 1990 and a core-peripheral modeling approach (Clark and Beckfield, 2009). Based on the
Snyder and Kick measure, the sample contains 30 periphery, 26 semi-periphery, and 17 core
countries.
Baseline model: economic regulation
Three measures of a country’s regulatory environment are included in the first baseline model: (1)
business regulation, (2) quality of enforcement, and (3) size of the public sector. The Heritage
Foundation’s (2009) BFI is used for measuring the intensity of economic regulation. The BFI is a
standardized multidimensional index based on a number of economic regulations governing the
opening, operating, and closing a business.6 Data on these economic regulations are drawn from
World Bank’s Doing Business reports. The index is inversely measured, where higher scores (100)
indicate complete business freedom (little to no regulation) and lower scores (0) indicate no business freedom (complete regulation).
For measuring the quality of enforcement, I use the ‘Rule of Law Index’ (RLI) from the
Governance Matters database (World Bank, 2009). The RLI is measured using aggregated survey
data from government officials, business owners, and corporate managers. In the survey, respondents were asked a series of questions aimed at accounting for
[the] perceptions of the extent to which agents have confidence in and abide by the rules of society, and in
particular the quality of contract enforcement, property rights, the police, and the courts, as well as the
likelihood of crime and violence. (Kaufman et al., 2009)7
Lower scores on the index indicate a lack of enforcement, while higher scores indicate consistent
and efficient enforcement of regulations.
Finally, public sector size is measured as the total final expenditures of all government expenses,
excluding military expenditures, as a percentage of GDP. Previous research shows that public
expenditures is associated with a growth in the size of informal economy in Germany during the
1970s (Petersen, 1982). Data on government expenditures are drawn from the World Bank (2012)
World Development Indicators database.
Baseline model: economic development and labor market performance
The second baseline model accounts for the effects of economic development and labor market
performance by including the following variables: (1) the national unemployment rate, (2) the
3-year average growth rate, (3) industrialization, (4) and urbanization. The national unemployment
rate is measured as the share of the labor force that is without work but are available for and seeking employment. Data for unemployment were drawn from the World Development Indicator database (World Bank, 2012). The rate of unemployment is transformed by a natural log function in
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Roberts
order to adjust for univariate outliers and non-normality. Economic growth is measured as a country’s average GDP growth rate over the previous 3 years. Data on economic growth are drawn from
the World Development Indicator database (World Bank, 2012). Size of the manufacturing sector
is measured as the value added from the manufacturing sector as a percentage of GDP. Data on the
size of the manufacturing sector are drawn from the World Development Indicators database
(World Bank, 2012). Urbanization is measured as the proportion of the total population living in
urban areas. Data on urbanization come from the World Population Prospects database (United
Nations, 2008).
In addition to the previous three measures, I include indicators for level of development.
Specifically, I include indicators for whether a country is low-income or lower-middle-income
based on the 2010 World Bank income group classification.8 Low-income countries are defined as
countries with a per capita gross national income (GNI) less than US$1025, while lower-middleincome countries are defined as countries with a GNI per capita greater than US$1025 and less
than US$4035.9
Table 1 provides summary statistics for the dependent and independent variables.
Estimation
The hierarchical structure of panel data violates the basic assumption of case independence for
unbiased estimation with ordinary least squares regression. More importantly, failing to account
for the clustering of observation in country panels increases the likelihood of a false positive in
hypothesis testing. Additionally, a central problem in inference is the potential for omitted variable
bias caused by model misspecification (Halaby, 2004). If these issues are not accounted for, then
the likelihood of bias estimates and standard errors increases (Wooldridge, 2002). In order to estimate unbiased standard errors and parameters, this study utilizes generalized least square (GLS)
models with random and fixed effects and clustered standard errors that are heteroskedasticityconsistent (Rogers, 1993).
The two most common GLS models for panel data are the random-effect model (REM) and
fixed-effect model (FEM). The REM utilizes between-country and within-country variation for
estimating parameters and includes a normally distributed panel-specific error component for
measuring random unobserved country-specific heterogeneity. The FEM only utilizes withincountry variation for estimating parameters because the model includes a vector of panel-specific
intercepts for measuring time-invariant unobserved heterogeneity. Since the REM only includes a
single parameter for unobserved heterogeneity, it is more efficient for than the FEM, but it assumes
that the random panel-specific error component is orthogonal to the observed covariates in the
model. If this assumption is violated, the REM is unbiased, but inconsistent, which makes the FEM
preferable. In order to test this assumption, researchers compare coefficients from the consistent
model (FEM) to coefficients from the efficient model (REM) and determine whether there is a
statistically significant difference (Hausman, 1978). In the analysis, the coefficients of the REMs
are found to be significantly different than the coefficients of FEMs, which suggests that the strict
exogeneity assumption was not met and the FEM is preferable for consistent estimates.
Even though the REMs are inconsistent, they are preferred over FEMs for two reasons. First,
the FEM is incapable of estimating parameters for time-invariant variables because these variables
are perfectly collinear with the panel-specific intercepts. Second, since most of the variation in the
size of the informal economy is between countries rather than within countries, FEMs may be
unreliable (Rabe-Hesketh and Skrondal, 2012: 258).10 However, given the inconsistency of the
REMs, I also estimate the same models with fixed effects as a robustness check.11
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International Journal of Comparative Sociology 54(5-6)
Table 1. Summary statistics.
Variable
Mean
SD
Minimum
Maximum
Size of the informal economy
Trade openness
Foreign capital penetration
FDI rate
Domestic investment
Periphery
Semi-periphery
Urbanization level
Size of manufacturing sector
Unemployment rate
Lower middle income
Low income
Three-year GDP growth rate
Rule of law index
Business freedom index
Size of public sector
28.18
88.30
42.47
.14
21.40
.41
.34
65.49
18.13
7.95
.27
.12
2.43
.55
69.79
15.28
13.90
61.33
86.69
.14
4.44
.49
.47
19.94
6.43
4.98
.45
.33
3.32
.96
12.52
5.07
8.40
15.87
0.68
−.41
10.67
0
0
10.32
2.27
.70
0
0
−15.16
−1.25
39.80
4.48
68.10
456.65
1007.67
1.86
42.54
1
1
100.00
35.01
31.20
1
1
11.88
2.12
100.00
30.50
SD: standard deviation; FDI: foreign direct investment; GDP: gross domestic product.
N = 554.
I test for two other potential problems in panel data analysis: temporal autocorrelation and
groupwise heteroskedasticity. If both conditions are present, standard errors are likely bias and the
likelihood of committing Type 1 or Type 2 errors is increased. Based on a test first-order autocorrelation10 (Wooldridge, 2002) of the full model, I found the data exhibited significant first-order
autocorrelation (F = 39.395, p < .001).12 Next, I test for the presence of groupwise heteroskedasticity, or unequal error variance across countries. Based on a standard test for panel-level heteroskedasticity (Baum, 2001), I found that the residuals exhibited significant variation across countries.
In order to ensure valid inference of the REMs and FEMs, I use robust-clustered standard errors
(Rogers, 1993). Additionally, to account for the potential spatial autocorrelation of countries in the
same geographic area, I include region fixed effects in the model.
Results
The structure of the world economy, trade, investment, and the informal economy
Model 1 in Table 2 shows the unstandardized coefficients of trade openness, foreign capital penetration, and world-system position. The result from Model 1 confirms that, net of international
trade and foreign capital penetration, there is a significant difference in the average size of the
informal economy between core, semi-peripheral, and peripheral countries. The average size of the
informal economy in the core is 9 percent smaller than the average in the periphery and 7.2 percent
smaller than average in the semi-periphery. Based on the results from Model 2, even when controlling for the regulatory environment, internal development processes, and economic globalization,
the average difference in the size of the informal economy between the core and periphery is 13.7
percent, while the average difference between the core and semi-periphery is 8.5 percent. These
findings provide tentative support for the general hypothesis that the informal economy is larger in
peripheral and semi-peripheral countries because formal production in these countries is dependent
on the informal economy for maintaining and reproducing a surplus of low-wage labor.
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Table 2. Random-effect models of the size of the informal economy, 1999–2007.
Trade openness (log)
Foreign capital penetration
(log)
Foreign direct investment
rate
Domestic investment
Peripherya
Semi-peripherya
Periphery × foreign capital
penetration
Semi-periphery × foreign
capital penetration
Periphery × trade
openness
Semi-periphery × trade
openness
Urbanization level
Size of manufacturing
sector
Unemployment rate (log)
Economic growth rate
Lower middle incomeb
Low incomeb
Rule of law index
Business freedom index
Size of public sector
Constant
R2
(1)
(2)
(3)
3.368*** (.622)
.546* (.227)
2.394*** (.678)
.441+ (.265)
2.119***(.579)
.154 (.235)
−.504 (.814)
.423 (.274)
.006 (.316)
.219 (.340)
.363 (.329)
.209 (.329)
.044 (.037)
9.020** (3.055)
7.241* (2.900)
.007 (.031)
13.68** (4.291)
8.472* (3.502)
(4)
.002 (.029)
10.340* (4.186)
5.427 (3.458)
1.009** (.371)
.002 (.029)
5.812 (5.795)
−2.557 (5.571)
.916* (.369)
1.885+ (.982)
2.617* (1.124)
−1.268 (3.307)
.222
.225*** (.053)
.003 (.038)
.223*** (.052)
.006 (.036)
.227*** (.053)
−.006 (.040)
−.615* (.273)
.069*** (.018)
.513 (.312)
1.397 (.885)
−.260 (.491)
−.003 (.008)
.020 (.068)
−12.960* (5.737)
.252
−.640* (.267)
.072*** (.017)
.509 (.311)
1.463+ (.837)
−.462 (.515)
.002 (.008)
.007 (.064)
−9.091+ (5.307)
.260
−.626* (.278)
.068*** (.018)
.526+ (.309)
1.459+ (.864)
−.218 (.517)
.003 (.008)
.023 (.068)
−5.083 (6.332)
.244
N = 554; n = 74; estimates for region fixed effects not shown. Robust-cluster standard errors in parentheses.
aReference group is core countries.
bReference group is high- and upper-middle-income countries.
+p < .05 (one-tail); *p < .05 (two-tail); **p < .01 (two-tail); ***p < .001 (two-tail).
According to results from Model 1, trade openness exerts a positive effect on the size of the
informal economy, where a unit increase in the log of trade openness is associated with an
expansion in the size of the informal economy equal to 3.4 percent of official GDP. In Model 4,
trade openness is interacted with indicators for world-system position to test whether this positive effect varies by whether a country is located in the periphery or semi-periphery. According
to the results, trade openness exerts a positive effect on the size of the informal economy in
peripheral and semi-peripheral countries. Specifically, a unit increase in the log of trade openness is associated with an increase in the size of the informal economy equal to 1.3 percent of
the official GDP in peripheral countries and 2.1 percent of the official GDP in semi-peripheral
countries, controlling for all other variables. In core countries, a unit increase in the log of trade
openness is associated with a decrease in the size of the informal economy equal to 0.5 percent
of official GDP. However, this relationship is not statistically significant. The findings suggest
that trade openness does not affect the size of the informal economy in core countries, which is
consistent with the unequal exchange hypothesis.
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International Journal of Comparative Sociology 54(5-6)
Figure 3. Differences in the effect of trade openness on size of the informal economy.
Source: Data from Schneider et al. (2010) and Snyder and Kick (1979).
GDP: gross domestic product.
Regression slopes from Model 4 in Table 2.
Figure 3 shows the relationship between trade openness and the size of the informal economy
in core, semi-peripheral, and peripheral countries based on the coefficients in Model 4. Trade openness exhibits a negative relationship with the size of the informal economy in core countries, but
this relationship does not exist in the population. Conversely, trade openness shows a positive
relationship with the size of the informal economy in peripheral and semi-peripheral countries. It
is important to note that the interaction effect between periphery and trade openness is marginally
significant (p < .10), which raises some doubt over whether this effect exists in the population.
Overall, Figure 3 illustrates the unequal exchange hypothesis that trade openness is only positively
associated with the size of the informal economy in the periphery and semi-periphery of world
economy.
According to the results in Model 1, foreign capital penetration exerts a positive effect on the
size of the informal economy. For a unit increase in the log of FDI stock, the informal economy is
larger by 0.5 percent of official GDP. In Model 3, this effect was conditioned by world-system
position. Similar to the conditional effect of trade openness, foreign capital penetration exhibits a
positive effect on the size of the informal economy in peripheral and semi-peripheral countries, but
has no effect on the informal economy in core countries. In peripheral countries, a unit increase in
the log of FDI stock was associated with a growth in the informal economy equal to 1.2 percent of
official GDP. In semi-peripheral countries, a unit increase in the log of FDI stock was associated
with a growth in the informal economy equal to 1 percent of official GDP.
Figure 4 shows the relationship between foreign capital penetration and the size of the informal
economy in periphery, semi-periphery, and core countries. In core countries, foreign capital
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Roberts
Figure 4. Differences in the effect of foreign capital penetration on size of the informal economy.
Sources: Data from Schneider et al. (2010) and Snyder and Kick (1979).
GDP: gross domestic product.
Regression slopes from Model 3 in Table 2.
penetration showed little to no association with the size of the informal economy and is statistically
insignificant, which is consistent with the disarticulation hypothesis. In peripheral and semiperipheral countries, foreign capital penetration shows a strong positive association with the size
of the informal economy, and these associations are statistically significant (p < .01). The results
from the interaction model are consistent with the predictions of disarticulation hypothesis, which
states that foreign capital penetration only increases the size of the informal economy in peripheral
and semi-peripheral countries.
Model sensitivity analysis
As previously discussed, the consistency of the random-effects model depends on the assumption that the random country-specific error component is orthogonal to the observed covariates
in the model. Since this assumption is violated, I re-estimate the same models from Table 2
using a fixed-effects estimator. World-system position is omitted from the FEMs in Table 3
because it is perfectly collinear with the country-specific intercepts. Even though the indicators
for world-system position are omitted from the models, the estimates of the interaction effects
are unbiased because the country-specific intercepts account for the effects of the time-invariant variables (Allison, 2009). Models 1–3 in Table 3 confirm the consistency of the direct
effects of international trade and foreign capital penetration as well as the conditional effects of
world-system position on the relationships between international trade, foreign capital penetration, and the size of the informal economy. Based on the results, it appears that the
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.006 (.031)
.012 (.032)
554
74
554
74
479
63
479
63
−8.993 (5.510)
−5.567 (5.428)
N
N
Mahutga and Smith (2011)
−.009 (.031)
−1.952 (6.788)
1.773 (1.757)
.191 (.340)
479
63
−1.319 (4.942)
N
1.348+ (.764)
.515* (.243)
−.020 (.033)
14.47** (4.593)
1.210 (1.553)
1.276** (.427)
.450 (.403)
−.104 (.625)
.634** (.197)
(6)
2.819* (1.158)
−6.465 (5.084)
Y
554
74
(5)
1.917** (.671)
.067 (.235)
4.957*** (1.142)
−.016 (.033)
18.55*** (4.670)
2.766* (1.311)
.587 (.424)
1.915** (.688)
.641** (.235)
(4)
1.947+ (1.056)
.007 (.030)
.338 (.326)
−.579 (.886)
.335 (.267)
(3)
−7.720 (5.484)
−6.538 (5.071)
Y
Y
Snyder and Kick (1979)
.952** (.352)
.897* (.368)
.480 (.331)
2.144** (.643)
.206 (.230)
(2)
.351 (.333)
2.427** (.733)
.359+ (−.203)
(1)
Models include control variables from Model 2 in Table 2; robust-cluster standard errors in parentheses.
+p < .05 (one-tail); *p < .05 (two-tail); **p < .01 (two-tail); ***p < .001 (two-tail).
Trade openness (log)
Foreign capital
penetration (log)
Foreign direct
investment rate
Domestic investment
Periphery
Semi-periphery
Periphery × foreign
capital penetration
Semi-periphery × foreign
capital penetration
Periphery × trade
openness
Semi-periphery × trade
openness
Constant
Country fixed-effects?
World-system position
measure
Observations
Number of countries
Table 3. Model sensitivity analysis.
(7)
1.153*** (.298)
.006 (.029)
6.947+ (4.064)
10.35* (4.708)
1.748*** (.558)
.703+ (.359)
1.655* (.661)
.178 (.236)
(8)
536
72
536
72
−5.227 (4.689)
−3.859 (4.612)
N
N
Clark and Beckfield (2009)
.011 (.031)
7.400+ (4.12)
11.06* (4.894)
.551+ (.311)
1.760** (.675)
.805*** (.209)
−.162 (4.122)
536
72
N
3.772*** (.643)
3.294** (1.168)
−.005 (.028)
5.171 (4.383)
9.022* (4.237)
.574+ (.302)
−1.182* (.590)
.798*** (.197)
(9)
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inconsistency of REMs is primarily due to the association between the random country-specific
error component and the variables in the baseline models.
A second concern of the analysis is the validity of the Snyder and Kick (1979) world-system
position measure (Babones, 2005; Lloyd et al., 2009). I re-estimate the REMs from Table 2 using
two alternative (and more recent) world-system position measures derived from the analysis of
international trade networks (Clark and Beckfield, 2009; Mahutga and Smith, 2011). The results
from Models 4–9 in Table 3 are fairly consistent with the models using the updated Snyder and
Kick (1979) measure. However, it is important to note the differences between the models using
the Snyder and Kick measure and the models using the two alternative measures. First, the direct
and conditional effects of semi-periphery status are smaller, while the effects of periphery status
are larger in the models using the Mahutga and Smith (2011) world-system position measure compared to the models using the Snyder and Kick (1979) measure. Second, the direct effect of periphery status is larger, while the direct and conditional effects of semi-periphery status are smaller in
the models using the Clark and Beckfield (2009) measure compared to the models using the Snyder
and Kick (1979) measure. These differences in effect size are primarily attributable to differences
in the classification of countries and differences in samples.13 The stronger effects with the alternative world-system position measures suggest that trade-based classification are more valid for
approximating structural roles in the world economy. Overall, the results are consistent with fixedeffects estimation and alternative measures of world-system position.
Discussion and conclusion
In this article, I argue that the informal economy is a critical component of peripheral accumulation. Since periphery and semi-periphery countries specialize in labor-intensive and competitive
industries (Chase-Dunn, 1989; Mahutga and Smith, 2011), firms in these countries require a surplus of low-wage labor for profitable production. Specifically, the informal economy is essential
for subsidizing low-value labor-intensive production in the periphery and semi-periphery by providing inexpensive informal labor, a secondary market for inexpensive goods and services for the
reproduction of low-wage labor; and by suppressing the wages of formal workers (Portes, 1978;
Portes and Walton, 1981). Therefore, the informal economy is larger in the periphery and semiperiphery compared to the core.
The findings of the study suggest that cross-national variation in the size of the informal economy is primarily attributable to the structure and processes of the world economy. The substantial
difference in the size of the informal economy between peripheral, semi-peripheral, and core countries provides empirical support for the general argument that informal economy is a key component of peripheral capitalism in the world economy. Additionally, the results show that processes
of world economic exchange are important determinants of the size of the informal economy, but
these effects vary by a country’s location in the structure of the world economy. Since peripheral
and semi-peripheral countries primarily export labor-intensive manufacturing goods and raw materials, international trade induces local firms to utilize low-cost labor to earn a profit. Similarly,
given these countries’ specialization in labor-intensive industry, the inflow of foreign capital into
export-oriented sectors causes the informal economy to grow through the disarticulation of exportoriented sectors from the rest of the local economy.
An important consideration is the significant mean difference between core, periphery, and
semi-periphery countries after accounting for the effects of international trade and foreign capital
penetration. Based on the results, other unobserved processes associated with a country’s structural
location in the world economy appear to affect the size of the informal economy. A limitation of
this study is the inability to account for these unobserved factors. Future research should identify
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International Journal of Comparative Sociology 54(5-6)
what other processes are associated with the reproduction of peripheral accumulation. Additionally,
another limitation of this study is the assumption that informal workers earn less than their formal
counterparts. Given the controversy over the relationship between formal and informal wages
(Maloney, 2004), future research should systematically analyze whether large informal economies
depress wages in the formal economy. This line of research is critical for confirming whether the
informal economy is an essential component for reproducing low-wage regimes in the periphery
and semi-periphery.
In countries located in the core of the world economy, international trade and investment show
no relationship with the size of the informal economy. Unlike peripheral and semi-peripheral countries, production processes in the core are not dependent on the availability of a large surplus of
low-wage labor. Instead, profit accumulation in the core is dependent on the returns to capital and
monopoly rents because core countries tend to specialize in capital-intensive and high-value industries (Chase-Dunn, 1989). Therefore, the development of the informal economy in the core may be
driven by immigration into urban centers and the growth of petty producers. The informal economy provides low-cost goods and services to migrant and impoverished populations in urban centers who may be unable to fully participate in the formal economy (Sassen, 1997, 2001). In order to
test these claims, future research should analyze the effects of international migration, immigration
policy, and economic regulations on the informal economy in core countries.
According to the results, the informal economy in peripheral and semi-peripheral countries is
driven by world economic processes. International trade and foreign investment induce local firms
to utilize goods, services, and labor from the informal economy because peripheral and semiperipheral countries specialize in competitive industries and labor-intensive production. The informal economy ‘subsidizes’ the costs of the formal economy in the periphery and semi-periphery
with inexpensive labor, goods, and services (Portes, 1978). This subsidy is essential for the profits
of local firms and for the reproduction of low-wage informal and formal labor in the periphery and
semi-periphery. Based on the results of this study, I conclude that the informal economy is an integral part of global capitalism because it facilitates profit accumulation in the periphery and
semi-periphery.
As peripheral and semi-peripheral economies are increasingly integrated into the world economy through international trade and investment, the demand for a surplus of low-wage labor will
rise (Carr and Chen, 2002; Phillips, 2011) because these countries are structurally induced to specialize in labor-intensive production processes (Mahutga, 2006; Mahutga and Smith, 2011). Given
this trend, the informal economy will likely grow as local firms become increasingly integrated
into global production networks. Future research needs to re-orient the structural perspective to
account for how the emergence of global production networks impacts the development of the
informal economy (see Phillips, 2011). By studying how local firms in the periphery and semiperiphery are incorporated into global production networks, researchers can better account for the
structural dynamics driving the recent growth of the informal economy in developed and lessdeveloped countries.
Alternatively, based on the results, internal developmental processes partially explain crossnational variation in the size of the informal economy. Specifically, the rapid urbanization of the
periphery and semi-periphery, induced by internal migration from rural to urban centers, appears
to promote the development of the informal economy (Smith, 1987). In general, an increase in the
size of the urban population increases the demand for informal goods and services as well as informal housing (Sassen, 1997, 2001). Since peripheral capitalism is more reliant on low-wage labor,
urbanization should have a greater effect on the informal economy in periphery and semi-periphery
countries. Future research should examine the differences in the relationship between spatial development and the informal economy across the structure of the world economy.
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The persistence and recent expansion of the informal economy during a period of ubiquitous
economic growth raises questions about the relationship between the formal and informal economy. Given the paucity of cross-national studies of the informal economy, the literature on the
informal economy remains mired in disagreement over the determinants of informal economic
development. Based on insights from the world-systems perspective, I show that the cross-national
variation in the size of the informal economy is explained by the structure of the world economy,
international trade, and foreign investment. In particular, the results of the study suggest that the
informal economy is a component of peripheral accumulation and that processes of international
trade and investment are critical drivers of the development of the informal economy in the periphery and semi-periphery. As the globalization of production intensifies and the world economy
becomes increasingly integrated, the informal economy will persist and expand in accordance with
the demand for low-wage labor. Therefore, it is imperative that researchers remain committed to
investigating the informal economy in context of the world economy.
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit
sectors.
Notes
1. This approach is based on the premise that informal economic activity is unobservable because it operates outside of official accounting practices. Therefore, these researchers develop measurement models
using observable indicators of informal economic activity.
2. According to Chase-Dunn (1989), the categorical distinction between the core and periphery is misleading because core countries contain elements of peripheral capitalism. Specifically, rather than representing discrete areas of the world economy, Chase-Dunn (1989) argues that the ‘core/periphery dimension
is a continuous variable between constellations of economic activities …’ (p. 207).
3. The following countries are included in the analysis: Algeria, Argentina, Australia, Austria, Bangladesh,
Belgium, Bolivia, Brazil, Bulgaria, Cambodia, Canada, Chile, China, Costa Rica, Cyprus, Denmark,
Dominican Republic, Egypt, El Salvador, Ethiopia, Finland, France, Germany, Greece, Guatemala,
Honduras, Hong Kong, Hungary, Iceland, India, Indonesia, Iran, Ireland, Italy, Japan, Jordan, Republic
of Korea, Kuwait, Luxembourg, Madagascar, Malaysia, Mauritius, Mexico, Mongolia, Morocco, the
Netherlands, New Zealand, Nicaragua, Norway, Pakistan, Panama, Paraguay, Peru, Philippines, Poland,
Portugal, Romania, Saudi Arabia, Singapore, South Africa, Spain, Sri Lanka, Sweden, Switzerland,
Syrian Arab Republic, Thailand, Trinidad and Tobago, Tunisia, Turkey, the United Kingdom, the United
States, Uruguay, Venezuela, and Vietnam.
4. Empirical investigation of the informal economy is complicated by the intentional concealment of informal activities reducing the availability of reliable and precise estimations of its size (Portes and Haller,
2005). In order to estimate the size of the informal sector, two general methods have been developed
– direct and indirect. Direct measures employ voluntary surveys or tax auditing and other compliance
methods (Schneider and Enste, 2002). Indirect methods utilize macroeconomic indicators to estimate
the size of the informal sector. Four indirect approaches are commonly used: labor market approaches,
the small firm approaches, household consumption approaches, and the macroeconomic discrepancy
approach (Portes and Haller, 2005). The latent variable approach provides the best method for measuring
the informal economy because it assumes the informal economy is unobservable
5. See Schneider et al. (2010: 448–452) for a discussion of their methodology. In order to obtain absolute
measures of the informal economy, instead of relative measures, Schneider utilizes previous estimations
based on the currency-demand approach (Tanzi, 1980, 1983) to approximate the relative measure produced by the latent variable approach.
6. See the appendix in the Heritage Foundation (2009) report on economic freedom for specific
variables.
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7. See Kaufman et al. (2009: Table B5) for a list of concepts and data sources used in constructing the
index.
8. Originally, models included gross domestic product (GDP) per capita; however, this measure was highly
collinear with the level of urbanization and the rule of law index. The correlation between natural logged
GDP per capita and the rule of law index was .81 and the correlation between logged GDP per capita and
percentage of urban population was .82. The variance inflation factor (VIF) for GDP per capita, with the
other independent variables, was too high for reliable analysis (VIF = 6.43). Dropping GDP per capita
reduced the VIF for the rule of law index from 4.33 to 2.98 and reduced the VIF for percentage urban
population from 3.49 to 2.32.
9. The relationship between economic development and world-system position is well-documented.
However, these indicators are not perfectly collinear with world-system position (g = .62).
10. The between-country standard deviation for the size of the informal economy is 14.54, while the withincountry standard deviation is 0.94.
11. In the fixed-effect model, time-invariant variables are perfectly collinear with the country-specific intercepts. Therefore, in Models 1–3 in Table 3, world-system position and regional location are omitted from
the model. Even though these main effects are omitted from the model, the fixed-effects term ensures
unbiased significance tests of the interaction term.
12. XTSERIAL program by Drukker (2003).
13. For example, Brazil, China, Pakistan, and Thailand are classified differently across each measure.
According to the Snyder and Kick (1979) measure, each of these countries is located in the periphery,
while Mahutga and Smith (2011) classify them as semi-peripheral and Clark and Beckfield (2009) classify them as core.
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