Peripheral accumulation in the world economy: A cross-national analysis of the informal economy

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 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 Sassen-Koob, 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 Sassen-Koob 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.

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 small-scale 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; Chase-Dunn, 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 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).

Figure 1.

Trends in informal economic development by income group, 1999–2007.

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, 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; Moser, 1978; Sethuraman, 1976). These observations are fairly consistent with the early ‘over-urbanization 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 decision-making 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 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 labor-intensive 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; Chase-Dunn, 1989; Mahutga, 2006; Mahutga and Smith, 2011). Semi-peripheral countries perform a structurally important role in stabilizing the world economy by specializing in a mix of skill-intensive 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, semi-peripheral, 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.

Figure 2.

Average size of the informal economy by world-system position.

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 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 non-core’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 semi-periphery 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 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 non-normality. 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 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 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-middle-income 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.

Table 1.

Summary statistics.

Variable	Mean	SD	Minimum	Maximum
Size of the informal economy	28.18	13.90	8.40	68.10
Trade openness	88.30	61.33	15.87	456.65
Foreign capital penetration	42.47	86.69	0.68	1007.67
FDI rate	.14	.14	−.41	1.86
Domestic investment	21.40	4.44	10.67	42.54
Periphery	.41	.49	0	1
Semi-periphery	.34	.47	0	1
Urbanization level	65.49	19.94	10.32	100.00
Size of manufacturing sector	18.13	6.43	2.27	35.01
Unemployment rate	7.95	4.98	.70	31.20
Lower middle income	.27	.45	0	1
Low income	.12	.33	0	1
Three-year GDP growth rate	2.43	3.32	−15.16	11.88
Rule of law index	.55	.96	−1.25	2.12
Business freedom index	69.79	12.52	39.80	100.00
Size of public sector	15.28	5.07	4.48	30.50

SD: standard deviation; FDI: foreign direct investment; GDP: gross domestic product.

N = 554.

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 heteroskedasticity-consistent (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 within-country 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

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.

Table 2.

Random-effect models of the size of the informal economy, 1999–2007.

	(1)	(2)	(3)	(4)
Trade openness (log)	3.368*** (.622)	2.394*** (.678)	2.119***(.579)	−.504 (.814)
Foreign capital penetration (log)	.546* (.227)	.441⁺ (.265)	.154 (.235)	.423 (.274)
Foreign direct investment rate	.006 (.316)	.219 (.340)	.363 (.329)	.209 (.329)
Domestic investment	.044 (.037)	.007 (.031)	.002 (.029)	.002 (.029)
Periphery^a	9.020** (3.055)	13.68** (4.291)	10.340* (4.186)	5.812 (5.795)
Semi-periphery^a	7.241* (2.900)	8.472* (3.502)	5.427 (3.458)	−2.557 (5.571)
Periphery × foreign capital penetration			1.009** (.371)
Semi-periphery × foreign capital penetration			.916* (.369)
Periphery × trade openness				1.885⁺ (.982)
Semi-periphery × trade openness				2.617* (1.124)
Urbanization level		.225*** (.053)	.223*** (.052)	.227*** (.053)
Size of manufacturing sector		.003 (.038)	.006 (.036)	−.006 (.040)
Unemployment rate (log)		−.615* (.273)	−.640* (.267)	−.626* (.278)
Economic growth rate		.069*** (.018)	.072*** (.017)	.068*** (.018)
Lower middle income^b		.513 (.312)	.509 (.311)	.526⁺ (.309)
Low income^b		1.397 (.885)	1.463⁺ (.837)	1.459⁺ (.864)
Rule of law index		−.260 (.491)	−.462 (.515)	−.218 (.517)
Business freedom index		−.003 (.008)	.002 (.008)	.003 (.008)
Size of public sector		.020 (.068)	.007 (.064)	.023 (.068)
Constant	−1.268 (3.307)	−12.960* (5.737)	−9.091⁺ (5.307)	−5.083 (6.332)
R ²	.222	.252	.260	.244

N = 554; n = 74; estimates for region fixed effects not shown. Robust-cluster standard errors in parentheses.

Reference group is core countries.

Reference 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.

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.

Figure 3.

Differences in the effect of trade openness on size of the informal 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 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 semi-peripheral 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.

Figure 4.

Differences in the effect of foreign capital penetration on size of the informal economy.

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 inconsistency of REMs is primarily due to the association between the random country-specific error component and the variables in the baseline models.

Table 3.

Model sensitivity analysis.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Trade openness (log)	2.427** (.733)	2.144** (.643)	−.579 (.886)	1.915** (.688)	1.917** (.671)	−.104 (.625)	1.760** (.675)	1.655* (.661)	−1.182* (.590)
Foreign capital penetration (log)	.359⁺ (−.203)	.206 (.230)	.335 (.267)	.641** (.235)	.067 (.235)	.634** (.197)	.805*** (.209)	.178 (.236)	.798*** (.197)
Foreign direct investment rate	.351 (.333)	.480 (.331)	.338 (.326)	.587 (.424)	.450 (.403)	.191 (.340)	.551⁺ (.311)	.703⁺ (.359)	.574⁺ (.302)
Domestic investment	.012 (.032)	.006 (.031)	.007 (.030)	−.016 (.033)	−.020 (.033)	−.009 (.031)	.011 (.031)	.006 (.029)	−.005 (.028)
Periphery				18.55*** (4.670)	14.47** (4.593)	−1.952 (6.788)	7.400⁺ (4.12)	6.947⁺ (4.064)	5.171 (4.383)
Semi-periphery				2.766* (1.311)	1.210 (1.553)	1.773 (1.757)	11.06* (4.894)	10.35* (4.708)	9.022* (4.237)
Periphery × foreign capital penetration		.897* (.368)			1.276** (.427)			1.748*** (.558)
Semi-periphery × foreign capital penetration		.952** (.352)			.515* (.243)			1.153*** (.298)
Periphery × trade openness			1.947⁺ (1.056)			4.957*** (1.142)			3.294** (1.168)
Semi-periphery × trade openness			2.819* (1.158)			1.348⁺ (.764)			3.772*** (.643)
Constant	−7.720 (5.484)	−6.538 (5.071)	−6.465 (5.084)	−8.993 (5.510)	−5.567 (5.428)	−1.319 (4.942)	−5.227 (4.689)	−3.859 (4.612)	−.162 (4.122)
Country fixed-effects?	Y	Y	Y	N	N	N	N	N	N
World-system position measure	Snyder and Kick (1979)			Mahutga and Smith (2011)			Clark and Beckfield (2009)
Observations	554	554	554	479	479	479	536	536	536
Number of countries	74	74	74	63	63	63	72	72	72

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).

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 fixed-effects 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 semi-periphery 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 export-oriented 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 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 semi-peripheral 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 semi-periphery 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 less-developed countries.

Alternatively, based on the results, internal developmental processes partially explain cross-national 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.

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.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Notes

References

Alderson

Nielsen

(1999) Income inequality, development, and dependence: A reconsideration. American Sociological Review 64(4): 606–631.

Allison

(2009) Fixed Effect Regression Models. Thousand Oaks, CA: SAGE.

Amin

(1974) Accumulation on a World Scale. New York: Monthly Review Press.

Arrighi

Drangel

(1986) The stratification of the world economy: An exploration of the semiperipheral zone. Review 10: 9–74.

Babones

(2005) The country-level income structure of the world economy. Journal of World-Systems Research 11(1): 29–55.

Bajada

Schneider

(2009) Unemployment and the shadow economy in the OECD. Revue Economique 60(5): 1033–1067.

Baum

(2001) Residual diagnostics for cross-section time series regression models. Stata Journal 1(1): 101–104.

Beckfield

(2003) Inequality in the world polity: The structure of international organization. American Sociological Review 68: 401–424.

Beer

Boswell

(2002) The resilience of dependency effects in explaining income inequality in the global economy: A cross-national analysis, 1975–1995. Journal of World-Systems Research 8(1): 30–59.

10.

Bienefeld

(1975) The informal sector and peripheral capitalism: The case of Tanzania. IDS Bulletin: Institute of Development Studies 6: 53–73.

11.

Bollen

(1983) World system position, dependency, and democracy: The cross-national evidence. American Sociological Review 48: 468–479.

12.

Bollen

Appold

(1993) National industrial structure and the global system. American Sociological Review 58: 283–301.

13.

Bornschier

Chase-Dunn

(1985) Transnational Corporations and Underdevelopment. New York: Praeger.

14.

Borocz

(2000) Informality rules. East European Politics and Societies 14(2): 348–380.

15.

Bosch

Maloney

(2008) Cyclical movements in unemployment and informality in developing countries. World Bank Policy Research Working Paper 4648. Washington, DC: World Bank.

16.

Bosch

Maloney

(2010) Comparative analysis of labor market dynamics using Markov processes: An application to informality. Labour Economics 17: 621–631.

17.

Caporaso

(1981) Industrialization in the periphery: The evolving global division of labor. International Studies Quarterly 25(3): 347–384.

18.

Carr

Chen

(2002) Globalization and the informal economy: How global trade and investment impact on the working poor. Working Paper on the Informal Economy #1, 1 January. Geneva: ILO.

19.

Castells

Portes

(1989) World underneath: The origins, dynamics, and effects of the informal economy. In: Alejandro

Manuel

Lauren

(eds) The Informal Economy: Studies in Advanced and Less Developed Countries. Baltimore, MD: John Hopkins University Press, pp. 11–37.

20.

Chase-Dunn

(1989) Global Formation: Structures in the World-Economy. Lanham, MD: Rowman & Littlefield.

21.

Chase-Dunn

Rubinson

(1977) Toward a structural perspective on the world-system. Politics & Society 4: 453–476.

22.

Chen

(2009) Informalization of labour markets: Is formalization the answer? In: Shara

(ed.) The Gendered Impacts of Liberalization. New York: Routledge, pp. 191–218.

23.

Chiang

(2004) The dynamics of self-employment and ethnic business ownership among Taiwanese and Australia. International Migration 42(2): 153–173.

24.

Clark

(2010) World-system mobility and economic growth, 1980–2000. Social Forces 86(3): 1123–1151.

25.

Clark

(2012) World-system position and democracy, 1972–2008. International Journal of Comparative Sociology 53(5–6): 367–399.

26.

Clark

Beckfield

(2009) A new trichotomous measure of world-system position using the international trade network. International Journal of Comparative Sociology 50: 5–38.

27.

Davies

Thurlow

(2010) Formal-informal economy linkages and unemployment in South Africa. South African Journal of Economics 78(4): 437–459.

28.

Davis

(2006) Planet of Slums. New York: Verso.

29.

De Janvry

Garramon

(1977) Laws of motion in capital in the center-periphery structure. Review of Radical Political Economics 9: 29–38.

30.

De Santos

(1970) The structure of dependence. American Economic Review 60(2): 231–236.

31.

De Soto

(1989) The Other Path. New York: Harper & Row.

32.

Dixon

Boswell

(1996) Dependency, disarticulation and denominator effects: Another look at foreign capital penetration. American Journal of Sociology 102(2): 543–562.

33.

Djankov

Ramalho

(2009) Employment laws in developing countries. Journal of Comparative Economics 37(1): 3–13.

34.

Drukker

(2003) Testing for serial correlation in linear panel-data models. Stata Journal 3: 168–177.

35.

Emmanuel

(1972) Unequal Exchange. New York: Monthly Review Press.

36.

Evans

Michael

(1980) Dependence, inequality, and the growth of the tertiary: A comparative analysis of less-developed countries. American Sociological Review 45(4): 531–552.

37.

Evans

(1979) Beyond center and periphery: A comment on the contribution of the world-system approach to the study of development. Social Inquiry 49(4): 15–20.

38.

Evans

(1995) The Embedded Autonomy: States & Industrial Transformation. Princeton, NJ: Princeton University Press.

39.

Feenstra

Hanson

(1997) Foreign direct investment and relative wage: Evidence from Mexico’s Maquiladoras. Journal of International Economics 42(3–4): 371–393.

40.

Feige

(1990) Defining and estimating the underground and informal economies: The new institutional economies approach. World Development 18(7): 989–1002.

41.

Firebaugh

(1996) Does foreign capital harm poor nations? New estimates based on Dixon and Boswell’s measures of capital penetration. American Journal of Sociology 102: 563–575.

42.

Frey

Weck-Hanneman

(1984) The hidden economy as an ‘Unobservable’ variable. European Economic Review 26: 33–53.

43.

Gerry

(1987) Developing economies and the informal sector in historical perspective. Annals of the American Academic of Political and Social Science 493: 100–119.

44.

Gibbs

Martin

(1962) Urbanization, technology, and the division of labor: International patterns. American Sociological Review 27: 667–677.

45.

Giles

(1999) Modeling the hidden economy and the tax-gap in New Zealand: A latent variable analysis. Empirical Economics 24: 621–640.

46.

Gugler

(1982) Overurbanization reconsidered. Economic Development and Cultural Change 31(1): 173–189.

47.

Hart

(1973) Informal income opportunities and urban employment in Ghana. Journal of Modern African Studies 11: 61–89.

48.

Halaby

(2004) Panel models in sociological research: Theory into practice. Annual Review of Sociology 30: 507–544.

49.

Hausman

(1978) Specification tests in econometrics. Econometrica 46(6): 1251–1271.

50.

Heintz

Pollin

(2003) Informalization, economic growth and the challenge of creating viable labor standards in developing countries. Political Economy Research Institute Working Paper Series 60. Available at: http://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1048&context=peri_workingpapers

51.

Henry

(1987) The political economy of informal economies. Annals of the American Academy of Political and Social Science 493: 137–153.

52.

Heritage Foundation (2009) Economic Freedom Index. Washington, DC: Heritage Foundation.

53.

Ihrig

Karine

(2004) Lurking in the shadows: The informal sector and government policy. Journal of Development Economics 73(2): 541–557.

54.

Ihrig

Moe

(2001) Tax policies and informal employment: The Asian experience. Asian Economic Journal 15(4): 369–383.

55.

International Labor Organization (ILO) (1972) Employment, Incomes and Inequality: A Strategy for Increasing Productive Employment in Kenya. Geneva: ILO.

56.

International Labor Organization (ILO) (2002) Women and Men in the Informal Economy: A Statistical Picture. Geneva: ILO.

57.

Kaufman

Kaary

Mastruzzi

(2009) Governance matters VIII. World Bank Policy Research Working Paper #4978. Available at: https://openknowledge.worldbank.org/bitstream/handle/10986/4170/WPS4978.pdf?sequence=1

58.

Kaya

(2008) Proletarianization with polarization: Industrialization, globalization, and social class in Turkey, 1980–2005. Research in Social Stratification and Mobility 26: 161–181.

59.

Kesteloot

Meert

(1999) Informal spaces: The geography of informal economic activities in Brussels. International Journal of Urban and Regional Research 23: 232–251.

60.

Kingdon

Knight

(2004) Unemployment in South Africa: The nature of the beast. World Development 32(3): 398–408.

61.

Koo

Smith

(1983) Migration, the urban informal sector, and earnings in the Philippines. Sociological Quarterly 24(2): 219–232.

62.

Kus

(2010) Regulatory governance and the informal economy: Cross-national comparisons. Socio-Economic Review 8: 487–510.

63.

Lee

C-S

Nielsen

Alderson

(2007) Income inequality, global economy, and the state. Social Forces 86(1): 77–112.

64.

Lloyd

Mahutga

De Leeuw

(2009) Looking back and forging ahead: Thirty years of social network research on the world-system. Journal of World-System Research 15(1): 48–85.

65.

Loayza

Rigolini

(2011) Informal employment: Safety net or growth engine? World Development 39(9): 1503–1515.

66.

McGee

(1973) Peasants in the cities: A paradox, paradox, a most ingenious paradox. Human Organization 32(2): 135–142.

67.

Macias

Cazzavillan

(2009) The dynamics of parallel economies: Measuring the informal sector in Mexico. Research in Economics 63: 189–199.

68.

Mahutga

(2006) The persistence of structural inequality? A network analysis of international trade, 1965–2000. Social Forces 84(4): 1863–1889.

69.

Mahutga

Bandelj

(2008) Foreign investment and income inequality: The natural experiment of Central and Eastern Europe. International Journal of Comparative Sociology 29(6): 429–454.

70.

Mahutga

Smith

(2011) Globalization, the structure of the world economy and economic development. Social Science Research 40(1): 257–272.

71.

Mahutga

Kwon

Grainger

(2011) Within-country inequality and the modern world-system: A theoretical reprise and empirical first step. Journal of World-Systems Research 17(2): 279–307.

72.

Maloney

(2004) Informality revisited. World Development 32(7): 1159–1178.

73.

Moser

(1978) Informal sector or petty commodity production: Dualism or dependence in urban development? World Development 6(9–10: 1041–1064.

74.

Nolan

(1983) Status in the world system, income inequality, and economic growth. American Journal of Sociology 83(2): 410–419.

75.

Organisation for Economic Co-operation and Development (OECD) (2009) Is Informal Normal? Paris: OECD.

76.

Petersen

H-G

(1982) Size of the public sector, economic growth, and the informal economy: Development trends in the Federal Republic of Germany. Review of Income and Wealth 28(2): 191–215.

77.

Phillips

(2011) Informality, global production networks, and the dynamics of adverse incorporation. Global Networks 11(3): 380–397.

78.

Portes

(1978) The informal sector and the world economy: Notes on the structure of subsidized labour. Bulletin of the Institute of Development Studies 9: 35–40.

79.

Portes

Centeno

(2006) The informal economy in the shadow of the state. In: Fernández-Kelly

Sheffner

(eds) Out of the Shadows: The Informal Economy and Political Movements in Latin America. University Park, PA: Pennsylvania State University Press, pp. 23–49.

80.

Portes

Haller

(2005) The informal economy. In: Neil

Richard

(eds) The Handbook of Economic Sociology, 2nd edn. Princeton, NJ: Princeton University Press, pp. 403–425.

81.

Portes

Sassen-Koob

(1987) Making it underground: Comparative material on the informal sector in Western market economies. American Journal of Sociology 93(1): 30–61.

82.

Portes

Walton

(1981) Labor, Class, and the International System. New York: Academic Press.

83.

Rabe-Hesketh

Skrondal

(2012) Multilevel and Longitudinal Modeling Using Stata, vol. 1. College Station, TX: Stata Press.

84.

Raijman

Tienda

(2000) Immigrants’ pathways to business ownership: A comparative ethnic perspective. International Migration Review 34(3): 682–706.

85.

Rogers

(1993) Regression standard errors in clustered samples. Stata Technical Bulletin 13: 19–23.

86.

Sassen

(1997) Informalization in advanced market economies. ILO Issues in Development Discussion Paper 20. Available at: http://www.ilo.int/wcmsp5/groups/public/ed_emp/documents/publication/wcms_123590.pdf

87.

Sassen

(2001) The Global City: New York, London, Tokyo. Princeton, NJ: Princeton University Press.

88.

Schneider

(2005) Shadow economies of 145 countries all over the world: What do we really know? European Journal of Political Economy 21: 598–642.

89.

Schneider

Enste

(2002) The Shadow Economy: Theoretical Approaches, Empirical Studies, and Political Implication. Cambridge: Cambridge University Press.

90.

Schneider

Buehn

Montenegro

(2010) New estimates for the shadow economies all over the world. International Economic Journal 21(4): 443–461.

91.

Sethuraman

(1976) The urban informal sector: Concept, measurement, and policy. International Labour Review 114(1): 69–81.

92.

Smith

(1987) Overurbanization reconceptualized: A political economy of the world-system approach. Urban Affairs Review 23: 270–294.

93.

Snyder

Kick

(1979) Structural position in the world system and economic growth, 1955–1970: A multiple-network analysis of transnational interactions. American Journal of Sociology 84(5): 1096–1126.

94.

Standing

(1999) Global Labour Flexibility: Seeking Distributive Justice. New York: St Martin’s Press.

95.

Stokes

Anderson

(1990) Disarticulation and human welfare in less developed countries. American Sociological Review 55(1): 63–74.

96.

Tabak

Crichlow

(eds) (2000) Informalization: Process and Structure. Baltimore, MD: Johns Hopkins University Press.

97.

Tanzi

(1980) The underground economy in the United States: Estimates and implications. Banca Nazionale del Lavoro Quarterly Review 135(4): 427–453.

98.

Tanzi

(1983) The underground economy in the United States: Annual estimates, 1930–1980. IMF Staff Papers 33: 283–305 (published by Palgrave Macmillian).

99.

Tokman

(1978) An exploration into the nature of informal-formal sector relationships. World Development 6(9/10): 1065–1075.

100.

Ulyssea

(2010) Regulation of entry, labor market institutions, and the informal sector. Journal of Development Economics 91: 87–99.

101.

United Nations (2008) World Population Prospects (Online Database). Available at: http://esa.un.org/wpp/Excel-Data/population.htm

102.

United Nations Conference on Trade and Development (UNCTAD) (2009) Foreign Direct Investment Database (Online Database). Available at: http://unctad.org/en/pages/Statistics.aspx

103.

Waldinger

Lapp

(1993) Back to the sweatshop or ahead to the informal sector? International Journal of Urban and Regional Research 17(1): 6–29.

104.

Wallerstein

(1974a) The Modern World-System I: Capitalist Agriculture and the Origins of the European World-Economy in the 16th Century. New York: Academic Press.

105.

Wallerstein

(1974b) The rise and future demise of the world capitalist system: Concepts for comparative analysis. Comparative Studies in Society and History 16: 387–415.

106.

Wallerstein

(1974c) Dependence in an interdependent world: Limited possibilities for transformation in the capitalist world economy. African Studies Review 17(1): 1–26.

107.

Williams

Round

(2008) Retheorizing the nature of informal employment. International Sociology 23(3): 367–388.

108.

Wooldridge

(2002) Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.

109.

World Bank (2009) Worldwide governance indicator (Online database). Available at: http://data.worldbank.org/data-catalog/worldwide-governance-indicators

110.

World Bank (2010) Country and lending groups. Available at: http://data.worldbank.org/about/country-classifications/country-and-lending-groups

111.

World Bank (2012) World Development Indicators (Online Database). Available at: http://data.worldbank.org/data-catalog/world-development-indicators