Chapter 8 How Institutions Shape the Informal Economy

International Monetary Fund

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Keywords:: size of the informal economy; value-added tax; governance variable; informal economy in country; c-efficiency VAT; Informal economy; Tax incidence; Business environment; Emerging and frontier financial markets; Corruption; Global; system GMM estimation

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Abstract

The Global Informal Workforce is a fresh look at the informal economy around the world and its impact on the macroeconomy. The book covers interactions between the informal economy, labor and product markets, gender equality, fiscal institutions and outcomes, social protection, and financial inclusion. Informality is a widespread and persistent phenomenon that affects how fast economies can grow, develop, and provide decent economic opportunities for their populations. The COVID-19 pandemic has helped to uncover the vulnerabilities of the informal workforce.

Introduction

A large body of literature has investigated interrelations between the informal sector and institutions. Yet no consensus has emerged on the exact determinants of or transmission channels through which this association arises. Ongoing work has investigated why the informal economy is large and persistent in many developing countries and what the barriers to formalization are (Loayza and Meza-Cuadra 2018; Afonso, Neves, and Pinto 2020).

One strand of this literature analyzes how the size of the informal economy relates to institutional settings, including taxation, regulatory burdens, corruption, law and order, and governance, as well as how informality reflects and responds to the business cycle—an important aspect in designing policy responses to the current coronavirus disease 2019 (COVID-19) crisis.

A second strand of the literature explores the relationship between informality and institutions in the context of democratic or political environment (Aruoba 2010; Elgin 2010; Teobaldelli and Schneider 2013; Elbahnasawy, Ellis, and Adom 2016). Better institutions and government policies are clearly linked to higher tax revenues and lower informality, with some recent studies finding a negative relationship between measures of institutional quality and the size of the informal economy (Torgler and Schneider 2009; Aruoba 2010; Elgin 2010).Yet limited research shows the direction of causality (Elgin 2010; Mazhar 2015; Elbahnasawy, Ellis, and Adom 2016; Elgin, Elveren, and Bourgeois 2020).

Institutional settings are influenced by the political environment and can foster polices that lead to the development of, or a reduction in, the informal economy. For example, countries with low political turnover have been found to have, on average, a higher tax burden as well as a smaller informal economy (Elgin 2010). This implies that changes in political environment and political stability, even toward more democratic regimes, could be associated with an increase in the size of the informal economy, if the reforms create greater political instability (Elbahnasawy, Ellis, and Adom 2016).

This chapter draws on this previous work to address the question, “Are institutional settings and changes in institutions significantly different in countries with decreasing or low informality, as compared with those with high or increasing informality?” Therefore, the chapter focuses on drawing a link between institutions and their effect on informal activity and identifying the direction of causality using political cycles to control for changes in institutional settings. We explore the literature to analyze how changes in institutional settings lead to changes in the size of the informal sector.

To model our hypothesis and account for endogeneity between institutional variables and the informal economy, we use a dynamic panel data set and several methods to determine the direction of causality between measures of institutional settings as determinants of the size of the informal economy. Given the difficulty in finding credible instruments to account for the considerable endogeneity between the size of the informal economy and institutions, we use the generalized method of moments (GMM) estimator with lags based on the political cycles in the data to identify changes in variables. We undertake two robustness checks comparing alternative specifications to measure the effect of political changes and an alternative measure of the change in the informal economy. In addition, we also compare two methods for measuring the size of the informal economy to check the robustness of our results. We use both the multiple indicators, multiple causes (MIMIC) model developed by Medina and Schneider (2018) and the dynamic general equilibrium (DGE) model from Elgin and Oztunali (2012). We find that, even when political turnover is controlled for, institutional settings affect the size of the informal economy. Institutional indicators such as tax administration, business environment, corruption, and government accountability are significantly related to the size of the informal economy.

The remainder of this chapter is structured as follows. We present stylized facts, review existing work on informality and institutions, and briefly assess how the informal economy is measured. Next, we outline the method and the data used in our analysis, present and describe the results, and conclude with policy recommendations.

Stylized Facts

We briefly present stylized facts on the size of the informal economy over time and how well it correlates to our institutional and political variables. The informal economy includes all economic activities hidden from official authorities for regulatory and institutional reasons and is defined as a percentage of official GDP. Informal economic activities are legal and productive activities that would be included in GDP if recorded (Medina and Schneider 2018). Two methods for measuring the informal economy are presented in Figure 8.1 showing the similarity of the two measures for emerging market and developing economies and for advanced economies (Box 8.1). The figure illustrates that although informality has been on a downward trend since the 1980s, it remains a significant share of the official GDP of emerging market and developing economies.

^{Box 8.1.}

Measuring Informality

By its nature, the informal economy is difficult to measure. Informality has been defined as activity that is legal but hidden from public authorities (Schneider, Buehn, and Montenegro 2010). Various methods are used to derive and measure the informal economy through both surveys and model-based estimates.

The informal economy is typically measured through household, labor force, and firm-based surveys. Surveys can be more robust than model-based estimates, because they do not rely on calibration and assumptions. However, they are infrequently conducted and have varied definitions and methods across countries, limiting their usefulness for cross-country panel analysis.

Model-based estimates use indirect measures that derive the size of the informal economy from various indicators as proxies. Proxies include the currency-demand approach (as in Ardizzi and others 2014); the electricity-demand approach (as in Schneider and Enste 2000); the multiple indicators, multiple causes model (Schneider, Buehn, and Montenegro 2010); and the dynamic general equilibrium model (as in Ihrig and Moe 2004; Elgin and Oztunali 2012; and Orsi, Raggi, and Turino 2014). These measures all have strengths and weaknesses. Source: Author.

To facilitate our analysis, we compare emerging market and developing economies where informality is increasing and decreasing. We define decreasing informality as the informal economy falling as a percentage of official GDP for five consecutive years or longer, to enable us to compare institutional changes pre-ceeding or during these periods. From this, we identify a high-informality group whose informal economy has increased for five or more consecutive years between 1991 and 2017, 64 out of 126 countries. The second group is countries where informality has decreased or remained the same as a percentage of official GDP, 100 out of 164 countries. The decreasing group demonstrates a steady and ongoing reduction in the size of its informal economies, whereas the sustained size of the informal economy is steady or growing across all years in the increasing group (Figure 8.2). Both groups after 2005 show a decrease, which is much steeper for those with more informality to start with.

Selected indicators for emerging market and developing economies with increasing or decreasing informal sectors show better institutional settings are associated with decreasing informal sectors (Figure 8.2). Figure 8.2 shows the sample is split between countries where informality is increasing or decreasing, comparing the correlation between governance indicators of these two groups. Better tax administration measured using C-efficiency value-added tax (VAT) is associated with smaller or decreasing informal sectors, indicating that less efficient or more onerous tax administration may drive entrepreneurs into informal activity. Government accountability also shows a marked difference between economies with increasing informality and those with an informal sector: as informality decreases, government accountability increases, indicating that more transparent government policy and actions may help shrink the informal economy. Property rights are associated with a similar pattern, although the difference is not as pronounced.

Informality and Institutions

Existing evidence on the quality of institutions using various measures highlights that institutions vary considerably among emerging market and developing economies. Acemoglu, Johnson, and Robinson (2005) outline the theoretical and empirical importance of institutions, particularly on the allocation of resources in the economy, highlighting that the disparity in economic development outcomes between developing and advanced economies is related to the varying quality of economic institutions (also see Hall and Jones 1999; Rodrik, Subramanian, and Trebbi 2004; Lederman, Loayza, and Soares 2005). This relationship has been further explored, and the size of the informal economy has been empirically related to institutional determinants such as taxation, burden of regulations, and provision of public services (Friedman and others 2000; Schneider and Enste 2000).

Yet the literature on informality and institutions remains inconclusive: despite the observed correlations, there is no consensus on causal links. One body of work examines the link between high informality and level of development, with higher informality from lower growth and poorer development outcomes caused by lower revenues and investment, inequality, and higher poverty rates, as well as poor governance (Loayza 1996; Docquier, Müller, and Naval 2017). Other work has investigated how institutional settings, policies, and lack of development lead to higher informality in emerging market and developing economies (Dabla-Norris, Gradstein, and Inchauste 2008; Dreher and Schneider 2010; Mazhar 2015; Loayza 2016). Although neither hypothesis is incorrect, Loayza and Meza-Cuadra (2018) note the level of development and poor productivity are not sufficient to explain the cross-country differences in the size of the informal economy we observe. Our chapter therefore focuses on this second argument, drawing a link between institutions and their effect on informal activity to seek a causal link, using political cycles to control for changes in institutional settings.

We focus on institutional settings that encompass policy decisions by governments and investigate how they might affect the degree and the level of formalization of the informal economy. We investigate three areas: (1) fiscal institutions and tax burden; (2) regulatory burden and business environment; and (3) political environment, including corruption.

Fiscal institutions and tax burden are key reasons many join the informal economy; that is, the heavy burden of tax and tax administration drives entrepreneurs involved in legitimate and legal activities into informal operations.

The business environment and regulatory burdens’ effect on informality is similar to that of taxation, whereby the imposition of heavy-handed regulations and unnecessary transaction costs can drive businesses into informal activity. Regulatory burden also includes factors such as property rights and the ability to enforce contracts; the possibility of being unable to enforce contracts or ownership rights in an unbiased court system may also drive activity into the informal sector.

The third group of institutional indicators covers political and governance variables, including corruption, government accountability, and constraints on the executive.¹ These indicators capture the potential for political agents to misuse or misdirect resources toward low-productivity and low-growth activities, such as rent seeking. Political environment includes not only government resources but also political power: corruption at all levels of government can misuse and misdirect resources, creating a greater incentive for workers to join the informal economy.

Fiscal Institutions and Tax Burden

Strong fiscal institutions are an indicator of better fiscal and economic outcomes (Alesina and others 1999; Glaeser and others 2004; Dabla-Norris and others 2010). Better fiscal institutions are associated with effective collection of revenues, stronger management of public expenditures, and budget planning, which provide greater fiscal space and support macroeconomic sustainability and resilience (Deléchat and others 2015). Better-managed fiscal positions that allow for provision of public goods and support economic development, without heavy-handed taxation, have been found to be linked to a smaller informal economy (Loayza 1997; Loayza, Oviedo, and Servén 2006; Kuehn 2007).

Fiscal Management

Poor fiscal management is associated with negative economic consequences, including larger fiscal deficits and, over time, increased debt (Elgin and Uras 2013). It can also crowd out private sector investment, resulting in lower growth. However, developing strong fiscal institutions, including efficient tax systems and strong expenditure management, has been shown to be important in controlling the informal economy (Costa, Garcia-Cintado, and Usabiaga 2019). Institutional settings and the modalities of checks and balances on expenditures; taxation; and the distribution of expenditure toward development objectives, investment, or redistribution of wealth are core functions of government and often mishandled or abused (Cortellese 2015). Disclosure of public expenditure and public involvement in spending decisions can limit tax evasion, fostering improvements in compliance and governance, including accountability of officials (Perry and others 2007).

A large informal sector can complicate fiscal consolidation efforts. A recent study examining fiscal consolidation in Greece after the global financial crisis shows the informal sector can distort the effect of fiscal policy (Dellas and others 2019). The large informal sector in Greece limited the decrease in total output usually associated with large fiscal consolidation; however, this was at the expense of tax revenue collection needed for procyclical policies. The design of tax systems and of fiscal adjustment measures could also be related to the size of the informal sector. Our hypothesis is that countries with strong fiscal institutions should, on average, have smaller informal sectors. We include a measure of the budget balance, an index created by the International Country Risk Guide capturing the likelihood of large deficits or surplus. We expect a negative relationship between budget balance and the size of the informal economy.

Tax Burden

The tax burden is often cited as a strong deterrent against entry into the formal economy or as a reason to remain informal, as discussed in Chapter 9. Although the evidence is mixed on whether the tax burden drives firms out of the formal sector or it is the size of the informal sector that places a higher burden on those who pay, a negative correlation between tax rates and size of the informal economy has been found empirically (Kuehn 2007; Elgin 2010).

Tax administration is often a barrier to informal businesses becoming part of the formal economy. As a result, nonpayment of taxes by large sections of the economy also means that emerging market and developing economies often cannot raise necessary revenues. C-efficiency, a measure of tax collection, is the ratio of actual revenue collection to potential revenue, indicating collection and administrative efficiency (Ueda 2017). Increases in revenue collection in emerging market and developing economies have been driven by increases in C-efficiency rather than increases in tax rates (Keen 2013). Therefore, we expect a higher C-efficiency VAT ratio to be associated with a smaller informal economy. Because VAT is the main source of tax revenues for many emerging market and developing economies (Coady 2018), we include measures of tax administration (C-efficiency VAT) as well as measures of the tax burden (tax revenues as percentage of GDP) to capture this relationship, anticipating a negative relationship with the size of the informal economy.

Regulatory Burden and Business Environment

Informality is more common where the regulatory or administrative burden is larger; informal activity is undertaken to avoid potentially heavy compliance costs. The regulatory burden covers both compliance (including labor, safety laws, and product standards) and bureaucratic rules and procedures that are costly in time or money and can lead to evasion in the informal sector (De Soto 1989; Loayza 1996; Krakowski 2005).

Regulatory Burden

Regulatory burden also covers the effectiveness of governments for which compliance and enforcement of regulations are required. Johnson, Kaufmann, and Zoido-Lobaton (1998) demonstrate that the effectiveness of government and administration of regulations are key determinants of the size of the informal sector. Johnson, Kaufmann, and Zoido-Lobaton (1998) highlight that fewer regulations and a more business-friendly environment are correlated with a smaller informal sector; however, how regulations are administered appears to be as important as the regulations themselves. We include a measure from the World Bank Worldwide Governance Indicators (Kaufmann, Kraay, and Mastruzzi 2010) that captures as an index the quality of regulation across counties, expecting a negative relationship with the size of the informal sector.

Business Environment

Distinct from regulatory burden, the rules that govern the business environment are often more tacit, relying on networks and relationships in addition to formal rules and regulations (Klovienė 2012). Goel and Nelson (2016) note that incentives to remaining in informal sectors (that is, not formalizing) are different from those to joining the informal sector (that is, newly entering). The study finds robust determinants of the informal sector size, including business startup costs, property registration costs, and complexity of bureaucracy. In addition to indicators that measure formal regulation and quality, we also include several indicators, including property rights, private credit, and contract viability, to capture this negative relationship with the size of the informal economy.

Political Environment

Two key strands of the existing literature, salient to our definition of institutional settings, relate to changes in the political environment and governance and corruption. Consensus on their association with informality and the direction of causality is still limited.

Changes in Political Regime

Our key contribution is to evaluate institutional settings and their interactions with political economy and the informal sector. Policy changes resulting from the political process determine institutional settings and thereby affect economic actors’ decisions to participate in the formal or informal sector. “Institutions” can be long-term rules underpinning political and economic activity, but they are not immune to changes resulting from the political cycle—particularly fiscal rules, which can adapt with political direction and budget cycles.

Institutional change is not well explored in relation to the informal economy. Elgin (2015) constructs a theoretical model whereby two political parties can alternate in office and are only able to set economic polices while in office. In Elgin’s model, if the incumbent remains in power and is able to increase taxes to invest in public goods, the formal sector benefits most from public investment. A corollary is that the smaller the informal sector, the greater the political stability.

Elgin (2010) further explores the relation between political turnover and informality: once the political cycle is controlled for, the empirical relation between the tax burden and the informal economy disappears. Therefore, we include political turnover in our model, incorporating a lag in our panel data set to capture average political cycles in emerging market and developing economies. This control allows us to estimate the relation between the informal economy and institutional quality separately from the political cycle.

Governance and Corruption

Governance and corruption have been empirically shown to be significantly associated with the size of the informal economy (Sarte 2000; Choi and Thum 2005; Dreher and Schneider 2010). Corruption can be either complement or substitute to informal sector participation, depending on whether corruption is interpreted as a tax on operations to avoid formal economy taxes and other obligations (complements) or whether firms and individuals join the informal sector to avoid corruption and the cost of bribery (substitutes).

Corruption is broadly defined but varies considerably across countries in how it manifests and who it benefits. Bribes and payments to bureaucrats affect informal sector participants differently than high-level corruption by the executive (Ang 2020). Bribes and payments made to bureaucrats influence informality directly and may deter entry into the formal market to avoid these costly interactions. Corruption by the executive and high-level officials resulting in theft or misallocation of resources may not affect informal sector participants directly but may deter them from paying taxes, and the resulting lack of public services and infrastructure may reduce the incentive to participate in the formal sector. To capture this difference, we use several measures in our analysis to explore whether changes in corruption and governance lead to changes in the informal sector’s size. We include measures of bureaucratic quality, corruption, and government accountability, as well as constraint on the executive, to test this relationship with the size of the informal economy.

Measures of Informality

For robustness, we use the two most widely used measures of informality— MIMIC and DGE models—for comparison in our analysis.

Multiple Indicators, Multiple Causes Model

MIMIC is a structural equation model applied to indirectly measure the size of the informal economy through seven causes and three indicators: fiscal freedom, rule of law, unemployment, trade openness, currency (M0/M1), labor force participation, and size of economy from night lights satellite data.² The informal sector is difficult to measure. This form of estimation is therefore attractive, considering that it uses multiple indicators to capture informal activity. Although earlier versions of MIMIC have been criticized for using GDP growth or GDP per capita growth in estimates, later iterations have overcome this objection by using the independently observed night lights metric as an alternative activity measure (Medina and Schneider 2018). Night lights are a widely used and cited proxy for economic activity, given their country coverage and long time period. However, the indicator has some limitations, including its need for independent survey-based estimates to calibrate model outputs and its sensitivity to model specifications.

Dynamic General Equilibrium Model

DGE models are an increasingly common method to estimate the size of the informal economy (Ihrig and Moe 2004; Aruoba 2010; Elgin and Oztunali 2012). Such models are constructed based on households’ choice to allocate their labor between formal and informal employment, considering the capital households own and the technology of the formal and informal sectors. The model’s time variation is partly determined by comparing the output of the informal to the official formal sector. This model provides a long time series for 1950 through 2016 and large country coverage for panel models. As with MIMIC and other model-based approaches, the DGE relies on assumptions and requires independent observations (usually from surveys) to calibrate.

Figure 8.3 shows measures of the informal sector on a country and year basis and highlights the strong correlation between both measures with limited outliers. As shown in Figures 8.1 and 8.3, there is a strong correlation between the Elgin and Oztunali (2012) and the Medina and Schneider (2018) measures. We use both of these measures, which are available for long time periods, to explore the relationship between the size of the informal economy and institutional settings.

Model and Data

Inherent endogeneity exists between institutions and informality, and finding a suitable and credible instrument is difficult.³ We adopt a dynamic system GMM model (Arellano and Bond 1991; Arellano and Bover 1995; Blundell and Bond 1998) that uses lagged variables to account for changes in institutional quality and the size of the informal economy.

We compare two measures of informality, as outlined in Annex Tables 8.3.1 and 8.3.2. This comparison has the advantage of using both independent measures from Elgin and Oztunali (2012) and Medina and Schneider (2018), which have different theoretical underpinnings, therefore helping us reduce endogeneity. Data on institutional settings are collected from a wide variety of sources, with variables, definitions, and sources included in Annex Tables 8.1.1 and 8.1.2.

Model

The link between institutional settings and the informal economy has been established by many (Schhneider and Enste 2000; Oviedo, Thomas, and Karakurum-Özdemir 2009; Loayza 2016). However, the challenge is to disentangle the direction of causality between institutions and informality. The model to present our estimation is outlined as follows:

\begin{matrix} I n f o r m a l_{i t} = f (I n f o r m a l_{i t - x}, i n s t i t u t i o n a l q u a l i t y_{i t}, c o n t r o l var i a b l e s, μ_{i t}) & (1) \end{matrix}

The dependent variables are the extent of the informal economy in country i (measured as the share of the informal economy in country i’s official GDP); we include institutional quality variables in country i and vectors of control variables that affect the informal economy and institutions, and μ_i represents the error term.

Our hypothesis is that strengthening institutions and improving institutional quality, controlling for the political cycle, reduces the size of the informal economy as firms formalize and engage in more productive formal activity. Our calculations use system GMM with Windmeijer robust standard error correction (Windmeijer 2005). The use of lagged instruments to capture the persistence of the informal economy addresses the endogeneity problem and modeling issues, including unobserved country effects that may create omitted variable bias (Roodman 2009). Equation (1) is estimated both in levels and in first differences for efficient estimates of the model without endogeneity.

As in Elgin (2010) and in Elbahnaswy, Ellis, and Adom (2016), we also consider political turnover, or the political cycle. In the model we assume that any changes in institutional setting are made within or alongside political election cycles, that is, changes in governments and leadership or an incumbent advancing a political agenda. Rather than incorporate an independent variable, we use this premise to integrate the political cycle into our panel, lagging our institutional quality variables by the average length of election cycles in emerging market and developing economies (four years). This controls for political instability and its effect on institutional settings.

Data

In the regressions, we include several control variables, including GDP per capita, inflation, trade restrictions, and measure of human capital. GDP per capita is correlated with economic development, and we expect a negative relationship with informality. Although there is correlation between less-developed economies and larger informal sectors, Loayza and Meza-Cuadra (2018) notes there is not always a one-to-one relationship. Some countries have higher or lower informality than predicted by their development, indicating other determinants of informality.

Trade restrictions are also controlled for, because they indicate a shift toward domestic activity and larger informal sectors as domestic demand increases. Trade restrictions also limit international competition, meaning there is a lower opportunity cost to being informal (Elbahnasawy, Ellis, and Adom 2016). We use an index of trade restrictions that includes tariff and nontariff barriers, trade taxes, and numbers of trade agreements, in which the highest index value denotes the least amount of restrictions, so that we expect a negative relationship with informality.

As a control we include inflation, which is positively correlated with informal economy and an important factor in the interaction between informality and institutions (Aruoba 2010). Koreshkova (2006) and Aruoba (2010) observe quantitatively and theoretically the relationship between tax evasion and inflation, whereby low inflation, increased tax base, and lower informality are observed. Inflation is also a proxy for the quality of macroeconomic management and macroeconomic stability.

Human capital is a measure from Penn World Tables⁴ that combines a measure of average years of schooling with an assumed rate of return to education. A higher share of lower-skilled workers in a country is associated with a larger informal economy (Docquier, Müller, and Naval 2017; Elgin and others 2019). As LaPorta and Shleifer (2008) note, although informality provides employment and wages, the informal sector is associated with fewer worker skills and low productivity compared with the formal sector. We therefore expect a negative relationship with higher informality.

Results

Table 8.1 presents the results of the system GMM estimations for our institutional quality measures. The main results for measures of fiscal and tax burden (columns 2 through 4) show that C-efficiency VAT and risk of budget balance are negative and significant at the 10 percent and 1 percent levels, respectively. This indicates that even when political cycles are controlled for, institutional settings are directly related to the size of the informal economy. However, the size of tax revenues is not significant when the political cycle is controlled for. This interesting result indicates that it may be tax administration, rather than the tax rates or the tax burden, that affects choice to participate in the informal sector. Care, however, should be taken with interpretations of the C-efficiency VAT measure, considering that there are limited observations.

^{Table 8.1.}

System GMM Estimations, Medina and Schneider Informality, 1990–2017

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Table 8.1.}

System GMM Estimations, Medina and Schneider Informality, 1990–2017

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina informal	0.807*** (0.012)	0.722*** (0.027)	0.794*** (0.015)	0.805*** (0.014)	0.766*** (0.014)	0.775*** (0.016)	0.781*** (0.017)	0.807*** (0.012)	0.817*** (0.014)	0.814*** (0.014)	0.782*** (0.017)	0.808*** (0.012)	0.809*** (0.013)
Real GDP per capita	-0.030*** (0.009)	-0.118*** (0.049)	-0.026*** (0.009)	-0.03 7*** (0.009)	-0.039*** (0.009)	-0.056*** (0.012)	-0.049*** (0.013)	-0.030*** (0.009)	-0.030*** (0.009)	-0.028*** (0.009)	-0.046*** (0.013)	0.031*** (0.009)	-0.034*** (0.009)
Trade restrictions	-0.016*** (0.005)	-0.004 (0.015)	-0.014*** (0.006)	-0.009*** (0.005)	0.002 (0.005)	-0.016»» (0.007)	-0.009 (0.008)	-0.017*** (0.005)	-0.012** (0.006)	-0.011** (0.005)	-0.009 (0.008)	-0.014*** (0.005)	-0.013** (0.005)
Inflation	0.108*** (0.034)	0.071 (0.089)	0.089*** (0.040)	0.074*** (0.039)	0.071*** (0.038)	0.122*** (0.045)	0.077 (0.053)	0.110*** (0.034)	0.110*** (0.039)	0.106*** (0.039)	0.088* (0.053)	0.112*** (0.034)	0.103*** (0.035)
Human capital	-2.530*** (0.302)	-1.826*** (1.042)	-2.213*** (0.394)	-2.349*** (0.354)	-1.396*** (0.362)	-2.696*** (0.478)	-2.527*** (0.559)	-2.556*** (0.305)	-2.410*** (0.358)	-2.225*** (0.361)	-2.363*** (0.559)	-2.466*** (0.313)	-2.714*** (0.319)
Fiscal and Tax Burden
C-efficiency VAT		-1.527*** (0.807)
Tax revenues			-0.022 (0.014)
Risk budget balance				-0.134*** (0.025)
Business and Regulatory Environment
Contract viability					-0.373*** -0.038
Property rights						-0.019*** (0.005)
Regulatory quality Private credit							-0.170 (0.217)	-0.002 (0.003)
Political and Legal Environment
ICRG bureaucracy									0.004 (0.071)
Corruption										-0.156*** (0.050)
Rule of law Government integrity											-0.199 (0.242)
Government accountability												-0.218** -0.094
Executive constraint													-0.023 (0.031)
Constant	4.311*** (1.565)	3.125 (2.019)	2.564*** (0.978)	4.134*** (1.478)	3.579*** (1.802)	1.537 (2.088)	3.882*** (1.307)	4.367*** (1.545)	3.715*** (1.298)	3.592*** (1.174)	3.607** (1.452)	4.251*** (1.604)	4.054*** (1.083)
No. of observations	2,501	722	1,883	1,961	1,961	1,760	1,493	2,501	1,961	1,961	1,493	2,397	2,293
No. of countries	100	61	95	84	84	98	100	100	84	84	100	96	95
Year dummies	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
No. of instruments	36	32	44	42	42	37	33	44	42	42	33	44	44
AR(2)p values	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
AR(l)p values	0.874	0.138	0.111	0.558	0.659	0.262	0.282	0.827	0.768	0.774	0.353	0.971	0.914

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Table 8.1.}

System GMM Estimations, Medina and Schneider Informality, 1990–2017

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina informal	0.807*** (0.012)	0.722*** (0.027)	0.794*** (0.015)	0.805*** (0.014)	0.766*** (0.014)	0.775*** (0.016)	0.781*** (0.017)	0.807*** (0.012)	0.817*** (0.014)	0.814*** (0.014)	0.782*** (0.017)	0.808*** (0.012)	0.809*** (0.013)
Real GDP per capita	-0.030*** (0.009)	-0.118*** (0.049)	-0.026*** (0.009)	-0.03 7*** (0.009)	-0.039*** (0.009)	-0.056*** (0.012)	-0.049*** (0.013)	-0.030*** (0.009)	-0.030*** (0.009)	-0.028*** (0.009)	-0.046*** (0.013)	0.031*** (0.009)	-0.034*** (0.009)
Trade restrictions	-0.016*** (0.005)	-0.004 (0.015)	-0.014*** (0.006)	-0.009*** (0.005)	0.002 (0.005)	-0.016»» (0.007)	-0.009 (0.008)	-0.017*** (0.005)	-0.012** (0.006)	-0.011** (0.005)	-0.009 (0.008)	-0.014*** (0.005)	-0.013** (0.005)
Inflation	0.108*** (0.034)	0.071 (0.089)	0.089*** (0.040)	0.074*** (0.039)	0.071*** (0.038)	0.122*** (0.045)	0.077 (0.053)	0.110*** (0.034)	0.110*** (0.039)	0.106*** (0.039)	0.088* (0.053)	0.112*** (0.034)	0.103*** (0.035)
Human capital	-2.530*** (0.302)	-1.826*** (1.042)	-2.213*** (0.394)	-2.349*** (0.354)	-1.396*** (0.362)	-2.696*** (0.478)	-2.527*** (0.559)	-2.556*** (0.305)	-2.410*** (0.358)	-2.225*** (0.361)	-2.363*** (0.559)	-2.466*** (0.313)	-2.714*** (0.319)
Fiscal and Tax Burden
C-efficiency VAT		-1.527*** (0.807)
Tax revenues			-0.022 (0.014)
Risk budget balance				-0.134*** (0.025)
Business and Regulatory Environment
Contract viability					-0.373*** -0.038
Property rights						-0.019*** (0.005)
Regulatory quality Private credit							-0.170 (0.217)	-0.002 (0.003)
Political and Legal Environment
ICRG bureaucracy									0.004 (0.071)
Corruption										-0.156*** (0.050)
Rule of law Government integrity											-0.199 (0.242)
Government accountability												-0.218** -0.094
Executive constraint													-0.023 (0.031)
Constant	4.311*** (1.565)	3.125 (2.019)	2.564*** (0.978)	4.134*** (1.478)	3.579*** (1.802)	1.537 (2.088)	3.882*** (1.307)	4.367*** (1.545)	3.715*** (1.298)	3.592*** (1.174)	3.607** (1.452)	4.251*** (1.604)	4.054*** (1.083)
No. of observations	2,501	722	1,883	1,961	1,961	1,760	1,493	2,501	1,961	1,961	1,493	2,397	2,293
No. of countries	100	61	95	84	84	98	100	100	84	84	100	96	95
Year dummies	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
No. of instruments	36	32	44	42	42	37	33	44	42	42	33	44	44
AR(2)p values	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
AR(l)p values	0.874	0.138	0.111	0.558	0.659	0.262	0.282	0.827	0.768	0.774	0.353	0.971	0.914

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

Institutional quality measures for the business and regulatory environment (columns 5 to 8) show that contract viability and property rights are both negative and significant at a 1 percent level. Regulatory quality and private credit coefficients are both negative but are not significant, indicating that these may be relevant only contemporaneously, rather than for longer term political turnover or as barriers to entering the formal economy.

The institutional quality for political and legal environment (columns 9 to 13) show that corruption and government accountability are negative and significant at the 1 percent and 5 percent levels, respectively. This indicates that higher corruption (Elgin 2010; Dreher and Schneider 2010) and greater government accountability are associated with smaller informal sectors. The results indicate that institutional quality matters even when political turnover is considered, and improvements in institutions reduce the size of the informal economy over time.

As a further robustness check, we use a measure of the informal economy developed by Elgin and Oztunali (2012). The results are in Annex 8.3 and are consistent with those for Medina and Schneider (2018) presented in Tables 8.1 and 8.2.

^{Table 8.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2017

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Table 8.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2017

	1	2	3	4	5	6	7	8	9	10	11	12	13
L Medina informal	3.419*** (0.119)	3.213*** (0.208)	3.579*** (0.131)	3.441*** (0.133)	3.333*** (0.133)	3.546*** (0.129)	3.437*** (0.136)	3.407*** (0.119)	3.453*** (0.132)	3.430*** (0.132)	3.435*** (0.136)	3.342*** (0.122)	3.238*** (0.124)
Real GDP per capita	-0.0352*** (0.00996)	-0.143*** (0.0386)	-0.0395*** (0.0105)	-0.0376*** (0.0109)	-0.0396*** (0.0105)	-0.0404*** (0.0118)	-0.0338*** (0.0110)	-0.0349*** (0.0100)	-0.0378*** (0.0107)	-0.0346*** (0.0104)	-0.0336*** (0.0111)	-0.0496*** (0.0136)	-0.0502*** (0.0138)
Trade restrictions	-0.00836*** (0.00477)	-0.00160 (0.00829)	-0.0123** (0.00528)	-0.0110** (0.00525)	-0.00726 (0.00534)	-0.00936* (0.00521)	-0.00930 (0.00572)	-0.0127** (0.00496)	-0.0110** (0.00524)	-0.0114** (0.00523)	-0.00878 (0.00562)	0.00774 (0.00493)	-0.00837* (0.00502)
Inflation	0.0369 (0.0512)	0.0258 (0.0991)	0.0105 (0.0573)	0.00921 (0.0565)	0.0766 (0.0600)	0.0403 (0.0569)	0.066 (0.0618)	0.0756 (0.0525)	0.0114 (0.0563)	0.00283 (0.0569)	0.0648 (0.0616)	-0.0496 (0.0519)	0.0559 (0.0524)
Human capital	-0.0269 (0.124)	-0.528*** (0.279)	-0.0328 (0.143)	-0.0867 (0.140)	-0.168 (0.142)	-0.0237 (0.133)	-0.0526 (0.143)	-0.0446 (0.126)	-0.126 (0.149)	-0.0719 (0.140)	-0.0692 (0.141)	0.0599 (0.135)	-0.0871 (0.144)
Fiscal and Tax Burden
C-efficiency VAT		-0.208 (0.618)
Tax revenues			-0.0187** (0.00906)
Risk budget balance				-0.0369** (0.0176)
Business and Regulatory Environment
Contract viability					-0.270*** (0.0560)
Property rights						-0.00135 (000408)
Regulatory quality							-0.147 (0.136)
Private credit							-0.00848*** (0.00252)
Political and Legal Environment
ICRG bureaucracy									-0.0858 (0.0917)
Corruption										-0.142* (0.0781)
Rule of law											-0.132 (0.135)
Government accountability											-0.108* (O0652)
Executive constraint													-0.0296 (0.0356)
Constant	-2.206*** (0.304)	-1.952*** (0.561)	-2.201*** (0.331)	-2.370*** (0.414)	-2.616*** (0.365)	-2.318*** (0.348)	-2.147*** (0.408)	-2.185*** (0.303)	-2.281*** (0.354)	-1.976*** (0.376)	-2.106*** (0.397)	-2.179*** (0.305)	-2.022*** (0.312)
No. of observations	2,421	721	2,088	1,947	1,947	2,139	1,776	2,421	1,947	1,947	1,776	2,224	2,049
No. of countries	100	61	95	84	84	99	100	100	84	84	100	96	95

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Table 8.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2017

	1	2	3	4	5	6	7	8	9	10	11	12	13
L Medina informal	3.419*** (0.119)	3.213*** (0.208)	3.579*** (0.131)	3.441*** (0.133)	3.333*** (0.133)	3.546*** (0.129)	3.437*** (0.136)	3.407*** (0.119)	3.453*** (0.132)	3.430*** (0.132)	3.435*** (0.136)	3.342*** (0.122)	3.238*** (0.124)
Real GDP per capita	-0.0352*** (0.00996)	-0.143*** (0.0386)	-0.0395*** (0.0105)	-0.0376*** (0.0109)	-0.0396*** (0.0105)	-0.0404*** (0.0118)	-0.0338*** (0.0110)	-0.0349*** (0.0100)	-0.0378*** (0.0107)	-0.0346*** (0.0104)	-0.0336*** (0.0111)	-0.0496*** (0.0136)	-0.0502*** (0.0138)
Trade restrictions	-0.00836*** (0.00477)	-0.00160 (0.00829)	-0.0123** (0.00528)	-0.0110** (0.00525)	-0.00726 (0.00534)	-0.00936* (0.00521)	-0.00930 (0.00572)	-0.0127** (0.00496)	-0.0110** (0.00524)	-0.0114** (0.00523)	-0.00878 (0.00562)	0.00774 (0.00493)	-0.00837* (0.00502)
Inflation	0.0369 (0.0512)	0.0258 (0.0991)	0.0105 (0.0573)	0.00921 (0.0565)	0.0766 (0.0600)	0.0403 (0.0569)	0.066 (0.0618)	0.0756 (0.0525)	0.0114 (0.0563)	0.00283 (0.0569)	0.0648 (0.0616)	-0.0496 (0.0519)	0.0559 (0.0524)
Human capital	-0.0269 (0.124)	-0.528*** (0.279)	-0.0328 (0.143)	-0.0867 (0.140)	-0.168 (0.142)	-0.0237 (0.133)	-0.0526 (0.143)	-0.0446 (0.126)	-0.126 (0.149)	-0.0719 (0.140)	-0.0692 (0.141)	0.0599 (0.135)	-0.0871 (0.144)
Fiscal and Tax Burden
C-efficiency VAT		-0.208 (0.618)
Tax revenues			-0.0187** (0.00906)
Risk budget balance				-0.0369** (0.0176)
Business and Regulatory Environment
Contract viability					-0.270*** (0.0560)
Property rights						-0.00135 (000408)
Regulatory quality							-0.147 (0.136)
Private credit							-0.00848*** (0.00252)
Political and Legal Environment
ICRG bureaucracy									-0.0858 (0.0917)
Corruption										-0.142* (0.0781)
Rule of law											-0.132 (0.135)
Government accountability											-0.108* (O0652)
Executive constraint													-0.0296 (0.0356)
Constant	-2.206*** (0.304)	-1.952*** (0.561)	-2.201*** (0.331)	-2.370*** (0.414)	-2.616*** (0.365)	-2.318*** (0.348)	-2.147*** (0.408)	-2.185*** (0.303)	-2.281*** (0.354)	-1.976*** (0.376)	-2.106*** (0.397)	-2.179*** (0.305)	-2.022*** (0.312)
No. of observations	2,421	721	2,088	1,947	1,947	2,139	1,776	2,421	1,947	1,947	1,776	2,224	2,049
No. of countries	100	61	95	84	84	99	100	100	84	84	100	96	95

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

Table 8.2 presents results using the random effects logit model, which allows us to identify the marginal effects of institutional change from the probability of change in the size of the informal economy as a percentage of official GDP. We use the same institutional quality variables as in the systems GMM estimation to investigate the effect.

Fiscal and tax burden variables are presented in columns 2 to 4. Tax revenues as a percentage of GDP and the risk of budget balance are both negative and significantly related to the size of the informal economy.

Indicators for business and regulatory environment (columns 5 to 8) show that contract viability and private credit are both negatively and strongly significantly linked to the size of the informal economy. Indicators of political and legal environment (columns 9 to 13) show that corruption and government accountability are negatively and significantly related to the size of the informal economy, although the marginal effect on the size of the informal economy is only significant at the 10 percent level.

We undertake robustness checks to test the validity of our results (Annex 8.2). The first check addresses the strength of including a lag in the panel to account for the effect of political cycles on institutional quality and indicates that our main results are robust. Such a check demonstrates that when government turnover is accounted for, institutional changes still matter for the size of the informal economy. Political and legal environment indicators, other than rule of law, are no longer significant once government turnover is controlled.

Our second check addressed the robustness of the logit model by using an alternative measure of the decrease in the size of the informal economy, using a standard deviation decrease rather than an indicator of the sustained decrease in the informal economy. Results for tax revenues and risk of budget balance are both significant, as are those for regulatory quality. All measures of political and legal environment, except for government accountability, are significant at the 10 percent level or higher, indicating that the marginal changes in these variables are significant for changes in the informal economy.

These two robustness check results do not change our underlying results, confirming that once political changes are controlled for, institutional factors are still important determinants for participation in, and therefore size of, the informal economy.

Conclusion

This chapter links changes in the size of the informal economy to changes in institutional setting and political cycle to capture why the informal economy is so large and persistent in emerging market and developing economies. Following from previous work, we use political turnover to help explain the variation in institutional settings. One of our key contributions is to build the political cycle into our panel to explain changes in institutions and in the size of the informal sector. The analysis shows that, controlling for political cycles, institutions still matter. Indicators of the quality of fiscal institutions, the business and regulatory environment, and the political and legal environment are found to be significant. Our robustness checks help confirm our results that political turnover is relevant to institutions and the size of the informal sector and needs to be controlled for in empirical analysis. Changes in institutional variables also affect informality and are robust to alternative definitions of changes in informality. These results highlight that structural reforms to enhance the quality of fiscal institutions, the business and regulatory environment, and the political and legal environment can all be effective in reducing informality over time.

Annex 8.1. Summary Statistics and Variables

^{Annex Table 8.1.1.}

Summary Statistics

Source: Author. Note: VAT = value-added tax.

^{Annex Table 8.1.1.}

Summary Statistics

Variables	No. of Observations	Mean	Standard Deviation	Minimum	Maximum
Dependent Variables
Medina informal	3,267	35.3	10.9	11.0	70.5
Elgin informal	2,208	37.2	11.4	11.5	80.3
Explanatory Variables
Real GDP per capita	3,346	4.3	7.7	31.3	10,193
Trade restrictions	3,345	48.4	16.2	11.0	92
Inflation	3,326	0.4	4.7	0	5
Human capital	3,158	6.4	2.8	0	13
Government turnover	3,072	8.2	8.7	1	46
C-efficiency VAT	779	0.5	0.2	0	1
Tax revenues	2,744	14.7	7.7	0	53
Risk budget balance	2,574	5.6	1.9	0	10
Contract viability	2,574	1.7	1.4	0	4
Property rights	2,624	39.4	17.7	0	90
Regulatory quality	2,268	-0.4	0.7	-2.6	1.5
Private credit	3,402	28.8	27.3	0	167
Bureaucratic quality	2,574	1.7	0.9	0	4
Corruption	2,574	2.4	1.0	0	5
Rule of law	2,268	-0.5	0.7	-2.2	1.5
Government integrity	2,628	32.2	15.0	0.0	90.0
Government accountability	3,107	0.5	0.8	-1.6	2.0
Executive constraint	2,820	4.5	2.0	1.0	7.0

Source: Author. Note: VAT = value-added tax.

^{Annex Table 8.1.1.}

Summary Statistics

Variables	No. of Observations	Mean	Standard Deviation	Minimum	Maximum
Dependent Variables
Medina informal	3,267	35.3	10.9	11.0	70.5
Elgin informal	2,208	37.2	11.4	11.5	80.3
Explanatory Variables
Real GDP per capita	3,346	4.3	7.7	31.3	10,193
Trade restrictions	3,345	48.4	16.2	11.0	92
Inflation	3,326	0.4	4.7	0	5
Human capital	3,158	6.4	2.8	0	13
Government turnover	3,072	8.2	8.7	1	46
C-efficiency VAT	779	0.5	0.2	0	1
Tax revenues	2,744	14.7	7.7	0	53
Risk budget balance	2,574	5.6	1.9	0	10
Contract viability	2,574	1.7	1.4	0	4
Property rights	2,624	39.4	17.7	0	90
Regulatory quality	2,268	-0.4	0.7	-2.6	1.5
Private credit	3,402	28.8	27.3	0	167
Bureaucratic quality	2,574	1.7	0.9	0	4
Corruption	2,574	2.4	1.0	0	5
Rule of law	2,268	-0.5	0.7	-2.2	1.5
Government integrity	2,628	32.2	15.0	0.0	90.0
Government accountability	3,107	0.5	0.8	-1.6	2.0
Executive constraint	2,820	4.5	2.0	1.0	7.0

Source: Author. Note: VAT = value-added tax.

^{Annex Table 8.1.2.}

Variables and Data Sources

Source: Author. Note: VAT = value-added tax.

^{Annex Table 8.1.2.}

Variables and Data Sources

Variables	Details	Time Span	Source
L. Medina informal	Size of the informal economy as a percent of official GDP, as estimated in Medina and Schneider (2018).	1991–2017	Medina and Schneider (2017)
Elgin informal	Size of the informal economy as a percent of official GDP, as estimated in Elgin and Oztunali (2012).	1960–2008	Elgin and Oztunali (2012)
Real GDP per capita	Growth of real GDP per capita in US dollars.	1960–2017	Elgin and Oztunali 2012
Trade restrictions	Range from 0 to 100, where lower values suggest greater economic restrictions, components, hidden import barriers, mean tariff rate taxes on international trade, and capital controls. Index has been reversed for analysis.	1970–2017	KOF Swiss Economic Institute, the KOF Globalization Index
Inflation	Index based on annual average Consumer Price Index growth; 1 = negative growth, 2 = 0 to 5 percent growth, 3 = 5 to 10 percent growth, 4 = 10 to 15 percent growth, 5 = 15+ percent growth.	1960–2017	IMF, World Economic Outlook database
Human capital	Human capital index based on average years of schooling from Barro and Lee (2013) and assumed rate of return to education based on Mincer equation estimates around the world (Psacharopoulos 1994).	1960–2018	Penn World Tables, 9.1
Government turnover	Number of years the incumbent executive’s political party has held executive office.	1975–2015	World Bank Database of Political Institutions
C-efficiency VAT	C-efficiency VAT ratio is the share of the VAT in GDP divided by the standard VAT rate.	2000–2016	IMF, Fiscal Affairs Department Tax Rate database
Tax revenues	General government tax revenues, based on percent of fiscal year GDP.	1960–2017	IMF, World Economic Outlook Database
Risk budget balance	Central government budget balance (including grants) for a given year in the national currency is expressed as a percentage of the estimated GDP, ranging from high 10 to low –30. The higher the points, the lower the risk.	1990–2016	International Country Risk Guide
Contract viability	Risk of contract modification or cancellations and possible appropriation of assets.	1990–2016	International Country Risk Guide
Property rights	Index 1–100 measuring degree to which a country’s laws protects private property rights and the degree to which its government enforces those laws.	1990–2017	Heritage Foundation
Regulatory quality	Regulatory quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development, on a scale of –2.5 (worst) to 2.5 (best).	1995–2017	World Bank Governance Indicators
Private credit	Domestic credit to private sector as a percent of GDP.	1960–2017	World Bank, World Development Indicators
Bureaucratic quality	Institutional strength and quality of the bureaucracy limits the ability for political interference. The scale ranges from 0 (worst) to 4 (best).	1990–2017	International Country Risk Guide
Corruption	Measure of corruption that distorts the political system. Scale is from 1 (worst) to 6 (best).	1990–2017	International Country Risk Guide
Rule of law	Rule of law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, in particular, the quality of contract enforcement, property rights, the police, and the courts; scale is from –2.5 (worst) to 2.5 (best).	1996–2017	World Bank Governance Indicators
Government integrity	Transparency International’s Corruption Perceptions Index; a 10-point scale in which a score of 10 indicates very little corruption and a score of 0 indicates a very corrupt government.		Heritage Foundation
Government accountability	Measure of government accountability and requirements for justification for its actions and decisions, composite index.	1960–2017	Polity IV Project; Marshall, Gurr, and Jaggers 2017
Executive constraint	Institutionalized constraints on the decision-making powers of the executive branch on a scale of 1 to 7.	1960–2017	Polity IV Project; Marshall, Gurr, and Jaggers 2017

Source: Author. Note: VAT = value-added tax.

^{Annex Table 8.1.2.}

Variables and Data Sources

Variables	Details	Time Span	Source
L. Medina informal	Size of the informal economy as a percent of official GDP, as estimated in Medina and Schneider (2018).	1991–2017	Medina and Schneider (2017)
Elgin informal	Size of the informal economy as a percent of official GDP, as estimated in Elgin and Oztunali (2012).	1960–2008	Elgin and Oztunali (2012)
Real GDP per capita	Growth of real GDP per capita in US dollars.	1960–2017	Elgin and Oztunali 2012
Trade restrictions	Range from 0 to 100, where lower values suggest greater economic restrictions, components, hidden import barriers, mean tariff rate taxes on international trade, and capital controls. Index has been reversed for analysis.	1970–2017	KOF Swiss Economic Institute, the KOF Globalization Index
Inflation	Index based on annual average Consumer Price Index growth; 1 = negative growth, 2 = 0 to 5 percent growth, 3 = 5 to 10 percent growth, 4 = 10 to 15 percent growth, 5 = 15+ percent growth.	1960–2017	IMF, World Economic Outlook database
Human capital	Human capital index based on average years of schooling from Barro and Lee (2013) and assumed rate of return to education based on Mincer equation estimates around the world (Psacharopoulos 1994).	1960–2018	Penn World Tables, 9.1
Government turnover	Number of years the incumbent executive’s political party has held executive office.	1975–2015	World Bank Database of Political Institutions
C-efficiency VAT	C-efficiency VAT ratio is the share of the VAT in GDP divided by the standard VAT rate.	2000–2016	IMF, Fiscal Affairs Department Tax Rate database
Tax revenues	General government tax revenues, based on percent of fiscal year GDP.	1960–2017	IMF, World Economic Outlook Database
Risk budget balance	Central government budget balance (including grants) for a given year in the national currency is expressed as a percentage of the estimated GDP, ranging from high 10 to low –30. The higher the points, the lower the risk.	1990–2016	International Country Risk Guide
Contract viability	Risk of contract modification or cancellations and possible appropriation of assets.	1990–2016	International Country Risk Guide
Property rights	Index 1–100 measuring degree to which a country’s laws protects private property rights and the degree to which its government enforces those laws.	1990–2017	Heritage Foundation
Regulatory quality	Regulatory quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development, on a scale of –2.5 (worst) to 2.5 (best).	1995–2017	World Bank Governance Indicators
Private credit	Domestic credit to private sector as a percent of GDP.	1960–2017	World Bank, World Development Indicators
Bureaucratic quality	Institutional strength and quality of the bureaucracy limits the ability for political interference. The scale ranges from 0 (worst) to 4 (best).	1990–2017	International Country Risk Guide
Corruption	Measure of corruption that distorts the political system. Scale is from 1 (worst) to 6 (best).	1990–2017	International Country Risk Guide
Rule of law	Rule of law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, in particular, the quality of contract enforcement, property rights, the police, and the courts; scale is from –2.5 (worst) to 2.5 (best).	1996–2017	World Bank Governance Indicators
Government integrity	Transparency International’s Corruption Perceptions Index; a 10-point scale in which a score of 10 indicates very little corruption and a score of 0 indicates a very corrupt government.		Heritage Foundation
Government accountability	Measure of government accountability and requirements for justification for its actions and decisions, composite index.	1960–2017	Polity IV Project; Marshall, Gurr, and Jaggers 2017
Executive constraint	Institutionalized constraints on the decision-making powers of the executive branch on a scale of 1 to 7.	1960–2017	Polity IV Project; Marshall, Gurr, and Jaggers 2017

Source: Author. Note: VAT = value-added tax.

Annex 8.2. Robustness Checks

We undertake robustness checks to check the validity of our results. The first, presented in Annex Table 8.2.1, addresses the lag included in the panel to account for the effect of political cycles on institutional quality and informality. For this check, we remove the lag and add an additional variable, as in Elbahnasawy, Ellis, and Adom (2016): a time-varying indicator of political turnover that measures the years since the most recent regime change with the same institutional quality variables used in the systems GMM. This gives robust results for fiscal and tax burdens, and business and regulatory environment indicators. Negative and significant results are reported for C-efficiency VAT, tax revenues, risk of budget balance and contract viability, property rights regulatory quality, and private credit. The results for political and legal environments are not significant, although they give the correct sign. This indicates that our main results are robust, and the implication of including the lag on the basis of political cycles is twofold: when government turnover is accounted for, institutional changes still matter for the size of the informal economy. Additionally, political and legal environment indicators, other than rule of law, are no longer significant once government turnover is controlled.

^{Annex Table 8.2.1.}

System GMM Estimation, Medina and Schneider Informality, 1990–2017: Robustness Check, Alternate Political Turnover Variables with No Election Lag

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.2.1.}

System GMM Estimation, Medina and Schneider Informality, 1990–2017: Robustness Check, Alternate Political Turnover Variables with No Election Lag

	1	2	3	4	5	6	7	8	9	10	11	12	13
L Medina informal	0.778*** (0.014)	0.652*** (0.031)	0.763*** (0.015)	0.780*** (0.015)	0.786*** (0.015)	0.755*** (0.015)	0.780*** (0.017)	0.784*** (0.014)	0.783*** (0.015)	0.784*** (0.015)	0.771*** (0.017)	0.778*** (0.014)	0.778*** (0.014)
Real GDP per capita	-0.026*** (0.010)	-0.203*** (0.050)	-0.023** (0.010)	-0.020** (0.010)	-0.023** (0.010)	-0.041*** (0.012)	-0.034*** (0.012)	-0.027*** (0.010)	-0.024** (0.010)	-0.024** (0.010)	-0.029** (0.012)	-0.026*** (0.010)	-0.026*** (0.010)
Trade restrictions	-0.026*** (0.005)	-0.034** (0.015)	-0.029*** (0.006)	-0.020*** (0.006)	-0.018*** (0.006)	-0.029*** (0.006)	-0.033*** (0.007)	-0.028*** (0.005)	-0.021*** (0.006)	-0.022*** (0.006)	-0.037*** (0.007)	-0.025*** (0.005)	-0.027*** (0.005)
Inflation	0.087** -0.037	0.033 (0.074)	0.072* (0.040)	0.064 (0.040)	0.044 (0.042)	0.114*** (0.041)	0.121*** (0.045)	0.102*** (0.037)	0.066 (0.040)	0.069* (0.040)	0.112** (0.044)	0.086** (0.037)	0.089** (0.037)
Human capital	-2.466*** (0.358)	-1.715*** (1.175)	-2.335*** (0.423)	-2.519*** (0.378)	-2.125*** (0.416)	-2.139*** (0.444)	-1.957*** (0.518)	-2.589*** (0.360)	-2.572*** (0.384)	-2.566*** (0.392)	-2.245*** (0.515)	-2.466*** (0.358)	-2.431*** (0.359)
Government turnover	-0.081*** (0.030)	-0.167* (0.100)	-0.071** (0.034)	-0.066* (0.034)	-0.064* (0.034)	-0.074* (0.038)	-0.101** (0.044)	-0.071** (0.030)	-0.071** (0.034)	-0.070** (0.034)	-0.062 (0.044)	0.064* (0.036)	-0.134*** (0.048)
Fiscal and Tax Burden
C-efficiency VAT		-3.481*** (0.791)
Tax revenues			-0.072*** (0.015)
Risk budget balance				-0.072*** (0.028)
Business and Regulatory Environment
Contract viability					-0.094** (0.040)
Property rights						-0.021*** (0.005)
Regulatory quality							-0.762*** (0.212)
Private credit								-0.008*** (0.003)
Political and Legal Environment
ICRG bureaucracy									-0.063 (0.095)
Corruption										-0.020 (0.059)
Rule of law											-1.435*** (0.232)
Government accountability											-0.149 (0.176)
Executive constraint													-0.088 (0.063)
Constant	-2.018*** (0.290)	-3.526*** (0.794)	-2.152*** (0.338)	-1.841*** (0.423)	-2.004*** (0.324)	-2.552*** (0.366)	-1.000** (0.427)	-2.022*** (0.290)	-2.428*** (0.355)	-3.426*** (0.434)	-1.066** (0.435)	-1.967*** (0.299)	-1.903*** (0.304)
No. of observations	2,171	709	1,787	1,854	1,854	1,836	1,558	2,171	1,854	1,854	1,558	2,171	2,171
No. of countries	95	61	90	81	81	94	95	95	81	81	95	95	95
Year dummies	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
No. of instruments	45	38	48	48	48	45	41	48	48	48	41	48	45
AR(2) p values	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
AR(1)p values	0.545	0.995	0.159	0.495	0.493	0.485	0.018	0.523	0.474	0.475	0.015	0.580	0.545
Hansen p values	0.527	0.905	0.761	0.167	0.176	0.134	0.481	0.879	0.218	0.203	0.380	0.845	0.527

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.2.1.}

System GMM Estimation, Medina and Schneider Informality, 1990–2017: Robustness Check, Alternate Political Turnover Variables with No Election Lag

	1	2	3	4	5	6	7	8	9	10	11	12	13
L Medina informal	0.778*** (0.014)	0.652*** (0.031)	0.763*** (0.015)	0.780*** (0.015)	0.786*** (0.015)	0.755*** (0.015)	0.780*** (0.017)	0.784*** (0.014)	0.783*** (0.015)	0.784*** (0.015)	0.771*** (0.017)	0.778*** (0.014)	0.778*** (0.014)
Real GDP per capita	-0.026*** (0.010)	-0.203*** (0.050)	-0.023** (0.010)	-0.020** (0.010)	-0.023** (0.010)	-0.041*** (0.012)	-0.034*** (0.012)	-0.027*** (0.010)	-0.024** (0.010)	-0.024** (0.010)	-0.029** (0.012)	-0.026*** (0.010)	-0.026*** (0.010)
Trade restrictions	-0.026*** (0.005)	-0.034** (0.015)	-0.029*** (0.006)	-0.020*** (0.006)	-0.018*** (0.006)	-0.029*** (0.006)	-0.033*** (0.007)	-0.028*** (0.005)	-0.021*** (0.006)	-0.022*** (0.006)	-0.037*** (0.007)	-0.025*** (0.005)	-0.027*** (0.005)
Inflation	0.087** -0.037	0.033 (0.074)	0.072* (0.040)	0.064 (0.040)	0.044 (0.042)	0.114*** (0.041)	0.121*** (0.045)	0.102*** (0.037)	0.066 (0.040)	0.069* (0.040)	0.112** (0.044)	0.086** (0.037)	0.089** (0.037)
Human capital	-2.466*** (0.358)	-1.715*** (1.175)	-2.335*** (0.423)	-2.519*** (0.378)	-2.125*** (0.416)	-2.139*** (0.444)	-1.957*** (0.518)	-2.589*** (0.360)	-2.572*** (0.384)	-2.566*** (0.392)	-2.245*** (0.515)	-2.466*** (0.358)	-2.431*** (0.359)
Government turnover	-0.081*** (0.030)	-0.167* (0.100)	-0.071** (0.034)	-0.066* (0.034)	-0.064* (0.034)	-0.074* (0.038)	-0.101** (0.044)	-0.071** (0.030)	-0.071** (0.034)	-0.070** (0.034)	-0.062 (0.044)	0.064* (0.036)	-0.134*** (0.048)
Fiscal and Tax Burden
C-efficiency VAT		-3.481*** (0.791)
Tax revenues			-0.072*** (0.015)
Risk budget balance				-0.072*** (0.028)
Business and Regulatory Environment
Contract viability					-0.094** (0.040)
Property rights						-0.021*** (0.005)
Regulatory quality							-0.762*** (0.212)
Private credit								-0.008*** (0.003)
Political and Legal Environment
ICRG bureaucracy									-0.063 (0.095)
Corruption										-0.020 (0.059)
Rule of law											-1.435*** (0.232)
Government accountability											-0.149 (0.176)
Executive constraint													-0.088 (0.063)
Constant	-2.018*** (0.290)	-3.526*** (0.794)	-2.152*** (0.338)	-1.841*** (0.423)	-2.004*** (0.324)	-2.552*** (0.366)	-1.000** (0.427)	-2.022*** (0.290)	-2.428*** (0.355)	-3.426*** (0.434)	-1.066** (0.435)	-1.967*** (0.299)	-1.903*** (0.304)
No. of observations	2,171	709	1,787	1,854	1,854	1,836	1,558	2,171	1,854	1,854	1,558	2,171	2,171
No. of countries	95	61	90	81	81	94	95	95	81	81	95	95	95
Year dummies	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
No. of instruments	45	38	48	48	48	45	41	48	48	48	41	48	45
AR(2) p values	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
AR(1)p values	0.545	0.995	0.159	0.495	0.493	0.485	0.018	0.523	0.474	0.475	0.015	0.580	0.545
Hansen p values	0.527	0.905	0.761	0.167	0.176	0.134	0.481	0.879	0.218	0.203	0.380	0.845	0.527

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

The second check, presented in Annex Table 8.2.2, verifies the robustness of the logit test by using an alternative measure of the decrease in the size of the informal economy. In this model, rather than using an indicator of the sustained reduction of the informal economy, we use the standard deviation decrease in the informal economy away from a five-year average (for example, 2005–09 or 2010–15). The purpose is to capture a “natural rate” of informal activity. Advanced economies with the best institutions still record an informal economy averaging 16 percent of official GDP (Medina and Schneider 2018), indicating that although informal activities can be minimized, they do not disappear at high levels of development.

^{Annex Table 8.2.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2017: Robustness Check, Alternative Dependent Variable Change in Informality

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.2.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2017: Robustness Check, Alternative Dependent Variable Change in Informality

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina informal	2.959*** (0.271)	5.984*** (0.383)	2.940*** (0.298)	2.902*** (0.314)	2.932*** (0.316)	2.516*** (0.262)	3.027*** (0.381)	2.956*** (0.273)	2.921*** (0.316)	2.946*** (0.313)	2.947*** (0.372)	2.931*** (0.279)	2.785*** (0.293)
Real GDP per capita	-0.273*** (0.0772)	-0.126* (0.0701)	-0.328*** (0.0896)	-0.327*** (0.0913)	-0.347*** (0.0943)	-0.323*** (0.103)	-0.388*** (0.121)	-0.277*** (0.0781)	-0.348*** (0.0960)	-0.337*** (0.0926)	-0.415*** (0.128)	-0.289*** (0.0944)	-0.303*** (0.0980)
Trade restrictions	-0.0320* (0.0177)	-0.00396 (0.0155)	-0.0276 (0.0191)	-0.0233 (0.0209)	-0.0226 (0.0213)	-0.0336* (0.0193)	-0.0585** (0.0238)	-0.0337* (0.0184)	-0.0193 (0.0201)	-0.0317 (0.0202)	-0.0551** (0.0239)	-0.0319* (0.0185)	-0.0324* (0.0197)
Inflation	0.162 (0.113)	0.132 (0.174)	0.141 (0.120)	0.248* (0.135)	0.276* (0.143)	0.198 (0.124)	0.219 (0.143)	0.157 (0.115)	0.204 (0.132)	0.19 (0.134)	0.290** (0.148)	-0.177 (0.116)	0.212* (0.121)
Human capital	-0.838 (0.697)	-0.0166 (0.513)	-0.882 (0.766)	-0.646 (0.842)	-1.245 (0.977)	-0.0365 (0.707)	-0.614 (0.937)	-0.826 (0.701)	-0.788 (0.795)	-0.415 (0.825)	-0.423 (0.913)	0.388 (0.786)	-0.254 (0.843)
Fiscal and Tax Burden
C-efficiency VAT		-0.927 (1.056)
Tax revenues			-0.358** (0.153)
Risk budget balance				-0.0162* (0.00943)
Business and Regulatory Environment
Contract viability					-0.151 (0.134)
Property rights						-0.00641 (0.0118)
Regulatory quality							-2.133*** (0.566)
Private credit								0.00371 (0.0112)
Political and Legal Environment
ICRG bureaucracy									-0.841*** (0.311)
Corruption										-0.381* (0.231)
Rule of law											-3.687*** (0.639)
Government accountability												0.0934 (0.346)
Executive constraint													-0.348* (0.211)
Constant	0.0526 (1.469)	-2.095* (1.099)	0.613 (1.466)	1.400 (1.864)	-0.359 (1.948)	1.862 (1.345)	4.391” (2.025)	0.0466 (1.475)	1.361 (1.652)	2.079 (1.920)	3.140 (1.992)	0.993 (1.541)	2.420 (1.645)
No. of observations	2,503	721	2,129	2,016	2,016	2,139	1,776	2,503	2,016	2,016	1,776	2,302	2,120
No. of countries	100	61	95	84	84	99	100	100	84	84	100	96	95

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.2.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2017: Robustness Check, Alternative Dependent Variable Change in Informality

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina informal	2.959*** (0.271)	5.984*** (0.383)	2.940*** (0.298)	2.902*** (0.314)	2.932*** (0.316)	2.516*** (0.262)	3.027*** (0.381)	2.956*** (0.273)	2.921*** (0.316)	2.946*** (0.313)	2.947*** (0.372)	2.931*** (0.279)	2.785*** (0.293)
Real GDP per capita	-0.273*** (0.0772)	-0.126* (0.0701)	-0.328*** (0.0896)	-0.327*** (0.0913)	-0.347*** (0.0943)	-0.323*** (0.103)	-0.388*** (0.121)	-0.277*** (0.0781)	-0.348*** (0.0960)	-0.337*** (0.0926)	-0.415*** (0.128)	-0.289*** (0.0944)	-0.303*** (0.0980)
Trade restrictions	-0.0320* (0.0177)	-0.00396 (0.0155)	-0.0276 (0.0191)	-0.0233 (0.0209)	-0.0226 (0.0213)	-0.0336* (0.0193)	-0.0585** (0.0238)	-0.0337* (0.0184)	-0.0193 (0.0201)	-0.0317 (0.0202)	-0.0551** (0.0239)	-0.0319* (0.0185)	-0.0324* (0.0197)
Inflation	0.162 (0.113)	0.132 (0.174)	0.141 (0.120)	0.248* (0.135)	0.276* (0.143)	0.198 (0.124)	0.219 (0.143)	0.157 (0.115)	0.204 (0.132)	0.19 (0.134)	0.290** (0.148)	-0.177 (0.116)	0.212* (0.121)
Human capital	-0.838 (0.697)	-0.0166 (0.513)	-0.882 (0.766)	-0.646 (0.842)	-1.245 (0.977)	-0.0365 (0.707)	-0.614 (0.937)	-0.826 (0.701)	-0.788 (0.795)	-0.415 (0.825)	-0.423 (0.913)	0.388 (0.786)	-0.254 (0.843)
Fiscal and Tax Burden
C-efficiency VAT		-0.927 (1.056)
Tax revenues			-0.358** (0.153)
Risk budget balance				-0.0162* (0.00943)
Business and Regulatory Environment
Contract viability					-0.151 (0.134)
Property rights						-0.00641 (0.0118)
Regulatory quality							-2.133*** (0.566)
Private credit								0.00371 (0.0112)
Political and Legal Environment
ICRG bureaucracy									-0.841*** (0.311)
Corruption										-0.381* (0.231)
Rule of law											-3.687*** (0.639)
Government accountability												0.0934 (0.346)
Executive constraint													-0.348* (0.211)
Constant	0.0526 (1.469)	-2.095* (1.099)	0.613 (1.466)	1.400 (1.864)	-0.359 (1.948)	1.862 (1.345)	4.391” (2.025)	0.0466 (1.475)	1.361 (1.652)	2.079 (1.920)	3.140 (1.992)	0.993 (1.541)	2.420 (1.645)
No. of observations	2,503	721	2,129	2,016	2,016	2,139	1,776	2,503	2,016	2,016	1,776	2,302	2,120
No. of countries	100	61	95	84	84	99	100	100	84	84	100	96	95

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

We use standard deviations away from the emerging market and developing economy average instead of a growth measure to capture the change for the logit. Standard deviations above or below the average indicate a growing or shrinking informal economy. The results are presented in Annex Table 8.2.2. Both tax revenues and risk of budget balance are significant, as is regulatory quality, based on these measures. All measures of political and legal environment are significant at the 10 percent level or higher, indicating that the marginal changes in these variables are significant for changes in the informal economy. These two robustness check results do not change our underlying results, confirming that once political changes are controlled for, institutional factors are still important determinants for participation in, and therefore size of, the informal economy.

Annex 8.3. Alternative Results Using Elgin and Oztunali (2012)

^{Annex Table 8.3.1.}

System GMM Estimation, Elgin and Oztunali Informality, 1990–2008

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.3.1.}

System GMM Estimation, Elgin and Oztunali Informality, 1990–2008

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Elgin informal	0.958*** (0.007)	1.088** (0.030)	* 0.967*** (0.011)	0.946*** (0.010)	0.936*** (0.010)	0.965*** (0.016)	0.961*** (0.018)	0.964*** (0.007)	0.944*** (0.010)	0.946*** (0.010)	0.961*** (0.018)	0.961*** (0.007)	0.958*** (0.007)
Real GDP per capita	-0.001 (0.000)	0.004* (0.002)	0.000 (0.001)	-0.001 (0.001)	0.000 (0.001)	-0.003*** (0.001)	-0.003 (0.002)	-0.001 (0.000)	-0.001 (0.001)	-0.001 (0.001)	-0.003 (0.002)	0.000 (0.001)	0.000 (0.000)
Trade restrictions	-0.005** (0.002)	0.006 (0.009)	-0.004 (0.003)	-0.003 (0.003)	-0.001 (0.003)	-0.005 (0.004)	-0.005 (0.006)	-0.007*** (0.002)	-0.004 (0.003)	-0.004 (0.003)	-0.005 (0.006)	-0.004 (0.002)	-0.002 (0.002)
Inflation	0.036** (0.014)	-0.057 (0.040)	0.040** (0.017)	0.019 (0.018)	0.020 (0.017)	0.015 (0.023)	0.030 (0.030)	0.043*** (0.014)	0.027 (0.017)	0.028 (0.017)	0.032 (0.030)	0.037*** (0.014)	0.021 (0.013)
Human capital	-0.600*** (0.146)	-3.244** (0.799)	* -0.762*** (0.209)	-0.615*** (0.207)	-0.067 (0.218)	-0.780** (0.355)	-1.929*** (0.432)	-0.618*** (0.145)	-0.788*** (0.201)	-0.792*** (0.205)	-1.908*** (0.430)	-0.577*** (0.162)	-0.808*** (0.141)
Fiscal and Tax Burden
C-efficiency VAT		-0.533 (0.513)
Tax revenues			-0.016** (0.008)
Risk budget balance				-0.032*** (0.012)
Business and Regulatory Environment
Contract viability					-0.110*** (0.015)
Property rights						0.008*** (0.002)
Regulatory quality							-0.143 (0.124)
Private credit								0.006*** (0.001)
Political and Legal Environment
ICRG bureaucracy									-0.028 (0.028)
Corruption										-0.010 (0.022)
Rule of law											-0.151 (0.152)
Government accountability												-0.093** (0.039)
Executive constraint													-0.023** (0.011)
Constant	2.583*** (0.422)	3.645 (2.287)	2.676*** (0.601)	3.223*** (0.602)	2.254*** (0.608)	2.432** (1.070)	5.232*** (1.204)	2.308*** (0.424)	3.488*** (0.616)	3.422*** (0.619)	5.150*** (1.199)	2.399*** (0.449)	2.994*** (0.411)
No. of observations	1,625	219	1,049	1,226	1,226	907	602	1,625	1,226	1,226	602	1,557	1,481
No. of countries	101	55	95	85	85	98	101	101	85	85	101	97	96
Year dummies	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
No. of instruments	27	23	35	33	33	28	24	35	33	33	24	35	35
AR(2) p values	0.0631	0.747	0.0358	0.0552	0.0758	0.00271	0.488	0.0418	0.0696	0.0639	0.457	0.0545	0.00118
AR(1)p values	0.907	0.968	0.225	0.880	0.895	0.257	0.892	0.873	0.864	0.893	0.880	0.904	0.120
Hansen p values	0.416	0.331	0.426	0.723	0.736	0.182	0.244	0.059	0.298	0.784	0.902	0.472	0.565

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.3.1.}

System GMM Estimation, Elgin and Oztunali Informality, 1990–2008

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Elgin informal	0.958*** (0.007)	1.088** (0.030)	* 0.967*** (0.011)	0.946*** (0.010)	0.936*** (0.010)	0.965*** (0.016)	0.961*** (0.018)	0.964*** (0.007)	0.944*** (0.010)	0.946*** (0.010)	0.961*** (0.018)	0.961*** (0.007)	0.958*** (0.007)
Real GDP per capita	-0.001 (0.000)	0.004* (0.002)	0.000 (0.001)	-0.001 (0.001)	0.000 (0.001)	-0.003*** (0.001)	-0.003 (0.002)	-0.001 (0.000)	-0.001 (0.001)	-0.001 (0.001)	-0.003 (0.002)	0.000 (0.001)	0.000 (0.000)
Trade restrictions	-0.005** (0.002)	0.006 (0.009)	-0.004 (0.003)	-0.003 (0.003)	-0.001 (0.003)	-0.005 (0.004)	-0.005 (0.006)	-0.007*** (0.002)	-0.004 (0.003)	-0.004 (0.003)	-0.005 (0.006)	-0.004 (0.002)	-0.002 (0.002)
Inflation	0.036** (0.014)	-0.057 (0.040)	0.040** (0.017)	0.019 (0.018)	0.020 (0.017)	0.015 (0.023)	0.030 (0.030)	0.043*** (0.014)	0.027 (0.017)	0.028 (0.017)	0.032 (0.030)	0.037*** (0.014)	0.021 (0.013)
Human capital	-0.600*** (0.146)	-3.244** (0.799)	* -0.762*** (0.209)	-0.615*** (0.207)	-0.067 (0.218)	-0.780** (0.355)	-1.929*** (0.432)	-0.618*** (0.145)	-0.788*** (0.201)	-0.792*** (0.205)	-1.908*** (0.430)	-0.577*** (0.162)	-0.808*** (0.141)
Fiscal and Tax Burden
C-efficiency VAT		-0.533 (0.513)
Tax revenues			-0.016** (0.008)
Risk budget balance				-0.032*** (0.012)
Business and Regulatory Environment
Contract viability					-0.110*** (0.015)
Property rights						0.008*** (0.002)
Regulatory quality							-0.143 (0.124)
Private credit								0.006*** (0.001)
Political and Legal Environment
ICRG bureaucracy									-0.028 (0.028)
Corruption										-0.010 (0.022)
Rule of law											-0.151 (0.152)
Government accountability												-0.093** (0.039)
Executive constraint													-0.023** (0.011)
Constant	2.583*** (0.422)	3.645 (2.287)	2.676*** (0.601)	3.223*** (0.602)	2.254*** (0.608)	2.432** (1.070)	5.232*** (1.204)	2.308*** (0.424)	3.488*** (0.616)	3.422*** (0.619)	5.150*** (1.199)	2.399*** (0.449)	2.994*** (0.411)
No. of observations	1,625	219	1,049	1,226	1,226	907	602	1,625	1,226	1,226	602	1,557	1,481
No. of countries	101	55	95	85	85	98	101	101	85	85	101	97	96
Year dummies	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
No. of instruments	27	23	35	33	33	28	24	35	33	33	24	35	35
AR(2) p values	0.0631	0.747	0.0358	0.0552	0.0758	0.00271	0.488	0.0418	0.0696	0.0639	0.457	0.0545	0.00118
AR(1)p values	0.907	0.968	0.225	0.880	0.895	0.257	0.892	0.873	0.864	0.893	0.880	0.904	0.120
Hansen p values	0.416	0.331	0.426	0.723	0.736	0.182	0.244	0.059	0.298	0.784	0.902	0.472	0.565

Source: Author. Note: Standard errors appear in parentheses. GMM = generalized method of moments; ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.3.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2008

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.3.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2008

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina Informal	4.288*** (0.173)	5.368*** (0.552)	4.210*** (0.193)	4.190*** (0.185)	4.194*** (0.191)	4.094*** (0.195)	3.926*** (0.229)	4.275*** (0.173)	4.131*** (0.185)	4.168*** (0.187)	3.952*** (0.229)	4.315*** (0.178)	4.235*** (0.179)
Real GDP per capita	0.00551 (0.0155)	-0.199* (0.113)	0.00507 (0.0164)	0.00675 (0.0160)	0.00113 (0.0171)	-0.0168 (0.0189)	-0.0202 (0.0195)	0.00624 (0.0153)	-0.000163 (0.0160)	0.00644 (0.0153)	-0.0192 (0.0194)	-0.00993 (0.0219)	-0.00734 (0.0216)
Trade restrictions	-0.000455 (0.00717)	0.0141 (0.0197)	0.000486 (0.00825)	-0.00136 (0.00759)	0.00725 (0.00788)	-0.000384 (0.00803)	-0.0127 (0.00988)	-0.00152 (0.00723)	-0.00236 (0.00764)	-0.00224 (0.00765)	-0.0116 (0.00978)	-0.00277 (0.00751)	-0.00314 (0.00751)
Inflation	0.315*** (0.0679)	0.691*** (0.211)	0.306*** (0.0769)	0.279*** (0.0727)	0.150** (0.0760)	0.321*** (0.0774)	0.287*** (0.0908)	0.336*** (0.0700)	0.287*** (0.0722)	0.232*** (0.0739)	0.305*** (0.0906)	0.325*** (0.0696)	0.321*** (0.0698)
Human capital	-0.246 (0.190)	-0.132 (0.560)	-0.193 (0.222)	-0.150 (0.206)	-0.0127 (0.210)	-0.524** (0.217)	-0.726*** (0.276)	-0.291 (0.194)	-0.313 (0.215)	-0.199 (0.205)	-0.550** (0.260)	-0.159 (0.213)	-0.225 (0.223)
Fiscal and Tax Burden
C-efficiency VAT		-0.417 (1.399)
Tax revenues			-0.00734 (0.0141)
Risk budget balance				-0.0254 (0.0571)
Business and Regulatory Environment
Contract viability					-0.418*** (0.0667)
Property rights						0.0200*** (0.00579)
Regulatory quality							1.019*** (0.240)
Private credit								0.00412 (0.00325)
Political and Legal Environment
ICRG bureaucracy									0.261** (0.119)
Corruption										0.416*** (0.0988)
Rule of law											0.863*** (0.219)
Government accountability											-0.0986 (0.120)
Executive constraint													-0.0144 (0.0492)
Constant	-3.242*** (0.421)	-6.132*** (1.208)	-3.339*** (0.459)	-3.095*** (0.525)	-2.914*** (0.464)	-3.541*** (0.504)	-1.454** (0.657)	-3.288*** (0.423)	-3.321*** (0.467)	-4.016*** (0.514)	-1.829*** (0.633)	-3.292*** (0.425)	-3.067*** (0.429)
No. of observations	1,637	449	1,306	1,377	1,377	1,280	995	1,637	1,377	1,377	995	1,569	1,507
No. of countries	101	60	96	85	85	98	101	101	85	85	101	97	96

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

^{Annex Table 8.3.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2008

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina Informal	4.288*** (0.173)	5.368*** (0.552)	4.210*** (0.193)	4.190*** (0.185)	4.194*** (0.191)	4.094*** (0.195)	3.926*** (0.229)	4.275*** (0.173)	4.131*** (0.185)	4.168*** (0.187)	3.952*** (0.229)	4.315*** (0.178)	4.235*** (0.179)
Real GDP per capita	0.00551 (0.0155)	-0.199* (0.113)	0.00507 (0.0164)	0.00675 (0.0160)	0.00113 (0.0171)	-0.0168 (0.0189)	-0.0202 (0.0195)	0.00624 (0.0153)	-0.000163 (0.0160)	0.00644 (0.0153)	-0.0192 (0.0194)	-0.00993 (0.0219)	-0.00734 (0.0216)
Trade restrictions	-0.000455 (0.00717)	0.0141 (0.0197)	0.000486 (0.00825)	-0.00136 (0.00759)	0.00725 (0.00788)	-0.000384 (0.00803)	-0.0127 (0.00988)	-0.00152 (0.00723)	-0.00236 (0.00764)	-0.00224 (0.00765)	-0.0116 (0.00978)	-0.00277 (0.00751)	-0.00314 (0.00751)
Inflation	0.315*** (0.0679)	0.691*** (0.211)	0.306*** (0.0769)	0.279*** (0.0727)	0.150** (0.0760)	0.321*** (0.0774)	0.287*** (0.0908)	0.336*** (0.0700)	0.287*** (0.0722)	0.232*** (0.0739)	0.305*** (0.0906)	0.325*** (0.0696)	0.321*** (0.0698)
Human capital	-0.246 (0.190)	-0.132 (0.560)	-0.193 (0.222)	-0.150 (0.206)	-0.0127 (0.210)	-0.524** (0.217)	-0.726*** (0.276)	-0.291 (0.194)	-0.313 (0.215)	-0.199 (0.205)	-0.550** (0.260)	-0.159 (0.213)	-0.225 (0.223)
Fiscal and Tax Burden
C-efficiency VAT		-0.417 (1.399)
Tax revenues			-0.00734 (0.0141)
Risk budget balance				-0.0254 (0.0571)
Business and Regulatory Environment
Contract viability					-0.418*** (0.0667)
Property rights						0.0200*** (0.00579)
Regulatory quality							1.019*** (0.240)
Private credit								0.00412 (0.00325)
Political and Legal Environment
ICRG bureaucracy									0.261** (0.119)
Corruption										0.416*** (0.0988)
Rule of law											0.863*** (0.219)
Government accountability											-0.0986 (0.120)
Executive constraint													-0.0144 (0.0492)
Constant	-3.242*** (0.421)	-6.132*** (1.208)	-3.339*** (0.459)	-3.095*** (0.525)	-2.914*** (0.464)	-3.541*** (0.504)	-1.454** (0.657)	-3.288*** (0.423)	-3.321*** (0.467)	-4.016*** (0.514)	-1.829*** (0.633)	-3.292*** (0.425)	-3.067*** (0.429)
No. of observations	1,637	449	1,306	1,377	1,377	1,280	995	1,637	1,377	1,377	995	1,569	1,507
No. of countries	101	60	96	85	85	98	101	101	85	85	101	97	96

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

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Constraints on the executive is an index from the Polity IV Database and measures institutionalized constraints on the decision-making powers of the executive branch, presented as a scale of 1 (worst) to 7 (best).

By estimating light density from satellite data, night lights provide an alternative estimate of economic activity to official GDP, which may only estimate, at best, part of the informal economy.

Typically used instruments are latitude (Friedman and others 2000; Dreher and Schneider 2010), a variable for presidential versus parliamentary regimes (Lederman, Loayza, and Soares 2005; Elgin 2010), and legal system (LaPorta and others 1999; Elgin 2010).

Version 9.1 of Penn World Tables is used here.

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^{Annex Table 8.3.2.}

Random Effects Logit, Medina and Schneider Informality, 1990–2008

	1	2	3	4	5	6	7	8	9	10	11	12	13
L. Medina Informal	4.288*** (0.173)	5.368*** (0.552)	4.210*** (0.193)	4.190*** (0.185)	4.194*** (0.191)	4.094*** (0.195)	3.926*** (0.229)	4.275*** (0.173)	4.131*** (0.185)	4.168*** (0.187)	3.952*** (0.229)	4.315*** (0.178)	4.235*** (0.179)
Real GDP per capita	0.00551 (0.0155)	-0.199* (0.113)	0.00507 (0.0164)	0.00675 (0.0160)	0.00113 (0.0171)	-0.0168 (0.0189)	-0.0202 (0.0195)	0.00624 (0.0153)	-0.000163 (0.0160)	0.00644 (0.0153)	-0.0192 (0.0194)	-0.00993 (0.0219)	-0.00734 (0.0216)
Trade restrictions	-0.000455 (0.00717)	0.0141 (0.0197)	0.000486 (0.00825)	-0.00136 (0.00759)	0.00725 (0.00788)	-0.000384 (0.00803)	-0.0127 (0.00988)	-0.00152 (0.00723)	-0.00236 (0.00764)	-0.00224 (0.00765)	-0.0116 (0.00978)	-0.00277 (0.00751)	-0.00314 (0.00751)
Inflation	0.315*** (0.0679)	0.691*** (0.211)	0.306*** (0.0769)	0.279*** (0.0727)	0.150** (0.0760)	0.321*** (0.0774)	0.287*** (0.0908)	0.336*** (0.0700)	0.287*** (0.0722)	0.232*** (0.0739)	0.305*** (0.0906)	0.325*** (0.0696)	0.321*** (0.0698)
Human capital	-0.246 (0.190)	-0.132 (0.560)	-0.193 (0.222)	-0.150 (0.206)	-0.0127 (0.210)	-0.524** (0.217)	-0.726*** (0.276)	-0.291 (0.194)	-0.313 (0.215)	-0.199 (0.205)	-0.550** (0.260)	-0.159 (0.213)	-0.225 (0.223)
Fiscal and Tax Burden
C-efficiency VAT		-0.417 (1.399)
Tax revenues			-0.00734 (0.0141)
Risk budget balance				-0.0254 (0.0571)
Business and Regulatory Environment
Contract viability					-0.418*** (0.0667)
Property rights						0.0200*** (0.00579)
Regulatory quality							1.019*** (0.240)
Private credit								0.00412 (0.00325)
Political and Legal Environment
ICRG bureaucracy									0.261** (0.119)
Corruption										0.416*** (0.0988)
Rule of law											0.863*** (0.219)
Government accountability											-0.0986 (0.120)
Executive constraint													-0.0144 (0.0492)
Constant	-3.242*** (0.421)	-6.132*** (1.208)	-3.339*** (0.459)	-3.095*** (0.525)	-2.914*** (0.464)	-3.541*** (0.504)	-1.454** (0.657)	-3.288*** (0.423)	-3.321*** (0.467)	-4.016*** (0.514)	-1.829*** (0.633)	-3.292*** (0.425)	-3.067*** (0.429)
No. of observations	1,637	449	1,306	1,377	1,377	1,280	995	1,637	1,377	1,377	995	1,569	1,507
No. of countries	101	60	96	85	85	98	101	101	85	85	101	97	96

Source: Author. Note: Standard errors appear in parentheses. ICRG = International Country Risk Guide; VAT = value-added tax. *p < 0.10; **p < 0.05; ***p < 0.01.

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Abstract

Introduction

Stylized Facts

Informality and Institutions

Fiscal Institutions and Tax Burden

Fiscal Management

Tax Burden

Regulatory Burden and Business Environment

Regulatory Burden

Business Environment

Political Environment

Changes in Political Regime

Governance and Corruption

Measures of Informality

Multiple Indicators, Multiple Causes Model

Dynamic General Equilibrium Model

Model and Data

Model

Data

Results

Conclusion

Annex 8.1. Summary Statistics and Variables

Annex 8.2. Robustness Checks

Annex 8.3. Alternative Results Using Elgin and Oztunali (2012)

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