4.1.1 Context descriptors
A basic question that needs to be answered when designing the policies tackling the informal economy is the character of relationships between the informal economy on one side and other national social and economic characteristics on the other side. Furthermore, if any significant relationship is observed, it is also important to examine the presence or absence of causality, which could be further exploited in the policy formulation. If a causal relationship can be found between certain socio-economic parameters and the informal economy, then acting on these parameters would influence also the informal economy, thus making the policies more effective. In this section we provide stylised facts documenting the potential relationships between the informal economy and other features in the socio-economic context.
First of all, the extent of informality has to be quantified. The issues of measurement and data collection in relation to the informal economy have been discussed at length in Charmes, RNSF, ARS Progetti (2016). Therefore, in this section we only briefly revisit the indicator that is traditionally used to describe the informal economy - the share of employment in the informal economy in total non-agricultural employment. Figure 1 provides an overview of the employment in the informal economy expressed as percentage of total non-agricultural employment for several geographical regions by Charmes, RNSF ARS Progetti (2016). Figure 2 presents the distribution of the informal employment measure by Charmes, RNSF ARS Progetti (2016) across a wide range of countries. The lowest values are attained by the transition economies; the trend tends to increase through Latin American and Asian countries towards African countries. However, the intra-regional variation is also large: e.g. Costa Rica versus Guatemala for Latin America, Thailand versus Bangladesh in Asia, and Sudan versus Benin in Africa. It is obvious from the figures that the depicted variable does not show any systematic regional pattern. Large differences exist within the same continents and even starker differences can be observed at the national level.
Figure 1: Employment in the informal economy in % of non-agricultural employment 2010-14
Source: Charmes, RNSF, ARS Progetti 2016, Table 1, based on Charmes Jacques (2012) ‘The informal economy worldwide: trends and characteristics’, Margin—The Journal of Applied Economic Research, 6:2 (2012): 103–132, updated with new countries.
A deeper insight into the variability at regional and national level is provided at Figure 3 that illustrates the intra-regional variation in the extent of informality. The first panel depicts the extent of informality on a light blue-dark blue scale, the darker tones corresponding to a higher extent of informality. The second panel depicts the same indicator using a pairwise scheme allocating the same colours to the countries with similar extent of informality. The figure documents that there is no uniform pattern within various regions. In each continent or in each major region one can find countries with similar extent of informality. There is also no obvious North-South divide, neither East-West divide. The intra-regional variation in terms of informal economy incidence is large. One can find countries with very high and very low incidence of informal economy within the same geographic region.
Therefore, the high average incidence of the informal economy in particular countries could be explained by other characteristics than just regional identification. In particular, as documented in Charmes, RNSF, ARS Progetti (2016) and briefly illustrated below, the poverty incidence and GDP level were found to be significantly related to the extent of informal economy by numerous academic studies.
Figure 2: Employment in the informal economy and its share in non-agricultural employment, 2010-2014
Legend: Colours by world regions
Source: Charmes, RNSF ARS Progetti (2016), Tables 2, 3, 4, 5, 6, based on Charmes Jacques (2012) ‘The informal economy worldwide: trends and characteristics’, Margin—The Journal of Applied Economic Research, 6:2 (2012): 103–132, updated with new countries.
The variation at the national level can also be used to look into the possible relationship between the informal economy and socio-political context. For example, is there a reason to believe that democratic-inclusive- rights-based political systems are associated with lower degrees of informality than fragmented- exclusive- centralized/authoritarian systems? Similarly, is there a systematic pattern of informality in relation to market-based and fiscality- or state-based economic systems.
The varieties of capitalism approach (VoC) developed by institutional economists (see for instance Hall P.A. and Soskice D., 2001) can be also used to illustrate the absence of strong relationship between the institutional system and the level of informality. The VoC approach classifies the national systems on a bi-polar scale ranging from the liberal market economies (LMCE) coordinated mainly by the market, to the strategically coordinated market economies (SCME) coordinated to a high degree by the state of other central authorities. Countries are classified along this range using qualitative approaches(based on description of the main subsystems, such as labour market, fiscal system, degree of redistribution, education systems), and quantitative approaches (usually based on factor analysis that uses observable variables to capture the underlying unobserved latent variables - subsystems).
An example of a typical LMCE is the United States, in Europe the United Kingdom, and among the transition economies Estonia. On the other side – typical SCMEs are Germany, Austria, Scandinavian countries, or Slovenia for the transitional world. One can easily show that this popular and academically respected typology is not consistent with the observed degree of informality. For example, the two extremes of the scale – the United States (as a representative of liberal market coordinated economies) and Austria (as a representative of social strategically coordinated economies) - both exhibit very low degrees of informality.
Figure 3: National variations in the measures of informality
Source: Charmes, RNSF ARS Progetti 2016, Tables 2, 3, 4, 5, 6, based on Charmes Jacques (2012) ‘The informal economy worldwide: trends and characteristics’, Margin—The Journal of Applied Economic Research, 6:2 (2012): 103–132, updated with new countries. Note: Grey areas denote missing data.
Figure 4: National variations in the measures of informality: Pairwise scale
Source: Charmes, RNSF ARS Progetti, 2016, Tables 2, 3, 4, 5, 6, based on Charmes Jacques (2012) ‘The informal economy worldwide: trends and characteristics’, Margin—The Journal of Applied Economic Research, 6:2 (2012): 103–132, updated with new countries. Note: Grey areas denote missing data
Numerous studies examined the relationship between the informal economy and other variables of interest. As documented in Charmes, RNSF ARS Progetti (2016), many authors confirm a significant negative relationship between the informal economy and income levels, or a significant positive relationship between the informal economy and poverty. The two relationships are depicted at Figures 1.4 and 1.5 (for more details see Charts 3 and 4 in Charmes, RNSF ARS Progetti (2016). Therefore, it seems to be plausible to conclude that informality is more significantly linked to poverty and income than to any particular socio-political system.
As discussed in more detail in Charmes, RNSF ARS Progetti, 2016, employment in the informal economy isgenerally assimilated to low productivity, low income and poverty and the fact is that it is negatively related to GDP per capita and to poverty rate, as illustrated at Figure 4.
Figure 5 shows that very high proportions of employment in the informal economy are associated with very high shares of population living under poverty line in Madagascar and Zimbabwe for example, or with moderate rate of poverty such as in Benin or Mauritania or also with low poverty rates (Indonesia, Morocco). And relatively low proportions of employment in the informal economy can be associated with low poverty rates in Brazil, Thailand or Tunisia, as well as with high poverty rates as in South Africa.
It has been also established by many authors that the informal economy tends to behave counter-cyclically, i.e. it diminishes during the times of economic booms and swells during the economic downturns. This finding can help to explain the lack of causality between the informality and socio-political systems. The relationship seems to be determined by the dynamics/state of the economic cycle rather than by the static picture defined by the institutions. Controlling for the dynamics can bring further insights into the relationships.
Thus although there seems to be a general agreement among the researchers regarding the linkages between the degree of informality and other variables of interest, such as incidence of poverty, GDP, the pace and direction of GDP growth or the phase of economic cycle, the major problem is the absence of a clear indication of causality in these relationships. If there was clear evidence that certain variable “causes” the informality, then acting on such a variable could lead to the reduction of informal economy. However, the finding of correlation between the degree of informality and poverty does not automatically reveal the direction of causality between the two. Although it is certainly justifiable to design policies aimed at poverty reduction, it is not guaranteed that decreasing poverty in any country would also automatically lead to the reduction of informal economy (as the relationship between the two can be more complex, scale-dependent, linked to the dynamics and phase of economic cycle, or other factors and interactions).
Figure 5: Relationship between employment in the informal economy and GDP per capita
Source: Charmes, RNSF ARS Progetti, 2016
Sources: Charmes, RNSF ARS Progetti 2016, Chart 3, project database and Human Development Report for GDP per capita (PPP).
Figure 6: Employment in the informal economy is positively related to poverty
Sources: Charmes, RNSF ARS Progetti, 2016, Chart 4, and Human Development Report for GDP per capita (PPP).
Numerous academic studies examined also the relationship between the extent of informality and the degree of regulations. However, due to rather diversified research frameworks and findings, the results remain generally inconclusive. On one hand, many authors conclude that the informal economy can be reduced by lowering the degree of regulations. For example, the work by Palmade and Anayiotos (2005) published in the influential World Bank Policy Note Series recommends reducing the extent of regulations. However, the formula includes also other types of interventions, such as to reduce and simplify the taxes and tariffs, to improve access to credit, to increase the stock of formal land, and to improve public sector governance (See Box 1 for more details), as only a mixed strategy (“forceful action along these five fronts”) can cut the vicious circle of informality.
On the other hand, many authors conclude that lowering the regulatory burden does not necessarily result in the decrease of informality. For example, in another World Bank Policy Note, Kapaz and Kenyon (2005) use data from the World Bank’s Investment Climate Survey in Brazil to examine the extent of tax evasion. The authors confirm that informal firms are less productive and less likely to access financial markets than other firms. They also provide some advice on how to tackle the problem – notably - they emphasize the benefits of regulatory compliance, reducing the costs of going formal, and tightening up enforcement.
The latter finding is particularly valuable, as it admits that “contrary to what many people have argued, informal firms do not always “grow up” and join the formal sector. Instead, they can remain stuck in an informality trap, excluded from markets for finance and forced to evade taxes and other regulations to compete with their more productive rivals. The solution lies in a mix of stronger incentives for compliance and stiffer penalties for noncompliance”. These findings are consistent with the assumption that many firms may remain in the informal economy by choice.
One of the obvious problems is the fact that for some individuals and economic units being informal is not a necessity, but a rational choice. For example, the cause of reducing tax costs, wage costs or costs of compliance with various regulations can be a legitimate reason for some economic units to be fully or partially informal. In such a case the poverty reduction may not lead to reduction in the extent of informality. Rather, policies aimed at lowering these costs could be more effective. However, even substantial reduction of costs of formality or substantial degree of deregulation does not guarantee the economic units would join the ranks of formal economy. Therefore, some authors suggest that certain degree of enforcement may be more effective than purely dismantling the various barriers. Similarly, empowering the people dependent on the informal economy by providing them with finance, skills and access to services may increase their income and productivity, and improve their living and working conditions, but does not necessarily imply that they will become parts of the formal economy.
Therefore, even the supporters of deregulation admit that the regulatory ease can be effective only if accompanied by a number of other measures, notably appropriate enforcement.
This said, one still has to explore the issue of causality in the relationship between the informal economy and other variables that were found to be significantly related to the extent of informality (such as the poverty incidence, national income, or regulatory burden). On this front, the research results so far are rather deficient and inconclusive. Most of the authors conclude by recommending that more insights are needed into the matter as complex as informality.