Economic fluctuations have always been a key issue in macroeconomics (Gambacorta and Marques-Ibanez 2011). The empirical literature identified several drivers of economic instability from both side: demand shocks (Hall 1986) and supply shocks (Gali 1999) but also shocks from economic integration as trade activities and capital flows (Kose and Riezman 2001), shocks from fiscal policy and monetary policy (Creal and Wu 2017) and shocks from the financial sphere (credit supply or stock prices) (Chauvet and Guo 2003, Christiano, Motto, and Rostagno 2010). More recently, Furlanetto, Ravazzolo, and Sarferaz (2014) found that financial shocks are actually the major driver of fluctuations while Gilchrist, Yankov, and Zakrajšek (2009) showed that credit market shocks contributed significantly to the US economic fluctuations for the period of 1990–2008. On another point, Konstantakis, Michaelides, and Tsionas (2016) documented that the ten-year bond yields and the elections can play a pro-cyclical role on the Greek business cycle in the period of 1995–2004.
Economic fluctuations are also related to human expectations and how the market perceives the level of uncertainty associated with the economic context under consideration. Using survey data in US, Leduc and Sill (2013) found that changes in expected future economic activity act as an important driver for economic fluctuations. Creal and Wu (2017) documented that uncertainty contributes negatively to economic activity when they investigated the relationship between uncertainty about monetary policy and economic fluctuations. Related to this aspect, Forni, Gambetti, and Sala (2017) explained that the Great Recession were exacerbated by the uncertain context generated by media and news.
A particular way of characterizing the uncertainty of a country is to investigate the importance of its shadow economy. Surprisingly, the influence of shadow economy on economic fluctuations is still relatively under-investigated in the literature despite the existence of some research: Mai & Friedrich, 2016; Medina & Schneider, 2018. Because agents operating in shadow economy do not wish to be identified, the estimation of such economy can be tricky. Schinckus (2009) explained that uncertainty is probably the major driver of all economic activities despite the difficulty to estimate it. Fortunately, recent databases about shadow economy (Medina and Schneider 2018) have been developed offering new opportunities for academic research.
Shadow economy refers to all currently unregistered economic activities which if counted, would contribute to the official output (Schneider and Williams 2013). Mai and Friedrich (2016) specifically defined shadow economy as the legal economic and productive activities that would contribute to national GDP if recorded, but it does not include illegal, criminal activities, do-it-yourself, charitable or household activities. In other words, shadow activities refers to all these legal economic activities actually refer to market-based production of goods and services that are deliberately concealed from public authorities to avoid payment of income, value added, other taxes or costs related to legal labour market policy (social security, minimum wages, maximum working hours, safety standards, etc.) (Schneider and Williams 2013).
Shadow economy can also be related to (i) tax evasion since economic agents are not willing to pay when taxes or social security burdens are high (see Tanzi (1999), Schneider (1994)) and (ii) the quality of government in implementing and enforcing their regulations (La Porta et al. 1999). A weak institutional quality (associated with bureaucracy, regulatory discretion, rule of law, corruption, and a weak legal system) usually paved the way to a higher level of shadow activities (Friedman et al. 2000). Several studies examined the effects of shadow economy on other economic aspects. While Dreher, Kotsogiannis, and McCorriston (2009) found that corruption and shadow markets have a substitution effect in 145 countries over the period of 2000–2002; Choi and Thum (2005) documented that shadow sectors can be perceived as a complementary element to the official economy. In the light of these findings one can question remains: how does shadow economy influence the economic instability?
There exist few studies detailing the link between these two aspects. (Granda-Carvajal 2010, Shapiro 2015). Broadly speaking, the literature explains that unofficial businesses are mostly small and therefore 1) they cannot benefit from economies of scale; and 2) they have a limited financial access (Ferreira-Tiryaki 2008). As a result, informal businesses are likely more exposed to economic instability, which resulting in the fail and overall higher economic fluctuations.
In this study, we use the few existing studies to investigate further these aspects by adding the economic reasoning eventual influence of the shadow economy on the economic instability. First, a higher shadow economy might reduce the government’s capability to implement a fiscal policy, especially a counter-cyclical fiscal policy. In other words, an increase of shadow economy reduces government’s revenue implying therefore a negative impact on the ability of government to provide public goods and services. Paradoxically, such situation might lead the government to react by increasing the tax rates (Talvi and Végh 2005). Consequently, shadow economy distorts and weakens government roles in its allocation, redistribution and stabilization function (Κάτσιος 2015).
It is also worth mentioning the possible link between shadow economy and the effectiveness of monetary policy. Both fiscal and monetary policies require a precise estimation of the key macroeconomic indicators related to output and unemployment. In this context, shadow economy and its non-declared activities become an important issue. (Fleming, Roman, and Farrell 2000). For instance, the velocity of currency in the official sector is quite difficult to value but it becomes totally impossible to estimate when the shadow economy activities are important (Schneider 2000) leading to the use of biased estimations in conducting monetary policies. Furthermore, shadow banking (Gennaioli, Shleifer, and Vishny 2013) or informal credit (Barslund and Tarp 2008) have also severely misled decision related to monetary policy. In this challenging context, a higher shadow economy implies a higher economic uncertainty complicating the role of central banks in the implementation of monetary policy (that have often been blamed for the turbulences in recent crisis, (Duncan, 2014; (Creal and Wu 2017). Related to that, economic activities taking place in the shadow economy are not protected by any legal framework but these activities are rather ruled by the informal trust between economic agents who usually focus on a short-term horizon. However, a higher shadow economy generally leads to a lower generalized trust in the overall economy (D’Hernoncourt and Méon 2012). All these aspects influence the investors mood and it might exacerbate economic fluctuations (Forni, Gambetti, and Sala 2017).
In overall, the shadow economy may induce higher economic fluctuations through the links with the effectiveness of macroeconomic policies and the nature of informal businesses, which are far from economies of scales or optimal mix of labor/capital in production, and moreover face with financial constraints. Restrepo-Echavarria (2014) showed that shadow economy can affect on the measurement of official economic fluctuations. Ferreira-Tiryaki (2008) found that larger shadow economies tend to induce the volatility in output, investment and consumption over the business cycle in a sample of 22 economies over the period 1961–2002. Recently, Horvath (2018) notice a positive relationship between the relative volatility of consumption to output and the size of the informal economy.
However, the link between shadow economy and economic fluctuations must be treated in different ways. We mentioned above the potential influence of shadow economy on economic instability. There are also other reasons why shadow economy may have a positive influence in reducing the economic fluctuations. We detail hereafter the reasons for why we decided to investigate further the relationship between shadow economy and economic fluctuations.
Tax evasion, for instance, can actually bring to economic agents additional unexpected benefits offering therefore an advantage for informal sectors in case of economic fluctuations. Second, the informal businesses are small, which mean they are more flexible in changing their production or business model. Third, the cost and the spread effects to the economy of the fail in small businesses will be much more smaller than the fail of large firms so that the informal businesses under recessions may be fail but their failure would have a weaker marginal impact on the economy. Overall, shadow economy may act as a buffer or a complement for official economic activities in case of large economic fluctuations with less cost and weaker spread impacts. As a result, there is a surprising claim according to which shadow economy in some circumstances, may be useful for the economy depending on its size and the development of the national economy. This study investigates further this surprising claim.