Finance

The hidden cycle: How informality shapes fiscal policy and sovereign default

The informal sector tends to expand during economic downturns and contract in recoveries, and is also highly sensitive to fiscal policy. This column explores the impact of these informality dynamics on optimal fiscal policy and the risk of sovereign default. The interaction of tax distortions and limited commitment to reimburse sovereign debt strongly constrains the dynamics of optimal fiscal policy and leads to more frequent default episodes and costly consumption fluctuations. Toning down the impact of fiscal policy on future returns to taxation or tempering the threat of default would both lead to welfare gains and more muted consumption fluctuations.
The informal sector tends to expand during economic downturns and contract in recoveries, exhibiting a clear countercyclical behaviour (Pappadà and Rogoff 2025a), suggesting that “the market moves the informal sector”. Informality not only fluctuates with the business cycle; it is also highly sensitive to fiscal policy. Tax increases, in particular, can trigger a lasting shift toward informality as individuals and businesses exit the formal economy. This persistent move reduces the effective tax base over time, undermining future revenue collection and increasing sovereign default risk.

In this column, we discuss the macroeconomic implications of such informality dynamics: how they affect optimal fiscal policy and the risk of sovereign default. In short, we look at how the informal sector moves the market. While these dynamics are more salient in middle-income economies, ignoring the endogenous response of informality to fiscal instruments can lead to a systematic underestimation of fiscal fragility even in advanced economies.

In Pappadà and Zylberberg (2025), we study the economic consequences of informality dynamics by adding dynamic entrepreneurial decisions to a standard model of sovereign debt with limited commitment. Entrepreneurs can choose to operate in the formal or informal sector, and this choice is subject to some rigidity (or sluggishness). In the model, higher taxes lead to an expansion of the informal sector. Due to the previous rigidity, the reallocation of the economy away from taxable activity does not only affect fiscal revenues in the short run (a static distortion); these adjustments might outlive the initial contractionary fiscal policy and persistently lower returns to taxation (a dynamic distortion). Through this channel, (i) austerity measures based on tax increases might threaten the future capacity of governments to reimburse sovereign debt; and (ii) fiscal policy might prove to be a weak instrument to stabilise household consumption.

We explore the consequences of such interplay between informality, fiscal policy, and sovereign default in two steps. First, we focus on how and when tax increases lead to high risks of sovereign default in a typical middle-income economy. Second, we consider economies facing different dynamics of informality and levels of commitment to reimburse sovereign debt in order to quantify how the dynamic properties of informality – interacted with imperfect commitment – affect optimal fiscal policy and welfare.

To illustrate the impact of the previous dynamic distortion, we calibrate our model to a typical middle-income economy. First, we display in Figure 1 the distribution of our two endogenous state variables – debt (as standard in models of sovereign default) and formality (as induced by the fact that past entrepreneurial choices still partly influence the making of the economy in the current period) – and their relationship with default frequency. We find that the government has incentives to accumulate debt, but it comes at a cost. The government mostly accumulates debt over a range going from about 0% to 55% of output, but debt levels above 50% of output are very rarely observed (the latter could be interpreted as a ‘sustainable’ debt ceiling); default is nil for low levels of inherited debt but sharply increases for debt between 40% and 55% of output. These patterns are very standard in the sovereign default literature. This increase of default with inherited debt implies that (i) there exists a region in the set of state variables where default is likely, and (ii) the government is still tempted to accumulate debt within this region, as the marginal cost of doing so is not immediately prohibitive.

Second, informality is also key to understanding default. The share of economic activity in the formal sector ranges between 60% and 82% with a slightly asymmetric left tail, and default is predominantly observed towards the lower end of this distribution. The staggered technological adjustment of entrepreneurs implies that the dynamics of informality exhibits stickiness – a key property of our calibrated economy. Through this channel, high informality today induces low returns to taxation in the medium run, thereby giving strong incentives to default. In summary, when do tax increases lead to sovereign default? When debt is high and/or when informality is high.

Figure 1 Distribution of debt, technological choices, and default frequency: Model

Notes: This figure displays the distribution of the two endogenous state variables, (debt and formality), and their relationship with the occurrence of a default across 10,000 simulated economies over 50 years. We run simulations across 100 years and only keep the last 50 years to limit the influence of initial conditions. Panel (a) shows the distribution of debt (as normalised by average output), and the average likelihood to observe a default as a function of inherited debt level (as a dashed line). For visualisation purposes, we omit the less frequent debt levels below 25% of output. Panel (b) shows the distribution of technological choice (the incidence of the formal sector). We label the incidence of the formal sector as formality. The default frequency, reported in the second y-axis, is the likelihood of default occurrences in period t (excluding periods of autarky and averaged over the other endogenous or exogenous state variables); and the constructed distributions are based on simulated data during periods of repayment.

To further highlight the impact of dynamic distortions, we study the impulse response of the economy to a negative government expenditure shock (e.g. an external conflict leading to additional required expenses) and how this response depends on the state of the economy. In our paper, we show that both theoretical and empirical such analyses provide similar results, and we focus here on the latter (Figure 2). Following Born et al. (2020), we identify conditional impulse responses to exogenous expenditure shocks based on two regimes: a low-informality regime and a high-informality regime (calculated by the position of formality in t-1 relative to its median value within each country). The responses of the economy to the expenditure shock markedly differ across the two regimes. In the high-informality regime (when the economy inherits high informality in t-1, the default premium increases (panel a) – in line with the forces at play in our quantitative model. By contrast, there is not higher default risk in the low-informality regime (panel b).

Figure 2 State-dependent impulse response functions: Data

Notes: This figure displays the estimated impulse response function to an increase of one percent of output in government expenditures (as in Born et al. 2020). Panels (a) and (b) display the estimated response (dashed line) and the 10-90% confidence interval for debt as a percentage of output and the default spread. The estimation procedure allows for regime switching between two regimes: low and high tax compliance in the previous period.

The interactions between fiscal policy and the dynamics of formality may have non-negligible welfare consequences, which we quantify through the lens of our quantitative model. To do so, we now consider different economies and compare their performance in the longer-run steady state:

  1. The baseline, as our economy calibrated on a typical middle-income economy
  2. An economy with flexible technology adjustment (flexible) – without the dynamic distortions associated with the sluggish adjustment in technology
  3. An economy with a smaller fiscal multiplier (formal complementarity)
  4. An economy with less-responsive entrepreneurs (informal response), both lowering the elasticity of informality to fiscal policy – with smaller static distortions
  5. An economy where the government has full commitment to repay (no default)

We compute the welfare costs as the share of consumption that the government/household would accept losing in order to get rid of all consumption fluctuations – i.e. in which economies is fiscal policy better able to insure the household?

We show that the welfare costs depend upon the endogenous response of entrepreneurs to fiscal policy. The prospect of a future default forces the government to raise taxes to finance an exogenous shock in expenses. This tax hike decreases the return in the formal sector, pushing entrepreneurs to produce in the informal sector. Since their choice to produce in the formal or informal sector is persistent, the cost for the government to repay is higher and the prospect of a future default raises even further. The model is crucially disciplined by the volatility and persistence of informality, whose estimation requires rich variation in fiscal policy and tax compliance.

In the baseline economy (1), calibrated on a selected sample of countries with non-negligible levels of informality and default risk, this cost amounts to 0.743% of average consumption. In counterfactual economies (2), (3), and (4), we reduce the persistence of the technology choice and the elasticity of the formal sector to changes in fiscal policy. Contrasting the previous experiments (2)-(4) with the baseline experiment (1) sheds light on how the dynamics of informality – its elasticity combined with its sluggishness – affects fiscal policy and default risk. As reported in Figure 3, these losses fall to 0.674%, 0.536%, and 0.523%, respectively, of average consumption in economies with a more flexible adjustment of technology (2), lower fiscal multipliers (3), or marginally less responsive choices of technology (4). The last experiment (5) captures how default risk shapes fiscal policy and the dynamics of informality: with full commitment (and a fixed borrowing constraint), fiscal policy stabilises consumption much more effectively. The welfare cost of consumption volatility markedly drops to 0.104%.

Overall, these experiments highlight the central role of the interaction between dynamic informality distortions and imperfect commitment in shaping fiscal policy: toning down the impact of fiscal policy on future returns to taxation or tempering the threat of default would both lead to non-negligible welfare gains and to more muted consumption fluctuations.

Figure 3 The welfare costs of dynamic informality

Notes: This figure reports the costs in terms of consumption fluctuations, computed as a second-order approximation in the spirit of Lucas (1987) for the baseline and counterfactual economies.

The interaction of limited commitment to repay sovereign debt and imperfect tax enforcement strongly influences the dynamics of fiscal policy during default crises. With dynamic distortions in informality, current fiscal policy affects future choices between repayment and default, and these prospective incentives to default impact contemporary debt prices and thus the inclination to bring consumption forward. Through this particular channel, the costs in terms of consumption volatility associated with the dynamics of informality may be substantial.

While these dynamics are more salient in middle-income economies, ignoring the endogenous response of informality to fiscal instruments can lead to a systematic underestimation of fiscal fragility even in advanced economies. As shown in Pappadà and Rogoff (2025b), the size of the informal economy among European countries is non-negligible, averaging around 30% of GDP in Southern European countries over the period 1999-2020.

Source : VOXeu

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