We set the discount factor _β_ at 0.99, implying that the annual real interest rate is 4 percent. The value of the risk aversion parameter, _γc_ , is equal to 2. Following Bernard et al. (2003), we set the elasticity of substitution across product varieties, _θ_ , equal to 3.8. Following Ghironi and Melitz (2005), we set the elasticity of substitution across Home and Foreign goods, _φ_ , equal to _θ_ , and the dispersion of rm productivity _kp_ equal to 3.4. We normalize _zmin_ to 1. We set iceberg trade costs _τ_ equal to 1.7, following the estimates of trade costs reported by Anderson and van Wincoop (2004). We calibrate the xed export costs _fx_ so that the shares of exporting plants in the developed and emerging country are respectively equal to 21 percent and 18 percent, consistently with data reported in Bernard et al. (2003) for the United States and in the World Bank Enterprise Survey for Brazil.<sup>15</sup> To ensure steady-state determinacy stationarity of net foreign assets, we set the parameter _ψ_ measuring asset adjustment costs equal to 0.0025 as in Ghironi and Melitz (2005). Following Ebell and Haefke (2009), we set entry costs, _fe_ , so that regulation costs amount to 5.2 months of per capita output. To pin down the rm exit rate _δ_ , we target the portion of worker separation due to rm exit equal to 30 percent in the United States and to 37 percent in Brazil: these values fall within the range of estimates reported by Haltiwanger et al. (2008). Empirical evidence indicates that informal rms are less productive than formal ones. We normalize the productivity parameter in the informal sector to unity and we assume that the productivity in the formal sector is 30 percent higher than in the informal sector.<sup>16</sup> Regarding the parameters specic to the search and matching framework, the gross replacement rate for unemployment benets _b_ in the formal sector is set to 13 percent for the United States and 15.2 percent for Brazil. The parameter measuring rms' bargaining power, _η_ , is equal to 0.4, as estimated by Flinn (2006). The elasticity of the matching function _ε_ is equal to 0.4, so that it falls within the range of estimates reported by Petrongolo and Pissarides (2006) and the Hosios condition holds. We set the costs of vacancy posting ( _κF_ and _κI_ ), matching eciency ( _χF_ and _χI_ ) and exogenous separation rate ( _λF_ and _λI_ ) in the formal and informal sectors so to match the underlying structure of the two countries, with the values of steady-state ratios summarized in Table 1. We choose a calibration based on the long-run averages (1992-2017) from ILO data. Steady-state unemployment rates are respectively 6 percent and 8.7 percent in the United States and Brazil, while the ratio of informal employment to total employment is respectively 7 percent and 30 percent in the United States and Brazil.<sup>17</sup> This calibration yields an informal wage gap (i.e. dierence between wages for formal and informal workers) equal to 66 percent in the United States and 11 percent in Brazil. This latter value is very close to estimates in Bargain and Kwenda (2010, 2014) who conclude that earning dierentials driven by the informal wage penalties are quite modest in Brazil and remain below 10 percent all along the distribution. Labor market regulations and high employer costs attached to formal employment in Brazil may simultaneously explain the large extent of informal work and the relatively modest informal

> 15As a caveat, we point out that the World Bank Enterprise Survey covers only rms of the formal private sector with ve or more employees. Hence informal and micro rms are excluded from the sample.

> 16This assumption allows us to reproduce a wage premium equal to 30 percent as in Charlot et al. (2015). 17 We use vulnerable employment as a proxy for informal employment.

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