# **5.3 Robustness Tests**

In Table 1, we demonstrate the robustness of our results to different specifications. In columns 1, 5 and 9, we reproduce the results from our preferred specification from Figure 3 for comparison purposes. In columns 2, 6 and 10, we show that the results are very similar when considering a balanced sample of taxpayers who file regularly during 2011-2015.<sup>22</sup> All point estimates are small and statistically indistinguishable from zero. The same result emerges when we winsorize the outcome variables more conservatively, at the 95th percentile (columns 3, 7 and 11). It thus does not seem to be the case that smaller or larger firms are affected differently. Finally, we still obtain the same results when extending our main specification to include observations for the year 2016 (columns 4, 8 and 12). The 2016 data we have access to is only partial, covering CEDE firms and about 3,500 non-CEDE firms. The results are hence tentative, but they do not provide any indication that a treatment effect emerges over the medium-term horizon. Graphical representations of these results and confirmations of the parallel trends assumption in each estimation are shown in Figure C.1.<sup>23</sup> While we would like to conduct heterogeneity analyses that split the sample based on firm characteristics predictive of responsiveness, e.g. comparing firms with above vs below medium size, share of card sales or firms with and without a POS, such sample splits are not suitable in our setting, as the treatment can lead consumers to switch from smaller firms or from firms without a POS to firms with a POS. Hence, if we observe an effect in a subsample of firms more susceptible to offer card payments, the effect could be a compliance effect or a real effect driven to consumer switching. The sectoral DiD is not affected by this concern, as consumers are unlikely to switch between buying from a retailer vs buying from a wholesaler.

As a refinement of the sectoral DiD, we present in Figure C.2 a DiD where we zoom in on the retail sector and compare firms in four-digit subsectors with above-median pre-reform POS penetration (treatment group) to firms in subsectors with below-median POS penetration (control group). These subsectors are mostly distinguished by the products sold, e.g. book vs clothes vs food, so that the treatment effect is less likely to be confounded by consumer switching between retailers. If firms in subsectors with higher POS penetration were more

> 22We require taxpayers to file at least once in each of those years, and to file once in 2010 and at least once in the last three months of 2015. The additional sample restrictions are required to avoid that 2010 and 2015 contain a disproportionate share of firms filing less than 12 months.

> 23In addition, we show in the Appendix that we obtain very similar results when adding additional controls (e.g. region _×_ year/month and firm-size deciles _×_ year/month fixed effects). These latter controls do little to reduce the variance of the estimates, as treated and control firms are almost equally distributed across the firm-size deciles and the overwhelming majority of firms is located in the capital city. The results are shown in Tables C.1-C.2.

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