observe for at least four years before and three years after the event, allowing us to evaluate events happening in event periods _p_ = _{_ 2010 _,_ 2011 _,_ 2012 _}_ . For the sales tax, we consider a balanced panel of rms that we can observe for at least ve months before and after the event, allowing us to evaluate events happening in event periods between February 2009 and August 2014.<sup>40</sup> Each panel in Figure VI displays the trend in (real) reported taxable income for the event group (orange dots) and the control group (blue crosses), scaled by the pre-event average, along with the dierence-in-dierence coecient obtained from estimating The unit of observation in this estimation is a rm _i_ in event period _p_ at event time _k_ . For instance, a rm may be in the control group group for events happening in 2010 and 2011, but in the treatment group for event happening in 2012. Each rm-year observation for this rm will thus appear in the event dataset three times, for event years 2010, 2011 and 2012. We estimate the rm's reported taxable income as a function of event-time dummies _γk_ , rm-event-period xed eects _αip_ , and the post-event and treatment group dummy _I{k ≥_ 0 _, g_ = _E}_ .<sup>41</sup> Outcomes are in levels rather than logs, to include the large number of rms with zero values, and winsorized at the 95th percentile to limit the inuence of outliers. Panels on the left side of gure VI correspond to the self-employed, and panels on the right side correspond to corporations.

For most rms, the rst transacting partner reporting to the tax authorities is a supplier, leading to a D151 cost report about the rm's purchase. As panels A1 and B1 show, receipt of this rst information report is associated with a 26% increase in reported taxable income for the self-employed and a 49% increase for corporations. This large eect emerges precisely at event time, after otherwise identical trends in the event and control group, which means it is unlikely to be driven purely by true income growth.

Over time, rms gradually become covered by more information reports, such as reports from their clients (D151 sales). This event, which happens on average a year after the rst cost report, is considered in panels A2 and B2. The rst sales report is associated with a much smaller increase in taxable income than the rst cost report, possibly because part of the relevant transactions have already been reported to the tax authorities in response to the rst cost report. The eect size is again larger for corporations than for the self-employed. Consistent with the fact that rms under-

> 40 Results are robust to considering fewer or more event periods, or omitting the propensity score reweighting.

> 41Contrary to Naritomi (2015), we conduct the estimation at the rm level rather than on the collapsed data, to estimate the standard errors. The results are qualitatively similar in a simple event study without control group, in which we estimate coecients for each event time. However, limited statistical power makes the point estimates signicantly more noisy. Firm-event-period xed eects and clustering of standard errors at the rm level account for potentially repeated appearance of rm-year/rm-month observations.

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