INTERNETRISING,PRICESFALLING 15 7 Appendix 7.1 SummaryoftheComputations We calculate inflation in the Adobe Analytics e-commerce data dataset to facilitate comparison to the CPI in the same categories. Our procedure consistedbroadlyinthefollowingsteps: 1. WefirstmatchedasmanyofAdobe’scategoriesaspossiblewithcategories usedbytheCPI.Afterthisstep,wecontinuedworkingonlywithmatched data and used CPI category names, which are formally called Entry-Level items(ELIs). 2. Since the CPI is computed on a monthly basis, we aggregated the daily Adobe data on revenue and quantities by month for each product. We computedtheaveragepriceforproductiincategory(ELI)j by: 30 XR i,j pi,j,t = 30 Xqi,j wherefromnowontreferstothemonth. 3. For our baseline we do not trim the data at all. As a robustness check, wegaugetheeffectoftrimmingonthepricelevel. AsshowninTableA1, trimmingonthepricelevelhaslittleeffectonAdobeinflationrates. 4. Next, to compute the price index for every ELI at a given month, we first find the products which were sold both in the last and present month (adjacentproducts). 5. Again, our baseline does not trim at all. But Table A1 shows robustness to trimmingonextremepricechangeswithinELI’s.