5.8 Sales Stability

FIGURE 5.8 Sales Stability

Sources: Administrative data on transactions and business and entrepreneur characteristics associated with a partner firm website; data at CPhS (Consumer Pyramids household Survey) (dashboard), Consumer Pyramidsdx, Centre for monitoring indian Economy, mumbai, https://consumerpyramidsdx.cmie.com/. Note: The figure shows the share of months with no sales (panel a) and the share of months with a drop in sales of 50 percent or more (panel b) among firms in the sample, based on administrative data.

the sample had sales in more than 95 percent of the months of their presence on the platform. The firms that recorded no sales in any of the months on the platform are firms that left the platform in the first or second month after they registered.3

Second, to study whether online sales fluctuate significantly from month to month, the analysis considered for each firm the proportion of months with a drop in sales of 50 percent or more relative to the previous month and calculated the ratio of months with a drop in sales of 50 percent or more to total months on the platform. Figure 5.8, panel b, plots this ratio. It shows that about 32 percent of the firms did not experience any months with online revenue drops of this magnitude, while 75 percent of the firms did not have a drop in sales of this magnitude in 80 percent of the months in which they were active on the platform. This finding suggests that, for most businesses, online sales revenues are relatively stable.

Taken together, the results indicate that, for most businesses, online sales represent a relatively stable source of income. More than 65 percent of the firms on the platform experienced almost no months with zero sales, and large month-on-month fluctuations in sales were also relatively rare. These estimates are upper bounds on sales drops because most businesses that use online sales channels are active on more than one platform, while the study only observed sales and sales drops on one platform. In any case, the results suggest that e-commerce can be a reliable source of revenue that allows firms to expand their business, especially small, informal enterprises.

EXPANSION IN GEOGRAPHICAL MARKET SIZE

The final question addressed by this study is the extent to which online sales channels allow small businesses to expand sales by reaching consumers in a larger geographical area. Intuitively, online sales channels might increase sales in two ways. First, it may be that there is a substantial home bias among consumers, and online channels increase sales by making it easier for consumers to buy products from local merchants that they already know. Second, it may be that online channels increase sales by making a merchant’s products visible to a larger geographical market. Which of these channels dominates has important implications for competition, market power, and, potentially, for how online markets should be regulated.

To examine how registering on an e-commerce platform expands the geographical reach of businesses, the study relies on the geographical identifiers contained in the transaction data. Specifically, the analysis uses as the outcome of interest the number of postal codes (pin codes) and states in which a given firm’s customers are located, and estimates regressions identical to equation 5.1, with monthly number of pin codes with any sales, monthly growth in the number of pin codes with sales, monthly number of states with sales, and monthly growth in the number of states with sales as the dependent variables.

Table 5.7 presents the results and shows that formal businesses sell in more postal codes and more states on average (table 5.7, columns 3 and 9). The average formal firm