Demographics and Firm Characteristics

TABLE 5.4 Relationship between Monthly Sales and Experience on the Platform, Demographics and Firm Characteristics

Dependent variable: Monthly sales

Dependent variable: Monthly growth in sales (%)

Dependent variable: Monthly sales per employee

Dependent variable: Monthly growth in sales per employee (%)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Formal 35.740 (23.330) 48.851* (28.148) 0.006 (0.006) 0.016** (0.006) −37.042*** (5.937) −34.696*** (6.259) −0.006* (0.004) 0.001 (0.004)

Experience on the platform (months) woman-owned 4.843*** (1.031) 5.354*** (1.457) −39.047 (28.145) −0.005*** (0.000) −0.005*** (0.000) 0.004 (0.009) 1.158*** (0.317) 1.291*** (0.413) −3.596 (9.537) −0.003*** (0.000) −0.004*** (0.000) −0.001 (0.007)

Years in business > median −46.388* (26.963) −0.000 (0.006) −10.475 (7.114) −0.001 (0.005)

Secondary

Senior secondary 44.836 (79.554) 100.375 (80.263) −0.051*** (0.017) −0.031** (0.015) 0.576 (13.630) 15.720 (19.192) −0.033*** (0.013) −0.019* (0.010)

university or more −1.492 (47.813) −0.026** (0.013) −5.543 (8.972) −0.018** (0.009)

Age

merchant −1.995 (1.448) 23.097 (34.747) −0.000 (0.000) −0.003 (0.008) −0.929** (0.451) 11.105 (8.941) −0.000* (0.000) −0.001 (0.006)

Producer −27.171 (31.190) −0.003 (0.009) −3.352 (6.662)

−0.002 (0.006) Observations 38,576 39,687 29,779 33,150 34,115 25,713 38,576 38,576 29,779 33,150 33,150 25,713 Number of businesses 2,261 2,316 1,709 1,971 2,023 1,489 2,261 2,261 1,709 1,971 1,971 1,489

Notes: Each column corresponds to a separate OlS regression. The dependent variable in columns (1), (2), and (3) is the number of monthly sales, in columns (4), (5), and (6), the first difference in the logarithm of monthly sales, in columns (7), (8), and (9), the number of monthly sales per employee, and in columns (10), (11), and (12), the first difference in the logarithm of monthly sales per employee. All regressions include fixed effects by time. Clustered standard errors by firm in parentheses. * p < 0.1; ** p < 0.05; *** p < 0.01.

expected to have an average of 49 more sales transactions per month than an informal firm with similar characteristics (p-value = .083).

However, there is almost no difference between formal and informal enterprises in the growth rate of monthly sales (columns 4 and 6). Figure 5.5, panel a, complements these results by showing the average number of monthly sales among formal and informal businesses. The average number of online sales is greater among formal businesses, but the growth rate of sales does not seem to be so different among formal and informal businesses. Figure 5.5 also shows that the average number of sales grows steadily during the first 12 months on the platform among both formal and informal businesses. This finding suggests that online sales channels offer opportunities for growing sales to both informal and formal enterprises.

Because formal firms are larger, it is thus natural to expect them to generate more sales. Sales per employee might therefore be an outcome that more meaningfully captures the impact of e-commerce on business growth. The study thus uses this productivity measure as an additional outcome in table 5.4, columns 7 to 12. The results indicate that, although formal businesses report higher sales on average, they are less productive than informal businesses. In particular, a formal business is found to have 35 fewer sales per employee than an informal business with similar characteristics (p-value < .001). Table 5.4, columns 10 and 12, also show that growth in sales per capita is—if anything—slightly lower for larger formal businesses. This suggests that informal businesses use online sales channels more effectively and perform better in relative terms than formal businesses.

In addition, the results show that firms with greater experience on the e-commerce platform generate more monthly sales (see table 5.4, column 3). A firm with one additional month on the platform is expected to have about five additional monthly sales (p < .001). Similarly, firms with more experience on the platform show more monthly sales per employee on average (see column 9). Taken together, these results suggest that firms may learn how to use the platform and are able to increase sales as they gain experience. The exact mechanism through which this result occurs is, however, not clear and may reflect either a supply- or a demand-side channel. It may be, for instance, that more experienced entrepreneurs learn how to pursue more effective pricing and marketing strategies that increase sales by making their products more visible on the platform. It may also be the case, however, that businesses that have been active on the platform for longer are able to increase their sales through reputation effects. For example, it may be that customers are more likely to buy products from merchants with more customer reviews, which would disproportionally benefit firms that have been active for longer.

Finally, while in table 5.4, column 3, indicate that newer businesses have higher monthly sales, the analysis does not find any differences in the growth rate of monthly sales. One may wonder whether the ability to grow sales and sales revenues is a function of the entrepreneurs’ education. If there were such an effect, this might indicate that the experience effects documented result from deliberate choices of the entrepreneur and