Official estimates peg global business-to-business ecommerce at 15 trillion dollars and global business-to-consumer ecommerce at 1.2 trillion dollars in 2013 (UNCTAD 2015). When we turn to official estimates for Korea, it is easy to find that Korea’s business-to-consumer ecommerce market is grow-ing at more than twenty percent per year and has emerged as the third larg-est global ecommerce market in Asia. It is not very much surprising to know the numbers for Korea since Korea is one of the world’s most ad-vanced countries in terms of information and communication technology. However, it is somewhat surprising that we know little about how ecom-merce firms or establishments are distributed in the economy of Korea. In addition, we know little about how ecommerce establishments perform relative to their counterparts of a similar age and size in the same industry.
The paper aims to characterize and test performance differences between ecommerce and non-ecommerce firms or establishments. Although the number of ecommerce establishments makes up a small fraction of the economy, ecommerce establishments have a heavier weight in sales, em-ployment, and wage. Due to endogeneity of ecommerce variable, the paper reconstructs the 2010 Korea Census dataset by using Propensity Matching Score and shows that in manufacture ecommerce establishments have, on average, larger sales-per-worker and pay higher wage whereas in services ecommerce ones have higher sales-per-worker but pay no larger wage than their counterparts of a similar age and size in the same industry. It also adds quantile estimates showing that sales-per-worker differences between ecommerce and non-ecommerce establishments in manufacture are positive and statistically significant only at lower quantiles of the distribution. In ser-vices, sales-per-worker differences between them are positive and signifi-cant at most of distribution but turns to be negative, though not significant, at above upper quantile of the distribution.

Keywords: Ecommerce, Firm Performance, Sales-per-worker, Wage
JEL Classification Numbers: F1 

Executive Summary

1. Introduction

2 Data and Statistical Description
2.1. Data
2.2. Statistical Description

3. Estimation
3.1. Constructing a Matched Dataset
3.2. Estimation

4. Results
4.1. Sales-Per-Worker and Ecommerce Activity
4.2. Wage and Ecommerce Activity

5. Conclusion

References

Appendix