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Productivity dynamics in the retail trade sector: the roles of large modern retailers and small entrants

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Abstract

The massive reallocation and restructuring triggered by the growth of large modern retailers (LMRs) have improved retail productivity worldwide. Using establishment-level census data, we examine the roles of LMRs and small stores in reallocation and productivity growth in the Korean retail trade sector. We find that retail sector productivity growth is accounted for mostly by the entry of small, productive stores. These small stores are more likely to enter counties with LMRs. Moreover, we find that the entrants in LMR counties are more productive than those elsewhere. Our finding of a complementary relationship between small and large stores contrasts with the evidence from developed countries, where retail productivity growth is explained predominantly by more productive, large entrants such as Wal-Mart displacing less productive incumbents.

Plain English Summary

Large modern retailers have contributed to Korea’s retail sector productivity growth by attracting the entry of productive small stores. The massive restructuring triggered by the growth of large modern retailers (LMRs) has improved retail productivity worldwide. We use establishment-level census data and examine the roles of LMRs and small stores in reallocation and productivity growth in the Korean retail trade sector. We find that retail sector productivity growth is explained mostly by the entry of small, productive stores. These small stores are more likely to enter counties with LMRs. Moreover, we find that the entrants in LMR counties are more productive than those elsewhere. Our finding suggests that the relationship between small and large stores is rather complementary than competitive. This finding is in sharp contrast with the evidence from developed countries, where retail productivity growth is explained predominantly by more productive, large entrants such as Wal-Mart displacing less productive incumbents.

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Notes

  1. These large national chains are often called big boxes, superstores, supercenters, or hypermarkets. We label them LMRs since they are not only large in terms of size but also provide modern retail services (e.g., indoor parking, credit card payment, and indoor shopping areas with air conditioning and heating) unavailable in traditional retail stores. A typical LMR in Korea belongs to a national chain brand, selling food and general merchandise. The store format is similar to a hypermarket or superstore because food products comprise about half of store sales.

  2. While Foster, Haltiwanger, and Krizan (2006) relate the prevalence of national chains to sector-wide reallocation and productivity growth, Doms, Jarmin, and Klimek (2004) and Basker (2012) link the diffusion of information technologies and productivity at the firm and store levels, respectively.

  3. See Basker (2007), Jarmin, Klimek, and Miranda (2009), and Hortacsu and Syverson (2015) for reviews of growth in retail chains (e.g., Wal-Mart) and its effects in advanced countries.

  4. On the role of reallocation in retail productivity growth, see also Matsuura and Motohashi (2005) for Japan, Hijzen, Upward, & Wright (2010) for the United Kingdom, Baldwin and Gu (2011) for Canada, and Maican and Orth (2017) for Sweden.

  5. Small- and medium-sized chain stores such as convenience stores and supermarkets also rapidly expanded during the sample period as large, national retail chains expanded nationally. These new stores, the first modern format of national chains with modernized shopping infrastructures and advanced technologies, led the structural change and productivity growth in the Korean retail sector.

  6. While the recent studies related with the retail industry focus on the effects of “new” more innovative entrants such as Wal-Mart or LMRs, Firtsch and Changolusia (2007) argue that the productivity enhancing effects of the entrants are not necessarily driven by innovative entrants. Entry of common new firms have a positive influence on the performance of the incumbents.

  7. This selection-induced reallocation mechanism is similar to what Sampson (2016) labeled as “dynamic selection”. We focus on the fact that the distribution of entrants rather than that of incumbents may shift as new technologies and formats are introduced by an LMR.

  8. In this case, incumbents’ productivity growth, driven by entrants, is classified as the within-effect, not the entry or reallocation effect. Such an indirect effect of competition is also observed in other industries. For example, in the U.S. iron ore industry, producers have attempted to lower costs in the face of increased foreign competition (Schmitz, 2005). We focus on the selection effect driven by entry and exit because the net entry effect is known to dominate productivity dynamics in the retail sector.

  9. The increased competition driven by large entrants makes incumbents strategically respond in various ways such as lowering prices (Basker & Noel, 2009) and increasing product differentiation and offerings (Igami, 2011; Matsa, 2011). Unlike medium-sized (modern) incumbent supermarkets, very small independent (traditional) incumbent stores are not capable of changing product prices or service quality to maintain competitiveness.

  10. This finding is consistent with Lagakos’ (2016) theory that car ownership is important for the diffusion of modern retail technologies in developing countries.

  11. In a study examining the impact of large retail store entry on local supermarkets, Zhu, Singh, and Dukes (2011) show that such an entry generates a positive demand externality to the incumbents located in the same shopping plaza by attracting consumers. However, the positive externality created by the entry of large discount stores in Korea is not limited to an increase in traffic. The entry of LMRs accompanied the development of modern shopping plazas, which attracted small specialized shops not only near the plazas but also in the broad area (e.g., county).

  12. In 2010, Statistics Korea conducted the first Economic Census combining both the Industrial Census (Mining, Manufacturing, and Electricity, Gas, and Water Supply) and the Census of Service Industry.

  13. By using the concordance table at the five-digit industry level provided by Statistics Korea, the KSIC rev. 8 used in the 2005 Census of Service Industry is converted into the KSIC rev. 9 used in the 2010 Economic Census.

  14. We do not distinguish between entry by new single establishments (i.e., single unit firms) and entry through the opening of new establishments by multi-establishment firms (i.e., multi-unit firms). In a similar way, we do not distinguish between exiting establishments by exiting firms and exiting establishments that belong to continuing, multi-establishment firms. Because multi-establishment firms in the retail trade sector are rare and mainly concentrated in large GMSs (4711) and medium-sized supermarkets (47,121), our results based on the entry and exit of small establishments are not affected.

  15. See Coe and Lee (2013) for a detailed discussion of the success and failure of multinational retail chains in Korea and their strategies.

  16. Throughout the paper, we focus on the within-industry reallocation at the narrowly defined four-digit level, which accounts for most of the aggregate productivity growth in the retail trade sector. Between-industry reallocation across four-digit-level industries explains only about 15 percent of aggregate retail productivity growth in 2005–2010.

  17. See Foster, Haltiwanger, and Krizan (2001) for a detailed discussion of this decomposition method and the studies utilizing this method. The time-series change in aggregate productivity of Eq. (1) is based on an index of industry-level productivity, \({P}_{i, t}=\sum_{e\in i}{\theta }_{e, t} {P}_{e, t}\), where \({P}_{i, t}\) is the industry productivity, \({\theta }_{e, t}\) is the share of establishment e in industry i, and \({P}_{e, t}\) is establishment-level productivity.

  18. Foster, Haltiwanger, & Krizan (2006) distinguish entering stores of continuing firms from those from entering firms as well as exiting stores of continuing firms from those from exiting firms. Although we cannot identify types of entrants and exiters because of data limitation, the share of multi-unit firms is very small in the Korean retail sector, suggesting that the entry effect is mainly driven by entering firms rather than the expansion of continuing firms.

  19. The high entry rate of self-employed small business in Korea might be related to the lack of social safety nets, labor market rigidity, and non-financial motives (Sung & Kim, 2020).

  20. The reported numbers are the weighted averages across four-digit industries, with labor hours used as weights. The results did not change when we used alternative weights. Table 2 in the Appendix reports the results with the number of establishments used as weights.

  21. A uniformly distributed productivity of entrants is also observed in Matsuura and Motohashi (2005) for the Japanese retail trade sector and de Vries (2008) for the Brazilian retail trade sector.

  22. To control the difference in the productivity of establishments, we include the establishment size, gender of a business owner, and chain store. The gender of a business owner is used as a proxy variable for human capital, which is based on the large gender gap in schooling. Furthermore, we include variables for regional demand factors that could affect productivity such as the age structure (the ratio of people aged 65 or older to the total population), income (GRDP per capital), and an urban area dummy (seven metropolitan areas). The results including control variables are qualitatively similar to those in Table 3. Full results are presented in Table 1 of Appendix. We would like to thank an anonymous referee for suggesting variables that control the productivity of establishments.

  23. Table 3 in the Appendix reports the summary statistics for the variables used in the regressions.

  24. The entry effect of productive stores in LMR counties is different from the increased traffic effect around or inside shopping malls. The entry of more productive stores in LMR counties is not confined to the neighborhood near the LMR, but is also observed in other areas in the LMR county. This result is reported in robustness check section.

  25. In Sampson (2016), knowledge spillovers from incumbent firms to entrants play an important role in technology diffusion and in the changes in average productivity. The Census data are too coarse to address knowledge spillovers between entrants and LMRs in this study. However, this is important for understanding the mechanism of the shift in the productivity distribution. We leave this topic to future research.

  26. For the three groups between LMR and non-LMR counties, Table 4 in the Appendix reports the t-test results for the differences in entry rates.

  27. For example, Paruchuri, Baum, and Potere (2009) find that the presence of Wal-Mart suppresses the entry rate of small independent retailers rather than the overall entry rate.

  28. To address endogeneity issues with the location and timing of Wal-Mart’s entry, Basker (2005) and Neumark, Zhang, & Ciccarella (2008) also use the store planning dates of Wal-Mart and distance from the first Wal-Mart store in Bentonville, Arkansas as instrumental variables, respectively. Because the actual distance from the first LMRs to counties without LMRs cannot be measured, for consistency, we use the distance based on the county centroid.

  29. We thank an anonymous referee for suggesting the test for the possible sorting patterns that could generate endogeneity problems in our instrumental variable.

  30. Although the distance variable is a good instrument for the LMR location variable, the cross-product of the distance and store-type variables is not necessarily a good instrument for the cross-product of the LMR dummy and store-type variables.

  31. Appendix Figure A1 displays the diffusion of LMRS from 2000 to 2010.

  32. Table 6 in the Appendix reports the results of the first-stage regressions. F-statistics in the first-stage regressions are above 10 in both specifications 1 and 2 (27 and 24, respectively) suggesting that our instruments pass a weak IV test. A map in Appendix Figure A2 presents counties with actual LMRs along with those that are predicted to have LMRs, which also confirms the relevance of our distance instrument. We thank an anonymous referee for suggesting the map.

  33. When we assign the value of 1 for the 73 counties that actually have an LMR among the 119 counties with the highest predicted probability of LMR entry, the results are qualitatively the same. Table 7 in the Appendix reports the results.

  34. Instead of output per worker, Basker (2012) uses nominal sales over payroll as a measure of productivity. If payroll captures the quality of worker and wage, it is likely to be correlated with the quality and price of the product. However, because most small Korean retail stores employ unpaid family workers, it is not possible to use the payroll information for those stores.

  35. Using data on the Local Area Labor Force Survey by Statistics Korea, we checked whether there exists a systematic difference in the hours worked between the two groups of counties. The weekly hours worked in the counties with LMRs is on average 0.171 h longer than the counterpart and the difference is statistically significant at the 1% level. However, the magnitude of the difference is too small (0.358%p) to make a substantial difference in labor productivities between the two groups of counties. The test results are available upon request.

  36. The use of industry-level price deflators may exaggerate these stores’ productivity in the LMR county if the quality effect dominates the price effect. If the latter dominates the former, the productivity in the LMR county can be underestimated. Nonetheless, not only non-GMS but also GMS stores in the LMR county exhibit higher productivity than those in the non-LMR counties, as shown in Tables 3 and 4.

  37. In addition to the demand complementarity effect, the headquarters or franchiser may own a distribution center or brand equity, which provides benefits of scale economies and intangible capital for these small chain stores. The omitted capital may have larger effects on labor productivity of the chained entrants.

  38. Compared with other advanced countries, chain stores have not fully diffused in Korea. For most of the four-digit retail trade industries, with the exception of 10 industries such as convenience stores and bakery, the share of chain stores is less than 10 percent in the sample period.

  39. Moreover, chain stores may purchase more capital at the store level to provide a better shopping environment and services. For example, franchised bakeries and clothing stores may spend more money to provide better product displays than single-unit stores. By excluding chain stores in the analysis, we may therefore avoid the measurement issues caused by (unobserved) differences in these capital types.

  40. We also dropped the industries, not just chain stores as in Table 7. Our key finding is robust when we excluded the 10 non-GMS industries with a share of chain stores above 10 percent (Table 8 in the Appendix).

  41. The results in Table A9 are also robust to the inclusion of control variables.

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Acknowledgements

An earlier version of this paper was circulated under the title “Productivity Growth in the Retail Sector: Entry, Exit and Reallocation.” We are very grateful to the editor, Michael Fritsch, and the two anonymous referees for their helpful comments. We also thank Emek Basker, Tim Dunne, Hugo Hopenhayn, Taewhan Kim, Shawn Klimek, Florin Maican, Matilda Orth, Margaret Slade, Janne Tukianen, and the participants at the Annual Conference of the European Association for Research in Industrial Economics, Bank of Korea, Comparative Analysis of Enterprise Data Conference, Hitotsubashi Summer Institute, International Industrial Organization Conference, KEA International Conference, Korea Academic Society of Industrial Organization Workshop, Midwest Macro Meeting, and Pac Rim 3 Conference of the Association for Comparative Economic Studies for their helpful comments. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A5A2A01043698). We also thank Statistics Korea and the Korea Statistics Promotion Institute for allowing us access to the data used in this study in a secure data center. All results have been reviewed to ensure that no confidential information is disclosed.

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  1. Department of Economics, Faculty of Data Science for Sustainable Growth, Jeju National University, Jeju, 63243, Korea

    Janghee Cho

  2. Department of Economics, Sogang University, Seoul, 04107, Korea

    Hyunbae Chun & Yoonsoo Lee

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Cho, J., Chun, H. & Lee, Y. Productivity dynamics in the retail trade sector: the roles of large modern retailers and small entrants. Small Bus Econ 60, 291–313 (2023). https://doi.org/10.1007/s11187-022-00632-7

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