1. The Case of Business Groups in Korea
Comparing Productivity Impacts of Knowledge Spillovers from Network and Arm’s Length Industries :
The Case of Business Groups in Korea
Keun LEE* 이근
and
Kineung CHOO** 추기능
*Professor of economics, Seoul National University,
** Assistant Professor; Korea Naval Academy, Changwon, Korea.

2. Background
▪ Firms located in a spatial/conceptual neighborhood benefit from other firms’ knowledge-creating activities
 Knowledge spillovers -> Productivity or performance
▪ Tacitness of knowledge tends to restrict knowledge flows in terms of its transferability to, and learning, by other firms.
 Spillover and transfer among sister firms affiliated with the same business group or conglomerate might be less subject to such limitations.
=> bigger impact than in arm’s length relationship

3. Background
▪ However,
few studies analyze the spillover impacts of a knowledge pool of a ‘network’ consisting of affiliates in a business group, and
compare them with spillovers from arm’s length firms
 We deal with a new question of the relative size of spillovers from networks vs. industries,
and also revisit the debate on the size of
intra- vs. inter-sector spillovers,
dividing the knowledge pool into those within and outside a sector

4. The Literature
▪ Knowledge accumulated by a firm tends to deepen and broaden other firms' technology bases, without appropriate compensation and exhaustion (Glaeser et al., 1992; Laursen & Meliciani, 2000).
▪ A firm’s production function depends on the level of knowledge available in the economy, as well as on its own inputs (Jaffe, 1986; Medda and Piga, 2007).
▪ Labor mobility of scientists and engineers is a conduit for knowledge spillovers among firms (Dindaroglu, 2010; Kim and Marschke, 2005).
Higher mobility of skilled labor between affiliates may facilitate transfers of knowledge better within the business group than within the market.
▪ A resource-based view of the firm stresses the sharing of resources among affiliates within the group (Chang & Hong, 2000).
 By pooling resources at the business group level, and then sharing them among affiliates, more efficient resource utilization is possible.

5. The Literature 2
▪ Studies have addressed the issue of the relative size of inter- and intra-sector spillovers; for example, Bernstein (1988), Rouvinen (2002), and Kafouros and Buckley (2008).
▪ However, no previous studies focus on the effects of inter- and intra-sector spillovers within a business group, and compare spillovers from affiliates in the different sectors and spillovers from affiliates in the same sector.

6. Therefore,
▪ we propose that knowledge pools at the group level affect affiliates’ innovations and thus their productivities.
▪ Furthermore, influence of the spillover pool from the network may be stronger than those from the market.
▪ Then, we compare the spillovers from the same and different sectors within a business group.

7. Four Sources of Spillover Pools and Comparison Combinations

8. Data ▪ financial data for the Korean firms
▪ patent applications filed with the Korean Intellectual Property Office (KIPO) from 1989 to 1997.
▪ 79 groups and 417 firms were included in the sample. The number of firm-year observations is 2,242 in the sample.
- The group definition was obtained from the study of Lee et al. (2007).
- broader than the typical top 30 chaebols that the Korea Fair Trade Commission (FTC) had designated and monitored.
- to be included in the sample, the group needs to have more than two affiliates each year during the seven-year sample period,
- should have more than two patent applications, and continue to be in the KIS data set all throughout the period,

9. Variable Construction
▪ We sums up the number of patent which were applied for in periods T-2, T-1, and T to obtain a proxy for a firm’s knowledge base for the year T.
▪ Then, concerned explanatory variables such as group and industry patents are calculated
▪ We construct four variables representing additional knowledge bases of a firm besides the firm's own patents based on these cumulative values.
▪ inter-sector-within-group spillover
: group _patent(out)
▪ intra-sector-within-group spillover pool
: group _patent(in)
▪ inter-sector spillover pool
: industry_patent(out)
▪ intra-sector spillover pool
: industry_patent(in)

10. Summary of variables used in spillover estimation

11. Regression Models
(1)
(2)
(3)

12. Comparing the Impacts of the Intra- and Inter- sector Spillovers

13. Comparing the Impacts of the Spillovers from the Network and the Industry

14. Spillovers from the Affiliates in the Same and Different Sectors

15. Hypothesis test for the difference between the estimated coefficients

16. The magnitude of the spillover estimated from the regressions
▪ One more patent applied for by sister firms in the same sector bring about 6.58 dollars increase in sales per employee for the firm affiliated to the same business group.
=> 11,534 increase in sales
▪ A firm would experience a 1.12 dollars increase in labor productivity from one patent by an unrelated firm in the same sector.
=>1,960 dollars increase in sales
▪ One more patent of the affiliated firms doing business in other sectors tend to increases my firm’s sales per employee by 3.99 dollars.
=> 6,986 dollars increase in sales
▪ Additional patent in whatever an unrelated firm in other sectors produces 1.89 dollars increase in labor productivity of the concerned firm.
=> 3,320 dollars increase in sales

17. Regression Results
▪ Our results provide no evidence for dominance of either intra- or inter-sector spillovers.
This would be a support for the arguments that both intra- and inter- industry spillovers matter (Hubert and Pain, 2001; Medda and Piga, 2007)
▪ The impacts of network-based spillovers are stronger than those of arm’s length relationship-based spillovers.
 This finding implies that group-affiliated firms have additional benefits from their sister firms in the viewpoint of spillovers.
We have the consistent results of bigger impacts from the network than from arm’s length industry either in terms of intra- or inter-sector impacts.

18. Concluding Remarks : From Spillovers to Productivity
▪ Spillovers from the network are greater than those from arm’s length industry
This should be a new contribution because the literature tends to focus on spillover from arm’s length industry in general.
A business group is an effective organization to internalize knowledge spillovers or to promote greater knowledge diffusion between affiliates.
 Owing to this benefit, affiliated firms would find it more possible to broaden their technological capabilities and to achieve higher level of productivity, other things being equal.
▪ There is no evidence for dominance of either intra- or inter-sector spillovers, regardless of whether it is from arm’s length industry or from networks.
 Both matters.

19. Thank you!