Declining Competition and Industrial Disruption Study

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Research conducted by James Bessen, Erich Denk, Joowon Kim, and Cesare Righi focuses on the trends in competition and industrial disruption, with a specific emphasis on the hazard of displacing top firms, impacts of investments by dominant firms, and the relationship between displacement hazard, markups, and industry concentration. The study reveals a rise in displacement hazard post-1970 followed by a decline after 2000, negative correlation with investment in intangibles like software, and associations with higher markups and lower industry concentration.


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  1. Declining Industrial Declining Industrial Disruption Disruption James Bessen, Erich Denk, Joowon Kim, Cesare Righi TPRI, Technology & Declining Economic Dynamism , 2020

  2. Is competition declining? Is competition declining? Markups rising? Industry concentration rising? Markups measure price competition Not dynamism

  3. Price competition Price competition Schumpeterian competition Schumpeterian competition Innovative firms earn rents on technology markups Why competition matters Price competition static deadweight loss Schumpeterian competition productivity growth Measuring industry dynamism Entry rates Growth rates of innovative firms Displacement of market leaders

  4. This paper This paper 1. What are trends in hazard of displacing top firms? 2. What investments by dominant firms affect displacement? 3. Is displacement hazard related to markups and industry concentration?

  5. This paper This paper 1. Hazard of displacing leading firm rose since 1970 but fell sharply after 2000 2. Displacement hazard negatively related to investment in intangibles, software Accounts for much of decline 3. Displacement hazard associated with higher markups, lower industry concentration

  6. Data Data Compustat, 1976-2017, global, publicly listed Peters and Taylor (2016) intangibles Advertising Patents Lobbying Software Acquisitions NETS, 1990-2014, US, private & public ACES, 2002-2012, US, private & public [not disclosed]

  7. I. Dominant firm displacement I. Dominant firm displacement

  8. II. Displacement & Investments II. Displacement & Investments

  9. IO models: investments IO models: investments market share market share Cournot: investments in capacity Sutton, endogenous sunk costs: investments in quality, differentiation Investments by acquisition Regulation: investments in lobbying

  10. IO models: investments IO models: investments market share market share Cournot: investments in capacity Sutton, endogenous sunk costs: investments in quality, differentiation Investments by acquisition Regulation: investments in lobbying Q: Which investments associated with change in displacement?

  11. Basic model: Duopoly Basic model: Duopoly Revenue Production function (reduced form) ???= ????( ???,? ?? A = productivity; stochastic, dynamic K = Beginning of year capital variable inputs adjust K-i= other firm capital; externality

  12. Leapfrog ?( ???,? ?? ?( ? ??,???

  13. Assume Assume Shocks independent (Sutton 2007) and normal; Markov process ln???= ???+ ???~? ???,??, ? = 1,2 Cobb Douglas, ln? = ?1ln???+ ?2ln? ?? ?2? ?1?+ ln? ?2?,?1? ln ?(?1?,?2? ? ?2?< ?1? = 2??

  14. Probability of leapfrog / dropout Probability of leapfrog / dropout ???= ??+ ??+ ??+ ?1ln???+ ?2ln? ??+ ???. Linear approximation ?? industry FE ?? captures changes in volatility, ?? ?? absorbed into ??? Multiple firms Top 4 Second 4 (ranked 5-8) Multiple capital stocks

  15. Identification Identification ???= ??+ ??+ ??+ ?1ln???+ ?2ln? ??+ ???. ?? unobserved & possibly correlated with ??? Obtain ??? from productivity function estimation (ACF) ???= ??+ ??+ ???+ ?1ln???+ ?2ln? ??+ ???. Robustness: bootstrap errors

  16. Displacement Hazard of Top 4 firm 1 4 5 Base <=2000 1976-2000 >2000 2001-2017 1976-2017 Productivity -0.019 (0.018) -0.029*** (0.003) -0.102*** (0.031) -0.043*** (0.004) -0.032 (0.023) -0.023*** (0.005) Net PPE Intangibles -0.026*** (0.003) -0.030*** (0.004) -0.032*** (0.005) Industry FE Year FE Industry x year FE Observations Adjusted R-squared x x x x x x 26471 15936 10535 0.091 0.109 0.091

  17. Displacement Hazard of Top 4 firm 1 4 5 Base <=2000 1976-2000 >2000 2001-2017 1976-2017 Productivity -0.019 (0.018) -0.029*** (0.003) -0.102*** (0.031) -0.043*** (0.004) -0.032 (0.023) -0.023*** (0.005) Net PPE Intangibles -0.026*** (0.003) -0.030*** (0.004) -0.032*** (0.005) Industry FE Year FE Industry x year FE Observations Adjusted R-squared x x x x x x 26471 15936 10535 0.091 0.109 0.091

  18. Top 4 firm moves down Second 4 firm moves up Hazard: Firm interactions -0.006 (0.021) -0.033*** (0.004) -0.035*** (0.004) 0.090*** (0.022) 0.039*** (0.003) 0.032*** (0.003) -0.001 (0.004) -0.002 (0.004) -0.011*** (0.004) -0.014*** (0.004) -0.014*** (0.004) -0.004 (0.004) -0.005 (0.005) -0.006 (0.004) Subject firm Productivity Net PPE Firm 1 Intangibles Tangible Capital Firm 5 0.004 (0.003) 0.001 (0.002) -0.001 (0.003) -0.002 (0.002) Firm 6 Firm 2 Firm 7 Firm 3 Firm 8 Firm 4 Intangible Capital Firm 5 Firm 1 -0.001 (0.002) 0.003 (0.003) 0.002 (0.003) 0.004 (0.003) Firm 6 Firm 2 Firm 7 Firm 3 Firm 8 Firm 4

  19. Top 4 firm moves down Second 4 firm moves up Hazard: Firm interactions -0.006 (0.021) -0.033*** (0.004) -0.035*** (0.004) 0.090*** (0.022) 0.039*** (0.003) 0.032*** (0.003) -0.001 (0.004) -0.002 (0.004) -0.011*** (0.004) -0.014*** (0.004) -0.014*** (0.004) -0.004 (0.004) -0.005 (0.005) -0.006 (0.004) Subject firm Productivity Net PPE Firm 1 Intangibles Tangible Capital Firm 5 0.004 (0.003) 0.001 (0.002) -0.001 (0.003) -0.002 (0.002) Firm 6 Firm 2 Firm 7 Firm 3 Firm 8 Firm 4 Intangible Capital Firm 5 Firm 1 -0.001 (0.002) 0.003 (0.003) 0.002 (0.003) 0.004 (0.003) Firm 6 Firm 2 Firm 7 Firm 3 Firm 8 Firm 4

  20. Two sides of investment Two sides of investment Boosts firm output Diminishes displacement for firms #3 and #4 Externality Dominant firm investments suppress leapfrogging Sutton endogenous sunk cost model

  21. Subject firm Productivity Net PPE 1 0.0885*** (0.0085) 0.0400*** (0.0041) 0.0024 (0.0017) 0.0263*** (0.0048) 0.0030** (0.0012) Decomposing Intangibles R&D Org. capital Other intangibles Top 4 firms (average) PPE, firm #3 -0.0173*** (0.0037) -0.0214*** (0.0037) -0.0042 (0.0027) -0.0174** (0.0078) 0.0011 (0.0015) PPE, firm #4 R&D Org. capital Other intangibles

  22. 2 0.085*** (0.023) 0.053*** (0.004) 0.003 (0.004) 0.009 (0.006) 0.006** (0.003) 3 0.056*** (0.017) 0.051*** (0.004) 0.008 (0.005) -0.001 (0.004) -0.013*** (0.004) -0.014** (0.006) 9140 0.106 Subject firm Productivity Net PPE Decomposing Intangibles Software Stock Acquisitions Advertising Top 4 firms (average) PPE, firm #3 -0.003 (0.006) -0.012*** (0.004) -0.014** (0.007) 0.002 (0.007) 0.003* (0.002) 7706 0.118 PPE, firm #4 Software Stock Acquisitions Advertising Observations R-squared

  23. Magnitude of effect ??? ???= -.014 x 2

  24. Industry level analysis Industry level analysis Own account software vs pre-packaged, contracted BEA data own account software Instrumental variable estimates EU KLEMS software for EU nations

  25. III. Markups & Concentration III. Markups & Concentration

  26. De Loecker & Warzynski (2012), De Loecker & Eeckhout (2017)

  27. Markups Markups High markup industries high displacement Leading firms temporarily earn rents, but are more likely to be displaced

  28. Conclusion Conclusion Schumpeterian competition declined since ~2000 Associated with shift to intangibles / proprietary software Relationship strengthened after 2000 Investment shifted after 2000 Especially own-account software Markups associated with higher dynamism Industry concentration with less

  29. Conclusion: main idea Conclusion: main idea Technology playing a new role Tech disruption

  30. Conclusion: main idea Conclusion: main idea Technology playing a new role Tech disruption Tech suppresses disruption

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