THE PRICE EFFECTS OF ELIMINATING POTENTIAL

Transcription

1 THE PRICE EFFECTS OF ELIMINATING POTENTIAL COMPETITION: EVIDENCE FROM AN AIRLINE MERGER John Kwoka Evgenia Shumilkina Northeastern University

2 INTRODUCTION Mergers are very common phenomenon in market economies Economics teaches that mergers can result in efficiencies, but also create or enhance market power Reduction in numbers of direct competitors enhances ability to coordinate on price Some literature finds evidence of higher prices from mergers Several studies in US airline markets Hurdle et al (1989) Kim and Singal (1993) Reasons are lots of markets, data availability, prominence and importance None of these studies examines the effect of a merger that t reduces or eliminates i potential ti competition

3 ROUTE/CARRIER CONFIGURATIONS Consider possible configurations of carriers serving market A-B Carriers 1 and 2 are incumbents Studies already examine effects of merger Carriers 3 and 4 are potential entrants Have feed traffic, ground infrastructure, information Would seem carrier 3 better positioned than carrier 4 Past studies of airfares find number of such potential entrants matter Regression models on fares include variable for that number Morrison and Winston report price effect due to one additional incumbent is.44% while effect of one additional potential ti entrant is.15%

4 FOCUS OF STUDY Focus of this study is not price effect of merger between carrier 1 and carrier 2 Nor is it simply to count number of well-positioned nonincumbents Rather, concern is with effect of merger between carrier 1 and carrier 3 or 4 Concentration among incumbents (carriers 1 and 2) does not change Number of potential entrants falls, but more importantly, a particular potential entrant is eliminated No reason its effect captured by simple reduction in number of potential entrants Actual merger of network carriers creates pattern of both actual and potential competition effects In sense, we are redoing standard airline merger models In reality, our model built with focus on those routes where carrier alignment allows for measurement of effect of elimination

5 The US Air-Piedmont Merger Paper examines merger of USAir and Piedmont Large regionally based network carriers with both overlap and adjacency Announced intent to merge in January 1987 Finally integrated operations in August 1989 Two prior studies of effects of this merger on prices on routes served by both Morrison (1996) finds prices rose 4.4% immediately, 22.8% in longer run Peters (2006) calculates l fare increases of %

6 DATA AND MODEL Data from DOT DB1A, Origin and Destination Survey Quarterly, 10% ticket sample Examine four quarters before merger ( ), four after ( ) Adopt standard conventions Exclude foreign and non-continental US travel Use only round trip tickets Routes assumed non-directional Exclude tickets with more than one stop between O & D Exclude routes with fewer than 30 recorded passengers per quarter Exclude tickets with anomalous prices (less than $10, greater than $2,000) Exclude first class and business travel Result is database of 22,000 observations for each quarter

7 CATEGORIZATION OF MERGING CARRIERS ON ROUTES Routing alternatives for USAir and Piedmont Both are incumbents One is incumbent, other a potential competitor One is incumbent, other neither incumbent nor potential competitor Neither is incumbent Potential competitor defined in usual way Carrier serving one or both endpoints of route, but not route Distinguish one vs. two endpoint serving carriers

8 ROUTE INTERACTIONS BETWEEN USAIR AND PIEDMONT Definition No. of Routes Both USAir and Piedmont present 807 Either USAir or Piedmont present, other is potential entrant 1,443 Incumbent rivals to USAir and Piedmont 6,377 Unrelated 13,005 TOTAL 21,673

9 MODEL AND ESTIMATION Complete model given by LNFARE it = α 1 + α 2 RouteType i + α 3 Post:RouteType it + α 4 POST:MERGER t + α 5 DISTANCE i + α 6 POP it + α 7 HHI it + α 8 POT-ENTS it + α 9 TOURIST i + α 10 SLOT i + α 11 HUB i + μ it Where RouteType can be TW0-ZERO, i.e. both incumbents ONE-ONE, for one incumbent, one potential entrant ONE-ZERO, where one incumbent, other not present RIVALS, for other carriers on routes where USAir and Piedmont competed

10 Each variable interacted with POST for quarters following merger Also POST-MERGER And DISTANCE POP HHI POT-ENTS TOURIST SLOT HUB Essentially difference-in-difference i approach Estimation uses both pooled OLS and fixed effects model Pooled OLS allows inclusion of other control variables Fixed effects controls for other, unobserved influences Hausman test favors fixed effects over random effects

11 BENCHMARK RESULTS Variable Pooled OLS DISTANCE.308 (217.1) POP (27.5) SLOTS.045 (15.9) TOURIST (61.2) HUB.120 (48.6) HHI.023 (11.5) POT-ENTS (38.8) 8) TWO-ZERO (1.90) ONE-ONE.038 (8.55) Variable ONE-ZERO Pooled OLS (8.52) RIVALS.059 (23.6) POST: MERG.118 (56.9) POST: TWO-ZERO.090 (12.0) POST: ONE-ONE.050 (8.18) POST: ONE-ZERO.008 (.25) POST: RIVALS (14.2) CONSTANT 3.73 (132.6) ADJ-R F 4123

12 IMPLICATIONS Effect of eliminating either carrier as direct competitor on a route is 9.0% Effect of eliminating either as a potential competitor is 5.0% Significantly different from elimination of actual competitor (t=4.33) Effect of USAir or Piedmont as potential competitor on other s route larger than from elimination of any other potential competitor (1.9%) Significantly different (t=11.2)

13 BENCHMARK RESULTS REGRESSION RESULTS ON FARES Variable POP (11.6) HHI.057 (20.3) POT-ENTS (17.1) POST: MERG.117 (54.8) POST: TWO-ZERO.102 (18.9) POST: ONE-ONE.060 (13.6) POST: ONE-ZERO (.30) POST: RIVALS (18.7) CONSTANT (22.8) ADJ-R F 1001 Fixed Effects

14 These are key results Establish importance of potential competition as a constraint Importance of eliminating such a constraint via merger Next we examine series of refinements to see if effects differ for: Large vs. small direct competitors Large vs. small potential competitors Varying level of market concentration One endpoint vs. two endpoint serving potential competitors USAir vs. Piedmont as incumbent Will report only fixed effects ec results s

15 SMALL VS. LARGE COMPETITORS Some studies contend that competitors with small market share matter less That would imply pytheir elimination by merger should matter less, as well We distinguish cases where USAir or Piedmont were less than 5% vs. more than 5% There are 458 out of 807 routes where incumbent is small competitor Similarly, possible that small presence at endpoint makes potential entrant matter less We distinguish cases where either USAir or Piedmont as potential entrant had less than 2% share of endpoint traffic vs. where they had more than 2% There are 239 out of 1443 routes where one potential ti competitor was small

16 SMALL VS. LARGE COMPETITORS REGRESSION RESULTS ON FARES Variable Fixed Effects POP (11.6) HHI.057 (20.3) POT-ENTS (17.0) POST: MERG.117 (54.8) POST: TWO-ZERO.121 (15.1) POST: SM-ACTUAL.087 (12.7) POST: ONE-ONE.062 (12.8) POST: SM- POTENTIAL.054 (5.07) POST: ONE-ZERO (.30) POST: RIVALS (18.7) CONSTANT (22.8) ADJ-R F 802

17 IMPLICATIONS Effect of eliminating USAir or Piedmont when one was small actual competitor is 8.7% Smaller than effect of eliminating either as a large competitor: 12.1% Difference is statistically significant (t=3.24) Effect of eliminating either carrier as potential competitor is 5.4% when small vs. 6.2% otherwise Difference is not statistically significant (t =.69) Only presence matters, not size Given magnitudes and relative importance of routes, calculate consumer effects of merger as $125 M on routes where both were competitors $49 M on routes where one was incumbent, other potential competitor

18 VARIATION IN EFFECTS BY LEVEL OF CONCENTRATION Elimination of competitor (actual or potential) likely different depending on concentration Where industry fragmented, loss of competitor may not matter so much Where industry already highly concentrated, may already achieve higher price We test for variation in effect of eliminating competitors depending on HHI Divide data into quartiles by level of HHI Rerun basic model Table reports only key coefficients

19 VARIATION IN EFFECTS BY CONCENTRATION KEY COEFFICIENT ESTIMATES: REGRESSIONS BY HHI QUARTILE HHI Quartile FIXED EFFECTS POST: TWO-ZERO POST: ONE-ONE , OVERALL

20 IMPLICATIONS Largest price effect from eliminating actual competitor in middle ranges of HHI When HHI high, price already elevated When HHI low, competition dominates elimination i Largest price effect from eliminating potential competitor also in middle ranges of HHI Reasons analogous

21 ONE ENDPOINT VS. TWO ENDPOINT POTENTIAL ENTRANTS REGRESSION RESULTS ON FARES: ONE VS. TWO ENDPOINTS VARIABLE POP (11.6) HHI.057 (20.3) POT-ENTS (17.1) POST: MERG.117 (54.8) POST: TWO-ZERO.121 (15.1) POST: SM-ACTUAL.087 (12.7) POST:ONE -1END.061 (12.2) POST: ONE-2END.059 (6.55) POST: ONE-ZERO (.30) POST: RIVALS (18.7) CONSTANT (22.8) Adj-R F 802 FIXED EFFECTS

22 EFFECTS BY CARRIER REGRESSION RESULTS ON FARES: USAIR VS. PIEDMONT VARIABLE POP (11.5) HHI.057 (20.3) POT-ENTS (17.1) POST: MERG.117 (54.7) POST: TWO-ZERO.121 (15.1) POST: SM-ACTUAL.087 (12.7) POST: US-PD.068 (11.5) POST: PD-US.051 (8.21) POST: ONE-ZERO (.30) POST: RIVALS (18.7) CONSTANT (22.7) Adj-R F 802 FIXED EFFECTS

23 CONCLUSIONS Effect of eliminating gpotential competitor is significant Also substantial in this case Should be important consideration in merger analysis