Apresentação do SET2 - Simpósio

The estimation of “Azul Effect" on the induction of domestic air travel and the impact of the merger of Trip Regional Airline Júlio César Neves Juncioni Alessandro V. M. Oliveira, PHD

GOALS This study keeps the focus on: The Impact of the LCC at the Airport Demand and Routes. The Merger Effects involving Azul and Trip on The Airport Demand.

PANORAMA Regulatory Environment Liberalized Market

Bankruptcy Traditional Airlines No adjustment to the unregulated market

New entrants The emergence of the Low-Cost Carriers

Market concentration Tam and Gol dominant in the market

MOTIVATION Merger between AZUL and TRIP

2006

2007

2008

2009

2010

2011

2012

2013

2014

12000000 10000000 8000000 6000000

Passenger Demand in Viracopos Airport

4000000 2000000 0 2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2015

MOTIVATION AZUL’s entry in Viracopos Airport 2006

2007

2008

2009

2010

2011

2012

2013

2014

12000000 10000000 8000000 6000000

Passenger Demand in Viracopos Airport

4000000

2000000 0 2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2015

CONTRIBUTION  The contribution is to analyze the issue of expansion of the network of a LCC, after a process of acquisition, and its "effect" on passenger demand.

 Moreover, it also contributes by the use of instrumental variables to determine the better estimation for this research.

LITERATURE REVIEW Low Cost = High Impact Vowles (2001) analyzes the Southwest effect in American airports. The author defines the Southwest effect, as being a increased traffic and a reduction in average fares, when southwest enters a market. Abda et. al (2012) In Airports in the LCCs obtain substantial growth, they gain visibility and strengthen its competitive position, further affecting passenger volumes and average rates.

LITERATURE REVIEW Low Cost = High Impact

Pantazis and Liefner (2011) analyzes the issue of LCCS in Airports. The Authors suggest that the airports are willing to attract companies (LCC) to increase "influence area". So airports can attract passengers from cities that are relatively distant. Barret (2004) Airports, however, should have to deal with the LCCs or risk losing market share and, in fact, the total market .

LITERATURE REVIEW Merger Effects: Fageda and Perdiguero (2014) evaluated the effects of a merger in three different airlines, Iberia, one FSA, Clickair (a LCC subsidiary of Iberia) and Vueling, an independent LCC.  Routes affected by the merger process can generate increases or decreases in term of prices and flight frequencies. It depends on the kind of airline involved in the merger.

CONCEPTUAL MODEL Presence/LCC

Presence LCC/Distance

Yield

Demand

Presence/ Regional

Presence Both

Income

HYPOTHESES Hypotheses to be tested: H1- Azul’s entry positively affects the Airport Demand. H2 - The Distance, in terms of routes, is able to positively affect the air travel demand. H3 – The regional airline influenced positively the demand on routes operated at the time of the merger. H4 -The companies, Azul and Trip, on a premerger process, is able to influence positively the demand at the Airport.

Variables Variables

Description of Variables

Passenger Demand (lnPdew)

Daily passenger demand, in log. (explaibed Variable)

lnYield

Ticket price per km, in log. (endogenous regressor)

Average Income(lngminc)

GDP (Gross Domestic Product) per capita, origin and destination, in geometric mean , in log. (exogenous regressor)

Presence of LCC (pres_azu)

Dummy indicative of the presence of air BLUE company

Presence of LCC - Short distance (pr_azu_less300)

Dummy of Presence of LCC in Short Distance, until 300 miles

Presence of LCC -Long Distance (Pr_azu_more1200)

Dummy of Presence of LCC in Short Distance, more than1200 miles

Presence of LCC x Regional (pr_azu_posmertib)

Dummy of presence of the Azul, just only for the routes on which, at the time of the merger, in 2012, the company TRIP was operating.

Presençe Both (pr_azu_posmer2)

Dummy of presence of the Azul, just only for the routes on which, at the time of the merger, contained

Econometric Model ln PdewAP   0  1lnyield   2 lngminc  3 pres_azu   4 pr_azu_less300 

5pr_azu_more1200   6 pr_azu_posmertib   7 pr_azu_posmer2 

 Y sazonality _ month _ m  u m

m

ln PdewCP   0  1lnyield   2 lngminc  3 pres_azu   4 pr_azu_less300 

5pr_azu_more1200   6 pr_azu_posmertib   7 pr_azu_posmer2 

 Y sazonality _ month _ m  u m

m

Data base Panel data, from January 2002 until December 2013. Reporting to ANAC (National Civil Aviation Agency), IPEADATA, etc.

Statistical Tests A complete sequence of Statistical Tests gives the model adopted the best practices found in econometric studies. Tests

AP database

CP database

Unit root

Yes

Yes

Cointegration?

Yes

Yes

Multicollinearity

No

No

Heteroskedasticity*

Yes

Yes

Autocorrelation*

Yes

Yes

Endogeneity of Yield Variable

Implemented the use of instruments for this analysis.

*Heteroskedasticity and Autocorrelation were controlled.

SENSITIVITY ANALYSIS OLS (Ordinary Least Squares) Problems with Autocorrelation and Heterokedascity. It was discarded. 2SLS (Two-Stage Least Squares) It is a variation of the OLS estimator. It was discarded.

GMM2S (Two-Step Generalized Method of Moments) versus LIML (Limited-Information Maximum Likelihood). It was not noted any lack of significance in LIML over GMM2S estimation. So, It was adopted GMM2S like the preferred estimator for its robustness.

Results

Results The result of Lnyield variable, presented the expected sign negative, ie 1% increase in the Yield, causes a decrease of 0.4889% in demand. (Significant at 1%) The income level determined by the income variable, proved according to the literature, that is, presented a positive sign. The 1% increase in the average income of passengers, generates approximately an increase of 0.7729% in demand for air transport and is significant at 1%.

Results The presence of Azul variable informs the entry of LCC company at the airport. It noted an increase in demand at the airport in 0.8150%. Consistent with the findings of Vowles (2001) to analyze the effect Southweast. Therefore similar to the Azul effect found. Long and short routes were not statistical significance by the estimation. It is suggested that the Company LCC focuses its efforts on the routes of average distances between 300 and 1200 miles. A paradigm has not surpassed by Brazilian LCC.

Results With respect to the Company Trip presence (Pres_lccx reg,) in 2012, prior to the merger on routes where only this company was operating.The estimation showed no statistical significance. However, on routes that both Trip and Azul were operating ,in the preacquisition period, there was an increase in demand of 0.1880%, with 5% significance. The effects of the acquisition may have been transmitted by companies even before the final consolidation. This may reflect the interaction between companies (joint efforts). Other facts can have influenced: new routes served by the companies, fares reduction, new consumers attracted by market appeal.

Conclusions Thus, the findings for this study are that the presence of LCC at a secondary airport is able to noticeably increase the demand for passengers.

The short and long routes were not statistically significant, perhaps by too much competition for other modes or caused by not to be an explored market by Brazilian LCC.

Conclusions The pre-acquisition effects were significant only when both Azul and Trip companies were present on the same route. It can be inferred that companies in the pre-merger already availed themselves of some joint strategy, since agreements are previously treated before final disclosure of the acquisition.

References • • • • • • •

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Abda, M. B., Belobaba, P. P., & Swelbar, W. S. (2012). Impacts of LCC growth on domestic traffic and fares at largest US airports. Journal of Air Transport Management, 18(1), 21-25. Barrett, S. D. (2004). How do the demands for airport services differ between full-service carriers and lowcost carriers?. Journal of Air Transport Management, 10(1), 33-39. Elwakil, O. S., & Dresner, M. (2013). Low-cost carriers and Canadian traffic generation at US border airports. Journal of Air Transport Management, 33, 68-72.

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Pantazis, N., & Liefner, I. (2006). The impact of low-cost carriers on catchment areas of established international airports: the case of Hanover Airport, Germany. Journal of Transport Geography, 14(4), 265272.

Vowles, T. M. (2001). The “Southwest Effect” in multi-airport regions. Journal of Air Transport Management, 7(4), 251-258.