Relevant Degree Programs
Graduate Student Supervision
Doctoral Student Supervision (Jan 2008 - May 2019)
This dissertation studies three different topics in estimating air transport demand processes and the formation of oligopolies. Chapter 1 provides an overview of the thesis.Chapter 2 investigates the sensitivity of demand for air travel by singleton passengers, couples, and families. It examines how the demand for air travel by these groups is potentially different. In this study, a compound Poisson structure of the demand of different passenger groups is considered and aggregate demand observations and decompounding techniques are used to estimate demand sensitivity of each group of customers to price, time, season, and the economic cycle. The methodology is applied to Canadian market data and the results indicate there are significant differences among the different groups of customers.In Chapter 3 a new decompounding procedure based on rudimentary number theory is developed. The advantages and disadvantages of this new framework are discussed, and the efficiency of these methodologies for certain class of problems is demonstrated. The framework is capable of decompounding when group sizes are either pairwise co-prime or composed of two elements. Under some conditions, the methodologies are generalized to cases where data are recorded in non-equal intervals. It is also not dependent on a restrictive assumption of having some zero observations that exists in conventional decompounding algorithms such as the Panjer recursion algorithm.Chapter 4 shows how hierarchical decision making and franchising is used as a fine-tuned strategy for brands to both compete aggressively and softly. In a hierarchical decision making process, as a part of long-run plan, the head office of a brand first decides on how many franchises they will grant. At the second stage, the flagships or company owned divisions decide on their level of output and lastly franchises decide how much to produce.We show brands can use this strategy both as a commitment not to compete fiercely with other brands who share the same cost efficiency and to credibly threaten or possibly keep the inefficient brands out of the market. The efficient brands’ incentive to pre-empt the competition is high when either the market size is small or their cost advantage is substantial.
Master's Student Supervision (2010 - 2018)
This paper uses panel regression techniques and trade gravity models to explore the linkages between Open Skies agreement (OSA) signed by the United States and recent bilateral trade development. US bilateral trade in services data is not available; thus only US merchandise trade by air data is used as dependent variable in this paper’s econometric analysis. US merchandise trade by air series has not experienced significant growth since the implementation of numerous Open Skies agreements in 2007. Few studies have analyzed the relationship between OSAs and trade. These provide the motivation for exploring if signing more Open Skies agreements continues to benefit recent US merchandise trade by air development, and if the performance of these policies depends on other macroeconomic factors and on the properties of the agreement itself.Using data between years 2004 and 2009, panel regression models suggest that the performance of Open Skies agreements are not robust to market volatilities. Reductions in air cargo costs and expansions of air markets resulting from OSAs are not strong enough to combat trade declines when the recession hits. On the other hand, free trade agreements exert large, positive influences to US trade by air even during times of economic slowdown. Yet, the duration of the Open Skies agreements and the economic power of the trading partners do influence the performance of these policies. The preferred model specifications are different for exports and imports by air data, which confirms that the performance of OSAs on exports is different from that on imports. Finally, model results indicate that the impact of Open Skies policies on passenger traffic flows indirectly improves US trade by air figures. OSAs have stimulated passenger traffic growth, and model results suggest that lagged passenger traffic is positively related to trade value. Increased business travel opportunities conducted prior to the delivery of the goods help lower information asymmetries and develop trust among the supply chain partners. Combination of these effects aids expansion of trade by air, as well as trade by other modes of transportation.