How do Incumbents Respond to the Threat of Entry? Evidence from the Major Airlines

We examine how incumbents respond to the threat of entry by competitors (as distinct from how they respond to actual entry). We look specifically at passenger airlines, using the evolution of Southwest Airlines’ route network to identify particular routes where the probability of future entry rises abruptly. We find incumbents cut fares significantly when threatened by Southwest’s entry. Over half of Southwest’s total impact on incumbent fares occurs before Southwest starts flying. These cuts are only on threatened routes, not those out of non-Southwest competing airports. The evidence on whether incumbents are seeking to deter or accommodate entry is mixed.

Real options modeling and valuation of price adjustment flexibility with an application to the leasing industry

Uncertainty poses not only threats but also opportunities. This study sought to build the scientific foundation for introducing a real options (ROs) methodology for price risk management to the leasing industry. A price risk management that allows for both coping with threats and taking advantage of opportunities. In the leasing industry, fixed rate long-term lease contracts help contract parties stabilize cash flows within volatile markets. The contract\u27s term, however, may be extended long enough that prevent capturing the opportunities of gaining greater profits or reducing expenses. Therefore, the flexibility that enables participants to take advantage of favorable market price is desirable. This discussion is dedicated to the study of three different forms of price adjustments flexibility: 1) single-sided price adjustment flexibility (SSPAF). 2) double-sided price adjustment flexibility (DSPAF) with the preemptive right to exercise. 3) DSPAF with the non-preemptive right to exercise. Each was designed to meet various participants flexibility requirements and budgets. An ROs methodology was developed to model, price, and optimize these flexibility clauses. The proposed approach was then tested in the example of Time Charter (TC) rate contracts from the maritime transport industry. Both the metric and the process for quantifying the benefit of the proposed flexibility clauses are provided. This work provides an alternative approach to the price risk management, which is accessible to all participants in the leasing industry. It is also the starting point in studying the multiple-party, multiple-exercisable price adjustment flexibility. Moreover, both the flexibility designs and the proposed ROs methodology for price risk management are applicable to not only other forms of lease contracts but also to other forms of contract relationships. --Abstract, page iii

Development of a power monitoring and control system to provide demand side management of electric vehicle charging activity.

Due to the recent inflow of Electric Vehicles (EVs) to the automobile market, new concerns have risen with respect to the additional electrical load and the resultant effects on an overloaded electric grid. Either for convenience purposes or possibly necessity due to limited electric range on EVs, some EV owners may desire to charge their EV while at work in addition to charging at home. These forward-thinking daytime charging providers are typically Commercial and Industrial (C&I) electric ratepayers, or other large electric consumers which constitute the majority of businesses, shopping centers, academic campuses and manufacturing facilities. Increased electricity consumption due to EV charging activity results in higher electricity costs due to differences in the billing structures between residential and C&I electric ratepayers. Therefore, it is beneficial to the EVSE charging provider to minimize charging activity around peak demand periods which would result in lower electrical costs overall. A solution is developed that can provide this control without creating a nuisance to electric vehicle owners since EV charging demand is somewhat inelastic due to range anxiety. The primary objective of the research detailed in this dissertation is to develop a novel demand side management system for monitoring the peak demand of commercial time-of-day electric ratepayers that cost effectively predicts and controls electric vehicle charging during peak demand periods. This objective is achieved, therefore confirming the hypothesis that such a system can provide cost and demand benefits to forward-thinking commercial electric ratepayers that provide daytime charging capabilities. This work proposes and evaluates a novel Power Monitoring and Control System (PMCS) that can be implemented at C&I EV charging locations to minimize or eliminate the negative impacts of charging electric vehicles at the workplace in C&I environments. Operation of the PMCS begins by forecasting electrical demand in advance of every 15 minute demand interval throughout the day. The forecast is generated using an artificial neural network and a number of input data streams. Electrical demand has been shown to correlate well with weather data such as temperature and dew point. Therefore, using those measurements along with a date and time stamp, and historical electrical demand measurements, a highly accurate forecast for the following 15-minute demand interval was achieved. From that forecast, the number of EV charging stations that may be active, without the chance of creating new electrical demand peaks, is calculated. Finally, the forecast is then used to properly schedule EV charging activity so that electrical demand peaks can be avoided but charging activity is maximized. The avoidance of charging activity at or near peaks in electrical demand results in lower total electric costs associated with the charging process. The final design was implemented in an EV charging testbed at the University of Louisville and data was collected to verify the operation and performance of the PMCS. With a properly designed scheduling and prioritization control algorithm, increases in electrical demand and associated costs are limited to the error in the forecasting algorithm used for predicting electrical demand levels. The final design of the forecasting algorithm results in a mean absolute percent error of 0.02% to 0.08% in the electrical demand forecast. This corresponds to approximately 3 to 10 kVA of error in electrical demand. Taking this error into account, total cost of charging several EVs is reduced by nearly 90%. Furthermore, for scenarios where there are several more electric vehicles requiring charge than there are charging stations available, several scheduling algorithms are presented in an attempt to minimize the total processing time required for completing all charging transactions

Financial Stability, Deflation, and Monetary Policy

The paper explores the relationship between financial stability, deflation, and monetary policy. A discussion of narrow liquidity, broad liquidity, market liquidity, and financial distress provides the foundation for the analysis. There are two preliminary conclusions. Equity prices are a misleading guide for interest rate policy. Monetary policy tactics protect market liquidity while maximizing the central bank's leverage over longer-term interest rates and aggregate demand. Monetary policy is a fundamental source of deflation and stagnation risk when price stability is fully credible. A central bank can be fooled by its own credibility for low inflation into being insufficiently preemptive in a business expansion. Then monetary policy can be constrained by the zero bound from reducing real interest rates enough in the subsequent contraction. The chain of events that leads to deflation and stagnation can be weakened or broken in a number of places. Monetary policy has the power to preempt deflation and the power to overcome the zero bound to restore prosperity after a deflationary shock. Fiscal policy is likely to be relatively ineffective at best and counterproductive at worst.

A Welfare Analysis of Spectrum Allocation Policies

Analysis of spectrum allocation policies in the economics literature focuses on competitive bidding for wireless licenses. Auctions generating high bids, as in Germany and the UK, are identified as "successful," while those producing lower receipts, as in Switzerland and the Netherlands, are deemed "fiascoes." Yet, even full and costless extraction of license rents does not map directly to social welfare, because spectrum policies creating rents impose social costs. For example, rules favoring monopoly market structure predictably increase license values, but reduce welfare. This paper attempts to shift analytical focus to the relationship between spectrum policy (including license auctions) and efficiency in output markets. In cross-country comparisons of performance metrics in mobile telephone service markets, empirical estimates suggest that countries that auction licenses do not achieve lower prices or higher levels of output than other nations. Rather, countries allocating greater bandwidth to licensed operators and achieving more competitive market structures realize demonstrable social welfare benefits. These gains generally dominate efficiencies associated with license sales. Policies to increase auction revenues, such as reservation prices and subsidies for weak bidders, should be evaluated in this light.

A model of airport slot allocation with posted prices

In this paper, we study the impact of the introduction of posted prices in the slot allocation process currently in use at congested airports in most European countries. In particular, we show that if the airport is initially saturated, while low level of slot prices entail no response from the airlines, requests for slots ”suddenly and violently” drop when the price reaches a certain threshold. In general, there is therefore no market clearing price for airport slots. We also present a dynamic model which highlights how the current grandfather rule - stating that slots used today are kept in the future - generates baby-sitting, that is airlines requiring and using slots today just because they expect them to be profitable in the future.Capacity-constrained competition, airport slots

The impact of horizontal mergers on rivals: Gains to being left outside a merger

It is commonly perceived that firms do not want to be outsiders to a merger between competitor firms. We instead argue that it is beneficial to be a non-merging rival firm to a large horizontal merger. Using a sample of mergers with expert-identification of relevant rivals and the event-study methodology, we find rivals generally experience positive abnormal returns at the merger announcement date. Further, we find that the stock reaction of rivals to merger events is not sensitive to merger waves; hence, 'future acquisition probability' does not drive the positive abnormal returns of rivals. We then build a conceptual framework that encompasses the impact of merger events on both merging and rival firms in order to provide a schematic to elicit more information on merger type