The Value Relevance of Earnings and Nonearnings Information in Regulated and Deregulated Markets: The Case of the Airline Industry

This paper examines the valuation effects of earnings and two nonearnings-based measurements (book values and operating cash flow) on security prices of airline companies under two different market structures: regulated and deregulated. The literature lacks empirical evidence in examining the relative importance of earnings and nonearnings accounting-based measurements in regulated and deregulated markets, especially in the airlines industry. We compare coefficient estimates of regressing stock prices on earnings, book value, and cash flow from operations of airline companies during regulated and deregulated times. A control sample of manufacturing companies is also used for supporting inferences from the airline sample’s findings. In a typical regulated market, using cost recovery plus an adequate rate of return on assets, security prices are highly aligned with nonearnings measurements such as the book value. In the airline industry, regulation took the form of guaranteed routes and subsidies to service rural areas, giving rise to a differential effect of both earnings and nonearnings measurements. Under deregulation, airline firms operate in highly competitive markets with large airline firms enjoying the benefits of economy of scale and service diversification. Thus, the asset capitalization (book value), cash flow, and operational efficiencies (earnings) would be major indicators in the market assessment of the firm’s future profitability and security price. This paper finds that nonearnings measures have higher explanatory power of security prices in regulated times for the airline firms. In deregulated times, although earnings have a stronger relationship with prices, nonearnings measures continued to influence stock price levels, reflecting airline specific economics.

Searching Pareto Optimal Solutions for the Problem of Forming and Restructuring Coalitions in Multi-Agent Systems

Coordination is one of the fundamental research issues in distributed artificial intelligence and multi-agent systems. Current multi-agent coalition formation methods present two limits: First, computation must be completely restarted when a change occurs. Second, utility functions of the agents are either global or aggregated. We present a new algorithm to cope with these limits. The first part of this paper presents a coalition formation method for multi-agent systems which finds a Pareto optimal solution without aggregating the preferences of the agents. This protocol is adapted to problems requiring coordination by coalition formation, where it is undesirable, or not possible, to aggregate the preferences of the agents. The second part of this paper proposes an extension of this method enabling dynamic restructuring of coalitions when changes occur in the system.     

Duration of sudden stop spells: A hazard model approach

Using a hazard‐based duration model, we analyze the determinants of the duration of a period of sudden stop, which is defined as a drop in capital inflow by two standard deviations, for at least two consecutive quarters. The hazard model estimates the conditional probability that the country exits the sudden stop today given that it experienced one until the end of last period. We find that a higher ratio of foreign exchange reserves to short‐term external debt shortens the duration of sudden stops. We also find that a higher global economic growth rate tends to shorten sudden stop spells. Our results are robust to various alternative specifications.     

Modeling preference evolution in discrete choice models: A Bayesian state-space approach

We develop discrete choice models that account for parameter driven preference dynamics. Choice model parameters may change over time because of shifting market conditions or due to changes in attribute levels over time or because of consumer learning. In this paper we show how such preference evolution can be modeled using hierarchial Bayesian state space models of discrete choice. The main feature of our approach is that it allows for the simultaneous incorporation of multiple sources of preference and choice dynamics. We show how the state space approach can include state dependence, unobserved heterogeneity, and more importantly, temporal variability in preferences using a correlated sequence of population distributions. The proposed model is very general and nests commonly used choice models in the literature as special cases. We use Markov chain monte carlo methods for estimating model parameters and apply our methodology to a scanner data set containing household brand choices over an eight-year period. Our analysis indicates that preferences exhibit significant variation over the time-span of the data and that incorporating time-variation in parameters is crucial for appropriate inferences regarding the magnitude and evolution of choice elasticities. We also find that models that ignore time variation in parameters can yield misleading inferences about the impact of causal variables. This paper is based on the first author's doctoral dissertation.     

Regional Trade Agreements in Mediterranean Area: Econometric Analysis by Static Gravity Model

Since the mid-1980s, there was the rise of a new wave of economic regionalism in the world economy with the spread of free trade agreements (FTAs). A key objective of free trade involves developing commercial exchanges between member countries. The gravity model is a vital tool to explain the bilateral trade data against the variables of the relative size of the pair of countries implicated in the trade: distance, common border, and language and models for each of the FTAs. This article focuses on studying the influence of FTAs in the Mediterranean countries in which we integrate the role of regional dummy EU (15), EMU (euro zone), the AMU and AGADIR agreement in trade flows. The use of regional variables are designed to determine whether its FTAs contribute to the creation of trade diversion. This study examines a cross-section and panel of 27 countries for 1980–2011. The results show the existence of a strong relationship between the factors of FTAs and trade flows.