Degree awarded (2004): PhDEc, Economics, George Washington University / This research introduces a new theoretical framework for the analysis of access pricing (the prices that networks charge each other for the completion of calls) and the modeling of network interconnection competition. Prior work on two-way access by Armstrong (1998), Laffont, Rey and Tirole (1998), and Carter and Wright (1999), et al has been built on a two-network Hotelling (1929) differentiated competition model applied to network interconnection. The current research develops an alternative approach that is based on a cross-nested logit (CNL) discrete/continuous consumer choice model with a constant elasticity of substitution (CES) calling utility specification. A principal contribution of the new modeling framework is that in addition to being able to analyze interconnection competition among multiple networks, it is designed to incorporate the element of multiple network subscription where consumers may simultaneously subscribed to more than one type of access network. By introducing multiple-network subscription and usage substitution for users subscribed to multiple networks, the analysis allows more general assessments to be made of the impact of access pricing schemes on the degree of competition between interconnected networks. The model is also not restricted to assumptions of homogeneity in calling on the differentiated networks but can incorporate call differentiation according to network type. The model is applied to evaluate the effects of dual network subscription and asymmetric network competition and to assess multi-network competition in an environment served by two mobile networks and a fixed, wireline network. While confirming the results of prior single network subscription analysis, a central finding of the research based on the developed model is that while network competition is intensified when dual network subscription occurs, negotiated access charges between connected networks continue to serve as an instrument of collusion even in cases of non-linear (two-part) consumer tariffs. / Advisory Committee: John Kwoka, Christopher Snyder (Chair), Sumit Joshi

Recent advances in travel demand modeling have concentrated on adding behavioral realism by focusing on an individual’s activity participation. And, to account for trip-chaining, tour-based methods are largely replacing trip-based methods. Alongside these advances and innovations in dynamic traffic assignment (DTA) techniques, however, time-of-day (TOD) modeling remains an Achilles’ heel. As congestion worsens and operators turn to variable road pricing, sensors are added to networks, cell phones are GPS-enabled, and DTA techniques become practical, accurate time-of-day forecasts become critical. In addition, most models highlight tradeoffs between travel time and cost, while neglecting variations in travel time. Research into stated and revealed choices suggests that travel time variability can be highly consequential. This dissertation introduces a method for imputing travel time variability information as a continuous function of time-of-day, while utilizing an existing method for imputing average travel times (by TOD). The methods employ ordinary least squares (OLS) regression techniques, and rely on reported travel time information from survey data (typically available to researchers), as well as travel time and distance estimates by origin-destination (OD) pair for free-flow and peak-period conditions from network data. This dissertation also develops two models of activity timing that recognize the imputed average travel times and travel time variability. Both models are based in random utility theory and both recognize potential correlations across time-of-day alternatives. In addition, both models are estimated in a Bayesian framework using Gibbs sampling and Metropolis-Hastings (MH) algorithms, and model estimation relies on San Francisco Bay Area data collected in 2000. The first model is the continuous cross-nested logit (CCNL) and represents tour outbound departure time choice in a continuous context (rather than discretizing time) over an entire day. The model is formulated as a generalization of the discrete cross-nested logit (CNL) for continuous choice and represents the first random utility maximization model to incorporate the ability to capture correlations across alternatives in a continuous choice context. The model is then compared to the continuous logit, which represents a generalization of the multinomial logit (MNL) for continuous choice. Empirical results suggest that the CCNL out-performs the continuous logit in terms of predictive accuracy and reasonableness of predictions for three tolling policy simulations. Moreover, while this dissertation focuses on time-of-day modeling, the CCNL could be used in a number of other continuous choice contexts (e.g., location/destination, vehicle usage, trip durations, and profit-maximizing production). The second model is a bivariate multinomial probit (BVMNP) model. While the model relies on discretization of time (into 30-minute intervals), it captures both key dimensions of a tour’s timing (rather than just one, as in this dissertation’s application of the CCNL model), which is important for tour- and activity-based models of travel demand. The BVMNP’s ability to capture correlations across scheduling alternatives is something no existing two-dimensional choice models of tour timing can claim. Both models represent substantial contributions for continuous choice modeling in transportation, business, biology, and various other fields. In addition, the empirical results of the models evaluated here enhance our understanding of individuals’ time-of-day decisions. For instance, average travel time and its variance are estimated to have a negative effect on workers’ utilities, as expected, but are not found to be that practically relevant here, probably because most workers are rather constrained in their activity scheduling and/or work hours. However, correlations are found to be rather strong in both models, particularly for home-to-work journeys, suggesting that if models fail to accommodate such correlations, biased application results may emerge. / text

Cette thèse s'articule autour de deux thèmes : l'évaluation monétaire des biens environnementaux et l'innovation en environnement. Si ces deux volets sont traités séparément, ils s'attachent toutefois à contribuer à un objectif commun : la lutte contre le changement climatique. Cette thèse se décline en cinq chapitres. Le premier propose une introduction générale, qui présente les deux thèmes développés, ainsi que leur contribution au défi du changement climatique. En attribuant une valeur pécuniaire aux biens environnementaux, l'évaluation monétaire peut servir la décision publique, non seulement lors de la mise en œuvre de projets pro-environnementaux, mais aussi en aidant é évaluer les dommages causés à l'environnement. L'innovation environnementale peut encourager les transferts de technologies et une croissance plus verte, dans une volonté de développement durable. Les chapitres 2 et 3 s'intéressent aux expériences de choix, en vue d'évaluer le consentement-à-payer pour l'amélioration de la qualité de l'eau de rivières. A partir d'une enquête proposant aux résidents de choisir entre différentes options de gestion pour les rivières de leur voisinage, nous montrons dans le chapitre 2 que ces derniers sont disposés à payer pour une meilleure qualité de l'eau. Nous nous apercevons toutefois que plus de 20% des individus de notre échantillon adoptent un comportement de protestation, c'est-à-dire déclarent un consentement-à-payer nul alors même que leur valeur pour l'eau des rivières est positive. Dans le chapitre 3, nous recourons à un modèle logit emboîté, afin de prendre en compte ce type de comportement. Nous obtenons des consentements-à-payer plus élevés, signe que le modèle utilisé est mieux adapté pour traiter des données comportant des zéros de protestation. Les chapitres 4 et 5 étudient les déterminants de l'innovation en environnement. A partir de données sur les dépôts de brevets et de l'enquête d'opinion du forum économique mondial, le chapitre 4 s'intéresse à l'impact de politiques publiques sur l'innovation en matière de technologies propres dans les domaines de l'eau, de l'air et des déchets. Notre analyse met en évidence le rôle positif sur l'innovation en environnement de la capacité d'innovation globale d'un pays et de la rigueur de ses politiques environnementales. Le chapitre 5 étudie l'influence des collaborations pour la publication d'articles scientifiques sur l'innovation en matière d'énergie éolienne. Nous couplons notre base de données sur les brevets avec une base rassemblant de nombreuses références littéraires dans le domaine de la recherche scientifique. Nous montrons que les transferts de connaissance entre les pays membres et non membres de l'OCDE dans le domaine éolien contribuent à améliorer la capacité d'innovation des pays non membres de l'OCDE. / This dissertation is interested in two areas of the environmental economics field: monetary valuation of environmental goods and services and environmental innovation. Even if those two fields are studied separately in this dissertation, they both aim at contributing to a common objective: fight against climate change. This dissertation ranges into five chapters. The first one is a general introduction, which depicts the two fields of the dissertation and their relevance towards climate change. Environmental valuation serves public decision through monetary valuation of environmental goods. This is useful not only for the implementation of projects directed to environmental protection, but also for the quantification of environmental damages. Environmental innovation may encourage technological transfers, but also a greener growth, in a will that our societies develop themselves following a sustainable path. Chapters 2 and 3 are interested in the choice experiments method in order to value local residents’ willingness-to-pay for water quality improvements at a specific river basin in France. Using a choice experiment with different management regimes for the river basin, we find that residents are willing-to-pay for an improved water quality. Despite this positive result, we observe a significant proportion (20%) of protest bids in our sample. Protest bids are respondents that state a zero willingness-to-pay, even though their true value for the good is positive. In order to take into account the existence of protest bids, we estimate a cross-nested logit model in chapter 3. We then obtain larger willingness-to-pay, which proves that the cross-nested logit model best fits the peculiarity of our data. Chapters 4 and 5 try to identify the drivers of environmental innovation. Using world patent data and data from the world economic forum survey, we study the impact of environmental public policies on innovation in clean technologies directed to water and air pollution, and waste. We find that both general innovative capacity and environmental policy stringency have a positive role on environment-related innovation. Chapter 5 looks at the influence of co-authorship of scientific publications on wind energy-related innovation. We use both the world patent database and the “Scopus” database, which contains lots of scientific literature references. We highlight the existence of knowledge spillovers between OECD and NON-OECD countries. Therefore, we show that knowledge transfers, regarding wind energy-related innovation, between OECD and NON-OECD countries contribute to improve NON-OECD countries' innovative capacity.