87 research outputs found

    Constrained nested logit model: formulation and estimation

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    Modeling Absolute and Relative Cost Differences in Stochastic User Equilibrium Problem

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    AbstractThis paper aims to develop a hybrid closed-form route choice model and the corresponding stochastic user equilibrium (SUE) to alleviate the drawbacks of both Logit and Weibit models by simultaneously considering absolute cost difference and relative cost difference in travelers’ route choice decisions. The model development is based on an observation that the issues of absolute and relative cost differences are analogous to the negative exponential and power impedance functions of the trip distribution gravity model. Some theoretical properties of the hybrid model are also examined, such as the probability relationship among the three models, independence from irrelevant alternatives, and direct and indirect elasticities. To consider the congestion effect, we provide a unified modeling framework to formulate the Logit, Weibit and hybrid SUE models with the same entropy maximization objective but with different total cost constraint specifications representing the modelers’ knowledge of the system. With this, there are two ways to interpret the dual variable associated with the cost constraint: shadow price representing the marginal change in the entropy level to a marginal change in the total cost, and dispersion/shape parameter representing the travelers’ perceptions of travel costs. To further consider the route overlapping effect, a path-size factor is incorporated into the hybrid SUE model. Numerical examples are also provided to illustrate the capability of the hybrid model in handling both absolute and relative cost differences as well as the route overlapping problem in travelers’ route choice decisions

    Short-term household income mobility before and after the Great Recession: A four-country study

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    This paper analyses short-term intra-generational income mobility in France, Italy, Spain and the UK by exploiting the longitudinal component of EU-SILC for the periods 2005-2008 and 2012-2015. We investigate whether and to what extent the ability of households to move along the income distribution changed after the 2008 crisis and whether heterogeneities among countries exist. For this purpose, we employ mobility indexes and transition matrices as well as estimation of a 2SLS regression and of a dynamic ordered probit with random effects. Overall, indexes and transition matrices point to a decrease of mobility in the aftermath of the crisis. The econometric analyses suggest both the existence of a convergence process of incomes and state dependence of current and lagged income in both periods. We also observe sluggish income convergence and lower upward mobility in the second period. Among the microeconomic drivers, education and employment status are positive determinants of mobility. Finally, our results confirm crosscountry heterogeneity

    The Siting Of Multi-User Inland Intermodal Container Terminals In Transport Networks

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    Almost without exception, cargo movements by sea have their origins and destinations in the hinterlands and efficient land transport systems are required to support the transport of these cargo to and from the port. Furthermore, not all goods produced are exported or all goods consumed are imported. Those produced and consumed domestically also require efficient transport to move them from their production areas to areas of consumption. The use of trucks for these transport tasks and their disproportionate contribution to urban congestion and harmful emissions has led governments, transport and port authorities and other policy-makers to seek for more efficient and sustainable means of transport. A promising solution to these problems lies in the implementation of intermodal container terminals (IMTs) that interface with both road and rail or possibly inland waterway networks to promote the use of intermodal transport. This raises two important linked questions; where should IMTs be located and what will be their likely usage by individual shippers, each having a choice of whether or not to use the intermodal option. The multi-shipper feature of the problem and the existence of competing alternative modes means the demand for IMTs are outcome of many individual mode choice decisions and the prevailing cargo production and distribution patterns in the study area. This thesis introduces a novel framework underpinned by the principle of entropy maximisation to link mode choice decisions and variable cargo production and distribution problems with facility location problems. The overall model allows both decisions on facility location and usage to be driven by shipper preferences, following from the random utility interpretation of the discrete choice model. Several important properties of the proposed model are presented as propositions including the demonstration of the link between entropy maximisation and welfare maximisation. Exact and heuristic algorithms have been also developed to solve the overall problem. The computational efficiency, solution quality and properties of the heuristic algorithm are presented along with extensive numerical examples. Finally, the implementation of the model, illustration of key model features and use in practice are demonstrated through a case study

    Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

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    The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

    An Equilibrium Model of Sorting in an Urban Housing Market: The Causes and Consequences of Residential Segregation

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    This paper presents a new equilibrium framework for analyzing economic and policy questions related to the sorting of households within a large metropolitan area. We estimate the model using restricted-access Census data that precisely characterize residential and employment locations for households the San Francisco Bay Area, yielding accurate measures of preferences for a wide variety of housing and neighborhood attributes across different types of household. We use these estimates to explore the causes and consequences of racial segregation in general equilibrium. Our results indicate that, given the preference structure of households in the Bay Area, the elimination of racial differences in income and wealth would significantly increase the residential segregation of each major racial group, as the equalization of income leads, for example, to the formation of new wealthy, segregated Black and Hispanic neighborhoods. We also provide evidence that sorting on the basis of race itself (whether driven by preferences or discrimination) leads to large reductions in the consumption of housing, public safety, and school quality by Black and Hispanic households.Segregation, Sorting, Housing Markets, Locational Equilibrium, Residential Choice, Discrete Choice

    Multi-Fidelity Gaussian Process Emulation And Its Application In The Study Of Tsunami Risk Modelling

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    Investigating uncertainties in computer simulations can be prohibitive in terms of computational costs, since the simulator needs to be run over a large number of input values. Building a statistical surrogate model of the simulator, using a small design of experiments, greatly alleviates the computational burden to carry out such investigations. Nevertheless, this can still be above the computational budget for many studies. We present a novel method that combines both approaches, the multilevel adaptive sequential design of computer experiments (MLASCE) in the framework of Gaussian process (GP) emulators. MLASCE is based on the two major approaches: efficient design of experiments, such as sequential designs, and combining training data of different degrees of sophistication in a so-called multi-fidelity method, or multilevel in case these fidelities are ordered typically for increasing resolutions. This dual strategy allows us to allocate efficiently limited computational resources over simulations of different levels of fidelity and build the GP emulator. The allocation of computational resources is shown to be the solution of a simple optimization problem in a special case where we theoretically prove the validity of our approach. MLASCE is compared with other existing models of multi-fidelity Gaussian process emulation. Gains of orders of magnitudes in accuracy for medium-size computing budgets are demonstrated in numerical examples. MLASCE should be useful in a computer experiment of a natural disaster risk and more than a mere tool for calculating the scale of natural disasters. To show MLASCE meets this expectation, we propose the first end-to-end example of a risk model for household asset loss due to a possible future tsunami. As a follow-up to this proposed framework, MLASCE provides a reliable statistical surrogate to a realistic tsunami risk assessment under a restricted computational resource and provides accurate and instant predictions of future tsunami risks

    Embedding Decision Heuristics in Discrete Choice Models: Assessing the MERITS of Majority of Confirming Dimensions, Extremeness Aversion, and Reference Revision

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    Contrary to the usual assumption of fixed, well-defined preferences, it is increasingly evident that individuals are likely to approach a choice task using decision heuristics that depend on the choice environment. These include heuristics defined by the local choice context, such as the gains or losses of an attribute value relative to the other attributes. Recent empirical findings also demonstrate that previous choices and previously encountered choice tasks can affect the current choice outcome, indicating a form of inter-dependence across choice sets. A number of these heuristics, namely the majority of confirming dimensions (MCD), the extremeness aversion and the reference revision heuristics, are analysed. These heuristics are not new, but their application, using the discrete choice modelling framework, to the transportation field has only barely begun. In particular, arising from the extremeness aversion heuristic, three models are discussed. The first is a recently developed model of context dependence known as the random regret minimisation (RRM) model. The second model is a non-linear utility model that makes reference to the worst attribute level in a choice set. The third model is a “relative advantage maximisation” (RAM) model, with an updated version of the existing RAM model introduced in this thesis. All these models are compared against one another and with the standard random utility maximisation (RUM) model. The results strongly indicate that incorporating context dependency into existing models should be a key consideration for the practitioner. Moreover, having identified some heuristics of special interest, the role of multiple heuristics in choice behaviour is also analysed. Interestingly, the heuristics themselves can be embedded directly into the utility functions by means of heuristic weighting functions, which weight the contribution of each heuristic to overall utility. The thesis examines the validity of such an approach

    Non-Extensive Entropy Econometrics for Low Frequency Series

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    The second edition of Non-extensive Entropy Econometrics for Low Frequency Series provides a new and robust power-law-based, non-extensive entropy econometrics approach to the economic modelling of ill-behaved inverse problems. Particular attention is paid to national account-based general equilibrium models known for their relative complexity. This new proposed approach could extend the frontier of theoretical and applied econometrics
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