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Author: Jan Rouwendal
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
An emerging quantitative spatial economics literature models commuting interactions by a gravity equation that is mathematically equivalent to a multinomial logit model. This model is widely viewed as restrictive because of the independence of irrelevant alternatives (IIA) property that links substitution behavior in response to changes in the attractiveness of choice alternatives to choice probabilities in a mechanistic way. This is relevant for counterfactual analysis. In this paper we examine the appropriateness of the commuting model from a theoretical as well as an empirical point of view. We show that conventional specification tests of the multinomial logit model are of limited use when alternative specific constants are used, as is common in the recent literature, and offer no information with respect to the validity of IIA. In particular, we show that maximum likelihood estimation of relevant nested logit model is impossible because the crucial parameters are not identified. We discuss cross-nested and mixed logit as alternatives. We argue that a comparison between predicted and actual changes in commuting flows in response to a change in the attractiveness of choice alternatives provides a more informative test for the validity of the multinomial logit model for commuting interaction and report the results of such a test – as well as others – for data referring to Copenhagen.
Author: Jan Rouwendal
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
An emerging quantitative spatial economics literature models commuting interactions by a gravity equation that is mathematically equivalent to a multinomial logit model. This model is widely viewed as restrictive because of the independence of irrelevant alternatives (IIA) property that links substitution behavior in response to changes in the attractiveness of choice alternatives to choice probabilities in a mechanistic way. This is relevant for counterfactual analysis. In this paper we examine the appropriateness of the commuting model from a theoretical as well as an empirical point of view. We show that conventional specification tests of the multinomial logit model are of limited use when alternative specific constants are used, as is common in the recent literature, and offer no information with respect to the validity of IIA. In particular, we show that maximum likelihood estimation of relevant nested logit model is impossible because the crucial parameters are not identified. We discuss cross-nested and mixed logit as alternatives. We argue that a comparison between predicted and actual changes in commuting flows in response to a change in the attractiveness of choice alternatives provides a more informative test for the validity of the multinomial logit model for commuting interaction and report the results of such a test – as well as others – for data referring to Copenhagen.
Author: Kenneth Train
Publisher: Cambridge University Press
ISBN: 0521766559
Category : Business & Economics
Languages : en
Pages : 399
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Book Description
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Author: Moshe Ben-Akiva
Publisher: MIT Press
ISBN: 0262536404
Category : Architecture
Languages : en
Pages : 414
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Book Description
Discrete Choice Analysis presents these results in such a way that they are fully accessible to the range of students and professionals who are involved in modelling demand and consumer behavior in general or specifically in transportation - whether from the point of view of the design of transit systems, urban and transport economics, public policy, operations research, or systems management and planning. The methods of discrete choice analysis and their applications in the modelling of transportation systems constitute a comparatively new field that has largely evolved over the past 15 years. Since its inception, however, the field has developed rapidly, and this is the first text and reference work to cover the material systematically, bringing together the scattered and often inaccessible results for graduate students and professionals. Discrete Choice Analysis presents these results in such a way that they are fully accessible to the range of students and professionals who are involved in modelling demand and consumer behavior in general or specifically in transportation - whether from the point of view of the design of transit systems, urban and transport economics, public policy, operations research, or systems management and planning. The introductory chapter presents the background of discrete choice analysis and context of transportation demand forecasting. Subsequent chapters cover, among other topics, the theories of individual choice behavior, binary and multinomial choice models, aggregate forecasting techniques, estimation methods, tests used in the process of model development, sampling theory, the nested-logit model, and systems of models. Discrete Choice Analysis is ninth in the MIT Press Series in Transportation Studies, edited by Marvin Manheim.
Author: David A. Hensher
Publisher: Routledge
ISBN: 1351140744
Category : Business & Economics
Languages : en
Pages : 280
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Book Description
Originally published in 1981. Discrete-choice modelling is an area of econometrics where significant advances have been made at the research level. This book presents an overview of these advances, explaining the theory underlying the model, and explores its various applications. It shows how operational choice models can be used, and how they are particularly useful for a better understanding of consumer demand theory. It discusses particular problems connected with the model and its use, and reports on the authors’ own empirical research. This is a comprehensive survey of research developments in discrete choice modelling and its applications.
Author: Timothy Brathwaite
Publisher:
ISBN:
Category :
Languages : en
Pages : 221
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Book Description
Every day, decision-makers make choices among finite and discrete sets of alternatives. For example, people decide whether to walk, bike, take transit, or drive to work; shoppers decide which of the available brands of toothpaste to buy; and firms decide which vacant buildings they will rent for office space. Across these disparate domains, discrete choice models mathematically represent the procedures that analysts believe decision-makers are using to make such choices. Historically, the field of discrete choice modeling grew mainly out of economics, and this lineage has had long-lasting methodological ramifications. In particular, despite the great mathematical similarity between discrete choice models and models in statistics, machine learning, and causal inference, discrete choice research remains mostly siloed, seldom drawing from or contributing to methods in these related disciplines. In this dissertation, we help demolish the methodological silo around discrete choice re- search. Drawing from recent techniques in statistics, machine learning, and causal inference, we remove substantive limitations on the decision-making processes that could be be represented and predicted with previously available discrete choice methods. At the same time, by addressing concerns of discrete choice modelers, we make methodological contributions to the fields of statistics and machine learning, and we identify future research areas where discrete choice modelers are well suited to advancing the state of the art in causal inference. Importantly, the methodological advances described above were not divorced from to- day’s societal concerns. Given that more and more government agencies are (unsuccessfully) attempting to raise bicycle commuting rates in their jurisdictions, we guide our interactions with the statistics, machine learning, and causal inference literatures by trying to more accurately model an individual’s choice of commuting by bicycle. In particular, we use parametric link functions from statistics to better model the adoption and abandonment of bicycling. From machine learning, we use decision trees to represent the non-compensatory decision protocols that individuals appear to follow when deciding whether to commute by bicycle, and we use diagrams from the causal inference literature to gain insight into how we can bet- ter model the effects of bike lane investments on bicycle commute mode shares. All together, we not only make methodological contributions to the fields of discrete choice, statistics, machine learning, and causal inference, but we contribute to the efforts of transportation planners and modelers who are trying to make our cities and regions more sustainable and environmentally friendly. The methods developed in this dissertation have applications to strategic bicycle planning, helping analysts understand when certain interventions are not enough to cause people to abandon non-bicycle modes of travel at the desired rates and what alternative interventions might be more effective. In total, the specific contributions of this dissertation are the following: 1. We create a new spatial unit of analysis (the zone of likely travel) for the incorporation of roadway-level variables such as presence and type of bicycle infrastructure, roadway slopes, and traffic speeds into mode choice models. 2. We propose and demonstrate the novel use decision-tree methods for directly including roadway-level variables in mode choice models. 3. We create a new class of closed-form, finite-parameter, multinomial choice models that avoid an undesirable symmetry property that we describe in Chapter 3. 4. We create a procedure for using this new class of models to extend many existing binary choice models to the multinomial setting for the first time. 5. We create methods for creating new, symmetric and asymmetric, binary choice models. 6. We provide a microeconomic framework for interpreting decision trees by showing that decision trees represent a non-compensatory decision rule known as disjunctions-of-conjunctions and that such rules generalize many of the non-compensatory rules used in the discrete choice literature so far. 7. We propose and estimate the first bayesian model tree, thereby combining decision trees and discrete choice models in the first two-stage, semi-compensatory model that jointly: a) uses disjunctions-of-conjunctions for the choice-set generation stage, b) allows for context-dependent preference heterogeneity in the choice stage, and c) quantifies analyst uncertainty in the estimated disjunctions-of-conjunctions 8. We identify techniques such as the use of causal diagrams that can be borrowed from the causal inference literature to improve the ability of discrete choice modelers to predict outcomes under external changes or policy interventions such as investing in on-street bicycle lanes. 9. We identify areas of the causal inference literature that can be improved through the incorporation of techniques from discrete choice or through the application of causal inference techniques that are very relevant to discrete choice modellers yet only infrequently researched by traditional causal inference researchers. Through this dissertation, we empirically demonstrate most of our contributions using commute mode choice data from the San Francisco Bay Area. In every case, we found that the new models developed as part of this dissertation fit our data better than traditional discrete choice models. These results were stable across all measures of fit that were used, whether the measures were in-sample or out-of-sample, frequentist or bayesian. Beyond fit, all of our new models also proved to be qualitatively different than traditional discrete choice methods. Our new models provided insights and forecasts that both made more sense and were more accurate than their traditional counterparts. Finally, our contributions related to causal inference are the only items from the list above without empirical demonstrations. Instead, these contributions are bolstered by substantial literature review, discussion, and thought exercises that show the (general and bicycle specific) benefits of merging discrete choice and causal inference techniques.
Author: Reggiani, Aura
Publisher: Edward Elgar Publishing
ISBN: 1839100591
Category : Social Science
Languages : en
Pages : 640
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Book Description
This ground-breaking Handbook presents a state-of-the-art exploration of entropy, complexity and spatial dynamics from fundamental theoretical, empirical and methodological perspectives. It considers how foundational theories can contribute to new advances, including novel modeling and empirical insights at different sectoral, spatial and temporal scales.
Author: William A. Brock
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
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Book Description
This paper provides an analysis of aggregate behavioral outcomes when individual utility exhibits social interaction effects. We study generalized logistic models of individual choice which incorporate terms reflecting the desire of individuals to conform to the behavior of others in an environment of noncooperative decisionmaking. Laws of large numbers are generated in such environments. Multiplicity of equilibria in these models, which are equivalent to the existence of multiple self-consistent means for average choice behavior, will exist when the social interactions exceed a particular threshold. Local stability of these multiple equilibria is also studied. The properties of the noncooperative economy are contrasted with the properties of an economy in which a social planner determines the set of individual choices. The model is additionally shown to be well suited to explaining a number of empirical phenomena, such as threshold effects in individual behavior, ethnic group fixed effects of income equations, and large cross-group differences in binary choice behavior.
Author: Charlie Karlsson
Publisher: Edward Elgar Publishing
ISBN: 178643248X
Category : Business & Economics
Languages : en
Pages : 349
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Book Description
As a consequence of globalization, news, ideas and knowledge are moving quickly across national borders and generating international spillovers. So too, however, are economic and financial crises. Combining a variety of methods, concepts and interdisciplinary approaches, this book provides an in-depth examination of these structural changes and their impact. Assessing the implications of globalization for businesses and sectors, chapters focus on the interdependencies between different economic and political layers, and explore topics such as human capital, creativity, innovation, networks and collaboration.
Author: Antonio Páez
Publisher: Springer Nature
ISBN: 303120719X
Category : Mathematics
Languages : en
Pages : 349
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Book Description
This book is designed as a gentle introduction to the fascinating field of choice modeling and its practical implementation using the R language. Discrete choice analysis is a family of methods useful to study individual decision-making. With strong theoretical foundations in consumer behavior, discrete choice models are used in the analysis of health policy, transportation systems, marketing, economics, public policy, political science, urban planning, and criminology, to mention just a few fields of application. The book does not assume prior knowledge of discrete choice analysis or R, but instead strives to introduce both in an intuitive way, starting from simple concepts and progressing to more sophisticated ideas. Loaded with a wealth of examples and code, the book covers the fundamentals of data and analysis in a progressive way. Readers begin with simple data operations and the underlying theory of choice analysis and conclude by working with sophisticated models including latent class logit models, mixed logit models, and ordinal logit models with taste heterogeneity. Data visualization is emphasized to explore both the input data as well as the results of models. This book should be of interest to graduate students, faculty, and researchers conducting empirical work using individual level choice data who are approaching the field of discrete choice analysis for the first time. In addition, it should interest more advanced modelers wishing to learn about the potential of R for discrete choice analysis. By embedding the treatment of choice modeling within the R ecosystem, readers benefit from learning about the larger R family of packages for data exploration, analysis, and visualization.
Author: Junyi Zhang
Publisher: Elsevier
ISBN: 0128162848
Category : Business & Economics
Languages : en
Pages : 452
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Book Description
Transport and Energy Research: A Behavioral Perspective deals with the transport issues associated with energy from a behavioral perspective in an interdisciplinary and systematic way. Existing transport and energy research has focused on technologies and energy efficiency; however, more efficient technologies do not necessarily lead to energy reduction. Unfortunately, very limited behavioral research can be found in the literature. This book covers major transport modes in major countries. It emphasizes the importance of researching the behaviors of not only transport and energy service users, but also transport and energy service providers, policy makers, organizations, company managers, and other stakeholders who are involved in and/or affected by transport and energy policies. It not only overviews the history of relevant research and presents new developments but also extensively discusses the future research issues. Various findings are summarized for reducing energy consumption from a behavioral perspective. This book provides readers with behavioral insights into more effective policymaking. Behavioral interventions are recommended as a key policy instrument for reducing energy consumption in a sustainable way. It provides policy makers with comprehensive insights into making more effective policies over the whole process of policymaking. The book can serve as a handbook for researchers and a textbook for graduate students in the fields of transport, energy, environment, planning, public policy, behavioral studies, and so on. - Examines transport and domestics issues associated with energy from a behavioral perspective in both an interdisciplinary and comprehensive way - Offers an overview of current relevant research and the most recent developments - Provides rich information about future research trends and innovative insights into effective policymaking
