DISCRETE CHOICE METHODS WITH SIMULATION

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Discrete Choice Methods With Simulation

Author : Kenneth Train
ISBN : 0521017157
Genre : Business & Economics
File Size : 44.83 MB
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The author investigates recent discrete choice methods, focusing on advances that simulation has made possible.
Category: Business & Economics

Discrete Choice Methods With Simulation

Author : Kenneth E. Train
ISBN : 9781139480376
Genre : Business & Economics
File Size : 50.76 MB
Format : PDF, Mobi
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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. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This 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.
Category: Business & Economics

Maximum Simulated Likelihood Methods And Applications

Author : William Greene
ISBN : 9780857241498
Genre : Business & Economics
File Size : 32.10 MB
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This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.
Category: Business & Economics

Random Regret Based Discrete Choice Modeling

Author : Caspar G. Chorus
ISBN : 9783642291500
Genre : Business & Economics
File Size : 66.53 MB
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This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. This tutorial is written for students, scholars and practitioners who have a basic background in choice modeling in general and RUM-modeling in particular. It has been taken care of that all concepts and results should be clear to readers that do not have an advanced knowledge of econometrics.
Category: Business & Economics

The Oxford Handbook Of Panel Data

Author : Badi H. Baltagi
ISBN : 9780190210823
Genre : Business & Economics
File Size : 40.27 MB
Format : PDF, Kindle
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The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels. This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.
Category: Business & Economics

Modeling Techniques In Predictive Analytics

Author : Thomas W. Miller
ISBN : 9780133886191
Genre : Computers
File Size : 24.20 MB
Format : PDF, ePub
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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
Category: Computers

Modeling Techniques In Predictive Analytics With Python And R

Author : Thomas W. Miller
ISBN : 9780133892147
Genre : Computers
File Size : 72.24 MB
Format : PDF, ePub
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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
Category: Computers

Frontiers Of Environmental Input Output Analysis

Author : Shigemi Kagawa
ISBN : 9781136651205
Genre : Business & Economics
File Size : 31.94 MB
Format : PDF, ePub
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Input-Output Analysis (IOA) is widely used in the field of ecological economics, industrial ecology, and environmental sciences. Industrial Ecology (IE) and Ecological Economics (EE) are promising and growing fields. IOA plays a crucial role in analyzing the related environmental and resource issues and providing quantitative information to many research questions and policy implications. The major aim of this book is to provide not only a comprehensive overview of environmental IOA from 1930s to the present but also the frontiers of environmental IOA including energy structural decomposition analysis, spatial energy structural decomposition analysis, multi-regional waste make-use analysis, augmented waste input-output analysis, dynamic structural decomposition analysis with product lifetime distributions, and endogenous input-output analysis with product lifetime distributions to professionals, practitioners, and students. This book presents a novel dynamic structural decomposition analysis to evaluate the effects of the product lifetime shifts and structural changes such as technological changes and final demand shifts on the life cycle energy consumptions. It also contributes to modelling a simple social accounting method with cumulative product lifetime distributions and argues how product lifetime extension affects energy consumptions and income flow throughout the entire economic system. The book demonstrates the author’s expertise in IOA and is an essential read for students and scholars in the field.
Category: Business & Economics

Social Ecological Restoration In Paddy Dominated Landscapes

Author : Nisikawa Usio
ISBN : 9784431553304
Genre : Science
File Size : 71.94 MB
Format : PDF, Mobi
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With a focus on environmentally friendly rice farming, this unique book integrates both ecosystem and human dimensions of ecological restoration to provide strategies to promote sustainable agriculture and rural development. Paddy fields have multiple functions beyond their role of producing rice: They serve as refuge habitats for a range of wildlife that once inhabited floodplain wetlands and contain a number of unique and threatened aquatic species. They also provide various ecosystem services for regional communities such as water retention, erosion control, flood control, fish culture, and educational opportunities. However, rice paddies are threatened worldwide due to the modernization of agriculture and abandonment of farmland caused by depopulation and the aging of rural communities. Therefore, multiple ecological and sociological aspects must be considered in the ecological restoration of paddy fields. This book aims to do so by incorporating various disciplines of natural and social sciences. Strategies for sustainable agriculture are reviewed, including financial incentives for farmers and the use of flagship wildlife species such as the crested ibis (toki) to promote ecological restoration. With the increasing popularity of environmentally friendly rice farming in parts of Asia and the western United States, this book offers model cases for sustainable management of paddy-dominated landscapes.
Category: Science