The Economics of Information Technology is a concise and accessible review of some of the important economic factors affecting information technology industries. These industries are characterized by high fixed costs and low marginal costs of production, large switching costs for users, and strong network effects. These factors combine to produce some unique behavior. The book consists of two parts. In the first part, Professor Varian outlines the basic economics of these industries. In the second part, Professors Farrell and Shapiro describe the impact of these factors on competition policy. The clarity of the analysis and exposition makes this an ideal introduction for undergraduate and graduate students in economics, business strategy, law and related areas.

The ability to conceptualize an economic problem verbally, to formulate it as a mathematical model, and then represent the mathematics in software so that the model can be solved on a computer is a crucial skill for economists. Computational Economics contains well-known models--and some brand-new ones--designed to help students move from verbal to mathematical to computational representations in economic modeling. The authors' focus, however, is not just on solving the models, but also on developing the ability to modify them to reflect one's interest and point of view. The result is a book that enables students to be creative in developing models that are relevant to the economic problems of their times. Unlike other computational economics textbooks, this book is organized around economic topics, among them macroeconomics, microeconomics, and finance. The authors employ various software systems--including MATLAB, Mathematica, GAMS, the nonlinear programming solver in Excel, and the database systems in Access--to enable students to use the most advantageous system. The book progresses from relatively simple models to more complex ones, and includes appendices on the ins and outs of running each program. The book is intended for use by advanced undergraduates and professional economists and even, as a first exposure to computational economics, by graduate students. Organized by economic topics Progresses from simple to more complex models Includes instructions on numerous software systems Encourages customization and creativity

Computational Economics: A concise introduction is a comprehensive textbook designed to help students move from the traditional and comparative static analysis of economic models, to a modern and dynamic computational study. The ability to equate an economic problem, to formulate it into a mathematical model and to solve it computationally is becoming a crucial and distinctive competence for most economists. This vital textbook is organized around static and dynamic models, covering both macro and microeconomic topics, exploring the numerical techniques required to solve those models. A key aim of the book is to enable students to develop the ability to modify the models themselves so that, using the MATLAB/Octave codes provided on the book and on the website, students can demonstrate a complete understanding of computational methods. This textbook is innovative, easy to read and highly focused, providing students of economics with the skills needed to understand the essentials of using numerical methods to solve economic problems. It also provides more technical readers with an easy way to cope with economics through modelling and simulation. Later in the book, more elaborate economic models and advanced numerical methods are introduced which will prove valuable to those in more advanced study. This book is ideal for all students of economics, mathematics, computer science and engineering taking classes on Computational or Numerical Economics.

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

This book presents introductory economics material using standard mathematical tools, including calculus. It is designed for a relatively sophisticated undergraduate who has not taken a basic university course in economics. The book can easily serve as an intermediate microeconomics text. The focus of this book is on the conceptual tools. Contents: 1) What is Economics? 2) Supply and Demand. 3) The US Economy. 4) Producer Theory. 5) Consumer Theory. 6) Market Imperfections. 7) Strategic Behavior.

This book provides a comprehensive introduction to the mathematical foundations of economics, from basic set theory to fixed point theorems and constrained optimization. Rather than simply offer a collection of problem-solving techniques, the book emphasizes the unifying mathematical principles that underlie economics. Features include an extended presentation of separation theorems and their applications, an account of constraint qualification in constrained optimization, and an introduction to monotone comparative statics. These topics are developed by way of more than 800 exercises. The book is designed to be used as a graduate text, a resource for self-study, and a reference for the professional economist.

The Internet has rapidly become an important element of the economic system. The lack of accepted metrics for economic analysis of Internet transactions is therefore increasingly problematic. This book, one of the first to bring together research on Internet engineering and economics, attempts to establish such metrics. The chapters, which developed out of a 1995 workshop held at MIT, include architectural models and analyses of Internet usage, as well as alternative pricing policies. The book is organized into six sections: 1) Introduction to Internet Economics, 2) The Economics of the Internet, 3) Interconnection and Multicast Economics, 4) Usage Sensitive Pricing, 5) Internet Commerce, and 6) Internet Economics and Policy. Contributors Loretta Anania, Joseph P. Bailey, Nevil Brownlee, David Carver, David Clark, David W. Crawford, Ketil Danielsen, Deborah Estrin, Branko Gerovac, David Gingold, Jiong Gong, Alok Gupta, Shai Herzog, Clark Johnson, Martyne M. Hallgren, Frank P. Kelly, Charlie Lai, Alan K. McAdams, Jeffrey K. MacKie-Mason, Lee W. McKnight, Gennady Medvinsky, Liam Murphy, John Murphy, B. Clifford Neuman, Jon M. Peha, Joseph Reagle, Mitrabarun Sarkar, Scott Shenker, Marvin A. Sirbu, Richard Jay Solomon, Padmanabhan Srinagesh, Dale O. Stahl, Hal R. Varian, Qiong Wang, Martin Weiss, Andrew B. Whinston