Probability Models for Economic Decisions, second edition
568 pp., 7 x 9 in, 153 figures
- Published: November 22, 2019
- Publisher: The MIT Press
- Published: December 17, 2019
- Publisher: The MIT Press
An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty.
This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets.
The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk.
New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.
In the new world of big data and fast computations, simulations incorporating randomness have grown increasingly important for business analysis, but had been largely beyond the reach of students without a technical background. This remarkable book and accompanying tools change that by teaching students to run simulations in spreadsheets that they can create and explore for themselves!
Paul Milgrom, Shirley R. and Leonard W. Ely Jr. Professor of Humanities and Sciences, Stanford University
Making decisions under uncertainty is one of the most complex and challenging problems faced by human beings and communities. Myerson and Zambrano's book conveys the beauty and simplicity of simple decision tools, from the purest theoretical and statistical concepts to most useful techniques available today for decision-makers.
Christian Gollier, Professor of Economics, Toulouse School of Economics
Excel permits students with limited math training to understand and use multivariate optimization, decisions under uncertainty, and option theory successfully. Myerson and Zambrano's use of Excel to teach economic analysis in a stochastic environment is fantastic.
Preston McAfee, former Microsoft Chief Economist