Economic models of empirical phenomena are developed for a variety of reasons, the most obvious of which is the numerical characterization of available evidence, in a suitably parsimonious form. Another is to test a theory, or evaluate it against the evidence; still another is to forecast future outcomes. Building such models involves a multitude of decisions, and the large number of features that need to be taken into account can overwhelm the researcher.
Financial Modeling is now the standard text for explaining the implementation of financial models in Excel. This long-awaited fourth edition maintains the “cookbook” features and Excel dependence that have made the previous editions so popular. As in previous editions, basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds are explained with detailed Excel spreadsheets.
This book provides an innovative, integrated, and methodical approach to understanding complex financial models, integrating topics usually presented separately into a comprehensive whole. The book brings together financial models and high-level mathematics, reviewing the mathematical background necessary for understanding these models organically and in context. It begins with underlying assumptions and progresses logically through increasingly complex models to operative conclusions.
Energy utilization, especially from fossil fuels, creates hidden costs in the form of pollution and environmental damages. The costs are well documented but are hidden in the sense that they occur outside the market, are not reflected in market prices, and are not taken into account by energy users. Double Dividend presents a novel method for designing environmental taxes that correct market prices so that they reflect the true cost of energy.
This unique introduction to econometrics provides undergraduate students with a command of regression analysis in one semester, enabling them to grasp the empirical literature and undertake serious quantitative projects of their own. It does not assume any previous exposure to probability and statistics but does discuss the concepts in these areas that are essential for econometrics. The bulk of the textbook is devoted to regression analysis, from simple to advanced topics.
Empirical literature in disciplines ranging from behavioral genetics to economics shows that in virtually every aspect of life the outcomes of children are correlated to a greater or lesser extent with the outcomes of their parents and their siblings. In Heredity, Family, and Inequality, the economist Michael Beenstock offers theoretical, statistical, and methodological tools for understanding these correlations.
This book bridges optimal control theory and economics, discussing ordinary differential equations, optimal control, game theory, and mechanism design in one volume. Technically rigorous and largely self-contained, it provides an introduction to the use of optimal control theory for deterministic continuous-time systems in economics.
This text offers a comprehensive presentation of the mathematics required to tackle problems in economic analyses. To give a better understanding of the mathematical concepts, the text follows the logic of the development of mathematics rather than that of an economics course. The only prerequisite is high school algebra, but the book goes on to cover all the mathematics needed for undergraduate economics. It is also a useful reference for graduate students.
The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity.