This is the first volume in a three-volume exposition of Martin Shubik's vision of "mathematical institutional economics"—a term he coined in 1959 to describe the theoretical underpinnings needed for the construction of an economic dynamics. The goal is to develop a process-oriented theory of money and financial institutions that reconciles micro- and macroeconomics, using as a prime tool the theory of games in strategic and extensive form.
This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics.In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models.
The authors of The Economic Effects of Constitutions use econometric tools to study what they call the "missing link" between constitutional systems and economic policy; the book is an uncompromisingly empirical sequel to their previous theoretical analysis of economic policy. Taking recent theoretical work as a point of departure, they ask which theoretical findings are supported and which are contradicted by the facts. The results are based on comparisons of political institutions across countries or time, in a large sample of contemporary democracies.
A Guide to Econometrics has established itself as a preferred text for teachers and students throughout the world. It provides an overview of the subject and an intuitive feel for its concepts and techniques without the notation and technical detail that characterize most econometrics textbooks.
This book addresses an often neglected aspect of econometrics, the question of how to assess the specification, strengths, weaknesses, limits, and sensitive features of a model. The contributions are the result of a five-year inter-university research project to improve understanding of concepts of model reliability.
The relentless decline in the prices of information technology (IT) has steadily enhanced the role of IT investment as a source of economic growth in the United States. Productivity growth in IT-producing industries has gradually risen in importance, and a productivity revival has taken place in the rest of the economy. In this book Dale Jorgenson shows that IT provides the foundation for the resurgence of American economic growth.
A vast theoretical and empirical literature in corporate finance considers the interrelationships of corporate governance, takeovers, management turnover, corporate performance, corporate capital structure, and corporate ownership structure. Most of the studies look at two variables at a time. In this book, Sanjai Bhagat and Richard Jefferis argue that from an econometric viewpoint, the proper way to study the relationship between any two of these variables is to set up a system of simultaneous equations that specifies the relationships among the six variables.
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.
Historically, the theory of forecasting that underpinned actual practice in economics has been based on two key assumptions?-that the model was a good representation of the economy and that the structure of the economy would remain relatively unchanged. In reality, forecast models are mis-specified, the economy is subject to unanticipated shifts, and the failure to make accurate predictions is relatively common.
In their second book on economic forecasting, Michael Clements and David Hendry ask why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to economic forecasting, they look at the implications for causal modeling, present a taxonomy of forecast errors, and delineate the sources of forecast failure. They show that forecast-period shifts in deterministic factors—interacting with model misspecification, collinearity, and inconsistent estimation—are the dominant source of systematic failure.