Dynamic Modeling And Applications For Global Economic Analysis

This book presents the technical aspects of an economic model used to examine issues of global economic significance, such as the impact on the world economy of changes in trade and environmental policy. The book provides a number of studies using the model to examine trade reform, growth and investment, climate change, natural resources, technology, and demographic change and migration.

This book, drawn from the Global Trade Analysis Project (GTAP), aims to help readers conduct quantitative analysis of international trade issues in an economy-wide framework. In addition to providing a succinct introduction to the GTAP modeling framework and data base, this book contains seven of the most refined GTAP applications undertaken to date, covering topics ranging from trade policy, to the global implications of environmental policies, factor accumulation and technological change.

Global econometric models have a long history. From the early 1970s to the present, as modeling techniques have advanced, different modeling paradigms have emerged and been used to support national and international policy making. One purpose of this volume -- based on a conference in recognition of the seminal impact of Nobel Prize winner in Economic Sciences Lawrence R Klein, whose pioneering work has spawned the field of international econometric modeling -- is to survey these developments from today's perspective. A second objective of the volume is to shed light on the wide range of attempts to broaden the scope of modeling on an international scale. Beyond new developments in traditional areas of the trade and financial flows, the volume reviews new approaches to the modeling of linkages between macroeconomic activity and individual economic units, new research on the analysis of trends in income distribution and economic wellbeing on a global scale, and innovative ideas about modeling the interactions between economic development and the environment. With the expansion of elaborated economic linkages, this volume makes an important contribution to the evolving literature of global econometric models.

The major goal of the book is to create an environment for matching different d- ciplinary approaches to studying economic growth. This goal is implemented on the basis of results of the Symposium “Applications of Dynamic Systems to E- nomic Growth with Environment” which was held at the International Institute for Applied Systems Analysis (IIASA) on the 7th–8th of November, 2008, within the IIASA Project “Driving Forces of Economic Growth” (ECG). The symposium was organized by coordinators of the ECG project: Jesus Crespo-Cuaresma from IIASA World Population Program, and Tapio Palokangas and Alexander Tarasyev from IIASA Dynamic Systems Program. The book addresses the issues of sustainability of economic growth in a cha- ing environment, global warming and exhausting energy resources, technological change, and also focuses on explanations of signi?cant ?uctuations in countries’ growth rates. The chapters focus on the analysis of historical economic growth - periences in relation to environmental policy, technological change, development of transport infrastructure, population issues and environmental mortality. The book is written in a popular-science style, accessible to any intelligent lay reader. The prime audience for the book is economists, mathematicians and en- neersworkingonproblemsofeconomicgrowthandenvironment.Themathematical part of the book is presented in a rigorous manner, and the detailed analysis is - pected to be of interest to specialists in optimal control and applications to economic modeling. The book consists of four interrelated parts.

Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples

Concise yet rigorous, this textbook provides a clear and systematic introduction to the theory and application of dynamic economic models.