Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the economy (the social choice problem). Optimization in Economics and Finance extends and improves the usual optimization techniques, in a form that may be adopted for modeling social choice problems. Problems discussed include: when is an optimum reached; when is it unique; relaxation of the conventional convex (or concave) assumptions on an economic model; associated mathematical concepts such as invex and quasimax; multiobjective optimal control...
Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the econom...
Dynamic Modeling of Monetary and Fiscal Cooperation Among Nations analyzes coordination of monetary and fiscal stabilization policies between countries and currency areas using a dynamic game approach. The first four chapters introduce the reader to the dynamics of fiscal and monetary policy cooperation. Issues covered include: fiscal coordination, fiscal stringency requirements, structural and bargaining power asymmetries and the design of monetary and fiscal policymaking in a monetary union. In the four last chapters multiple-player settings with aspects of fiscal and/or monetary...
Dynamic Modeling of Monetary and Fiscal Cooperation Among Nations analyzes coordination of monetary and fiscal stabilization policies between count...
Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed stochastic volatility', or conditional heteroskedasticity', has been well known for at least 20 years; in this part, further, useful theoretical properties of conditionally heteroskedastic models are uncovered. The second part...
Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into th...
Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those...
Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this ...
The analysis ofwhat might be called "dynamic nonlinearity" in time series has its roots in the pioneering work ofBrillinger (1965) - who first pointed out how the bispectrum and higher order polyspectra could, in principle, be used to test for nonlinear serial dependence - and in Subba Rao and Gabr (1980) and Hinich (1982) who each showed how Brillinger's insight could be translated into a statistical test. Hinich's test, because ittakes advantage ofthe large sample statisticalpropertiesofthe bispectral estimates became the first usable statistical test for nonlinear serial dependence. We are...
The analysis ofwhat might be called "dynamic nonlinearity" in time series has its roots in the pioneering work ofBrillinger (1965) - who first pointed...
Dynamic Programming in Economics is an outgrowth of a course intended for students in the first year PhD program and for researchers in Macroeconomics Dynamics. It can be used by students and researchers in Mathematics as well as in Economics. The purpose of Dynamic Programming in Economics is twofold: (a) to provide a rigorous, but not too complicated, treatment of optimal growth models in infinite discrete time horizon, (b) to train the reader to the use of optimal growth models and hence to help him to go further in his research. We are convinced that...
Dynamic Programming in Economics is an outgrowth of a course intended for students in the first year PhD program and for researchers ...
This book is about the study of topics in macro dynamics from an applied, empirical perspective. The modeling philosophy behind most of the chapters ofthisbookisofKeynesiannature, representinganattempttorevivethist- oreticalperspectiveontheworkingofthemacroeconomy. Themacroeconomic research pursued here is somewhat di?erent from the mainstream literature using the Dynamic Stochastic General Equilibrium (DSGE) approach as the basic modeling device. The main features of the latter are the assumptions of intertemporally optimizing agents, rational expectations, competitive m- kets and price...
This book is about the study of topics in macro dynamics from an applied, empirical perspective. The modeling philosophy behind most of the chapters o...
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...
The major goal of the book is to create an environment for matching different d- ciplinary approaches to studying economic growth. This goal is implem...
Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the economy (the social choice problem). Optimization in Economics and Finance extends and improves the usual optimization techniques, in a form that may be adopted for modeling social choice problems. Problems discussed include: when is an optimum reached; when is it unique; relaxation of the conventional convex (or concave) assumptions on an economic model; associated mathematical concepts such as invex and quasimax; multiobjective optimal control...
Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the econom...
The basic characteristic of Modern Linear and Nonlinear Econometrics is that it presents a unified approach of modern linear and nonlinear econometrics in a concise and intuitive way. It covers four major parts of modern econometrics: linear and nonlinear estimation and testing, time series analysis, models with categorical and limited dependent variables, and, finally, a thorough analysis of linear and nonlinear panel data modeling. Distinctive features of this handbook are:
-A unified approach of both linear and nonlinear econometrics, with an integration of the...
The basic characteristic of Modern Linear and Nonlinear Econometrics is that it presents a unified approach of modern linear and n...
