This book analyses stochastic dynamic systems across a broad spectrum in economics and finance. The major unifying theme is the coherent and rigorous treatment of uncertainty and its implications for describing stochastic processes by the stochastic differential equations of the fundamental models in various fields. Pertinent subjects are interrelated, juxtaposed, and examined for consistency in theoretical and empirical contexts. The volume consists of three parts: Developments in Stochastic Dynamics; Stochastic Dynamics in Basic Economic Growth Models; Intertemporal Optimisation in Consumption, Finance, and Growth. Key topics include: fractional Brownian motion in finance; moment evolution of Gaussian and geometric Wiener diffusions; stochastic kinematics and stochastic mechanics; stochastic growth in continuous time; time delays and Hopf bifurcation; consumption and investment strategies; differential systems in finance and life insurance; uncertainty of technological innovations; investment and employment cycles; stochastic control theory; and risk aversion. The works collected in this book serves to bridge the "old" deterministic dynamics and the "new" stochastic dynamics. The collection is important for scholars and advanced graduate students of economics, statistics, and applied mathematics.

This book exposes the theory under the phenomenon of economic cycles and provides mathematical tools for their quantitative description. The approach allows to provide the stochastic description of the investment function, to recover the income function from GDP estimates, and to propose the identification procedure for pseudo-stationary models of economic cycles. .

This book is devoted to a specific problem in the general theory of automatic control -- sequential control under conditions of incomplete information. The main results concern the case in which at each moment of (continuous) time only a finite number of controls are admissible and the results of control action are represented by realizations of random variables whose distributions at a given control correspond to one of several alternative hypotheses. The analysis is conducted in a Bayesian framework.

This book is a collection of Amitrajeet A Batabyal's most important papers on the environment and economic development. It begins with a comprehensive and previously unpublished introductory chapter, followed by 12 chapters on different problems such as land use for agricultural purposes, environmental policy design, flood control, and renewable resource management. This book's uniqueness stems from the fact that it uses novel modeling tools that are largely unfamiliar to economists to shed valuable light on contemporary problems at the interface of the environment and economic development.

Treating the mathematical methods used in the economic dynamics, this book shows how they are utilised to build and analyse dynamical models. Accordingly, the focus is on the methods, and every new mathematical technique introduced is followed by its application to select economic models. The mathematical methods coveredc range from elementary linear difference and differential equations and simultaneous systems to the qualitative analysis of non-linear dynamical systems. Stability considerations are stressed throughout, including many advanced topics. Bifurcation and chaos theory are also dealt with. The reader is guided through a step-by-step analysis of each topic, be it a mathematical method or an economic model. The Study Edition also provides the reader with solutions to the numerous exercises.

Stochastic Economics: Stochastic Processes, Control, and Programming presents some aspects of economics from a stochastic or probabilistic point of view. The application of stochastic processes to the theory of economic development, stochastic control theory, and various aspects of stochastic programming is discussed. Comprised of four chapters, this book begins with a short survey of the stochastic view in economics, followed by a discussion on discrete and continuous stochastic models of economic development. The next chapter focuses on methods of stochastic control and their application to dynamic economic models, with emphasis on those aspects connected especially with the theory of quantitative economic policy. Some basic operational problems of applying stochastic control, particularly in economic systems and organizations for problems such as dynamic resource allocation, growth planning, and economic coordination are considered. The last chapter is devoted to stochastic programming, paying particular attention to the decision rule theory of operations research under the chance-constrained model and a method of incorporating reliability measures into a systems reliability model. This book will be of interest to economists, statisticians, applied mathematicians, operations researchers, and systems engineers.

This is a book on stochastic dynamic macroeconomics from a Keynesian perspective. It shows that including Keynesian features in intertemporal models considerably contributes to resolve major puzzles arising in the context of the Dynamic General Equilibrium (DGE) model. It also demonstrates that including microeconomic intertemporal behavior of economic agents in macroeconomics is not inconsistent with Keynesian economics.

​There are several techniques to study noncooperative dynamic games, such as dynamic programming and the maximum principle (also called the Lagrange method). It turns out, however, that one way to characterize dynamic potential games requires to analyze inverse optimal control problems, and it is here where the Euler equation approach comes in because it is particularly well–suited to solve inverse problems. Despite the importance of dynamic potential games, there is no systematic study about them. This monograph is the first attempt to provide a systematic, self–contained presentation of stochastic dynamic potential games.

This paper presents and estimates a small open economy dynamic stochastic general-equilibrium model (DSGE) for the Jordanian economy. The model features nominal and real rigidities, imperfect competition and habit formation in the consumer’s utility function. Oil imports are explicitly modeled in the consumption basket and domestic production. Bayesian estimation methods are employed on quarterly Jordanian data. The model’s properties are described by impulse response analysis of identified structural shocks pertinent to the economy. These properties assess the effectiveness of the pegged exchange rate regime in minimizing inflation and output trade-offs. The estimates of the structural parameters fall within plausible ranges, and simulation results suggest that while the peg amplifies output, consumption and (price and wage) inflation volatility, it offers a relatively low risk premium.