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Advanced Lectures in Quantitative Economics summarizes some of the efforts of a second-phase program for first-rate candidates with a Master's degree in economics who wish to continue with a doctoral degree in quantitative economics. This book is organized into three main topics—macroeconomics, microeconomics, and econometrics. This text specifically discusses the Neo-Keynesian macroeconomics in an open economy, international coordination of monetary policies under alternative exchange-rate regimes, and prospects for global trade imbalances. The post-war developments in labor economics, introduction to overlapping generation models, and measurement of expectations and direct tests of the REH are also elaborated. This monograph likewise covers the dynamic econometric modeling of decisions under uncertainty and fundamental bordered matrix of linear estimation. This publication is a good reference for students and specialists interested in quantitative economics.
This book contains a series of lectures recently given to researchers and students in quantitative economics by an international group of distinguished scholars. The topics covered are at the forefront of recent developments of research in economics and econometrics. The book is divided into three sections: Microeconomics, Macroeconomics and Econometrics. The section on Microeconomics contains chapters on the economics of destitution and an overview of general equilibrium theory with incomplete markets. The section on Macroeconomics contains chapters on the new endogenous growth theory and the microeconomic underpinning of dynamic international macroeconomic models. The section on Econometrics contains chapters on the rapidly expanding literature for GARCH models of volatility, empirical analysis of time series and asymptotic estimation theory for nonlinear econometric models. This will be essential reading for graduate students and researchers in economics, econometrics and finance.
The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems. This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field. New for the second edition: “Programming-language agnostic” presentation using pseudocode. New chapter 1 covering conceptual issues concerning Markov chains such as ergodicity and stability. New focus in chapter 2 on algorithms and techniques for program design and high-performance computing. New focus on household problems rather than optimal growth in material on dynamic programming. Solutions to many exercises, code, and other resources available on a supplementary website.
The main features of this text are a thorough treatment of cross-section models—including qualitative response models, censored and truncated regression models, and Markov and duration models—and a rigorous presentation of large sample theory, classical least-squares and generalized least-squares theory, and nonlinear simultaneous equation models.
Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
This book contains essays in honour of Claus Weddepohl who, after 22 years, is retiring as professor of mathematical economics at the Department of Quantitative Economics of the University of Amsterdam. Claus Weddepohl may be viewed as th~ first Dutch mathematical economist in the general equi librium tradition of Arrow, Debreu and Hahn. The essays in this book are centered around the themes Equilibrium, Markets and Dynamics, that have been at the heart of Weddepohl's work on mathematical economics for more than three decades. The essays have been classified according to these three themes. Admittedly such a classification always is somewhat arbitrary, and most essays would in fact fit into two or even all three themes. The essays have been written by international as well as Dutch friends and colleagues including Weddepohl's former Ph. D. students. The book starts with a review of Claus Weddepohl's work by Roald Ramer, who has been working with him in Amsterdam for all those years. The review describes how Weddepohl became fascinated by general equilibrium theory in the early stages of his career, how he has been working on the theory of markets throughout his career, and how he turned to applications of nonlinear dynamics to price adjustment processes in a later stage of his career. The first part of the book, Equilibrium, collects essays with general equilib rium theory as the main theme.
As most econometricians will readily agree, the data used in applied econometrics seldom provide accurate measurements for the pertinent theory's variables. Here, Bernt Stigum offers the first systematic and theoretically sound way of accounting for such inaccuracies. He and a distinguished group of contributors bridge econometrics and the philosophy of economics--two topics that seem worlds apart. They ask: How is a science of economics possible? The answer is elusive. Economic theory seems to be about abstract ideas or, it might be said, about toys in a toy community. How can a researcher with such tools learn anything about the social reality in which he or she lives? This book shows that an econometrician with the proper understanding of economic theory and the right kind of questions can gain knowledge about characteristic features of the social world. It addresses varied topics in both classical and Bayesian econometrics, offering ample evidence that its answer to the fundamental question is sound. The first book to comprehensively explore economic theory and econometrics simultaneously, Econometrics and the Philosophy of Economics represents an authoritative account of contemporary economic methodology. About a third of the chapters are authored or coauthored by Heather Anderson, Erik Biørn, Christophe Bontemps, Jeffrey A. Dubin, Harald E. Goldstein, Clive W.J. Granger, David F. Hendry, Herman Ruge-Jervell, Dale W. Jorgenson, Hans-Martin Krolzig, Nils Lid Hjort, Daniel L. McFadden, Grayham E. Mizon, Tore Schweder, Geir Storvik, and Herman K. van Dijk.