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Nonlinear Labor Market Dynamics discusses adjustment processes in labor markets. Contrary to linear-stochastic approaches this book is based on a non-linear deterministic framework. It is shown that even textbook-like-models of the labor market can generate long lasting adjustment processes, local instabilities, and chaotic movements, once nonlinear relationships and widely accepted adjustment rules are introduced. Thus, labor market dynamics may have an endogenous component that is governed by a nonlinear deterministic core. Of course, all results are tied to the particular models discussed in this book. Nevertheless, these models imply that by incorporating nonlinear relationships, one may arrive at an explanation of labor market behavior where linear stochastic approaches fell. Time series studies for German labor market data support this point of view.
This book describes the state of the art in the field of modeling and solving numerically inverse problems of wave propagation and diffraction. It addresses mathematicians, physicists and engineers as well. Applications in such fields as acoustics, optics, and geophysics are emphasized. Of special interest are the contributions to two and three dimensional problems without reducing symmetries. Topics treated are the obstacle problem, scattering by classical media, and scattering by distributed media.
In this book on disequilibrium, growth and labor market dynamics we take predominantly a macroeconomic perspective. We present a working model that can easily be varied in different directions in order to subsume innovations in the literature on macroeconomics, old and new, and to contribute to important currently discussed macroeconomic issues. Our working model is set up in a way that there is a close relationship between our presented dynamic models and modern macro econometric models with disequilibrium both in the labor and the goods markets. One of our objectives is, therefore, to narrow the gap between theoretical and applied structural macrodynamic model building. We hope that the book will be a useful reference for all researchers, academic teachers and practitioners of macroeconomic and macro econometric model building who are interested in economic dynamics, independently of whether they use equilibrium or disequilibrium methods in their own research. We base this hope on the fact that our approach contains a number of unique features. The emphasis on the identification and analysis of the basic feedback mechanisms at work in modern macro economies. A detailed study of the partial as well as integrated dynamic interaction between these feedback mechanisms that consti tute the interdependence of markets and sectors of the modern macro economy. The rela tionship between the macroeconomic framework of our working model and the Walrasian, Non-Walrasian and New-Keynesian reformulations of macroeconomics.
Interest in business cycles has had its 'ups and downs'. After a period of almost steady state growth and of economic tranquility, when the business cycle seemed to be obsolete, the turbulence of the 70s and 80s has contributedto a renewed interest in the topic. Important analytical and methodological innovations have also favored the present abundance of contributions. Four innovations are of particular importance: i. microfoundations ii. nonlinearities iii. stochastic variables iv. real aspects. Both Classical macroeconomics and new-Keynesian approaches seem to share these characteristics, which apply both to endogenous and exogenous explanations of the cycle. The distance separating the newer literature from its forebears seems vast. Previously, cycle theory was characterized by a macro approach and utilized nonlinearities either through piecewise 'linear models or with the aid of Classical theorems in the field of dynamic systems. To consider and to compare the old and the new literature on business cycles is one of the goals of this book. To narrow the distance separating them is another goal of this research. We do not try to bridge it, but rather to revisit the former tradition with new tools. Finally, a particular emphasis is put on the 'ceilings and floors' type of literature. One of us has written a D. Phil. thesis with Sir John Hicks, and both have worked with H. P. Minsky. Hicks, along with Goodwin, introdu. ced the concept of ceilings and floors into business cycle analysis, and Minsky made important contributions to the area.
This paper proposes a hidden state Markov model (HMM) that incorporates workers’ unobserved labor market attachment into the analysis of labor market dynamics. Unlike previous literature, which typically assumes that a worker’s observed labor force status follows a first-order Markov process, the proposed HMM allows workers with the same labor force status to have different history-dependent transition probabilities. I show that the estimated HMM generates labor market transition probabilities that match those observed in the data, while the first-order Markov model (FOM) and its many-state extensions cannot. Even compared with the extended FOM, the HMM improves the fit of the empirical transition probabilities by a factor of 30. I apply the HMM to (1) calculate the long-run consequences of separation from stable employment, (2) study evolutions of employment stability across different demographic groups over the past several decades, (3) compare the dynamics of labor market flows during the Great Recession to those during the 1981 recession, and (4) highlight the importance of looking beyond distributions of current labor force status.
This book represents an ongoing research agenda the aim of which is to contribute to the Keynesian paradigm in macroeconomics. It examines the Dynamic General Equilibrium (DGE) model, the assumption of intertemporal optimizing behavior of economic agents, competitive markets and price mediated market clearing through flexible wages and prices.
This book is a revised version of my doctoral dissertation submitted to the University of St. Gallen in October 1999. I would like to thank Dr. oec. Marc Wildi whose careful reading of much of the text led to many improvements. All errors remain mine. Pfiiffikon SZ, Switzerland, March 2001 Pierre-Yves Moix Preface to the dissertation "Education is man's going forward from cocksure ignorance to thoughtful uncertainty" Don Clark's Scrapbook quoted in Wonnacott and Wonnacott (1990). After several years of banking practice, I decided to give up some of my certitudes and considered this thesis project a good opportunity to study some of the quantitative tools necessary for the modelling of uncertainty. lowe very much to Prof. Dr. Karl Frauendorfer, the referee of my thesis, for the time he took to read the manuscript and for the numerous valuable suggestions he made. I am also very grateful to Prof. Dr. Klaus Spremann who kindly accepted to co-refer my thesis and who strengthened my inter est in finance during my study period. During my time at the Institute for Operations Research of the University of St. Gallen (lfU-HSG) I had the opportunity to participate in the project "RiskLab" which provides a very profitable link between finance practice and academics. I would especially like to thank Dr. Christophe Rouvinez from Credit Suisse for his comments and all the data he provided so generously.
Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics.