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A macroeconomic disequilibrium model is developed for the Federal Republic of Germany. Starting with a microeconomic model of firm's behaviour, the optimal dynamic adjustment of employment and investment is derived. The model of the firm is complemented by an explicite aggregation procedure which allows to derive macroeconomic relations. The model is estimated with macroeconomic data for the Federal Republic of Germany. An important feature is the consistent introduction of dynamic adjustment into a model of the firm. A new method is the particular approach of a delayed adjustment of employment and investment. The estimation results show significant underutilizations of labour and capital and indicate the importance of supply constraints for imports and exports. As the most prominent result, they reveal the importance of the slow adjustment of employment and investment for the macroeconomic situation in Germany and especially for the persistence of high unemployment in the eighties.
. The organizers of the ninth symposium, which produced the current proceedings volume, were Claude Hillinger at the University of Munich, Giancarlo Gandolfo at the University of Rome "La Sapienza," A. R. Bergstrom at the University of Essex, and P. C. B. Phillips at Yale University.
The productivity slowdown of the 1970s and 1980s and the resumption of productivity growth in the 1990s have provoked controversy among policymakers and researchers. Economists have been forced to reexamine fundamental questions of measurement technique. Some researchers argue that econometric approaches to productivity measurement usefully address shortcomings of the dominant index number techniques while others maintain that current productivity statistics underreport damage to the environment. In this book, the contributors propose innovative approaches to these issues. The result is a state-of-the-art exposition of contemporary productivity analysis. Charles R. Hulten is professor of economics at the University of Maryland. He has been a senior research associate at the Urban Institute and is chair of the Conference on Research in Income and Wealth of the National Bureau of Economic Research. Michael Harper is chief of the Division of Productivity Research at the Bureau of Labor Statistics. Edwin R. Dean, formerly associate commissioner for Productivity and Technology at the Bureau of Labor Statistics, is adjunct professor of economics at The George Washington University.
Foundations of Dynamic Economic Analysis presents a modern and thorough exposition of the fundamental mathematical formalism used to study optimal control theory, i.e., continuous time dynamic economic processes, and to interpret dynamic economic behavior. The style of presentation, with its continual emphasis on the economic interpretation of mathematics and models, distinguishes it from several other excellent texts on the subject. This approach is aided dramatically by introducing the dynamic envelope theorem and the method of comparative dynamics early in the exposition. Accordingly, motivated and economically revealing proofs of the transversality conditions come about by use of the dynamic envelope theorem. Furthermore, such sequencing of the material naturally leads to the development of the primal-dual method of comparative dynamics and dynamic duality theory, two modern approaches used to tease out the empirical content of optimal control models. The stylistic approach ultimately draws attention to the empirical richness of optimal control theory, a feature missing in virtually all other textbooks of this type.
This paper presents a dynamic model of the industrial demands for structures, equipment, and blue- and white-collar labor. Our approach is consistent with producers holding rational expectations and optimizing dynamically in the presence of adjustment costs, yet it permits generality of functional form regarding the technology. We represent the technology by atranslog input requirement function that specifies the amount of blue-collar labor (a flexible factor) the firm must hire to produce a level of output given its quantities of three quasi-fixed factors that are subject to adjustment costs: non-production (white-collar) workers, equipment, and structures.A complete description of the production structure is obtained by simultaneously estimating the input requirement function and three stochastic Euler equations.We apply an instrumental variable technique to estimate these equations using aggregate data for U.S. manufacturing. We find that as a fraction of total expenditures, adjustment costs are small in total hut large on the margin,and that they differ considerably across quasi-fixed factors. We also present short- and long-run elasticities of factor demands.
This book contains eleven articles which provide empirical applications as well as theoretical extensions of some of the most exciting recent developments in time-series econometrics. The papers are grouped around three broad themes: (I) the modeling of multivariate times series; (II) the analysis of structural change; (III) seasonality and fractional integration. Since these themes are closely inter-related, several other topics covered are also worth stressing: vector autoregressive (VAR) models, cointegration and error-correction models, nonparametric methods in time series, and fractionally integrated models. Researchers and students interested in macroeconomic and empirical finance will find in this collection a remarkably representative sample of recent work in this area.
This book investigates the impact of production input factors on the market, consumer and producer energy demand characteristics in 30 industrial sectors for South Korea over the period 1980–2009, and for Japan over the period 1973-2006, with special emphasis placed on the effects of ICT investment on the demand for energy. A dynamic factor demand model is developed, accounting for the adjustment costs that are defined in terms of forgone output from current production. It addresses four key aspects of production and energy demand in manufacturing: first, it establishes the various relationships between different factors of production. Second, it investigates whether the energy demand in the industrial sectors in South Korea would be decreased or increased by substituting/complementing with other input factors such as ICT capital and labor. Third, it looks at sources of growth in the industrial sectors through decomposing the Divisia index based total factor productivity (TFP). Finally it provides appropriate policy recommendations based on these findings. The results of this study may provide industrial sectors’ stakeholders and environmental and industrial policy makers with a flexible model that has the capacity to assess outcomes of various policies under certain scenarios. The factor demand methodology described in this book is very advanced and up-to-date. It can be used when teaching advanced graduate courses and in empirically advanced research. Therefore, it is highly relevant in both teaching as a main or supplementary text and in particular as a reference handbook in conducting empirical research. The focus on ICT effects on energy use makes this book an important addition to the existing literature on industrial development.