Zvi Griliches – författare

"An essential reference for specialists in the economics of technological change."--D. G. McFertridge, Canadian Journal of Economics

Is the fall in overall productivity growth in the United States and other developed countries related to the rising share of the service sectors in the economy? Since services represent well over half of the U.S. gross national product, it is also important to ask whether these sectors have had a slow rate of growth, as this would act as a major drag on the productivity growth of the overall economy and on its competitive performance. In this timely volume, leading experts from government and academia argue that faulty statistics have prevented a clear understanding of these issues.

Is the fall in overall productivity growth in the United States and other developed countries related to the rising share of the service sectors in the economy? Since services represent well over half of the U.S. gross national product, it is also important to ask whether these sectors have had a slow rate of growth, as this would act as a major drag on the productivity growth of the overall economy and on its competitive performance. In this timely volume, leading experts from government and academia argue that faulty statistics have prevented a clear understanding of these issues.

Zvi Griliches, a world-renowned pioneer in the field of productivity growth, has compiled in a single volume his pathbreaking research on R&D and productivity. Griliches addresses the relationship between research and development (R&D) and productivity, one of the most complex yet vital issues in today''s business world. Using econometric techniques, he establishes this connection and measures its magnitude for firm-, industry-, and economy-level data. Griliches began his studies of productivity growth during the 1950s, adding a variable of "knowledge stock" to traditional production function models, and his work has served as the point of departure for much of the research into R&D and productivity. This collection of essays documents both Griliches''s distinguished career as well as the history of this line of thought. As inputs into production increasingly taking the form of "intellectual capital" and new technologies that are not as easily measured as traditional labor and capital, the methods Griliches has refined and applied to R&D become crucial to understanding today''s economy.

Zvi Griliches, a world-renowned pioneer in the field of productivity growth, has compiled in a single volume his pathbreaking research on R&D and productivity. Griliches addresses the relationship between research and development (R&D) and productivity, one of the most complex yet vital issues in today''s business world. Using econometric techniques, he establishes this connection and measures its magnitude for firm-, industry-, and economy-level data.

Zvi Griliches was a modern master of empirical economics. In this short book, he recounts what he and others have learned about the sources of economic growth. This book conveys the way he tackled research problems. For Griliches, economic theorizing without measurement is merely the fashioning of parables, but measurement without theory is blind. Judgment enables one to strike the right balance.The book begins with economists' first attempts to measure productivity growth systematically in the 1930s. In the mid-1950s these efforts culminated in a startling puzzle. The growth of measured inputs like labor and capital explained only a fraction of the growth of national output. Economists called this phenomenon "efficiency" or "technical change" or "the residual." However, Griliches observes that the most accurate name was a "measure of our ignorance." What explained the rest of economic growth quickly became one of the most important questions in economics.Over the next thirty years, Griliches and his colleagues and students looked for various components of the residual in education (the formation of human capital), investment (the formation of physical capital), and research and development. In 1973, after the oil price shocks, productivity growth slowed and the residual almost disappeared. Since the shocks were a short-term phenomenon, they could not account for the slowdown. A main focus of this book is therefore the puzzle of the productivity slowdown and how to date it and how to explain it.

7 take advantage of the panel structure of their data to control for possible errors of specifica­ tion in their models. It is interesting to note that the econometric and DEA methods may be closer than some of their respective advocates seem to believe. Several of the studies show that the former as well as the latter can be effectively used to assess the relative effi­ ciency of groups of firms or individual firms, and one of them explicitly compare results arising from both (Fecher et al.). Econometric techniques can also be nonparametric and applied to estimating cost or production frontiers (and not only "average" functions), while ultimately DEA should be amenable to statistical inference. Perhaps the most valuable feature of all the analyses is their care and ingenuity in putting together the data, measuring variables, and pulling out relevant information. Many of them are not content with an overall output measure, but endeavor to manage with less aggregated measures. Nearly all also include in the estimated models a number of auxiliary variables intended to control for specific attributes of outputs, inputs, or production techniques, and other characteristics of firms.

Zvi Griliches has made many seminal contributions to econometrics during the course of a long and distinguished career. His work has focused primarily on the economics of technological change and the econometric problems that arise in trying to study it. This major collection presents Professor Griliches's most important essays and papers on method, applied econometrics and specification problems. It reflects his interests in data-instigated contributions to econometric methodology, developments in and exposition of specification analysis, statistical aggregation, distributed lag models, sample selection bias and measurement error and other unobservable variance component models. These methods are applied to important substantive questions such as the estimation of the returns to education, the measurement of quality change, and productivity and economies of scale.Practicing Econometrics provides an essential reference source to the work of one of the most influential econometricians of the late 20th century.

7 take advantage of the panel structure of their data to control for possible errors of specifica­ tion in their models. It is interesting to note that the econometric and DEA methods may be closer than some of their respective advocates seem to believe. Several of the studies show that the former as well as the latter can be effectively used to assess the relative effi­ ciency of groups of firms or individual firms, and one of them explicitly compare results arising from both (Fecher et al.). Econometric techniques can also be nonparametric and applied to estimating cost or production frontiers (and not only "average" functions), while ultimately DEA should be amenable to statistical inference. Perhaps the most valuable feature of all the analyses is their care and ingenuity in putting together the data, measuring variables, and pulling out relevant information. Many of them are not content with an overall output measure, but endeavor to manage with less aggregated measures. Nearly all also include in the estimated models a number of auxiliary variables intended to control for specific attributes of outputs, inputs, or production techniques, and other characteristics of firms.

7 take advantage of the panel structure of their data to control for possible errors of specifica­ tion in their models. It is interesting to note that the econometric and DEA methods may be closer than some of their respective advocates seem to believe. Several of the studies show that the former as well as the latter can be effectively used to assess the relative effi­ ciency of groups of firms or individual firms, and one of them explicitly compare results arising from both (Fecher et al.). Econometric techniques can also be nonparametric and applied to estimating cost or production frontiers (and not only "average" functions), while ultimately DEA should be amenable to statistical inference. Perhaps the most valuable feature of all the analyses is their care and ingenuity in putting together the data, measuring variables, and pulling out relevant information. Many of them are not content with an overall output measure, but endeavor to manage with less aggregated measures. Nearly all also include in the estimated models a number of auxiliary variables intended to control for specific attributes of outputs, inputs, or production techniques, and other characteristics of firms.