Contained in this volume are the edited and refereed papers which were presented at a conference held at Nuffield College, Oxford in May 1987. The papers, which represent the recent research of a group of eminent economists, reflect the variety and scope of modern economic analysis. New results are presented in econometric estimation, the theory of aggregation, poverty measurement and the general theory of measurement in economics. The volume is distinguished by the inclusion of the discussion which occurred as each paper was presented, so capturing the interaction and exchange of ideas that characterised the conference.
"Measurement in Economics: A Handbook" aims to serve as a source, reference, and teaching supplement for quantitative empirical economics, inside and outside the laboratory. Covering an extensive range of fields in economics: econometrics, actuarial science, experimental economics, index theory, national accounts, and economic forecasting, it is the first book that takes measurement in economics as its central focus. It shows how different and sometimes distinct fields share the same kind of measurement problems and so how the treatment of these problems in one field can function as a guidance in other fields. This volume provides comprehensive and up-to-date surveys of recent developments in economic measurement, written at a level intended for professional use by economists, econometricians, statisticians and social scientists. It employs an integrative approach of measurement in economics. It contains multi-disciplinary chapters and up-to-date survey of measurement literature in economics and econometrics.
Most empirical work in economics has considered only a narrow set of measures as meaningful and useful to characterize individual behavior, a restriction justified by the difficulties in collecting a wider set. However, this approach often forces the use of strong assumptions to estimate the parameters that inform individual behavior and identify causal links. In this paper, we argue that a more flexible and broader approach to measurement could be extremely useful and allow the estimation of richer and more realistic models that rest on weaker identifying assumptions. We argue that the design of measurement tools should interact with, and depend on, the models economists use. Measurement is not a substitute for rigorous theory, it is an important complement to it, and should be developed in parallel to it. We illustrate these arguments with a model of parental behavior estimated on pilot data that combines conventional measures with novel ones.
Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples
This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Since its establishment in the 1950s the American Economic Association's Committee on Economic Education has sought to promote improved instruction in economics and to facilitate this objective by stimulating research on the teaching of economics. These efforts are most apparent in the sessions on economic education that the Committee organizes at the Association's annual meetings. At these sessions economists interested in economic education have opportunities to present new ideas on teaching and research and also to report the findings of their research. The record of this activity can be found in the Proceedings of the American Eco nomic Review. The Committee on Economic Education and its members have been actively involved in a variety of other projects. In the early 1960s it organized the National Task Force on Economic Education that spurred the development of economics teaching at the precollege level. This in turn led to the development of a standardized research instrument, a high school test of economic understanding. This was followed later in the 1960s by the preparation of a similar test of understanding college economics. The development of these two instruments greatly facilitated research on the impact of economics instruction, opened the way for application of increasingly sophisticated statistical methods in measuring the impact of economic education, and initiated a steady stream of research papers on a subject that previously had not been explored.
In financially constrained health systems across the world, increasing emphasis is being placed on the ability to demonstrate that health care interventions are not only effective, but also cost-effective. This book deals with decision modelling techniques that can be used to estimate the value for money of various interventions including medical devices, surgical procedures, diagnostic technologies, and pharmaceuticals. Particular emphasis is placed on the importance of the appropriate representation of uncertainty in the evaluative process and the implication this uncertainty has for decision making and the need for future research. This highly practical guide takes the reader through the key principles and approaches of modelling techniques. It begins with the basics of constructing different forms of the model, the population of the model with input parameter estimates, analysis of the results, and progression to the holistic view of models as a valuable tool for informing future research exercises. Case studies and exercises are supported with online templates and solutions. This book will help analysts understand the contribution of decision-analytic modelling to the evaluation of health care programmes. ABOUT THE SERIES: Economic evaluation of health interventions is a growing specialist field, and this series of practical handbooks will tackle, in-depth, topics superficially addressed in more general health economics books. Each volume will include illustrative material, case histories and worked examples to encourage the reader to apply the methods discussed, with supporting material provided online. This series is aimed at health economists in academia, the pharmaceutical industry and the health sector, those on advanced health economics courses, and health researchers in associated fields.
Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples
