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Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.
This IMA Volume in Mathematics and its Applications NEW DIRECTIONS IN TIME SERIES ANALYSIS, PART II is based on the proceedings of the IMA summer program "New Directions in Time Series Analysis. " We are grateful to David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad Taqqu for organizing the program and we hope that the remarkable excitement and enthusiasm of the participants in this interdisciplinary effort are communicated to the reader. A vner Friedman Willard Miller, Jr. PREFACE Time Series Analysis is truly an interdisciplinary field because development of its theory and methods requires interaction between the diverse disciplines in which it is app...
This book presents some of the more recent developments in nonlinear time series, including Bayesian analysis and cointegration tests.
This 1997 book presents developments in nonlinear economic dynamics along with related research from other fields, including mathematics, statistics, biology, and physics.
The Sixth Annual International Symposium in Economic Theory and Econometrics was dedicated to Jacques Drèze on the occasion of his retirement.
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From David Card, winner of the Nobel Prize in Economics, and Alan Krueger, a provocative challenge to conventional wisdom about the minimum wage David Card and Alan B. Krueger have already made national news with their pathbreaking research on the minimum wage. Here they present a powerful new challenge to the conventional view that higher minimum wages reduce jobs for low-wage workers. In a work that has important implications for public policy as well as for the direction of economic research, the authors put standard economic theory to the test, using data from a series of recent episodes, including the 1992 increase in New Jersey's minimum wage, the 1988 rise in California's minimum wage...
Evolutionary approach to systems from the entire economy to the behaviour of single markets.
We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that the range is not only a highly efficient volatility proxy, but also that it is approximately Gaussian and robust to microstructure noise. The good properties of the range imply that range-based Gaussian quasi-maximum likelihood estimation produces simple and highly efficient estimates of stochastic volatility models and extractions of latent volatility series. We use our method to examine the dynamics of daily exchange rate volatility and discover that traditional one-factor models are inadequate for describing simultaneously the high- and low-frequency dynamics of volatility. Instead, the evidence points strongly toward two-factor models with one highly persistent factor and one quickly mean-reverting factor.