Model Reliability

This book addresses an often neglected aspect of econometrics, the question of how to assess the specification, strengths, weaknesses, limits, and sensitive features of a model. The contributions are the result of a five-year inter-university research project to improve understanding of concepts of model reliability.Contents
Introduction, David A. Belsley and Edwin Kuh Wholesale and Retail Prices: Bivariate Time Series Modeling with Forecastable Error Variables, C.W.J. Granger, R.P. Robins, and Robert F. Engle Recursive Stability Analysis: The Demand for Money during the German Hyperinflation, Jean-Marie Dufour A Bayesian Analysis of the Determinant of Inflation, Edward E. Learner The Use of Outside Information in Econometric Forecasting, Mark N. Greene, E. Philip Howrey, and Saul H. Hymans Centering, the Constant, First Differencing, and Assessing Conditioning, David A. Belsley Applications of Bounded-Influence and Diagnostic Methods in Energy Modeling, Roy Welsch and Stephen Swartz A Comparison of the Michigan and Fair Models: Further Results, Ray C. Fair and Lewis S. Alexander Linear Analysis of Large Nonlinear Models and Model Simplification, Edwin Kuh, John Neese, and Peter Hollinger