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.
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