Statistical Analysis and Forecasting of Economic Structural Change

1. Front Matter

   Pages i-xix

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2. Introduction

   1. Front Matter

      Pages 1-1

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   2. What Can Statistics Contribute to the Analysis of Economic Structural Change?

      • Gordon J. Anderson, Grayham E. Mizon

      Pages 3-21

3. Identification of Structural Change

   1. Front Matter

      Pages 23-23

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   2. Testing for Structural Change in Simultaneous Equation Models

      • Andrew C. Harvey, Garry D. A. Phillips

      Pages 25-36

   3. Specification and Stability Tests versus Jackknifing: Some Illustrative Examples

      • Bernd Schips, Yngve Abrahamsen

      Pages 37-43

   4. The Robustness of the Chow Test to Autocorrelation among Disturbances

      • Walter Krämer

      Pages 45-52

   5. Tests against Nonconstancy in Linear Models Based on Counting Statistics

      • Peter Hackl, Walter Katzenbeisser

      Pages 53-70

   6. Nonparametric Tests for Shift and Change in Regression at an Unknown Time Point

      • Marie Hušková, Pranab K. Sen

      Pages 71-85

   7. Detection of Join Point in Regression Models

      • Hiroki Tsurumi

      Pages 87-95

   8. On the Identification of Time for Structural Changes by MOSUM-SQ and CUSUM-SQ Procedures

      • Anders H. Westlund, Birgitta Törnkvist

      Pages 97-126

   9. The Local Power of the CUSUM-SQ Test against Heteroscedasticity

      • Werner Ploberger

      Pages 127-133

   10. Bahadur Efficiency of Tests for a Shift in Location of Normal Populations

       • Jaap Praagman

       Pages 135-165

   11. The Use of Graphical Displays in the Analysis of Structural Change

       • Zbigniew Wasilewski

       Pages 167-188

4. Model Building in the Presence of Structural Change

   1. Front Matter

      Pages 189-189

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   2. Adaptive Estimation and Structural Change in Regression and Time Series Models

      • Johannes Ledolter

      Pages 191-208

   3. An Adaptive Method of Regression Analysis

      • Yuri P. Lukashin

      Pages 209-216

   4. Changing and Random Coefficient Models. A Survey

      • Józef Dziechciarz

      Pages 217-251

   5. Nonparametric Estimation of Time-Varying Parameters

      • Peter M. Robinson

      Pages 253-264

   6. Latent Variables in Regression Analysis

      • Valeri V. Fedorov

      Pages 265-272

In 1984, the University of Bonn (FRG) and the International Institute for Applied System Analysis (IIASA) in Laxenburg (Austria), created a joint research group to analyze the relationship between economic growth and structural change. The research team was to examine the commodity composition as well as the size and direction of commodity and credit flows among countries and regions. Krelle (1988) reports on the results of this "Bonn-IIASA" research project. At the same time, an informal IIASA Working Group was initiated to deal with prob­ lems of the statistical analysis of economic data in the context of structural change: What tools do we have to identify nonconstancy of model parameters? What type of models are particularly applicable to nonconstant structure? How is forecasting affected by the presence of nonconstant structure? What problems should be anticipated in applying these tools and models? Some 50 experts, mainly statisticians or econometricians from about 15 countries, came together in Lodz, Poland (May 1985); Berlin, GDR (June 1986); and Sulejov, Poland (September 1986) to present and discuss their findings. This volume contains a selected set of those conference contributions as well as several specially invited chapters.

• data analysis
• econometrics
• economics
• efficiency
• forecasting
• latent variables
• macroeconomics
• modeling
• nonlinear dynamics
• poverty
• regression
• regression analysis
• statistics
• taxation
• time series analysis

• Institut für Statistik, Wirtschaftsuniversität, Wien, Austria

  Peter Hackl

• Department of Statistics and Actuarial Science, The University of Iowa, Iowa City, USA

  Peter Hackl

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