Determine location of structural break in cross-section data

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SUMMARY

The discussion focuses on identifying the precise location of a structural break in cross-sectional data using regression analysis. A Chow Test indicated a structural break, with estimates of .08 and .2 for values below and above 70,000, respectively. The participant seeks a mathematical method to accurately determine the break point rather than relying on an educated guess. Suggested methods include cluster analysis and discriminant analysis, with a recommendation to rank-order the data and test various thresholds such as 5%, 10%, 25%, and 50%.

PREREQUISITES
  • Understanding of regression analysis and structural breaks
  • Familiarity with the Chow Test for structural break detection
  • Knowledge of cluster analysis and discriminant analysis techniques
  • Ability to rank-order data for threshold testing
NEXT STEPS
  • Research advanced methods for detecting structural breaks in regression, such as the Bai-Perron test
  • Learn about the application of cluster analysis in identifying data subsets
  • Explore discriminant analysis for predicting group membership in datasets
  • Investigate techniques for rank-ordering data and determining optimal thresholds
USEFUL FOR

Data analysts, statisticians, and researchers working with regression models and seeking to improve the accuracy of their structural break assessments.

phantomcow2
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I'm trying to run a simple regression for a data set (n=165). I've determined via a Chow Test that there exists a structural break somewhere; the same least squares estimate cannot be accurately used to represent the entire range of values the explanatory variable takes on. I've found two very different (.08 and .2) estimates if I break the data down into two catagories: whenexplanatory variable takes values of less than 70000, and where it takes values above 70,000.

However I only took an educated guess to arrive at the 70,000 figure. Is there a more precise, mathematical method available that allows me to determine where the structural break begins to occur?
 
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phantomcow2 said:
However I only took an educated guess to arrive at the 70,000 figure. Is there a more precise, mathematical method available that allows me to determine where the structural break begins to occur?

Cluster analysis or discriminant analysis may be useful here. The latter is primarily for anticipated or predetermined subsets in the data.http://faculty.chass.ncsu.edu/garson/PA765/cluster.htm
 
Last edited by a moderator:
There is no hard and fast rule -- a rule of thumb is to rank-order the data and try 5%, 10%, 25% and 50%.
 

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