학술저널
Grouping and clustering methods in econometrics
- 서울대학교 경제연구소
- 경제논집
- 경제논집 59권 2호
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2020.1287 - 106 (20 pages)
- 33
커버이미지 없음
This paper reviews recent developments in the application of clustering methods in econometrics. In particular, we discuss how the k-means algorithm can be extended and applied to econometric problems. Models with group structures are useful to describe heterogeneity across units. Such models can be estimated by extensions of the k-means algorithm. We also discuss inference methods for group memberships and methods to incorporate possible structural breaks.
1. Introduction
2. The k-means algorithm
3. Group heterogeneity in panel data
4. Structural breaks
5. Conclusion
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