Citation Analysis – Double Machine Learning of Continuous Treatment Effects with General Instrumental Variables

Double Machine Learning of Continuous Treatment Effects with General Instrumental Variables
Shuyuan Chen, Peng Zhang, Yifan Cui
https://arxiv.org/abs/2601.01471

102

Citation mentions

Cited references

Sections

9,056

Words (approx)

References by Citation Intensity

Ordered by composite index (descending). Higher values indicate more intensive citation.

#	Mentions	Breadth	Sec. Wtd	Share	Composite	Main %
1	7	6	11.5	0.069	0.950	86%
2	9	6	10.5	0.088	0.874	67%
3	6	4	8.0	0.059	0.874	67%
4	9	5	11.0	0.088	0.822	56%
5	3	2	4.0	0.029	0.737	100%
6	5	4	4.5	0.049	0.737	40%
7	2	2	3.0	0.020	0.644	100%
8	2	2	3.0	0.020	0.644	100%
9	2	2	3.0	0.020	0.644	100%
10	2	2	3.0	0.020	0.644	100%
11	2	2	3.0	0.020	0.644	100%
12	2	2	1.5	0.020	0.511	50%
13	2	2	1.5	0.020	0.511	50%
14	2	2	1.5	0.020	0.511	50%
15	3	2	2.0	0.029	0.511	33%
16	1	1	1.0	0.010	0.406	100%
17	1	1	1.0	0.010	0.406	100%
18	1	1	1.0	0.010	0.406	100%
19	1	1	1.0	0.010	0.406	100%
20	1	1	1.0	0.010	0.406	100%
21	1	1	1.0	0.010	0.406	100%
22	1	1	1.0	0.010	0.406	100%
23	1	1	1.0	0.010	0.406	100%
24	1	1	1.0	0.010	0.406	100%
25	1	1	1.0	0.010	0.406	100%
26	1	1	1.0	0.010	0.406	100%
27	1	1	1.0	0.010	0.406	100%
28	1	1	1.0	0.010	0.406	100%
29	1	1	1.0	0.010	0.406	100%
30	1	1	1.0	0.010	0.406	100%
31	1	1	1.0	0.010	0.406	100%
32	1	1	1.0	0.010	0.406	100%
33	1	1	1.0	0.010	0.406	100%
34	1	1	1.0	0.010	0.406	100%
35	1	1	1.0	0.010	0.406	100%
36	1	1	1.0	0.010	0.406	100%
37	1	1	1.0	0.010	0.406	100%
38	1	1	1.0	0.010	0.406	100%
39	1	1	1.0	0.010	0.406	100%
40	1	1	1.0	0.010	0.406	100%
41	1	1	2.0	0.010	0.406	100%
42	1	1	2.0	0.010	0.406	100%
43	1	1	2.0	0.010	0.406	100%
44	1	1	2.0	0.010	0.406	100%
45	1	1	2.0	0.010	0.406	100%
46	1	1	2.0	0.010	0.406	100%
47	1	1	2.0	0.010	0.406	100%
48	1	1	2.0	0.010	0.406	100%
49	1	1	2.0	0.010	0.406	100%
50	1	1	2.0	0.010	0.406	100%
51	1	1	2.0	0.010	0.406	100%
52	1	1	2.0	0.010	0.406	100%
53	1	1	2.0	0.010	0.406	100%
54	1	1	2.0	0.010	0.406	100%
55	1	1	2.0	0.010	0.406	100%
56	1	1	2.0	0.010	0.406	100%
57	2	2	1.0	0.020	0.139	0%
58	1	1	0.5	0.010	0.087	0%

Reference

Year

Mentions

Breadth

Sec. Wtd

Composite

Main %

11.5

0.069

0.950

86%

10.5

0.088

0.874

67%

8.0

0.059

0.874

67%

11.0

0.088

0.822

56%

4.0

0.029

0.737

100%

4.5

0.049

0.737

40%

3.0

0.020

0.644

100%

3.0

0.020

0.644

100%

3.0

0.020

0.644

100%

3.0

0.020

0.644

100%

3.0

0.020

0.644

100%

1.5

0.020

0.511

50%

1.5

0.020

0.511

50%

1.5

0.020

0.511

50%

2.0

0.029

0.511

33%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

1.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

2.0

0.010

0.406

100%

1.0

0.020

0.139

0.5

0.010

0.087

Measures: Mentions = total in-text citations; Breadth = distinct sections; Sec. Wtd = section-weighted count (body ×2, lit review/appendix ×0.5); Share = mentions / total citations in paper; Composite = geometric mean of normalised count, breadth, and main-text ratio; Main % = fraction of mentions in main text (excl. appendix). (self) = self-citation.