Citation Analysis

\Large \textbfTesting for Asymmetric Information in Insurance\\ with Deep Learning
Serguei Maliar, Bernard Salanie
https://arxiv.org/abs/2404.18207

Citation mentions

Cited references

Sections

6,054

Words (approx)

References by Citation Intensity

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

#	Reference	Year	Mentions	Breadth	Sec. Wtd	Share	Composite	Main %
1	Chiappori, P.-A.	2000	16	4	21.0	0.356	0.979	94%
2	Victor Chernozhukov and Mert Demirer and Esther Du...	2023	7	5	12.0	0.156	0.950	86%
3	Vira Semenova and Victor Chernozhukov		4	3	7.0	0.089	0.928	100%
4	Chernozhukov, Victor and Lee, Sokbae and Rosen, Ad...	2013	4	3	5.0	0.089	0.843	75%
5	Chernozhukov, Victor and others	2018	3	2	4.0	0.067	0.737	100%
6	Chiappori, P.-A.	2006	2	1	2.0	0.044	0.511	100%
7	Michael Rothschild and Joseph Stiglitz		1	1	1.0	0.022	0.406	100%
8	Chiappori, P.-A.	2013	1	1	1.0	0.022	0.406	100%
9	Kim, H. and D. Kim and S. Im and J. W. Hardin		1	1	1.0	0.022	0.406	100%
10	Liangjun Su and Martin Spindler		1	1	1.0	0.022	0.406	100%
11	Martin Spindler		1	1	1.0	0.022	0.406	100%
12	Diederik P. Kingma and Jimmy Ba	2017	1	1	2.0	0.022	0.406	100%
13	Fran\cc	2021	1	1	2.0	0.022	0.406	100%
14	M. Abadi and others	2016	1	1	2.0	0.022	0.406	100%
15	Nitish Srivastava and Geoffrey Hinton and Alex Kri...		1	1	2.0	0.022	0.406	100%

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.