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Paper Citation Record · LEDGER

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections

As of 20 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2509.00742.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.00742 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:23:32.839912Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

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  • unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ddb208f-b448-4486-b8d2-56cdf3a9da8d · outbound

This paper cites , " * write output.state after.block = add.period write newline.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections , " * write output.state after.block = add.period write newline

Reference 1

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cb98a768-1607-409e-b49e-a575c0e3aa80 · outbound

This paper cites write newline.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections write newline

Reference 2

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unresolved
no resolver link, observed 2026-08-05T13:23:27.190636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:23:27.190636Z digest=sha256:f89bd8eb5f27a92e2a4cbf2069a6ffa3952741784f66957f8aad4001030534ea

Observation 633adea7-cc71-4d7d-8b62-cc68d134b80d · outbound

This paper cites (1988), Spatial econometrics: methods and models, vol.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (1988), Spatial econometrics: methods and models, vol

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fef6a8d5-c6ef-49a2-b19f-e5e7b4bc8e53 · outbound

This paper cites (2020), Local fiscal multipliers and fiscal spillovers in the USA, IMF Economic Review, 68, 195--229.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2020), Local fiscal multipliers and fiscal spillovers in the USA, IMF Economic Review, 68, 195--229

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:27.352430Z digest=sha256:85444bebe95c1a74db5634d1bd841bfb19c33a20ae2f5a7ceee1c18b20a74252

Observation 7f365282-d824-4fe1-b404-d628b92a2f32 · outbound

This paper cites (2012), Statistical analysis of factor models of high dimension, The Annals of Statistics, 40, 436.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2012), Statistical analysis of factor models of high dimension, The Annals of Statistics, 40, 436

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fbf962c0-7ef1-4acf-8a32-1e95f2afa266 · outbound

This paper cites and Li, K.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Li, K

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:27.526309Z digest=sha256:c7917934338ac7d57966d2b4e13944fe0e4b2d918be964aaeb94574d93a80e79

Observation 461aad75-8f09-4096-9183-4e20e0b2b165 · outbound

This paper cites and Ng, S.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Ng, S

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:27.576947Z digest=sha256:f2d07cf369797fdb7eba7ceccca196e7cfcc6a3bcd905a576d7859937b29e3fd

Observation f19a9bce-f703-4c45-8e5e-9c4ded9c5332 · outbound

This paper cites S., Boivin, J., and Eliasz, P.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections S., Boivin, J., and Eliasz, P

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.645046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:27.681303Z digest=sha256:b78049dd95ffe380f58f61dd84b73e226ca28313ede1d2b759d2c1a2e3e395a3

Observation 6a3e6095-17ad-4504-bf61-580bb96fc48a · outbound

This paper cites J., Lucas, A., and Schaumburg, J.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections J., Lucas, A., and Schaumburg, J

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.635367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:27.749763Z digest=sha256:5685116c1f3045c1dc3157eaf8e1d11c77cd9787ff6942e2295aca430928dbf8

Observation 5125497e-ba43-40ce-979e-58de142c7753 · outbound

This paper cites and Chen, Z.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Chen, Z

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:27.821164Z digest=sha256:cef4d5da3dbedeb9c57678a799f346e5d53f0e1bc519a5105fa475b0b8cdbdeb

Observation 55b912f6-d8cc-4767-970b-793215c4c951 · outbound

This paper cites (2025), Estimating time-varying networks for high-dimensional time series, Journal of Econometrics, 105941.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2025), Estimating time-varying networks for high-dimensional time series, Journal of Econometrics, 105941

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a97377aa-1d96-46a6-a361-a9ce1a50006b · outbound

This paper cites and Qu, A.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Qu, A

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.026461Z digest=sha256:4f865db8c6dbe8830b0d1bb04fcd6a5c4cadbd13434bdef5f5d6059e5ea54d6c

Observation 8fd52365-8137-4d94-b31e-304a87621192 · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 13

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.113628Z digest=sha256:edc835640f216d8f88195a0de2c58c19417ab58fdf66b5d61808968c82c1dada

Observation 19db86a4-6b28-465f-8d34-ae0250ecde19 · outbound

This paper cites (2001), Infrastructure development and economic growth: an explanation for regional disparities in China? Journal of Comparative Economics, 29, 95--117.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2001), Infrastructure development and economic growth: an explanation for regional disparities in China? Journal of Comparative Economics, 29, 95--117

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.589435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.173785Z digest=sha256:a6b27a4977e8de0c3231a70db08210a0d2df6ddd01820f6a49ed2653e20fbf12

Observation fc2f782a-f994-402a-b794-581a64cde25e · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:23:37.580141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.252841Z digest=sha256:de6d76d6915be06e981c44e976ef63994f3e98f0bd1111f0df3e6c121a02601c

Observation d1d1da30-5cb5-438b-822b-aea8faea1880 · outbound

This paper cites (2004), Least angle regression, The Annals of Statistics, 407--451.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2004), Least angle regression, The Annals of Statistics, 407--451

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.331155Z digest=sha256:11ae952b317b5a01c70b61d6a391844da96325b95535bff4d12683d38e8214cb

Observation 8f395085-6cde-4c8a-a07d-90b6c6f2fa65 · outbound

This paper cites (2008), High dimensional covariance matrix estimation using a factor model, Journal of Econometrics, 147, 186--197.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2008), High dimensional covariance matrix estimation using a factor model, Journal of Econometrics, 147, 186--197

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.559632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.394364Z digest=sha256:0e426e98824aaa271b5f866d944fb8065115f6b4372f16de20d29abf628c9e43

Observation b686eeb8-f238-4a36-aff5-535fa7be712d · outbound

This paper cites (2022), Estimating number of factors by adjusted eigenvalues thresholding, Journal of the American Statistical Association, 117, 852--861.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2022), Estimating number of factors by adjusted eigenvalues thresholding, Journal of the American Statistical Association, 117, 852--861

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.488221Z digest=sha256:c0fabf4e6bfcb2db15dc381811cf49c7ce4a634cc91d23b99c5b88f3c30e87c3

Observation 16001db5-c9c2-4526-baa0-d0c6b8c412f5 · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:23:37.537979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.564879Z digest=sha256:4414e002ced8b601b0bb5e3ae245fc0554b756601fa1783d3e4cde17ac511e45

Observation 9a5efd96-88ab-4d6e-abec-7263053bece8 · outbound

This paper cites and Li, R.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Li, R

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.527488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.657103Z digest=sha256:9014e9c4841413c31db5d892f7db9b6736c9d4dc797efaf24948fd8f39402c27

Observation a5471de7-02a6-409f-b497-83862fdb102e · outbound

This paper cites (2020), Statistical foundations of data science, Chapman and Hall/CRC.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2020), Statistical foundations of data science, Chapman and Hall/CRC

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.515516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.780849Z digest=sha256:3f49fe5281a604719bf4ddd37a39ab272aa30f624379dec1175605657f6233b5

Observation 864d176e-4e5a-4f55-99b7-e9e57904298d · outbound

This paper cites and Liao, Y.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Liao, Y

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.502133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.841858Z digest=sha256:cfd7593b00af9ce65e2d509573c084f4d243705b71dac74c695a682e39b0b9a4

Observation 04c68e48-99a6-4cea-a208-4fc468b236b6 · outbound

This paper cites (2013), Large covariance estimation by thresholding principal orthogonal complements, Journal of the Royal Statistical Society Series B: Statistical Methodology, 75, 603--680.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2013), Large covariance estimation by thresholding principal orthogonal complements, Journal of the Royal Statistical Society Series B: Statistical Methodology, 75, 603--680

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.331169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:28.966833Z digest=sha256:57ab156bfca2dda46418ee558b336dd1445084f26bce9cd72c8d8d651077b8c3

Observation 140f3d00-b524-473b-9b92-c0bf7894f02f · outbound

This paper cites and Lv, J.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Lv, J

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:37.156490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.042492Z digest=sha256:59aa81c2b2148c194390675cd0010832d693bc6c1eea0c46f422a41cd538ceaf

Observation 6500ce9f-abc1-44df-87d5-6b0f068657ea · outbound

This paper cites (2021), A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery, Annals of statistics, 49, 1239.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2021), A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery, Annals of statistics, 49, 1239

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.980693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.157378Z digest=sha256:8706ff0b92c6682224dcefa488ba2044990261f81e6cfe24db1ba571cba83abe

Observation 4cf24160-6d4e-41c4-bdfd-0c2843d944ba · outbound

This paper cites R., and Venables, A.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections R., and Venables, A

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.869134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.247321Z digest=sha256:7e81bb0befefa8223948bfa9b8ee0ec4564645b15a405d65a09fa5c025ef2216

Observation dfda0117-bf6a-4560-a9bc-151f858315bd · outbound

This paper cites and Tracy, J.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Tracy, J

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.727868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.347643Z digest=sha256:0c0c39dfee4261bce2bc894565e1e0bb4f9ddbc1b392970dca2cfe59847a66c3

Observation e31a0ca9-68c6-4585-9760-e5966279b769 · outbound

This paper cites D., Raftery, A.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections D., Raftery, A

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-05T13:23:29.463142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:23:29.463142Z digest=sha256:107f7403274a6a680c35be1ba4b5d28e47cf10ac769b6a76b955648d9872916c

Observation 5fd635ac-6756-4278-a70e-8b76175f977f · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:23:36.611590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.553578Z digest=sha256:a31a0ba5bcf4606373fe78d975f2d62781c16e6e32a4330c7e1dbcb1ba1f7aea

Observation 35096320-4c8c-41d2-aa6d-206966d71070 · outbound

This paper cites H., and Wang, H.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections H., and Wang, H

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.466538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.649121Z digest=sha256:1f4fe6dff78fe595a3f687e877b24534721b64d666b4b30793a39a21ef1f1fa0

Observation 944df8c5-aecb-4a7e-bd94-342b839a945c · outbound

This paper cites (2021), Feature screening for network autoregression model, Statistica Sinica, 31, 1239.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2021), Feature screening for network autoregression model, Statistica Sinica, 31, 1239

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.352005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.801992Z digest=sha256:6023d0141fbe7439ea5d396e0fc39a625ca872ae010d3683f760c9b4fcafc519

Observation b8a7bac3-3941-4252-bbbb-5b499652a20f · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:23:36.222677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:29.959736Z digest=sha256:6cf29ff39182fe2bbe70446993291f027846f40a6255a234542e4f5993a4d467

Observation 49e136ee-6363-455c-9626-c87411ae77fa · outbound

This paper cites (1987), The primary, secondary, tertiary and quaternary sectors of the economy, Review of Income and Wealth, 33, 359--385.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (1987), The primary, secondary, tertiary and quaternary sectors of the economy, Review of Income and Wealth, 33, 359--385

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.119733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:30.148997Z digest=sha256:bfe4b716c8dc9b55e310086b5e1f896fec379881cc989a74d4c4f5923cb04054

Observation d3ebb289-c3ae-4ee3-8198-ff471d847508 · outbound

This paper cites and Yao, Q.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Yao, Q

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:36.013107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:30.276085Z digest=sha256:f85c589d3e1ac86d3e0d7db0536910874961334c4deedaf856f3dbe096e6d0a0

Observation d9fd6f23-4929-46c5-b9de-94736b528098 · outbound

This paper cites (2004), Asymptotic distributions of quasi-maximum likelihood estimators for spatial autoregressive models, Econometrica, 72, 1899--1925.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2004), Asymptotic distributions of quasi-maximum likelihood estimators for spatial autoregressive models, Econometrica, 72, 1899--1925

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:35.900863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:30.435995Z digest=sha256:cab6969efce654c8a02a51683760d8e0c0d86970e01bbce4335ed976deb5bbcb

Observation b4afdb27-360b-4a58-af2c-9d946ed22ca7 · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:23:35.709206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:30.587374Z digest=sha256:e9a7cd6bc04c8316e204a9661d68ba1e367ed2a58c42a7cad55e45fa71331eb5

Observation 40c28be9-3206-406d-9d04-ee3c53b19dbe · outbound

This paper cites (2010), Specification and estimation of social interaction models with network structures, The Econometrics Journal, 13, 145--176.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2010), Specification and estimation of social interaction models with network structures, The Econometrics Journal, 13, 145--176

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:35.525102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:30.749796Z digest=sha256:7422b5e056b7c1b145035e48aca5f1916d64ce4510c33484a6a0647d58d95e42

Observation 3abf00c9-7db8-4221-9c5d-56386c6e6e81 · outbound

This paper cites and Yu, J.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Yu, J

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:35.392988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:30.951271Z digest=sha256:d041caaf6a9f2c7381136bab4d78f4f5d34556e5514f8b4655aefe5f04cda32b

Observation 7c3d716b-b484-4f15-9df6-951391a6a0ff · outbound

This paper cites (2018), Interpolation theory, vol.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2018), Interpolation theory, vol

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:35.342617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:31.086884Z digest=sha256:55260cfcb9ec44547256020f927057b7a15a1a9fb88ccf094eb2050b528f2cb2

Observation ec215d97-ee00-433f-b98c-7e700d7da1d6 · outbound

This paper cites (2009), Contour projected dimension reduction, The Annals of Statistics, 3743--3778.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2009), Contour projected dimension reduction, The Annals of Statistics, 3743--3778

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:35.223684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:31.237990Z digest=sha256:0b3d8b8a8ed3e53668e93f37d2b584744a00a851a86b16014a5387a846cc4ff6

Observation f03388b7-1982-49b3-914a-323c81d67003 · outbound

This paper cites and Snijders, T.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Snijders, T

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:35.064011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:31.337213Z digest=sha256:5414da5a5cd36c8c9ffa897da4db05f0245672ed0aa8777327eafdb55c756aaa

Observation 2da2c561-9b39-415b-b300-01c5c2acc52e · outbound

This paper cites (1993), Linear model selection by cross-validation, Journal of the American statistical Association, 88, 486--494.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (1993), Linear model selection by cross-validation, Journal of the American statistical Association, 88, 486--494

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:34.912296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:31.485162Z digest=sha256:67885024ab9ed9524e3ae74cf29ff96d32976ee64ad25952bee9b92489e080c0

Observation 12cb0d17-3e2a-4fdc-ba20-de561258af5f · outbound

This paper cites (2012), Semiparametric GMM estimation of spatial autoregressive models, Journal of Econometrics, 167, 543--560.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2012), Semiparametric GMM estimation of spatial autoregressive models, Journal of Econometrics, 167, 543--560

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:34.780402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:31.692351Z digest=sha256:29d2b4cb8cb0544392b07298d50dd3c5e11e62ca150f7fa16f0da16444962a99

Observation 49f794be-f263-4e32-bfb7-e36ffe6b37b3 · outbound

This paper cites (1996), Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society Series B: Statistical Methodology, 58, 267--288.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (1996), Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society Series B: Statistical Methodology, 58, 267--288

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:34.635799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:31.952216Z digest=sha256:3dd91234e05d23002faba90c1696dd482921bb49d9a6d060dadec04ba6b16128

Observation 47fdfb63-8dba-4e5a-ae24-a23def447792 · outbound

This paper cites an unresolved cited work.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:23:34.510835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.038513Z digest=sha256:5e34499fcbe28ce794c2288e49330f53ed2fd4ee2352422d03c53a373ddc15f5

Observation 364c03cc-a317-4c4a-a61e-c2f55ec1dfb5 · outbound

This paper cites (2012), Factor profiled sure independence screening, Biometrika, 99, 15--28.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2012), Factor profiled sure independence screening, Biometrika, 99, 15--28

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:34.389295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.116721Z digest=sha256:d071829b0b9172aaf742655550e47cb73ae080117ae690f5fdb15b305a35b354

Observation edb501dc-d331-4558-8181-e265839938d4 · outbound

This paper cites (2009), Shrinkage tuning parameter selection with a diverging number of parameters, Journal of the Royal Statistical Society Series B: Statistical Methodology, 71, 671--683.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2009), Shrinkage tuning parameter selection with a diverging number of parameters, Journal of the Royal Statistical Society Series B: Statistical Methodology, 71, 671--683

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:34.264591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.199767Z digest=sha256:980628347412de78062dad09c073988e1903804982d74c866155495cd66b89f5

Observation c95f7186-ba82-40f1-af87-4b5a883acb92 · outbound

This paper cites (2007), Tuning parameter selectors for the smoothly clipped absolute deviation method, Biometrika, 94, 553--568.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2007), Tuning parameter selectors for the smoothly clipped absolute deviation method, Biometrika, 94, 553--568

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:34.109270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.258914Z digest=sha256:842c2efc7e6f09fb0d31bb816bb09fce9277fc646575f30361a3e3a76b8b0930

Observation c2897d25-08c5-40cf-af32-0bac732900e2 · outbound

This paper cites and Lee, L.-f.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections and Lee, L.-f

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.954761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.366923Z digest=sha256:b4ce16744242b184ef26f880af0a34c7262394b2dfd0ef640acfd451d01647c0

Observation 61038fe2-ca5c-4969-b80a-cf03d6af0871 · outbound

This paper cites (2022), Spatial heterogeneity of the economic growth pattern and influencing factors in formerly destitute areas of China, Journal of Geographical Sciences, 32, 829--852.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2022), Spatial heterogeneity of the economic growth pattern and influencing factors in formerly destitute areas of China, Journal of Geographical Sciences, 32, 829--852

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.813425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.469356Z digest=sha256:043c7e64904b18de3710b676fe162d31c29db2b7dd598af246301bafcafa1898

Observation 8aafbf24-6907-4b9a-a4cf-63ee7419a6dd · outbound

This paper cites (2016), Strategic interaction in political competition: Evidence from spatial effects across Chinese cities, Regional Science and Urban Economics, 57, 23--37.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2016), Strategic interaction in political competition: Evidence from spatial effects across Chinese cities, Regional Science and Urban Economics, 57, 23--37

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.669183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.532587Z digest=sha256:66224f22dfd1798752574bd91770ded73c771572deaae90da18604a22d4cd252

Observation 8c19b9f4-017f-42dc-8c1c-8ea7e1f90a37 · outbound

This paper cites (2022), Joint latent space models for network data with high-dimensional node variables, Biometrika, 109, 707--720.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2022), Joint latent space models for network data with high-dimensional node variables, Biometrika, 109, 707--720

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.530981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.604519Z digest=sha256:4ca9fa53968cf81b79288d960ff2869b8ceda9f3d21bd20190c65dfc9e2e5162

Observation 7b619258-1522-46e7-92a3-bccd0bc2a4f8 · outbound

This paper cites (2024), Variable selection and subgroup analysis for high-dimensional censored data, Statistical Theory and Related Fields, 8, 211--231.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2024), Variable selection and subgroup analysis for high-dimensional censored data, Statistical Theory and Related Fields, 8, 211--231

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.377497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.694847Z digest=sha256:ec8c61baa09af5e3c2184c412b13a6ef738a75e6bde684f1d65f16d48fd026dc

Observation ce1a9480-ade8-41aa-9fef-ed62a77390bb · outbound

This paper cites (2023), Spatial and temporal evolution characteristics and spillover effects of China's regional carbon emissions, Journal of Environmental Management, 325, 116423.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2023), Spatial and temporal evolution characteristics and spillover effects of China's regional carbon emissions, Journal of Environmental Management, 325, 116423

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.208136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.761913Z digest=sha256:9865ae1b22a155356d3c509fdc0eeb9161115d29f59b8ad92a1a96e5313b035f

Observation 18597778-4912-47c1-85a5-1042b0345602 · outbound

This paper cites (2020), Multivariate spatial autoregressive model for large scale social networks, Journal of Econometrics, 215, 591--606.

High-Dimensional Spatial Autoregression with Latent Factors by Diversified Projections (2020), Multivariate spatial autoregressive model for large scale social networks, Journal of Econometrics, 215, 591--606

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:23:33.029424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T13:23:32.839912Z digest=sha256:6344bf1d9cd01fbbeb179351850a942212c0b8c2593516079b6442c69d807797

Pith citing papers

No inbound Pith citation observations are available.