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Paper Citation Record · LEDGER

Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.01266.

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

pith.paper-citation-record.v1
2409.01266 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:58:19.926352Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cc22f676-1b93-40d1-907d-f3b90d1ca7a2 · inbound

On the (Mis)Use of Machine Learning with Panel Data cites this paper.

On the (Mis)Use of Machine Learning with Panel Data Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions

Reference 845

Resolution
unresolved
no resolver link, observed 2026-08-12T20:58:19.926352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:58:19.926352Z digest=sha256:a288192887c46dc724a4599dc7f465006a85648441f927dcadbba542ca070d93

Observation 35c038cf-9419-432f-93d5-ce107a8679da · inbound

The causal effects of modified treatment policies under network interference cites this paper.

The causal effects of modified treatment policies under network interference Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T00:04:50.679053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T00:04:50.679053Z digest=sha256:ebfc1696e03d233613697f8558001ec328e9be4c6de5f6edb738db19cdb14c1d

Observation c7f3d1a8-693b-406a-a6a6-6b6863e898f5 · inbound

Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation cites this paper.

Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T15:11:18.824748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:11:18.824748Z digest=sha256:dc4d5863a65a6b598e38401732bfba6f8a1e3bd44f109094c61a5f5094ce0666

Observation 393af0e5-e614-4c7a-8125-e77fc75ff3dd · inbound

Analytical and Bootstrap Confidence Intervals of Double Machine Learning: Simulation studies and an application to rural-urban difference in obesity prevalence cites this paper.

Analytical and Bootstrap Confidence Intervals of Double Machine Learning: Simulation studies and an application to rural-urban difference in obesity prevalence Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-03T06:49:09.329367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-03T06:45:07.325234Z digest=sha256:5831c8cd9039529c0cddb2034ecd234773182ad16bcecc5197cfb75f91186110