Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:11:19.001231Z
Paper Citation Record · LEDGER
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation
As of 9 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2508.20335.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
16 of 16 outbound references displayed
- verified exact5
- verified fuzzy5
- unresolved4
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a10f568a-a624-4855-bebe-e7e29a5d8a06 · outbound
This paper cites Synthetic control meth- ods for comparative case studies: Estimating the effect of california’s tobacco control program.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Synthetic control meth- ods for comparative case studies: Estimating the effect of california’s tobacco control program
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:11:20.876123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 520e702f-7a95-4986-a8f5-4376b22bab29 · outbound
This paper cites Understanding guest preferences and optimizing marketplace outcomes: A causal inference approach.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Understanding guest preferences and optimizing marketplace outcomes: A causal inference approach
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:11:20.751573Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e34d627f-aca6-4bfb-9638-3a6dd97cf5f3 · outbound
This paper cites Hirshberg, Guido W.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Hirshberg, Guido W
Reference 3
- Resolution
- verified exact
- doi, observed 2026-08-05T15:11:19.592131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 81499af3-2a8a-46ec-88ed-b0b0a5fd0907 · outbound
This paper cites The augmented synthetic control method.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation The augmented synthetic control method
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:11:18.660434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1ca559f0-d9bf-4fb6-b34b-202f3556a617 · outbound
This paper cites augsynth: The Augmented Syn- thetic Control Method, 2021.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation augsynth: The Augmented Syn- thetic Control Method, 2021
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:11:20.534206Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 955fc710-3940-4322-874f-7bac595aec2c · outbound
This paper cites Practical Marketplace Optimization at Uber Using Causally-Informed Machine Learning.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Practical Marketplace Optimization at Uber Using Causally-Informed Machine Learning
Reference 6
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T15:11:19.802410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a7eebebb-6a0b-4dda-8d70-a8c0bf6566e6 · outbound
This paper cites Double/debiased machine learning for treatment and structural parameters.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Double/debiased machine learning for treatment and structural parameters
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:11:20.453397Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2454a8fd-ef3d-4185-827d-156b07828793 · outbound
This paper cites Double Machine Learning for Static Panel Models with Fixed Effects.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Double Machine Learning for Static Panel Models with Fixed Effects
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T15:11:19.374745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c7f3d1a8-693b-406a-a6a6-6b6863e898f5 · outbound
This paper cites Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions.
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.
Observation 476b6d1a-e9c8-4add-9243-04df16bec69e · outbound
This paper cites Valid and Unobtrusive Measurement of Returns to Advertising through Asymmetric Budget Split.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Valid and Unobtrusive Measurement of Returns to Advertising through Asymmetric Budget Split
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T15:11:19.715896Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c91228e2-c515-44f2-b215-18f744c51205 · outbound
This paper cites an unresolved cited work.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Unresolved cited work
Reference 12
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-05T15:11:18.911658Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2499f067-1b73-455e-a362-8cab44b22ff6 · outbound
This paper cites Estimating dynamic treatment effects in event studies with heterogeneous treatment effects.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Estimating dynamic treatment effects in event studies with heterogeneous treatment effects
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:11:18.964760Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b86bea3c-9234-4ba3-9a9e-cd4697a809f6 · outbound
This paper cites Geolift: Measuring incremental impact of adver- tising.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Geolift: Measuring incremental impact of adver- tising
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:11:20.362509Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ea195be1-48c9-46be-917f-bbbd3526f8bc · outbound
This paper cites an unresolved cited work.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Unresolved cited work
Reference 2010
- Resolution
- verified exact
- raw_fallback, observed 2026-08-05T15:11:20.260799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6ebdc0c9-c15b-43df-a479-25d8cd692cc9 · outbound
This paper cites an unresolved cited work.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Unresolved cited work
Reference 2018
- Resolution
- verified exact
- doi, observed 2026-08-05T15:11:19.494750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 08449ef3-f058-4c25-af4d-1731c06e31c6 · outbound
This paper cites an unresolved cited work.
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation Unresolved cited work
Reference 2024
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:11:20.617541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.