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CS-DL/Evidence
Method evidence record

CS-DL

CS-DL (Cross-Sectional Distributed Lag) is a simplified dynamic panel model regressing outcomes on current and lagged explanatory variables without explicit autoregressive terms, while accounting for cross-sectional dependence. Built on Pesaran et al. (2001) and extended by Chudik et al. (2014), it estimates dynamic effects more parsimoniously than ARDL when autocorrelated lags are less critical. This approach is valuable for short-horizon effects and policy impact analysis.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Cross-Sectional Distributed Lag Model
Taxonomic method record · regression-model / econometrics
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships and dynamics. Journal of Applied Econometrics, 16(3), 289-326. · DOI 10.1002/jae.616
  • Chudik, A., Kapetanios, G., & Pesaran, M. H. (2014). Common correlated effects estimation in large panels with cross-sectional dependence. Econometric Reviews, 34(6-10), 1078-1088. · URL
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Curated claims

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyCS-ARDLmachine-suggested · Relational suggestion, not evidence.Same method familyCS-NARDLmachine-suggested · Relational suggestion, not evidence.Same method familyLocal Projectionsmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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