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Randomization Inference for Dynamic Causal Effects in Short Panels with Autoregressive Instruments

Pedro Picchetti

arXiv 13 Oct 2026 · Econometrics

arXiv:2610.19075 · PDF · Extracted main text

Abstract

I study randomization inference for dynamic causal effects in panels with many units and few periods when treatment is endogenous and an instrument is as good as randomly assigned only through the innovations of a first-order autoregressive assignment mechanism with unknown persistence. The persistence is a nuisance parameter in two senses: it determines which weighted average of heterogeneous causal effects the instrumented local projection estimand measures, and it governs the randomization distribution of any statistic built from the instrument. I propose tests that never estimate it. For each candidate value the innovations are recovered, rerandomized under a group that leaves their joint law invariant, and a randomization p-value is formed; the reported p-value is the supremum over candidate values or over an exact confidence set. Under a sharp null on the path of lag-specific effects the tests have level at most $α$ for every persistence in finite samples, including the unit root, and the supremum is a maximum over finitely many points. Under a weak null on the heterogeneity-weighted estimand a studentized version is uniformly asymptotically valid.

Citation extraction

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appendix boundary found by appendix_titled_section at “Appendix” · 63% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
agr2023unmatched citation key agr20230.64441100%
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6Stock \ Watson (2018) `Identification and estimation of dynamic causal effects in macroeconomics using external instruments', The Economic Journal 128…0.64422100%
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9Dufour (2006) `Monte carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics', Journal…0.51121100%
10Wu \ Ding (2021) `Randomization tests for weak null hypotheses in randomized experiments', Journal of the American Statistical Association 116(53…0.51121100%

Showing the top 10 of 36 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.