get_first_efficient_release: Identify the First Efficient Release in Vintage Data

In reviser: Analyzing Revisions in Real-Time Time Series Vintages

Identify the First Efficient Release in Vintage Data

Description

Identifies the first release in a sequence of vintages that is "efficient" relative to the final release. A release is deemed efficient if it satisfies specific conditions of unbiasedness and efficiency, tested using a Mincer-Zarnowitz type linear regression and hypothesis testing.

Usage

get_first_efficient_release(
  df,
  final_release,
  significance = 0.05,
  test_all = FALSE,
  robust = TRUE
)

Arguments

df	A data frame of class tbl_release containing the vintage data. It must include the columns: time: The reference period (e.g., quarter or month). value: The observed value for the given release. release: The release number or identifier.
final_release	A data frame containing the final release data. This must include the columns: time: The reference period. value: The observed final value for the given period.
significance	A numeric value specifying the significance level for the hypothesis test (default is 0.05).
test_all	A logical value indicating whether to test all releases, even after finding the first efficient release (default is FALSE).
robust	A logical value indicating whether to use robust HAC standard errors (default is TRUE).

Details

The function performs the following steps:

1. Validates inputs and ensures both df and final_release are in the correct format.

2. Iteratively tests each release for efficiency using a linear regression model of the form:

   final = \beta_0 + \beta_1 \cdot release_i + \epsilon

   The null hypothesis for efficiency is:

   • \beta_0 = 0 (no bias)

   • \beta_1 = 1 (efficiency) Uses heteroskedasticity and autocorrelation consistent (HAC) standard errors for robust hypothesis testing.

3. Stops testing when the first efficient release is found (unless test_all = TRUE).

If no efficient release is found, a warning is issued.

Value

A list of class lst_efficient with the following elements:

• e: The index of the first efficient release. (0 indexed)

• data: A long-format data frame containing the vintage data with the final release appended.

• models: A list of linear regression models fitted for each release.

• tests: A list of hypothesis test results for each release.

References

Aruoba, S. Boragan, "Revisions Are Not Well Behaved", Journal of Money, Credit and Banking, 40(2-3), 319-340, 2008.

See Also

Other revision analysis: diagnose(), diagnose.revision_summary(), get_revision_analysis(), print.lst_efficient(), print.revision_summary(), summary.lst_efficient(), summary.revision_summary()

Examples

# Example data
df <- get_nth_release(
  tsbox::ts_pc(dplyr::filter(reviser::gdp, id == "US")),
  n = 0:3
)

final_release <- get_nth_release(
  tsbox::ts_pc(dplyr::filter(reviser::gdp, id == "US")),
  n = 10
)

# Identify the first efficient release
result <- get_first_efficient_release(
  df,
  final_release,
  significance = 0.05,
  robust = FALSE
)

result <- get_first_efficient_release(df, final_release, significance = 0.05)

# Access the index of the first efficient release
result$e

reviser documentation built on Sept. 14, 2026, 9:09 a.m.