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xtbhst 1.1.0

This release corrects the computation of the test statistic and several related defects; the version on CRAN is 1.0.2.

• Unit-specific error variance. The previous versions divided the pooled fixed-effects residual sum of squares of each unit by T minus the number of partialled-out variables, which is neither the estimator of Blomquist and Westerlund (2016) nor that of Pesaran and Yamagata (2008). A new argument variance = c("bw", "py") selects the estimator: "bw" (default) is T^-1 times the residual sum of squares of the unit-specific least-squares regression (Blomquist and Westerlund, 2016, Section 3.1); "py" is the pooled fixed-effects residual sum of squares divided by T - K - 1 (Pesaran and Yamagata, 2008). The chosen estimator is used in the weights of the weighted fixed-effects estimator, in S and in every bootstrap statistic.
• Adjusted Delta. The variance in the denominator was 2K(T - K - Kpartial - 1)/(T - Kpartial + 1), where Kpartial counted the constant; it is now 2K(T - K - 1)/(T + 1) as in Pesaran and Yamagata (2008). The silent fallback to 2K when this was non-positive has been removed; delta_adj is NA with a warning when T - K - 1 <= 0.
• p-values. The bootstrap p-value pval is now based on the statistic S that the paper bootstraps (proportion of S* at least as large as S). Delta and adjusted Delta are fixed rescalings of S, so their bootstrap p-values coincided with each other; the duplicated pval_adj and delta_adj_stars elements have been removed and pval_delta_asy and pval_delta_adj_asy (asymptotic standard normal p-values) are reported instead. Delta and adjusted Delta are always computed with the Pesaran and Yamagata (2008) variance estimator (from the new element S_py), whatever the value of variance, so that they are the statistics of that paper; variance governs only S and the bootstrap. The conclusion in summary() uses the bootstrap p-value only. New elements S, S_py, S_stars, sigma2, variance and n_dropped.
• Lagged cross-sectional averages (csa_lags > 0). Rows with missing lagged averages were previously set to zero (including the constant) without reducing T, which distorted the unit estimates. The first csa_lags periods are now dropped for all units, T is reduced accordingly, and when the dependent variable enters csa its cross-sectional averages are recomputed from the pseudo-data in each bootstrap replication. The documentation states that CSA augmentation is an extension not covered by the paper.
• Block length. The default is now round(2 * T^(1/3)), which gives the block lengths 6, 7 and 9 for T = 25, 50 and 100 stated in Section 4.2 of the paper (previously floor(), giving 5, 7 and 9). A blocklength larger than T is now an error.
• Missing values. Rows with missing values in any variable used are dropped before the balance check, and the check now also detects duplicated (id, time) pairs; previously missing values in the model variables caused a “subscript out of bounds” error.
• Singular unit regressions now stop with an error naming the unit instead of silently applying a ridge correction.
• Citation corrected everywhere to Blomquist and Westerlund (2016), Empirical Economics, 50(4), 1359-1381; the reference to Pesaran and Yamagata (2008) has been added.
• plot(): plot 1 now shows the bootstrap distribution of S and plot 2 that of Delta.
• Removed the unused suggested dependency on ‘plm’.

xtbhst 1.0.2

• Removed Jan Ditzen from the contributors list at his explicit request.
• The acknowledgment of the original Stata xthst command now appears as a narrative reference in README.md only.

xtbhst 1.0.1

• Documentation and metadata updates.

xtbhst 1.0.0

• Initial CRAN release
• Implements bootstrap slope heterogeneity test of Blomquist and Westerlund (2016) [citation corrected in 1.1.0]
• Features:
  • Block bootstrap for panel data
  • Standard and adjusted Delta statistics
  • Support for partialling out control variables
  • Cross-sectional averages for handling cross-sectional dependence
  • Diagnostic plots for bootstrap distributions

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.