Rotemberg-weight summary and correlations (GPSS diagnostic table)

Summarises the Rotemberg-weight diagnostic in the spirit of Goldsmith-Pinkham, Sorkin & Swift (2020): the top-weight shocks, the largest single weight, the correlation of the weights with the just-identified estimates and first-stage F, and — if `covariates` are supplied — the correlation between each shock's Rotemberg weight and its exposure-weighted average of unit observables (do high-weight shocks load on systematically different places?).

Usage

ssb_weight_summary(design, covariates = NULL, top = 5)

Arguments

design: An [ssb_design()] object.
covariates: Optional unit-level observable columns in `data`.
top: Number of top-weight shocks to display.

Value

A list (class `ssb_weight_summary`).