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Estimate a shift-share IV regression with several confidence intervals

Source: R/estimate.R
ssb_estimate.Rd

Computes the shift-share 2SLS point estimate of `x` on `y` (instrumented by the constructed Bartik instrument, controls partialled out via FWL) and reports a panel of intervals side by side so the practical importance of the inference method is visible:

  • `iid` — classical (homoskedastic) IV,

  • `ehw` — Eicker-Huber-White (heteroskedasticity-robust),

  • `akm`, `akm0` — Adao-Kolesar-Morales exposure-robust inference, via ShiftShareSE when installed,

  • `cluster` — naive cluster-robust (needs `cluster` in the design),

  • `twoway` — two-way cluster-robust (needs `cluster` in the design and `cluster2` here).

The point estimate is identical across rows; only the standard errors and intervals differ, which is exactly what makes the comparison instructive.

Usage

ssb_estimate(
  design,
  methods = c("iid", "ehw", "akm", "akm0"),
  level = 0.95,
  cluster2 = NULL,
  shock_cluster = NULL
)

Arguments

design

An [ssb_design()] object.

methods

Which methods to report. Defaults to the exposure-robust panel (`iid`, `ehw`, `akm`, `akm0`); add `"cluster"` and/or `"twoway"` for cluster-robust intervals.

level

Confidence level for the reported intervals.

cluster2

Optional second clustering column in `data` for the `"twoway"` method (paired with the design's `cluster`).

shock_cluster

Optional grouping of the shocks for the AKM / AKM0 variance: a column name in the shocks table, or a vector of length equal to the number of shock-cells. Use it when shocks are mutually correlated within groups — e.g. sub-industries within broader industries, or sector cells of the same sector across periods — so the exposure-robust variance is clustered at the group level (Adao, Kolesar & Morales 2019; passed to ShiftShareSE as `sector_cvar`).

Value

A `data.frame` of class `ssb_estimate` with one row per method (`estimate`, `std.error`, `conf.low`, `conf.high`), carrying the first-stage F as an attribute. Plot with [ssb_plot_ci()].

Details

The primary object of the comparison is the **confidence interval**, not the standard error: AKM0 in particular is defined directly as a (possibly asymmetric, possibly unbounded) interval, and the `std.error` reported for it is a symmetric pseudo-SE implied by that interval rather than a conventional standard error. Read the table and [ssb_plot_ci()] figure as a comparison of intervals. When the instrument is weak the AKM0 confidence *set* need not be an interval at all: it can be the whole real line or the complement of an interval (a union of two rays). ShiftShareSE encodes the latter as `conf.low > conf.high`; `ssb_estimate()` flags both cases in the `note` column and the table/plot methods render them accordingly.

`cluster` and `twoway` are **not** in the default panel — they are usually a secondary concern next to the exposure-robust AKM / AKM0 intervals. Request them explicitly via `methods` when wanted (e.g. `methods = c("iid", "ehw", "akm", "akm0", "cluster")`, adding `"twoway"` and `cluster2` for two-way clustering).