panel.matrices: Convert a long (balanced) panel to a wide matrix

In synth-inference/synthdid: Synthetic Difference-in-Difference Estimation

Convert a long (balanced) panel to a wide matrix

Description

Converts a data set in panel form to matrix format required by synthdid estimators. A typical long panel date set looks like [unit, time, outcome, treatment]. Synthdid requires a balanced panel with simultaneous adoption of treatment: each unit must be observed at all times, and all treated units must begin treatment simultaneosly. This function creates num.units x num.time.periods matrices Y and W of outcomes and treatment indicators. In these matrices, columns are sorted by time, and by default (when treated.last=TRUE), rows for control units appear before those of treated units.

Usage

panel.matrices(
  panel,
  unit = 1,
  time = 2,
  outcome = 3,
  treatment = 4,
  treated.last = TRUE
)

Arguments

panel	A data.frame with columns consisting of units, time, outcome, and treatment indicator.
unit	The column number/name corresponding to the unit identifier. Default is 1.
time	The column number/name corresponding to the time identifier. Default is 2.
outcome	The column number/name corresponding to the outcome identifier. Default is 3.
treatment	The column number/name corresponding to the treatment status. Default is 4.
treated.last	Should we sort the rows of Y and W so treated units are last. If FALSE, sort by unit number/name. Default is TRUE.

Value

A list with entries Y: the data matrix, N0: the number of control units, T0: the number of time periods before treatment, W: the matrix of treatment indicators.

Examples

# Load tobacco sales in long panel format.
data("california_prop99")
# Transform to N*T matrix format required for synthdid,
# where N is the number of units and T the time periods.
setup <- panel.matrices(california_prop99, unit = 1, time = 2, outcome = 3, treatment = 4)

# Compute synthdid estimate
synthdid_estimate(setup$Y, setup$N0, setup$T0)

synth-inference/synthdid documentation built on Jan. 26, 2024, 7:21 a.m.