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Generate panel data with staggered treatment adoption (three periods)

gen_dgp_mult_periods.Rd

Generate panel data where units adopt treatment at different times across three periods.

Usage

gen_dgp_mult_periods(size, dgp_type = 1, include_covariates = TRUE)

Arguments

size

Integer. Number of units to simulate.

dgp_type

Integer in {1,2,3,4}. Only used when include_covariates = TRUE. 1 = both nuisance functions correct (default); 2 = only the outcome model correct; 3 = only the propensity-score model correct; 4 = both nuisance functions misspecified.

include_covariates

Logical. If TRUE (default), generates covariates with transformations and uses dgp_type specification. If FALSE, uses constant covariates and fixed propensity score probabilities for a simpler DGP.

Value

A named list with components:

data

A data.table in long format with columns:

  • id: unit identifier

  • cohort: first period when treatment is assigned

  • partition: partition indicator

  • x1, x2, x3, x4: covariates

  • cluster: cluster identifier (no within-cluster correlation)

  • time: time period index

  • y: observed outcome

data_wide

A data.table in wide format (one row per id) with columns:

  • id, cohort, partition, x1, x2, x3, x4, cluster

  • y_t0, y_t1, y_t2: outcomes in periods 0, 1, and 2

ES_0_unf

(Only if include_covariates = TRUE) Unfeasible (oracle) event-study parameter at time 0.

prob_g2_p1

(Only if include_covariates = TRUE) Proportion of units with cohort == 2 and eligibility in period 1.

prob_g3_p1

(Only if include_covariates = TRUE) Proportion of units with cohort == 3 and eligibility in period 1.