make_pliv_multiway_cluster_CKMS2021: Generates data from a partially linear IV regression model...

View source: R/datasets.R

make_pliv_multiway_cluster_CKMS2021R Documentation

Generates data from a partially linear IV regression model with multiway cluster sample used in Chiang et al. (2021).

Description

Generates data from a partially linear IV regression model with multiway cluster sample used in Chiang et al. (2021). The data generating process is defined as

Z_{ij} = X_{ij}' \xi_0 + V_{ij},

D_{ij} = Z_{ij}' \pi_{10} + X_{ij}' \pi_{20} + v_{ij},

Y_{ij} = D_{ij} \theta + X_{ij}' \zeta_0 + \varepsilon_{ij},

with

X_{ij} = (1 - \omega_1^X - \omega_2^X) \alpha_{ij}^X + \omega_1^X \alpha_{i}^X + \omega_2^X \alpha_{j}^X,

\varepsilon_{ij} = (1 - \omega_1^\varepsilon - \omega_2^\varepsilon) \alpha_{ij}^\varepsilon + \omega_1^\varepsilon \alpha_{i}^\varepsilon + \omega_2^\varepsilon \alpha_{j}^\varepsilon,

v_{ij} = (1 - \omega_1^v - \omega_2^v) \alpha_{ij}^v + \omega_1^v \alpha_{i}^v + \omega_2^v \alpha_{j}^v,

V_{ij} = (1 - \omega_1^V - \omega_2^V) \alpha_{ij}^V + \omega_1^V \alpha_{i}^V + \omega_2^V \alpha_{j}^V,

and \alpha_{ij}^X, \alpha_{i}^X, \alpha_{j}^X \sim \mathcal{N}(0, \Sigma) where \Sigma is a p_x \times p_x matrix with entries \Sigma_{kj} = s_X^{|j-k|}.

Further

\left(\begin{array}{c} \alpha_{ij}^\varepsilon \\ \alpha_{ij}^v \end{array}\right), \left(\begin{array}{c} \alpha_{i}^\varepsilon \\ \alpha_{i}^v \end{array}\right), \left(\begin{array}{c} \alpha_{j}^\varepsilon \\ \alpha_{j}^v \end{array}\right) \sim \mathcal{N}\left(0, \left(\begin{array}{cc} 1 & s_{\varepsilon v} \\ s_{\varepsilon v} & 1 \end{array}\right) \right)

and \alpha_{ij}^V, \alpha_{i}^V, \alpha_{j}^V \sim \mathcal{N}(0, 1).

Usage

make_pliv_multiway_cluster_CKMS2021(
  N = 25,
  M = 25,
  dim_X = 100,
  theta = 1,
  return_type = "DoubleMLClusterData",
  ...
)

Arguments

N

(integer(1))
The number of observations (first dimension).

M

(integer(1))
The number of observations (second dimension).

dim_X

(integer(1))
The number of covariates.

theta

(numeric(1))
The value of the causal parameter.

return_type

(character(1))
If "DoubleMLClusterData", returns a DoubleMLClusterData object. If "data.frame" returns a data.frame(). If "data.table" returns a data.table(). If "matrix" a named list() with entries X, y, d, z and cluster_vars is returned. Every entry in the list is a matrix() object. Default is "DoubleMLClusterData".

...

Additional keyword arguments to set non-default values for the parameters \pi_{10}=1.0, \omega_X = \omega_{\varepsilon} = \omega_V = \omega_v = (0.25, 0.25), s_X = s_{\varepsilon v} = 0.25, or the p_x-vectors \zeta_0 = \pi_{20} = \xi_0 with default entries \zeta_{0})_j = 0.5^j.

Value

A data object according to the choice of return_type.

References

Chiang, H. D., Kato K., Ma, Y. and Sasaki, Y. (2021), Multiway Cluster Robust Double/Debiased Machine Learning, Journal of Business & Economic Statistics, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/07350015.2021.1895815")}, https://arxiv.org/abs/1909.03489.


DoubleML documentation built on June 22, 2024, 10:50 a.m.